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A Computational Method forn-Dimensional Laplace Transforms Involved with Fourier Cosine Transform

International Scholarly Research Notices 2013年第1期2013卷

作者： Jafar Saberi-Nadjafi Department of Applied Mathematics School of Mathematical Sciences Ferdowsi University of Mashhad Mashhad Iranum.ac.ir The Center of Excellence on Modeling and Control Systems (CEMCE) Ferdowsi University of Mashhad Mashhad Iranum.ac.ir

In 2007, the author published some results on n -dimensional Laplace transform involved with the Fourier sine transform. In this paper, we propose some new result in n -dimensional Laplace transforms involved with Fourier cosine transform; these results provide few algorithms for evaluating some n -dimensional Laplace transform pairs. In addition, some examples are also presented, which explain the useful applications of the obtained results. Therefore, one can produce some two- and three- as well as n -dimensional Laplace transforms pairs.

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Weakly Aligned Feature Fusion for Multi-modal Object Detection

arXiv

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arXiv 2022年

作者： Zhang, Lu Liu, Zhiyong Zhu, Xiangyu Song, Zhan Yang, Xu Lei, Zhen Qiao, Hong The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100086 China Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of Sciences Shanghai200031 China The Center for Biometrics and Security Research National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing100190 China The Centre for Artificial Intelligence and Robotics Hong Kong Institute of Science & Innovation Chinese Academy of Sciences Hong Kong The Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Guangdong Shenzhen518055 China

To achieve accurate and robust object detection in the real-world scenario, various forms of images are incorporated, such as color, thermal, depth, etc. However, multi-modal data often suffer from the position shift problem, i.e. the image pair is not strictly aligned, making one object has different positions in different modalities. For the deep learning method, this problem makes it difficult to fuse multi-modal features and puzzles the CNN training. In this paper, we propose a general multi-modal detector named Aligned Region CNN (AR-CNN) to tackle the position shift problem. Firstly, a region feature alignment module with adjacent similarity constraint is designed to consistently predict the position shift between two modalities and adaptively align the cross-modal region features. Secondly, we propose a novel RoI jitter strategy to improve the robustness to unexpected shift patterns. Thirdly, we present a new multi-modal feature fusion method, which selects the more reliable feature and suppresses the less useful one via feature re-weighting. Additionally, by locating bounding boxes in both modalities and building their relationships, we provide novel multi-modal labelling named KAIST-Paired. Extensive experiments on 2D and 3D object detection, RGB-T and RGB-D datasets demonstrate the effectiveness and robustness of our method. Copyright © 2022, The Authors. All rights reserved.

关键词： Object recognition

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Nearest-Better Network for Fitness Landscape Analysis of Continuous Optimization Problems

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IEEE Transactions on Evolutionary Computation 2024年

作者： Diao, Yiya Li, Changhe Zeng, Sanyou Yang, Shengxiang Coello, Carlos A. Coello China University of Geosciences School of Automation Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan China Anhui University of Sciences and Technology School of Artificial Intelligence Hefei China China University of Geosciences School of Mechanical Engineering and Electronic Information Wuhan China De Montfort University School of Computer Science and Informatics LeicesterLE1 9BH United Kingdom Department of Computer Science CINVESTAV-IPN 07360 Mexico Tecnologico de Monterrey Faculty of Excellence The School of Engineering and Sciences N.L. Monterrey Mexico

Fitness landscape analysis (FLA) is quite important in evolutionary computation. In this paper, we propose a novel FLA method, the nearest-better network (NBN), which uses the nearest-better relationship to simplify the original fitness landscape of continuous optimization problems. We introduce an efficient algorithm to calculate NBN for continuous problems. We also propose four numerical measurements and a 3D visualization method based on NBN. Experiments show that compared to the other main FLA methods, the four numerical measurements proposed here can effectively measure the four intended features: neutrality, ruggedness, modality, and basin of attraction, respectively, and common features of the fitness landscape can be maintained in 3D NBN visualization, regardless of the scale of the problem. NBN also provides a view of how algorithms search in high-dimensional problems with the help of the 3D NBN visualization. © 1997-2012 IEEE.

关键词： Optimization algorithms

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Burdens of type 2 diabetes and cardiovascular disease attributable to sugar-sweetened beverages in 184 countries (06 Jan, 10.1038/s41591-024-03345-4, 2025)

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NATURE MEDICINE 2025年第2期31卷 696-696页

作者： Lara-Castor, Laura O'Hearn, Meghan Cudhea, Frederick Miller, Victoria Shi, Peilin Zhang, Jianyi Sharib, Julia R. Cash, Sean B. Barquera, Simon Micha, Renata Mozaffarian, Dariush Food Is Medicine Institute Friedman School of Nutrition Science and Policy Tufts University Boston MA USA Institute of Health Metrics and Evaluation University of Washington Seattle WA USA Food Systems for the Future Institute Chicago IL USA Department of Medicine McMaster University Hamilton Ontario Canada Population Health Research Institute Hamilton Ontario Canada University of Thessaly Volos Greece Tufts University School of Medicine Boston MA USA Department of Medicine Tufts Medical Center Boston MA USA Center for Surgery and Public Health Brigham and Women’s Hospital Boston MA USA Friedman School of Nutrition Science and Policy Tufts University Boston MA USA Research Center on Nutrition and Health National Institute of Public Health Cuernavaca Mexico National Institute of Public Health (INSP) Cuernavaca Mexico Academy of Athens Athens Greece Acibadem University Istanbul Turkey Addis Ababa University Addis Ababa Ethiopia Aga Khan Foundation Geneva Switzerland All India Institute of Medical Sciences New Delhi India American University of Beirut Beirut Lebanon Amrita School of Dentistry Eranakulum India Andalas University Padang Indonesia Arab Center for Nutrition Manama Bahrain Ardabil University of Medical Sciences Ardabil Iran Bacha Khan University Charsadda Pakistan Biodiversity International Nairobi Kenya Brighton and Sussex Medical School Brighton UK Center for Studies of Sensory Impairment Aging and Metabolism (CeSSIAM) Guatemala City Guatemala Centre For Media Studies New Delhi India Centro de Atencion Nutricional Antimano (CANIA) Miami FL USA Centro de Estudios sobre Nutrición Infantil (CESNI) Buenos Aires Argentina Child Growth and Development Research Center Isfahan University of Medical Sciences Isfahan Iran College of Applied Sciences Department of Food Science and Applied Nutrition Addis Ababa Science and Technology University Addis Ababa Ethiopia Consultative Group on International Agricultural Research (CGIAR) M

The consumption of sugar-sweetened beverages (SSBs) is associated with type 2 diabetes (T2D) and cardiovascular diseases (CVD). However, an updated and comprehensive assessment of the global burden attributable to SSBs remains scarce. Here we estimated SSB-attributable T2D and CVD burdens across 184 countries in 1990 and 2020 globally, regionally and nationally, incorporating data from the Global Dietary Database, jointly stratified by age, sex, educational attainment and urbanicity. In 2020, 2.2 million (95% uncertainty interval 2.0–2.3) new T2D cases and 1.2 million (95% uncertainty interval 1.1–1.3) new CVD cases were attributable to SSBs worldwide, representing 9.8% and 3.1%, respectively, of all incident cases. Globally, proportional SSB-attributable burdens were higher among men versus women, younger versus older adults, higher- versus lower-educated adults, and adults in urban versus rural areas. By world region, the highest SSB-attributable percentage burdens were in Latin America and the Caribbean (T2D: 24.4%; CVD: 11.3%) and sub-Saharan Africa (T2D: 21.5%; CVD: 10.5%). From 1990 to 2020, the largest proportional increases in SSB-attributable incident T2D and CVD cases were in sub-Saharan Africa (+8.8% and +4.4%, respectively). Our study highlights the countries and subpopulations most affected by cardiometabolic disease associated with SSB consumption, assisting in shaping effective policies and interventions to reduce these burdens globally.

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The relationship between rising temperatures and malaria incidence in Hainan, China, from 1984 to 2010: a longitudinal cohort study

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The Lancet Planetary Health 2022年第4期6卷 e350-e358页

作者： Wang, Zengmiao Liu, Yonghong Li, Yapin Wang, Guangze Lourenço, José Kraemer, Moritz He, Qixin Cazelles, Bernard Li, Yidan Wang, Ruixue Gao, Dongqi Li, Yuchun Song, Wenjing Sun, Dingwei Dong, Lu Pybus, Oliver G Stenseth, Nils Chr Tian, Huaiyu State Key Laboratory of Remote Sensing Science Center for Global Change and Public Health College of Global Change and Earth System Science Beijing Normal University Beijing China Ministry of Education Key Laboratory for Biodiversity and Ecological Engineering College of Life Sciences Beijing Normal University Beijing China School of National Security and Emergency Management Beijing Normal University Beijing China Central Theater Center for Disease Control and Prevention of PLA Beijing China Hainan Center for Disease Control and Prevention Haikou China Department of Zoology University of Oxford UK Oxford United Kingdom Harvard Medical School Harvard University Boston MA United States Boston Children's Hospital Boston MA United States Department of Ecology and Evolution University of Chicago Chicago IL United States Institut de Biologie de l’École Normale Supérieure Unité Mixte de Recherche 8197 Centre National de la Recherche Scientifique et École Normale Supérieure Paris France Unité Mixte Internationnale 209 Mathematical and Computational Modeling of Complex Systems Institut de Recherche pour le Développement et Sorbonne Université Bondy France Centre for Ecological and Evolutionary Synthesis Department of Biosciences University of Oslo Oslo Norway Biosystems and Integrative Sciences Institute University of Lisbon Lisbon Portugal Department of Pathobiology and Population Science The Royal Veterinary College UK London United Kingdom

Background: The influence of rising global temperatures on malaria dynamics and distribution remains controversial, especially in central highland regions. We aimed to address this subject by studying the spatiotemporal heterogeneity of malaria and the effect of climate change on malaria transmission over 27 years in Hainan, an island province in China. Methods: For this longitudinal cohort study, we used a decades-long dataset of malaria incidence reports from Hainan, China, to investigate the pattern of malaria transmission in Hainan relative to temperature and the incidence at increasing altitudes. Climatic data were obtained from the local meteorological stations in Hainan during 1984–2010 and the WorldClim dataset. A temperature-dependent R₀ model and negative binomial generalised linear model were used to decipher the relationship between climate factors and malaria incidence in the tropical region. Findings: Over the past few decades, the annual peak incidence has appeared earlier in the central highland regions but later in low-altitude regions in Hainan, China. Results from the temperature-dependent model showed that these long-term changes of incidence peak timing are linked to rising temperatures (of about 1·5°C). Further, a 1°C increase corresponds to a change in cases of malaria from –5·6% (95% CI –4·5 to –6·6) to –9·2% (95% CI –7·6 to –10·9) from the northern plain regions to the central highland regions during the rainy season. In the dry season, the change in cases would be 4·6% (95% CI 3·7 to 5·5) to 11·9% (95% CI 9·8 to 14·2) from low-altitude areas to high-altitude areas. Interpretation: Our study empirically supports the idea that increasing temperatures can generate opposing effects on malaria dynamics for lowland and highland regions. This should be further investigated and incorporated into future modelling, disease burden calculations, and malaria control, with attention for central highland regions under climate change. Funding: S

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Author Correction: Malaria elimination on Hainan Island despite climate change

Communications Medicine

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Communications Medicine 2022年第1期2卷 1页

作者： Huaiyu Tian Naizhe Li Yonghong Liu Yidan Li Ben Wang Peiyi Wu Yapin Li Dongqi Gao Wenjing Song Moritz U. G. Kraemer José Lourenço Oliver G. Pybus Christopher Dye Hua Tan Bernard Cazelles Dingwei Sun Yuchun Li Guangze Wang State Key Laboratory of Remote Sensing Science Center for Global Change and Public Health College of Global Change and Earth System Science Beijing Normal University Beijing China Central Theater Center for Disease Control and Prevention of PLA Beijing China Department of Zoology University of Oxford Oxford UK Department of Pathobiology and Population Science The Royal Veterinary College London UK Oxford Martin School University of Oxford Oxford UK School of Biomedical Informatics the University of Texas Health Science Center at Houston Houston TX USA Institut de Biologie de l’École Normale Supérieure Unité Mixte de Recherche Centre National de la Recherche Scientifique et École Normale Supérieure Paris France Unité Mixte Internationnale Mathematical and Computational Modeling of Complex Systems Institut de Recherche pour le Développement et Sorbonne Université Bondy France Hainan Center for Disease Control and Prevention Haikou China

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Back Cover: PD-L1 Aptamer-Functionalized Metal–Organic Framework Nanoparticles for Robust Photo-Immunotherapy against Cancer with Enhanced Safety (Angew. Chem. Int. Ed. 5/2023)

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Angewandte Chemie International Edition 2023年第5期62卷

作者： Dr. Jingfang Zhang Dr. Wenzhe Li Dr. Yafei Qi Dr. Guorong Wang Prof. Lele Li Prof. Zhengyu Jin Prof. Jie Tian Prof. Yang Du Beijing Key Laboratory for Bioengineering and Sensing Technology School of Chemistry and Biological Engineering University of Science and Technology Beijing Beijing 100083 China CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety and CAS Center for Excellence in Nanoscience National Center for Nanoscience and Technology Beijing 100190 China State Key Laboratory of Natural and Biomimetic Drugs School of Pharmaceutical Sciences Peking University Beijing 100191 China CAS Key Laboratory of Molecular Imaging Beijing Key Laboratory of Molecular Imaging the State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China Department of Radiology Peking Union Medical College Hospital Peking Union Medical College and Chinese Academy of Medical Sciences Beijing 100730 China Beijing Advanced Innovation Center for Big Data-Based Precision Medicine School of Medicine Beihang University Beijing 100191 China

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PD-L1 Aptamer-Functionalized Metal–Organic Framework Nanoparticles for Robust Photo-Immunotherapy against Cancer with Enhanced Safety

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Angewandte Chemie 2022年第5期135卷

Immune checkpoint blockade has become a paradigm-shifting treatment modality to combat cancer, while conventional administration of immune checkpoint inhibitors, such as anti-PD-L1 antibody (α-PD-L1), often shows unsatisfactory immune responses and lead to severe immune-related adverse effects (irAEs). Herein, we develop a PD-L1 aptamer-based spherical nucleic acids (SNAs), which consists of oxaliplatin (OXA) encapsulated in a metal–organic framework nanoparticle core and a dense shell of aptPD-L1 (denoted as M@O-A). Upon light irradiation, this nanosystem enables concurrent photodynamic therapy (PDT), chemotherapy, and enhanced immunotherapy in one shot to inhibit both primary colorectal tumors and untreated distant tumors in mice. Notably, M@O-A shows scarcely any systemic immunotoxicity in a clinical irAEs-mimic transgenic mouse model. Collectively, this study presents a novel strategy for priming robust photo-immunotherapy against cancer with enhanced safety.

关键词： DNA Nanotechnology Immunotherapy Metal–Organic Frameworks PD-L1 Aptamer Spherical Nucleic Acids (SNAs)

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Rücktitelbild: PD-L1 Aptamer-Functionalized Metal–Organic Framework Nanoparticles for Robust Photo-Immunotherapy against Cancer with Enhanced Safety (Angew. Chem. 5/2023)

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Angewandte Chemie 2023年第5期135卷

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26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 Antwerp, Belgium. 15-20 July 2017 Abstracts

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 95-176页

作者： [Anonymous] Department of Neuroscience Yale University New Haven CT 06520 USA Department Physiology & Pharmacology SUNY Downstate Brooklyn NY 11203 USA NYU School of Engineering 6 MetroTech Center Brooklyn NY 11201 USA Departament de Matemàtica Aplicada Universitat Politècnica de Catalunya Barcelona 08028 Spain Institut de Neurobiologie de la Méditerrannée (INMED) INSERM UMR901 Aix-Marseille Univ Marseille France Center of Neural Science New York University New York NY USA Aix-Marseille Univ INSERM INS Inst Neurosci Syst Marseille France Laboratoire de Physique Théorique et Modélisation CNRS UMR 8089 Université de Cergy-Pontoise 95300 Cergy-Pontoise Cedex France Department of Mathematics and Computer Science ENSAT Abdelmalek Essaadi’s University Tangier Morocco Laboratory of Natural Computation Department of Information and Electrical Engineering and Applied Mathematics University of Salerno 84084 Fisciano SA Italy Department of Medicine University of Salerno 84083 Lancusi SA Italy Dipartimento di Fisica Università degli Studi Aldo Moro Bari and INFN Sezione Di Bari Italy Data Analysis Department Ghent University Ghent Belgium Coma Science Group University of Liège Liège Belgium Cruces Hospital and Ikerbasque Research Center Bilbao Spain BIOtech Department of Industrial Engineering University of Trento and IRCS-PAT FBK 38010 Trento Italy Department of Data Analysis Ghent University Ghent 9000 Belgium The Wellcome Trust Centre for Neuroimaging University College London London WC1N 3BG UK Department of Electronic Engineering NED University of Engineering and Technology Karachi Pakistan Blue Brain Project École Polytechnique Fédérale de Lausanne Lausanne Switzerland Departement of Mathematics Swansea University Swansea Wales UK Laboratory for Topology and Neuroscience at the Brain Mind Institute École polytechnique fédérale de Lausanne Lausanne Switzerland Institute of Mathematics University of Aberdeen Aberdeen Scotland UK Department of Integrativ

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