检索结果-内蒙古大学图书馆

SSRN 2023年

作者： Ahmed, Mahmoud M.M. Liu, Yu-Ting Venkatesan, Srinivasadesikan Wu, Min Chien Nail, Howida M. Tzou, Der-Lii M. Lin, Ming-Chang Chen, Kai-Yue Tzou, Yu-Min Department of Soil and Environmental Sciences National Chung Hsing University 145 Xingda Rd. Taichung40227 Taiwan Innovation and Development Center of Sustainable Agriculture National Chung Hsing University 145 Xingda Rd. Taichung40227 Taiwan Department of Chemistry School of Science and Humanities Vignan's Foundation for Science Technology and Research Guntur Andhra Pradesh Vadlamudi522 213 India Graduate institute of Biomedical Engineering National Chung Hsing University 145 Xingda Rd. Taichung40227 Taiwan Institute of Chemistry Academia Sinica Nangang Taipei11529 Taiwan Department of Applied Chemistry National Yang Ming Chiao Tung University Hsinchu30010 Taiwan Professional Bachelor Program of Farm Management National Chiayi University Chiayi600355 Taiwan

The utilization of graphitic carbon nitride (C3N4) to enhance the oxidative polymerization of hydroquinone (HQ) within birnessite (δ-MnO2) systems was investigated. C3N4, a Lewis base enriched with nitrogen, acted as a bridge through π−π interactions between metal oxides and polyphenols. These interactions increased the affinity of the reactants, resulting in an enhanced reaction rate of six-fold, accelerated browning, and improved complex stability of C3N4...HQ...MnO2 complex. As a result, a humic-like substance (HS) was rapidly formed with improved surface morphology and larger particle sizes. Electron transfer of HQ...MnO2 promoted by C3N4 played a crucial role in HQ oxidation, expanding atomic distance and composite morphology. Theoretical calculations supported the experimental results, indicating strong affinity and higher binding energies in the C3N4...HQ...MnO2 complex. The complex had a more stable structure with a narrower HOMO-LUMO gap, facilitating HS formation. 13C and 1H NMR spectra confirmed the experimental-theoretical agreement. © 2023, The Authors. All rights reserved.

关键词： Binding energy

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Corrigendum to “Socio-economic status and occupational mobility of China’s Fishery Population: A quantitative analysis based on social-survey data” [Fish. Res. 285(2025) 107362]

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Fisheries Research 2025年 285卷

作者： Yi Huang Ulf Dieckmann Mikko Heino Coastal and Ocean Management Institute Xiamen University Xiamen 361102 China Evolution and Ecology Program & Advancing Systems Analysis Program International Institute for Applied Systems Analysis (IIASA) Schlossplatz 1 Laxenburg A2361 Austria Complexity Science and Evolution Unit Okinawa Institute of Science and Technology Graduate University (OIST) 1919-1 Tancha Onna Kunigami Okinawa 904-0495 Japan Department of Evolutionary Studies of Biosystems The Graduate University for Advanced Studies (Sokendai) Hayama Kanagawa 240-0193 Japan Department of Biological Sciences University of Bergen Box 7803 Bergen N-5020 Norway Institute of Marine Research Box 1870 Nordnes Bergen N-5817 Norway

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Sub-Meter Tree Height Mapping of California using Aerial Images and LiDAR-Informed U-Net Model

arXiv

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arXiv 2023年

作者： Wagner, Fabien H. Roberts, Sophia Ritz, Alison L. Carter, Griffin Dalagnol, Ricardo Favrichon, Samuel Hirye, Mayumi C.M. Brandt, Martin Ciais, Philipe Saatchi, Sassan Institute of Environment and Sustainability University of California Los AngelesCA United States Jet Propulsion Laboratory California Institute of Technology 4800 Oak Grove PasadenaCA91109 United States CTrees PasadenaCA91105 United States Virginia Polytechnic Institute State University Interdisciplinary Graduate Education Program in Remote Sensing Blacksburg United States Quapá Lab Faculty of Architecture and Urbanism University of São Paulo SP São Paulo05508080 Brazil Department of Geosciences and Natural Resource Management University of Copenhagen Copenhagen1350 Denmark Laboratoire des Sciences du Climat et de l’Environnement CEA-CNRS-UVSQ CE Orme des Merisiers Gif sur Yvette91190 France

Tree canopy height is one of the most important indicators of forest biomass, productivity, and species diversity, but it is challenging to measure accurately from the ground and from space. Here, we used a U-Net model adapted for regression to map the canopy height of all trees in the state of California with very high-resolution aerial imagery (60 cm) from the USDA-NAIP program. The U-Net model was trained using canopy height models computed from aerial LiDAR data as a reference, along with corresponding RGB-NIR NAIP images collected in 2020. We evaluated the performance of the deep-learning model using 42 independent 1 km2 sites across various forest types and landscape variations in California. Our predictions of tree heights exhibited a mean error of 2.9 m and showed relatively low systematic bias across the entire range of tree heights present in California. In 2020, trees taller than 5 m covered ∼ 19.3% of California. Our model successfully estimated canopy heights up to 50 m without saturation, outperforming existing canopy height products from global models. The approach we used allowed for the reconstruction of the three-dimensional structure of individual trees as observed from nadir-looking optical airborne imagery, suggesting a relatively robust estimation and mapping capability, even in the presence of image distortion. These findings demonstrate the potential of large-scale mapping and monitoring of tree height, as well as potential biomass estimation, using NAIP *** Codes 92-08 © 2023, CC BY.

关键词： Antennas

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Stochastic multi-objective optimization of hybrid distributed power generation with battery storage systems

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Energy Sources, Part B: Economics, Planning and Policy 2025年第1期20卷

作者： Barbosa, Aglaucibelly Maciel Rotella Junior, Paulo Peruchi, Rogério Santana Rocha, Luiz Célio Souza Pires, Arthur Leandro Guerra Janda, Karel Post-Graduate Program in Production Engineering and Systems Federal University of Paraiba João Pessoa Brazil Department of Production Engineering Federal University of Paraiba João Pessoa Brazil Faculty of Finance and Accounting Prague University of Economics and Business Prague Czech Republic Institute of Economic Studies Faculty of Social Sciences Charles University Prague Czech Republic Management Department - Federal Institute of Education Science and Technology - North of Minas Gerais Almenara Brazil Institute of Production Engineering and Management Federal University of Itajubá Brazil

Hybrid energy projects are gaining global interest due to their potential to promote sustainable development. This study addresses a gap in the literature by proposing a stochastic model that assesses the economic feasibility of a hybrid energy system combining wind, photovoltaic generation, and battery storage. Unlike traditional deterministic approaches, the model incorporates uncertainties in key financial and operational variables, improving decision-making in real-world conditions. The optimization framework integrates Design of Experiments (DoE), Response Surface Methodology (RSM), and the Desirability function to balance economic return and financial risk. By maximizing the mean and minimizing the variance of the Net Present Value (NPV), the model identifies an optimal system configuration with 92% wind energy, a demand level of 230 kWh/month, and lithium-ion battery storage. This approach reduces computational complexity and enhances hybrid system viability in regions with strong wind resources, providing a valuable tool for investors and policymakers in sustainable energy planning. © 2025 Taylor & Francis Group, LLC.

关键词： Multiobjective optimization

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Impact of Increasing Input and Output Prices on Chili Production and Farmer Income in Banten Province

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IOP Conference Series: Earth and Environmental Science 2022年第1期950卷 012060页

作者： V Siagian H Siregar A Fariyanti K Nainggolan I Hidayah PhD Study Program Natural Resources and Environmental Management Graduate School of IPB University Researcher of Assessment Institute for Agricultural Technology (AIAT) of Banten Indonesia Ministry of Agriculture Ciptayasa Avenue-Serang-Banten 42182 Indonesia IPB University STMIK Nusa Mandiri

In 2019, chili production in Banten province amounted to 12,122.9 tons with a harvest area of 1,395 ha or productivity of 8.7 tons/ha. The objectives of this study are: 1) Analyzing the factors affecting the cultivated land area and chili production in Banten Province, 2) Analyzing the impact of increasing input and output prices on chili production in Banten Province. This study method used a survey method with 80 respondents. The analysis method uses the Simultaneous Equation Model. The results of the study were 1) The factors that significantly influence the cultivated land area of Rainy Season (RS) 2015/2016 were the number of: manure, solid organic fertilizers, other fertilizers, solid leaf fertilizers, and the total land area. The factors that significantly influence chili production in Banten Province are the number of: KCL fertilizer, liquid leaf fertilizer, and liquid growth stimulant. 2) From the policy simulation results, it is known that an increase in chili prices by 25%, Urea fertilizer by 25%, and NPK by 25% simultaneously will reduce production by 2.8% and chili farming income by 16.2%, but increase the area land 5.8% and farmer household income 0.06%. The government needs to stabilize the chili price and maintain the subsidized fertilizer price.

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The role of input imaging combination and ADC threshold on segmentation of acute ischemic stroke lesion using U-Net

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European Radiology 2023年第9期33卷 6157-6167页

作者： Li, Ya-Hui Lin, Shao-Chieh Chung, Hsiao-Wen Chang, Chia-Ching Peng, Hsu-Hsia Huang, Teng-Yi Shen, Wu-Chung Tsai, Chon-Haw Lo, Yu-Chien Lee, Tung-Yang Juan, Cheng-Hsuan Juan, Cheng-En Chang, Hing-Chiu Liu, Yi-Jui Juan, Chun-Jung Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taipei Taiwan Department of Medical Imaging China Medical University Hsinchu Hospital No. 199 Sec. 1 Xinglong Rd. Zhubei City Hsinchu County 302 Hsinchu Taiwan Ph.D. Program in Electrical and Communication Engineering Feng Chia University Taichung Taiwan Department of Electrical Engineering National Taiwan University Taipei Taiwan Department of Management Science National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Biomedical Engineering and Environmental Sciences National Tsing Hua University Hsinchu Taiwan Department of Electrical Engineering National Taiwan University of Science and Technology Taipei Taiwan Department of Radiology School of Medicine College of Medicine China Medical University Taichung Taiwan Department of Medical Imaging Medical University Hospital Taichung Taiwan Department of Neurology China Medical University Hospital Taichung Taiwan Cheng Ching Hospital Taichung Taiwan Master’s Program of Biomedical Informatics and Biomedical Engineering Feng Chia University Taichung Taiwan Department of Automatic Control Engineering Feng Chia University No. 100 Wenhwa Rd. Seatwen Taichung 40724 Taiwan Department of Biomedical Engineering The Chinese University of Hong Kong ERB1112 11/F William M.W. Mong Engineering Building N.T Shatin Hong Kong Multi-Scale Medical Robotics Center The Chinese University of Hong Kong N.T Shatin Hong Kong Department of Biomedical Engineering National Defense Medical Center Taipei Taiwan Department of Computer Science and Information Engineering National Taiwan University Taipei Taiwan

Background: To evaluate the effect of the weighting of input imaging combo and ADC threshold on the performance of the U-Net and to find an optimized input imaging combo and ADC threshold in segmenting acute ischemic stroke (AIS) lesion. Methods: This study retrospectively enrolled a total of 212 patients having AIS. Four combos, including ADC-ADC-ADC (AAA), DWI-ADC-ADC (DAA), DWI-DWI-ADC (DDA), and DWI-DWI-DWI (DDD), were used as input images, respectively. Three ADC thresholds including 0.6, 0.8 and 1.8 × 10^–3 mm²/s were applied. Dice similarity coefficient (DSC) was used to evaluate the segmentation performance of U-Nets. Nonparametric Kruskal–Wallis test with Tukey–Kramer post-hoc tests were used for comparison. A p <.05 was considered statistically significant. Results: The DSC significantly varied among different combos of images and different ADC thresholds. Hybrid U-Nets outperformed uniform U-Nets at ADC thresholds of 0.6 × 10^–3 mm²/s and 0.8 × 10^–3 mm²/s (p <.001). The U-Net with imaging combo of DDD had segmentation performance similar to hybrid U-Nets at an ADC threshold of 1.8 × 10^–3 mm²/s (p =.062 to 1). The U-Net using the imaging combo of DAA at the ADC threshold of 0.6 × 10^–3 mm²/s achieved the highest DSC in the segmentation of AIS lesion. Conclusions: The segmentation performance of U-Net for AIS varies among the input imaging combos and ADC thresholds. The U-Net is optimized by choosing the imaging combo of DAA at an ADC threshold of 0.6 × 10^–3 mm²/s in segmentating AIS lesion with highest DSC. Key Points: • Segmentation performance of U-Net for AIS differs among input imaging combos. • Segmentation performance of U-Net for AIS differs among ADC thresholds. • U-Net is optimized using DAA with ADC = 0.6 × 10^–3mm²/s. © 2023, The Author(s), under exclusive licence to European Society of Radiology.

关键词： Deep Learning Diffusion Magnetic Resonance Imaging Ischemic Stroke Neural Networks, Computer Retrospective Study

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Exploring ultra-high-intensity wakefields in carbon nanotube arrays: An effective plasma-density approach

arXiv

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arXiv 2022年

作者： Bonatto, A. Xia, G. Apsimon, O. Bontoiu, C. Kukstas, E. Rodin, V. Yadav, M. Welsch, C.P. Resta-López, J. Graduate Program in Information Technology and Healthcare Management The Beam Physics Group Federal University of Health Sciences of Porto Alegre Porto Alegre RS 90050-170 Brazil Department of Physics and Astronomy The University of Manchester ManchesterM13 9PL United Kingdom The Cockcroft Institute Sci-Tech Daresbury WarringtonWA4 4AD United Kingdom Department of Physics The University of Liverpool LiverpoolL69 3BX United Kingdom Icmuv Instituto de Ciencia de Los Materiales Universidad de Valencia Valencia46071 Spain

Charged particle acceleration using solid-state nanostructures has attracted attention in recent years as a method of achieving ultra-high-gradient acceleration in the TV/m domain. More concretely, metallic hollow nanostructures could be suitable for particle acceleration through the excitation of wakefields by a laser or a high-intensity charged particle beam in a high-density solid-state plasma. For instance, due to their special channelling properties as well as optoelectronic and thermo-mechanical properties, carbon nanotubes could be an excellent medium for this purpose. This article investigates the feasibility of generating ultra-high gradient acceleration using carbon nanotube arrays, modelled as solid-state plasmas in conventional particle-in-cell simulations performed in a two-dimensional axisymmetric (quasi-3D) geometry. The generation of beam-driven plasma wakefields depending on different parameters of the solid structure is discussed in detail. Furthermore, by adopting an effective plasma-density approach, existing analytical expressions, originally derived for homogeneous plasmas, can be used to describe wakefields driven in periodic non-uniform plasmas. Copyright © 2022, The Authors. All rights reserved.

关键词： Plasma density

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Exploring disparities of teleconsultation readiness: A comparative analysis of healthcare facilities in Indonesia

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DIGITAL HEALTH 2024年 10卷

作者： Daniel Chriswinanto Adityo Nugroho Katherina Adisaputro Mitra Andini Sigilipoe Ida Ayu Triastuti Suryani Hutomo Ardhinta Bellano Septarda Aryososepti Yuwono Caraka Randi Yusuf Dedik Sulistiawan Balqis Gusbela Jason C Hsu Emily Chia-Yu Su Faculty of Medicine Universitas Kristen Duta Wacana Yogyakarta IndonesiaGraduate Institute of Biomedical Informatics College of Medical Science and Technology Taipei Medical University Taipei Faculty of Medicine Universitas Kristen Duta Wacana Yogyakarta Indonesia Faculty of Public Health Universitas Ahmad Dahlan Yogyakarta IndonesiaSchool of Public Health Taipei Medical University Taipei International PhD Program in Biotech and Healthcare Management College of Management Taipei Medical University Taipei International PhD Program in Biotech and Healthcare Management College of Management Taipei Medical University TaipeiClinical Data Center Office of Data Science Taipei Medical University TaipeiClinical Big Data Research Center Taipei Medical University Hospital TaipeiResearch Center of Health Care Industry Data Science College of Management Taipei Medical University Taipei Graduate Institute of Biomedical Informatics College of Medical Science and Technology Taipei Medical University TaipeiClinical Big Data Research Center Taipei Medical University Hospital TaipeiInstitute of Biomedical Informatics College of Medicine National Yang Ming Chiao Tung University Taipei

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Emotion recognition in doctor-patient interactions from real-world clinical video database: Initial development of artificial empathy

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Computer Methods and programs in Biomedicine 2023年 233卷 107480-107480页

作者： Huang, Chih-Wei Wu, Bethany C.Y. Nguyen, Phung Anh Wang, Hsiao-Han Kao, Chih-Chung Lee, Pei-Chen Rahmanti, Annisa Ristya Hsu, Jason C. Yang, Hsuan-Chia Li, Yu-Chuan Jack Taipei Medical University Taipei Taiwan Taipei Medical University Ringgold standard institution - Center for Simulation in Medical Education Taipei 116 Taiwan National Taiwan University Children and Family Research Center Sponsored by CTBC Charity Foundation Taipei Taiwan Clinical Data Center Office of Data Science Taipei Medical University Taipei Taiwan Clinical Big Data Research Center Taipei Medical University Hospital Taipei Taiwan Graduate Institute of Biomedical Informatics College of Medical Science and Technology Taipei Medical University TMU Da'an Campus 15 F No. 172-1 Kee lung Road Section 2 Da-an District Taipei Taiwan Research Center of Big Data and Meta-analysis Wanfang Hospital Taipei Medical University Taipei Taiwan Department of Dermatology Wanfang Hospital Taipei Medical University Taiwan Department of Dermatology School of Medicine College of Medicine Taipei Medical University Taipei Taiwan Delta Research Center Taipei Taiwan Department of Health Policy and Management Faculty of Medicine Public Health and Nursing Universitas Gadjah Mada Yogyakarta Indonesia International PhD Program in Biotech and Healthcare Management College of Management Taipei Medical University Taipei Taiwan Research Center of Data Science on Healthcare Industry College of Management Taipei Medical University Taipei Taiwan

Background and objective: The promising use of artificial intelligence (AI) to emulate human empathy may help a physician engage with a more empathic doctor-patient relationship. This study demonstrates the application of artificial empathy based on facial emotion recognition to evaluate doctor-patient relationships in clinical practice. Methods: A prospective study used recorded video data of doctor-patient clinical encounters in dermatology outpatient clinics, Taipei Municipal Wanfang Hospital, and Taipei Medical University Hospital collected from March to December 2019. Two cameras recorded the facial expressions of four doctors and 348 adult patients during regular clinical practice. Facial emotion recognition was used to analyze the basic emotions of doctors and patients with a temporal resolution of 1 second. In addition, a physician-patient satisfaction questionnaire was administered after each clinical session, and two standard patients gave impartial feedback to avoid bias. Results: Data from 326 clinical session videos showed that (1) Doctors expressed more emotions than patients (t [326] > = 2.998, p © 2023

关键词： Emotion Recognition

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Predicting the Participation in Social Science under Expanding System by Using ARIMAX

Predicting the Participation in Social Science under Expandi...

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International Conference on Mathematics, Modeling and Simulation Technologies and Applications

作者： Dian-Fu Chang Chia-Chi Chen Graduate Institute of Educational Policy and Leadership Tamkang University Doctoral Program of Educational Leadership and Technology Management Tamkang University

ISBN: (纸本)9781713800361

This study aims to predict the participation pattern related to the social science programs within a high participated higher education *** the expanding higher education system in Taiwan as an example,we collected the series data with student numbers in social science programs and total student enrollment numbers by using the annual statistics report(1950 to 2017) from Ministry of *** the concurrent series did not fit the classical ARIMA(autoregressive integrated moving average) model,this study selected transfer function in terms of multivariate autoregressive integrated moving average(ARIMAX) models to deal with the target ***,we applied the cross correlation function to check the relationships between the ***,we select the ARIMAX with transfer function to verify the fittest predicting *** result reveals the selected ARIMAX(1,1,1) model works well for predicting the trend of social science participation in *** study provides an example to tackle two series variables in ARIMAX process in higher education *** finding suggests useful information for related policy makers to renovating the social science programs.

关键词： ARIMA ARIMAX Cross correlation function Higher education Social science Transfer function Social Sciences ARIMA higher education TRANSFER FUNCTIONS cross correlation function

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