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arXiv 2024年

作者： Lee, Jun-Young Kim, Ji-Hoon Jung, Minyong Oh, Boon Kiat Jo, Yongseok Park, Songyoun Lee, Jaehyun Ting, Yuan-Sen Hwang, Ho Seong Institute for Data Innovation in Science Seoul National University Seoul08826 Korea Republic of Center for Theoretical Physics Department of Physics and Astronomy Seoul National University Seoul08826 Korea Republic of Seoul National University Astronomy Research Center Seoul08826 Korea Republic of Department of Physics University of Connecticut StorrsCT06269 United States Columbia Astrophysics Laboratory Columbia University New YorkNY10027 United States Center for Computational Astrophysics Flatiron Institute New YorkNY10010 United States Korea Astronomy and Space Science Institute Daejeon34055 Korea Republic of Research School of Astronomy & Astrophysics Australian National University CanberraACT2611 Australia School of Computing Australian National University ActonACT2601 Australia Department of Astronomy The Ohio State University ColumbusOH43210 United States The Ohio State University ColumbusOH43210 United States Astronomy Program Department of Physics and Astronomy Seoul National University Seoul08826 Korea Republic of

We present a proof-of-concept simulation-based inference on Ωm and σ8 from the SDSS BOSS LOWZ NGC catalog using neural networks and domain generalization techniques without the need of summary statistics. Using rapid lightcone simulations, L-PICOLA, mock galaxy catalogs are produced that fully incorporate the observational effects. The collection of galaxies is fed as input to a point cloud-based network, Minkowski-PointNet. We also add relatively more accurate GADGET mocks to obtain robust and generalizable neural networks. By explicitly learning the representations which reduces the discrepancies between the two different datasets via the semantic alignment loss term, we show that the latent space configuration aligns into a single plane in which the two cosmological parameters form clear axes. Consequently, during inference, the SDSS BOSS LOWZ NGC catalog maps onto the plane, demonstrating effective generalization and improving prediction accuracy compared to non-generalized models. Results from the ensemble of 25 independently trained machines find Ωm=0.339±0.056 and σ8=0.801±0.061, inferred only from the distribution of galaxies in the lightcone slices without relying on any indirect summary statistics. A single machine that best adapts to the GADGET mocks yields a tighter prediction of Ωm=0.282±0.014 and σ8=0.786±0.036. We emphasize that adaptation across multiple domains can enhance the robustness of the neural networks in observational data. © 2024, CC BY.

关键词： Cosmology

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Skill Assessment of North American Multi-Models Ensemble (NMME) for June-September (JJAS) Seasonal Rainfall over Ethiopia

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Atmospheric and Climate sciences 2022年第1期12卷 54-73页

作者： Asaminew Teshome Jie Zhang Qianrong Ma Stephen E. Zebiak Teferi Demissie Tufa Dinku Asher Siebert Jemal Seid Nachiketa Acharya National Meteorological Agency of Ethiopia Addis Ababa Ethiopia Key Laboratory of Meteorological Disaster Ministry of Education (KLME)/International Joint Research Laboratory of Climate and Environment Change (ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD) Nanjing University of Information Science & Technology (NUIST) Nanjing China International Research Institute for Climate and Society (IRI) The Earth Institute Columbia University New York USA NORCE Norwegian Research Center Bjerknes Center for Climate Research Bergen Norway CGIAR Research Program on Climate Change Agriculture and Food Security (CCAFS) East Africa Addis Ababa Ethiopia Ethiopian Institute of Agricultural Research Addis Ababa Ethiopia Scuola Superiore Sant’Anna Pisa Italy Center for Earth System Modeling Analysis and Data Department of Meteorology and Atmospheric Science Pennsylvania State University University Park PA USA

In recent years, there has been increasing demand for high-resolution seasonal climate forecasts at sufficient lead times to allow response planning from users in agriculture, hydrology, disaster risk management, and health, among others. This paper examines the forecasting skill of the North American Multi-model Ensemble (NMME) over Ethiopia during the June to September (JJAS) season. The NMME, one of the multi-model seasonal forecasting systems, regularly generates monthly seasonal rainfall forecasts over the globe with 0.5 - 11.5 months lead time. The skill and predictability of seasonal rainfall are assessed using 28 years of hindcast data from the NMME models. The forecast skill is quantified using canonical correlation analysis (CCA) and root mean square error. The results show that the NMME models capture the JJAS seasonal rainfall over central, northern, and northeastern parts of Ethiopia while exhibiting weak or limited skill across western and southwestern Ethiopia. The performance of each model in predicting the JJAS seasonal rainfall is variable, showing greater skill in predicting dry conditions. Overall, the performance of the multi-model ensemble was not consistently better than any single ensemble member. The correlation of observed and predicted seasonal rainfall for the better performing models—GFDL-CM2p5-FLOR-A06, CMC2-CanCM4, GFDL-CM2p5-FLOR-B01 and NASA-GMAO-062012—is 0.68, 0.58, 0.52, and 0.5, respectively. The COLA-RSMAS-CCSM4, CMC1- CanCM3 and NCEP-CFSv2 models exhibit less skill, with correlations less than 0.4. In general, the NMME offers

关键词： Ethiopia Ensemble June-September Correlation Coefficient Skill

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Spin-tunable thermoelectric performance in monolayer chromium pnictides

arXiv

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arXiv 2021年

作者： Muntini, Melania S. Suprayoga, Edi Wella, Sasfan A. Fatimah, Iim Yuwana, Lila Seetawan, Tosawat Cahaya, Adam B. Nugraha, Ahmad R.T. Hasdeo, Eddwi H. Department of Physics Faculty of Science and Data Analytics Institut Teknologi Sepuluh Nopember Surabaya60111 Indonesia Research Center for Quantum Physics National Research and Innovation Agency Tangerang Selatan15314 Indonesia Center of Excellence on Alternative Energy Research and Development Institution Sakon Nakhon Rajabhat University Sakon Nakhon47000 Thailand Program of Physics Faculty of Science and Technology Sakon Nakhon Rajabhat University Sakon Nakhon47000 Thailand Department of Physics Faculty of Mathematics and Natural Sciences Universitas Indonesia Depok16424 Indonesia Department of Physics and Material Science University of Luxembourg L-1511 Luxembourg

Historically, finding two-dimensional (2D) magnets is well known to be a difficult task due to instability against thermal spin fluctuations. Metals are also normally considered poor thermoelectric (TE) materials. Combining intrinsic magnetism in two dimensions with conducting properties, one may expect to get the worst for thermoelectrics. However, we will show this is not always the case. Here, we investigate spin-dependent TE properties of monolayer chromium pnictides (CrX, where X = P, As, Sb, and Bi) using first-principles calculations of electron- and phonon-energy dispersion, along with Boltzmann transport formalism under energy-dependent relaxation time approximation. All the CrX monolayers are dynamically stable and they also exhibit half metallicity with ferromagnetic ordering. Using the spin-valve setup with antiparallel spin configuration, the half metallicity and ferromagnetism in monolayer CrX enable manipulation of spin degrees of freedom to tune the TE figure of merit (ZT). At optimized chemical potential and operating temperature of 500 K, the maximum ZT values (≈ 0.22, 0.12, and 0.09) with the antiparallel spin-valve setup in CrAs, CrSb, and CrBi improve up to almost twice the original values (ZT ≈ 0.12, 0.08, and 0.05) without the spin-valve configuration. Only in CrP, which is the lightest species and less spin-polarized among CrX, the maximum ZT (≈ 0.34) without the spin-valve configuration is larger than that (≈ 0.19) with the spin-valve one. We also find that, at 500 K, all the CrX monolayers possess exceptional TE power factors of about 0.02-0.08 W/m.K2, which could be one of the best values among 2D conductors. © 2021, CC BY.

关键词： Chromium

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International cooperation in cardiogenic shock is key to improving outcomes: Cardiogenic Shock Working Group impacts a single center in a developing country

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Journal of Heart and Lung Transplantation 2025年第7期44卷 1165-1171页

作者： Ortega-Hernández, Jorge A. González-Pacheco, Héctor Hernandez-Montfort, Jaime Araiza-Garaygordobil, Diego Manzur-Sandoval, Daniel Gopar-Nieto, Rodrigo Sierra-Lara-Martínez, Daniel Kanwar, Manreet Sinha, Shashank S. Garan, Arthur Reshad Burkhoff, Daniel Abraham, Jacob Kapur, Navin K. Arias-Mendoza, Alexandra Instituto Nacional de Cardiologia Ignacio Chavez Coronary Care Unit Ciudad De Mexico Mexico Central Texas Baylor Scott & White Health Advanced Heart Failure and Recovery Program Temple Texas United States Cardiovascular Institute at Allegheny Health Network Pittsburgh PA United States Inova Heart and Vascular Institute Cardiac Intensive Care Unit Fairfax Virginia United States Beth Israel Deaconess Medical Center Advanced Heart Failure and Transplant Cardiology Boston Massachusetts United States Cardiovascular Research Foundation Heart Failure Hemodynamics and MCS Research New York New York United States Providence Heart Institute Center for Cardiovascular Analytics Research and Data Science (CARDS) Providence St. Joseph Health Portland Oregon United States Tufts Medical Center Inc. Cardiovascular Center for Research and Innovation Boston Massachusetts United States

The Cardiogenic Shock Working Group (CSWG) is an international research consortium formed in 2016. The National Institute of Cardiology Ignacio Chavez joined in 2021 and launched a cardiogenic shock (CS) program in 2022. This study evaluates the impact of CSWG core standards on outcomes in a middle-income country reference center of 9,430 patients with CS (Society for Cardiovascular Angiography and Interventions [SCAI] stages B→E) from a registry of 28,054 admissions (2005–2023). Using multivariate Cox regression and propensity score matching, outcomes were compared between historic pre-CSWG (2005–2021) and contemporary pre-CSWG (2017–2021) eras vs the CSWG era (2022–2023). Adoption of CS-team standards increased the use of pulmonary artery catheters (4.2%, 4% vs 7.9%, p < 0.001) and mechanical circulatory support devices (8.1% to 10.3%, p = 0.014) only in the legacy era. Reducing mortality from 22.3% and 20.5% vs 15.3% (p < 0.001). The adjusted hazard ratio for mortality in the pre-CSWG era was 1.22 (p = 0.015) for the historical cohort and 1.20 (p = 0.047) for the contemporary cohort. CS-international collaboration enhanced outcomes through standardized protocols, advanced interventions, and dedicated CS teams, underscoring the importance of international cooperation in CS care. © 2025 International Society for the Heart and Lung Transplantation

关键词： cardiogenic shock international cooperation mechanical circulatory support pulmonary artery catheter shock teams

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The evolution of lithium-ion battery recycling

Nature Reviews Clean Technology

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Nature Reviews Clean Technology 2025年第1期1卷

作者： Xiaotu Ma Zifei Meng Yan Wang Marilena Velonia Bellonia Jeffrey Spangenberger Gavin Harper Eric Gratz Elsa Olivetti Renata Arsenault Mechanical and Materials Engineering Department Worcester Polytechnic Institute Worcester MA USA Technology and Policy Program Institute for Data Systems and Society Massachusetts Institute of Technology Cambridge MA USA ReCell Center Argonne National Laboratory Lemont IL USA School of Metallurgy and Materials University of Birmingham Birmingham UK The Faraday Institution Harwell Science and Innovation Campus Didcot UK Ascend Elements Inc. Westborough MA USA Department of Materials Science and Engineering Massachusetts Institute of Technology Cambridge MA USA Ford Ion Park Battery Center of Excellence Romulus MI USA

Demand for lithium-ion batteries (LIBs) is increasing owing to the expanding use of electrical vehicles and stationary energy storage. Efficient and closed-loop battery recycling strategies are therefore needed, which will require recovering materials from spent LIBs and reintegrating them into new batteries. In this Review, we outline the current state of LIB recycling, evaluating industrial and developing technologies. Among industrial technologies, pyrometallurgy can be broadly applied to diverse electrode materials but requires operating temperatures of over 1,000 °C and therefore has high energy consumption. Hydrometallurgy can be performed at temperatures below 200 °C and has material recovery rates of up to 93% for lithium, nickel and cobalt, but it produces large amounts of wastewater. Developing technologies such as direct recycling and upcycling aim to increase the efficiency of LIB recycling and rely on improved pretreatment processes with automated disassembly and cleaner mechanical separation. Additionally, the range of materials recovered from spent LIBs is expanding from the cathode materials recycled with established methods to include anode materials, electrolytes, binders, separators and current collectors. Achieving an efficient recycling ecosystem will require collaboration between recyclers, battery manufacturers and electric vehicle manufacturers to aid the design and automation of battery disassembly lines.

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ZokorDB: tissue specific regulatory network annotation for non-coding elements of plateau zokor

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Quantitative Biology 2020年第1期8卷 43-50页

作者： Jingxue Xin Junjun Hao Lang Chen Tao Zhang Lei Li Luonan Chen Wenmin Zhao Xuemei Lu Peng Shi Yong Wang CEMS NCMISMDISAcademy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China State Key Laboratory of Genetic Resources and Evolution Laboratory of Evolutionary and Functional GenomicsKunming Institute of ZoologyChinese Academy of SciencesKunming 650223China Key Laboratory of Systems Biology Innovation Center for Cell Signaling NetworkInstitute of Biochemistry and Cell BiologyShanghai Institutes for Biological SciencesChinese Academy of SciencesShanghai 200031China Beijing Institute of Genomics Chinese Academy of SciencesBeijing 100101China Center for Excellence in Animal Evolution and Genetics Chinese Academy of SciencesKunming 650223China Department of Statistics Department of Biomedical Data ScienceBio-X ProgramStanford UniversityStanfordCA 94305USA University of Chinese Academy of Sciences Beijing 100049China

Background:Plateau zokor inhabits in sealed burrows from 2,000 to 4,200 meters at Qinghai-Tibet *** extreme living env ironment makes it a great model to study animal adaptation to hypoxia,low temperature,and high carbon dioxide ***:We provide an integrated resource,ZokorDB,for tissue specific regulatory network annotation for *** is based on a high-quality draft genome of a plateau zokor at 3,300 m and its transcriptional profiles in brain,heart,liver,kidney,and *** conserved non-coding elements of zokor are annotated by their nearest genes and upstream transcriptional factor motif binding ***:ZokorDB provides a general draft gene regulatory network(GRN),Le?potential transcription factor(TF)binds to non-coding regulatory elements and regulates the expression of target genes(TG).Furthermore,we refined the GRN by incorporating matched RNA-seq and DNase-seq data from mouse ENCODE project and reconstructed five tissue-specific regulatory ***:A web-based,open-access database is developed for easily searching,visualizing,and downloading the annotation and *** pipeline of non-coding region annotation for zokor will be useful for other non-model *** is free available at the website(***/zokordb/).

关键词： tissue specific regulatory network non-coding element plateau zokor non-model species

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Core variables for real-world clinicogenomic data collection in precision oncology

ESMO Real World Data and Digital Oncology

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ESMO Real World data and Digital Oncology 2025年 7卷 100117-100117页

作者： R. Dienstmann A. Hackshaw J.-Y. Blay C. Le Tourneau OC Precision Medicina Oncoclínicas & Co São Paulo Brazil PhD Program Doctoral School University of Vic—Central University of Catalonia Barcelona Spain Oncology Data Science Vall d’Hebron Institute of Oncology Barcelona Spain Cancer Research UK and UCL Cancer Trials Centre University College London London UK Centre Léon Bérard and Université Claude Bernard Lyon France Institut Curie Department of Drug Development and Innovation (D3i) Paris-Saclay University Paris France

Background Precision oncology evidence gaps may be bridged using real-world clinicogenomic data; however, current limitations compromise real-world data collection and evidence generation. We aimed to define a set of precision oncology core variables that can aid in fit-for-purpose real-world data collection to be used for a range of purposes and by various stakeholders based on the approach adopted when designing the WAYFIND-R registry (NCT04529122). Materials and methods A panel of precision oncology experts created a list of variables based on standard dictionaries and vocabularies, which was aligned with the European Medical Agency’s draft guidelines for registry-based studies. A list of core variables was selected from the initial broad list of variables. Results The initial overall list (∼500 variables) was consolidated to ∼150 variables that covered the entirety of the patient journey in oncology. The panel gave highest priority to patient demographics, socioeconomic information and comorbidities, cancer details, molecular information, particularly predictive biomarkers in routine use and next-generation sequencing technical aspects, systemic cancer therapies and other treatments, outcome assessments and survival outcomes. Conclusions The core oncology variables represent a harmonized list of key clinicogenomic data elements that can be collected during a patient’s journey in oncology and leveraged for their primary intended purpose of molecular tumor board decision making, and might be used for further secondary research purposes, if legal requirements allow. Definition of this list of core variables will help generate evidence from research- or regulatory-oriented precision oncology studies by ensuring synergy, dataset connectivity, and interoperability across different data.

关键词： precision oncology real-world data solid tumors next-generation sequencing molecular tumor boards

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Development and Evaluation of a Process to Link Cancer Patients in the SEER Registries to National Medicaid Enrollment data

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Journal of the National Cancer Institute - Monographs 2020年第55期2020卷 89-95页

作者： Warren, Joan L. Benner, Suzie Stevens, Jennifer Enewold, Lindsey Huang, Bin Zhao, Lirong Tilahun, Negussie Bradley, Cathy J. Healthcare Assessment Research Branch Healthcare Delivery Research Program Division of Cancer Control and Population Science National Cancer Institute Bethesda MD United States Fu Associates Ltd Arlington VA United States Information Management Services Calverton MD United States Department of Biostatistics College of Public Health Markey Cancer Center University of Kentucky Lexington KY United States Division of Data Research and Analytic Methods Center for Medicare and Medicaid Innovation Centers for Medicare and Medicaid Services Baltimore MD United States Department of Health Systems Management and Policy School of Public Health University of Colorado Aurora CO United States

Cancer patients receiving Medicaid have worse prognosis. Patients in 14 Surveillance, Epidemiology, and End Results (SEER) cancer registries were linked to national Medicaid enrollment files, 2006-2013, to determine enrollment status during the year before and after diagnosis. A deterministic algorithm based on Social Security number, Medicare Health Insurance Claim number, sex, and date of birth was utilized. Results were compared with an independent linkage of Kentucky-based SEER and Medicaid data. A total 559 484 cancer cases were linked to national Medicaid enrollment files, representing 15-17% of persons with cancer yearly. About 60% of these cases were a complete match on all variables. There was 99% agreement on enrollment status compared with the Kentucky linked data. SEER data were successfully linked to national Medicaid enrollment data. NCI will make the linked data available to researchers, allowing for more detailed assessments of the impact Medicaid enrollment has on cancer diagnosis and outcomes. © 2020 Published by Oxford University Press. This work is written by US Government employees and is in the public domain in the US.

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Landscape of global urban environmental resistome and its association with local socioeconomic and medical status

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science China(Life sciences) 2024年第6期67卷 1292-1301页

作者： Jun Wu Yige Hu Michael H Perlin David Danko Jun Lu Manuela Oliveira Johannes Werner Maria M Zambrano Maria A Sierra Olayinka O Osuolale Paweł Łabaj Nicolás Rascovan Nur Hazlin Hazrin-Chong Soojin Jang Haruo Suzuki Marina Nieto-Caballero Bharath Prithiviraj Patrick K H Lee Agnieszka Chmielarczyk Anna Różańska Yongxiang Zhao Lan Wang Christopher E Mason Tieliu Shi Center for Bioinformatics and Computational Biology and the Institute of Biomedical SciencesSchool of Life SciencesEast China Normal UniversityShanghai 200241China Department of Biology Program on Disease EvolutionUniversity of LouisvilleLouisville 40292USA Weill Cornell Medicine New York 10065USA The Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine New York 10065USA Department of Pulmonary Medicine Shanghai Chest HospitalShanghai Jiao Tong UniversityShanghai 200025China i3S-Instituto de Investiga玢o e Inova玢o em Saúde Universidade do PortoPorto 4050-290Portugal Ipatimup-Instituto de Patologia e Imunologia Molecular da Universidade do Porto Porto 4200-465Portugal Departamento de Biologia Faculdade de CiênciasUniversidade do PortoPorto 4050-290Portugal High Performance and Cloud Computing Group Zentrum für Datenverarbeitung(ZDV)Eberhard Karls University of TübingenW鋍hterstra遝7672074TübingenGermany Corporación Corpogen Research Center Bogotá110311Colombia Applied Environmental Metagenomics and Infectious Diseases Research(AEMIDR) Department of Biological SciencesElizade UniversityIlara-Mokin 340271Nigeria Maopolska Centre of Biotechnology Jagiellonian UniversityKraków 30-005Poland Aix-Marseille Université Mediterranean Institute of OceanologyUniversitéde ToulonCNRSIRDUM 110Marseille 83041France Department of Biological Sciences and Biotechnology Faculty of Science and TechnologyUniversiti Kebangsaan Malaysia43600 UKM BangiSelangor Institut Pasteur Korea Seoul 13488Republic of Korea Faculty of Environment and Information Studies Keio UniversityFujisawaKanagawa 252-0882Japan University of Colorado at Boulder CivilEnvironmental and Architectural DepartmentBoulder 80303USA Brooklyn College of the City University of New York Brooklyn 11210USA School of Energy and Environment City University of Hong KongHong Kong 999077China Department of Microbiology Faculty of MedicineJagiellonian UniversityKraków 30-005Poland Biological Targeting Diagnosis and The

Antimicrobial resistance(AMR)poses a critical threat to global health and development,with environmental factors—particularly in urban areas—contributing significantly to the spread of antibiotic resistance genes(ARGs).However,most research to date has been conducted at a local level,leaving significant gaps in our understanding of the global status of antibiotic resistance in urban *** address this issue,we thoroughly analyzed a total of 86,213 ARGs detected within 4,728 metagenome samples,which were collected by the Meta SUB International Consortium involving diverse urban environments in 60 cities of 27 countries,utilizing a deep-learning based *** findings demonstrated the strong geographical specificity of urban environmental resistome,and their correlation with various local socioeconomic and medical *** also identified distinctive evolutionary patterns of ARG-related biosynthetic gene clusters(BGCs)across different countries,and discovered that the urban environment represents a rich source of novel *** study provides a comprehensive overview of the global urban environmental resistome,and fills a significant gap in our knowledge of large-scale urban antibiotic resistome analysis.

关键词： urban environment metagenome antibiotic resistance resistance diversity biosynthetic gene clusters

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Multi-label classification for multi-temporal, multi-spatial coral reef condition monitoring using vision foundation model with adapter learning

arXiv

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arXiv 2025年

作者： Shao, Xinlei Chen, Hongruixuan Zhao, Fan Magson, Kirsty Chen, Jundong Li, Peiran Wang, Jiaqi Sasaki, Jun Department of Socio-Cultural Environmental Studies Graduate School of Frontier Sciences The University of Tokyo Chiba Kashiwa277-8563 Japan Department of Complexity Science and Engineering Graduate School of Frontier Sciences The University of Tokyo Chiba Kashiwa277-8563 Japan Department of Environment Systems Graduate School of Frontier Sciences The University of Tokyo Chiba Kashiwa277-8563 Japan New Heaven Reef Conservation Program Koh Tao Surat Thani84360 Thailand Data Science and AI Innovation Research Promotion Center Shiga University Shiga Hikone522-8522 Japan Interfaculty Initiative in Information Studies The University of Tokyo Tokyo113-0033 Japan

Coral reef ecosystems provide essential ecosystem services, but face significant threats from climate change and human activities. Although advances in deep learning have enabled automatic classification of coral reef conditions, conventional deep models struggle to achieve high performance when processing complex underwater ecological images. Vision foundation models, known for their high accuracy and cross-domain generalizability, offer promising solutions. However, fine-tuning these models requires substantial computational resources and results in high carbon emissions. To address these challenges, adapter learning methods such as Low-Rank Adaptation (LoRA) have emerged as a solution. This study introduces an approach integrating the DINOv2 vision foundation model with the LoRA fine-tuning method. The approach leverages multi-temporal field images collected through underwater surveys at 15 dive sites at Koh Tao, Thailand, with all images labeled according to universal standards used in citizen science-based conservation programs. The experimental results demonstrate that the DINOv2-LoRA model achieved superior accuracy, with a match ratio of 64.77%, compared to 60.34% achieved by the best conventional model. Furthermore, incorporating LoRA reduced the trainable parameters from 1,100M to 5.91M. Transfer learning experiments conducted under different temporal and spatial settings highlight the exceptional generalizability of DINOv2-LoRA across different seasons and sites. This study is the first to explore the efficient adaptation of foundation models for multi-label classification of coral reef conditions under multi-temporal and multi-spatial settings. The proposed method advances the classification of coral reef conditions and provides a tool for monitoring, conserving, and managing coral reef ecosystems. © 2025, CC BY-NC-SA.

关键词： Biotic

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