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American Society for photogrammetry and Remote Sensing, ASPRS 2020 Annual Conference

作者： Hashemi-Beni, Leila Gebrehiwot, Asmamaw Geomatics Program Department of Built Environment North Carolina A&T State University United States Applied Science and Technology Ph.D. Program Department of Built Environment North Carolina A&T State University United States

This research examines the ability of deep learning methods for remote sensing image classification for agriculture applications. U-net and convolutional neural networks are fine-tuned, utilized and tested for crop/weed classification. The dataset for this study includes 60 top-down images of an organic carrots field, which was collected by an autonomous vehicle and labeled by experts. FCN-8s model achieved 75.1% accuracy on detecting weeds compared to 66.72% of U-net using 60 training images. However, the U-net model performed better on detecting crops which is 60.48% compared to 47.86% of FCN-8s. © 2020 International Society for photogrammetry and Remote Sensing. All rights reserved.

关键词： Crops

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Modulation of gut microbiota by crude gac aril polysaccharides ameliorates diet-induced obesity and metabolic disorders

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International Journal of Biological Macromolecules 2024年第PT 2期273卷 133164页

作者： Lu, Tai-Jung Chiou, Wei-Chung Huang, Hsiu-Chen Pan, Heng-Chih Sun, Chiao-Yin Way, Tzong-der Huang, Cheng Department of Ph.D. Program for Biotechnology Industry China Medical University Taichung City406040 Taiwan Department of Biotechnology and Laboratory Science in Medicine National Yang Ming Chiao Tung University Taipei City112304 Taiwan Center for Teacher Education National Tsing Hua University Hsinchu City300044 Taiwan Department of Applied Science Nanda Campus National Tsing Hua University Hsinchu City300044 Taiwan Department of Nephrology Chang Gung Memorial Hospital Keelung City204201 Taiwan

Obesity is a global health challenge that causes metabolic dysregulation and increases the risk of various chronic diseases. The gut microbiome is crucial in modulating host energy metabolism, immunity, and inflammation and is influenced by dietary factors. Gac fruit (Momordica cochinchinensis), widely consumed in Southeast Asia, has been proven to have various biological activities. However, the composition and effect of crude gac aril polysaccharides (GAP) on obesity and gut microbiota disturbed by high-fat diet (HFd) remain to be elucidated. Compositional analysis showed that GAP contains high oligosaccharides, with an average of 7–8 saccharide units. To mimic clinical obesity, mice were first made obese by feeding HFd for eight weeks. GAP intervention was performed from week 9 to week 20 in HFd-fed mice. Our results showed that GAP inhibited body weight gain, eWAT adipocyte hypertrophy, adipokine derangement, and hyperlipidemia in HFd-induced obese mice. GAP improved insulin sensitivity, impaired glucose tolerance, and hepatic steatosis. GAP modulated the gut microbiota composition and reversed the HFd-induced dysbiosis of at least 20 genera. Taken together, GAP improves metabolic health and modulates the gut microbiome to relieve obesity risk factors, demonstrating the potential of dietary GAP for treating obesity-associated disorders. © 2024 The Authors

关键词： Oligosaccharides

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Short-Chain dense Brush Pegylation on Rigid Nanocarriers Overcomes Anti-Peg Antibody Recognition for Immune-Stealth drug delivery

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SSRN 2025年

作者： Chen, Ting-Yu Chang, Chi-Yuan Wen, Ting-Chun Xu, Li Lin, Yu-Han Peng, Cheng-Liang Yeh, Yi-Qi Chen, Chueh-Hsuan Chuang, Kuo-Hsiang Wu, Si-Han Graduate Institute of Pharmacognosy Taipei Medical University Taipei11031 Taiwan Graduate Institute of Nanomedicine and Medical Engineering Taipei Medical University Taipei11031 Taiwan Department of Isotope Application National Atomic Research Institute Taoyuan Taiwan National Synchrotron Radiation Research Center Hsinchu Science Park Hsinchu30076 Taiwan Research Center for Applied Science Academia Sinica Taiwan PhD Program in Clinical Drug Development of Chinese Herbal Medicine Taipei Medical University Taipei Taiwan International Ph.D. Program in Biomedical Engineering College of Biomedical Engineering Taipei Medical University Taipei11031 Taiwan

The immunogenicity of polyethylene glycol (PEG) remains a critical challenge in nanomedicine, as pre-existing anti-PEG antibodies can compromise therapeutic efficacy through accelerated blood clearance (ABC) and life-threatening hypersensitivity. Here, we address this challenge by engineering the PEG architecture, creating short-chain dense brush PEGylation (PEG500) on rigid mesoporous silica nanoparticles (MSNs). Unlike conventional PEG2000-liposomes, MSN-PEG500 evades antibodies via three synergistic mechanisms: (1) short-chain PEG500 reduces epitope accessibility, (2) high grafting density (4.43 chains/nm2, according to TGA) forms an dense steric shield, and (3) the rigid silica surface prevents PEG burial. ELISA studies demonstrated that, at equivalent nanoparticle concentrations, MSN-PEG500 exhibits a 26-fold reduction in anti-PEG IgG (6.3) binding and a 1000-fold reduction in anti-PEG IgM (AGP3) binding compared to Lipodox (PEG2000), both of which target the PEG backbone. Furthermore, radiolabeled MSN-PEG500 achieved prolonged circulation and 25% tumor accumulation (Id/g) at 24 hours. In strongly immunized mice, doxorubicin-loaded MSN-PEG500 preserved therapeutic efficacy and 100% survival, whereas Lipodox induced fatal hypersensitivity. Mechanistic investigations revealed that complement activation drives PEG2000 immunotoxicity, and pretreatment with the C3 inhibitor compstatin effectively mitigated temperature drops from 10°C to 2°C in immunized hosts. By demonstrating that nanoscale control of polymer conformation dictates immunological fate, this work provides a clinically translatable blueprint for developing immune-evasive nanomedicines. © 2025, The Authors. All rights reserved.

关键词： Silica nanoparticles

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FluoroFusion: NHC-Catalyzed Nucleophilic Aromatic Substitution Reaction Unveils Functional Perfluorinated diarylmethanones

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Organic letters 2024年第11期26卷 2338-2342页

作者： Cheng-Lin Chan Shao-Chi Lee Pei-Shan Lin Radyn Vanessa phaz P Tapales Jia-Syuan Li Chun-An Lai Jyh-Tsung Lee Chien-Hung Li Hsuan-Hung Liao Department of Chemistry National Sun Yat-sen University Kaohsiung 804201 Taiwan (R.O.C.). Department of International Ph.D. Program for Science National Sun Yat-sen University Kaohsiung 804201 Taiwan (R.O.C.). Department of Chemistry National Chung Hsing University Taichung 402202 Taiwan (R.O.C.). KAUST Catalysis Center (KCC) King Abdullah University of Science and Technology (KAUST) Thuwal 23955 Saudi Arabia. Department of Applied and Medicinal Chemistry Kaohsiung Medical University Kaohsiung 807378 Taiwan (R.O.C.).

A mild, facile, and metal-free approach via the -heterocyclic carbene-catalyzed SAr reaction between aryl aldehydes with perfluoroarenes to obtain the coveted functional perfluorinated diarylmethanones is disclosed. This method accommodates a diverse substrate range and exhibits notable tolerance toward various functional groups. Our success in modifying biologically relevant molecules, crafting a fully fluorinated bioisosteric analogue of drug candidate , and highlighting the potential of these ketones as valuable electrolyte additives for lithium-ion batteries (LIBs) underscores the versatility of our methodology.

关键词： Additives Aldehydes Aromatic compounds Chemical reactions Electrolytes

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Psychological Stress Classification Using Extreme Gradient Boosting Algorithm

Psychological Stress Classification Using Extreme Gradient B...

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International Conference on Information and Communication Technology Convergence (ICTC)

作者： Maria Mahardini Sakanti Viacheslav Siniaev Aurelia Amaris Win-Jet Luo Suhartono C. Bambang dwi Kuncoro Graduate Institute of Precision Manufacturing National Chin-Yi University of Technology Taichung Taichung Taiwan Institute of Applied Computer Science ITMO University St. Petersburg Russian Federation Department of Informatics Engineering Faculty of Computer Science Universitas Brawijaya Malang Indonesia Ph.D. Program Prospective Technology of Electrical Engineering and Computer Science National Chin-Yi University of Technology Taichung Taichung Taiwan Department of Refrigeration Air Conditioning and Energy Engineering National Chin-Yi University of Technology Taichung Taiwan

ISBN: (数字)9798350364637

ISBN: (纸本)9798350364644

Stress, as a reaction to threatening situations, can raise heart rate and result in serious conditions that might cause significant damage or even be life-threatening. Traditional methods for evaluating stress, which rely on subjective self-reporting and clinical assessments, often suffer from biases and inconsistencies. Artificial intelligence models have been explored to predict stress levels more accurately. This paper investigates the application of Extreme Gradient Boosting in classifying psychological stress using the WESAd dataset, which includes parameters such as acceleration, electrocardiogram, electromyography, electrodermal activity, temperature, and respiration. The dataset was balanced and sampled to create a manageable subset for experimental. Extreme Gradient Boosting was chosen for its efficiency and scalability in handling complex datasets. The model was trained and validated, achieving a 95% accuracy in predicting stress levels. This study highlights the potential of integrating Extreme Gradient Boosting models into wearable devices for real-time stress monitoring. Future work involves optimizing the model to utilize fewer sensors without decreasing accuracy, ensuring it can be integrated into portable/wearable systems using tiny microcontrollers.

关键词： Accuracy Microcontrollers Psychology Human factors Predictive models Boosting Prediction algorithms Real-time systems Sensors Wearable devices

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Marine macro-litter sources and ecological impact: a review

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Environmental Chemistry Letters 2024年第3期22卷 1257-1273页

作者： Le, Van-Giang Nguyen, Hoang-Lam Nguyen, Minh-Ky Lin, Chitsan Hung, Nguyen T. Quang Khedulkar, Akhil P. Hue, Nguyen K. Trang, phung T. Thu Mungray, Arvind Kumar Nguyen, d. duc Central Institute for Natural Resources and Environmental Studies Vietnam National University Hanoi111000 Viet Nam Department of Civil Engineering McGill University MontrealQC Canada Faculty of Environment and Natural Resources Nong Lam University Hamlet 6 Linh Trung Ward Thu Duc City Ho Chi Minh City700000 Viet Nam Ph.D. Program in Maritime Science and Technology National Kaohsiung University of Science and Technology Kaohsiung81157 Taiwan Department of Marine Environmental Engineering National Kaohsiung University of Science and Technology Kaohsiung81157 Taiwan Department of Biomedical Engineering and Environmental Science National Tsing Hua University Hsinchu30013 Taiwan Environmental Research Center Institute of Hydrology and Meteorology Science and Climate Change Hanoi111000 Viet Nam Department of Chemical Engineering Sardar Vallabhbhai National Institute of Technology Gujarat Surat395007 India Department of Civil and Energy System Engineering Kyonggi University Suwon16227 Korea Republic of Institute of Applied and Sustainable Technology Nguyen Tat Thanh University Ho Chi Minh City700000 Viet Nam

Marine pollution by various debris is rising in the context of increasing urbanization, industrialization and worldwide trade. Here, we review marine macro-litter with focus on sources, abundance, distribution, and impact on aquatic wildlife, human health, and the economy. We observe that about 75–80% of marine litter originates from land-based sources, including poorly managed landfills and improper disposal. Macro-litter ingestion by marine life is of growing concern, in particular concerning the presence of plastics and associated pollutants, e.g., bisphenol A and phthalates, in fishes. These pollutants are accumulated and transferred to human via seafood. Marine plastic pollution induces a substantial rise of economic costs due to the decline of ecosystem services. Mitigation of marine plastic pollution should be done by following the ten Rs principles of refuse, rethink, reduce, re-use, repair, refurbish, remanufacture, repurpose, recycle, and recover. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

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Modelling and forecasting daily average temperature in Bangkok, Thailand

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AIP Conference Proceedings 2024年第1期3123卷

作者： Kanyarat Thitiwatthanakan Manad Khamkong Ravi Lonkani Thanasak Mouktonglang Ph.D. Program in Applied Statistics Department of Statistics Faculty of Science Chiang Mai University 50200 Chiang Mai Thailand Department of Statistics Faculty of Science Chiang Mai University 50200 Chiang Mai Thailand Department of Finance Faculty of Business Administration Chiang Mai University 50200 Chiang Mai Thailand Department of Mathematics Faculty of Science Chiang Mai University 50200 Chiang Mai Thailand

In order to predict the occurrence of extreme climate events, forecasting and describing dynamic changes in temperature are essential. Understanding these events will allow action to be taken in order to minimize their associated effects. In this paper, we present a feasible model for estimating daily average temperatures in Bangkok, Thailand. The daily maximum and minimum temperature observations between 2006 and 2021 were collected from the Thai Meteorological department for the study. The Fourier series was then applied to the average daily temperature as the mean function, and then the auto-regressive integrated moving average, ARIMA (4,1,1), was used to predict the residuals that occurred from the mean function to describe the evolution of the temperature. Analysis of the root mean square error (RMSE) value from the models, which is 0.9536, revealed that the methods fitted the data quite well.

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Fabrication of sandwich-structured capacitor containing core@shell polystyrene@graphene oxide microspheres for switchable removal of dyes from water by dielectrophoresis force

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Separation and Purification Technology 2024年 331卷

作者： Chen, Wei-Liang Cheng, Chih-Chia Lu, Chien-Hsing Chen, Jem-Kun Department of Materials Science and Engineering National Taiwan University of Science and Technology 43 Sec. 4 Keelung Road Taipei 106 Taiwan Division of Gastroenterology and Hepatology Department of Internal Medicine Chung Shan Medical University Hospital Taichung City402 Taiwan Graduate Institute of Applied Science and Technology National Taiwan University of Science and Technology Taipei10607 Taiwan Department of Obstetrics and Gynecology Taichung Veterans General Hospital Taichung40705 Taiwan Institute of Biomedical Sciences Ph.D. Program in Translational Medicine and Rong-Hsing Research Center for Translational Medicine National Chung-Hsing University Taichung940227 Taiwan

Absorption rates for traditional adsorbents were predominately determined by the concentration gradient from bulk to absorbents and surface area. A novel sandwich-structured capacitor (SSC) containing adsorbents is designed to reduce the time consuming of absorption of pollutants by dielectrophoresis force (FdEP). Graphene oxide (GO) are coated on polystyrene microspheres (PSs) as the core/shell PS@GO adsorbents that were encapsulated within the SSC to treat the solution of dye-emulsified micells (dEM). The FdEP results the assembling of PS@GOs and dEMs under polarization and enhance the adsorption rate ca. 1 ∼ 2 times with polarization at 3 V and 200 kHz. Additionally, most adsorbents are recycled with secondary pollution. Only two-fifth pure water volume of the wastewater through the SSC could achieve the recycling of the adsorbents at 900 kHz. The high complex permittivity of GO coating at high frequency allows ultrafast alternative spinning of the induced dipoles in the PS@GOs facilitates desorption and hinders the re-adsorption of the dEM during the recycling of PS@GOs. The PS@GOs was reused ca. 10 times at 20 mL min−1 of flow rate through the SSC without damages between 200 and 900 kHz. The designed SSC containing PS@GOs accomplishes either reusing of adsorbents or concentrating of dyes with low secondary pollution in practice through frequency manipulation. © 2023 Elsevier B.V.

关键词： Graphene

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The Smart Analysis of Performing Scalable Inference for Big data Analytics

The Smart Analysis of Performing Scalable Inference for Big ...

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International Conference on Power Energy, Environment and Intelligent Control (PEEIC)

作者： Vishakha d Bhandarkar Aruna Sri Rongali Mohamed dawood Shamout Prof. Sachin Pund Gigih Forda Nama Shrishailappa Patil Applied Mathematics and Humanities Yeshwantrao Chavan College of Engineering India Graduate Doctoral Information Technology/Graduate (Information Technology Emphasis/Information Technology Ph.D.) University of The Cumberlands US Department of Management College of Business Administration University of Sharjah Sharjah United Arab Emirates Department of Industrial Engineering Shri Ramdeobaba College of Engineering and Management Nagpur Maharashtra India Department of Informatics Doctoral Program of Environtmental Science University of Lampung Bandar Lampung Computer engineering Vishwakarma Institute of Technology Pune

This paper examines the reproducibility of massive information analytics under particular factors. The paper proposes the “performing Scalable Inference” technique to cope with scalability troubles and to exploit current big statistics platforms for efficient computing and statistics garage of the statistics. In particular, the paper describes how to perform leak-free, parallelizable visible analytics over massive datasets using present extensive records analytics frameworks such as Apache Flink. This method presents an automated manner to execute analytics that preserves reproducibility and the ability to make adjustments without re-running the entire technique. The paper also demonstrates how these analytics may help several real-world use instances, explore affected person cohorts for studies, and develop stratified patient cohorts for hospital therapy. In the end, the paper observes how the proposed method may be exercised within the real world. Actively scalable inference for massive information analytics is pivotal in optimizing decision-making and allocation of assets. Typically, such inferences are made based on information accumulated from numerous sources, databases, unstructured data, and different digital sources. So one can ensure scalability, a complete cloud-primarily based platform has to be hired. This solution will permit the ***, deploying the essential records series and evaluation algorithms are prime here. It could permit the platform to recognize the styles inside the statistics and discover any ability correlations or traits. Additionally, predictive analytics and system mastering strategies may be incorporated to provide insights into the results of the information. In the long run, by leveraging those techniques, the platform can draw efficient inferences and appropriately compare situations in an agile and green way..

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Biological Evaluation of Sulfonate and Sulfate Analogues of Lithocholic Acid: A Bioisosterism-Guided Approach Towards the discovery of Potential Sialyltransferase Inhibitors for Antimetastatic Study

SSRN

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SSRN 2023年

作者： Perez, Ser John Lynon P. Chen, Chia-Ling Chang, Tzu-Ting Li, Wen-Shan Institute of Chemistry Academia Sinica Taipei115 Taiwan Department of Applied Chemistry National Yang Ming Chiao Tung University Hsinchu300 Taiwan Sustainable Chemical Science and Technology Taiwan International Graduate Program Academia Sinica Taipei115 Taiwan Biomedical Translation Research Center Academia Sinica Taipei115 Taiwan Department of Medicinal and Applied Chemistry College of Life Science Kaohsiung Medical University Kaohsiung807 Taiwan Ph.D. Program in Drug Discovery and Development Industry College of Pharmacy Taipei Medical University Taiwan Doctoral Degree Program in Marine Biotechnology National Sun Yat-Sen University Kaohsiung804 Taiwan Department of Chemistry College of Science Tamkang University New Taipei City251 Taiwan

The naturally occurring bile acid lithocholic acid (LCA) has been a crucial core structure for many non-sugar-containing sialyltranferase (ST) inhibitors documented in literature. With the aim of elucidating the impact of the terminal carboxyl acid substituent of LCA on its ST inhibition, in this present study, we report the (bio)isosteric replacement-based design and synthesis of sulfonate and sulfate analogues of LCA. Among these compounds, the sulfate analogue SPP-002 was found to selectively inhibit N-glycan sialylation by at least an order of magnitude, indicating a substantial improvement in both potency and selectivity when compared to the unmodified parent bile acid. Molecular docking analysis supported the stronger binding of the synthetic analogue in the enzyme active site. Treatment with SPP-002 also hampered the migration, adhesion, and invasion of MdA-MB-231 cells in vitro by suppressing the expression of signaling proteins involved in the cancer metastasis-associated FAK/paxillin pathway. In totality, these findings offer not only a novel structural scaffold but also valuable insights for the future development of more potent and selective ST inhibitors with potential therapeutic effects against tumor cancer metastasis. © 2023, The Authors. All rights reserved.

关键词： Sulfur compounds

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