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IoT-Based Strawberry Disease Detection With Wall-Mounted Monitoring Cameras

IEEE Internet of Things Journal 2024年第1期11卷 1439-1451页

作者： Lin, Yi-Bing Liu, Chun-You Chen, Wen-Liang Chang, Chia-Hui Ng, Fung-Ling Yang, Krista Hsung, Jerry Department of Computer Science National Yang Ming Chiao Tung University Hsinchu30010 Taiwan China Medical University College of Humanities and Sciences Taichung404 Taiwan National Cheng Kung University MiinWu School of Computing Tainan701 Taiwan Academia Sinica Research Center for Information Technology Innovation Taipei115 Taiwan National Yang Ming Chiao Tung University College of Biological Science and Technology Hsinchu30010 Taiwan National Yang Ming Chiao Tung University Industrial Development Graduate Program College of Biological Science and Technology Hsinchu30010 Taiwan Proto Solution System Company Ltd. Hsinchu302052 Taiwan

This article proposes StrawberryTalk, an Internet of Things (IoT) platform for image-based strawberry disease detection. StrawberryTalk reuses the wall-mounted monitoring cameras without extra hardware cost. The contributions of StrawberryTalk are the utilization of IoT for automatic photo shoot and the wind detection mechanism to eliminate the obscure photos due to the wind effects. Also, the data preprocessing and the infection detection models are manipulated as IoT devices to simplify the implementation of the multicascade artificial intelligence (AI) models. We derive the relationship between the camera zoom factor and the distance between the camera and the strawberries for optimal disease detection. Accuracy of detection may be affected by obscure photos. In terms of eliminating obscure photos due to wind effect, we analytically derive the relationship between the wind alert delay and the number of obscure photos that must be retaken. For the greenhouses in the Bao Mountain, we only need to retake one photo. Based on the experiments, the mean average precision (mAP) of StrawberryTalk (to detect exact spots in a leaf) can be up to 92.37%, which is better than the previous approaches. To detect if a pot has infected leaves, the accuracy of StrawberryTalk can be up to 97.92% at the zoom factor 30×. In commercial operation, it is important to detect all infected strawberry pots. StrawberryTalk is able to detect all infected pots (i.e., recall is 100%) with a camera of zoom factor of 12× . The accuracy is 96.88%. © 2014 IEEE.

关键词： Cameras

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3D scaffolds-specific cellular mechanoresponse as a pivotal regulating factor in tissue engineering

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JMST Advances 2024年第2期6卷 121-134页

作者： Ahn, Yejin Chang, Hyewon Baek, Jieung Department of Biological Sciences Pusan National University Busan Republic of Korea Division of Mechanical and Biomedical Engineering Ewha Womans University Seoul Republic of Korea Graduate Program in System Health Science and Engineering Ewha Womans University Seoul Republic of Korea

In tissue engineering, the mechanical properties of the extracellular matrix (ECM) or scaffolds have increasingly been considered to impact therapeutic efficacy by regulating cell behaviors, including differentiation, proliferation, migration, and adhesion. However, the understanding of how cells sense, integrate, and convert the mechanical cues from the ECM cues into biochemical signals to control certain cell behaviors is still elusive, especially in 3D, which more closely mimics the natural microenvironment than 2D systems. This review highlights the key differences between 2 and 3D in the contexts of mechanoregulative cell behaviors such as cell adhesion, spreading, migration, and force transmission. Furthermore, critical designing factors that needs to be considered for the fabrication of 3D tissue engineering scaffolds is discussed: stiffness, viscoelasticity, degradability, and the immobilization of biomolecules. Although mechanotransduction in 3D is actively being studied, understanding cellular mechanotransduction in 3D and designing of mechanoregulative 3D scaffolds still presents several challenges, including varying mechanical properties depending on different tissues, dynamic mechanical environments, and integration of multimodal cues. Interdisciplinary methodologies encompassing material engineering, cell biology, and mechanical engineering would serve to mitigate these challenges and augment our understanding of mechanoregulation governing cellular behaviors, thus fostering advancements in biomedical applications in the future.

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CAR-T and CAR-NK as cellular cancer immunotherapy for solid tumors

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Cellular & Molecular Immunology 2024年第10期21卷 1089-1108页

作者： Lei Peng Giacomo Sferruzza Luojia Yang Liqun Zhou Sidi Chen Department of Genetics Yale University School of MedicineNew HavenCTUSA System Biology Institute Yale UniversityWest HavenCTUSA Combined Program in the Biological and Biomedical Sciences Yale UniversityNew HavenCTUSA Molecular Cell Biology Geneticsand Development ProgramYale UniversityNew HavenCTUSA Immunobiology Program Yale UniversityNew HavenCTUSA Yale Comprehensive Cancer Center Yale University School of MedicineNew HavenCTUSA Department of Neurosurgery Yale University School of MedicineNew HavenCTUSA Yale Stem Cell Center Yale University School of MedicineNew HavenCTUSA Yale Liver Center Yale University School of MedicineNew HavenCTUSA Yale Center for Biomedical Data Science Yale University School of MedicineNew HavenCTUSA Yale Center for RNA Science and Medicine Yale University School of MedicineNew HavenCTUSA

In the past decade,chimeric antigen receptor(CAR)-T cell therapy has emerged as a promising immunotherapeutic approach for combating cancers,demonstrating remarkable efficacy in relapsed/refractory hematological malignancies in both pediatric and adult ***-natural killer(CAR-NK)cell complements CAR-T cell therapy by offering several distinct ***-NK cells do not require HLA compatibility and exhibit low safety ***,CAR-NK cells are conducive to“off-the-shelf”therapeutics,providing significant logistic advantages over CAR-T *** CAR-T and CAR-NK cells have shown consistent and promising results in hematological ***,their efficacy against solid tumors remains limited due to various obstacles including limited tumor trafficking and infiltration,as well as an immuno-suppressive tumor *** this review,we discuss the recent advances and current challenges of CAR-T and CAR-NK cell immunotherapies,with a specific focus on the obstacles to their application in solid *** also analyze in depth the advantages and drawbacks of CAR-NK cells compared to CAR-T cells and highlight CAR-NK CAR ***,we explore future perspectives of these adoptive immunotherapies,highlighting the increasing contribution of cutting-edge biotechnological tools in shaping the next generation of cellular immunotherapy.

关键词： CAR-T CAR-NK Cell therapy Cancer immunotherapy Solid tumor

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Materials Discovery with Extreme Properties via Reinforcement Learning-Guided Combinatorial Chemistry

arXiv

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arXiv 2023年

作者： Kim, Hyunseung Choi, Haeyeon Kang, Dongju Lee, Won Bo Na, Jonggeol School of Chemical and Biological Engineering Seoul National University Korea Republic of Department of Chemical Engineering and Materials Science Ewha Womans University Korea Republic of Graduate Program in System Health Science and Engineering Ewha Womans University Korea Republic of

The goal of most materials discovery is to discover materials that are superior to those currently known. Fundamentally, this is close to extrapolation, which is a weak point for most machine learning models that learn the probability distribution of data. Herein, we develop reinforcement learning-guided combinatorial chemistry, which is a rule-based molecular designer driven by trained policy for selecting subsequent molecular fragments to get a target molecule. Since our model has the potential to generate all possible molecular structures that can be obtained from combinations of molecular fragments, unknown molecules with superior properties can be discovered. We theoretically and empirically demonstrate that our model is more suitable for discovering better compounds than probability distribution-learning models. In an experiment aimed at discovering molecules that hit seven extreme target properties, our model discovered 1,315 of all target-hitting molecules and 7,629 of five target-hitting molecules out of 100,000 trials, whereas the probability distribution-learning models failed. Moreover, it has been confirmed that every molecule generated under the binding rules of molecular fragments is 100% chemically valid. To illustrate the performance in actual problems, we also demonstrate that our models work well on two practical applications: discovering protein docking molecules and HIV inhibitors. © 2023, CC BY-NC-SA.

关键词： Probability distributions

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Rapid assessment checklist for green roof ecosystem services in Bangkok,Thailand

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Ecological Processes 2020年第1期9卷 205-221页

作者： Rattanapan Phoomirat Nipada Ruankaew Disyatat Tae Yoon Park Dong Kun Lee Pongchai Dumrongrojwatthana Biological Sciences Program Faculty of ScienceChulalongkorn UniversityBangkok 10330Thailand Department of Biology Faculty of ScienceChulalongkorn UniversityBangkok 10330Thailand Graduate School of Education Yonsei UniversitySeoul 03722Republic of Korea Department of Landscape Architecture and Rural System Engineering Seoul National UniversitySeoul 08826Republic of Korea

Background:A green roof is a man-made ecosystem created when a rooftop is covered with substrate and *** green roof ecosystems(GREs)are able to provide ecosystem services,there is currently no assessment tool available to specifically evaluate ***,the aim of this study was to develop a rapid assessment checklist(RAC)to assess GRE services(GRES),which was developed and tested on 10 green roofs in Bangkok,***:The RAC consisted of 46 proxy indicators(33 qualitative and 13 quantitative indicators)encompassing various aspects of *** GRES values or scores varied according to structural differences in the green *** average score(from a maximum of 100)of total ecosystem services was 61±7,which could be inferred as a good performance in ecosystem service *** highest scores were obtained from the regulating services at 68±*** lowest average score was 53±11 from the provisioning ***:The RAC was able to evaluate the levels of GRES provided by the selected green roofs,enabling the meaningful comparison of their potential capability to provide ***,this RAC could be an innovative tool for evaluation of four categories of GRES.

关键词： Vegetated roof Evaluation Composite indicator Urban ecosystem Ecosystem management

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Optimal Planning of Hybrid Energy Storage systems Using Curtailed Renewable Energy Through Deep Reinforcement Learning

SSRN

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SSRN 2023年

作者： Kang, Dongju Kang, Doeun Hwangbo, Sumin Niaz, Haider Lee, Won Bo Liu, J. Jay Na, Jonggeol School of Chemical and Biological Engineering Seoul National University Gwanak-ro 1 Gwanak-gu Seoul08826 Korea Republic of Department of Chemical Engineering and Materials Science Ewha Womans University Seoul03760 Korea Republic of Graduate Program in System Health Science and Engineering Ewha Womans University Seoul03760 Korea Republic of Department of Chemical Engineering Pukyong National University Busan48513 Korea Republic of

Energy management systems (EMS) are becoming increasingly important in order to utilize the continuously growing curtailed renewable energy. Promising energy storage systems (ESS), such as batteries and green hydrogen should be employed to maximize the efficiency of energy stakeholders. However, optimal decision-making, i.e., planning the leveraging between different strategies, is confronted with the complexity and uncertainties of large-scale problems. Here, we propose a sophisticated deep reinforcement learning (DRL) methodology with a policy-based algorithm to realize the real-time optimal ESS planning under the curtailed renewable energy uncertainty. A quantitative performance comparison proved that the DRL agent outperforms the scenario-based stochastic optimization (SO) algorithm, even with a wide action and observation space. Owing to the uncertainty rejection capability of the DRL, we could confirm a robust performance, under a large uncertainty of the curtailed renewable energy, with a maximizing net profit and stable system. Action-mapping was performed for visually assessing the action taken by the DRL agent according to the state. The corresponding results confirmed that the DRL agent learns the way like what a human expert would do, suggesting reliable application of the proposed methodology. © 2023, The Authors. All rights reserved.

关键词： Reinforcement learning

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Dynamic phenotypic heterogeneity and the evolution of multiple RNA subtypes in hepatocellular carcinoma:the PLANET study

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National science Review 2022年第3期9卷 96-109页

作者： Weiwei Zhai Hannah Lai Neslihan Arife Kaya Jianbin Chen Hechuan Yang Bingxin Lu Jia Qi Lim Siming Ma Sin Chi Chew Khi Pin Chua Jacob Josiah Santiago Alvarez Pauline Jieqi Chen Mei Mei Chang Lingyan Wu Brian K.P.Goh Alexander Yaw-Fui Chung Chung Yip Chan Peng Chung Cheow Ser Yee Lee Juinn Huar Kam Alfred Wei-Chieh Kow Iyer Shridhar Ganpathi Rawisak Chanwat Jidapa Thammasiri Boon Koon Yoong Diana Bee-Lan Ong Vanessa H.de Villa Rouchelle D.Dela Cruz Tracy Jiezhen Loh Wei Keat Wan Zeng Zeng Anders Jacobsen Skanderup Yin Huei Pang Krishnakumar Madhavan Tony Kiat-Hon Lim Glenn Bonney Wei Qiang Leow Valerie Chew Yock Young Dan Wai Leong Tam Han Chong Toh Roger Sik-Yin Foo Pierce Kah-Hoe Chow Genome Institute of Singapore Agency for Science Technology and Research Key Laboratory of Zoological Systematics and Evolution Institute of Zoology Chinese Academy of Sciences Center for Excellence in Animal Evolution and Genetics Chinese Academy of Sciences School of Biological Sciences Nanyang Technological University Division of Biosciences Faculty of Life Sciences Division of Surgery and Surgical Oncology National Cancer Centre Department of Hepato-Pancreato-Biliary and Transplant Surgery Singapore General Hospital Division of Hepatobiliary and Pancreatic Surgery Department of Surgery University Surgical Cluster National University Health System Hepato-Pancreato-Biliary Surgery Unit Department of Surgery National Cancer Institute Division of Pathology National Cancer Institute Department of Surgery Faculty of Medicine University of Malaya Department of Surgery and Center for Liver Disease Management and Transplantation The Medical City Department of Laboratories The Medical City Department of Pathology Singapore General Hospital Institute for Infocomm Research ASTAR Department of Pathology National University Health System Translational Immunology Institute (TII) Sing Health Duke-NUS Academic Medical Centre Division of Gastroenterology and Hepatology University Medicine Cluster National University Hospital Department of Biochemistry Yong Loo Lin School of Medicine National University of Singapore Cancer Science Institute of Singapore National University of Singapore Division of Medical Oncology National Cancer Center Singapore Cardiovascular Research Institute National University of Singapore National University Healthcare System Singhealth-Duke-NUS Academic Surgery Program Duke-NUS Graduate Medical School Institute of Molecular and Cell Biology Agency for Science Technology and Research

Intra-tumor heterogeneity(ITH) is a key challenge in cancer treatment, but previous studies have focused mainly on the genomic alterations without exploring phenotypic(transcriptomic and immune)heterogeneity. Using one of the largest prospective surgical cohorts for hepatocellular carcinoma(HCC)with multi-region sampling, we sequenced whole genomes and paired transcriptomes from 67 HCC patients(331 samples). We found that while genomic ITH was rather constant across stages, phenotypic ITH had a very different trajectory and quickly diversified in stage Ⅱ patients. Most strikingly, 30% of patients were found to contain more than one transcriptomic subtype within a single tumor. Such phenotypic ITH was found to be much more informative in predicting patient survival than genomic ITH and explains the poor efficacy of single-target systemic therapies in HCC. Taken together, we not only revealed an unprecedentedly dynamic landscape of phenotypic heterogeneity in HCC, but also highlighted the importance of studying phenotypic evolution across cancer types.

关键词： hepatocellular carcinoma intra-tumor heterogeneity phenotypic evolution tumor evolution

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Methylglyoxal impairs human dermal fibroblast survival and migration by altering RAGE-hTERT mRNA expression in vitro

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Toxicology Reports 2024年 13卷 101835页

作者： Prakoso, Nurul Muhammad Sundari, Ayu Mulia Fadhilah Abinawanto Pustimbara, Anantya Dwiranti, Astari Bowolaksono, Anom Master Program in Biology Department of Biology Faculty of Mathematics and Natural Science University of Indonesia West Java Depok 16424 Indonesia Cellular and Molecular Mechanisms in Biological System (CEMBIOS) Research Group Department of Biology Faculty of Mathematics and Natural Science University of Indonesia West Java Depok 16424 Indonesia Tokyo Institute of Technology School of Life Science and Technology 4259 Midori-ku Yokohama 2268501 Japan Center for Photodynamic Medicine Kochi Medical School Kohasu Oko-cho Kochi Nankoku-shi 783-8505 Japan

Fibroblasts are native residents in dermal layer of human skin which are important for dermal regeneration and essential during cutaneous wound healing by releasing inflammatory markers and actively migrate to close an open wound. Premature skin ageing due to methylglyoxal (MGO) has recently caught the attention considering its potential to accelerate the emergence of skin ageing signs, however previous studies were only focused in primary neonatal dermal fibroblast and NIH3t3 fibroblast cell line. Therefore, thorough investigation is required to study the impact of MGO on primary human dermal fibroblast isolated from adult subject (HDFa). In our experiments, short exposure of MGO was observed to induced significant reductions in cell viability at concentrations of 7.5, 10, 12.5, 15, and 17.5 mM (p < 0.005) after 3 hours of treatment. The cellular death of HDFa at 10, 12.5 and 15 mM of MGO were also marked by increased in intracellular ROS level, indicating the involvement of oxidative stress-induced death in these cells. We also observed enlarge scratch areas of cells exposed with 7.5 and 10 mM MGO compared to control after 26 hours, thereby suggesting a decline in cell migration and viability in this group. We propose the increased ROS as the consequence of AGE-RAGE activation which was marked by significant elevation of RAGE mRNA on cells exposed to 10 mM MGO. Our data also suggest the occurrence of DNA damage events via ROS-induced oxidation or mediated by decline in hTERT mRNA expression. © 2024 The Authors

关键词： Dermal toxicity Human dermal fibroblasts Methylglyoxal Reactive oxygen species

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A deep learning system for predicting time to progression of diabetic retinopathy

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NATURE MEDICINE 2024年第2期30卷 358-359页

作者： [Anonymous] Shanghai Belt and Road International Joint Laboratory for Intelligent Prevention and Treatment of Metabolic Disorders Department of Computer Science and Engineering School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Department of Endocrinology and Metabolism Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine Shanghai Diabetes Institute Shanghai Clinical Center for Diabetes Shanghai China MOE Key Laboratory of AI School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China Department of Ophthalmology Huadong Sanatorium Wuxi China Department of Ophthalmology Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine Shanghai China Department of Ophthalmology and Visual Sciences The Chinese University of Hong Kong Hong Kong China Singapore Eye Research Institute Singapore National Eye Centre Singapore Singapore Department of Computer Science and Engineering The Hong Kong University of Science and Technology Hong Kong China Department of Chemical and Biological Engineering The Hong Kong University of Science and Technology Hong Kong China State Key Laboratory of Ophthalmology Zhongshan Ophthalmic Center Sun Yat-sen University Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science Guangzhou China Department of Ophthalmology Peking Union Medical College Hospital Peking Union Medical College Chinese Academy of Medical Sciences Beijing China Medical Records and Statistics Office Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine Shanghai China Department of Geriatrics Tongji Hospital Tongji Medical College Huazhong University of Science and Technology Wuhan China National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Tech

We developed and validated a deep learning system (termed DeepDR Plus) in a diverse, multiethnic, multi-country dataset to predict personalized risk and time to progression of diabetic retinopathy. We show that DeepDR Plus can be integrated into the clinical workflow to promote individualized intervention strategies for the management of diabetic retinopathy.

关键词： Diabetes complications Machine learning Predictive markers

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Effects of sodium alginate-poly(acrylic acid) cross-linked hydrogel beads on soil conditioner in the absence and presence of phosphate and carbonate ions

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Case Studies in Chemical and Environmental Engineering 2024年 9卷

作者： Hidayat, Endar Sarbani, Nur Maisarah Mohamad Lahiri, Sudip Kumar Samitsu, Sadaki Yonemura, Seiichiro Mitoma, Yoshiharu Harada, Hiroyuki Graduate School of Comprehensive Scientific Research Program in Biological System Sciences Prefectural University of Hiroshima Shobara 727-0023 Japan Department of Life System Science Faculty of Bioresources Science Prefectural University of Hiroshima Shobara 727-0023 Japan Data-driven Polymer Design Group Research Center for Macromolecules and Biomaterials National Institute for Materials Science 1−2−1 Sengen Tsukuba 305-0047 Japan Department of Mechanical & Industrial Engineering University of Toronto Toronto M5S 3G8 ON Canada Faculty of Allied Health Sciences Chettinad Hospital and Research Institute Chettinad Academy of Research and Education Tamil Nadu Kelambakkam 603103 India

Hydrogel beads, composed of polymers, possess the ability to absorb substantial quantities of water simultaneously and gradually release it in dry conditions. In this work, hydrogel beads were synthesized using sodium alginate (S-Alg) and poly (acrylic acid) (P-Acc), either in the absence or presence of phosphate (PO₄ ³⁻) (S-Alg/P-Acc@PO₄ ³⁻) and carbonate (CO₃ ²⁻) anionic ions (S-Alg/P-Acc@CO₃ ²⁻). Subsequently, these beads were crosslinked with Ca²⁺ ions. The scanning electron microscopy (SEM) images demonstrated that the presence of anionic ions has an impact on the structure of the hydrogel beads and enhances porosity expansion while concurrently reducing the concentration of carboxyl (COOH) groups. The hydrogel beads exhibited a great swelling behavior, with S-Alg/P-Acc@CO₃ ²⁻ capable of absorbing up to 73.5 % of water in acidic conditions, but decreased under neutral and basic conditions. Soil water loss (SWL) experiments confirmed the ability of hydrogel beads to retain water in the soil. Additionally, observations of soil characteristics after a 14-day treatment revealed no significant difference in pH and C/N ratio (P-value <0.05). However, soil's available Fe and N–NO₃ ^- significantly reduced (P-value <0.05) while substantially promoting soil N–NH₄ ⁺, available phosphorus (P), cation exchange capacity (CEC), soil organic carbon (SOC), and exchangeable cation (Ca²⁺, K⁺ and Mg²⁺). The presence of hydroxyl (-OH) and –COOH groups was found to be crucial for enhancing soil properties. © 2024 The Authors

关键词： Anionic ions Hydrogel beads Poly (acrylic acid) Sodium alginate Soil characteristics Soil water retention Swelling

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