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arXiv 2022年

作者： Lu, Xinyi Hooten, Mevin B. Raiho, Ann M. Swanson, David K. Roland, Carl A. Stehn, Sarah E. Department of Statistics Colorado State University Fort CollinsCO80523 United States Department of Statistics and Data Sciences The University of Texas at Austin AustinTX78712 United States NASA Goddard Space Flight Center GreenbeltMD20771 United States University of Maryland Earth System Science Interdisciplinary Center College ParkMD20740 United States National Park Service 4175 Geist Road FairbanksAK99709 United States Denali National Park and Preserve P.O. Box 9 Denali Park AK99755 United States Central Alaska Network Inventory and Monitoring Program 4175 Geist Road FairbanksAK99709 United States

The Alaskan landscape has undergone substantial changes in recent decades, most notably the expansion of shrubs and trees across the Arctic. We developed a dynamic statistical model to quantify the impact of climate change on the structural transformation of ecosystems using remotely sensed imagery. We used latent trajectory processes in a hierarchical framework to model dynamic state probabilities that evolve annually, from which we derived transition probabilities between ecotypes. Our latent trajectory model accommodates temporal irregularity in survey intervals and uses spatio-temporally heterogeneous climate drivers to infer rates of land cover transitions. We characterized multi-scale spatial correlation induced by plot and subplot arrangement in our study system. We also developed a Pólya-Gamma sampling strategy to improve computation. Our model facilitates inference on the response of ecosystems to shifts in the climate and can be used to predict future land cover transitions under various climate scenarios. © 2022, CC BY.

关键词： Climate change

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Optimizing Postneoadjuvant Treatment of Residual Breast Cancer With Adjuvant Bevacizumab Alone, With Metronomic or Standard-Dose Chemotherapy: A Combined Analysis of DFCI 05-055 and DFCI 09-134/TBCRC 012/ABCDE Clinical Trials

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Clinical Breast Cancer 2025年第4期25卷 e419-e430.e5页

作者： Trapani, Dario Jin, Qingchun Miller, Kathy D. Rugo, Hope S. Reeder-Hayes, Katherine E. Traina, Tiffany Abdou, Yara Falkson, Carla Abramson, Vandana Ligibel, Jennifer Chen, Wendy Come, Steven Nohria, Anju Ryabin, Nicole Tayob, Nabihah Tolaney, Sara M Burstein, Harold J. Mayer, Erica L. Medical Oncology Dana-Farber Cancer Institute Boston MA United States Breast Oncology Program Dana-Farber Brigham Cancer Center Boston MA United States Harvard Medical School Boston MA United States Data Science Dana-Farber Cancer Institute Boston MA United States Indiana University Melvin and Bren Simon Comprehensive Cancer Center Indianapolis IN United States University of California at San Francisco San Francisco CA United States University of North Carolina Lineberger Comprehensive Cancer Institute Chapel Hill NC United States Memorial Sloan Kettering Cancer Center New York NY United States University of Alabama Birmingham AL United States Vanderbilt University Nashville TN United States Beth Israel Deaconess Medical Center Boston MA United States Division of Cardiovascular Medicine Brigham and Women's Hospital Boston MA United States

Background: Breast cancer patients with residual disease after neoadjuvant therapy have increased risk of recurrence. Novel therapies to decrease this risk are urgently needed. Methods: Two clinical trials (05-055 and 09-134) offered adjuvant bevacizumab-based therapy to stage I–III breast cancer patients with residual disease after neoadjuvant chemotherapy. Study 05-055 evaluated four treatment regimens: bevacizumab (cohort A);bevacizumab with metronomic cyclophosphamide and methotrexate (CM) (cohort B);and bevacizumab with body surface area-dosed capecitabine (cohorts C);or flat-dosed capecitabine (cohort D). The primary endpoint was feasibility and tolerability. In 09-134, patients were randomized to bevacizumab with or without CM;the primary endpoint was recurrence-free survival (RFS). Study 09-134 closed prematurely for lack of accrual. A pooled survival analysis with participants from 05-055 and 09-134 was conducted. Results: Among 213 total patients (05-055, n = 163;09-134, n = 50), the most common adverse events (AEs) of any grade were headache (49.3%) and fatigue (57.3%). Grade 3-4 AEs were highest in cohorts C (71.4%) and D (72.5%). The 36-month RFS was 58.0% with bevacizumab monotherapy, 62.3% with bevacizumab plus CM, and 72.7%-75.0% with bevacizumab plus capecitabine (depending on schedule). Treatment with capecitabine was independently associated with improved RFS in triple-negative breast cancer (TNBC) (HR: 0.47;95% CI, 0.23-0.96). Conclusion: This pooled analysis demonstrates that postneoadjuvant bevacizumab plus capecitabine may be associated with improved RFS, especially in TNBC. Each regimen carries moderate toxicity, and despite these treatments, patients with residual disease after neoadjuvant therapy still experience high rates of recurrence, indicating that new strategies are warranted. Clinical Trial Registration: ***, NCT00121134 (DFCI Protocol Number: 05-055);NCT00925652 (DFCI Protocol Number: 09-134). © 2025 Elsevier Inc.

关键词： Anti-angiogenesis Capecitabine Preoperative TNBC VEGF

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Circular Polarization of Simulated Images of Black Holes

arXiv

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arXiv 2024年

作者： Joshi, Abhishek V. Prather, Ben S. Chan, Chi-Kwan Wielgus, Maciek Gammie, Charles F. Department of Physics University of Illinois 1110 West Green Street UrbanaIL61801 United States Illinois Center for Advanced Study of the Universe 1110 West Green Street UrbanaIL61801 United States Los Alamos National Lab Los AlamosNM87545 United States Steward Observatory Department of Astronomy University of Arizona 933 N. Cherry Ave. TucsonAZ85721 United States Data Science Institute University of Arizona 1230 N. Cherry Ave. TucsonAZ85721 United States Program in Applied Mathematics University of Arizona 617 N. Santa Rita TucsonAZ85721 United States Max-Planck-Institut für Radioastronomie Auf dem Hügel 69 BonnD-53121 Germany Department of Astronomy University of Illinois 1002 West Green Street UrbanaIL61801 United States National Center for Supercomputing Applications 605 East Springfield Avenue ChampaignIL61820 United States

Models of the resolved Event Horizon Telescope (EHT) sources Sgr A* and M87* are constrained by observations at multiple wavelengths, resolutions, polarizations, and time cadences. In this paper we compare unresolved circular polarization (CP) measurements to a library of models, where each model is characterized by a distribution of CP over time. In the library we vary the spin of the black hole, the magnetic field strength at the horizon (i.e. both SANE and MAD models), the observer inclination, a parameter for the maximum ion-electron temperature ratio assuming a thermal plasma, and the direction of the magnetic field dipole moment. We find that ALMA observations of Sgr A* are inconsistent with all edge-on (i = 90◦) models. Restricting attention to the magnetically arrested disk (MAD) models favored by earlier EHT studies of Sgr A*, we find that only models with magnetic dipole moment pointing away from the observer are consistent with ALMA data. We also note that in 26 of the 27 passing MAD models the accretion flow rotates clockwise on the sky. We provide a table of the mean and standard deviation of the CP distributions for all model parameters along with their trends. © 2024, CC BY.

关键词： Stars

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In situ Interweaved Binder Framework Mitigating the Structural and Interphasial Degradations of High-nickel Cathodes in Lithium-ion Batteries

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Angewandte Chemie 2023年第15期135卷

作者： Dr. Biyu Jin Zehao Cui Prof. Arumugam Manthiram Materials Science and Engineering Program and Texas Materials Institute The University of Texas at Austin Austin TX 78712 USA Contribution: Conceptualization (lead) Data curation (lead) Formal analysis (lead) Investigation (lead) Methodology (equal) Writing - original draft (lead) Contribution: Conceptualization (supporting) Data curation (equal) Formal analysis (supporting) Investigation (supporting) Methodology (equal) Writing - review & editing (equal) Contribution: Conceptualization (equal) Funding acquisition (lead) Investigation (supporting) Project administration (lead) Resources (lead) Supervision (lead) Validation (equal) Writing - review & editing (equal)

The practical viability of high-nickel layered oxide cathodes is compromised by the interphasial and structural degradations. Herein, we demonstrate that by applying an in situ interweaved binder, the cycling stability of high-nickel cathodes can be significantly improved. Specifically, the results show that the resilient binder network immobilizes the transition-metal ions, suppresses electrolyte oxidative decomposition, and mitigates cathode particles pulverization, thus resulting in suppressed cathode-to-anode chemical crossover and ameliorated chemistry and architecture of electrode-electrolyte interphases. Pouch full cells with high-mass-loading LiNi 0.8 Mn 0.1 Co 0.1 O 2 cathodes achieve 0.02 % capacity decay per cycle at 1 C rate over 1 000 deep cycles at 4.4 V (vs. graphite). This work demonstrates a rational structural and compositional design strategy of polymer binders to mitigate the structural and interphasial degradations of high-Ni cathodes in lithium-ion batteries.

关键词： Cathode-to-Anode Crossover Electrode-Electrolyte Interphase High-Nickel Cathode In Situ Interweaved Binder Particles Pulverization

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A Geoelectric Approach for Karst Groundwater Analysis

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IOP Conference Series: Earth and Environmental science 2022年第1期998卷

作者： Amallia Ferhat Taufik Seizarsyah Mohammad Prasanto Bimantio Nanda Satya Nugraha Dian Pratama Putra Teddy Suparyanto Alam Ahmad Hidayat Bens Pardamean Agribusiness Department Institute of Agricultural STIPER Yogyakarta 55282 Indonesia Geophysical Engineering Department Universitas Pembangunan Nasional 'Veteran' Yogyakarta Indonesia Agricultural Crop Technology Department Institute of Agricultural STIPER Yogyakarta 55282 Indonesia Forestry Department Institute of Agricultural STIPER Yogyakarta 55282 Indonesia Agricultural Engineering Department Institute of Agricultural STIPER Yogyakarta 55282 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program – Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

Artesian well is one of the major efforts to obtain water source for fulfilling water demands in Eroniti Conservation park, Ponjong, Yogyakarta by drilling deep into several soil layers. Vertical Electrical Sounding (VES) method is the most common approach to determine the existence of groundwater. The method probes layers of rock below the ground surface based on their electrical properties, since the electrical resistivity of each layer is theoretically different. This study aims to utilize the VES approach for investigating the properties of the rock layers in the area to explore groundwater sources. We install six different VES points in the observation area using Schlumberger electrode configuration. The methodology of the work consists of three steps: the planning of the placement of the sounding points, the measurement step performed by a unit of IRIS SYSCAL Resistivity meter, and the data analysis and interpretation. Employing the resistivity analysis, we conclude that the observed region consists of Mediterranean soil as a result of weathering of limestone as well as lithology of the limestone. Furthermore, there are two types of aquifer found in the area: a perched aquifer found 27 meters below the ground surface of VES point 1 and a confined aquifer 166 meters below the ground surface of VES point 2 and 6.

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SAIGE-GENE+ improves the efficiency and accuracy of set-based rare variant association tests (vol 54, pg 1446, 2022)

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NATURE GENETICS 2022年第11期54卷 1755-1755页

作者： Zhou, Wei Bi, Wenjian Zhao, Zhangchen Dey, Kushal K. Jagadeesh, Karthik A. Karczewski, Konrad J. Daly, Mark J. Neale, Benjamin M. Lee, Seunggeun Analytic and Translational Genetics Unit Massachusetts General Hospital Boston MA USA Program in Medical and Population Genetics Broad Institute of Harvard and MIT Cambridge MA USA Stanley Center for Psychiatric Research Broad Institute of Harvard and MIT Cambridge MA USA Institute for Molecular Medicine Finland Helsinki Institute of Life Sciences University of Helsinki Helsinki Finland Department of Medical Genetics School of Basic Medical Sciences Peking University Beijing China Center for Statistical Genetics University of Michigan School of Public Health Ann Arbor MI USA Department of Biostatistics University of Michigan School of Public Health Ann Arbor MI USA Department of Epidemiology Harvard T. H. Chan School of Public Health Boston MA USA Graduate School of Data Science Seoul National University Seoul Korea

Several biobanks, including UK Biobank (UKBB), are generating large-scale sequencing data. An existing method, SAIGE-GENE, performs well when testing variants with minor allele frequency (MAF) ≤ 1%, but inflation is observed in variance component set-based tests when restricting to variants with MAF ≤ 0.1% or 0.01%. Here, we propose SAIGE-GENE+ with greatly improved type I error control and computational efficiency to facilitate rare variant tests in large-scale data. We further show that incorporating multiple MAF cutoffs and functional annotations can improve power and thus uncover new gene–phenotype associations. In the analysis of UKBB whole exome sequencing data for 30 quantitative and 141 binary traits, SAIGE-GENE+ identified 551 gene–phenotype associations.

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Detection of features from the internet of things customer attitudes in the hotel industry using a deep neural network model

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Measurement: Sensors 2022年 22卷

作者： Rajesh, Sudha Abd Algani, Yousef Methkal Al Ansari, Mohammed Saleh Balachander, Bhuvaneswari Raj, Roop Muda, Iskandar Kiran Bala, B. Balaji, S. Dept. of Computational Intelligence College of Engineering and Technology School of Computing SRMIST Kattankulathur Chennai India Department of Mathematics Sakhnin College Israel College of Engineering Department of Chemical Engineering University of Bahrain Bahrain Department of ECE Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai602105 India Lecturer in Economics Education Department Government of Haryana Haryana Panchkula India Department of Doctoral Program Faculty Economic and Business Universitas Sumatera Utara 20222 Jl. Prof TM Hanafiah 12 USU Campus Padang bulan Medan20155 Indonesia Department of Artificial Intelligence and Data Science K.Ramakrishnan College of Engineering Tamil Nadu Trichy India Department of CSE Panimalar Engineering College Chennai India Department of Mathematics The Arab Academic College for Education in Israel-Haifa Israel

Tourism and the hotel business have benefited greatly from the use of digital social networking. Using social big data research, the application of deep learning seems to have been beneficial in a marketing strategies and customer preference estimate. Recognizing human psychology, which is critical to industrial success, has benefited greatly from digital technology and social media. The Internet of Things (IoT) provides a chance for a hotel sector to improve the customer experience although lowering operational expenses. The ratings are determined by the following factors: Value, Apartment, Location, Hygiene, Front Office, Facilities, Professional Service, Internet, and Parking. Traditional techniques which anticipate hotel evaluations through minimal precision add difficulty to the rating assessment. As a result, efficient deep learning algorithms are employed to evaluate reviews designed to help consumers in selecting better hotels. To predict qualities, multiple classification techniques, including convolutional neural network-based deep learning (CNN-DL) and support vector machine (SVM) network-based deep learning, were used in this research. The system examines system efficiency by using the TripAdvisor website, this is a well American database. The research results reveal that the CNN-DL method outperforms another method in terms of classification efficiency and failure *** graphical results could also be utilized to enhance the effectiveness of the suggested model and offer insights into response tactics, demonstrating the study's academic and conceptual achievements. Although it is feasible to conclude from such research that the possibility of IoT within the hotel industry has not yet been fully investigated, as researchers commonly speculate on using IoT for implementations that might quickly be of involvement to a hotel sector, but refuse to recognize that possibility as a massive market. © 2022 The Author(s)

关键词： Hotels

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AI-BASED FAST AND SCALABLE IMAGE SEARCH FOR RARE DISEASE DIAGNOSIS

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Journal of Pathology Informatics 2022年 13卷 100046-100046页

作者： Chen, Chengkuan Lu, Ming Y. Williamson, Drew F.K. Chen, Tiffany Y. Schaumberg, Andrew J. Mahmood, Faisal Department of Pathology Brigham and Women’s Hospital Harvard Medical School Boston MA USA Cancer Program Broad Institute of Harvard and MIT Cambridge MA USA Cancer Data Science Dana-Farber Cancer Institute Boston MA USA Department of Biomedical Informatics Harvard Medical School Boston MA USA

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Author Correction: A machine learning approach to leveraging electronic health records for enhanced omics analysis

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Nature Machine Intelligence 2025年第4期7卷 673页

作者： Samson J. Mataraso Camilo A. Espinosa David Seong S. Momsen Reincke Eloise Berson Yeasul Kim Marc Ghanem Chi-Hung Shu Tomin James Sayane Shome Ina A. Stelzer Dorien Feyaerts Martin S. Angst Brice Gaudilliere Nima Aghaeepour Jonathan D. Reiss Ronald J. Wong Gary M. Shaw David K. Stevenson Yuqi Tan Department of Anesthesiology Perioperative and Pain Medicine Stanford University School of Medicine Stanford CA USA Department of Pediatrics Stanford University School of Medicine Stanford CA USA Department of Biomedical Data Science Stanford University School of Medicine Stanford CA USA Immunology Program Stanford University School of Medicine Stanford CA USA Medical Scientist Training Program Stanford University School of Medicine Stanford CA USA Department of Pathology Stanford University School of Medicine Stanford CA USA Department of Pathology University of California San Diego La Jolla CA USA Department of Microbiology and Immunology Stanford University School of Medicine Stanford CA USA

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276MO Epidemiology, treatment (tx) patterns, and clinical outcomes of patients (pts) with locally advanced or metastatic urothelial cancer (la/mUC) in Taiwan: A retrospective cohort study

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Annals of Oncology 2024年 35卷 S1511-S1511页

作者： C-T. Wu L. Young A. Lee M-Y. Ku Y-C. Hsieh H-W. Lin K-L. Lin K-P. Chou M. Kearney L-N. Chien Department of Urology Chang Gung Memorial Hospital Taoyuan City Taiwan Global Medical Unit Oncology Merck Pte. Ltd. Singapore Science Park Singapore Medical Affairs Oncology Merck Ltd. Taipei Taiwan Graduate Institute of Data Science College of Management Taipei Medical University Taipei Taiwan Program in Medical Neuroscience Taipei Medical University Taipei Taiwan Real-world Solutions IQVIA Solutions Taiwan Ltd. Taipei Taiwan Global Value Demonstration Market Access and Pricing Biopharma Global Operations Merck Healthcare KGaA Darmstadt Germany Institute of Health and Welfare Policy College of Medicine National Yang Ming Chiao Tung University Taipei Taiwan

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