3,901 results on '"Heimann P"'
Search Results
52. Painful Enlarging Cervical Mass in Young Male
- Author
-
Jacob Lawing, Jeremy Towns, and Matthew A. Heimann
- Subjects
Medical emergencies. Critical care. Intensive care. First aid ,RC86-88.9 - Abstract
Case Presentation: A 32-year-old male who recently immigrated from Kenya presented to the emergency department (ED) with a painful, enlarging, right-sided neck mass for eight weeks duration. Point-of-care ultrasound was used to reveal a large cystic mass with internal septations and numerous hypoechoic round lesions. Initial tuberculosis blood test ordered in the ED was positive with cultures ultimately growing Mycobaceterium tuberculosis. Discussion: Scrofula should be considered in the differential in patients presenting with enlarging neck masses who have epidemiological risk factors for tuberculosis.
- Published
- 2024
- Full Text
- View/download PDF
53. Behavior of soda-lime silicate glass under laser-driven shock compression up to 315 GPa
- Author
-
Madhavi, Meera, Jangid, Rahul, Christiansen-Salameh, Joyce, Cheng, Yu-Hsing, Rao, Pooja, Li, Jianheng, Botu, Surya Teja, Jeppson, Spencer, Mehta, Jugal, Smith, Scott, Isobe, Jared T, Hok, Sovanndara, Saha, Rahul, Cunningham, Eric, Heimann, Philip, Khaghani, Dimitri, Lee, Hae Ja, Spaulding, DK, Polsin, Danae N, Gleason, Arianna E, and Kukreja, Roopali
- Subjects
Engineering ,Mathematical Sciences ,Physical Sciences ,Applied Physics ,Mathematical sciences ,Physical sciences - Abstract
Shock experiments give a unique insight into the behavior of matter subjected to extremely high pressures and temperatures. Understanding the behavior of materials under such extreme conditions is key to modeling material failure and deformation dynamics under impact. While studies on pure silica are extensive, the shock behavior of other commercial silicates that contain additional oxides has not been systematically investigated. To better understand the role of composition in the dynamic behavior of silicates, we performed laser-driven dynamic compression experiments on soda-lime glass (SLG) up to 315 GPa. Using the accurate pulse shaping offered by the long pulse laser system at the Matter in Extreme Conditions end-station at the Linac Coherent Light Source, SLG was shock compressed along the Hugoniot to multiple pressure-temperature points. Velocity Interferometer System for Any Reflector was used to measure the velocity and determine the pressure inside the SLG. The U s -u p relationship obtained agrees well with the previous parallel plate impact studies. Within the error bars, no transformation to the crystalline phase was observed up to 70 GPa, which is in contrast to the behavior of pure silica under shock compression. Our studies show that the glass composition strongly influences the shock compression behavior of the silicate glasses.
- Published
- 2023
54. Impact of library information literacy training on entrepreneurship competition scores: A quantitative study at University of California, Irvine
- Author
-
Heimann, Sara
- Subjects
Behavioral and Social Science ,Academic libraries ,embedded librarianship ,entrepreneurship ,entrepreneurship competition ,information literacy ,Library and Information Studies ,Business and Management - Abstract
The University of California, Irvine’s (UCI) Innovation and Entrepreneurship Librarian partnered with UCI’s New Venture Competition to provide embedded research support for teams participating in the competition, including a research workshop and individual team research consultations. To assess the impact of these library services, a quantitative study of three years of competition scores was conducted involving a control group and two experimental groups; the difference in the experimental groups was the mode in which the services were provided: in-person and virtually. The study hypothesized that teams who received information literacy training (i.e., attended a research workshop and/or participated in a research consultation) earned higher Concept Paper scores, as well as higher evidence question scores (i.e., scores for a rubric question related to providing evidence in support of claims made in the Concept Paper), than teams who did not receive information literacy training. Statistical analysis showed significant increases in both Concept Paper scores and evidence question scores for both experimental groups when compared to the control group, indicating that information literacy training positively impacted teams’ performance. Additional analysis revealed no statistically significant differences in teams’ scores based on training delivery mode, in-person or virtual. The results are of value to librarians seeking to initiate partnerships with entrepreneurship competitions on campus, as well as entrepreneurship educators interested in enhancing existing entrepreneurship competitions by incorporating research and information literacy training.
- Published
- 2023
55. Jointly Resampling and Reconstructing Corrupted Images for Image Classification
- Author
-
Heimann, Viktoria, Spruck, Andreas, and Kaup, André
- Subjects
Electrical Engineering and Systems Science - Image and Video Processing - Abstract
Neural networks became the standard technique for image classification throughout the last years. They are extracting image features from a large number of images in a training phase. In a following test phase, the network is applied to the problem it was trained for and its performance is measured. In this paper, we focus on image classification. The amount of visual data that is interpreted by neural networks grows with the increasing usage of neural networks. Mostly, the visual data is transmitted from the application side to a central server where the interpretation is conducted. If the transmission is disturbed, losses occur in the transmitted images. These losses have to be reconstructed using postprocessing. In this paper, we incorporate the widely applied bilinear and bicubic interpolation and the high-quality reconstruction Frequency-Selective Reconstruction (FSR) for the reconstruction of corrupted images. However, we propose to use Frequency-Selective Mesh-to-Grid Resampling (FSMR) for the joint reconstruction and resizing of corrupted images. The performance in terms of classification accuracy of EfficientNetB0, DenseNet121, DenseNet201, ResNet50 and ResNet152 is examined. Results show that the reconstruction with FSMR leads to the highest classification accuracy for most networks. Average improvements of up to 6.7 percentage points are possible for DenseNet121., Comment: IEEE 24th International Workshop on Multimedia Signal Processing 2022
- Published
- 2022
56. Frame Rate Up-Conversion Using Key Point Agnostic Frequency-Selective Mesh-to-Grid Resampling
- Author
-
Heimann, Viktoria, Spruck, Andreas, and Kaup, André
- Subjects
Electrical Engineering and Systems Science - Image and Video Processing - Abstract
High frame rates are desired in many fields of application. As in many cases the frame repetition rate of an already captured video has to be increased, frame rate up-conversion (FRUC) is of high interest. We conduct a motion compensated approach. From two neighboring frames, the motion is estimated and the neighboring pixels are shifted along the motion vector into the frame to be reconstructed. For displaying, these irregularly distributed mesh pixels have to be resampled onto regularly spaced grid positions. We use the model-based key point agnostic frequency-selective mesh-to-grid resampling (AFSMR) for this task and show that AFSMR works best for applications that contain irregular meshes with varying densities. AFSMR gains up to 3.2 dB in contrast to the already high performing frequency-selective mesh-to-grid resampling (FSMR). Additionally, AFSMR increases the run time by a factor of 11 relative to FSMR., Comment: 5 pages, 4 figures, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2021
- Published
- 2022
- Full Text
- View/download PDF
57. Increasing the Accuracy of a Neural Network Using Frequency Selective Mesh-to-Grid Resampling
- Author
-
Spruck, Andreas, Heimann, Viktoria, and Kaup, André
- Subjects
Computer Science - Computer Vision and Pattern Recognition ,Electrical Engineering and Systems Science - Image and Video Processing - Abstract
Neural networks are widely used for almost any task of recognizing image content. Even though much effort has been put into investigating efficient network architectures, optimizers, and training strategies, the influence of image interpolation on the performance of neural networks is not well studied. Furthermore, research has shown that neural networks are often sensitive to minor changes in the input image leading to drastic drops of their performance. Therefore, we propose the use of keypoint agnostic frequency selective mesh-to-grid resampling (FSMR) for the processing of input data for neural networks in this paper. This model-based interpolation method already showed that it is capable of outperforming common interpolation methods in terms of PSNR. Using an extensive experimental evaluation we show that depending on the network architecture and classification task the application of FSMR during training aids the learning process. Furthermore, we show that the usage of FSMR in the application phase is beneficial. The classification accuracy can be increased by up to 4.31 percentage points for ResNet50 and the Oxflower17 dataset., Comment: accepted for IEEE International Symposium on Circuits and Systems (ISCAS). May 2022
- Published
- 2022
58. Learning capability of parametrized quantum circuits
- Author
-
Heimann, Dirk, Schönhoff, Gunnar, Mounzer, Elie, Hohenfeld, Hans, and Kirchner, Frank
- Subjects
Quantum Physics - Abstract
Variational quantum algorithms (VQAs) and their applications in the field of quantum machine learning through parametrized quantum circuits (PQCs) are thought to be one major way of leveraging noisy intermediate-scale quantum computing devices. However, differences in the performance of certain VQA architectures are often unclear since established best practices as well as detailed studies are missing. In this paper, we build upon the work by Schuld et al. and Vidal et al. and compare popular ans\"atze for PQCs through the new measure of learning capability. We also examine dissipative quantum neural networks (dQNN) as introduced by Beer et al. and propose a data re-upload structure for dQNNs to increase their learning capability. Comparing the results for the different PQC architectures, we can provide guidelines for designing efficient PQCs., Comment: 16+22 pages, 30 figures
- Published
- 2022
59. Modified Kapandji technique in pediatric displaced distal radius fractures: results in 195 patients
- Author
-
Bassi, Cristina, Heimann, Alexander F., Schwab, Joseph M., Tannast, Moritz, and Raabe, Ines
- Published
- 2024
- Full Text
- View/download PDF
60. Material calculation and its unconscious: approaching computerization with Heidegger and Lacan
- Author
-
Heimann, Marc and Hübener, Anne-Friederike
- Published
- 2023
- Full Text
- View/download PDF
61. Toward Socially Meaningful Case Conceptualization: The Risk-Driven Approach
- Author
-
Taylor, Rachel S., Colombo, Richard A., Wallace, Michele, Heimann, Benjamin, Benedickt, Ashton, and Moore, Allyson
- Published
- 2023
- Full Text
- View/download PDF
62. Small-scale hydrological patterns in a Siberian permafrost ecosystem affected by drainage
- Author
-
S. Raab, K. Castro-Morales, A. Hildebrandt, M. Heimann, J. E. Vonk, N. Zimov, and M. Goeckede
- Subjects
Ecology ,QH540-549.5 ,Life ,QH501-531 ,Geology ,QE1-996.5 - Abstract
Climate warming and associated accelerated permafrost thaw in the Arctic lead to a shift in landscape patterns, hydrologic conditions, and release of carbon. In this context, the lateral transport of carbon and shifts therein following thaw remain poorly understood. Crucial hydrologic factors affecting the lateral distribution of carbon include the depth of the saturated zone above the permafrost table with respect to changes in water table and thaw depth and the connectivity of water-saturated zones. Landscape conditions are expected to change in the future due to rising temperatures and polygonal or flat floodplain Arctic tundra areas in various states of degradation; hydrologic conditions will also change. This study is focused on an experimental site near Chersky, northeast Siberia, where a drainage ditch was constructed in 2004 to simulate landscape degradation features that result in drier soil conditions and channeled water flow. We compared water levels and thaw depths in the drained area (dry soil conditions) with those in an adjacent control area (wet soil conditions). We also identified the sources of water at the site via stable water isotope analysis. We found substantial spatiotemporal changes in the water conditions at the drained site: (i) lower water tables resulting in drier soil conditions, (ii) quicker water flow through drier areas, (iii) larger saturation zones in wetter areas, and (iv) a higher proportion of permafrost meltwater in the liquid phase towards the end of the growing season. These findings suggest decreased lateral connectivity throughout the drained area. Shifts in hydraulic connectivity in combination with a shift in vegetation abundance and water sources may impact carbon sources and sinks as well as transport pathways. Identifying lateral transport patterns in areas with degrading permafrost is therefore crucial.
- Published
- 2024
- Full Text
- View/download PDF
63. Differential Smad2/3 linker phosphorylation is a crosstalk mechanism of Rho/ROCK and canonical TGF-β3 signaling in tenogenic differentiation
- Author
-
Michaela Melzer, Sabine Niebert, Manuela Heimann, Franziska Ullm, Tilo Pompe, Georgios Scheiner-Bobis, and Janina Burk
- Subjects
Tenogenic differentiation ,Mesenchymal stem cells ,Linker phosphorylation ,Smad ,Medicine ,Science - Abstract
Abstract The transforming growth factor (TGF)-β3 is a well-known inducer for tenogenic differentiation, signaling via the Smad2/3 pathway. Furthermore, other factors like extracellular matrix or mechanical force can induce tenogenic differentiation and possibly alter the response to TGF-β3 by signaling via the Rho/ROCK pathway. The aim of this study was to investigate the interplay of Rho/ROCK and TGF-β3/Smad signaling in tenogenic differentiation, with the Smad2/3 molecule hypothesized as a possible interface. Cultured as monolayers or on collagen I matrices, mesenchymal stromal cells (MSC) were treated with the ROCK inhibitor Y-27632 (10 µM), TGF-β3 (10 ng/ml) or both combined. Control cells were cultured accordingly, without Y-27632 and/or without TGF-β3. At different time points, MSC were analyzed by real-time RT-PCR, immunofluorescence, and Western blot. Cultivation of MSC on collagen matrices and ROCK inhibition supported tenogenic differentiation and fostered the effect of TGF-β3. The phosphorylation of the linker region of Smad2 was reduced by cultivation on collagen matrices, but not by ROCK inhibition. The latter, however, led to increased phosphorylation of the linker region of Smad3. In conclusion, collagen matrices and the Rho/ROCK signaling pathway influence the TGF-β3/Smad2/3 pathway by regulating different phosphorylation sites of the Smad linker region.
- Published
- 2024
- Full Text
- View/download PDF
64. Patients with Leptomeningeal Carcinomatosis and Hydrocephalus-Feasibility of Combined Ventriculoperitoneal Shunt and Reservoir Insertion for Intrathecal Chemotherapy
- Author
-
Matthias Schneider, Christian Wispel, Anna-Laura Potthoff, Muriel Heimann, Valeri Borger, Christina Schaub, Ulrich Herrlinger, Hartmut Vatter, Patrick Schuss, and Niklas Schäfer
- Subjects
brain metastasis ,leptomeningeal carcinomatosis ,intrathecal chemotherapy ,ventriculoperitoneal shunt ,hydrocephalus ,Rickham reservoir ,Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,RC254-282 - Abstract
Therapeutic management of patients with leptomeningeal carcinomatosis (LC) may require treatment of concomitant hydrocephalus (HC) in addition to intrathecal chemotherapy (ITC). Ventriculoperitoneal shunts (VPS) equipped with a valve for manual deactivation of shunt function and a concomitant reservoir for application of ITC pose an elegant solution to both problems. The present study evaluates indication, feasibility, and safety of such a modified shunt/reservoir design (mS/R). All patients with LC aged ≥ 18 years who had undergone mS/R implantation between 2013 and 2020 at the authors’ institution were further analyzed. ITC was indicated following the recommendation of the neuro-oncological tumor board and performed according to a standardized protocol. Sixteen patients with LC underwent mS/R implantation for subsequent ITC and concomitant treatment of HC. Regarding HC-related clinical symptoms, 69% of patients preoperatively exhibited lethargy, 38% cognitive impairment, and 38% (additional) visual disturbances. Postoperatively, 86% of patients achieved subjective improvement of HC-related symptoms. Overall, postoperative complications occurred in three patients (19%). No patient encountered cancer treatment-related complications. The present study describes a combination procedure consisting of a standard VPS-system and a standard reservoir for patients suffering from LC and HC. No cancer treatment-related complications occurred, indicating straightforward handling and thus safety.
- Published
- 2024
- Full Text
- View/download PDF
65. Fast Track Adaptation of Oncolytic Coxsackie B3 Virus to Resistant Colorectal Cancer Cells - a Method to Personalize Virotherapy
- Author
-
Leslie Elsner, Lisanne Heimann, Anja Geisler, Babette Dieringer, Klaus-Peter Knoch, Luisa Hinze, Karin Klingel, Michel Solimena, Jens Kurreck, and Henry Fechner
- Subjects
Cancer Therapy ,Oncolytic Virus ,Personalized Therapy ,Colorectal Carcinoma ,Direct Virus Evolution ,Coxsackievirus B3 ,Medicine (General) ,R5-920 ,Biology (General) ,QH301-705.5 - Abstract
Abstract Background The efficacy of oncolytic viruses (OV) in cancer treatment depends on their ability to successfully infect and destroy tumor cells. However, patients’ tumors vary, and in the case of individual insensitivity to an OV, therapeutic efficacy is limited. Here, we present a protocol for rapid generation of tumor cell-specific adapted oncolytic coxsackievirus B3 (CVB3) with enhanced oncolytic potential and a satisfactory safety profile. This is achieved by combining directed viral evolution (DVE) with genetic modification of the viral genome and the use of a microRNA-dependent regulatory tool. Methods The oncolytic CVB3 variant PD-H was adapted to the refractory colorectal carcinoma cell line Colo320 through serial passaging. XTT assays and virus plaque assays were used to determine virus cytotoxicity and virus replication in vitro. Recombinant PD-H variants were generated through virus mutagenesis. Apoptosis was detected by Western blots, Caspase 3/7 assays, and DAPI staining. The therapeutic efficacy and safety of the adapted recombinant OV PD-SK-375TS were assessed in vivo using a subcutaneous Colo320 xenograft mouse model. Results PD-H was adapted to the colorectal cancer cell line Colo320 within 10 passages. Sequencing of passage 10 virus P-10 revealed a heterogenous virus population with five nucleotide mutations resulting in amino acid substitutions. The genotypically homogeneous OV PD-SK was generated by inserting the five detected mutations of P-10 into the genome of PD-H. PD-SK showed significantly stronger replication and cytotoxicity than PD-H in Colo320 cells, but not in other colorectal carcinoma cell lines. Increase of apoptosis induction was detected as key mechanisms of Colo320 cell-specific adaptation of PD-SK. For in vivo safety PD-SK was engineered with target sites of the miR-375 (miR-375TS) to exclude virus replication in normal tissues. PD-SK-375TS, unlike the PD-H-375TS not adapted homolog suppressed the growth of subcutaneous Colo320 tumors in nude mice without causing any side effects. Conclusion Taken together, here we present an optimized protocol for the rapid generation of tumor cell-specific adapted oncolytic CVB3 based on the oncolytic CVB3 strain PD-H. The protocol is promising for the generation of personalized OV for tumor therapy and has the potential to be applied to other OV.
- Published
- 2024
- Full Text
- View/download PDF
66. CAPER: Coarsen, Align, Project, Refine - A General Multilevel Framework for Network Alignment
- Author
-
Zhu, Jing, Koutra, Danai, and Heimann, Mark
- Subjects
Computer Science - Social and Information Networks ,Computer Science - Information Retrieval ,Computer Science - Machine Learning - Abstract
Network alignment, or the task of finding corresponding nodes in different networks, is an important problem formulation in many application domains. We propose CAPER, a multilevel alignment framework that Coarsens the input graphs, Aligns the coarsened graphs, Projects the alignment solution to finer levels and Refines the alignment solution. We show that CAPER can improve upon many different existing network alignment algorithms by enforcing alignment consistency across multiple graph resolutions: nodes matched at finer levels should also be matched at coarser levels. CAPER also accelerates the use of slower network alignment methods, at the modest cost of linear-time coarsening and refinement steps, by allowing them to be run on smaller coarsened versions of the input graphs. Experiments show that CAPER can improve upon diverse network alignment methods by an average of 33% in accuracy and/or an order of magnitude faster in runtime., Comment: CIKM 2022
- Published
- 2022
- Full Text
- View/download PDF
67. Analyzing Data-Centric Properties for Graph Contrastive Learning
- Author
-
Trivedi, Puja, Lubana, Ekdeep Singh, Heimann, Mark, Koutra, Danai, and Thiagarajan, Jayaraman J.
- Subjects
Computer Science - Machine Learning - Abstract
Recent analyses of self-supervised learning (SSL) find the following data-centric properties to be critical for learning good representations: invariance to task-irrelevant semantics, separability of classes in some latent space, and recoverability of labels from augmented samples. However, given their discrete, non-Euclidean nature, graph datasets and graph SSL methods are unlikely to satisfy these properties. This raises the question: how do graph SSL methods, such as contrastive learning (CL), work well? To systematically probe this question, we perform a generalization analysis for CL when using generic graph augmentations (GGAs), with a focus on data-centric properties. Our analysis yields formal insights into the limitations of GGAs and the necessity of task-relevant augmentations. As we empirically show, GGAs do not induce task-relevant invariances on common benchmark datasets, leading to only marginal gains over naive, untrained baselines. Our theory motivates a synthetic data generation process that enables control over task-relevant information and boasts pre-defined optimal augmentations. This flexible benchmark helps us identify yet unrecognized limitations in advanced augmentation techniques (e.g., automated methods). Overall, our work rigorously contextualizes, both empirically and theoretically, the effects of data-centric properties on augmentation strategies and learning paradigms for graph SSL., Comment: Accepted to NeurIPS 2022
- Published
- 2022
68. Contrastive Knowledge-Augmented Meta-Learning for Few-Shot Classification
- Author
-
Subramanyam, Rakshith, Heimann, Mark, Thathachar, Jayram, Anirudh, Rushil, and Thiagarajan, Jayaraman J.
- Subjects
Computer Science - Machine Learning - Abstract
Model agnostic meta-learning algorithms aim to infer priors from several observed tasks that can then be used to adapt to a new task with few examples. Given the inherent diversity of tasks arising in existing benchmarks, recent methods use separate, learnable structure, such as hierarchies or graphs, for enabling task-specific adaptation of the prior. While these approaches have produced significantly better meta learners, our goal is to improve their performance when the heterogeneous task distribution contains challenging distribution shifts and semantic disparities. To this end, we introduce CAML (Contrastive Knowledge-Augmented Meta Learning), a novel approach for knowledge-enhanced few-shot learning that evolves a knowledge graph to effectively encode historical experience, and employs a contrastive distillation strategy to leverage the encoded knowledge for task-aware modulation of the base learner. Using standard benchmarks, we evaluate the performance of CAML in different few-shot learning scenarios. In addition to the standard few-shot task adaptation, we also consider the more challenging multi-domain task adaptation and few-shot dataset generalization settings in our empirical studies. Our results shows that CAML consistently outperforms best known approaches and achieves improved generalization.
- Published
- 2022
69. On Graph Neural Network Fairness in the Presence of Heterophilous Neighborhoods
- Author
-
Loveland, Donald, Zhu, Jiong, Heimann, Mark, Fish, Ben, Schaub, Michael T., and Koutra, Danai
- Subjects
Computer Science - Social and Information Networks ,Computer Science - Computers and Society ,Computer Science - Machine Learning - Abstract
We study the task of node classification for graph neural networks (GNNs) and establish a connection between group fairness, as measured by statistical parity and equal opportunity, and local assortativity, i.e., the tendency of linked nodes to have similar attributes. Such assortativity is often induced by homophily, the tendency for nodes of similar properties to connect. Homophily can be common in social networks where systemic factors have forced individuals into communities which share a sensitive attribute. Through synthetic graphs, we study the interplay between locally occurring homophily and fair predictions, finding that not all node neighborhoods are equal in this respect -- neighborhoods dominated by one category of a sensitive attribute often struggle to obtain fair treatment, especially in the case of diverging local class and sensitive attribute homophily. After determining that a relationship between local homophily and fairness exists, we investigate if the issue of unfairness can be associated to the design of the applied GNN model. We show that by adopting heterophilous GNN designs capable of handling disassortative group labels, group fairness in locally heterophilous neighborhoods can be improved by up to 25% over homophilous designs in real and synthetic datasets., Comment: 6 pages, KDD 2022 DLG Workshop
- Published
- 2022
70. Emerging Patterns in the Continuum Representation of Protein-Lipid Fingerprints
- Author
-
Georgouli, Konstantia, Ingólfsson, Helgi I, Aydin, Fikret, Heimann, Mark, Lightstone, Felice C, Bremer, Peer-Timo, and Bhatia, Harsh
- Subjects
Quantitative Biology - Quantitative Methods ,Computer Science - Machine Learning - Abstract
Capturing intricate biological phenomena often requires multiscale modeling where coarse and inexpensive models are developed using limited components of expensive and high-fidelity models. Here, we consider such a multiscale framework in the context of cancer biology and address the challenge of evaluating the descriptive capabilities of a continuum model developed using 1-dimensional statistics from a molecular dynamics model. Using deep learning, we develop a highly predictive classification model that identifies complex and emergent behavior from the continuum model. With over 99.9% accuracy demonstrated for two simulations, our approach confirms the existence of protein-specific "lipid fingerprints", i.e. spatial rearrangements of lipids in response to proteins of interest. Through this demonstration, our model also provides external validation of the continuum model, affirms the value of such multiscale modeling, and can foster new insights through further analysis of these fingerprints.
- Published
- 2022
71. End-to-end Learning for Image-based Detection of Molecular Alterations in Digital Pathology
- Author
-
Teichmann, Marvin, Aichert, Andre, Bohnenberger, Hanibal, Ströbel, Philipp, and Heimann, Tobias
- Subjects
Computer Science - Computer Vision and Pattern Recognition ,Electrical Engineering and Systems Science - Image and Video Processing ,Quantitative Biology - Quantitative Methods - Abstract
Current approaches for classification of whole slide images (WSI) in digital pathology predominantly utilize a two-stage learning pipeline. The first stage identifies areas of interest (e.g. tumor tissue), while the second stage processes cropped tiles from these areas in a supervised fashion. During inference, a large number of tiles are combined into a unified prediction for the entire slide. A major drawback of such approaches is the requirement for task-specific auxiliary labels which are not acquired in clinical routine. We propose a novel learning pipeline for WSI classification that is trainable end-to-end and does not require any auxiliary annotations. We apply our approach to predict molecular alterations for a number of different use-cases, including detection of microsatellite instability in colorectal tumors and prediction of specific mutations for colon, lung, and breast cancer cases from The Cancer Genome Atlas. Results reach AUC scores of up to 94% and are shown to be competitive with state of the art two-stage pipelines. We believe our approach can facilitate future research in digital pathology and contribute to solve a large range of problems around the prediction of cancer phenotypes, hopefully enabling personalized therapies for more patients in future., Comment: MICCAI 2022; 8.5 Pages, 4 Figures
- Published
- 2022
72. Reconstructing early human symbolic evolution using transmission experiments
- Author
-
Tylen, Kristian, Qvist, Aske Svane, Kjeldsen, Rebecca Foss, Rojo, Sergio, Heimann, Katrin, Fay, Nicolas, Johannsen, Niels N., Riede, Felix, Lombard, Marlize, and Fusaroli, Riccardo
- Subjects
Anthropology ,Psychology ,Aesthetics ,Culture ,Evolution ,Perception ,Computer-based experiment - Abstract
Engraved ochres and ostrich eggshells from the South African Blombos Cave and Diepkloof Rock Shelter are among the earliest expressions of human symbolic behavior. Furthermore, they appear to document a continuous practice of abstract mark-making across ~40.000 years. During this time, the engraved patterns change from simpler unstructured patterns to complex, ordered and symmetric cross-hatchings. To inform discussions of the possible function of the engravings, we conducted a two-part experimental study. Based on the assumption that the pragmatic use of an artifact will motivate incremental adaptive refinements, we used transmission chain experiments to reconstruct the original trajectory of changes. We then conducted five experiments to assess the cognitive implications of changes to the patterns and compared these to the original engravings. Although we observe interesting similarities, our findings suggest the Blombos and Diepkloof engravings are not only a product of human cognitive biases and constraints on working memory.
- Published
- 2023
73. Analytic pipelines to assess the relationship between immune response and germline genetics in human tumors.
- Author
-
Sayaman, Rosalyn W, Saad, Mohamad, Heimann, Carolina, Hu, Donglei, Kunji, Khalid, Roelands, Jessica, Wolf, Denise M, Huntsman, Scott, Ceccarelli, Michele, Thorsson, Vésteinn, Ziv, Elad, and Bedognetti, Davide
- Subjects
Germ Cells ,Humans ,Neoplasms ,Immunity ,Genome ,Genome-Wide Association Study ,Bioinformatics ,Cancer ,Gene expression ,Genetics ,Genomics ,Immunology ,Clinical Research ,Human Genome ,Immunization ,Genetic Testing ,Vaccine Related ,Aetiology ,2.1 Biological and endogenous factors ,Good Health and Well Being - Abstract
Germline genetic variants modulate human immune response. We present analytical pipelines for assessing the contribution of hosts' genetic background to the immune landscape of solid tumors using harmonized data from more than 9,000 patients in The Cancer Genome Atlas (TCGA). These include protocols for heritability, genome-wide association studies (GWAS), colocalization, and rare variant analyses. These workflows are developed around the structure of TCGA but can be adapted to explore other repositories or in the context of cancer immunotherapy. For complete details on the use and execution of this protocol, please refer to Sayaman et al. (2021).
- Published
- 2022
74. Transformational Experiences. The Role of Immersive Arts and Media in Individual and Societal Change
- Author
-
Federica Cavaletti and Katrin Heimann
- Subjects
Virtual reality ,Contemporary art ,Discrimination ,Climate change ,Attitude change ,Visual arts ,N1-9211 ,History of the arts ,NX440-632 - Abstract
We live in times of humanitarian and environmental crises. The effects of climate change add to the economic, physical, and mental suffering caused by social discrimination, in the form of gender, class, and race inequalities. Encounters with and creation of arts have been suggested as a potential remedy, allowing to stay with the trouble rather than running from it, and imagining a different future rather than manifesting the past. But what are the concrete chances that all this really happens? Similar questions can be raised in relation to immersive media. The latter have been claimed to possess an unprecedented prosocial potential. However, what are the appropriate strategies to ensure that such potential is actually expressed? For this issue of AN-ICON. Studies in Environmental Images, we selected diverse contributions investigating the role of the arts and media in rethinking (and acting upon) societal and environmental problems, focussing on immersive experiences in particular.
- Published
- 2024
- Full Text
- View/download PDF
75. Neues Regionalnetzwerk OW
- Author
-
Regina Heimann
- Subjects
General Works - Published
- 2024
- Full Text
- View/download PDF
76. Gestational age at birth, birth weight, and gestational age when intrauterine brain sparing occurs determines the neonatal outcome in growth-restricted infants born before 32 weeks of gestation: a retrospective cohort analysis
- Author
-
Franziska Köber, Yvonne Heimann, Thomas Lehmann, Ekkehard Schleußner, Hans Proquitté, and Tanja Groten
- Subjects
fetal growth restriction ,preterm birth ,very low birth weight ,very preterm birth ,brain sparing ,pentaerythrityl tetranitrate (PETN) ,Pediatrics ,RJ1-570 - Abstract
BackgroundPreterm birth and fetal growth restriction are the main determinants of perinatal mortality. In the absence of therapeutic interventions, management is restricted to the observation of fetal growth and fetoplacental perfusion to determine the timing of delivery. Fetal circulatory redistribution, known as “brain sparing,” represents a sign of fetal hypoxia and has been implemented in algorithms for when to deliver. In the absence of any other option, the nitric oxide donor pentaerythrityl tetranitrate (PETN), which has been shown to improve fetoplacental flow and reduce preterm birth in high-risk patients, is offered to patients as a personal therapy attempt. The aim of this study was to evaluate determinants related to pregnancy, including PETN intake during pregnancy, on immediate neonatal outcomes in a cohort of growth-restricted infants born before 32 completed weeks of gestation.MethodsWe performed a retrospective cohort study of 98 infants born with a birth weight below the 10th percentile before 32 completed weeks of gestation at our tertiary care center between 2010 and 2019. PETN was offered to all mothers with a history of severe adverse pregnancy outcomes who were at high risk of developing fetal growth restriction as an individual therapy attempt.ResultsThe mean gestational age at birth was 188.5 days, and the mean birth weight was 549 g, corresponding to a median percentile of three. In 73 (79.3%) cases, brain sparing occurred during pregnancy. A total of 22 (22.4%) neonates were stillborn, 20 died postnatally, and 37.3% developed a severe complication. Multivariable analysis revealed birth weight percentile, gestational age at birth, and gestational age when brain sparing first occurred to be robust predictors of mortality or severe neonatal morbidity. In 39 neonates of mothers taking PETN, this impact of brain sparing was not observed.ConclusionOur study is the first to demonstrate a significant association between the early occurrence of brain-sparing and severe neonatal outcomes in a cohort of very early preterm, growth-restricted newborns. The data suggest that PETN intake may ameliorate the effect of brain sparing in the affected neonates.
- Published
- 2024
- Full Text
- View/download PDF
77. Deep learning-based classification of erosion, synovitis and osteitis in hand MRI of patients with inflammatory arthritis
- Author
-
Chang Liu, Georg Schett, Michael Uder, Filippo Fagni, Arnd Kleyer, Frank Roemer, David Simon, Sara Bayat, Melek Yalcin Mutlu, Maja Schlereth, Jonas Utz, Tobias Heimann, Jingna Qiu, Chris Ehring, and Katharina Breininger
- Subjects
Medicine - Abstract
Objectives To train, test and validate the performance of a convolutional neural network (CNN)-based approach for the automated assessment of bone erosions, osteitis and synovitis in hand MRI of patients with inflammatory arthritis.Methods Hand MRIs (coronal T1-weighted, T2-weighted fat-suppressed, T1-weighted fat-suppressed contrast-enhanced) of rheumatoid arthritis (RA) and psoriatic arthritis (PsA) patients from the rheumatology department of the Erlangen University Hospital were assessed by two expert rheumatologists using the Outcome Measures in Rheumatology-validated RA MRI Scoring System and PsA MRI Scoring System scores and were used to train, validate and test CNNs to automatically score erosions, osteitis and synovitis. Scoring performance was compared with human annotations in terms of macro-area under the receiver operating characteristic curve (AUC) and balanced accuracy using fivefold cross-validation. Validation was performed on an independent dataset of MRIs from a second patient cohort.Results In total, 211 MRIs from 112 patients (14 906 region of interests (ROIs)) were included for training/internal validation using cross-validation and 220 MRIs from 75 patients (11 040 ROIs) for external validation of the networks. The networks achieved high mean (SD) macro-AUC of 92%±1% for erosions, 91%±2% for osteitis and 85%±2% for synovitis. Compared with human annotation, CNNs achieved a high mean Spearman correlation for erosions (90±2%), osteitis (78±8%) and synovitis (69±7%), which remained consistent in the validation dataset.Conclusions We developed a CNN-based automated scoring system that allowed a rapid grading of erosions, osteitis and synovitis with good diagnostic accuracy and using less MRI sequences compared with conventional scoring. This CNN-based approach may help develop standardised cost-efficient and time-efficient assessments of hand MRIs for patients with arthritis.
- Published
- 2024
- Full Text
- View/download PDF
78. Characterization and modulation of the pro‐inflammatory effects of immune cells in the canine intervertebral disk
- Author
-
Mary K. Heimann, Kelly Thompson, Gilian Gunsch, Shirley N. Tang, Brett Klamer, Kara Corps, Benjamin A. Walter, Sarah A. Moore, and Devina Purmessur
- Subjects
canine ,cromolyn sodium ,degeneration ,intervertebral disk ,low back pain ,macrophage ,Orthopedic surgery ,RD701-811 - Abstract
Abstract Background Intervertebral disk (IVD) degeneration affects both humans and canines and is a major cause of low back pain (LBP). Mast cell (MC) and macrophage (MØ) infiltration has been identified in the pathogenesis of IVD degeneration (IVDD) in the human and rodent model but remains understudied in the canine. MC degranulation in the IVD leads to a pro‐inflammatory cascade and activates protease activated receptor 2 (PAR2) on IVD cells. The objectives of the present study are to: (1) highlight the pathophysiological changes observed in the degenerate canine IVD, (2) further characterize the inflammatory effect of MCs co‐cultured with canine nucleus pulposus (NP) cells, (3) evaluate the effect of construct stiffness on NP and MCs, and (4) identify potential therapeutics to mitigate pathologic changes in the IVD microenvironment. Methods Canine IVD tissue was isolated from healthy autopsy research dogs (beagle) and pet dogs undergoing laminectomy for IVD herniation. Morphology, protein content, and inflammatory markers were assessed. NP cells isolated from healthy autopsy (Mongrel hounds) tissue were co‐cultured with canine MCs within agarose constructs and treated with cromolyn sodium (CS) and PAR2 antagonist (PAR2A). Gene expression, sulfated glycosaminoglycan content, and stiffness of constructs were assessed. Results CD 31+ blood vessels, mast cell tryptase, and macrophage CD 163+ were increased in the degenerate surgical canine tissue compared to healthy autopsy. Pro‐inflammatory genes were upregulated when canine NP cells were co‐cultured with MCs and the stiffer microenvironment enhanced these effects. Treatment with CS and PAR2 inhibitors mediated key pro‐inflammatory markers in canine NP cells. Conclusion There is increased MC, MØs, and vascular ingrowth in the degenerate canine IVD tissue, similar to observations in the clinical population with IVDD and LBP. MCs co‐cultured with canine NP cells drive inflammation, and CS and PAR2A are potential therapeutics that may mitigate the pathophysiology of IVDD in vitro.
- Published
- 2024
- Full Text
- View/download PDF
79. Comparison of seasonal viral prevalence supports honey bees as potential spring pathogen reservoirs for bumble bees
- Author
-
Briana E. Wham, Elyse C. McCormick, Casey M. Carr, Nicole R. Bracci, Ashley C. Heimann, Timothy J. Egner, M. Jesse Schneider, and Heather M. Hines
- Subjects
Apis ,Bombus ,pathogen ,seasonality ,transmission ,Ecology ,QH540-549.5 - Abstract
Abstract Bee declines pose a serious risk to agricultural sustainability, wild plant diversity, and the commercial bee industry, generating local and global concerns about bee health. Parasites, including micro‐parasites and macro‐parasites, negatively impact bee population dynamics. Management of parasites requires an understanding of the cyclic trends in prevalence and the factors impacting these patterns. In this study, we advance understanding of parasite epidemiology and transmission among members of the bee community toward the goal of improving predictability of parasite prevalence seasonally. Honey bees and bumble bees were collected throughout an active season and across multiple overwintering periods. These bees were molecularly tested for two common bee viruses—deformed wing virus (DWV) and black queen cell virus (BQCV)—and morphologically screened for Vairimorpha spp., nematodes, and parasitic flies to determine whether these parasites exhibit unique seasonal trends, if overwintering behavior impacts parasite survival, and how these patterns differ between honey bees and bumble bees. The results suggest consistent seasonal trends between honey bees and bumble bees; however, these trends are parasite‐specific. Honey bees consistently exhibited a higher magnitude of viral prevalence compared with bumble bees. Both honey bees and bumble bees reduced viral prevalence over the winter; however, only in bumble bees did this drop to negligible prevalence each spring. These data suggest that honey bees may have a larger impact on parasite transmission, as they pose to reinfect bees which otherwise would have very low prevalence each spring and sustain high levels of infection in communities year‐round.
- Published
- 2024
- Full Text
- View/download PDF
80. Frequency-Selective Geometry Upsampling of Point Clouds
- Author
-
Heimann, Viktoria, Spruck, Andreas, and Kaup, André
- Subjects
Electrical Engineering and Systems Science - Image and Video Processing ,Computer Science - Computer Vision and Pattern Recognition - Abstract
The demand for high-resolution point clouds has increased throughout the last years. However, capturing high-resolution point clouds is expensive and thus, frequently replaced by upsampling of low-resolution data. Most state-of-the-art methods are either restricted to a rastered grid, incorporate normal vectors, or are trained for a single use case. We propose to use the frequency selectivity principle, where a frequency model is estimated locally that approximates the surface of the point cloud. Then, additional points are inserted into the approximated surface. Our novel frequency-selective geometry upsampling shows superior results in terms of subjective as well as objective quality compared to state-of-the-art methods for scaling factors of 2 and 4. On average, our proposed method shows a 4.4 times smaller point-to-point error than the second best state-of-the-art PU-Net for a scale factor of 4., Comment: 5 pages, 3 figures, International Conference on Image Processing (ICIP) 2022
- Published
- 2022
- Full Text
- View/download PDF
81. Frequency-Selective Mesh-to-Mesh Resampling for Color Upsampling of Point Clouds
- Author
-
Heimann, Viktoria, Spruck, Andreas, and Kaup, André
- Subjects
Electrical Engineering and Systems Science - Image and Video Processing - Abstract
With the increased use of virtual and augmented reality applications, the importance of point cloud data rises. High-quality capturing of point clouds is still expensive and thus, the need for point cloud super-resolution or point cloud upsampling techniques emerges. In this paper, we propose an interpolation scheme for color upsampling of three-dimensional color point clouds. As a point cloud represents an object's surface in three-dimensional space, we first conduct a local transform of the surface into a two-dimensional plane. Secondly, we propose to apply a novel Frequency-Selective Mesh-to-Mesh Resampling (FSMMR) technique for the interpolation of the points in 2D. FSMMR generates a model of weighted superpositions of basis functions on scattered points. This model is then evaluated for the final points in order to increase the resolution of the original point cloud. Evaluation shows that our approach outperforms common interpolation schemes. Visual comparisons of the jaguar point cloud underlines the quality of our upsampling results. The high performance of FSMMR holds for various sampling densities of the input point cloud., Comment: 6 pages, 8 figures, MMSP 2021
- Published
- 2022
- Full Text
- View/download PDF
82. Key Point Agnostic Frequency-Selective Mesh-to-Grid Image Resampling using Spectral Weighting
- Author
-
Heimann, Viktoria, Genser, Nils, and Kaup, André
- Subjects
Electrical Engineering and Systems Science - Image and Video Processing - Abstract
Many applications in image processing require resampling of arbitrarily located samples onto regular grid positions. This is important in frame-rate up-conversion, super-resolution, and image warping among others. A state-of-the-art high quality model-based resampling technique is frequency-selective mesh-to-grid resampling which requires pre-estimation of key points. In this paper, we propose a new key point agnostic frequency-selective mesh-to-grid resampling that does not depend on pre-estimated key points. Hence, the number of data points that are included is reduced drastically and the run time decreases significantly. To compensate for the key points, a spectral weighting function is introduced that models the optical transfer function in order to favor low frequencies more than high ones. Thereby, resampling artefacts like ringing are supressed reliably and the resampling quality increases. On average, the new AFSMR is conceptually simpler and gains up to 1.2 dB in terms of PSNR compared to the original mesh-to-grid resampling while being approximately 14.5 times faster., Comment: 6 pages, 5 figures; Originally submitted to IEEE MMSP 2020
- Published
- 2022
- Full Text
- View/download PDF
83. Quantum Deep Reinforcement Learning for Robot Navigation Tasks
- Author
-
Hans Hohenfeld, Dirk Heimann, Felix Wiebe, and Frank Kirchner
- Subjects
Reinforcement learning ,autonomous agents ,robotics ,quantum machine learning ,quantum computing ,Electrical engineering. Electronics. Nuclear engineering ,TK1-9971 - Abstract
We utilize hybrid quantum deep reinforcement learning to learn navigation tasks for a simple, wheeled robot in simulated environments of increasing complexity. For this, we train parameterized quantum circuits (PQCs) with two different encoding strategies in a hybrid quantum-classical setup as well as a classical neural network baseline with the double deep Q network (DDQN) reinforcement learning algorithm. Quantum deep reinforcement learning (QDRL) has previously been studied in several relatively simple benchmark environments, mainly from the OpenAI gym suite. However, scaling behavior and applicability of QDRL to more demanding tasks closer to real-world problems e.g., from the robotics domain, have not been studied previously. Here, we show that quantum circuits in hybrid quantum-classic reinforcement learning setups are capable of learning optimal policies in multiple robotic navigation scenarios with notably fewer trainable parameters compared to a classical baseline. Across a large number of experimental configurations, we find that the employed quantum circuits outperform the classical neural network baselines when equating for the number of trainable parameters. Yet, the classical neural network consistently showed better results concerning training times and stability, with at least one order of magnitude of trainable parameters more than the best-performing quantum circuits. However, validating the robustness of the learning methods in a large and dynamic environment, we find that the classical baseline produces more stable and better performing policies overall. For the two encoding schemes, we observed better results for consecutively encoding the classical state vector on each qubit compared to encoding each component on a separate qubit. Our findings demonstrate that current hybrid quantum machine-learning approaches can be scaled to simple robotic problems while yielding sufficient results, at least in an idealized simulated setting, but there are yet open questions regarding the application to considerably more demanding tasks. We anticipate that our work will contribute to introducing quantum machine learning in general and quantum deep reinforcement learning in particular to more demanding problem domains and emphasize the importance of encoding techniques for classic data in hybrid quantum-classical settings.
- Published
- 2024
- Full Text
- View/download PDF
84. Foot lesions and forelimb skin abrasions in suckling piglets: development and risk factors
- Author
-
Marcus Heimann, Maria Hartmann, Fritjof Freise, Lothar Kreienbrock, and Elisabeth grosse Beilage
- Subjects
Heel bruising ,Sole bruising ,Erosion ,Floor ,Animal welfare ,SINS ,Animal culture ,SF1-1100 ,Veterinary medicine ,SF600-1100 - Abstract
Abstract Background Foot lesions in suckling piglets have been associated with poor flooring in several studies and were recently proposed to be indicative of swine inflammatory and necrosis syndrome. However, identical findings are also the typical outcome of various non-infectious causes; thus, further risk analysis is needed. The objective of this study was to describe the development of heel bruising, coronary band lesions and forelimb skin abrasion in suckling pigs up to 5 days of age. Furthermore, the effects of various intrinsic and extrinsic factors were examined. On each of four commercial piglet-producing farms, piglets from two or three batches of eight sows were studied. The piglets were included within 18 h after birth. Each piglet was individually scored four times. The score for the heels differentiated six (0–5) and for the coronary band and forelimb skin abrasion three stages (0–2). The body weight was measured two times. The effect of the floor was estimated by allocating the sows randomly to farrowing pens equipped with either soft rubber mats covered with litter or fully slatted plastic floors. Results The final analysis comprised data from 1045 piglets. Foot lesions were not found at birth but started to develop on day 1. On day 5, heel bruising was found in 94%, main claw coronary band lesions in 49% and forelimb skin abrasion in 73% of the piglets. In a multifactorial logistic regression analysis, it was shown that a slatted plastic floor significantly increased the odds of heel bruising and coronary band lesions, while a rubber floor with litter increased the odds of forelimb skin abrasions. Conclusion Foot and forelimb lesions in new-born piglets are mainly induced by the floor. The effect of slatted plastic floors on heel bruising showed an overwhelming OR of 52.89 (CI 26.29–106.43). Notably, coronary band lesions in young suckling piglets occur on slatted as well as non-slatted floors, indicating that the piglets incur these injuries not only from the wedging of their feet into the gaps between slats but also from contact with the floor while suckling. Based on these findings, preventive measures should be redirected to the improvement of the floor in the farrowing pen, particularly in the area under the sow’s udder.
- Published
- 2024
- Full Text
- View/download PDF
85. Quantum Deep Reinforcement Learning for Robot Navigation Tasks
- Author
-
Hohenfeld, Hans, Heimann, Dirk, Wiebe, Felix, and Kirchner, Frank
- Subjects
Computer Science - Robotics ,Computer Science - Machine Learning ,Quantum Physics - Abstract
We utilize hybrid quantum deep reinforcement learning to learn navigation tasks for a simple, wheeled robot in simulated environments of increasing complexity. For this, we train parameterized quantum circuits (PQCs) with two different encoding strategies in a hybrid quantum-classical setup as well as a classical neural network baseline with the double deep Q network (DDQN) reinforcement learning algorithm. Quantum deep reinforcement learning (QDRL) has previously been studied in several relatively simple benchmark environments, mainly from the OpenAI gym suite. However, scaling behavior and applicability of QDRL to more demanding tasks closer to real-world problems e. g., from the robotics domain, have not been studied previously. Here, we show that quantum circuits in hybrid quantum-classic reinforcement learning setups are capable of learning optimal policies in multiple robotic navigation scenarios with notably fewer trainable parameters compared to a classical baseline. Across a large number of experimental configurations, we find that the employed quantum circuits outperform the classical neural network baselines when equating for the number of trainable parameters. Yet, the classical neural network consistently showed better results concerning training times and stability, with at least one order of magnitude of trainable parameters more than the best-performing quantum circuits. However, validating the robustness of the learning methods in a large and dynamic environment, we find that the classical baseline produces more stable and better performing policies overall., Comment: 22 pages, 14 figure. Accepeted for publication in IEEE Access
- Published
- 2022
- Full Text
- View/download PDF
86. Geometrically Higher Order Unfitted Space-Time Methods for PDEs on Moving Domains
- Author
-
Heimann, Fabian, Lehrenfeld, Christoph, and Preuß, Janosch
- Subjects
Mathematics - Numerical Analysis - Abstract
In this paper, we propose new geometrically unfitted space-time Finite Element methods for partial differential equations posed on moving domains of higher order accuracy in space and time. As a model problem, the convection-diffusion problem on a moving domain is studied. For geometrically higher order accuracy, we apply a parametric mapping on a background space-time tensor-product mesh. Concerning discretisation in time, we consider discontinuous Galerkin, as well as related continuous (Petrov-)Galerkin and Galerkin collocation methods. For stabilisation with respect to bad cut configurations and as an extension mechanism that is required for the latter two schemes, a ghost penalty stabilisation is employed. The article puts an emphasis on the techniques that allow to achieve a robust but higher order geometry handling for smooth domains. We investigate the computational properties of the respective methods in a series of numerical experiments. These include studies in different dimensions for different polynomial degrees in space and time, validating the higher order accuracy in both variables.
- Published
- 2022
- Full Text
- View/download PDF
87. Development of slurry targets for high repetition-rate XFEL experiments
- Author
-
Smith, Raymond F., Rastogi, Vinay, Lazicki, Amy E., Gorman, Martin G., Briggs, Richard, Coleman, Amy L., Davis, Carol, Singh, Saransh, McGonegle, David, Clarke, Samantha M., Volz, Travis, Hutchinson, Trevor, McGuire, Christopher, Fratanduono, Dayne E., Swift, Damian C., Folsom, Eric, Bolme, Cynthia A., Gleason, Arianna E., Coppari, Federica, Lee, Hae Ja, Nagler, Bob, Cunningham, Eric, Granados, Eduardo, Heimann, Phil, Kraus, Richard G., Rudd, Robert E., Duffy, Thomas S., Eggert, Jon H., and Wicks, June K.
- Subjects
High Energy Physics - Experiment ,Physics - Geophysics - Abstract
Combining an x-ray free electron laser (XFEL) with high power laser drivers enables the study of phase transitions, equation-of-state, grain growth, strength, and transformation pathways as a function of pressure to 100s GPa along different thermodynamic compression paths. Future high-repetition rate laser operation will enable data to be accumulated at >1 Hz which poses a number of experimental challenges including the need to rapidly replenish the target. Here, we present a combined shock-compression and X-ray diffraction study on vol% epoxy(50)-crystalline grains(50) (slurry) targets, which can be fashioned into extruded ribbons for high repetition-rate operation. For shock-loaded NaCl-slurry samples, we observe pressure, density and temperature states within the embedded NaCl grains consistent with observations for shock-compressed single-crystal NaCl., Comment: 12 pages, 9 figures
- Published
- 2022
- Full Text
- View/download PDF
88. Facial thermal response to non-painful stressor in premature and term neonates
- Author
-
Kretschmer, Sophie C. A., Paul, Michael, Heussen, Nicole, Leonhardt, Steffen, Orlikowsky, Thorsten, and Heimann, Konrad
- Published
- 2023
- Full Text
- View/download PDF
89. The Time-resolved Atomic, Molecular and Optical Science Instrument at the Linac Coherent Light Source
- Author
-
Walter, Peter, Osipov, Timur, Lin, Ming-Fu, Cryan, James, Driver, Taran, Kamalov, Andrei, Marinelli, Agostino, Robinson, Joe, Seaberg, Matt, Wolf, Thomas J. A., Aldrich, Jeff, Brown, Nolan, Champenois, Elio G., Cheng, Xinxin, Cocco, Daniele, Conder, Alan, Curiel, Ivan, Egger, Adam, Glownia, James M., Heimann, Philip, Holmes, Michael, Johnson, Tyler, Li, Xiang, Moeller, Stefan, Morton, DanielS, Ng, May Ling, Ninh, Kayla, ONeal, Jordan T., Obaid, Razib, Pai, Allen, Schlotter, William, Shepard, Jackson, Shivaram, Niranjan, Stefan, Peter, Van, Xiong, Wang, Anna Li, Wang, Hengzi, Yin, Jing, Yunus, Sameen, Fritz, David, James, Justin, and Castagna, Jean-Charles
- Subjects
Physics - Instrumentation and Detectors ,Physics - Accelerator Physics - Abstract
The newly constructed Time-resolved atomic, Molecular and Optical science instrument (TMO), is configured to take full advantage of both linear accelerators at SLAC National Accelerator Laboratory, the copper accelerator operating at a repetition rate of 120 Hz providing high per pulse energy, as well as the superconducting accelerator operating at a repetition rate of about 1 MHz providing high average intensity. Both accelerators build a soft X-ray free electron laser with the new variable gab undulator section. With this flexible light sources, TMO supports many experimental techniques not previously available at LCLS and will have two X-ray beam focus spots in line. Thereby, TMO supports Atomic, Molecular and Optical (AMO), strong-field and nonlinear science and will host a designated new dynamic reaction microscope with a sub-micron X-ray focus spot. The flexible instrument design is optimized for studying ultrafast electronic and molecular phenomena and can take full advantage of the sub-femtosecond soft X-ray pulse generation program.
- Published
- 2021
- Full Text
- View/download PDF
90. Improving Undernutrition with Microalgae
- Author
-
Sunil K. Panchal, Kirsten Heimann, and Lindsay Brown
- Subjects
microalgae ,nutrition ,omega-3 fatty acids ,protein ,functional foods ,Nutrition. Foods and food supply ,TX341-641 - Abstract
Undernutrition is an important global health problem, especially in children and older adults. Both reversal of maternal and child undernutrition and heathy ageing have become United Nations-supported global initiatives, leading to increased attention to nutritional interventions targeting undernutrition. One feasible option is microalgae, the precursor of all terrestrial plants. Most commercially farmed microalgae are photosynthetic single-celled organisms producing organic carbon compounds and oxygen. This review will discuss commercial opportunities to grow microalgae. Microalgae produce lipids (including omega-3 fatty acids), proteins, carbohydrates, pigments and micronutrients and so can provide a suitable and underutilised alternative for addressing undernutrition. The health benefits of nutrients derived from microalgae have been identified, and thus they are suitable candidates for addressing nutritional issues globally. This review will discuss the potential benefits of microalgae-derived nutrients and opportunities for microalgae to be converted into food products. The advantages of microalgae cultivation include that it does not need arable land or pesticides. Additionally, most species of microalgae are still unexplored, presenting options for further development. Further, the usefulness of microalgae for other purposes such as bioremediation and biofuels will increase the knowledge of these microorganisms, allowing the development of more efficient production of these microalgae as nutritional interventions.
- Published
- 2024
- Full Text
- View/download PDF
91. Feasibility Study on the Use of NO2 and PM2.5 Sensors for Exposure Assessment and Indoor Source Apportionment at Fixed Locations
- Author
-
Miriam Chacón-Mateos, Erika Remy, Uta Liebers, Frank Heimann, Christian Witt, and Ulrich Vogt
- Subjects
air quality ,low-cost sensors ,indoor air ,exposure assessment ,source apportionment ,I/O ratio ,Chemical technology ,TP1-1185 - Abstract
Recent advances in sensor technology for air pollution monitoring open new possibilities in the field of environmental epidemiology. The low spatial resolution of fixed outdoor measurement stations and modelling uncertainties currently limit the understanding of personal exposure. In this context, air quality sensor systems (AQSSs) offer significant potential to enhance personal exposure assessment. A pilot study was conducted to investigate the feasibility of the NO2 sensor model B43F and the particulate matter (PM) sensor model OPC-R1, both from Alphasense (UK), for use in epidemiological studies. Seven patients with chronic obstructive pulmonary disease (COPD) or asthma had built-for-purpose sensor systems placed inside and outside of their homes at fixed locations for one month. Participants documented their indoor activities, presence in the house, window status, and symptom severity and performed a peak expiratory flow test. The potential inhaled doses of PM2.5 and NO2 were calculated using different data sources such as outdoor data from air quality monitoring stations, indoor data from AQSSs, and generic inhalation rates (IR) or activity-specific IR. Moreover, the relation between indoor and outdoor air quality obtained with AQSSs, an indoor source apportionment study, and an evaluation of the suitability of the AQSS data for studying the relationship between air quality and health were investigated. The results highlight the value of the sensor data and the importance of monitoring indoor air quality and activity patterns to avoid exposure misclassification. The use of AQSSs at fixed locations shows promise for larger-scale and/or long-term epidemiological studies.
- Published
- 2024
- Full Text
- View/download PDF
92. Research priorities for global food security under extreme events
- Author
-
Mehrabi, Zia, Delzeit, Ruth, Ignaciuk, Adriana, Levers, Christian, Braich, Ginni, Bajaj, Kushank, Amo-Aidoo, Araba, Anderson, Weston, Balgah, Roland A, Benton, Tim G, Chari, Martin M, Ellis, Erle C, Gahi, Narcisse Z, Gaupp, Franziska, Garibaldi, Lucas A, Gerber, James S, Godde, Cecile M, Grass, Ingo, Heimann, Tobias, Hirons, Mark, Hoogenboom, Gerrit, Jain, Meha, James, Dana, Makowski, David, Masamha, Blessing, Meng, Sisi, Monprapussorn, Sathaporn, Müller, Daniel, Nelson, Andrew, Newlands, Nathaniel K, Noack, Frederik, Oronje, MaryLucy, Raymond, Colin, Reichstein, Markus, Rieseberg, Loren H, Rodriguez-Llanes, Jose M, Rosenstock, Todd, Rowhani, Pedram, Sarhadi, Ali, Seppelt, Ralf, Sidhu, Balsher S, Snapp, Sieglinde, Soma, Tammara, Sparks, Adam H, Teh, Louise, Tigchelaar, Michelle, Vogel, Martha M, West, Paul C, Wittman, Hannah, and You, Liangzhi
- Subjects
Earth Sciences ,Environmental Sciences ,Zero Hunger ,Earth sciences ,Environmental sciences - Abstract
Extreme events, such as those caused by climate change, economic or geopolitical shocks, and pest or disease epidemics, threaten global food security. The complexity of causation, as well as the myriad ways that an event, or a sequence of events, creates cascading and systemic impacts, poses significant challenges to food systems research and policy alike. To identify priority food security risks and research opportunities, we asked experts from a range of fields and geographies to describe key threats to global food security over the next two decades and to suggest key research questions and gaps on this topic. Here, we present a prioritization of threats to global food security from extreme events, as well as emerging research questions that highlight the conceptual and practical challenges that exist in designing, adopting, and governing resilient food systems. We hope that these findings help in directing research funding and resources toward food system transformations needed to help society tackle major food system risks and food insecurity under extreme events.
- Published
- 2022
93. Hip MRI in flexion abduction external rotation for assessment of the ischiofemoral interval in patients with hip pain—a feasibility study
- Author
-
Heimann, Alexander F., Walther, Jonas, Tannast, Moritz, Schwab, Joseph M., Wagner, Moritz, Brunner, Alexander, Lerch, Till D., Steppacher, Simon D., Vavron, Peter, Schmaranzer, Ehrenfried, and Schmaranzer, Florian
- Published
- 2023
- Full Text
- View/download PDF
94. Staphylococcus aureus surgical site infection rates in 5 European countries
- Author
-
Mellinghoff, Sibylle C., Bruns, Caroline, Albertsmeier, Markus, Ankert, Juliane, Bernard, Louis, Budin, Sofia, Bataille, Camille, Classen, Annika Y., Cornely, Florian B., Couvé-Deacon, Elodie, Fernandez Ferrer, Maria, Fortún, Jesús, Galar, Alicia, Grill, Eva, Guimard, Thomas, Hampl, Jürgen A., Wingen-Heimann, Sebastian, Horcajada, Juan P., Köhler, Felix, Koll, Carolin, Mollar, Joan, Muñoz, Patricia, Pletz, Mathias W., Rutz, Jule, Salmanton-García, Jon, Seifert, Harald, Serracino-Inglott, Ferdinand, Soriano, Alex, Stemler, Jannik, Vehreschild, Janne J., Vilz, Tim O., Naendrup, Jan-Hendrik, Cornely, Oliver A., and Liss, Blasius J.
- Published
- 2023
- Full Text
- View/download PDF
95. Cross-species oncogenomics offers insight into human muscle-invasive bladder cancer
- Author
-
Wong, Kim, Abascal, Federico, Ludwig, Latasha, Aupperle-Lellbach, Heike, Grassinger, Julia, Wright, Colin W., Allison, Simon J., Pinder, Emma, Phillips, Roger M., Romero, Laura P., Gal, Arnon, Roady, Patrick J., Pires, Isabel, Guscetti, Franco, Munday, John S., Peleteiro, Maria C., Pinto, Carlos A., Carvalho, Tânia, Cota, João, Du Plessis, Elizabeth C., Constantino-Casas, Fernando, Plog, Stephanie, Moe, Lars, de Brot, Simone, Bemelmans, Ingrid, Amorim, Renée Laufer, Georgy, Smitha R., Prada, Justina, del Pozo, Jorge, Heimann, Marianne, de Carvalho Nunes, Louisiane, Simola, Outi, Pazzi, Paolo, Steyl, Johan, Ubukata, Rodrigo, Vajdovich, Peter, Priestnall, Simon L., Suárez-Bonnet, Alejandro, Roperto, Franco, Millanta, Francesca, Palmieri, Chiara, Ortiz, Ana L., Barros, Claudio S. L., Gava, Aldo, Söderström, Minna E., O’Donnell, Marie, Klopfleisch, Robert, Manrique-Rincón, Andrea, Martincorena, Inigo, Ferreira, Ingrid, Arends, Mark J., Wood, Geoffrey A., Adams, David J., and van der Weyden, Louise
- Published
- 2023
- Full Text
- View/download PDF
96. The effect of percentage of ideal body weight on outcomes in ileo-anal pull through for ulcerative colitis
- Author
-
Huber, Hans M., Slater, Gary, Heimann, Tomas, and Bangla, Venu
- Published
- 2023
- Full Text
- View/download PDF
97. Incurring detriments of unplanned readmission to the intensive care unit following surgery for brain metastasis
- Author
-
Schweppe, Justus August, Potthoff, Anna-Laura, Heimann, Muriel, Ehrentraut, Stefan Felix, Borger, Valeri, Lehmann, Felix, Schaub, Christina, Bode, Christian, Putensen, Christian, Herrlinger, Ulrich, Vatter, Hartmut, Schäfer, Niklas, Schuss, Patrick, and Schneider, Matthias
- Published
- 2023
- Full Text
- View/download PDF
98. Unplanned intensive care unit readmission after surgical treatment in patients with newly diagnosed glioblastoma — forfeiture of surgically achieved advantages?
- Author
-
Lehmann, Felix, Potthoff, Anna-Laura, Borger, Valeri, Heimann, Muriel, Ehrentraut, Stefan Felix, Schaub, Christina, Putensen, Christian, Weller, Johannes, Bode, Christian, Vatter, Hartmut, Herrlinger, Ulrich, Schuss, Patrick, Schäfer, Niklas, and Schneider, Matthias
- Published
- 2023
- Full Text
- View/download PDF
99. Vaginal and neonatal microbiota in pregnant women with preterm premature rupture of membranes and consecutive early onset neonatal sepsis
- Author
-
dos Anjos Borges, Luiz Gustavo, Pastuschek, Jana, Heimann, Yvonne, Dawczynski, Kristin, Schleußner, Ekkehard, Pieper, Dietmar H., and Zöllkau, Janine
- Published
- 2023
- Full Text
- View/download PDF
100. Survival in patients with surgically treated brain metastases: does infratentorial location matter?
- Author
-
Hamed, Motaz, Potthoff, Anna-Laura, Heimann, Muriel, Schäfer, Niklas, Borger, Valeri, Radbruch, Alexander, Herrlinger, Ulrich, Vatter, Hartmut, and Schneider, Matthias
- Published
- 2023
- Full Text
- View/download PDF
Catalog
Discovery Service for Jio Institute Digital Library
For full access to our library's resources, please sign in.