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247 results on '"Department of Computer Science [Purdue]"'

1. Authoring consistent landscapes with flora and fauna

Author: Pierre Ecormier-Nocca, Pooran Memari, Philippe Carrez, Marie-Paule Cani, Anne-Marie Moigne, Guillaume Cordonnier, Bedrich Benes, Laboratoire d'informatique de l'École polytechnique [Palaiseau] (LIX), École polytechnique (X)-Centre National de la Recherche Scientifique (CNRS), Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), GRAPHics and DEsign with hEterogeneous COntent (GRAPHDECO), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Université Côte d'Azur (UCA), Immersion Tools, Histoire naturelle de l'Homme préhistorique (HNHP), Muséum national d'Histoire naturelle (MNHN)-Université de Perpignan Via Domitia (UPVD)-Centre National de la Recherche Scientifique (CNRS), Department of Computer Science [Purdue], Purdue University [West Lafayette], We would like to thank all the participants of the ANR SCHOPPER project for their contributions, and Gowtham Harihara for the 3D animal models. This research was funded in part by National Science Foundation grant #10001387, Functional Proceduralization of 3D Geometric Models., and ANR-16-CE38-0007,SCHOPPER,Simulation des comportements des Hommes préhistoriques dasn leurs Paléo-Environnements pour la Recherche(2016)
Subjects: Resource (biology), business.industry, Environmental resource management, Wildlife, 020207 software engineering, Terrain, 02 engineering and technology, Vegetation, 15. Life on land, Data structure, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, Computer Graphics and Computer-Aided Design, Ecosystems, Natural Phenomena, Food chain, Geography, 0202 electrical engineering, electronic engineering, information engineering, Graph (abstract data type), 020201 artificial intelligence & image processing, Ecosystem, business, ComputingMethodologies_COMPUTERGRAPHICS
Abstract: International audience; We present a novel method for authoring landscapes with flora and fauna while considering their mutual interactions. Our algorithm outputs a steadystate ecosystem in the form of density maps for each species, their daily circuits, and a modified terrain with eroded trails from a terrain, climatic conditions, and species with related biological information. We introduce the Resource Access Graph, a new data structure that encodes both interactions between food chain levels and animals traveling between resources over the terrain. A novel competition algorithm operating on this data progressively computes a steady-state solution up the food chain, from plants to carnivores. The user can explore the resulting landscape, where plants and animals are instantiated on the fly, and interactively edit it by over-painting the maps. Our results show that our system enables the authoring of consistent landscapes where the impact of wildlife is visible through animated animals, clearings in the vegetation, and eroded trails. We provide quantitative validation with existing ecosystems and a user-study with expert paleontologist end-users, showing that our system enables them to author and compare different ecosystems illustrating climate changes over the same terrain while enabling relevant visual immersion into consistent landscapes.
Published: 2021
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2. Surface-based protein domains retrieval methods from a SHREC2021 challenge

Author: Florent Langenfeld, Tunde Aderinwale, Charles Christoffer, Woong-Hee Shin, Genki Terashi, Xiao Wang, Daisuke Kihara, Halim Benhabiles, Karim Hammoudi, Adnane Cabani, Feryal Windal, Mahmoud Melkemi, Ekpo Otu, Reyer Zwiggelaar, David Hunter, Yonghuai Liu, Léa Sirugue, Huu-Nghia H. Nguyen, Tuan-Duy H. Nguyen, Vinh-Thuyen Nguyen-Truong, Danh Le, Hai-Dang Nguyen, Minh-Triet Tran, Matthieu Montès, Laboratoire Génomique, bioinformatique et chimie moléculaire (GBCM), Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM), Department of Computer Science [Purdue], Purdue University [West Lafayette], Suncheon National University [Suncheon, Corée du Sud], Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 (IEMN), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Université Polytechnique Hauts-de-France (UPHF)-JUNIA (JUNIA), Université catholique de Lille (UCL)-Université catholique de Lille (UCL), Bio-Micro-Electro-Mechanical Systems - IEMN (BIOMEMS - IEMN), Université catholique de Lille (UCL)-Université catholique de Lille (UCL)-Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Université Polytechnique Hauts-de-France (UPHF)-JUNIA (JUNIA), JUNIA (JUNIA), Université catholique de Lille (UCL), Institut de Recherche en Informatique Mathématiques Automatique Signal - IRIMAS - UR 7499 (IRIMAS), Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA)), Université de Strasbourg (UNISTRA), École Supérieure d’Ingénieurs en Génie Électrique (ESIGELEC), Aberystwyth University, Edge Hill University, Vietnam National University - Ho Chi Minh City (VNU-HCM), and Léa Sirugue, Matthieu Montès and Florent Langenfeld are supported by the European Research Council Executive Agency under the research grant number 640,283. Daisuke Kihara acknowledges supports from the National Institutes of Health (R01GM133840, R01GM123055) and the National Science Foundation (DBI2003635, CMMI1825941, and MCB1925643). Charles Christoffer is supported by NIGMS-funded pre–doctoral fellowship (T32 GM132024). Huu-Nghia H. Nguyen, Tuan-Duy H. Nguyen, Vinh-Thuyen Nguyen-Truong, Danh Le, Hai-Dang Nguyen, and Minh-Triet Tran are supported by National University Ho Chi Minh City (VNU-HCM) (DS2020-42-01).
Subjects: Models, Molecular, Static Electricity, Proteins, Ligands, Computer Graphics and Computer-Aided Design, Article, Proteins surface, [SPI]Engineering Sciences [physics], SHREC2021, Protein Domains, Materials Chemistry, Physical and Theoretical Chemistry, Spectroscopy, 2000 MSC: 92-08
Abstract: publication dans une revue suite à la communication hal-03467479 (SHREC 2021: surface-based protein domains retrieval); International audience; Proteins are essential to nearly all cellular mechanism and the effectors of the cells activities. As such, they often interact through their surface with other proteins or other cellular ligands such as ions or organic molecules. The evolution generates plenty of different proteins, with unique abilities, but also proteins with related functions hence similar 3D surface properties (shape, physico-chemical properties, …). The protein surfaces are therefore of primary importance for their activity. In the present work, we assess the ability of different methods to detect such similarities based on the geometry of the protein surfaces (described as 3D meshes), using either their shape only, or their shape and the electrostatic potential (a biologically relevant property of proteins surface). Five different groups participated in this contest using the shape-only dataset, and one group extended its pre-existing method to handle the electrostatic potential. Our comparative study reveals both the ability of the methods to detect related proteins and their difficulties to distinguish between highly related proteins. Our study allows also to analyze the putative influence of electrostatic information in addition to the one of protein shapes alone. Finally, the discussion permits to expose the results with respect to ones obtained in the previous contests for the extended method. The source codes of each presented method have been made available online.
Published: 2022
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3. Metastable Kitaev Magnets

Author: Maignan, Antoine, Schmidt, Marcus, Prots, Yurii, Lebedev, Oleg, Daou, Ramzy, Chang, Chun-Fu, Kuo, Chang-Yang, Hu, Zhiwei, Chen, Chien-Te, Weng, Shih-Chang, Altendorf, Simone, Tjeng, Liu-Hao, Grin, Yuri, International Iberian Nanotechnology Laboratory (INL), Ludwig-Maximilians-Universität München (LMU), Laboratoire de cristallographie et sciences des matériaux (CRISMAT), Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU)-École Nationale Supérieure d'Ingénieurs de Caen (ENSICAEN), Normandie Université (NU)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche sur les Matériaux Avancés (IRMA), Normandie Université (NU)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Institut national des sciences appliquées Rouen Normandie (INSA Rouen Normandie), Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Rouen Normandie (UNIROUEN), Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS), Institut des Sciences et Techniques de la Réadaptation [Lyon] (ISTR), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon, Ministry of Science and Technology of the People’s Republic of China, Department of Chemical Sciences, University of Messina, Dipartimento di Fisica e Astronomia 'Galileo Galilei', Università degli Studi di Padova = University of Padua (Unipd), CICNanoGUNE, Universidad Complutense de Madrid = Complutense University of Madrid [Madrid] (UCM), Boston College (BC), Laboratoire Léon Brillouin (LLB - UMR 12), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Department of Computer Science [Purdue], Purdue University [West Lafayette], Max Planck Institute for chemical Physics of Solids, Max Planck Institute for Chemical Physics of Solids (CPfS), and Max-Planck-Gesellschaft
Subjects: Oxygen evolution reaction, Polymers and Plastics, Phthalocyanines, [CHIM.MATE]Chemical Sciences/Material chemistry, Catalysis, Electronic, Optical and Magnetic Materials, Biomaterials, Colloid and Surface Chemistry, Materials Chemistry, Covalent organic frameworks, Phthalocyanines, Earth abundant transition metals, Electrocatalysis, Oxygen evolution reaction, [CHIM]Chemical Sciences, Earth abundant transition metals, Electrocatalysis, Covalent organic frameworks
Abstract: International audience; Nearly two decades ago, Alexei Kitaev proposed a model for spin-1/2 particles with bond-directional interactions on a two-dimensional honeycomb lattice which had the potential to host a quantum spin-liquid ground state. This work initiated numerous investigations to design and synthesize materials that would physically realize the Kitaev Hamiltonian. The first generation of such materials, such as Na2IrO3, α-Li2IrO3, and α-RuCl3, revealed the presence of non-Kitaev interactions such as the Heisenberg and off-diagonal exchange. Both physical pressure and chemical doping were used to tune the relative strength of the Kitaev and competing interactions; however, little progress was made towards achieving a purely Kitaev system. Here, we review the recent breakthrough in modifying Kitaev magnets via topochemical methods that has led to the second generation of Kitaev materials. We show how structural modifications due to the topotactic exchange reactions can alter the magnetic interactions in favor of a quantum spin-liquid phase.
Published: 2022
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4. Urban Brush: Intuitive and Controllable Urban Layout Editing

Author: Xiaochen Zhou, Bedrich Benes, Marie-Paule R. Cani, Pascal Chang, Purdue University [West Lafayette], Laboratoire d'informatique de l'École polytechnique [Palaiseau] (LIX), École polytechnique (X)-Centre National de la Recherche Scientifique (CNRS), and Department of Computer Science [Purdue]
Subjects: Engineering drawing, Computer science, 0211 other engineering and technologies, Volume (computing), Brush, 020207 software engineering, 021107 urban & regional planning, 02 engineering and technology, 15. Life on land, [INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR], law.invention, Entertainment, Computer graphics, Set (abstract data type), Block (programming), law, Atomic operations, 0202 electrical engineering, electronic engineering, information engineering, Key (cryptography), [INFO.INFO-HC]Computer Science [cs]/Human-Computer Interaction [cs.HC], ComputingMethodologies_COMPUTERGRAPHICS
Abstract: International audience; We present a novel method for authoring landscapes with flora and fauna while considering their mutual interactions. Our algorithm outputs a steady-state ecosystem in the form of density maps for each species, their daily circuits, and a modified terrain with eroded trails from a terrain, climatic conditions, and species with related biological information. We introduce the Resource Access Graph, a new data structure that encodes both interactions between food chain levels and animals traveling between resources over the terrain. A novel competition algorithm operating on this data progressively computes a steady-state solution up the food chain, from plants to carnivores. The user can explore the resulting landscape, where plants and animals are instantiated on the fly, and interactively edit it by over-painting the maps. Our results show that our system enables the authoring of consistent landscapes where the impact of wildlife is visible through animated animals, clearings in the vegetation, and eroded trails. We provide quantitative validation with existing ecosystems and a user-study with expert paleontologist end-users, showing that our system enables them to author and compare different ecosystems illustrating climate changes over the same terrain while enabling relevant visual immersion into consistent landscapes.
Published: 2021
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5. Generalization Bounds using Lower Tail Exponents in Stochastic Optimizers

Author: Hodgkinson, Liam, Şimşekli, Umut, Khanna, Rajiv, Mahoney, Michael W., Şimşekli, Umut, PaRis Artificial Intelligence Research InstitutE - - PRAIRIE2019 - ANR-19-P3IA-0001 - P3IA - VALID, Department of Statistics [Berkeley], University of California [Berkeley] (UC Berkeley), University of California (UC)-University of California (UC), Statistical Machine Learning and Parsimony (SIERRA), Département d'informatique - ENS Paris (DI-ENS), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria), Department of Computer Science [Purdue], Purdue University [West Lafayette], and ANR-19-P3IA-0001,PRAIRIE,PaRis Artificial Intelligence Research InstitutE(2019)
Subjects: [STAT]Statistics [stat], FOS: Computer and information sciences, Computer Science - Machine Learning, Statistics - Machine Learning, Machine Learning (stat.ML), [STAT] Statistics [stat], Machine Learning (cs.LG)
Abstract: Despite the ubiquitous use of stochastic optimization algorithms in machine learning, the precise impact of these algorithms and their dynamics on generalization performance in realistic non-convex settings is still poorly understood. While recent work has revealed connections between generalization and heavy-tailed behavior in stochastic optimization, this work mainly relied on continuous-time approximations; and a rigorous treatment for the original discrete-time iterations is yet to be performed. To bridge this gap, we present novel bounds linking generalization to the lower tail exponent of the transition kernel associated with the optimizer around a local minimum, in both discrete- and continuous-time settings. To achieve this, we first prove a data- and algorithm-dependent generalization bound in terms of the celebrated Fernique-Talagrand functional applied to the trajectory of the optimizer. Then, we specialize this result by exploiting the Markovian structure of stochastic optimizers, and derive bounds in terms of their (data-dependent) transition kernels. We support our theory with empirical results from a variety of neural networks, showing correlations between generalization error and lower tail exponents., 22 pages, 6 figures
Published: 2021

6. Precise Minimax Regret for Logistic Regression

Author: Jacquet, Philippe, Shamir, Gil, Szpankowski, Wojciech, inTeRnet BEyond the usual (TRiBE ), Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Google Pittsburgh, Department of Computer Science [Purdue], Purdue University [West Lafayette], and Jacquet, Philippe
Subjects: [INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Abstract: We study online logistic regression with binary labels and general feature values in which a learner sequentially tries to predict an outcome/ label based on data/ features received in rounds. Our goal is to evaluate precisely the (maximal) minimax regret which we analyze using a unique and novel combination of information-theoretic and analytic combinatoric tools such as Fourier transform, saddle point method, and Mellin transform in the multi-dimensional settings. To be more precise, the pointwise regret of an online algorithm is defined as the (excess) loss it incurs over a constant comparator (weight vector) that is used for prediction. It depends on the feature values, label sequence, and the learning algorithm. In the maximal minimax scenario we seek the best weights for the worst label sequence over all label distributions. For dimension d = o(T 1/3) we show that the maximal minimax regret grows as d 2 log(2T /π) + C d + O(d 3/2 / √ T) where T is the number of rounds of running a training algorithm and C d is explicitly computable constant that depends on dimension d and data. For features uniformly distributed on a d-dimensional sphere or ball we estimate precisely the constant C d showing that C d ∼ −(d/2) log(d/ √ 2π) leading to the minimax regret growing for large d as (d/2) log(T /d) − (d/2) log(√ 8π) + O(1). We also extend these results to non-binary labels. The precise maximal minimax regret presented here is the first result of this kind for any feature values and wide range of d. This provides a precise answer to the challenge posed in McMahan and Streeter (2010).
Published: 2021

7. Performance Models for the Spike Banded Linear System Solver

Author: Grama, Ananth [Department of Computer Science, Purdue University, West Lafayette, IN, USA]
Published: 2011
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8. SHREC 2020: Classification in cryo-electron tomograms

Author: Remco C. Veltkamp, Min Xu, Nguyen P. Nguyen, Xuefeng Cui, Filiz Bunyak, Yu Hao, Xiangrui Zeng, Gijs van der Schot, Tommi A. White, Fa Zhang, Ilja Gubins, Xiao Wang, Daisuke Kihara, Marten L. Chaillet, Friedrich Förster, Xiaohua Wan, Emmanuel Moebel, Department of Information and Computing Sciences [Utrecht], Utrecht University [Utrecht], Department of Chemistry [Utrecht], CAS Institute of Computing Technology (ICT), Chinese Academy of Sciences [Beijing] (CAS), School of Computer Science and Technology [Jinan], Shandong University, Space-timE RePresentation, Imaging and cellular dynamics of molecular COmplexes (SERPICO), Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Department of Computer Science [Purdue], Purdue University [West Lafayette], Computational Biology Department [Pittsburgh], Carnegie Mellon University [Pittsburgh] (CMU), Department of Computer Science Electrical Engineering [Kansas City], University of Missouri [Kansas City] (UMKC), University of Missouri System-University of Missouri System, University of Missouri [St. Louis], and University of Missouri System
Subjects: Artificial neural network, business.industry, Computer science, Template matching, Resolution (electron density), General Engineering, 020207 software engineering, Pattern recognition, Context (language use), 02 engineering and technology, Function (mathematics), Computer Graphics and Computer-Aided Design, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], Human-Computer Interaction, [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV], 0202 electrical engineering, electronic engineering, information engineering, Benchmark (computing), 020201 artificial intelligence & image processing, Artificial intelligence, Tomography, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], Focus (optics), business, [PHYS.PHYS.PHYS-DATA-AN]Physics [physics]/Physics [physics]/Data Analysis, Statistics and Probability [physics.data-an]
Abstract: International audience; Cryo-electron tomography (cryo-ET) is an imaging technique that allows us to three-dimensionally visualize both the structural details of macro-molecular assemblies under near-native conditions and its cellular context. Electrons strongly interact with biological samples, limiting electron dose. The latter limits the signal-to-noise ratio and hence resolution of an individual tomogram to about 50 (5 nm). Biological molecules can be obtained by averaging volumes, each depicting copies of the molecule, allowing for resolutions beyond 4 (0.4 nm). To this end, the ability to localize and classify components is crucial, but challenging due to the low signal-to-noise ratio. Computational innovation is key to mine biological information from cryo-electron tomography.To promote such innovation, we provide a novel simulated dataset to benchmark different methods of localization and classification of biological macromolecules in cryo-electron tomograms. Our publicly available dataset contains ten tomographic reconstructions of simulated cell-like volumes. Each volume contains twelve different types of complexes, varying in size, function and structure.In this paper, we have evaluated seven different methods of finding and classifying proteins. Six research groups present results obtained with learning-based methods and trained on the simulated dataset, as well as a baseline template matching, a traditional method widely used in cryo-ET research. We find that method performance correlates with particle size, especially noticeable for template matching which performance degrades rapidly as the size decreases. We learn that neural networks can achieve significantly better localization and classification performance, in particular convolutional networks with focus on high-resolution details such as those based on U-Net architecture.
Published: 2020
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9. Semi‐Procedural Textures Using Point Process Texture Basis Functions

Author: Eric Galin, Jean-Michel Dischler, Rémi Allègre, Pascal Guehl, Bedrich Benes, Laboratoire des sciences de l'ingénieur, de l'informatique et de l'imagerie (ICube), École Nationale du Génie de l'Eau et de l'Environnement de Strasbourg (ENGEES)-Université de Strasbourg (UNISTRA)-Institut National des Sciences Appliquées - Strasbourg (INSA Strasbourg), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Matériaux et nanosciences d'Alsace (FMNGE), Institut de Chimie du CNRS (INC)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Chimie du CNRS (INC)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Réseau nanophotonique et optique, Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA), Department of Computer Science [Purdue], Purdue University [West Lafayette], Modélisation Géométrique, Géométrie Algorithmique, Fractales (GeoMod), Laboratoire d'InfoRmatique en Image et Systèmes d'information (LIRIS), Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École Centrale de Lyon (ECL), Université de Lyon-Université Lumière - Lyon 2 (UL2)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Université Lumière - Lyon 2 (UL2), Origami (Origami), ANR-16-CE33-0001,HDWorlds,Modèles procéduraux paramétriques pour la représentation d'univers virtuels complexes(2016), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Les Hôpitaux Universitaires de Strasbourg (HUS)-Centre National de la Recherche Scientifique (CNRS)-Matériaux et Nanosciences Grand-Est (MNGE), Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Réseau nanophotonique et optique, Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS), Université Lumière - Lyon 2 (UL2)-École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Lumière - Lyon 2 (UL2)-École Centrale de Lyon (ECL), and Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)
Subjects: noise, Computer science, business.industry, 020207 software engineering, Pattern recognition, Basis function, 02 engineering and technology, material synthesis, procedural generation, Computer Graphics and Computer-Aided Design, Window function, texture synthesis, [INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR], Convolution, Rendering (computer graphics), 0202 electrical engineering, electronic engineering, information engineering, Procedural texture, 020201 artificial intelligence & image processing, Artificial intelligence, business, Texture synthesis
Abstract: We introduce a novel semi-procedural approach that avoids drawbacks of procedural textures and leverages advantages of data-driven texture synthesis. We split synthesis in two parts: 1) structure synthesis, based on a procedural parametric model and 2) color details synthesis, being data-driven. The procedural model consists of a generic Point Process Texture Basis Function (PPTBF), which extends sparse convolution noises by defining rich convolution kernels. They consist of a window function multiplied with a correlated statistical mixture of Gabor functions, both designed to encapsulate a large span of common spatial stochastic structures, including cells, cracks, grains, scratches, spots, stains, and waves. Parameters can be prescribed automatically by supplying binary structure exemplars. As for noise-based Gaussian textures, the PPTBF is used as stand-alone function, avoiding classification tasks that occur when handling multiple procedural assets. Because the PPTBF is based on a single set of parameters it allows for continuous transitions between different visual structures and an easy control over its visual characteristics. Color is consistently synthesized from the exemplar using a multiscale parallel texture synthesis by numbers, constrained by the PPTBF. The generated textures are parametric, infinite and avoid repetition. The data-driven part is automatic and guarantees strong visual resemblance with inputs. Applications: this work is related to content creation tools for films and video games, especially procedural texture and material synthesis (e.g. Substance Designer), and inverse procedural modeling (e.g inverse shade tree approach). This paper has been published in the CGF journal (Computer Grapics Forum) in July 2020 and presented at the EGSR conference (Eurographics Symposium on Rendering) in July 2020 where it got an award: Honorable Mention from the Best Papers committee.
Published: 2020
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10. Power-Law Degree Distribution in the Connected Component of a Duplication Graph

Author: Jacquet, Philippe, Turowski, Krzysztof, Szpankowski, Wojciech, inTeRnet BEyond the usual (TRiBE ), Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Uniwersytet Jagielloński w Krakowie = Jagiellonian University (UJ), Department of Computer Science [Purdue], and Purdue University [West Lafayette]
Subjects: pure duplication model, tail exponent, analytic combinatorics, [INFO]Computer Science [cs], [MATH]Mathematics [math], degree distribution, random graphs, ComputingMilieux_MISCELLANEOUS
Abstract: We study the partial duplication dynamic graph model, introduced by Bhan et al. in [Bhan et al., 2002] in which a newly arrived node selects randomly an existing node and connects with probability p to its neighbors. Such a dynamic network is widely considered to be a good model for various biological networks such as protein-protein interaction networks. This model is discussed in numerous publications with only a few recent rigorous results, especially for the degree distribution. Recently Jordan [Jordan, 2018] proved that for 0 < p < 1/e the degree distribution of the connected component is stationary with approximately a power law. In this paper we rigorously prove that the tail is indeed a true power law, that is, we show that the degree of a randomly selected node in the connected component decays like C/k^β where C an explicit constant and β ≠ 2 is a non-trivial solution of p^(β-2) + β - 3 = 0. This holds regardless of the structure of the initial graph, as long as it is connected and has at least two vertices. To establish this finding we apply analytic combinatorics tools, in particular Mellin transform and singularity analysis., LIPIcs, Vol. 159, 31st International Conference on Probabilistic, Combinatorial and Asymptotic Methods for the Analysis of Algorithms (AofA 2020), pages 16:1-16:14
Published: 2020

11. Full-field thermal imaging of quasiballistic crosstalk reduction in nanoscale devices

Author: Xavier Cartoixà, Maryam Parsa, Yee Rui Koh, Bjorn Vermeersch, Ali Shakouri, Je-Hyeong Bahk, Alvar Torelló, Pol Torres, Peide D. Ye, Yi Xuan, F. Xavier Alvarez, Amirkoushyar Ziabari, Birck Nanotechnology Center, Purdue University [West Lafayette], Universitat Autònoma de Barcelona (UAB), Laboratoire d'Innovation pour les Technologies des Energies Nouvelles et les nanomatériaux (LITEN), Institut National de L'Energie Solaire (INES), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS), Department of Computer Science [Purdue], University of California [Santa Cruz] (UC Santa Cruz), University of California (UC), European Project: 645776,H2020,H2020-NMP-2014-two-stage,ALMA(2015), Centre National de la Recherche Scientifique (CNRS)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Centre National de la Recherche Scientifique (CNRS)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), University of California [Santa Cruz] (UCSC), and University of California
Subjects: Materials science, Science, General Physics and Astronomy, 02 engineering and technology, Imaging techniques, 01 natural sciences, Article, General Biochemistry, Genetics and Molecular Biology, Crosstalk, symbols.namesake, Thermal conductivity, 0103 physical sciences, Thermal, [SPI.NANO]Engineering Sciences [physics]/Micro and nanotechnologies/Microelectronics, lcsh:Science, 010306 general physics, Nanoscopic scale, [PHYS]Physics [physics], Multidisciplinary, Nanoscale materials, business.industry, General Chemistry, Full field, 021001 nanoscience & nanotechnology, Condensed matter physics, Semiconductor, Fourier transform, Nanoscale devices, symbols, Optoelectronics, lcsh:Q, 0210 nano-technology, business, Submicron scale
Abstract: Understanding nanoscale thermal transport is of substantial importance for designing contemporary semiconductor technologies. Heat removal from small sources is well established to be severely impeded compared to diffusive predictions due to the ballistic nature of the dominant heat carriers. Experimental observations are commonly interpreted through a reduction of effective thermal conductivity, even though most measurements only probe a single aggregate thermal metric. Here, we employ thermoreflectance thermal imaging to directly visualise the 2D temperature field produced by localised heat sources on InGaAs with characteristic widths down to 100 nm. Besides displaying effective thermal performance reductions up to 50% at the active junctions in agreement with prior studies, our steady-state thermal images reveal that, remarkably, 1–3 μm adjacent to submicron devices the crosstalk is actually reduced by up to fourfold. Submicrosecond transient imaging additionally shows responses to be faster than conventionally predicted. A possible explanation based on hydrodynamic heat transport, and some open questions, are discussed., When thermal fields in semiconductors approach the submicron scale, non-diffusive heat transport is observed where Fourier based heat transport models fail. Here, the authors use thermal imaging to visualise these thermal field variations and in turn derive a hydrodynamic heat transport model.
Published: 2018
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12. Interactive example-based terrain authoring with conditional generative adversarial networks

Author: Julie Digne, Eric Galin, Bedrich Benes, Benoît Martinez, Christian Wolf, Adrien Peytavie, Eric Guérin, Modélisation Géométrique, Géométrie Algorithmique, Fractales (GeoMod), Laboratoire d'InfoRmatique en Image et Systèmes d'information (LIRIS), Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École Centrale de Lyon (ECL), Université de Lyon-Université Lumière - Lyon 2 (UL2)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Université Lumière - Lyon 2 (UL2), Extraction de Caractéristiques et Identification (imagine), Department of Computer Science [Purdue], Purdue University [West Lafayette], Ubisoft, Fonds National pour la Societé Numérique - PAPAYA P110720-2659260, ANR HDWorlds, ANR-16-CE33-0001,HDWorlds,Modèles procéduraux paramétriques pour la représentation d'univers virtuels complexes(2016), Wolf, Christian, and Modèles procéduraux paramétriques pour la représentation d'univers virtuels complexes - - HDWorlds2016 - ANR-16-CE33-0001 - AAPG2016 - VALID
Subjects: terrain generation, Computer science, Process (engineering), [INFO.INFO-GR] Computer Science [cs]/Graphics [cs.GR], ComputerApplications_COMPUTERSINOTHERSYSTEMS, Terrain, 02 engineering and technology, Machine learning, computer.software_genre, GeneralLiterature_MISCELLANEOUS, Set (abstract data type), Human–computer interaction, 0202 electrical engineering, electronic engineering, information engineering, procedural modeling, Procedural modeling, ComputingMethodologies_COMPUTERGRAPHICS, business.industry, deep learning, 020207 software engineering, Computer Graphics and Computer-Aided Design, Pipeline (software), [INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR], Sketch, 020201 artificial intelligence & image processing, Artificial intelligence, business, computer
Abstract: International audience; Authoring virtual terrains presents a challenge and there is a strong need for authoring tools able to create realistic terrains with simple user-inputs and with high user control. We propose an example-based authoring pipeline that uses a set of terrain synthesizers dedicated to specific tasks. Each terrain synthesizer is a Conditional Generative Adversarial Network trained by using real-world terrains and their sketched counterparts. The training sets are built automatically with a view that the terrain synthesizers learn the generation from features that are easy to sketch. During the authoring process, the artist first creates a rough sketch of the main terrain features, such as rivers, valleys and ridges, and the algorithm automatically synthesizes a terrain corresponding to the sketch using the learned features of the training samples. Moreover, an erosion synthesizer can also generate terrain evolution by erosion at a very low computational cost. Our framework allows for an easy terrain authoring and provides a high level of realism for a minimum sketch cost. We show various examples of terrain synthesis created by experienced as well as inexperienced users who are able to design a vast variety of complex terrains in a very short time.
Published: 2017
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13. Authoring landscapes by combining ecosystem and terrain erosion simulation

Author: Guillaume Cordonnier, Marie-Paule Cani, Bedrich Benes, Eric Guérin, Adrien Peytavie, James Gain, Eric Galin, Intuitive Modeling and Animation for Interactive Graphics & Narrative Environments (IMAGINE ), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Laboratoire Jean Kuntzmann (LJK ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Modélisation Géométrique, Géométrie Algorithmique, Fractales (GeoMod), Laboratoire d'InfoRmatique en Image et Systèmes d'information (LIRIS), Université Lumière - Lyon 2 (UL2)-École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Lumière - Lyon 2 (UL2)-École Centrale de Lyon (ECL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS), University of Cape Town, Department of Computer Science [Purdue], Purdue University [West Lafayette], ERC, Fonds National pour la Société Numérique, ANR, NSF, ANR-16-CE33-0001,HDWorlds,Modèles procéduraux paramétriques pour la représentation d'univers virtuels complexes(2016), European Project: 291184,EC:FP7:ERC,ERC-2011-ADG_20110209,EXPRESSIVE(2012), Institut National des Sciences Appliquées de Lyon (INSA Lyon), Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École Centrale de Lyon (ECL), Université de Lyon-Université Lumière - Lyon 2 (UL2)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), and Université de Lyon-Université Lumière - Lyon 2 (UL2)
Subjects: 010504 meteorology & atmospheric sciences, Exploit, Landscapes, Computer science, Interface (Java), Terrain, 02 engineering and technology, 01 natural sciences, GeneralLiterature_MISCELLANEOUS, ACM: I.: Computing Methodologies/I.3: COMPUTER GRAPHICS, Computer graphics, 0202 electrical engineering, electronic engineering, information engineering, medicine, [INFO]Computer Science [cs], Ecosystem, ComputingMethodologies_COMPUTERGRAPHICS, 0105 earth and related environmental sciences, Vegetation, business.industry, Environmental resource management, 020207 software engineering, 15. Life on land, Computer Graphics and Computer-Aided Design, [INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR], Stochastic, Variety (cybernetics), Erosion, medicine.symptom, Simulation of Natural Phenomena, Vegetation (pathology), business
Abstract: The paper was presented at Siggraph 2017; International audience; We introduce a novel framework for interactive landscape authoring that supports bi-directional feedback between erosion and vegetation simulation. Vegetation and terrain erosion have strong mutual impact and their interplay innuences the overall realism of virtual scenes. Despite their importance, these complex interactions have been neglected in computer graphics. Our framework overcomes this by simulating the eeect of a variety of geomor-phological agents and the mutual interaction between diierent material and vegetation layers, including rock, sand, humus, grass, shrubs, and trees. Users are able to exploit these interactions with an authoring interface that consistently shapes the terrain and populates it with details. Our method, validated through side-by-side comparison with real terrains, can be used not only to generate realistic static landscapes, but also to follow the temporal evolution of a landscape over a few centuries.
Published: 2017
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14. Dendry: A Procedural Model for Dendritic Patterns

Author: Damien Rohmer, Bedrich Benes, Mathieu Gaillard, Marie-Paule Cani, Eric Galin, Eric Guérin, Guérin, Eric, Modèles procéduraux paramétriques pour la représentation d'univers virtuels complexes - - HDWorlds2016 - ANR-16-CE33-0001 - AAPG2016 - VALID, Department of Computer Science [Purdue], Purdue University [West Lafayette], Modélisation Géométrique, Géométrie Algorithmique, Fractales (GeoMod), Laboratoire d'InfoRmatique en Image et Systèmes d'information (LIRIS), Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École Centrale de Lyon (ECL), Université de Lyon-Université Lumière - Lyon 2 (UL2)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Université Lumière - Lyon 2 (UL2), Laboratoire d'informatique de l'École polytechnique [Palaiseau] (LIX), Centre National de la Recherche Scientifique (CNRS)-École polytechnique (X), Fonds National pour la Societé Numérique - PAPAYA P110720-2659260, ANR HDWorlds, and ANR-16-CE33-0001,HDWorlds,Modèles procéduraux paramétriques pour la représentation d'univers virtuels complexes(2016)
Subjects: Computer science, [INFO.INFO-GR] Computer Science [cs]/Graphics [cs.GR], 020207 software engineering, 02 engineering and technology, Function (mathematics), 010502 geochemistry & geophysics, 01 natural sciences, [INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR], Maxima and minima, Tree structure, 0202 electrical engineering, electronic engineering, information engineering, Range (statistics), Memory footprint, Geometric modeling, Procedural modeling, Algorithm, Smoothing, ComputingMilieux_MISCELLANEOUS, 0105 earth and related environmental sciences
Abstract: We introduce Dendry, a procedural function that generates dendritic patterns and is locally computable. The function is controlled by parameters such as the level of branching, the degree of local smoothing, random seeding and local disturbance parameters, and the range of the branching angles. It is also controlled by a global control function that defines the overall shape and can be used, for example, to initialize local minima. The algorithm returns the distance to a tree structure which is implicitly constructed on the fly, while requiring a small memory footprint. The evaluation can be performed in parallel for multiple points and scales linearly with the number of cores. We demonstrate an application of our model to the generation of terrain heighfields with consistent river networks. A quad core implementation of our algorithm takes about ten seconds for a 512 × 512 resolution grid on the CPU.
Published: 2019

15. A Review of Digital Terrain Modeling

Author: Guillaume Cordonnier, James Gain, Eric Galin, Bedrich Benes, Eric Guérin, Marie-Paule Cani, Adrien Peytavie, Modélisation Géométrique, Géométrie Algorithmique, Fractales (GeoMod), Laboratoire d'InfoRmatique en Image et Systèmes d'information (LIRIS), Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École Centrale de Lyon (ECL), Université de Lyon-Université Lumière - Lyon 2 (UL2)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Université Lumière - Lyon 2 (UL2), Laboratoire d'informatique de l'École polytechnique [Palaiseau] (LIX), Centre National de la Recherche Scientifique (CNRS)-École polytechnique (X), Department of Computer Science [Purdue], Purdue University [West Lafayette], University of Cape Town, ANR HDWorlds, Fonds National pour la Societé Numérique - PAPAYA P110720-2659260, and ANR-16-CE33-0001,HDWorlds,Modèles procéduraux paramétriques pour la représentation d'univers virtuels complexes(2016)
Subjects: geography, geography.geographical_feature_category, Computer science, Landform, 020207 software engineering, Terrain, 02 engineering and technology, 15. Life on land, Computer Graphics and Computer-Aided Design, [INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR], Variety (cybernetics), Computer graphics, Human–computer interaction, Component (UML), 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, Scale (map), Procedural modeling, Mountain range, ComputingMethodologies_COMPUTERGRAPHICS
Abstract: International audience; Terrains are a crucial component of three-dimensional scenes and are present in many Computer Graphics applications. Terrain modeling methods focus on capturing landforms in all their intricate detail, including eroded valleys arising from the interplay of varied phenomena, dendritic mountain ranges, and complex river networks. Set against this visual complexity is the need for user control over terrain features, without which designers are unable to adequately express their artistic intent. This article provides an overview of current terrain modeling and authoring techniques, organized according to three categories: procedural modeling, physically-based simulation of erosion and land formation processes, and example-based methods driven by scanned terrain data. We compare and contrast these techniques according to several criteria, specifically: the variety of achievable landforms; realism from both a perceptual and geomorphological perspective; issues of scale in terms of terrain extent and sampling precision; the different interaction metaphors and attendant forms of user-control, and computation and memory performance. We conclude with an in-depth discussion of possible research directions and outstanding technical and scientific challenges.
Published: 2019
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16. Verifying a Concurrent Garbage Collector with a Rely-Guarantee Methodology

Author: Jan Vitek, Gustavo Petri, Yannick Zakowski, Delphine Demange, David Cachera, Suresh Jagannathan, David Pichardie, École normale supérieure - Rennes (ENS Rennes), Software certification with semantic analysis (CELTIQUE), Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-LANGAGE ET GÉNIE LOGICIEL (IRISA-D4), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Institut de Recherche en Informatique Fondamentale (IRIF (UMR_8243)), Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), Department of Computer Science [Purdue], Purdue University [West Lafayette], Northeastern University [Boston], ANR-14-CE28-0004,DISCOVER,Représentations Intermédiaires et Sémantiques de la Concurrence pour les Compilateurs Vérifiés(2014), Université de Bretagne Sud (UBS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National de Recherche en Informatique et en Automatique (Inria)-École normale supérieure - Rennes (ENS Rennes)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-CentraleSupélec-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Bretagne Sud (UBS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-École normale supérieure - Rennes (ENS Rennes)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Rennes 1 (UR1), and Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique)
Subjects: Soundness, Intermediate language, [INFO.INFO-PL]Computer Science [cs]/Programming Languages [cs.PL], Programming language, Computer science, Concurrent data structure, Proof assistant, 020207 software engineering, 0102 computer and information sciences, 02 engineering and technology, computer.software_genre, 01 natural sciences, Computational Theory and Mathematics, 010201 computation theory & mathematics, Artificial Intelligence, TheoryofComputation_LOGICSANDMEANINGSOFPROGRAMS, 0202 electrical engineering, electronic engineering, information engineering, Compiler, computer, Software, Program logic, Garbage collection
Abstract: International audience; Concurrent garbage collection algorithms are a challenge for program verification. In this paper, we address this problem by proposing a mechanized proof methodology based on the Rely-Guarantee proof technique. We design a compiler intermediate representation with strong type guarantees, dedicated support for abstract concurrent data structures, and high-level iterators on runtime internals. In addition, we define an Rely-Guarantee program logic supporting an incremental proof methodology where annotations and invariants can be progressively enriched. We formalize the intermediate representation, the proof system, and prove the soundness of the methodology in the Coq proof assistant. Equipped with this, we prove a fully concurrent garbage collector where mutators never have to wait for the collector.
Published: 2018
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17. Feedforward Neural Networks for Caching: Enough or Too Much?

Author: Vladyslav Fedchenko, Bruno Ribeiro, Giovanni Neglia, Network Engineering and Operations (NEO ), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Department of Computer Science [Purdue], and Purdue University [West Lafayette]
Subjects: FOS: Computer and information sciences, Scheme (programming language), Computer Networks and Communications, Computer science, 0102 computer and information sciences, 02 engineering and technology, 01 natural sciences, Computer Science - Networking and Internet Architecture, [INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI], [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], 0202 electrical engineering, electronic engineering, information engineering, computer.programming_language, Networking and Internet Architecture (cs.NI), Hardware_MEMORYSTRUCTURES, Artificial neural network, business.industry, Estimator, 020206 networking & telecommunications, Recurrent neural network, 010201 computation theory & mathematics, Hardware and Architecture, Feedforward neural network, Artificial intelligence, business, computer, Software
Abstract: International audience; We propose a caching policy that uses a feedforward neural network (FNN) to predict content popularity. Our scheme outperforms popular eviction policies like LRU or ARC, but also a new policy relying on the more complex recurrent neural networks. At the same time, replacing the FNN predictor with a naive linear estimator does not degrade caching performance significantly, questioning then the role of neural networks for these applications.
Published: 2018
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18. Revisiting random walk based sampling in networks: Evasion of burn-in period and frequent regenerations

Author: Vivek S. Borkar, Arun Kadavankandy, Jithin K. Sreedharan, Konstantin Avrachenkov, Network Engineering and Operations (NEO ), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Department of Electrical Engineering [IIT-Bombay] (EE-IIT), Indian Institute of Technology Kanpur (IIT Kanpur), Department of Computer Science [Purdue], and Purdue University [West Lafayette]
Subjects: Mean squared error, Respondent-driven sampling, Computer science, Stability (learning theory), 02 engineering and technology, Stochastic approximation, 01 natural sciences, lcsh:QA75.5-76.95, [INFO.INFO-SI]Computer Science [cs]/Social and Information Networks [cs.SI], 010104 statistics & probability, symbols.namesake, [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], Reinforcement learning, 0202 electrical engineering, electronic engineering, information engineering, 0101 mathematics, Network sampling, Random walks on graph, lcsh:T58.5-58.64, lcsh:Information technology, Research, Sampling (statistics), Estimator, 020206 networking & telecommunications, Markov chain Monte Carlo, Complex network, Random walk, Computer Science Applications, Human-Computer Interaction, Modeling and Simulation, symbols, lcsh:Electronic computers. Computer science, Algorithm, Information Systems
Abstract: International audience; Background: In the framework of network sampling, random walk (RW) based estimation techniques provide many pragmatic solutions while uncovering the unknown network as little as possible. Despite several theoretical advances in this area, RW based sampling techniques usually make a strong assumption that the samples are in stationary regime, and hence are impelled to leave out the samples collected during the burn-in period. Methods: This work proposes two sampling schemes without burn-in time constraint to estimate the average of an arbitrary function defined on the network nodes, for example, the average age of users in a social network. The central idea of the algorithms lies in exploiting regeneration of RWs at revisits to an aggregated super-node or to a set of nodes, and in strategies to enhance the frequency of such regenerations either by contracting the graph or by making the hitting set larger. Our first algorithm, which is based on reinforcement learning (RL), uses stochastic approximation to derive an estimator. This method can be seen as intermediate between purely stochastic Markov chain Monte Carlo iterations and deterministic relative value iterations. The second algorithm, which we call the Ratio with Tours (RT)-estimator, is a modified form of respondent-driven sampling (RDS) that accommodates the idea of regeneration. Results: We study the methods via simulations on real networks. We observe that the trajectories of RL-estimator are much more stable than those of standard random walk based estimation procedures, and its error performance is comparable to that of respondent-driven sampling (RDS) which has a smaller asymptotic variance than many other estimators. Simulation studies also show that the mean squared error of RT-esti-mator decays much faster than that of RDS with time. Conclusion: The newly developed RW based estimators (RL-and RT-estimators) allow to avoid burn-in period, provide better control of stability along the sample path, and overall reduce the estimation time. Our estimators can be applied in social and complex networks.
Published: 2018
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19. Verifying a Concurrent Garbage Collector using a Rely-Guarantee Methodology

Author: Gustavo Petri, David Cachera, Delphine Demange, Jan Vitek, David Pichardie, Yannick Zakowski, Suresh Jagannathan, Software certification with semantic analysis (CELTIQUE), Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-LANGAGE ET GÉNIE LOGICIEL (IRISA-D4), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Rennes 1 (UR1), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Institut de Recherche en Informatique Fondamentale (IRIF (UMR_8243)), Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), Department of Computer Science [Purdue], Purdue University [West Lafayette], Northeastern University [Boston], ANR 14-CE28-0004, NSF CCF- 1318227, CCF-1544542, SHF-1518844, ONR N00014-15-1-2332, ANR-14-CE28-0004,DISCOVER,Représentations Intermédiaires et Sémantiques de la Concurrence pour les Compilateurs Vérifiés(2014), Université de Bretagne Sud (UBS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National de Recherche en Informatique et en Automatique (Inria)-École normale supérieure - Rennes (ENS Rennes)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-CentraleSupélec-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Bretagne Sud (UBS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-École normale supérieure - Rennes (ENS Rennes)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), and Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique)
Subjects: Soundness, Intermediate language, Computer science, Programming language, Concurrent data structure, Proof assistant, [SCCO.COMP]Cognitive science/Computer science, 020207 software engineering, 0102 computer and information sciences, 02 engineering and technology, computer.software_genre, 01 natural sciences, 010201 computation theory & mathematics, TheoryofComputation_LOGICSANDMEANINGSOFPROGRAMS, 0202 electrical engineering, electronic engineering, information engineering, Compiler, computer, Garbage collection, Program logic
Abstract: International audience; Concurrent garbage collection algorithms are an emblematic challenge in the area of concurrent program verification. In this paper, we address this problem by proposing a mechanized proof methodology based on the popular Rely-Guarantee (RG) proof technique. We design a specific compiler intermediate representation (IR) with strong type guarantees, dedicated support for abstract concurrent data structures, and high-level iterators on runtime internals. In addition, we define an RG program logic supporting an incremental proof methodology where annotations and invariants can be progressively enriched.We formalize the IR, the proof system, and prove the soundness of the methodology in the Coq proof assistant. Equipped with this IR, we prove a fully concurrent garbage collector where mutators never have to wait for the collector.
Published: 2017
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20. Error-Bounded and Feature Preserving Surface Remeshing with Minimal Angle Improvement

Author: Pierre Alliez, Dong-Ming Yan, Bedrich Benes, David Bommes, Kaimo Hu, Department of Computer Science [Purdue], Purdue University [West Lafayette], National Laboratory of Pattern Recognition [Beijing] (NLPR), Institute of Automation - Chinese Academy of Sciences, Rheinisch-Westfälische Technische Hochschule Aachen University (RWTH), Geometric Modeling of 3D Environments (TITANE), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), and European Project: 257474,EC:FP7:ERC,ERC-2010-StG_20091028,IRON(2011)
Subjects: Computational Geometry (cs.CG), FOS: Computer and information sciences, Surface (mathematics), Mathematical optimization, Computer science, 02 engineering and technology, [INFO.INFO-CG]Computer Science [cs]/Computational Geometry [cs.CG], Operator (computer programming), Computer Science - Graphics, feature preserving, Approximation error, error-bounded, surface remeshing, minimal angle improvement, feature intensity, 0202 electrical engineering, electronic engineering, information engineering, Polygon mesh, ComputingMethodologies_COMPUTERGRAPHICS, Approximation algorithm, 020207 software engineering, Geometry processing, Computer Graphics and Computer-Aided Design, Graphics (cs.GR), Vertex (geometry), Bounded function, Signal Processing, Computer Science - Computational Geometry, 020201 artificial intelligence & image processing, Algorithm design, Computer Vision and Pattern Recognition, Algorithm, Software
Abstract: The typical goal of surface remeshing consists in finding a mesh that is (1) geometrically faithful to the original geometry, (2) as coarse as possible to obtain a low-complexity representation and (3) free of bad elements that would hamper the desired application. In this paper, we design an algorithm to address all three optimization goals simultaneously. The user specifies desired bounds on approximation error {\delta}, minimal interior angle {\theta} and maximum mesh complexity N (number of vertices). Since such a desired mesh might not even exist, our optimization framework treats only the approximation error bound {\delta} as a hard constraint and the other two criteria as optimization goals. More specifically, we iteratively perform carefully prioritized local operators, whenever they do not violate the approximation error bound and improve the mesh otherwise. In this way our optimization framework greedily searches for the coarsest mesh with minimal interior angle above {\theta} and approximation error bounded by {\delta}. Fast runtime is enabled by a local approximation error estimation, while implicit feature preservation is obtained by specifically designed vertex relocation operators. Experiments show that our approach delivers high-quality meshes with implicitly preserved features and better balances between geometric fidelity, mesh complexity and element quality than the state-of-the-art., Comment: 14 pages, 20 figures. Submitted to IEEE Transactions on Visualization and Computer Graphics
Published: 2017
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21. Prediction of homo- and hetero-protein complexes by protein docking and template-based modeling: a CASP-CAPRI experiment

Author: Eichiro Ichiishi, Dmitri Beglov, Bernard Maigret, Gyu Rie Lee, Artem B. Mamonov, Shoshana J. Wodak, Jonathan C. Fuller, Dima Kozakov, Jong Young Joung, Petr Popov, Xiaofeng Yu, Keehyoung Joo, João P. G. L. M. Rodrigues, Anna Vangone, Koen M. Visscher, Xiaoqin Zou, Paul A. Bates, Andriy Kryshtafovych, Shourya S. Roy Burman, Daisuke Kihara, Romina Oliva, Efrat Ben-Zeev, Jeffrey J. Gray, Yang Shen, Li C. Xue, Sameer Velankar, Emilie Neveu, Shruthi Viswanath, Dina Schneidman-Duhovny, Juan Esquivel-Rodríguez, Mieczyslaw Torchala, Amit Roy, Alexandre M. J. J. Bonvin, David R. Hall, Tanggis Bohnuud, Xusi Han, David W. Ritchie, Ron Elber, Daisuke Kuroda, Zhiwei Ma, Joan Segura, Carlos A. Del Carpio, Nicholas A. Marze, Jong Yun Kim, Andrej Sali, Petras J. Kundrotas, Ezgi Karaca, Neil J. Bruce, Chaok Seok, Panagiotis L. Kastritis, Shen You Huang, Ilya A. Vakser, Lim Heo, Sanbo Qin, Raphael A. G. Chaleil, Adrien S. J. Melquiond, Miguel Romero-Durana, Anisah W. Ghoorah, Surendra S. Negi, Andrey Tovchigrechko, Françoise Ochsenbein, Narcis Fernandez-Fuentes, Liming Qiu, Miriam Eisenstein, Mehdi Nellen, Marie-Dominique Devignes, Lenna X. Peterson, Jinchao Yu, Minkyung Baek, Brian G. Pierce, Hasup Lee, Toshiyuki Oda, Rebecca C. Wade, Raphael Guerois, Juan Fernández-Recio, Iain H. Moal, Edrisse Chermak, Sergei Grudinin, Sangwoo Park, Ivan Anishchenko, Chengfei Yan, Thom Vreven, Kentaro Tomii, Bing Xia, Hyung Rae Kim, Chiara Pallara, Jooyoung Lee, Kazunori D. Yamada, Xianjin Xu, Kenichiro Imai, Zhiping Weng, Luigi Cavallo, Tyler M. Borrman, Jianlin Cheng, Marc F. Lensink, Huan-Xiang Zhou, Jilong Li, Gydo C. P. van Zundert, Brian Jiménez-García, Tsukasa Nakamura, Scott E. Mottarella, Sandor Vajda, Institut de Recherche Interdisciplinaire [Villeneuve d'Ascq] ( IRI ), Université de Lille, Sciences et Technologies-Université de Lille, Droit et Santé-Centre National de la Recherche Scientifique ( CNRS ), European Molecular Biology Laboratory, European Bioinformatics Institute, Genome Center [UC Davis], University of California at Davis, Research Support Computing [Columbia], University of Missouri-Columbia, Bioinformatics Consortium and Department of Computer Science [Columbia], Department of Bioengineering and Therapeutic Sciences, University of California [San Francisco] ( UCSF ), Department of Pharmaceutical Chemistry, Department of Bioengineering and Therapeutic Sciences, Department of Pharmaceutical Chemistry, University of California [San Francisco] ( UCSF ) -California Institute for Quantitative Biosciences, GN7 of the National Institute for Bioinformatics (INB) and Biocomputing Unit, Centro Nacional de Biotecnología (CSIC), Institute of Biological, Environmental and Rural Sciences ( IBERS ), Institute for Computational Engineering and Sciences [Austin] ( ICES ), University of Texas at Austin [Austin], Department of Computer Science, Department of Chemistry, Algorithms for Modeling and Simulation of Nanosystems ( NANO-D ), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique ( Inria ) -Institut National de Recherche en Informatique et en Automatique ( Inria ) -Laboratoire Jean Kuntzmann ( LJK ), Université Pierre Mendès France - Grenoble 2 ( UPMF ) -Université Joseph Fourier - Grenoble 1 ( UJF ) -Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique ( CNRS ) -Université Grenoble Alpes ( UGA ) -Université Pierre Mendès France - Grenoble 2 ( UPMF ) -Université Joseph Fourier - Grenoble 1 ( UJF ) -Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique ( CNRS ) -Université Grenoble Alpes ( UGA ) -Institut National Polytechnique de Grenoble ( INPG ), Moscow Institute of Physics and Technology [Moscow] ( MIPT ), Seoul National University [Seoul], Florida State University [Tallahassee] ( FSU ), Computational Algorithms for Protein Structures and Interactions ( CAPSID ), Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique ( Inria ) -Institut National de Recherche en Informatique et en Automatique ( Inria ) -Department of Complex Systems, Artificial Intelligence & Robotics ( LORIA - AIS ), Laboratoire Lorrain de Recherche en Informatique et ses Applications ( LORIA ), Institut National de Recherche en Informatique et en Automatique ( Inria ) -Université de Lorraine ( UL ) -Centre National de la Recherche Scientifique ( CNRS ) -Institut National de Recherche en Informatique et en Automatique ( Inria ) -Université de Lorraine ( UL ) -Centre National de la Recherche Scientifique ( CNRS ) -Laboratoire Lorrain de Recherche en Informatique et ses Applications ( LORIA ), Institut National de Recherche en Informatique et en Automatique ( Inria ) -Université de Lorraine ( UL ) -Centre National de la Recherche Scientifique ( CNRS ) -Université de Lorraine ( UL ) -Centre National de la Recherche Scientifique ( CNRS ), University of Mauritius, Biomolecular Modelling Laboratory, The Francis Crick Institute, Lincoln's Inn Fields Laboratory, G-INCPM, Weizmann Institute of Science, Chemical Research Support [Rehovot], Sealy Center for Structural Biology and Molecular Biophysics, The University of Texas Medical Branch ( UTMB ), Program in Bioinformatics and Integrative Biology [Worcester], University of Massachusetts Medical School [Worcester] ( UMASS ), Institut de Biologie Intégrative de la Cellule ( I2BC ), Université Paris-Saclay-Centre National de la Recherche Scientifique ( CNRS ) -Commissariat à l'énergie atomique et aux énergies alternatives ( CEA ) -Université Paris-Sud - Paris 11 ( UP11 ), Bijvoet Center for Biomolecular Research [Utrecht], Utrecht University [Utrecht], Dalton Cardiovascular Research Center [Columbia], Department of Computer Science [Columbia], Informatics Intitute, Department of Biochemistry, University of Missouri, UNIVERSITY OF MISSOURI, Toyota Technological Institute at Chicago [Chicago] ( TTIC ), Department of Biological Sciences, Purdue University, Purdue University [West Lafayette], Department of Computer Science [Purdue], Bioinformatics and Computational Biosciences Branch, Rocky Mountain Laboratories, Molecular and Cellular Modeling Group, Heidelberg Institute of Theoretical Studies, Center for Molecular Biology ( ZMBH ), Universität Heidelberg [Heidelberg], Interdisciplinary Center for Scientiﬁc Computing ( IWR ), Department of Molecular Biosciences [Lawrence], University of Kansas [Lawrence] ( KU ), Computational Biology Research Center ( CBRC ), National Institute of Advanced Industrial Science and Technology ( AIST ), Graduate School of Frontier Sciences, The University of Tokyo, Joint BSC-CRG-IRB Research Program in Computational Biology, Barcelona Supercomputing Center - Centro Nacional de Supercomputacion ( BSC - CNS ), Center for In-Silico Protein Science, Korea Institute for Advanced Study ( KIAS ), Center for Advanced Computation, Department of Biomedical Engineering [Boston], Boston University [Boston] ( BU ), Institute of Biological Diversity, International Pacific Institute of Indiana, Drosophila Genetic Resource Center, Kyoto Institute of Technology, International University of Health and Welfare Hospital ( IUHW Hospital ), International University of Health and Welfare Hospital, Department of Chemical and Biomolecular Engineering [Baltimore], Johns Hopkins University ( JHU ), Program in Molecular Biophysics [Baltimore], King Abdullah University of Science and Technology ( KAUST ), University of Naples, J Craig Venter Institute, Structural Biology Research Center, VIB, 1050 Brussels, Belgium, Institut de Recherche Interdisciplinaire [Villeneuve d'Ascq] (IRI), Université de Lille, Sciences et Technologies-Université de Lille, Droit et Santé-Centre National de la Recherche Scientifique (CNRS), European Bioinformatics Institute [Hinxton] (EMBL-EBI), EMBL Heidelberg, University of California [Davis] (UC Davis), University of California (UC)-University of California (UC), University of Missouri [Columbia] (Mizzou), University of Missouri System, University of California [San Francisco] (UC San Francisco), Centro Nacional de Biotecnología [Madrid] (CNB-CSIC), Consejo Superior de Investigaciones Científicas [Madrid] (CSIC)-Consejo Superior de Investigaciones Científicas [Madrid] (CSIC), Institute of Biological, Environmental and Rural Sciences (IBERS), Institute for Computational Engineering and Sciences [Austin] (ICES), Algorithms for Modeling and Simulation of Nanosystems (NANO-D), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Laboratoire Jean Kuntzmann (LJK ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Moscow Institute of Physics and Technology [Moscow] (MIPT), Seoul National University [Seoul] (SNU), Florida State University [Tallahassee] (FSU), Computational Algorithms for Protein Structures and Interactions (CAPSID), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Complex Systems, Artificial Intelligence & Robotics (LORIA - AIS), Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Biomolecular Modelling Laboratory [London], The Francis Crick Institute [London], Weizmann Institute of Science [Rehovot, Israël], The University of Texas Medical Branch (UTMB), University of Massachusetts Medical School [Worcester] (UMASS), University of Massachusetts System (UMASS)-University of Massachusetts System (UMASS), Institut de Biologie Intégrative de la Cellule (I2BC), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Assemblage moléculaire et intégrité du génome (AMIG), Département Biochimie, Biophysique et Biologie Structurale (B3S), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Institut de Biologie Intégrative de la Cellule (I2BC), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), University of Missouri System-University of Missouri System, Toyota Technological Institute at Chicago [Chicago] (TTIC), Department of Biological Sciences [Lafayette IN], Heidelberg Institute for Theoretical Studies (HITS ), Center for Molecular Biology (ZMBH), Universität Heidelberg [Heidelberg] = Heidelberg University, Interdisciplinary Center for Scientiﬁc Computing (IWR), University of Kansas [Lawrence] (KU), Computational Biology Research Center (CBRC), National Institute of Advanced Industrial Science and Technology (AIST), The University of Tokyo (UTokyo), Barcelona Supercomputing Center - Centro Nacional de Supercomputacion (BSC - CNS), Korea Institute for Advanced Study (KIAS), Boston University [Boston] (BU), International University of Health and Welfare Hospital (IUHW Hospital), Johns Hopkins University (JHU), King Abdullah University of Science and Technology (KAUST), University of Naples Federico II = Università degli studi di Napoli Federico II, J. Craig Venter Institute, VIB-VUB Center for Structural Biology [Bruxelles], VIB [Belgium], Centre National de la Recherche Scientifique (CNRS)-Université de Lille, Droit et Santé-Université de Lille, Sciences et Technologies, University of California-University of California, University of California [San Francisco] (UCSF), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL), University of Naples Federico II, Barcelona Supercomputing Center, NMR Spectroscopy, and Sub NMR Spectroscopy
Subjects: 0301 basic medicine, Protein Conformation, alpha-Helical, Protein Folding, Computer science, International Cooperation, Amino Acid Motifs, Oligomer state, Homoprotein, DATA-BANK, computer.software_genre, Molecular Docking Simulation, Biochemistry, CAPRI Round 30, DESIGN, Structural Biology, ALIGN, Blind prediction, AFFINITY, Protein interaction, Enginyeria biomèdica [Àrees temàtiques de la UPC], ZDOCK, Oligomer State, computer.file_format, Articles, Protein structure prediction, Proteïnes--Investigació, 3. Good health, WEB SERVER, CASP, Thermodynamics, Data mining, CAPRI, Protein docking, Molecular Biology, Algorithms, INTERFACES, Protein Binding, [ INFO.INFO-MO ] Computer Science [cs]/Modeling and Simulation, Bioinformatics, STRUCTURAL BIOLOGY, Computational biology, Molecular Dynamics Simulation, Article, 03 medical and health sciences, [ INFO.INFO-BI ] Computer Science [cs]/Bioinformatics [q-bio.QM], Heteroprotein, Humans, Protein binding, Macromolecular docking, Protein Interaction Domains and Motifs, Homology modeling, ALGORITHM, Protein-protein docking, Internet, Binding Sites, Models, Statistical, 030102 biochemistry & molecular biology, Bacteria, Sequence Homology, Amino Acid, Computational Biology, Proteins, Protein Data Bank, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, Protein Structure, Tertiary, 030104 developmental biology, Structural biology, Docking (molecular), Protein structure, Protein Conformation, beta-Strand, Protein Multimerization, oligomer state, blind prediction, protein interaction, protein docking, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], computer, Software
Abstract: We present the results for CAPRI Round 30, the first joint CASP-CAPRI experiment, which brought together experts from the protein structure prediction and protein–protein docking communities. The Round comprised 25 targets from amongst those submitted for the CASP11 prediction experiment of 2014. The targets included mostly homodimers, a few homotetramers, and two heterodimers, and comprised protein chains that could readily be modeled using templates from the Protein Data Bank. On average 24 CAPRI groups and 7 CASP groups submitted docking predictions for each target, and 12 CAPRI groups per target participated in the CAPRI scoring experiment. In total more than 9500 models were assessed against the 3D structures of the corresponding target complexes. Results show that the prediction of homodimer assemblies by homology modeling techniques and docking calculations is quite successful for targets featuring large enough subunit interfaces to represent stable associations. Targets with ambiguous or inaccurate oligomeric state assignments, often featuring crystal contact-sized interfaces, represented a confounding factor. For those, a much poorer prediction performance was achieved, while nonetheless often providing helpful clues on the correct oligomeric state of the protein. The prediction performance was very poor for genuine tetrameric targets, where the inaccuracy of the homology-built subunit models and the smaller pair-wise interfaces severely limited the ability to derive the correct assembly mode. Our analysis also shows that docking procedures tend to perform better than standard homology modeling techniques and that highly accurate models of the protein components are not always required to identify their association modes with acceptable accuracy. We are most grateful to the PDBe at the European Bioinformatics Institute in Hinxton, UK, for hosting the CAPRI website. Our deepest thanks go to all the structural biologists and to the following structural genomics initiatives: Northeast Structural Genomics Consortium, Joint Center for Structural Genomics, NatPro PSI:Biology, New York Structural Genomics Research Center, Midwest Center for Structural Genomics, Structural Genomics Consortium, for contributing the targets for this joint CASP-CAPRI experiment. MFL acknowledges support from the FRABio FR3688 Research Federation “Structural & Functional Biochemistry of Biomolecular Assemblies.”
Published: 2016
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22. Inference in OSNs via Lightweight Partial Crawls

Author: Bruno Ribeiro, Jithin K. Sreedharan, Konstantin Avrachenkov, Models for the performance analysis and the control of networks (MAESTRO), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Department of Computer Science [Purdue], Purdue University [West Lafayette], Bell Labs Inria Joint Lab, and ADR Network Science
Subjects: Theoretical computer science, Computer science, Computer Networks and Communications, Bayesian inference, Context (language use), 02 engineering and technology, Crawling, computer.software_genre, 01 natural sciences, Social network analysis, 010104 statistics & probability, [INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI], Graph sampling, 020204 information systems, 0202 electrical engineering, electronic engineering, information engineering, Random walk on graphs, 0101 mathematics, Random graph, Application programming interface, Social network, business.industry, Node (networking), Social network analysis (criminology), 020206 networking & telecommunications, Distributed algorithm, Hardware and Architecture, Data mining, Web crawler, business, computer, Software
Abstract: International audience; Are Online Social Network (OSN) A users more likely to form friendships with those with similar attributes? Do users at an OSN B score content more favorably than OSN C users? Such questions frequently arise in the context of Social Network Analysis (SNA) but often crawling an OSN network via its Application Programming Interface (API) is the only way to gather data from a third party. To date, these partial API crawls are the majority of public datasets and the synonym of lack of statistical guarantees in incomplete-data comparisons, severely limiting SNA research progress. Using regenerative properties of the random walks, we propose estimation techniques based on short crawls that have proven statistical guarantees. Moreover, our short crawls can be implemented in massively distributed algorithms. We also provide an adaptive crawler that makes our method parameter-free, significantly improving our statistical guarantees. We then derive the Bayesian approximation of the posterior of the estimates, and in addition, obtain an estima-tor for the expected value of node and edge statistics in an equivalent configuration model or Chung-Lu random graph model of the given network (where nodes are connected randomly) and use it as a basis for testing null hypotheses. The theoretical results are supported with simulations on a variety of real-world networks.
Published: 2016
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23. Large Scale Terrain Generation from Tectonic Uplift and Fluvial Erosion

Author: Adrien Peytavie, Marie-Paule Cani, Jean Braun, Eric Galin, Eric Guérin, Guillaume Cordonnier, Bedrich Benes, Intuitive Modeling and Animation for Interactive Graphics & Narrative Environments (IMAGINE ), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Laboratoire Jean Kuntzmann (LJK ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Institut des Sciences de la Terre (ISTerre), Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-Institut national des sciences de l'Univers (INSU - CNRS)-Institut de recherche pour le développement [IRD] : UR219-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Department of Computer Science [Purdue], Purdue University [West Lafayette], Modélisation Géométrique, Géométrie Algorithmique, Fractales (GeoMod), Laboratoire d'InfoRmatique en Image et Systèmes d'information (LIRIS), Université Lumière - Lyon 2 (UL2)-École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Lumière - Lyon 2 (UL2)-École Centrale de Lyon (ECL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS), European Project: 291184,EC:FP7:ERC,ERC-2011-ADG_20110209,EXPRESSIVE(2012), Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École Centrale de Lyon (ECL), Université de Lyon-Université Lumière - Lyon 2 (UL2)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), and Université de Lyon-Université Lumière - Lyon 2 (UL2)
Subjects: geography, river incision model, geography.geographical_feature_category, Landform, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Fluvial, 020207 software engineering, Terrain, equation, 02 engineering and technology, 15. Life on land, Computer Graphics and Computer-Aided Design, [INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR], Tectonics, Tectonic uplift, parallel, evolution, 0202 electrical engineering, electronic engineering, information engineering, Erosion, 020201 artificial intelligence & image processing, Digital elevation model, Geomorphology, Stream power, Geology, ComputingMethodologies_COMPUTERGRAPHICS
Abstract: International audience; At large scale, landscapes result from the combination of two major processes: tectonics which generate the main relief through crust uplift, and weather which accounts for erosion. This paper presents the first method in computer graphics that combines uplift and hydraulic erosion to generate visually plausible terrains. Given a user-painted uplift map, we generate a stream graph over the entire domain embedding elevation information and stream flow. Our approach relies on the stream power equation introduced in geology for hydraulic erosion. By combining crust uplift and stream power erosion we generate large realistic terrains at a low computational cost. Finally, we convert this graph into a digital elevation model by blending landform feature kernels whose parameters are derived from the information in the graph. Our method gives high-level control over the large scale dendritic structures of the resulting river networks, watersheds, and mountains ridges.
Published: 2016
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24. Forty Years of Suffix Trees

Author: Apostolico, Alberto, Crochemore, Maxime, Farach-Colton, Martín, Galil, Zvi, Muthukrishnan, S., Department of Computer Science [Purdue], Purdue University [West Lafayette], Informatics, King‘s College London, Rutgers, The State University of New Jersey [New Brunswick] (RU), Rutgers University System (Rutgers), College of Computing (GATECH), Georgia Institute of Technology [Atlanta], and Google Inc.
Subjects: factor automaton, wavelet tree, fix tree, [INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS], suffix tree, bi-tree, array, suffix, suffix automaton, pattern matching, dawg, suf, string searching, FM-index
Abstract: International audience; This paper reviews the first 40 years in the life of suffix trees, their many incarnations, and their applications. The paper is non-technical but assumes some familiarity with the structures and constructions discussed. It is not meant to be exhaustive. It is meant to be a tribute to a ubiquitous tool of string matching — the suffix tree and its variants — and one of the most persistent subjects of study in the theory of algorithms.
Published: 2016
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25. Tuning of Pectin Methylesterification : PECTIN METHYLESTERASE INHIBITOR 7 modulates the processive activity of co-expressed PECTIN METHYLESTERASE 3 in a pH-dependent manner

Author: Senechal, Fabien, L’Enfant, Mélanie, Domon, Jean-Marc, Rosiau, Emeline, CREPEAU, Marie-Jeanne, Surcouf, Ogier, Esquivel-Rodríguez, Juan, Marcelo, Paulo, Mareck, Alain, Guerineau, Francois, Kim, Hyung-Rae, MRAVEC, Jozef, Bonnin, Estelle, Jamet, Elisabeth, Kihara, Daisuke, Lerouge, Patrice, Ralet, Marie-Christine, Pelloux, Jérome, Rayon, Catherine, Biologie des Plantes et Innovation - UR UPJV 3900 (BIOPI), Université de Picardie Jules Verne (UPJV), Unité de recherche sur les Biopolymères, Interactions Assemblages (BIA), Institut National de la Recherche Agronomique (INRA), Laboratoire de Glycobiologie et Matrice Extracellulaire Végétale (Glyco-MEV), Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Normandie Université (NU), Department of Computer Science [Purdue], Purdue University [West Lafayette], Spectrométrie de Masse Biologique et Protéomique (USR3149 / FRE2032) (SMBP), Ecole Superieure de Physique et de Chimie Industrielles de la Ville de Paris (ESPCI Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS), Toyota Technological Institute at Chicago [Chicago] (TTIC), University of Copenhagen = Københavns Universitet (KU), Dynamique et Evolution des Parois cellulaires végétales, Laboratoire de Recherche en Sciences Végétales (LRSV), Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Université Toulouse III - Paul Sabatier (UT3), and Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)
Subjects: pectin methylesterase inhibitor (PMEI), [SDV.BIO]Life Sciences [q-bio]/Biotechnology, homology modeling, food and beverages, [SDV.BBM.BM]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Molecular biology, [SDV.BBM.MN]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Molecular Networks [q-bio.MN], [SDV.BC.BC]Life Sciences [q-bio]/Cellular Biology/Subcellular Processes [q-bio.SC], microscale thermophoresis, [SDV.BV.PEP]Life Sciences [q-bio]/Vegetal Biology/Phytopathology and phytopharmacy, degree of blockiness, protein-protein interaction, [SDV.BV.AP]Life Sciences [q-bio]/Vegetal Biology/Plant breeding, [CHIM.POLY]Chemical Sciences/Polymers, gel diffusion assay, plant biochemistry, [SDV.BBM.GTP]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Genomics [q-bio.GN], [SDV.BC.IC]Life Sciences [q-bio]/Cellular Biology/Cell Behavior [q-bio.CB], plant cell wall, pectin methylesterase (PME), [SDV.BBM.BC]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Biochemistry [q-bio.BM], protein expression, [SDV.BDD.GAM]Life Sciences [q-bio]/Development Biology/Gametogenesis
Abstract: International audience; Background: PME and PMEI isoforms are co-expressed in Arabidopsis. Their biochemical interaction is yet to be characterized. Results: The processive activity of AtPME3 is regulated by AtPMEI7 in a pH-dependent manner in vitro. Conclusion: AtPMEI7 is a key component of the regulation of AtPME3 activity in planta. Significance: The tuning of AtPME3 activity by AtPMEI7 brings insights into the control of homogalacturonan methylesteri-fication in plant cell walls.
Published: 2015
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26. Security-Aware Business Process as a Service by hiding provenance

Author: Salima Benbernou, Mehdi Bentounsi, Mikhail J. Atallah, Laboratoire d'Informatique Paris Descartes (LIPADE - EA 2517), Université Paris Descartes - Paris 5 (UPD5), Department of Computer Science [Purdue], Purdue University [West Lafayette], and CIFRE 1169-2010
Subjects: [INFO.INFO-WB] Computer Science [cs]/Web, Computer science, Business process, Cloud computing, 02 engineering and technology, BPaaS, Computer security, computer.software_genre, Outsourcing, Business process management, Business process discovery, 020204 information systems, 0202 electrical engineering, electronic engineering, information engineering, Process composition, business.industry, Artifact-centric business process model, Security by design, [INFO.INFO-WB]Computer Science [cs]/Web, Business process modeling, Secure by design, Hardware and Architecture, 020201 artificial intelligence & image processing, Process reuse, business, Law, computer, Software
Abstract: We adress in this paper the security issues that arise when outsourcing business processes in the BPaaS (Business Process as a Service). In particular when sharing and reusing process fragments coming from different organizations for faster and easier development of process-based applications (PBA). The goal is twofold, to preserve the process fragment provenance, i.e., the companies's business activities which provide the reused fragments in order to avoid the competition, and to guarantee the end-to-end availability of PBA to fragment's consumers. We formally define the problem, and offer an efficient anonymization-based protocol. Experiments have been conducted to show the effectiveness of the proposed solution. We address the security issues that arise when outsourcing business processes in the cloud as BPaaS (Business Process as a Service).We formally define the concept of sharing and reusing process fragments for faster and easier development of process-based applications.We provide an efficient anonymization-based protocol to preserve the process fragment provenance, and to guarantee the end-to-end availability of process-based applications.We evaluate the performance of the proposed approach on real datasets.
Published: 2015
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27. Modélisation de terrains par primitives

Author: Génevaux, Jean-David, Grosbellet, François, Galin, Eric, Peytavie, Adrien, Guérin, Eric, Briquet, Cyril, Beneš, Bedřich, Modélisation Géométrique, Géométrie Algorithmique, Fractales (GeoMod), Laboratoire d'InfoRmatique en Image et Systèmes d'information (LIRIS), Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École Centrale de Lyon (ECL), Université de Lyon-Université Lumière - Lyon 2 (UL2)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Université Lumière - Lyon 2 (UL2), Synthèse et analyse d'images (XLIM-ASALI), XLIM (XLIM), Université de Limoges (UNILIM)-Centre National de la Recherche Scientifique (CNRS)-Université de Limoges (UNILIM)-Centre National de la Recherche Scientifique (CNRS), Department of Computer Science [Purdue], Purdue University [West Lafayette], and Génevaux, Jean-David
Subjects: [INFO.INFO-GR] Computer Science [cs]/Graphics [cs.GR], natural phenomena, [INFO.INFO-MO] Computer Science [cs]/Modeling and Simulation, procedural modelling, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, terrain modelling, [INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR], implicit surface
Abstract: National audience; Nous proposons un modèle de terrain hiérarchique et compact permettant de représenter des scènes complexes. Ce modèle de représentation s'inspire des surfaces implicites à squelettes et définit une fonction d'élévation sous la forme d'un arbre de construction. Les feuilles sont des primitives décrivant des morceaux de terrains à différentes échelles (montagnes, fleuves, ...) et les noeuds internes sont des opérateurs de combinaison. L'élévation d'un point est calculée en traversant la structure d'arbre et en combinant les contributions de chaque primitive. La définition des feuilles et des opérateurs garantit que la fonction d'élévation résultante est Lipschitzienne, ce qui permet d'accélérer les calculs de visualisation en utilisant un algorithme de sphere tracing. Mots Clés : modélisation de terrains, phénomènes naturels, modélisation procédurale, surface implicite We propose a compact hierarchical procedural model that combines feature-based primitives to create complex continuous terrains. Our model is inspired by skeletal implicit surfaces and defines the terrain elevation by using a construction tree whose leaves are primitives describing terrain fragments, and whose inner nodes include operations that combine its sub-trees. The elevation of a point is evaluated by traversing the tree and by combining the contributions of each primitive. The definition of both leaves and operators guarantees that the resulting elevation function is Lipschitz which enables us to speed up sphere tracing and surface adaptive tesselation algorithms.
Published: 2014

28. Community-wide evaluation of methods for predicting the effect of mutations on protein-protein interactions

Author: Moretti, Rocco, Fleishman, Sarel J, Agius, Rudi, Torchala, Mieczyslaw, Bates, Paul A., Kastritis, Panagiotis L, Rodrigues, João P. G. L. M., Trellet, Mikael, Bonvin, Alexandre M. J. J., Cui, Meng, Rooman, Marianne, Gillis, Dimitri, Dehouck, Yves, Moal, Iain, Romero-Durana, Miguel, Pérez-Cano, Laura, Pallara, Chiara, Jimenez, Brian, Fernández-Recio, Juan, Flores, Samuel C, Pacella, Michael, Praneeth Kilambi, Krishna, Gray, Jeffrey J, Popov, Petr, Grudinin, Sergei, Esquivel-Rodríguez, Juan, Kihara, Daisuke, Zhao, Nan, Korkin, Dmitry, Zhu, Xiaolei, Demerdash, Omar N A, Mitchell, Julie, Kanamori, Eiji, Tsuchiya, Yuko, Nakamura, Haruki, Lee, Hasup, Park, Hahnbeom, Seok, Chaok, Sarmiento, Jamica, Liang, Shide, Teraguchi, Shusuke, Standley, Daron M, Shimoyama, Hiromitsu, Terashi, Genki, Takeda-Shitaka, Mayuko, Iwadate, Mitsuo, Umeyama, Hideaki, Beglov, Dmitri, Hall, David R, Kozakov, Dima, Vajda, Sandor, Pierce, Brian G, Hwang, Howook, Vreven, Thom, Weng, Zhiping, Huang, Yangyu, Li, Haotian, Yang, Xiufeng, Ji, Xiaofeng, Liu, Shiyong, Xiao, Yi, Zacharias, Martin, Qin, Sanbo, Zhou, Huan-Xiang, Huang, Sheng-You, Zou, Xiaoqin, Velankar, Sameer, Janin, Joel, Wodak, Shoshana J, Baker, David, Department of Biochemistry [Washington ], University of Washington [Seattle], Molecular Carcinogenesis [Sutton], Institute of cancer research, Weizmann Institute of Science [Rehovot, Israël], Biomolecular Modelling laboratory [London], Cancer Research UK London Research Institute, Bijvoet Center of Biomolecular Research [Utrecht], Utrecht University [Utrecht], Virginia Commonwealth University (VCU), Département d'Informatique [Bruxelles] (ULB), Faculté des Sciences [Bruxelles] (ULB), Université libre de Bruxelles (ULB)-Université libre de Bruxelles (ULB), Université libre de Bruxelles (ULB), Unite de Bioinformatique genomique et structurale (3BIO-BIO-INFO), Barcelona Supercomputing Center - Centro Nacional de Supercomputacion (BSC - CNS), Department of Cell and Molecular Biology [Uppsala], Uppsala University, Johns Hopkins University (JHU), Algorithms for Modeling and Simulation of Nanosystems (NANO-D), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Jean Kuntzmann (LJK), Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS), Department of Computer Science [Purdue], Purdue University [West Lafayette], University of Missouri [Columbia] (Mizzou), University of Missouri System, Department of Mathematics [Madison], University of Wisconsin-Madison, Japan Biological Informatics Consortium [Tokyo], Ochanomizu University, Osaka University [Osaka], Seoul National University [Seoul] (SNU), Kitasato University, Chuo University (Chuo University), Department of Biomedical Engineering [Boston], Boston University [Boston] (BU), University of Massachusetts Medical School [Worcester] (UMASS), University of Massachusetts System (UMASS), Huazhong University of Science and Technology [Wuhan] (HUST), Technische Universität Munchen - Université Technique de Munich [Munich, Allemagne] (TUM), Florida State University [Tallahassee] (FSU), European Bioinformatics Institute [Hinxton] (EMBL-EBI), EMBL Heidelberg, Institut de biochimie et biophysique moléculaire et cellulaire (IBBMC), Université Paris-Sud - Paris 11 (UP11)-Centre National de la Recherche Scientifique (CNRS), University of Toronto, and The Hospital for sick children [Toronto] (SickKids)
Subjects: binding, deep mutational scanning, Mutation, Protein Interaction Mapping, yeast display, hemagglutinin, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], Databases, Protein, CAPRI, [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], Algorithms, Article, Protein Binding
Abstract: International audience; Community-wide blind prediction experiments such as CAPRI and CASP provide an objective measure of the current state of predictive methodology. Here we describe a community-wide assessment of methods to predict the effects of mutations on protein-protein interactions. Twenty-two groups predicted the effects of comprehensive saturation mutagenesis for two designed influenza hemagglutinin binders and the results were compared with experimental yeast display enrichment data obtained using deep sequencing. The most successful methods explicitly considered the effects of mutation on monomer stability in addition to binding affinity, carried out explicit side-chain sampling and backbone relaxation, evaluated packing, electrostatic, and solvation effects, and correctly identified around a third of the beneficial mutations. Much room for improvement remains for even the best techniques, and large-scale fitness landscapes should continue to provide an excellent test bed for continued evaluation of both existing and new prediction methodologies.
Published: 2013
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29. Classification of Markov Sources Through Joint String Complexity: Theory and Experiments

Author: Dimitris Milioris, Wojciech Szpankowski, Philippe Jacquet, Alcatel-Lucent Bell Labs France [Nozay], Alcatel-Lucent Bell Labs France, High performance communication (HIPERCOM), Inria Paris-Rocquencourt, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université Paris-Sud - Paris 11 (UP11)-Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-École polytechnique (X)-Centre National de la Recherche Scientifique (CNRS), Laboratory of Information, Network and Communication Sciences (LINCS), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut Mines-Télécom [Paris] (IMT), École polytechnique (X), Department of Computer Science [Purdue], and Purdue University [West Lafayette]
Subjects: Discrete mathematics, Average-case complexity, TheoryofComputation_MISCELLANEOUS, String (computer science), 020206 networking & telecommunications, 0102 computer and information sciences, 02 engineering and technology, Descriptive complexity theory, 01 natural sciences, symbols.namesake, High Energy Physics::Theory, 010201 computation theory & mathematics, Markov algorithm, 0202 electrical engineering, electronic engineering, information engineering, symbols, Worst-case complexity, Communication complexity, Time complexity, Algorithm, Quantum complexity theory, Mathematics
Abstract: International audience; We propose a classification test to discriminate Markov sources based on the joint string complexity. String complexity is defined as the cardinality of a set of all distinct words (factors) of a given string. For two strings, we define the joint string complexity as the cardinality of the set of words which both strings have in common. In this paper we analyze the average joint complexity when both strings are generated by two Markov sources. We provide fast converging asymptotic expansions and present some experimental results showing usefulness of the joint complexity to text discrimination.
Published: 2013

30. Joint String Complexity for Markov Sources

Author: Wojciech Szpankowski, Philippe Jacquet, Alcatel-Lucent Bell Labs France [Nozay], Alcatel-Lucent Bell Labs France, Department of Computer Science [Purdue], Purdue University [West Lafayette], Broutin, Nicolas and Devroye, and Luc
Subjects: String complexity, General Computer Science, Singularity analysis, media_common.quotation_subject, [INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS], [INFO.INFO-DS] Computer Science [cs]/Data Structures and Algorithms [cs.DS], [INFO.INFO-DM]Computer Science [cs]/Discrete Mathematics [cs.DM], [INFO.INFO-CG]Computer Science [cs]/Computational Geometry [cs.CG], String (physics), semi-complexity, Theoretical Computer Science, Set (abstract data type), Combinatorics, High Energy Physics::Theory, Cardinality, Saddle point, [MATH.MATH-CO]Mathematics [math]/Combinatorics [math.CO], saddle point method, Discrete Mathematics and Combinatorics, double depoissonization, Mathematics, media_common, Markov chain, Infinity, [MATH.MATH-CO] Mathematics [math]/Combinatorics [math.CO], double Mellin transform, [INFO.INFO-DM] Computer Science [cs]/Discrete Mathematics [cs.DM], [INFO.INFO-CG] Computer Science [cs]/Computational Geometry [cs.CG], Joint (audio engineering)
Abstract: String complexity is defined as the cardinality of a set of all distinct words (factors) of a given string. For two strings, we define $\textit{joint string complexity}$ as the set of words that are common to both strings. We also relax this definition and introduce $\textit{joint semi-complexity}$ restricted to the common words appearing at least twice in both strings. String complexity finds a number of applications from capturing the richness of a language to finding similarities between two genome sequences. In this paper we analyze joint complexity and joint semi-complexity when both strings are generated by a Markov source. The problem turns out to be quite challenging requiring subtle singularity analysis and saddle point method over infinity many saddle points leading to novel oscillatory phenomena with single and double periodicities.
Published: 2012
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31. A New Binomial Recurrence Arising in a Graphical Compression Algorithm

Author: Wojciech Szpankowski, Charles Knessl, Yongwook Choi, J. Craig Venter Institute, Department of Mathematics, Statistics and Computer Science [Chicago] (UIC), University of Illinois [Chicago] (UIC), University of Illinois System-University of Illinois System, Department of Computer Science [Purdue], Purdue University [West Lafayette], Broutin, Nicolas and Devroye, and Luc
Subjects: General Computer Science, Binomial (polynomial), [INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS], [INFO.INFO-DS] Computer Science [cs]/Data Structures and Algorithms [cs.DS], [INFO.INFO-DM]Computer Science [cs]/Discrete Mathematics [cs.DM], [INFO.INFO-CG]Computer Science [cs]/Computational Geometry [cs.CG], Theoretical Computer Science, Combinatorics, Integer, Algorithmics, Trie, [MATH.MATH-CO]Mathematics [math]/Combinatorics [math.CO], Discrete Mathematics and Combinatorics, graph compression, poissonization, Mellin transform, Mathematics, Discrete mathematics, 16. Peace & justice, [MATH.MATH-CO] Mathematics [math]/Combinatorics [math.CO], Digital trees, Tree (data structure), [INFO.INFO-DM] Computer Science [cs]/Discrete Mathematics [cs.DM], [INFO.INFO-CG] Computer Science [cs]/Computational Geometry [cs.CG], Ball (bearing), Node (circuits)
Abstract: In a recently proposed graphical compression algorithm by Choi and Szpankowski (2009), the following tree arose in the course of the analysis. The root contains n balls that are consequently distributed between two subtrees according to a simple rule: In each step, all balls independently move down to the left subtree (say with probability $p$) or the right subtree (with probability 1-$p$). A new node is created as long as there is at least one ball in that node. Furthermore, a nonnegative integer $d$ is given, and at level $d$ or greater one ball is removed from the leftmost node before the balls move down to the next level. These steps are repeated until all balls are removed (i.e., after $n+d$ steps). Observe that when $d=∞$ the above tree can be modeled as a $\textit{trie}$ that stores $n$ independent sequences generated by a memoryless source with parameter $p$. Therefore, we coin the name $(n,d)$-tries for the tree just described, and to which we often refer simply as $d$-tries. Parameters of such a tree (e.g., path length, depth, size) are described by an interesting two-dimensional recurrence (in terms of $n$ and $d$) that – to the best of our knowledge – was not analyzed before. We study it, and show how much parameters of such a $(n,d)$-trie differ from the corresponding parameters of regular tries. We use methods of analytic algorithmics, from Mellin transforms to analytic poissonization.
Published: 2012

32. Counting Markov Types

Author: Jacquet, Philippe, Knessl, Charles, Szpankowski, Wojciech, High performance communication (HIPERCOM), Inria Paris-Rocquencourt, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université Paris-Sud - Paris 11 (UP11)-Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-École polytechnique (X)-Centre National de la Recherche Scientifique (CNRS), Department of Mathematics, Statistics and Computer Science [Chicago] (UIC), University of Illinois [Chicago] (UIC), University of Illinois System-University of Illinois System, Department of Computer Science [Purdue], Purdue University [West Lafayette], Drmota, Michael and Gittenberger, and Bernhard
Subjects: General Computer Science, [INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS], [INFO.INFO-DS] Computer Science [cs]/Data Structures and Algorithms [cs.DS], [INFO.INFO-DM]Computer Science [cs]/Discrete Mathematics [cs.DM], [INFO.INFO-CG]Computer Science [cs]/Computational Geometry [cs.CG], Theoretical Computer Science, [MATH.MATH-CO] Mathematics [math]/Combinatorics [math.CO], [INFO.INFO-DM] Computer Science [cs]/Discrete Mathematics [cs.DM], [INFO.INFO-CG] Computer Science [cs]/Computational Geometry [cs.CG], [MATH.MATH-CO]Mathematics [math]/Combinatorics [math.CO], saddle point method, linear diophantine equations, Discrete Mathematics and Combinatorics, Markov types, integer matrices, multidimensional generating functions
Abstract: The method of types is one of the most popular techniques in information theory and combinatorics. Two sequences of equal length have the same type if they have identical empirical distributions. In this paper, we focus on Markov types, that is, sequences generated by a Markov source (of order one). We note that sequences having the same Markov type share the same so called $\textit{balanced frequency matrix}$ that counts the number of distinct pairs of symbols. We enumerate the number of Markov types for sequences of length $n$ over an alphabet of size $m$. This turns out to coincide with the number of the balanced frequency matrices as well as with the number of special $\textit{linear diophantine equations}$, and also balanced directed multigraphs. For fixed $m$ we prove that the number of Markov types is asymptotically equal to $d(m) \frac{n^{m^{2-m}}}{(m^2-m)!}$, where $d(m)$ is a constant for which we give an integral representation. For $m \to \infty$ we conclude that asymptotically the number of types is equivalent to $\frac{\sqrt{2}m^{3m/2} e^{m^2}}{m^{2m^2} 2^m \pi^{m/2}} n^{m^2-m}$ provided that $m=o(n^{1/4})$ (however, our techniques work for $m=o(\sqrt{n})$). These findings are derived by analytical techniques ranging from multidimensional generating functions to the saddle point method.
Published: 2010
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33. On the Ehrenfeucht-Mycielski Balance Conjecture

Author: John C. Kieffer, Wojciech Szpankowski, Department of Electrical and Computer Engineering [Minneapolis] (ECE), University of Minnesota [Twin Cities] (UMN), University of Minnesota System-University of Minnesota System, Department of Computer Science [Purdue], Purdue University [West Lafayette], and Jacquet, Philippe
Subjects: Balance (metaphysics), Sequence, Conjecture, General Computer Science, [INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS], [INFO.INFO-DS] Computer Science [cs]/Data Structures and Algorithms [cs.DS], 0102 computer and information sciences, [INFO.INFO-DM]Computer Science [cs]/Discrete Mathematics [cs.DM], [INFO.INFO-CG]Computer Science [cs]/Computational Geometry [cs.CG], 01 natural sciences, Pseudorandom binary sequence, Substring, Theoretical Computer Science, Combinatorics, [MATH.MATH-CO] Mathematics [math]/Combinatorics [math.CO], [INFO.INFO-DM] Computer Science [cs]/Discrete Mathematics [cs.DM], [INFO.INFO-CG] Computer Science [cs]/Computational Geometry [cs.CG], 010201 computation theory & mathematics, Limit point, [MATH.MATH-CO]Mathematics [math]/Combinatorics [math.CO], Ehrenfeucht-Mycielski sequence, Discrete Mathematics and Combinatorics, Interval (graph theory), Tree (set theory), Mathematics
Abstract: In 1992, A. Ehrenfeucht and J. Mycielski defined a seemingly pseudorandom binary sequence which has since been termed the EM-sequence. The balance conjecture for the EM-sequence, still open, is the conjecture that the sequence of EM-sequence initial segment averages converges to $1/2$. In this paper, we do not prove the balance conjecture but we do make some progress concerning it, namely, we prove that every limit point of the aforementioned sequence of averages lies in the interval $[1/4,3/4]$, improving the best previous result that every such limit point belongs to the interval $[0.11,0.89]$. Our approach is novel and exploits an analysis of the growth behavior as $n \to \infty$ of the rooted tree formed by the binary strings appearing at least twice as substrings of the length $n$ initial segment of the EM-sequence.
Published: 2007

34. On the Exit Time of a Random Walk with Positive Drift

Author: Wojciech Szpankowski, Michael Drmota, Institut für Geometrie, Vienna University of Technology (TU Wien), Department of Computer Science [Purdue], Purdue University [West Lafayette], and Jacquet, Philippe
Subjects: General Computer Science, [INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS], Random walk in the plane, Asymptotic distribution, [INFO.INFO-DS] Computer Science [cs]/Data Structures and Algorithms [cs.DS], 0102 computer and information sciences, 02 engineering and technology, [INFO.INFO-DM]Computer Science [cs]/Discrete Mathematics [cs.DM], [INFO.INFO-CG]Computer Science [cs]/Computational Geometry [cs.CG], 01 natural sciences, Theoretical Computer Science, Quadrant (plane geometry), Combinatorics, Saddle point, [MATH.MATH-CO]Mathematics [math]/Combinatorics [math.CO], 0202 electrical engineering, electronic engineering, information engineering, Discrete Mathematics and Combinatorics, Khodak code, number of paths, Mellin transform, Mathematics, Infinite number, Random walk, Abelian and tauberian theorems, [MATH.MATH-CO] Mathematics [math]/Combinatorics [math.CO], [INFO.INFO-DM] Computer Science [cs]/Discrete Mathematics [cs.DM], Tauberian theorems, [INFO.INFO-CG] Computer Science [cs]/Computational Geometry [cs.CG], 010201 computation theory & mathematics, Bounded function, 020201 artificial intelligence & image processing, exit time, Tunstall's code
Abstract: We study a random walk with positive drift in the first quadrant of the plane. For a given connected region $\mathcal{C}$ of the first quadrant, we analyze the number of paths contained in $\mathcal{C}$ and the first exit time from $\mathcal{C}$. In our case, region $\mathcal{C}$ is bounded by two crossing lines. It is noted that such a walk is equivalent to a path in a tree from the root to a leaf not exceeding a given height. If this tree is the parsing tree of the Tunstall or Khodak variable-to-fixed code, then the exit time of the underlying random walk corresponds to the phrase length not exceeding a given length. We derive precise asymptotics of the number of paths and the asymptotic distribution of the exit time. Even for such a simple walk, the analysis turns out to be quite sophisticated and it involves Mellin transforms, Tauberian theorems, and infinite number of saddle points.
Published: 2007

35. The 'Art' of Programming Gossip-based Systems

Author: Pascal Felber, Patrick Eugster, Fabrice Le Fessant, Department of Computer Science [Purdue], Purdue University [West Lafayette], Institut d'Informatique [Neuchâtel] (IIUN), Université de Neuchâtel (UNINE), As Scalable As Possible: foundations of large scale dynamic distributed systems (ASAP), Université de Rennes (UR)-Inria Saclay - Ile de France, and Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)
Subjects: Theoretical computer science, Computer science, Interface (Java), business.industry, ComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKS, Probabilistic logic, Intrinsics, Gossip, Programming paradigm, General Earth and Planetary Sciences, Gossip protocol, Imperfect, Artificial intelligence, [INFO.INFO-DC]Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], Completeness (statistics), business, General Environmental Science
Abstract: International audience; How does one best go about building actual gossip-based protocols? Trying to answer this question has brought us to address two preliminary questions, namely (1) what the in- trinsics of such systems or protocols are, and (2) what kind of applications would in the end be built on top of such protocols. We address the first question by arguing that gossip-based protocols are all built following one and the same pattern, and describing three building blocks which we claim are used to support this recurrent pattern—most notably a source of randomness. We validate these claims by devising simplified versions of well-known protocols, in a layered fashion, on top of a conceptual interface describing these basic services. The second question is addressed by ar- guing that gossip-based protocols exhibit some probabilistic or imperfect flavor (e.g., probabilistic or partial completion), and by proposing to take such probabilistic behavior into ac- count when devising interfaces for applications building on top of gossip-based protocols. We argue for inherent support for these probabilities in the programming model.
Published: 2007

36. Multicast tree structure and the power law

Author: Leonidas Georgiadis, Cedric Adjih, Philippe Jacquet, Wojciech Szpankowski, High performance communication (HIPERCOM), Inria Paris-Rocquencourt, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université Paris-Sud - Paris 11 (UP11)-Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-École polytechnique (X)-Centre National de la Recherche Scientifique (CNRS), Department of Electrical & Computer Engineering [Thessaloniki], Aristotle University of Thessaloniki, Laboratoire de Physique Corpusculaire - Clermont-Ferrand (LPC), Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), Department of Computer Science [Purdue], and Purdue University [West Lafayette]
Subjects: Discrete mathematics, Spanning tree, Theoretical computer science, Degree (graph theory), Multicast, ComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKS, 020206 networking & telecommunications, 0102 computer and information sciences, 02 engineering and technology, Data_CODINGANDINFORMATIONTHEORY, Library and Information Sciences, Network topology, 01 natural sciences, Computer Science Applications, Tree (data structure), [INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI], Tree structure, 010201 computation theory & mathematics, Reachability, Metric (mathematics), Computer Science::Networking and Internet Architecture, 0202 electrical engineering, electronic engineering, information engineering, Computer Science::Information Theory, Information Systems, Mathematics
Abstract: In this paper, we investigate structural properties of multicast trees that give rise to the so-called multicast power law. The law asserts that the ratio R(n) of the average number of links in a multicast tree connecting the source to n destinations to the average number of links in a unicast path, satisfies asymptotically R(n)/spl ap/cn/sup /spl phi//, 0
Published: 2006
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37. Philippe flajolet, the father of analytic combinatorics

Author: Wojciech Szpankowski, Brigitte Vallée, Bruno Salvy, Michèle Soria, Bob Sedgewick, Algorithms (ALGORITHMS), Inria Paris-Rocquencourt, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Computer Science Department [Princeton], Princeton University, Algorithmes, Programmes et Résolution (APR), Laboratoire d'Informatique de Paris 6 (LIP6), Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS), Department of Computer Science [Purdue], Purdue University [West Lafayette], Equipe AMACC - Laboratoire GREYC - UMR6072, Groupe de Recherche en Informatique, Image et Instrumentation de Caen (GREYC), Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Ingénieurs de Caen (ENSICAEN), Normandie Université (NU)-Normandie Université (NU)-Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Ingénieurs de Caen (ENSICAEN), Normandie Université (NU), Bousquet-Mélou, Mireille, Wachs, Michelle, Hultman, Axel, Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU)-École Nationale Supérieure d'Ingénieurs de Caen (ENSICAEN), Normandie Université (NU)-Centre National de la Recherche Scientifique (CNRS)-Université de Caen Normandie (UNICAEN), and Normandie Université (NU)-Centre National de la Recherche Scientifique (CNRS)
Subjects: General Computer Science, media_common.quotation_subject, 02 engineering and technology, [MATH] Mathematics [math], 0102 computer and information sciences, [INFO] Computer Science [cs], 01 natural sciences, Prime (order theory), Theoretical Computer Science, Combinatorics, Mathematics (miscellaneous), 0202 electrical engineering, electronic engineering, information engineering, Discrete Mathematics and Combinatorics, [INFO]Computer Science [cs], [MATH]Mathematics [math], media_common, Mathematics, Taste (sociology), obituary, General Medicine, Obituary, Epistemology, Algebra, 010201 computation theory & mathematics, Curiosity, Analytic combinatorics, 020201 artificial intelligence & image processing, Algorithm, Philippe Flajolet, Computer Science(all)
Abstract: Philippe Flajolet, mathematician and computer scientist extraordinaire, suddenly passed away on March 22, 2011, at the prime of his career. He is celebrated for opening new lines of research in analysis of algo- rithms, developing powerful new methods, and solving difficult open problems. His research contributions will have impact for generations, and his approach to research, based on curiosity, a discriminating taste, broad knowledge and interest, intellectual integrity, and a genuine sense of camaraderie, will serve as an inspiration to those who knew him for years to come
Published: 2011
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38. Fast parallel Lyndon factorization and applications

Author: Apostolico, Alberto, Crochemore, Maxime, Crochemore, Maxime, Department of Computer Science [Purdue], Purdue University [West Lafayette], Dipartimento di Ingegneria e Scienze dell'Informazione e Matematica [L'Aquila] (DISIM), Università degli Studi dell'Aquila (UNIVAQ), Laboratoire d'Informatique Gaspard-Monge (LIGM), Centre National de la Recherche Scientifique (CNRS)-Fédération de Recherche Bézout-ESIEE Paris-École des Ponts ParisTech (ENPC)-Université Paris-Est Marne-la-Vallée (UPEM), Department of Information Engineering, Computer Science and Mathematics = Dipartimento di Ingegneria e Scienze dell'Informazione e Matematica [L'Aquila] (DISIM), Università degli Studi dell'Aquila = University of L'Aquila (UNIVAQ), and Université Paris-Est Marne-la-Vallée (UPEM)-École des Ponts ParisTech (ENPC)-ESIEE Paris-Fédération de Recherche Bézout-Centre National de la Recherche Scientifique (CNRS)
Subjects: string matching, [INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS], [INFO.INFO-DS] Computer Science [cs]/Data Structures and Algorithms [cs.DS], combinatorics on words, Lyndon words, parallel computation
Abstract: International audience; It is shown that the Lyndon decomposition of a word of n symbols can be computed by an n-processors CRCW PRAM in O(log n) time. Extensions of the basic algorithm convey, within the same time and processors bounds, efficient parallel solutions to problems such as finding the lexicographically minimum or maximum suffix for all prefixes of the input string, and finding the lexicographically least rotation of all prefixes of the input.
Published: 1995

39. On the multisearching problem for hypercubes

Author: Mikhail J. Atallah, Andreas Fabri, Department of Computer Science [Purdue], Purdue University [West Lafayette], Geometry, Algorithms and Robotics (PRISME), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Ce travail a été partiellement soutenu par National Science Foundation et Esprit Research Basic Action N°7141 (ALCOM II), and INRIA
Subjects: Control and Optimization, Parallel algorithms, Computer science, Trapezoidal decomposition, [INFO.INFO-OH]Computer Science [cs]/Other [cs.OH], Parallel algorithm, Multisearch, 0102 computer and information sciences, 02 engineering and technology, 01 natural sciences, Combinatorics, Set (abstract data type), Computer Science::Hardware Architecture, Multisearching, 0202 electrical engineering, electronic engineering, information engineering, Point location, Time complexity, Mathematics, Discrete mathematics, Sequence, Computer Sciences, Sorting, ComputerSystemsOrganization_PROCESSORARCHITECTURES, Binary logarithm, Computational geometry, Search tree, Computer Science Applications, 020202 computer hardware & architecture, Hypercube, Computational Mathematics, Computational Theory and Mathematics, 010201 computation theory & mathematics, 020201 artificial intelligence & image processing, Geometry and Topology, Constant (mathematics)
Abstract: We build on the work of Dehne and Rau-Chaplin and give improved bounds for the multisearch problem on a hypercube. This is a parallel search problem where the elements in the structure S to be searched are totally ordered, but where it is not possible to compare in constant time any two given queries q and q'. This problem is fundamental in computational geometry, for example it models planar point location in a slab. More precisely, we are given on a n-processor hypercube a sorted n-element sequence S and a set Q of n queries and we need to find for each query q [??]Q its location in the sorted S. Note that one cannot solve this problem by sorting S[??] Q, because every comparison- based parallel sorting algorithm needs to compare a pair q, q' [??]Q in constant time. We present an improved algorithm for the multisearch problem, one that takes 0(log n(log log n)3) time on a n-processor hypercube. This essentially replaces a logarithmic factor in the time complexities of previous schemes by a (log log n)3 factor. The hypercube model for which we claim our bounds is the standard one, with 0(1) memory registers per processor, and with one-port communication. Each register can store 0(log n) bits, so that a processor knows its ID.
Published: 1994
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40. Co-Design and Verification of an Available File System

Author: Patrick Eugster, Marc Shapiro, Mahsa Najafzadeh, Department of Computer Science [Purdue], Purdue University [West Lafayette], DistributEd aLgorithms and sYStems (DELYS), Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-LIP6, Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Isil Dillig, and Jens Palsberg
Subjects: File system, Structure (mathematical logic), Computer science, Semantics (computer science), Concurrency, Strong consistency, 0102 computer and information sciences, 02 engineering and technology, computer.software_genre, 01 natural sciences, 010201 computation theory & mathematics, POSIX, 0202 electrical engineering, electronic engineering, information engineering, Operating system, 020201 artificial intelligence & image processing, [INFO]Computer Science [cs], Sequential model, Distributed File System, computer
Abstract: International audience; Distributed file systems play a vital role in large-scale enterprise services. However, the designer of a distributed file system faces a vexing choice between strong consistency and asynchronous replica-tion. The former supports a standard sequential model by synchronising operations, but is slow and fragile. The latter is highly available and responsive, but exposes users to concurrency anomalies. In this paper, we describe a rigorous and general approach to navigating this trade-off by leveraging static verification tools that allow to verify different file system designs. We show that common file system operations can run concurrently without synchronisation, while still retaining a semantics reasonably similar to Posix hierarchical structure. The one exception is the move operation, for which we prove that, unless synchronised, it will have an anomalous behaviour.
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41. NuFold: end-to-end approach for RNA tertiary structure prediction with flexible nucleobase center representation.

Author: Kagaya Y, Zhang Z, Ibtehaz N, Wang X, Nakamura T, Punuru PD, and Kihara D
Subjects: Deep Learning, Computational Biology methods, Neural Networks, Computer, Sequence Alignment methods, Software, Nucleic Acid Conformation, RNA chemistry, RNA genetics
Abstract: RNA plays a crucial role not only in information transfer as messenger RNA during gene expression but also in various biological functions as non-coding RNAs. Understanding mechanical mechanisms of function needs tertiary structure information; however, experimental determination of three-dimensional RNA structures is costly and time-consuming, leading to a substantial gap between RNA sequence and structural data. To address this challenge, we developed NuFold, a novel computational approach that leverages state-of-the-art deep learning architecture to accurately predict RNA tertiary structures. NuFold is a deep neural network trained end-to-end for the output structure from the input sequence. NuFold incorporates a nucleobase center representation, which enables flexible conformation of ribose rings. Benchmark study showed that NuFold clearly outperformed energy-based methods and demonstrated comparable results with existing state-of-the-art deep-learning-based methods. NuFold exhibited a particular advantage in building correct local geometries of RNA. Analyses of individual components in the NuFold pipeline indicated that the performance improved by utilizing metagenome sequences for multiple sequence alignment and increasing the number of recycling. NuFold is also capable of predicting multimer complex structures of RNA by linking the input sequences., Competing Interests: Competing interests: The authors declare no competing interests., (© 2025. The Author(s).)
Published: 2025
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42. Developing a Machine Learning-Based Automated Patient Engagement Estimator for Telehealth: Algorithm Development and Validation Study.

Author: Guhan P, Awasthi N, McDonald K, Bussell K, Reeves G, Manocha D, and Bera A
Subjects: Humans, Adult, Female, Male, Telemedicine, Machine Learning, Algorithms, Patient Participation methods, Patient Participation psychology
Abstract: Background: Patient engagement is a critical but challenging public health priority in behavioral health care. During telehealth sessions, health care providers need to rely predominantly on verbal strategies rather than typical nonverbal cues to effectively engage patients. Hence, the typical patient engagement behaviors are now different, and health care provider training on telehealth patient engagement is unavailable or quite limited. Therefore, we explore the application of machine learning for estimating patient engagement. This can assist psychotherapists in the development of a therapeutic relationship with the patient and enhance patient engagement in the treatment of mental health conditions during tele-mental health sessions., Objective: This study aimed to examine the ability of machine learning models to estimate patient engagement levels during a tele-mental health session and understand whether the machine learning approach could support therapeutic engagement between the client and psychotherapist., Methods: We proposed a multimodal learning-based approach. We uniquely leveraged latent vectors corresponding to affective and cognitive features frequently used in psychology literature to understand a person's level of engagement. Given the labeled data constraints that exist in health care, we explored a semisupervised learning solution. To support the development of similar technologies for telehealth, we also plan to release a dataset called Multimodal Engagement Detection in Clinical Analysis (MEDICA). This dataset includes 1229 video clips, each lasting 3 seconds. In addition, we present experiments conducted on this dataset, along with real-world tests that demonstrate the effectiveness of our method., Results: Our algorithm reports a 40% improvement in root mean square error over state-of-the-art methods for engagement estimation. In our real-world tests on 438 video clips from psychotherapy sessions with 20 patients, in comparison to prior methods, positive correlations were observed between psychotherapists' Working Alliance Inventory scores and our mean and median engagement level estimates. This indicates the potential of the proposed model to present patient engagement estimations that align well with the engagement measures used by psychotherapists., Conclusions: Patient engagement has been identified as being important to improve therapeutic alliance. However, limited research has been conducted to measure this in a telehealth setting, where the therapist lacks conventional cues to make a confident assessment. The algorithm developed is an attempt to model person-oriented engagement modeling theories within machine learning frameworks to estimate the level of engagement of the patient accurately and reliably in telehealth. The results are encouraging and emphasize the value of combining psychology and machine learning to understand patient engagement. Further testing in the real-world setting is necessary to fully assess its usefulness in helping therapists gauge patient engagement during online sessions. However, the proposed approach and the creation of the new dataset, MEDICA, open avenues for future research and the development of impactful tools for telehealth., (©Pooja Guhan, Naman Awasthi, Kathryn McDonald, Kristin Bussell, Gloria Reeves, Dinesh Manocha, Aniket Bera. Originally published in JMIR Formative Research (https://formative.jmir.org), 20.01.2025.)
Published: 2025
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43. Quantum quench dynamics of geometrically frustrated Ising models.

Author: Ali A, Xu H, Bernoudy W, Nocera A, King AD, and Banerjee A
Abstract: Geometric frustration in two-dimensional Ising models allows for a wealth of exotic universal behavior, both Ising and non-Ising, in the presence of quantum fluctuations. In particular, the triangular antiferromagnet and Villain model in a transverse field can be understood through distinct XY pseudospins, but have qualitatively similar phase diagrams including a quantum phase transition in the (2+1)-dimensional XY universality class. While the quantum dynamics of modestly-sized systems can be simulated classically using tensor-based methods, these methods become infeasible for larger lattices. Here we perform both classical and quantum simulations of these dynamics, where our quantum simulator is a superconducting quantum annealer. Our observations on the triangular lattice suggest that the dominant quench dynamics are not described by the quantum Kibble-Zurek scaling of the quantum phase transition, but rather a faster coarsening dynamics in an effective two-dimensional XY model in the ordered phase. Similarly, on the Villain model, the scaling exponent does not match the Kibble-Zurek expectation. These results demonstrate the ability of quantum annealers to perform coherent quantum dynamics simulations that are hard to classically scale beyond small systems, and open the avenue to predictive simulations of the dynamics of Ising magnetic materials on quantum simulators., Competing Interests: Competing interests: W.B. and A.D.K. are employees and stockholders of D-Wave Quantum Inc. and declare a competing interest on that basis. The remaining authors declare no competing interests., (© 2024. The Author(s).)
Published: 2024
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44. A generalizable Hi-C foundation model for chromatin architecture, single-cell and multi-omics analysis across species.

Author: Wang X, Zhang Y, Ray S, Jha A, Fang T, Hang S, Doulatov S, Noble WS, and Wang S
Abstract: Nuclear DNA is organized into a compact three-dimensional (3D) structure that impacts critical cellular processes. High-throughput chromosome conformation capture (Hi-C) is the most widely used method for measuring 3D genome architecture, while linear epigenomic assays, such as ATAC-seq, DNase-seq, and ChIP-seq, are extensively employed to characterize epigenomic regulation. However, the integrative analysis of chromatin interactions and associated epigenomic regulation remains challenging due to the pairwise nature of Hi-C data, mismatched resolution between Hi-C and epigenomic assays, and inconsistencies among analysis tools. Here we propose HiCFoundation, a Hi-C-based foundation model for integrative analysis linking chromatin structure to downstream regulatory function. HiCFoundation is trained from hundreds of Hi-C assays encompassing 118 million contact matrix submatrices. The model achieves state-of-the-art performance on multiple types of 3D genome analysis, including reproducibility analysis, resolution enhancement, and loop detection. We further demonstrate the model's generalizability through genome architecture analysis of 316 species. Notably, by enhancing low-coverage experimental Hi-C data, HiCFoundation reveals genome-wide loop loss during differentiation of hematopoietic stem and progenitor cells (HSPCs) to neutrophils. Additionally, HiCFoundation is able to predict multiple types of epigenomic activity from Hi-C input and further interprets the link between Hi-C input and epigenomic output to reveal the relationship between chromatin conformation and genome function. Finally, HiCFoundation can analyze single-cell Hi-C data, shedding light on genome structure at single-cell resolution. HiCFoundation thus provides a unified, efficient, generalizable, and interpretable foundation for genome architecture, single-cell and multi-omics analysis across species, paving the path for systematically studying genome 3D architecture and its regulatory mechanisms., Competing Interests: Competing Interests Statement Authors declare that they have no competing interests.
Published: 2024
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45. Evaluating the performance of herd-specific long short-term memory models to identify automated health alerts associated with a ketosis diagnosis in early-lactation cows.

Author: Taechachokevivat N, Kou B, Zhang T, Montes ME, Boerman JP, Doucette JS, and Neves RC
Subjects: Cattle, Animals, Female, Algorithms, Dairying methods, Machine Learning, Ketosis veterinary, Ketosis diagnosis, Cattle Diseases diagnosis, Lactation, Milk chemistry
Abstract: The growing use of automated systems in the dairy industry generates a vast amount of cow-level data daily, creating opportunities for using these data to support real-time decision-making. Currently, various commercial systems offer built-in alert algorithms to identify cows requiring attention. To our knowledge, no work has been done to compare the use of models accounting for herd-level variability on their predictive ability against automated systems. Long short-term memory (LSTM) models are machine learning models capable of learning temporal patterns and making predictions based on time series data. The objective of our study was to evaluate the ability of LSTM models to identify a health alert associated with a ketosis diagnosis (HAK) using deviations of daily milk yield, milk fat-to-protein ratio (FPR), number of successful milkings, rumination time, and activity index from the herd median by parity and DIM, considering various time series lengths and numbers of days before HAK. Additionally, we aimed to use Explainable Artificial Intelligence method to understand the relationships between input variables and model outputs. Data on daily milk yield, milk FPR, number of successful milkings, rumination time, activity, and health events during 0 to 21 DIM were retrospectively obtained from a commercial Holstein dairy farm in northern Indiana from February 2020 to January 2023. A total of 1,743 cows were included in the analysis (non-HAK = 1,550; HAK = 193). Variables were transformed based on deviations from the herd median by parity and DIM. Six LSTM models were developed to identify HAK 1, 2, and 3 d before farm diagnosis using historic cow-level data with varying time series lengths. Model performance was assessed using repeated stratified 10-fold cross-validation for 20 repeats. The Shapley additive explanations framework (SHAP) was used for model explanation. Model accuracy was 83%, 74%, and 70%; balanced error rate was 17% to 18%, 26% to 28%, and 34%; sensitivity was 81% to 83%, 71% to 74%, and 62%; specificity was 83%, 74%, and 71%; positive predictive value was 38%, 25% to 27%, and 21%; negative predictive value was 97% to 98%, 95% to 96%, and 94%; and area under the curve was 0.89 to 0.90, 0.80 to 0.81, and 0.72 for models identifying HAK 1, 2, and 3 d before diagnosis, respectively. Performance declined as the time interval between identification and farm diagnosis increased, and extending the time series length did not improve model performance. Model explanation revealed that cows with lower milk yield, number of successful milkings, rumination time, and activity, and higher milk FPR compared with herdmates of the same parity and DIM were more likely to be classified as HAK. Our results demonstrate the potential of LSTM models in identifying HAK using deviations of daily milk production variables, rumination time, and activity index from the herd median by parity and DIM. Future studies are needed to evaluate the performance of health alerts using LSTM models controlling for herd-specific metrics against commercial built-in algorithms in multiple farms and for other disorders., (© 2024, The Authors. Published by Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)
Published: 2024
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46. Twenty years of advances in prediction of nucleic acid-binding residues in protein sequences.

Author: Basu S, Yu J, Kihara D, and Kurgan L
Subjects: RNA chemistry, RNA metabolism, RNA genetics, DNA chemistry, DNA metabolism, DNA genetics, Binding Sites, Sequence Analysis, Protein methods, RNA-Binding Proteins metabolism, RNA-Binding Proteins chemistry, RNA-Binding Proteins genetics, Proteins chemistry, Proteins metabolism, Proteins genetics, Nucleic Acids chemistry, Nucleic Acids metabolism, DNA-Binding Proteins chemistry, DNA-Binding Proteins metabolism, DNA-Binding Proteins genetics, Protein Binding, Databases, Protein, Amino Acid Sequence, Computational Biology methods
Abstract: Computational prediction of nucleic acid-binding residues in protein sequences is an active field of research, with over 80 methods that were released in the past 2 decades. We identify and discuss 87 sequence-based predictors that include dozens of recently published methods that are surveyed for the first time. We overview historical progress and examine multiple practical issues that include availability and impact of predictors, key features of their predictive models, and important aspects related to their training and assessment. We observe that the past decade has brought increased use of deep neural networks and protein language models, which contributed to substantial gains in the predictive performance. We also highlight advancements in vital and challenging issues that include cross-predictions between deoxyribonucleic acid (DNA)-binding and ribonucleic acid (RNA)-binding residues and targeting the two distinct sources of binding annotations, structure-based versus intrinsic disorder-based. The methods trained on the structure-annotated interactions tend to perform poorly on the disorder-annotated binding and vice versa, with only a few methods that target and perform well across both annotation types. The cross-predictions are a significant problem, with some predictors of DNA-binding or RNA-binding residues indiscriminately predicting interactions with both nucleic acid types. Moreover, we show that methods with web servers are cited substantially more than tools without implementation or with no longer working implementations, motivating the development and long-term maintenance of the web servers. We close by discussing future research directions that aim to drive further progress in this area., (© The Author(s) 2025. Published by Oxford University Press.)
Published: 2024
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47. Inflammation impacts androgen receptor signaling in basal prostate stem cells through interleukin 1 receptor antagonist.

Author: Cooper PO, Yang J, Wang HH, Broman MM, Jayasundara SM, Sahoo SS, Yan B, Awdalkreem GD, Cresswell GM, Wang L, Goossens E, Lanman NA, Doerge RW, Zheng F, Cheng L, Alqahtani S, Crist SA, Braun RE, Kazemian M, Jerde TJ, and Ratliff TL
Subjects: Male, Animals, Mice, Inflammation metabolism, Inflammation pathology, Humans, Prostatitis metabolism, Prostatitis pathology, Cell Differentiation, Prostatic Hyperplasia metabolism, Prostatic Hyperplasia pathology, Cell Proliferation, Receptors, Androgen metabolism, Prostate metabolism, Prostate pathology, Signal Transduction, Stem Cells metabolism, Interleukin 1 Receptor Antagonist Protein metabolism, Mice, Transgenic
Abstract: Chronic prostate inflammation in patients with benign prostate hyperplasia (BPH) correlates with the severity of symptoms. How inflammation contributes to prostate enlargement and/or BPH symptoms and the underlying mechanisms remain unclear. In this study, we utilize a unique transgenic mouse model that mimics chronic non-bacterial prostatitis in men and investigate the impact of inflammation on androgen receptor (AR) in basal prostate stem cells (bPSC) and their differentiation in vivo. We find that inflammation significantly enhances AR levels and activity in bPSC. More importantly, we identify interleukin 1 receptor antagonist (IL-1RA) as a crucial regulator of AR in bPSC during inflammation. IL-1RA is one of the top molecules upregulated by inflammation, and inhibiting IL-1RA reverses the enhanced AR activity in organoids derived from inflamed bPSC. Additionally, IL-1RA appears to activate AR by counteracting IL-1α's inhibitory effect. Furthermore, using a lineage tracing model, we observe that inflammation induces bPSC proliferation and differentiation into luminal cells even under castrate conditions, indicating that AR activation driven by inflammation is sufficient to promote bPSC proliferation and differentiation. Taken together, our study uncovers mechanisms through which inflammation modulates AR signaling in bPSC and induces bPSC luminal differentiation that may contribute to prostate hyperplasia., (© 2024. The Author(s).)
Published: 2024
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48. Unbiased discovery of cancer pathways and therapeutics using Pathway Ensemble Tool and Benchmark.

Author: Wang L, Pattnaik A, Sahoo SS, Stone EG, Zhuang Y, Benton A, Tajmul M, Chakravorty S, Dhawan D, Nguyen MA, Sirit I, Mundy K, Ricketts CJ, Hadisurya M, Baral G, Tinsley SL, Anderson NL, Hoda S, Briggs SD, Kaimakliotis HZ, Allen-Petersen BL, Tao WA, Linehan WM, Knapp DW, Hanna JA, Olson MR, Afzali B, and Kazemian M
Subjects: Humans, Signal Transduction drug effects, Biomarkers, Tumor metabolism, Biomarkers, Tumor genetics, Drug Repositioning, Animals, Prognosis, Antineoplastic Agents pharmacology, Antineoplastic Agents therapeutic use, Cell Line, Tumor, Computational Biology methods, Mice, Neoplasms drug therapy, Neoplasms metabolism, Neoplasms genetics, Benchmarking
Abstract: Correctly identifying perturbed biological pathways is a critical step in uncovering basic disease mechanisms and developing much-needed therapeutic strategies. However, whether current tools are optimal for unbiased discovery of relevant pathways remains unclear. Here, we create "Benchmark" to critically evaluate existing tools and find that most function sub-optimally. We thus develop the "Pathway Ensemble Tool" (PET), which outperforms existing methods. Deploying PET, we identify prognostic pathways across 12 cancer types. PET-identified prognostic pathways offer additional insights, with genes within these pathways serving as reliable biomarkers for clinical outcomes. Additionally, normalizing these pathways using drug repurposing strategies represents therapeutic opportunities. For example, the top predicted repurposed drug for bladder cancer, a CDK2/9 inhibitor, represses cell growth in vitro and in vivo. We anticipate that using Benchmark and PET for unbiased pathway discovery will offer additional insights into disease mechanisms across a spectrum of diseases, enabling biomarker discovery and therapeutic strategies., (© 2024. The Author(s).)
Published: 2024
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49. GLObal Building heights for Urban Studies (UT-GLOBUS) for city- and street- scale urban simulations: Development and first applications.

Author: Kamath HG, Singh M, Malviya N, Martilli A, He L, Aliaga D, He C, Chen F, Magruder LA, Yang ZL, and Niyogi D
Abstract: We introduce University of Texas - GLObal Building heights for Urban Studies (UT-GLOBUS), a dataset providing building heights and urban canopy parameters (UCPs) for more than 1200 city or locales worldwide. UT-GLOBUS combines open-source spaceborne altimetry (ICESat-2 and GEDI) and coarse-resolution urban canopy elevation data with a machine-learning model to estimate building-level information. Validation using LiDAR data from six U.S. cities showed UT-GLOBUS-derived building heights had a root mean squared error (RMSE) of 9.1 meters. Validation of mean building heights within 1-km 2 grid cells, including data from Hamburg and Sydney, resulted in an RMSE of 7.8 meters. Testing the UCPs in the urban Weather Research and Forecasting (WRF-Urban) model resulted in a significant improvement (55% in RMSE) in intra-urban air temperature representation compared to the existing table-based local climate zone approach in Houston, TX. Additionally, we demonstrated the dataset's utility for simulating heat mitigation strategies and building energy consumption using WRF-Urban, with test cases in Chicago, IL, and Austin, TX. Street-scale mean radiant temperature simulations using the SOlar and LongWave Environmental Irradiance Geometry (SOLWEIG) model, incorporating UT-GLOBUS and LiDAR-derived building heights, confirmed the dataset's effectiveness in modeling human thermal comfort in Baltimore, MD (daytime RMSE = 2.85°C). Thus, UT-GLOBUS can be used for modeling urban hazards with significant socioeconomic and biometeorological risks, enabling finer scale urban climate simulations and overcoming previous limitations due to the lack of building information., (© 2024. The Author(s).)
Published: 2024
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50. DDX5 deficiency drives non-canonical NF-κB activation and NRF2 expression, influencing sorafenib response and hepatocellular carcinoma progression.

Author: Li Z, Kim W, Utturkar S, Yan B, Lanman NA, Elzey BD, Kazemian M, Yeo Y, and Andrisani O
Subjects: Animals, Humans, Mice, Gene Expression Regulation, Neoplastic drug effects, Cell Line, Tumor, Wnt Signaling Pathway drug effects, Ferroptosis drug effects, Ferroptosis genetics, Sorafenib pharmacology, Carcinoma, Hepatocellular drug therapy, Carcinoma, Hepatocellular genetics, Carcinoma, Hepatocellular pathology, Carcinoma, Hepatocellular metabolism, Liver Neoplasms genetics, Liver Neoplasms drug therapy, Liver Neoplasms pathology, Liver Neoplasms metabolism, DEAD-box RNA Helicases metabolism, DEAD-box RNA Helicases genetics, NF-E2-Related Factor 2 metabolism, NF-E2-Related Factor 2 genetics, Disease Progression, NF-kappa B metabolism
Abstract: In advanced hepatocellular carcinoma (HCC), RNA helicase DDX5 regulates the Wnt/β-catenin-ferroptosis axis, influencing the efficacy of the multi-tyrosine kinase inhibitor (mTKI) sorafenib. DDX5 inhibits Wnt/β-catenin signaling, preventing sorafenib-induced ferroptosis escape. Sorafenib/mTKIs reduce DDX5 expression, correlating with poor patient survival post-sorafenib treatment. Notably, DDX5-knockout in HCC cells activates Wnt/β-catenin signaling persistently. Herein, we investigate the mechanistic impact of Wnt/β-catenin activation resulting from DDX5 downregulation in the progression and treatment of HCC. RNAseq analyses identified shared genes repressed by DDX5 and upregulated by sorafenib, including Wnt signaling genes, NF-κB-inducing kinase (NIK) essential for non-canonical NF-κB (p52/RelB) activation, and cytoprotective transcription factor NRF2. We demonstrate, Wnt/β-catenin activation induced NIK transcription, leading to non-canonical NF-κB activation, which subsequently mediated NRF2 transcription. Additionally, DDX5 deficiency extended NRF2 protein half-life by inactivating KEAP1 through p62/SQSTM1 stabilization. In a preclinical HCC mouse model, NRF2 knockdown or DDX5 overexpression restricted tumor growth upon sorafenib treatment, via induction of ferroptosis. Importantly, DDX5-knockout HCC cells exhibited elevated expression of Wnt signaling genes, NIK, p52/RelB, and NRF2-regulated genes, regardless of sorafenib treatment. Transcriptomic analyses of HCCs from TCGA and the Stelic Animal Model (STAM) of non-alcoholic steatohepatitis revealed elevated expression of these interconnected pathways in the context of DDX5 downregulation. In conclusion, DDX5 deficiency triggers Wnt/β-catenin signaling, promoting p52/RelB and NRF2 activation, thereby enabling ferroptosis evasion upon sorafenib treatment. Similarly, independent of sorafenib, DDX5 deficiency in liver tumors enhances activation and gene expression of these interconnected pathways, underscoring the clinical relevance of DDX5 deficiency in HCC progression and therapeutic response., (© 2024. The Author(s).)
Published: 2024
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