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1. A Spitting Image: Modular Superpixel Tokenization in Vision Transformers

Author

Aasan, Marius, Kolbjørnsen, Odd, Solberg, Anne Schistad, and Rivera, Adín Ramirez

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence, Computer Science - Machine Learning, 68T45, I.2.10, I.4.10
Abstract

Vision Transformer (ViT) architectures traditionally employ a grid-based approach to tokenization independent of the semantic content of an image. We propose a modular superpixel tokenization strategy which decouples tokenization and feature extraction; a shift from contemporary approaches where these are treated as an undifferentiated whole. Using on-line content-aware tokenization and scale- and shape-invariant positional embeddings, we perform experiments and ablations that contrast our approach with patch-based tokenization and randomized partitions as baselines. We show that our method significantly improves the faithfulness of attributions, gives pixel-level granularity on zero-shot unsupervised dense prediction tasks, while maintaining predictive performance in classification tasks. Our approach provides a modular tokenization framework commensurable with standard architectures, extending the space of ViTs to a larger class of semantically-rich models., Comment: To appear in ECCV (MELEX) 2024 Workshop Proceedings

Published
2024

2. Learning from Memory: Non-Parametric Memory Augmented Self-Supervised Learning of Visual Features

Author

Silva, Thalles, Pedrini, Helio, and Rivera, Adín Ramírez

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract

This paper introduces a novel approach to improving the training stability of self-supervised learning (SSL) methods by leveraging a non-parametric memory of seen concepts. The proposed method involves augmenting a neural network with a memory component to stochastically compare current image views with previously encountered concepts. Additionally, we introduce stochastic memory blocks to regularize training and enforce consistency between image views. We extensively benchmark our method on many vision tasks, such as linear probing, transfer learning, low-shot classification, and image retrieval on many datasets. The experimental results consolidate the effectiveness of the proposed approach in achieving stable SSL training without additional regularizers while learning highly transferable representations and requiring less computing time and resources., Comment: To appear in ICML 2024. Code at https://github.com/sthalles/MaSSL

Published
2024

4. Higher Lie characters and root enumeration in classical Weyl groups

Author

Adin, Ron M., Hegedüs, Pál, and Roichman, Yuval

Subjects
Mathematics - Combinatorics, Mathematics - Group Theory, Mathematics - Representation Theory
Abstract

We prove that, for any integer $k$, the $k$-th root enumerator in the classical Weyl group of type $D$ is a proper character. The proof uses higher Lie characters of type $B$., Comment: 35 pages, minor changes, to appear in J. Algebra

Published
2023

5. A statistical algorithm showing coenzyme Q10 and citrate synthase as biomarkers for mitochondrial respiratory chain enzyme activities

Author

D. Yubero, A. Adin, R. Montero, C. Jou, C. Jiménez-Mallebrera, A. García-Cazorla, A. Nascimento, M. M. O’Callaghan, J. Montoya, L. Gort, P. Navas, A. Ribes, M. D. Ugarte, and R. Artuch

Subjects
Medicine, Science
Abstract

Abstract Laboratory data interpretation for the assessment of complex biological systems remains a great challenge, as occurs in mitochondrial function research studies. The classical biochemical data interpretation of patients versus reference values may be insufficient, and in fact the current classifications of mitochondrial patients are still done on basis of probability criteria. We have developed and applied a mathematic agglomerative algorithm to search for correlations among the different biochemical variables of the mitochondrial respiratory chain in order to identify populations displaying correlation coefficients >0.95. We demonstrated that coenzyme Q10 may be a better biomarker of mitochondrial respiratory chain enzyme activities than the citrate synthase activity. Furthermore, the application of this algorithm may be useful to re-classify mitochondrial patients or to explore associations among other biochemical variables from different biological systems.

Published
2016
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9. Automatic cross-validation in structured models: Is it time to leave out leave-one-out?

Author

Adin, A., Krainski, E., Lenzi, A., Liu, Z., Martínez-Minaya, J., and Rue, H.

Subjects
Statistics - Methodology, Statistics - Applications, Statistics - Computation
Abstract

Standard techniques such as leave-one-out cross-validation (LOOCV) might not be suitable for evaluating the predictive performance of models incorporating structured random effects. In such cases, the correlation between the training and test sets could have a notable impact on the model's prediction error. To overcome this issue, an automatic group construction procedure for leave-group-out cross validation (LGOCV) has recently emerged as a valuable tool for enhancing predictive performance measurement in structured models. The purpose of this paper is (i) to compare LOOCV and LGOCV within structured models, emphasizing model selection and predictive performance, and (ii) to provide real data applications in spatial statistics using complex structured models fitted with INLA, showcasing the utility of the automatic LGOCV method. First, we briefly review the key aspects of the recently proposed LGOCV method for automatic group construction in latent Gaussian models. We also demonstrate the effectiveness of this method for selecting the model with the highest predictive performance by simulating extrapolation tasks in both temporal and spatial data analyses. Finally, we provide insights into the effectiveness of the LGOCV method in modelling complex structured data, encompassing spatio-temporal multivariate count data, spatial compositional data, and spatio-temporal geospatial data.

Published
2023
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10. Representation Learning via Consistent Assignment of Views over Random Partitions

Author

Silva, Thalles and Rivera, Adín Ramírez

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract

We present Consistent Assignment of Views over Random Partitions (CARP), a self-supervised clustering method for representation learning of visual features. CARP learns prototypes in an end-to-end online fashion using gradient descent without additional non-differentiable modules to solve the cluster assignment problem. CARP optimizes a new pretext task based on random partitions of prototypes that regularizes the model and enforces consistency between views' assignments. Additionally, our method improves training stability and prevents collapsed solutions in joint-embedding training. Through an extensive evaluation, we demonstrate that CARP's representations are suitable for learning downstream tasks. We evaluate CARP's representations capabilities in 17 datasets across many standard protocols, including linear evaluation, few-shot classification, k-NN, k-means, image retrieval, and copy detection. We compare CARP performance to 11 existing self-supervised methods. We extensively ablate our method and demonstrate that our proposed random partition pretext task improves the quality of the learned representations by devising multiple random classification tasks. In transfer learning tasks, CARP achieves the best performance on average against many SSL methods trained for a longer time., Comment: To appear in NeurIPS 2023. Code available at https://github.com/sthalles/carp

Published
2023

11. Bound states in the continuum induced via local symmetries in complex structures

Author

Wang, Cheng-Zhen, Kuhl, Ulrich, Dowling, Adin, Schanz, Holger, and Kottos, Tsampikos

Subjects
Physics - Optics, Nonlinear Sciences - Chaotic Dynamics, Quantum Physics
Abstract

Bound states in the continuum (BICs) defy conventional wisdom that assumes a spectral separation between propagating waves, that carry energy away, and spatially localized waves corresponding to discrete frequencies. They can be described as resonance states with infinite lifetime, i.e., leaky modes with zero leakage. The advent of metamaterials and nanophotonics allowed the creation of BICs in a variety of systems. Mainly, BICs have been realized by destructive interference between outgoing resonant modes or exploiting engineered global symmetries that enforce the decoupling of a symmetry-incompatible bound mode from the surrounding radiation modes. Here, we introduce theoretically BICs relying on a different mechanism, namely local symmetries that enforce a field concentration on a part of a complex system without implying any global symmetry. We experimentally implement such BICs using microwaves in a compact one-dimensional photonic network and show that they emerge from the annihilation of two topological singularities, a zero and a pole, of the measured scattering matrix. Our alternative for achieving BICs in complex wave systems may be useful for applications like sensing, lasing, and enhancement of nonlinear interactions that require high-$Q$ modes., Comment: 11 pages, 6 figures

Published
2023
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12. SelfGraphVQA: A Self-Supervised Graph Neural Network for Scene-based Question Answering

Author

Souza, Bruno, Aasan, Marius, Pedrini, Helio, and Rivera, Adín Ramírez

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

The intersection of vision and language is of major interest due to the increased focus on seamless integration between recognition and reasoning. Scene graphs (SGs) have emerged as a useful tool for multimodal image analysis, showing impressive performance in tasks such as Visual Question Answering (VQA). In this work, we demonstrate that despite the effectiveness of scene graphs in VQA tasks, current methods that utilize idealized annotated scene graphs struggle to generalize when using predicted scene graphs extracted from images. To address this issue, we introduce the SelfGraphVQA framework. Our approach extracts a scene graph from an input image using a pre-trained scene graph generator and employs semantically-preserving augmentation with self-supervised techniques. This method improves the utilization of graph representations in VQA tasks by circumventing the need for costly and potentially biased annotated data. By creating alternative views of the extracted graphs through image augmentations, we can learn joint embeddings by optimizing the informational content in their representations using an un-normalized contrastive approach. As we work with SGs, we experiment with three distinct maximization strategies: node-wise, graph-wise, and permutation-equivariant regularization. We empirically showcase the effectiveness of the extracted scene graph for VQA and demonstrate that these approaches enhance overall performance by highlighting the significance of visual information. This offers a more practical solution for VQA tasks that rely on SGs for complex reasoning questions., Comment: To appear in Vision-and-Language Algorithmic Reasoning Workshop at ICCV 2023

Published
2023

13. Self-supervised Learning of Contextualized Local Visual Embeddings

Author

Silva, Thalles Santos, Pedrini, Helio, and Rivera, Adín Ramírez

Subjects
Computer Science - Computer Vision and Pattern Recognition, I.4.6, I.4.7
Abstract

We present Contextualized Local Visual Embeddings (CLoVE), a self-supervised convolutional-based method that learns representations suited for dense prediction tasks. CLoVE deviates from current methods and optimizes a single loss function that operates at the level of contextualized local embeddings learned from output feature maps of convolution neural network (CNN) encoders. To learn contextualized embeddings, CLoVE proposes a normalized mult-head self-attention layer that combines local features from different parts of an image based on similarity. We extensively benchmark CLoVE's pre-trained representations on multiple datasets. CLoVE reaches state-of-the-art performance for CNN-based architectures in 4 dense prediction downstream tasks, including object detection, instance segmentation, keypoint detection, and dense pose estimation., Comment: Pre-print. 4th Visual Inductive Priors for Data-Efficient Deep Learning Workshop ICCV 2023. Code at https://github.com/sthalles/CLoVE

Published
2023

14. Transitive and Gallai colorings

Author

Adin, R. M., Berenstein, A., Greenstein, J., Li, J. -R., Marmor, A., and Roichman, Y.

Subjects
Mathematics - Combinatorics
Abstract

A Gallai coloring of the complete graph is an edge-coloring with no rainbow triangle. This concept first appeared in the study of comparability graphs and anti-Ramsey theory. We introduce a transitive analogue for acyclic directed graphs, and generalize both notions to Coxeter systems, matroids and commutative algebras. It is shown that for any finite matroid (or oriented matroid), the maximal number of colors is equal to the matroid rank. This generalizes a result of Erd\H{o}s-Simonovits-S\'os for complete graphs. The number of Gallai (or transitive) colorings of the matroid that use at most $k$ colors is a polynomial in $k$. Also, for any acyclic oriented matroid, represented over the real numbers, the number of transitive colorings using at most 2 colors is equal to the number of chambers in the dual hyperplane arrangement. We count Gallai and transitive colorings of the root system of type A using the maximal number of colors, and show that, when equipped with a natural descent set map, the resulting quasisymmetric function is symmetric and Schur-positive., Comment: 31 pages, 5 figures

Published
2023

15. Geriatric trauma triage: optimizing systems for older adults-a publication of the American Association for the Surgery of Trauma Geriatric Trauma Committee.

Author

Egodage, Tanya, Ho, Vanessa, Bongiovanni, Tasce, Knight-Davis, Jennifer, Adams, Sasha, Digiacomo, Jody, Swezey, Elisabeth, Posluszny, Joseph, Ahmed, Nasim, Prabhakaran, Kartik, Ratnasekera, Asanthi, Putnam, Adin, Behbahaninia, Milad, Hornor, Melissa, Cohan, Caitlin, and Joseph, Bellal

Subjects
Outcome Assessment, Health Care, geriatrics, resource allocation, triage
Abstract

BACKGROUND: Geriatric trauma patients are an increasing population of the United States (US), sustaining a high incidence of falls, and suffer greater morbidity and mortality to their younger counterparts. Significant variation and challenges exist to optimize outcomes for this cohort, while being mindful of available resources. This manuscript provides concise summary of locoregional and national practices, including relevant updates in the triage of geriatric trauma in an effort to synthesize the results and provide guidance for further investigation. METHODS: We conducted a review of geriatric triage in the United States (US) at multiple stages in the care of the older patient, evaluating existing literature and guidelines. Opportunities for improvement or standardization were identified. RESULTS: Opportunities for improved geriatric trauma triage exist in the pre-hospital setting, in the trauma bay, and continue after admission. They may include physiologic criteria, biochemical markers, radiologic criteria and even age. Recent Trauma Quality Improvement Program (TQIP) Best Practices Guidelines for Geriatric Trauma Management published in 2024 support these findings. CONCLUSION: Trauma systems must adjust to provide optimal care for older adults. Further investigation is required to provide pertinent guidance.

Published
2024

18. A scalable approach for short-term disease forecasting in high spatial resolution areal data

Author

Orozco-Acosta, E., Riebler, A., Adin, A., and Ugarte, M. D.

Subjects
Statistics - Methodology, Statistics - Computation
Abstract

Short-term disease forecasting at specific discrete spatial resolutions has become a high-impact decision-support tool in health planning. However, when the number of areas is very large obtaining predictions can be computationally intensive or even unfeasible using standard spatio-temporal models. The purpose of this paper is to provide a method for short-term predictions in high-dimensional areal data based on a newly proposed ``divide-and-conquer" approach. We assess the predictive performance of this method and other classical spatio-temporal models in a validation study that uses cancer mortality data for the 7907 municipalities of continental Spain. The new proposal outperforms traditional models in terms of mean absolute error, root mean square error and interval score when forecasting cancer mortality one, two and three years ahead. Models are implemented in a fully Bayesian framework using the well-known integrated nested Laplace (INLA) estimation technique.

Published
2023
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19. EVALUATING ACETONE AND METHANOL FOR ELECTROPHORETIC DEPOSITION OF SS 316L COATED WITH HYDROXYAPATITE/MULTIWALLED CARBON NANOTUBES DENTAL IMPLANTS: A FOCUS ON CORROSION RESISTANCE

Author

Ersyi Arini Valmelina, Praswasti Pembangun Dyah Kencana Wulan, Yudan Whulanza, and Mehmer Șükrü Adin

Subjects
acetone, electrophoretic deposition, methanol, stainless steel, Chemistry, QD1-999
Abstract

Dental implants offer a reliable solution for replacing damaged tooth roots. This research investigates the comparative performance of acetone and methanol as suspension media in the fabrication of stainless steel type 316L-based dental implants using the Electrophoretic Deposition (EPD) method, a technique known for its simplicity and cost-effectiveness. Voltage variations of 20V, 30V, and 40V were applied to both acetone and methanol suspensions for a duration of 20 minutes. The morphology of the Hydroxyapatite/Multiwalled Carbon Nanotube (HA/MWCNT) coatings was meticulously characterized using Scanning Electron Microscopy (SEM). Corrosion resistance was evaluated through Potentiodynamic Polarization (PDP) and Electrochemical Impedance Spectroscopy (EIS) techniques. Remarkably, at 30V, a homogeneous and crack-free coating was achieved, demonstrating superior corrosion resistance. This was further corroborated by the resistance values of 23.891 Ω and 114.990 Ω for the acetone and methanol samples, respectively. Additionally, the corrosion rates of 0.075 (mmpy) and 0.0004 (mmpy) for the acetone and methanol samples further emphasized the superiority of methanol as a suspension medium. These findings unequivocally establish methanol as the optimal choice for achieving superior deposition quality and corrosion resistance in the context of the EPD method for stainless steel type 316L-based dental implants.

Published
2024
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20. Out-of-hospital cardiac arrest (OHCA) in Bosnia and Herzegovina in the period 2018 -2022: current trends, usage of automated external defibrillators (AED) and bystanders’ involvement

Author

Armin Šljivo, Tatjana Jevtić, Selma Terzić-Salihbašić, Arian Abdulkhaliq, Leopold Reiter, Faris Salihbašić, Ajla Bečar-Alijević, Adin Alijević, Ilma Dadić, and Fatima Gavrankapetanović

Subjects
cardiopulmonary resuscitation, car-diac events, resus-citation, return of spontaneous circu-lation, Medicine
Abstract

Aim To investigate out-of-hospital cardiac arrest (OHCA) trend, provided advanced life support (ALS) measures, automated external defibrillator (AEDs) utilization and by-standers involvement in cardiopulmonary resuscitation (CPR) during OHCA incidents.Methods This cross-sectional study encompassed data pertaining to all OHCA incidents attended to by the Emergency Medical Service of Canton Sarajevo, Bosnia and Herzegovina, covering the period from January 2018 to December 2022.Results Among a total of 1131 OHCA events, 236 (20.8 %) patients achieved return of spontaneous circulation (ROSC); there were 175 (74.1%) males and 61 (25.9%) females. The OHCA incidence was 54/100.000 inhabitants per year. After a 30-day period post-ROSC, 146 (61.9%) patients fully recovered, while 90 (38.1%) did not survive during this timeframe. Younger age (p

Published
2024
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23. Design and Construction of Dual-Axis Solar Tracking Using Arduino Electronics

Author

Memić, Adin, Muftić Dedović, Maja, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Ademović, Naida, editor, Akšamija, Zlatan, editor, and Karabegović, Almir, editor

Published
2024
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24. Optimal Placement of Phasor Measurement Units in Power Systems Using Genetic Algorithms

Author

Muftić Dedović, Maja, Dautbašić, Nedis, Alihodžić, Ajdin, Memić, Adin, Mujezinović, Adnan, Avdaković, Samir, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Ademović, Naida, editor, Akšamija, Zlatan, editor, and Karabegović, Almir, editor

Published
2024
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25. High-dimensional order-free multivariate spatial disease mapping

Author

Vicente, G., Adin, A., Goicoa, T., and Ugarte, M. D.

Subjects
Statistics - Methodology, Statistics - Computation
Abstract

Despite the amount of research on disease mapping in recent years, the use of multivariate models for areal spatial data remains limited due to difficulties in implementation and computational burden. These problems are exacerbated when the number of small areas is very large. In this paper, we introduce an order-free multivariate scalable Bayesian modelling approach to smooth mortality (or incidence) risks of several diseases simultaneously. The proposal partitions the spatial domain into smaller subregions, fits multivariate models in each subdivision and obtains the posterior distribution of the relative risks across the entire spatial domain. The approach also provides posterior correlations among the spatial patterns of the diseases in each partition that are combined through a consensus Monte Carlo algorithm to obtain correlations for the whole study region. We implement the proposal using integrated nested Laplace approximations (INLA) in the R package bigDM and use it to jointly analyse colorectal, lung, and stomach cancer mortality data in Spanish municipalities. The new proposal permits the analysis of big data sets and provides better results than fitting a single multivariate model.

Published
2022
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26. Cyclic descents, matchings and Schur-positivity

Author

Adin, Ron M. and Roichman, Yuval

Subjects
Mathematics - Combinatorics
Abstract

A new descent set statistic on involutions, defined geometrically via their interpretation as matchings, is introduced in this paper, and shown to be equi-distributed with the standard one. This concept is then applied to construct explicit cyclic descent extensions on involutions, standard Young tableaux and Motzkin paths. Schur-positivity of the associated quasisymmetric functions follows., Comment: 23 pages, 2 figures

Published
2022

29. Fostering Students' English Grammar Learning Outcomes and Handling Classroom Technological Inclusivity by Integrating Quiziz

Author

Dian Fadhilawati, Adin Fauzi, Moh Mansur, and Dwita Laksmita Rachmawati

Subjects
quizizz paper mode, grammar, technological inclusivity, Language and Literature
Abstract

This study fostered grammar learning outcomes of tenth-grade students and handled technological inclusivity by using Quizizz paper mode, especially in understanding and using simple past and present perfect tense. This study utilized four stages of classroom action research encompassing planning, implementation, observation and evaluation, and reflection, the researchers used pre-tests, post-tests, and questionnaires for collecting the data. The outcomes unveiled a substantial improvement in students' learning from 66.50 to 89.50. Furthermore, students displayed favorable reactions, affirming the power of Quizizz paper mode in addressing challenges in grammar learning due to its engaging nature, cost-effectiveness, and provision of real-time feedback. Additionally, it fostered inclusivity by allowing every student to participate, irrespective of their access to technology. Moreover, it allowed students to rest their eyes on electronic devices while combining physical and digital learning experiences. The findings of this study suggest that integrating technology-based platforms like Quizizz paper mode can enhance grammar mastery by promoting increased engagement and interactivity among students. based on those results, it is recommended that future researchers explore Quizizz paper mode for teaching various grammar topics or language skills by applying larger sample sizes and examining the prolonged impacts of this tool on students' mastery of grammar or other language skills.

Published
2024
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30. Increasing the development of national ideological values from an early age through family education

Author

Sri Sulistijaningsih, Encep Syarief Nurdin, Puji Yanti Fauziah, Adin Ariyanti Dewi, and Gumpanat Bariboon

Subjects
early age, family education, pancasila values, Education (General), L7-991
Abstract

This research aims to determine the role of the family in training the application of Pancasila values in early childhood. The researchers used a literature review method to determine the role played by families in training young children to apply Pancasila valuesin everyday life. This research used Google Scholar and Scopus databases to search for relevant articles and conduct a more in-depth analysis. The research stage began with identifying previously determined keywords, screening by reading the abstract and research results and finding relevant articles to study. In analysis, the researcher conducted an analysis based on the context of the study of the selected articles until new themes emerged, which became the focus of the research. The theme was the role of family education in training Pancasila values from an early age. The results of the research showed that efforts to practice Pancasila values could be made by practising belief in God the Almighty, worshipping, respecting each other, praying, taking advantage of God's blessings, respecting older people, loving the environment, working together, respecting opinions, and being fair.

Published
2024
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31. ACVIM consensus statement on diagnosis and management of urinary incontinence in dogs

Author

Allison Kendall, Julie K. Byron, Jodi L. Westropp, Joan R. Coates, Shelly Vaden, Chris Adin, Garrett Oetelaar, Joe W. Bartges, Jonathan D. Foster, Larry G. Adams, Natasha Olby, and Allyson Berent

Subjects
canine, incontinence, urinary, Veterinary medicine, SF600-1100
Abstract

Abstract Urinary incontinence (UI) is a disorder of micturition that can occur in dogs of any age, sex, and breed depending on the underlying cause and time of onset. Diagnosis and treatment for various causes of UI in dogs have been described by multiple comprehensive single author review articles, but large prospective clinical trials comparing treatment outcomes in veterinary medicine are lacking. The objectives of this consensus statement therefore are to provide guidelines on both recommended diagnostic testing and treatment for various causes of UI in dogs. Specifically, pathophysiology directly related to the canine urinary system will be reviewed and diagnostic and therapeutic challenges will be addressed. A panel of 12 experts in the field (8 small animal internists [L. Adams, J. Bartges, A. Berent, J. Byron, J. Foster, A. Kendall, S. Vaden, J. Westropp], 2 neurologists [J. Coates, N. Olby], 1 radiologist [G. Oetelaar], and 1 surgeon [C. Adin]) was formed to assess and summarize evidence in the peer‐reviewed literature and to complement it with consensus recommendations using the Delphi method. Some statements were not voted on by all panelists. This consensus statement aims to provide guidance for management of both male and female dogs with underlying storage or voiding disorders resulting in UI.

Published
2024
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32. Global and Local Features through Gaussian Mixture Models on Image Semantic Segmentation

Author

Saire, Darwin and Rivera, Adín Ramírez

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

The semantic segmentation task aims at dense classification at the pixel-wise level. Deep models exhibited progress in tackling this task. However, one remaining problem with these approaches is the loss of spatial precision, often produced at the segmented objects' boundaries. Our proposed model addresses this problem by providing an internal structure for the feature representations while extracting a global representation that supports the former. To fit the internal structure, during training, we predict a Gaussian Mixture Model from the data, which, merged with the skip connections and the decoding stage, helps avoid wrong inductive biases. Furthermore, our results show that we can improve semantic segmentation by providing both learning representations (global and local) with a clustering behavior and combining them. Finally, we present results demonstrating our advances in Cityscapes and Synthia datasets., Comment: Pre-print to appear in IEEE Access. Code available at https://gitlab.com/mipl/phgmm

Published
2022
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33. RepFair-GAN: Mitigating Representation Bias in GANs Using Gradient Clipping

Author

Kenfack, Patrik Joslin, Sabbagh, Kamil, Rivera, Adín Ramírez, and Khan, Adil

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence
Abstract

Fairness has become an essential problem in many domains of Machine Learning (ML), such as classification, natural language processing, and Generative Adversarial Networks (GANs). In this research effort, we study the unfairness of GANs. We formally define a new fairness notion for generative models in terms of the distribution of generated samples sharing the same protected attributes (gender, race, etc.). The defined fairness notion (representational fairness) requires the distribution of the sensitive attributes at the test time to be uniform, and, in particular for GAN model, we show that this fairness notion is violated even when the dataset contains equally represented groups, i.e., the generator favors generating one group of samples over the others at the test time. In this work, we shed light on the source of this representation bias in GANs along with a straightforward method to overcome this problem. We first show on two widely used datasets (MNIST, SVHN) that when the norm of the gradient of one group is more important than the other during the discriminator's training, the generator favours sampling data from one group more than the other at test time. We then show that controlling the groups' gradient norm by performing group-wise gradient norm clipping in the discriminator during the training leads to a more fair data generation in terms of representational fairness compared to existing models while preserving the quality of generated samples.

Published
2022

34. Physicochemical characteristics of Pangasius sp. skin-gelatin-based-edible film enriched with silver nanoparticles [version 2; peer review: 2 approved with reservations]

Author

Rahmi Nurdiani, Asep A. Prihanto, Muhamad Firdaus, Faridatul Nur Aini, Fajrin Adin Nabilah, Rosnita A Talib, and Nurul Huda

Subjects
Research Article, Articles, Bruguiera gymnorrhiza, edible film, gelatin, physicochemical characteristics, silver nanoparticles
Abstract

Background: Edible films intended for food packaging have been produced from hydrocolloids, lipids, resins, and composites, including gelatin. Gelatin is known to have a good filming ability and has been suggested as an alternative to non-biodegradable plastics. Naturally active compounds incorporated into film packaging may not only protect the food product from oxidation and microbial contamination, but they may also alter the physicochemical properties of the film. Silver nanoparticles have been used in food packaging as active agents due to their antibacterial and antifungal properties. The addition may affect the characteristics of the packaging. Therefore, this study aims to determine the effect of the addition of silver nanoparticles on the physicochemical characteristics of edible film from Pangasius sp. skin gelatin. Methods: Mangrove extract of Bruguiera gymnorrhiza was used to synthesize silver into nanoparticle size. In this study, silver nanoparticles (AgNPs) with different concentrations (0, 2, 4 and 8%) were added into gelatin-based edible film. The edible films produced were observed for their physicochemical characteristics, including thickness, tensile strength, elongation, water vapour transmission, moisture content, pH, and colour. Results: AgNPs affected the colour of the fish-gelatin-based edible film, as an increased concentration of AgNPs resulted in a darker film. Nevertheless, the addition of AgNPs showed no significant effect on the thickness (145–216 µm), tensile strength (14.58–19.72 MPa), elongation (21.86–54.19%), water vapour transmission (30.91–42.55 g/m 2/day), moisture content (9.57–11.16%) or pH (5.92–6.01) of the fish-gelatin-based edible film. Conclusions: The addition of AgNPs has no significant effect on gelatin-based edible film physicochemical properties except colour. Therefore, the incorporated edible film has the potential to be developed further.

Published
2024
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35. Open innovation between university-industry: A review of research trends and practices

Author

Adin Gustina, Nuraini Desty Nurmasari, and Jane Su Chuan Liu

Subjects
Open innovation, University collaboration, Innovation, Academic collaboration, Management. Industrial management, HD28-70, Business, HF5001-6182
Abstract

This study aims to review papers on open innovation in the university by examining the research profile, open innovation form and the process underpinning, key variables used, and suggestions for potential future studies. This study conducted an analysis of 71 relevant articles among 2.759 obtained from Web of Science and Scopus databases. Content analysis was used to identify significant research concerns and gaps that could be addressed in future studies. This study offers the intersection of open innovation-focused university domains. This paper proposes a conceptual open innovation model in university settings by mapping key characteristics and identifying relevant areas for future research.

Published
2024
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37. Risk of intensive care unit admission and mortality in patients hospitalized due to influenza A or B and SARS‑CoV‑2 variants Omicron or Delta

Author

Omid Rezahosseini, Casper Roed, Adin Sejdic, Mads Frederik Eiberg, Lene Nielsen, Jonas Boel, Caroline Klint Johannesen, Maarten vanWijhe, Kristina Træholt Franck, Sisse Rye Ostrowski, Birgitte Lindegaard, Thea K. Fischer, Troels Bygum Knudsen, Jon Gitz Holler, Zitta Barrella Harboe, and the COVID‐19 Omicron Delta study group collaborators

Subjects
influenza A, influenza B, intensive care units, mortality, SARS‐CoV‐2 Delta variants, SARS‐CoV‐2 Omicron variant, Immunologic diseases. Allergy, RC581-607
Abstract

Abstract Background Respiratory viral infections have significant global health impacts. We compared 30‐day intensive care unit (ICU) admission and all‐cause mortality risks in patients with severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) Delta and Omicron variants versus influenza A and B (A/B). Methods Data from two retrospective inpatient cohorts in Capital Region of Denmark were analyzed. Cohorts included hospitalized influenza A/B patients (2017–2018) and SARS‐CoV‐2 Delta/Omicron patients (2021–2022), aged ≥18 years, admitted within 14 days of a positive real‐time polymerase chain reaction test result. Cumulative ICU admission and mortality rates were estimated using the Aalen–Johansen estimator. Cox regression models calculated hazard ratios (HRs) for ICU admission and mortality. Results The study encompassed 1459 inpatients (Delta: 49%; Omicron: 26%; influenza A: 6.4%; and influenza B: 18%). Cumulative incidence of ICU admission was 11%, 4.0%, 7.5%, and 4.1%, for Delta, Omicron, influenza A, and B, respectively. For ICU admission, adjusted HRs (aHRs) were 3.1 (p

Published
2024
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38. Geriatric trauma triage: optimizing systems for older adults—a publication of the American Association for the Surgery of Trauma Geriatric Trauma Committee

Author

Bellal Joseph, Vanessa P Ho, Nasim Ahmed, Tasce Bongiovanni, Kartik Prabhakaran, Asanthi Ratnasekera, Sasha D Adams, Joseph Posluszny, Jody Digiacomo, Milad Behbahaninia, Melissa Hornor, Jennifer Knight-Davis, Tanya Egodage, Elisabeth Swezey, Adin Tyler Putnam, and Caitlin Cohan

Subjects
Surgery, RD1-811, Medical emergencies. Critical care. Intensive care. First aid, RC86-88.9
Abstract

Background Geriatric trauma patients are an increasing population of the United States (US), sustaining a high incidence of falls, and suffer greater morbidity and mortality to their younger counterparts. Significant variation and challenges exist to optimize outcomes for this cohort, while being mindful of available resources. This manuscript provides concise summary of locoregional and national practices, including relevant updates in the triage of geriatric trauma in an effort to synthesize the results and provide guidance for further investigation.Methods We conducted a review of geriatric triage in the United States (US) at multiple stages in the care of the older patient, evaluating existing literature and guidelines. Opportunities for improvement or standardization were identified.Results Opportunities for improved geriatric trauma triage exist in the pre-hospital setting, in the trauma bay, and continue after admission. They may include physiologic criteria, biochemical markers, radiologic criteria and even age. Recent Trauma Quality Improvement Program (TQIP) Best Practices Guidelines for Geriatric Trauma Management published in 2024 support these findings.Conclusion Trauma systems must adjust to provide optimal care for older adults. Further investigation is required to provide pertinent guidance.

Published
2024
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39. Comparison of Lung and Contralateral Scattered Breast Dose between Field-in-Field and Wedge Techniques in Patients with Early Breast Cancer

Author

Seraj Adin Zare, Maryam Bahador, and Samira Yazdani

Subjects
Breast Cancer, Radiotherapy, Radiation Dose, Field In Field Technique, Medical technology, R855-855.5
Abstract

Purpose: This study aims to evaluate the dosimetric result of the Field-In-Field (FIF) plans compared with Tangential Wedged Beams (TWB) plans for whole breast radiotherapy of patients. Materials and Methods: In this survey, we entered fifty patients with breast-conserving surgery and postoperative whole-breast radiotherapy. FIF and a TWB plan were made for each patient to compare dosimetric outcomes. Results: The Homogeneity Index (HI) and Conformity Index (CI) were specified for the evaluation of Planning Target Volume (PTV). The mean dose of the ipsilateral lung and contra-lateral breast for the evaluation of organs at risk dose were used. The FIF plans had significantly lower HI (p < 0.01) and CI (p < 0.01) than those of the TWB plans. It means in the dosimetric comparisons of the PTV, the FIF plans were better than the TWB plans. The V10lung (31.152vs. 32.72%, p < 0.01), V20lung (25.6064vs. 26.6%, p < 0.01) V30lung (17.4% vs. 18.4%, p < 0.01) were lower with the FIF plans compared with those of the TWB plans, with statistical significance. The FIF plans had a lower mean dose for the lung than those of TWB plans (1225.48 vs. 1670.32 cGy) but no statistical significance (p=0.06). The mean dose in the contra-lateral of the breast in FIF plans was lower than in TWB plans (61.666 vs. 163.45 cGy), with statistical significance (p < 0.01). Conclusion: The FIF plans increased the dose homogeneity, and conformity of the target volume for the whole-breast irradiation compared with the TWB plans contralateral breast. Moreover, the doses of organs at risk (ipsilateral lung and contralateral breast) were reduced with FIF plans.

Published
2024
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40. Immune cell populations and induced immune responses at admission in patients hospitalized with vaccine breakthrough SARS-CoV-2 infections

Author

Adin Sejdic, Hans Jakob Hartling, Jon Gitz Holler, Lars Klingen Gjærde, Birgitte Lindegaard, Arnold Matovu Dungu, Filip Gnesin, Maria Elizabeth Engel Møller, Rebecca Svanberg Teglgaard, Carsten Utoft Niemann, Patrick Terrence Brooks, Charlotte Sværke Jørgensen, Kristina Træholt Franck, Thea K. Fischer, Hanne Vibeke Marquart, Zitta Barrella Harboe, and Sisse Rye Ostrowski

Subjects
immune cell populations, inflammation, vaccine breakthrough infection, mRNA vaccine against SARS-CoV2, cytokines, Immunologic diseases. Allergy, RC581-607
Abstract

BackgroundVaccine breakthrough SARS-CoV-2 infections are common and of clinical and public health concern. However, little is known about the immunological characteristics of patients hospitalized due to these infections. We aimed to investigate and compare immune cell subpopulations and induced immune responses in vaccinated and non-vaccinated patients hospitalized with severe COVID-19.MethodsA nested case-control study on adults (≥ 18 years) who received at least two doses of a mRNA-COVID-19 vaccine and were hospitalized with SARS-CoV-2 breakthrough infections and severe COVID-19 between January 7, 2021, and February 1, 2022, were eligible for inclusion. Age- and sex-matched non-vaccinated controls were identified. Immunophenotyping was performed using a custom-designed 10-color flow cytometry prefabricated freeze-dried antibody panel (DuraClone, Beckman Coulter (BC), Brea, Calif). TruCulture (Myriad RBM, Austin, USA) was used to assess induced immune response in whole blood, revealing different critical signaling pathways as a proxy for immune function. All samples were obtained within 48 hours of admission.ResultsIn total, 20 hospitalized patients with severe COVID-19 and a breakthrough SARS-CoV-2 infection were included, ten vaccinated and ten non-vaccinated patients. Vaccinated patients had lower concentrations of CD19 B cells (p = 0.035), naïve CD4 T cells (p = 0.015), a higher proportion of γδ1 T cells (p = 0.019), and higher unstimulated immune cell release of IL-10 (p = 0.015).ConclusionWe observed immunological differences between vaccinated and non-vaccinated patients hospitalized due to severe COVID-19 that indicate that vaccinated patients had lower B cell concentrations, lower concentrations of CD4 naïve T cells, a skewed gamma-delta V1/V2 ratio, and an exaggerated IL-10 response at admission. These results could indicate a suboptimal immune response involved in SARS-CoV-2 breakthrough infections that cause severe COVID-19 in vaccinated adults. However, the sample size was small, and further research is needed to confirm these results.

Published
2024
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41. A deep learning approach to halo merger tree construction

Author

Robles, Sandra, Gómez, Jonathan S., Rivera, Adín Ramírez, Padilla, Nelson D., and Dujovne, Diego

Subjects
Astrophysics - Astrophysics of Galaxies, Astrophysics - Cosmology and Nongalactic Astrophysics, Computer Science - Machine Learning
Abstract

A key ingredient for semi-analytic models (SAMs) of galaxy formation is the mass assembly history of haloes, encoded in a tree structure. The most commonly used method to construct halo merger histories is based on the outcomes of high-resolution, computationally intensive N-body simulations. We show that machine learning (ML) techniques, in particular Generative Adversarial Networks (GANs), are a promising new tool to tackle this problem with a modest computational cost and retaining the best features of merger trees from simulations. We train our GAN model with a limited sample of merger trees from the Evolution and Assembly of GaLaxies and their Environments (EAGLE) simulation suite, constructed using two halo finders-tree builder algorithms: SUBFIND-D-TREES and ROCKSTAR-ConsistentTrees. Our GAN model successfully learns to generate well-constructed merger tree structures with high temporal resolution, and to reproduce the statistical features of the sample of merger trees used for training, when considering up to three variables in the training process. These inputs, whose representations are also learned by our GAN model, are mass of the halo progenitors and the final descendant, progenitor type (main halo or satellite) and distance of a progenitor to that in the main branch. The inclusion of the latter two inputs greatly improves the final learned representation of the halo mass growth history, especially for SUBFIND-like ML trees. When comparing equally sized samples of ML merger trees with those of the EAGLE simulation, we find better agreement for SUBFIND-like ML trees. Finally, our GAN-based framework can be utilised to construct merger histories of low- and intermediate-mass haloes, the most abundant in cosmological simulations., Comment: 17 pages, 12 figures, 3 tables, 2 appendices. Minor editorial improvements, matches published version

Published
2022
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44. Deep immune cell phenotyping and induced immune cell responses at admission stratified by BMI in patients hospitalized with COVID-19: An observational multicenter cohort pilot study

Author

Sejdic, Adin, Hartling, Hans Jakob, Gitz Holler, Jon, Klingen Gjærde, Lars, Matovu Dungu, Arnold, Engel Møller, Maria Elizabeth, Svanberg Teglgaard, Rebecca, Utoft Niemann, Carsten Utoft, Brooks, Patrick Terrence, Mogensen, Trine H., Weis, Nina, Podlekareva, Daria, Baum Jørgensen, Marie Louise, Ortved Gang, Anne, Stampe Hersby, Ditte, Hald, Annemette, Dam Nielsen, Susanne, Lebech, Anne-Mette, Helleberg, Marie, Lundgren, Jens, Træholt Franck, Kristina, Fischer, Thea K., Barrella Harboe, Zitta, Marquart, Hanne Vibeke, Rye Ostrowski, Sisse, and Lindegaard, Birgitte

Published
2024
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47. A comparison of quality-adjusted life years in older adults after heart transplantation versus long-term mechanical support: Findings from the SUSTAIN-IT study

Author

Grady, Kathleen L., Dew, Mary Amanda, Pagani, Francis D., Spertus, John A., Hsich, Eileen, Yuzefpolskaya, Melana, Lampert, Brent, Kirklin, James K., Petty, Michael, Kao, Andrew, Yancy, Clyde, Hartupee, Justin, Pamboukian, Salpy V., Johnson, Maryl, Murray, Margaret, Wu, Tingqing, and Andrei, Adin-Cristian

Published
2024
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49. Analysis of the Role of Teacher’s Parenting Styles on Student Learning Motivation at State Vocational Schools in Surakarta

Author

Fika Adin Laila, Dwi Maryono, and Dwi Esti Wardani

Subjects
learning motivation, parenting style teacher, student relationships, teacher role, Education (General), L7-991
Abstract

The motivation of students to learn is greatly influenced by their teachers. Teachers are significant figures in the classroom who can uplift and mentor students. The parenting and teaching styles of educators can foster an atmosphere that encourages students to become motivated learners. A spirit of learning can be fostered by teachers who can offer constructive criticism, offer challenges that are appropriate for their student's abilities, and pay attention to each student's personal growth. The purpose of this research is to ascertain how teacher parenting influences students' motivation to learn. Teachers and students are the study's subjects, and a qualitative descriptive method is being used. Three methods were employed to acquire the data: observation, interviews, and documentation. Data analysis used descriptive qualitative data analysis. The results of the study show that the dominant teacher parenting in motivating student learning is democratic parenting. This parenting style emphasizes open communication, giving freedom of expression, and instilling positive values in students. Democratic parenting can increase student learning motivation because it can make students feel valued, recognized, and in control of themselves. In addition, democratic parenting can also shape students' positive characteristics, such as discipline, independence, and communication. These positive characteristics can support students in learning and achieving maximum achievement.

Published
2024
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50. Efficacy of a mitral regurgitation severity index to predict long‐term outcome in dogs with myxomatous mitral valve disease

Author

Michelle Vereb, Clarke E. Atkins, Darcy Adin, Thomas Blondel, Melissa Coffman, Seunggon Lee, Emilie Guillot, and Jessica L. Ward

Subjects
congestive heart failure, echocardiography, prognosis, thoracic radiographs, vertebral heart size, vertebral left atrial size, Veterinary medicine, SF600-1100
Abstract

Abstract Background Predicting progression of myxomatous mitral valve disease (MMVD) in dogs can be challenging. Hypothesis/Objectives The mitral regurgitation severity index (MRSI) will predict time to congestive heart failure (CHF) and all‐cause death in dogs with MMVD. Animals Eight hundred sixty‐nine client‐owned dogs. Methods Retrospective study pooling data from 4 previous samples including dogs with MMVD stage B2 or C. MRSI was calculated as: (heart rate [HR]/120) × left atrium‐to‐aorta ratio (LA:Ao) × (age in years/10) × 100. Alternative MRSI formulas substituting radiographic measures of left atrial size were also calculated. Cox proportional hazard modeling and time‐dependent receiver‐operator characteristic curves quantified prognostic performance. Results For Stage B2 pooled samples, MRSI > 156 was predictive of time to CHF (median 407 vs 1404 days; area under the curve [AUC] 0.68; hazard ratio 3.02 [95% CI 1.9‐4.9]; P 173 was predictive of all‐cause death (median survival 868 vs 1843 days; AUC 0.64; hazard ratio 4.26 [95% CI 2.4‐7.5]; P

Published
2024
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