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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Rodrigo V. Leite William Wagner Margaret Wooten Monique B. Schlickmann Carlos A. Silva Cibele H. Do Amaral Diogo N. Cosenza Carlos M.M.E. Torres Ameni Mkaouar Shashank Bhushan David Shean Paul Montesano Douglas C. Morton Christopher S.R. Neigh Goddard Space Flight Center NASA Postdoctoral Program Fellow Greenbelt MD Biospheric Sciences Laboratory Code 618 NASA Goddard Space Flight Center Greenbelt MD USA Forest Biometrics Artificial Intelligence and Remote Sensing Laboratory (Silva lab) School of Forest Fisheries and Geomatics Sciences University of Florida Gainesville FL USA Earth Lab Cooperative Institute for Research in Environmental Sciences University of Colorado Boulder Boulder CO USA Environmental Data Science Innovation & Inclusion Lab (ESIIL) University of Colorado Boulder Boulder CO USA Department of Forest Engineering Federal University of Viçosa Viçosa MG Brazil Department of Civil and Environmental Engineering University of Washington Seattle WA USA

ISBN: (数字)9798350360325

ISBN: (纸本)9798350360332

Quantifying aboveground biomass (AGB) in tropical forests is a challenging but necessary task to support actions to preserve and restore these ecosystems. Recent methods have leveraged the integration of NASA’s spaceborne lidar GEDI with imaging sensors to improve AGB predictions. However, the use of high-resolution (<1 m) stereo images from spaceborne sensors still needs to be explored within these frameworks. The objective of this study was to predict AGB in a tropical forest patch by combining stereo images and GEDI data. A digital surface model (Stereo-DSM) was generated by stereophotogrammetric processing of high-resolution stereo pairs collected from a spaceborne sensor. A canopy height model (Stereo-CHM) was then derived by subtracting an airborne lidar-derived digital terrain model from the Stereo-DSM. Descriptive statistics were calculated from the Stereo-CHM to be used as predictors in the model to predict AGB. We also calculated vegetation indices from the Harmonized Landsat-Sentinel and Sentinel-1 images to compare their relative importance in the model and assess their relationship to the Stereo-CHM metrics. Finally, we trained a Random Forest model using stereogrammetry - derived, multispectral and SAR metrics as features and GEDI’s footprint-level AGB product as a reference. The model to predict AGB yielded performance metrics of r = 0.63, RMSE = 25.38 Mg/ha, and MD = 2.1 Mg/ha. The metrics from the Stereo-CHM were ranked as the most important to the model. This is an indication that these metrics can add important information related to canopy structure to inform GEDI-based models to predict AGB. It is still necessary to evaluate these results considering a variation in canopy cover, topography, and understory vegetation. The findings are important to support advances on the integration of large footprint spaceborne lidar and images with sub-meter spatial resolution to characterize vegetation in tropical forests.

关键词： Measurement Image sensors Forests Laser radar Atmospheric modeling Vegetation mapping Predictive models

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The CD8α hinge is intrinsically disordered with a dynamic exchange that includes proline cis-trans isomerization

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Journal of Magnetic Resonance 2022年 340卷 107234页

作者： Chen, Xiang Mirazee, Justin M. Skorupka, Katarzyna A. Matsuo, Hiroshi Youkharibache, Philippe Taylor, Naomi Walters, Kylie J. Center for Structural Biology Center for Cancer Research National Cancer Institute National Institutes of Health FrederickMD21702 United States Pediatric Oncology Branch Center for Cancer Research National Cancer Institute National Institutes of Health BethesdaMD20814 United States Laboratory of Integrative Cancer Immunology Center for Cancer Research National Cancer Institute National Institutes of Health BethesdaMD20894 United States Johns Hopkins University Department of Biology 3400 N. Charles Street BaltimoreMD21218 United States Basic Science Program Frederick National Laboratory for Cancer Research FrederickMD21702 United States Cancer Data Science Laboratory Center for Cancer Research National Cancer Institute National Institutes of Health BethesdaMD20894 United States

T cells engineered to express artificial chimeric antigen receptors (CARs) that selectively target tumor-specific antigens or deleterious cell types offer transformative therapeutic possibilities. CARs contain an N-terminal extracellular antigen recognition domain, C-terminal intracellular signal transduction domains, and connecting hinge and transmembrane regions, each of which have been varied to optimize targeting and minimize toxicity. We find that a CD22-targeting CAR harboring a CD8α hinge (H) exhibits greater cytotoxicity against a low antigen density CD22+ leukemia as compared to an equivalent CAR with a CD28 H. We therefore studied the biophysical and dynamic properties of the CD8α H by nuclear magnetic resonance (NMR) spectroscopy. We find that a large region of the CD8α H undergoes dynamic chemical exchange between distinct and observable states. This exchanging region contains proline residues dispersed throughout the sequence that undergo cis-trans isomerization. Up to four signals of differing intensity are observed, with the most abundantly populated being intrinsically disordered and with all prolines in the trans isomerization state. The lesser populated states all contain cis prolines and evidence of local structural motifs. Altogether, our data suggest that the CD8α H lacks long-range structural order but has local structural motifs that transiently exchange with a dominant disordered state. We propose that structural plasticity and local structural motifs promoted by cis proline states within the CD8α H are important for relaying and amplifying antigen-binding effects to the transmembrane and signal transduction domains. © 2022

关键词： T-cells

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An artificial intelligence method for vessel detection in images of cardiac catheterization

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Informatics in Medicine Unlocked 2023年 39卷

作者： Chien, Ting-Ying Ting, Hsien-Wei Li, Hao-Wei Chang, Hsiao-Huang Department of Computer Science and Engineering Yuan Ze University 320 Taoyuan City Taiwan Graduate Program in Biomedical Informatics Yuan Ze University 320 Taoyuan City Taiwan Innovation Center for Big Data and Digital Convergence Yuan Ze University 320 Taoyuan City Taiwan Department of Neurosurgery Taipei Hospital Ministry of Health and Welfare 242 New Taipei City Taiwan Division of Cardiovascular Surgery Department of Surgery Taipei Veterans General Hospital Taipei 11217 Taiwan Department of Surgery School of Medicine College of Medicine Taipei Medical University Taipei 11031 Taiwan

Coronary artery disease (CAD) is one of the top ten leading causes of death in countries worldwide. There are several methods used by physicians to diagnose CAD. One common method is the use of X-ray angiogram (XRA) images. When employing a computer-aided automatic analysis method to locate blood vessels in XRA images, problems such as complex background noise, low contrast, and difficulty in separating blood vessels from the background are encountered, especially for blood vessels with a low contrast to the background noise. In this study, we used various image preprocessing methods to highlight blood vessels from complex backgrounds and different types of blood vessel, followed by the employment of four superpixel segmentation methods to partition an image into multiple segments, and finally the utilization of Weighted Voting to determine the best superpixel algorithm. A genetic algorithm was used to identify the best weights by which to determine the locations of blood vessels in images of cardiac catheterization. Our proposed method achieved an average F1-score of 73.4% in the analysis of five patients, which was better than the other superpixel algorithms tested. The results of this research will be helpful for future SYNTAX score analysis. © 2023

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A Systematic Search of Distant Superclusters with the Subaru Hyper Suprime-Cam Survey

arXiv

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arXiv 2024年

作者： Chen, Tsung-Chi Lin, Yen-Ting Schive, Hsi-Yu Oguri, Masamune Chen, Kai-Feng Okabe, Nobuhiro Ali, Sadman Bottrell, Connor Dalal, Roohi Koyama, Yusei Monteiro-Oliveira, Rogério Shimakawa, Rhythm Goto, Tomotsugu Hsieh, Bau-Ching Kodama, Tadayuki Nishizawa, Atsushi J. Institute of Astronomy and Astrophysics Academia Sinica Taipei10617 Taiwan Department of Physics National Taiwan University Taipei10617 Taiwan Graduate Institute of Astrophysics National Taiwan University Taipei10617 Taiwan Institute of Physics National Yang Ming Chiao Tung University Hsinchu30010 Taiwan Center for Theoretical Physics National Taiwan University Taipei10617 Taiwan Physics Division National Center for Theoretical Sciences Taipei10617 Taiwan Center for Frontier Science Chiba University Chiba-shi Chiba263-8522 Japan Department of Physics Massachusetts Institute of Technology CambridgeMA02139 United States Physics Program Graduate School of Advanced Science and Engineering Hiroshima University 1-3-1 Kagamiyama Higashi-Hiroshima Hiroshima739-8526 Japan Hiroshima Astrophysical Science Center Hiroshima University 1-3-1 Kagamiyama Higashi-Hiroshima Hiroshima739-8526 Japan Core Research for Energetic Universe Hiroshima University 1-3-1 Kagamiyama Higashi-Hiroshima Hiroshima739-8526 Japan Subaru Telescope National Astronomical Observatory of Japan HiloHI96720 United States International Centre for Radio Astronomy Research University of Western Australia 35 Stirling Highway Perth6009 Australia Department of Astrophysical Sciences Princeton University PrincetonNJ08544 United States Waseda University 1-21-1 Nishi Waseda Shinjuku Tokyo169-0051 Japan Center for Data Science Waseda University 1-6-1 Nishi-Waseda Shinjuku Tokyo169-0051 Japan Institute of Astronomy National Tsing Hua University Hsinchu30013 Taiwan Astronomical Institute Graduate School of Science Tohoku University Sendai Miyagi980-8578 Japan DX Center Gifu Shotoku Gakuen University Gifu501-6194 Japan

Superclusters, encompassing environments across a wide range of overdensities, can be regarded as unique laboratories for studying galaxy evolution. Although numerous supercluster catalogs have been published, none of them goes beyond redshift z = 0.7. In this work, we adopt a physically motivated supercluster definition, requiring that superclusters should eventually collapse even in the presence of dark energy. Applying a friends-of-friends (FoF) algorithm to the CAMIRA cluster sample constructed using the Subaru Hyper Suprime-Cam survey data, we have conducted the first systematic search for superclusters at z = 0.5-1.0 and identified 673 supercluster candidates over an area of 1027 deg2. The FoF algorithm is calibrated by evolving N-body simulations to the far future to ensure high purity. We found that these high-z superclusters are mainly composed of 2 - 4 clusters, suggesting the limit of gravitationally bound structures in the younger Universe. In addition, we studied the properties of the clusters and brightest cluster galaxies (BCGs) residing in different large-scale environments. We found that clusters associated with superclusters are typically richer, but no apparent dependence of the BCG properties on large-scale structures is found. We also compared the abundance of observed superclusters with mock superclusters extracted from halo light cones, finding that photometric redshift uncertainty is a limiting factor in the performance of superclusters detection. © 2024, CC BY.

关键词： Dark energy

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Addressing research software sustainability via institutes

arXiv

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arXiv 2021年

作者： Katz, Daniel S. Carver, Jeffrey C. Chue Hong, Neil P. Gesing, Sandra Hettrick, Simon Honeyman, Tom Ram, Karthik Weber, Nicholas NCSA & CS & ECE & iSchool University of Illinois UrbanaIL United States Department of Computer Science University of Alabama TuscaloosaAL United States Software Sustainability Institute EPCC University of Edinburgh Edinburgh United Kingdom Center for Research Computing University of Notre Dame Notre DameIN United States Software Sustainability Institute ECS University of Southampton Southampton United Kingdom Software Program Australian Research Data Commons Univ. of Technology Sydney Australia Berkeley Institute for Data Science University of California BerkeleyCA United States Information School University of Washington SeattleWA United States

Research software is essential to modern research, but it requires ongoing human effort to sustain: to continually adapt to changes in dependencies, to fix bugs, and to add new features. Software sustainability institutes, amongst others, develop, maintain, and disseminate best practices for research software sustainability, and build community around them. These practices can both reduce the amount of effort that is needed and create an environment where the effort is appreciated and rewarded. The UK SSI is such an institute, and the US URSSI and the Australian AuSSI are planning to become institutes, and this extended abstract discusses them and the strengths and weaknesses of this approach. Copyright © 2021, The Authors. All rights reserved.

关键词： Sustainable development

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MedRep: Medical Concept Representation for General Electronic Health Record Foundation Models

arXiv

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arXiv 2025年

作者： Kim, Junmo Lee, Namkyeong Kim, Jiwon Kim, Kwangsoo Interdisciplinary Program in Bioengineering Seoul National University Korea Republic of Dept. of Industrial and Systems Engineering KAIST Korea Republic of Interdisciplinary Program of Medical Informatics Seoul National University Korea Republic of Dept. of Transdisciplinary Medicine ICMIT Seoul National University Hospital Korea Republic of Center for Data Science Healthcare AI Research Institute Seoul National University Hospital Korea Republic of Dept. of Medicine College of Medicine Seoul National University Korea Republic of

Electronic health record (EHR) foundation models have been an area ripe for exploration with their improved performance in various medical tasks. Despite the rapid advances, there exists a fundamental limitation: Processing unseen medical codes out of the vocabulary. This problem limits the generality of EHR foundation models and the integration of models trained with different vocabularies. To deal with this problem, we propose MedRep for EHR foundation models based on the observational medical outcome partnership (OMOP) common data model (CDM), providing the integrated medical concept representations and the basic data augmentation strategy for patient trajectories. For concept representation learning, we enrich the information of each concept with a minimal definition through large language model (LLM) prompts and enhance the text-based representations through graph ontology of OMOP vocabulary. Trajectory augmentation randomly replaces selected concepts with other similar concepts that have closely related representations to let the model practice with the concepts out-of-vocabulary. Finally, we demonstrate that EHR foundation models trained with MedRep better maintain the prediction performance in external datasets. Our code implementation is publicly available at https://***/kicarussays/MedRep. Copyright © 2025, The Authors. All rights reserved.

关键词： Electronic health record

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Analysis of Acoustic Features in Gender Identification Model for English and Bahasa Indonesia Telephone Speeches

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Procedia Computer science 2019年 157卷 199-204页

作者： Muhamad Fitra Kacamarga Tjeng Wawan Cenggoro Arif Budiarto Reza Rahutomo Bens Pardamean Eureka.ai Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta Indonesia 11480

One of the most interesting topics in auditory problem is determining gender of the speaker. In recent years, machine learning has gained significant attentions as a way to build a classifier from labeled data which also can be implemented to build a gender classifier. In this study we develop gender classifier using two different datasets with different languages, English and Bahasa Indonesia. Each data from both datasets is represented by 20 acoustic features. Multi Layer Perceptron (MLP) is used to build the classification model using all these features and trained only on English dataset. This model is evaluated in both dataset to get the performance matrices consist of accuracy, AUROC, precision and recall. Ultimately, using this model we also identify and compare important features from both dataset to see the different characteristics of English and Bahasa Indonesia speeches.

关键词： Gender Identification Acoustic Feature Speech Recognition

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The phase diagram of a deep potential water model

arXiv

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arXiv 2021年

作者： Zhang, Linfeng Wang, Han Car, Roberto Weinan, E. Program in Applied and Computational Mathematics Princeton University PrincetonNJ08544 United States Laboratory of Computational Physics Institute of Applied Physics and Computational Mathematics Fenghao East Road 2 Beijing100094 China Department of Chemistry Department of Physics Program in Applied and Computational Mathematics Princeton Institute for the Science and Technology of Materials Princeton University PrincetonNJ08544 United States Department of Mathematics and Program in Applied and Computational Mathematics Princeton University PrincetonNJ08544 United States Beijing Institute of Big Data Research Beijing100871 China

Using the Deep Potential methodology, we construct a model that reproduces accurately the potential energy surface of the SCAN approximation of density functional theory for water, from low temperature and pressure to about 2400 K and 50 GPa, excluding the vapor stability region. The computational efficiency of the model makes it possible to predict its phase diagram using molecular dynamics. Satisfactory overall agreement with experimental results is obtained. The fluid phases, molecular and ionic, and all the stable ice polymorphs, ordered and disordered, are predicted correctly, with the exception of ice III and XV that are stable in experiments, but metastable in the model. The evolution of the atomic dynamics upon heating, as ice VII transforms first into ice VII′′ and then into an ionic fluid, reveals that molecular dissociation and breaking of the ice rules coexist with strong covalent fluctuations, explaining why only partial ionization was inferred in experiments. © 2021, CC BY-NC-ND.

关键词： Phase diagrams

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Biases in inverse Ising estimates of near-critical behavior

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Physical Review E 2023年第1期108卷 014109-014109页

作者： Maximilian B. Kloucek Thomas Machon Shogo Kajimura C. Patrick Royall Naoki Masuda Francesco Turci School of Physics HH Wills Physics Laboratory University of Bristol Tyndall Avenue Bristol BS8 1TL United Kingdom Bristol Centre for Functional Nanomaterials HH Wills Physics Laboratory University of Bristol Tyndall Avenue Bristol BS8 1TL United Kingdom Faculty of Information and Human Sciences Kyoto Institute of Technology Kyoto 606-8585 Japan Gulliver UMR CNRS 7083 ESPCI Paris Université PSL 75005 Paris France Department of Mathematics State University of New York at Buffalo Buffalo New York 14260-2900 USA Computational and Data-Enabled Science and Engineering Program State University of New York at Buffalo Buffalo New York 14260-5030 USA

Inverse Ising inference allows pairwise interactions of complex binary systems to be reconstructed from empirical correlations. Typical estimators used for this inference, such as pseudo-likelihood maximization (PLM), are biased. Using the Sherrington-Kirkpatrick model as a benchmark, we show that these biases are large in critical regimes close to phase boundaries, and they may alter the qualitative interpretation of the inferred model. In particular, we show that the small-sample bias causes models inferred through PLM to appear closer to criticality than one would expect from the data. data-driven methods to correct this bias are explored and applied to a functional magnetic resonance imaging data set from neuroscience. Our results indicate that additional care should be taken when attributing criticality to real-world data sets.

关键词： Critical phenomena Cortical networks Spin glasses Functional magnetic resonance imaging Ising model

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DNAku Consumers Profile: One of The First Direct to Customer Genetics Testing in Indonesia

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IOP Conference Series: Earth and Environmental science 2021年第1期794卷

作者： Deby Erina Parung Kians Azizatikarna Dian Amirulloh Erlin Listiyaningsih Bharuno Mahesworo Arif Budiarto Simon Bens Pardamean Genetics Indonesia Jakarta Indonesia 12940 Bioinformatics & Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta Indonesia 11480

DNAku test is one of the first direct to customer genetics testing in Indonesia. DNAku test came with a different approach as it gave their customer reports of their genetic predisposition to corresponding traits. Four months after launch, we create consumer report of this genetics testing based on DNAku questionnaire results. We applied three statistical methods, including descriptive statistics, multivariate normality test, and t-test to the demographic data of the DNAku customers. The result shows population clusters which may represent population groups that are interested in genetics testing. The questionnaire also has questions about the customer's lifestyle. The results of these questions were processed to find the lifestyle of DNAku customers.

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