检索结果-内蒙古大学图书馆

International Electron Devices Meeting (IEDM)

作者： Eunah Ko Kanghwan Kim Mihály Vöröslakos Sungjin Oh György Buzsáki Kensall D. Wise Euisk Yoon Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor MI USA Center for BioMicrosystems Brain Science Institute Korea Institute of Science and Technology Seoul Korea Neuroscience Institute Langone Medical Center New York University New York NY USA Department of Biomedical Engineering University of Michigan Ann Arbor MI USA Center for Nanomedicine Institute for Basic Science (IBS) and Graduate Program of Nano Biomedical Engineering (Nano BME) Advanced Science Institute Yonsei University Seoul Korea

ISBN: (纸本)9781665489607

Evolution of “Michigan Probes” has enabled unraveling the connectivity of neurons at cellular resolution and their dynamic interaction within and across brain areas that underlie behavioral and cognitive functions. Recently, micro-LEDs were monolithically integrated for optogenetic neuromodulation at scale without requiring external optical fiber connection. The ‘hectoSTAR’ micro-LED optoelectrode features 256 recording electrodes and 128 stimulation micro-LEDs in four silicon micro-needle shanks, covering a large volume with 1.3-mm × 0.9-mm cross-sectional area located as deep as 6 mm inside the brain. Technical challenges to overcome in scaling of optogenetic probes will be discussed, followed by future direction.

关键词： Optical fibers Electrodes Brain Optogenetics Silicon Recording Optical fiber devices

来源：评论

学校读者我要写书评

暂无评论

Maintaining the Quality and Aroma of Coffee with Fuzzy Logic Coffee Roasting Machine 3

Maintaining the Quality and Aroma of Coffee with Fuzzy Logic...

引用

3rd International Conference on Eco Engineering Development, ICEED 2019

作者： Harsawardana Samodro, Bayu Mahesworo, Bharuno Suparyanto, Teddy Surya Atmaja, Don Bosco Pardamean, Bens Institut Pertanian STIPER Yogyakarta55281 Indonesia Mechatronics and AI Research and Development Center Biotechnic Innovation Yogyakarta55281 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta11480 Indonesia

With the increasing global demands of coffee, Indonesia need to increase their coffee beans supply and improve the quality to maintain its position in the international coffee industry. One of the most important coffeepre-processing, coffee bean roasting, is under developed in Indonesia. Indonesia coffee farmers prefer to use the traditional cauldron to roast their coffee beans. Roasting coffee beans using traditional cauldron is inefficient and resulting unequal roasted level for the coffee beans. In this study, we proposed atemperature control system based on fuzzy logic for coffee roaster machine. The system controls the temperature in accordance with the demanded roasting level. A thermal camera is attached inside the roasting chamber to monitor the heaton the roasted coffee beans. The thermal camera is integrated with a stirring mechanism to equalise the heat among the beans. © 2020 Published under licence by IOP Publishing Ltd.

关键词： Fuzzy logic

来源：评论

学校读者我要写书评

暂无评论

Efficient and Accurate Physics-aware Multiplex Graph Neural Networks for 3D Small Molecules and Macromolecule Complexes

arXiv

引用

arXiv 2022年

作者： Zhang, Shuo Liu, Yang Xie, Lei Ph.D. Program in Computer Science The Graduate Center The City University of New York United States Department of Computer Science Hunter College The City University of New York United States Helen & Robert Appel Alzheimer’s Disease Research Institute Feil Family Brain & Mind Research Institute Weill Cornell Medicine Cornell University United States

Recent advances in applying Graph Neural Networks (GNNs) to molecular science have showcased the power of learning three-dimensional (3D) structure representations with GNNs. However, most existing GNNs suffer from the limitations of insufficient modeling of diverse interactions, computational expensive operations, and ignorance of vectorial values. Here, we tackle these limitations by proposing a novel GNN model, Physics-aware Multiplex Graph Neural Network (PaxNet), to efficiently and accurately learn the representations of 3D molecules for both small organic compounds and macromolecule complexes. PaxNet separates the modeling of local and non-local interactions inspired by molecular mechanics, and reduces the expensive angle-related computations. Besides scalar properties, PaxNet can also predict vectorial properties by learning an associated vector for each atom. To evaluate the performance of PaxNet, we compare it with state-of-the-art baselines in two tasks. On small molecule dataset for predicting quantum chemical properties, PaxNet reduces the prediction error by 15% and uses 73% less memory than the best baseline. On macromolecule dataset for predicting protein-ligand binding affinities, PaxNet outperforms the best baseline while reducing the memory consumption by 33% and the inference time by 85%. Thus, PaxNet provides a universal, robust and accurate method for large-scale machine learning of molecules. Our code is available at https://***/zetayue/Physics-aware-Multiplex-GNN. Copyright © 2022, The Authors. All rights reserved.

关键词： Macromolecules

来源：评论

学校读者我要写书评

暂无评论

Ludwigia octovalvis (Jacq.) P.H. Raven extract improves memory performance in mice with chronic kidney disease

引用

Phytomedicine Plus 2024年第2期4卷 100556-100556页

作者： Wang, Hao-Wei Huang, Yi-Hsuan Tung, Hsiao-Jou Lin, Wei-Sheng Chiu, Hao-Chieh Lin, Shuei-Liong Fan, Shou-Zen Wang, Pei-Yu Hsieh Yu Enterprise Co. Ltd. Taipei Taiwan Graduate Institute of Brain and Mind Sciences College of Medicine National Taiwan University Taipei Taiwan Department of Pediatrics Taipei Veterans General Hospital Taipei Taiwan Department of Clinical Laboratory Sciences and Medical Biotechnology College of Medicine National Taiwan University Taipei Taiwan Graduate Institute of Physiology College of Medicine National Taiwan University Taipei Taiwan Department of Anesthesiology National Taiwan University Hospital National Taiwan University Taipei Taiwan Department of Anesthesiology En Chu Kong Hospital Taipei Taiwan Neurobiology and Cognitive Science Center National Taiwan University Taipei Taiwan PhD. Program in Translational Medicine National Taiwan University and Academia Sinica Taipei Taiwan PhD. Program in Medical Neuroscience College of Medical Science and Technology Taipei Medical University Taipei Taiwan

Background: Chronic kidney disease (CKD) is a significant global health concern often accompanied by cognitive impairment in affected patients. Ludwigia octovalvis extract (LOE) is a traditional medicine widely used for various conditions, including renal disease and its associated complications. However, the pharmacological effects and underlying mechanisms of LOE on CKD remain unclear. Methods: Adult male mice underwent a 4-week oral adenine-induced CKD model, followed by daily administration of either a vehicle, losartan, or LOE for 1 to 2 months. A battery of behavioral tests was conducted to examine CKD-associated cognitive impairments. Additionally, RNA sequencing, Golgi staining, and immunohistochemistry were performed to decipher the underlying mechanisms. Results: Neither losartan nor LOE supplementation could reverse adenine-induced kidney damage. However, during behavioral tests, both losartan and LOE treatments improved memory performance in mice without affecting emotional status and general locomotor activity. Transcriptome profiling and histological analyses revealed altered dendritic arborization and increased spine density of dentate granule cells, along with augmented adult hippocampal neurogenesis, contributing to the improved memory performance of mice treated with LOE. Conclusion: Our study provides comprehensive neurobehavioral and molecular evidence supporting the potential use of LOE for future CKD-associated memory dysfunction treatment. © 2024 The Author(s)

关键词： Adenine Cognitive dysfunction Neurogenesis

来源：评论

学校读者我要写书评

暂无评论

Robust Prediction of Patient-Specific Clinical Response to Unseen Drugs From in vitro Screens Using Context-aware Deconfounding Autoencoder

Research Square

引用

Research Square 2021年

作者： He, Di Liu, Qiao Xie, Lei Program in Computer Science Graduate Center City University of New York New York City10016 United States Department of Computer Science Hunter College City University of New York New York City10065 United States

Accurate and robust prediction of patient-specific responses to drug treatments is critical for drug development and personalized medicine. However, patient data are often too scarce to train a generalized machine learning model. Although many methods have been developed to utilize cell line data, few of them can reliably predict individual patient clinical responses to new drugs due to data distribution shift and confounding factors. We develop a novel Context-aware Deconfounding Autoencoder (CODE-AE) that can extract common biological signals masked by context-specific patterns and confounding factors. Extensive studies demonstrate that CODE-AE effectively alleviates the out-of-distribution problem for the model generalization, significantly improves accuracy and robustness over state-of-the-art methods in both predicting patient-specific ex vivo and in vivo drug responses purely from in vitro screens and disentangling intrinsic biological signals from confounding factors. Using CODE-AE, we screened 50 drugs for 9,808 cancer patients and discovered novel personalized anti-cancer therapies and drug-response biomarkers. © 2021, CC BY.

关键词： Cell culture

来源：评论

学校读者我要写书评

暂无评论

Modifying BiVO4 as a photocatalyst for water oxidation using constant-duration alkaline-etched post treatments

引用

New Journal of Chemistry 2023年第2期48卷 569-577页

作者： Hsu, Chuan-Chih Chuang, Kai-Jie Huang, Hsiao-Wen Pan, Bo-Jin Chen, Hung-Ming Husain, Sadang Yougbaré, Sibidou Hsiao, Yu-Cheng Wu, Yung-Fu Lin, Lu-Yin Division of Cardiovascular Surgery Department of Surgery School of Medicine College of Medicine Taipei Medical University Taiwan Division of Cardiovascular Surgery Department of Surgery Taipei Medical University Hospital Taiwan Department of Chemical Engineering and Biotechnology National Taipei University of Technology Taipei Taiwan Department of Chemical Engineering Ming Chi University of Technology New Taipei City24301 Taiwan Gingen Technology Co. Ltd. Rm. 7 10F. No. 189 Sec. 2 Keelung Rd. Xinyi Dist. Taipei11054 Taiwan Department of Physics Faculty of Mathematics and Natural Science Lambung Mangkurat University Banjarmasin70124 Indonesia /Nanoro Ouagadougou03 Burkina Faso International PhD Program in Biomedical Engineering College of Biomedical Engineering Taipei Medical University Taipei11031 Taiwan Stanford Byers Center for Biodesign Stanford University CA94305-5428 United States Graduate Institute of Biomedical Optomechatronics College of Biomedical Engineering Taipei Medical University Taipei11031 Taiwan Cell Physiology and Molecular Image Research Center Wan Fang Hospital Taipei Medical University Taipei11696 Taiwan

BiVO4 with suitable band edges and a small band gap is considered an efficient photocatalyst for the oxygen evolution reaction (OER), but short charge-transfer lengths limit its photocatalytic ability. Increasing active sites can essentially enhance oxidation reactions and photocatalytic ability. The alkaline etching technique can refine the surface properties of BiVO4 by introducing oxygen vacancies and possibly establishing a heterojunction, but suitable alkaline etching methods are rarely discussed. In this study, three alkaline etching methods, including hydrothermal, soaking, and electrodeposition processes, are first applied for a constant duration to tailor the surface properties of BiVO4 as a photocatalyst for the OER. Alkaline-etched BiVO4 prepared using hydrothermal and soaking processes shows better photocatalytic abilities due to the generation of additional oxygen vacancies, while poor photocatalytic ability is found for that fabricated using electrodeposition due to the formation of less photocatalytic VO2. The highest photocurrent density of 2.38 mA cm−2 is obtained at 1.23 V versus a reversible hydrogen electrode in an electrolyte without a hole scavenger for the BiVO4 etched in the hydrothermal process, while the untreated BiVO4 presents a photocurrent density of 0.58 mA cm−2. A photocurrent retention of 92.3% is achieved after 5000 seconds of continuous illumination. The study supplies blueprints for establishing effective alkaline etching methods for enhancing the photocatalytic ability of BiVO4, with the exception of time costs. © 2024 The Royal Society of Chemistry.

关键词： Charge transfer

来源：评论

学校读者我要写书评

暂无评论

Count time series modelling of Twitter data topic modelling: A case of Indonesia flood events

引用

AIP Conference Proceedings 2023年第1期2594卷

作者： A. A. Hidayat B Pardamean Bioinformatics & Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

Twitter data provide rich and powerful information to leverage the dynamics of public perception to establish situational awareness and disaster mitigation strategies during critical times. In this paper, we perform topic modeling via Latent Dirichlet Allocation to extract topics from a collection of tweets related to Indonesia flood events in February 2021 with the query: “banjir”. The extracted topics are used as one of the features to build a generalized linear count time series model with Negative Binomial distribution. We find seven major topics from the model in which tweets containing a topic about the government’s role in handling the situation dominate the conversation. Taking into account a simple intervention analysis, we demonstrate a statistically significant change in the users’ behavior before and after the severe Jakarta flood on 20 February 2021. Moreover, a metric evaluation demonstrates that a covariate that describes the turning point of the Jakarta flood event is convenient to build a more accurate count time series model of the tweets.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A new capnellene skeleton from the octocoral Capnella imbricata (Quoy & Gaimard, 1833)

引用

Journal of Molecular Structure 2023年 1271卷

作者： Wu, I-Ting Fan, Yu-Chen Lin, Guan-Zhou Wang, Yi-Lin Hwang, Tsong-Long Lai, Kuei-Hung Chung, Hsu-Ming Department of Applied Chemistry National Pingtung University Pingtung900391 Taiwan Graduate Institute of Biomedical Sciences Graduate Institute of Natural Products College of Medicine Chang Gung University Taoyuan33305 Taiwan Research Center for Chinese Herbal Medicine Graduate Institute of Healthy Industry Technology College of Human Ecology Chang Gung University of Science and Technology Taoyuan33305 Taiwan Department of Chemical Engineering Ming Chi University of Technology New Taipei City243303 Taiwan Department of Anesthesiology Chang Gung Memorial Hospital Taoyuan333 Taiwan PhD Program in Clinical Drug Development of Herbal Medicine College of Pharmacy Taipei Medical University Taipei11031 Taiwan Graduate Institute of Pharmacognosy College of Pharmacy Taipei Medical University Taipei11031 Taiwan Traditional Herbal Medicine Research Center Taipei Medical University Hospital Taipei11031 Taiwan

Chemical investigations on the ethyl acetate extract of the octocoral Capnella imbricata collected from the waters of Taiwan, which led to the isolation of three capnellenes (1–3), including one new metabolite, 9(12)-capnellene-8β,10α,15-triol (1), along with two known metabolites, 9(12)-capnellene-5α,8β,10α-triol (2), and 9(12)-capnellene-8β,10α-diol (3). The structures of the isolated metabolites were elucidated through extensive spectroscopic analyses, while the relative stereochemistry of 3 was confirmed by a single-crystal X-ray diffraction analysis for the first time in this study. Compounds 1–3 were evaluated in terms of their anti-inflammatory activity by examining their inhibitory effects on the generation of superoxide anions and the release of elastase by human neutrophils. © 2022 Elsevier B.V.

关键词： Metabolites

来源：评论

学校读者我要写书评

暂无评论

Meteorological parameters for PV installations in Indonesia

引用

AIP Conference Proceedings 2024年第1期3026卷

作者： Joko Pebrianto Trinugroho Alam Ahmad Hidayat Reza Rahutomo Bens Pardamean Bioinformatics & Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Information System Department School of Information Systems Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta Indonesia 11480

Many countries are still dependent on fossil fuels as their primary energy supply. However, there is a growing concern about the sustainability and the environmental issue of fossil fuels. Therefore, it is important to utilize renewable resources as the energy supply, such as solar energy. As a country with a tropical climate, Indonesia has a great potential to use solar energy, due to the abundance of sunlight exposure. The present study aims to analyze several meteorological parameters for the installation of photovoltaic (PV) technology in Jakarta, Indonesia. The meteorological data provided by the Ministry of Environment and Forestry, Indonesia from 2008-2021 were used at three different locations in Jakarta. Data visualizations were used to show the difference between each variable in different locations. In addition, the statistical difference between the variables in the three locations was also examined using the Mann-Whitney U test. The test shows that all parameters are evenly distributed in the three locations except for a moderate difference in air temperature in the two locations. Furthermore, the monthly analysis of the parameters also indicates that the dry season, especially from August to September, would be the optimal time to utilize PV technology. Hence, this study would be useful to give preliminary insight regarding a site-specified assessment of PV plants in Jakarta based on local meteorological data.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Generative AI-enabled Vehicular Networks: Fundamentals, Framework, and Case Study

arXiv

引用

arXiv 2023年

作者： Zhang, Ruichen Xiong, Ke Du, Hongyang Niyato, Dusit Kang, Jiawen Shen, Xuemin Poor, H. Vincent The Engineering Research Center of Network Management Technology High Speed Railway of Ministry of Education School of Computer and Information Technology Beijing Jiaotong University Beijing100044 China The Collaborative Innovation Center of Railway Traffic Safety Beijing Jiaotong University Beijing100044 China The National Engineering Research Center of Advanced Network Technologies Beijing Jiaotong University Beijing100044 China The School of Computer Science and Engineering The Energy Research Institute @ NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore The School of Automation Guangdong University of Technology China The Department of Electrical and Computer Engineering University of Waterloo Canada The Department of Electrical and Computer Engineering Princeton University PrincetonNJ08544 United States

Recognizing the tremendous improvements that the integration of generative AI can bring to intelligent transportation systems, this article explores the integration of generative AI technologies in vehicular networks, focusing on their potential applications and challenges. Generative AI, with its capabilities of generating realistic data and facilitating advanced decision-making processes, enhances various applications when combined with vehicular networks, such as navigation optimization, traffic prediction, data generation, and evaluation. Despite these promising applications, the integration of generative AI with vehicular networks faces several challenges, such as real-time data processing and decision-making, adapting to dynamic and unpredictable environments, as well as privacy and security concerns. To address these challenges, we propose a multi-modality semantic-aware framework to enhance the service quality of generative AI. By leveraging multi-modal and semantic communication technologies, the framework enables the use of text and image data for creating multi-modal content, providing more reliable guidance to receiving vehicles and ultimately improving system usability and efficiency. To further improve the reliability and efficiency of information transmission and reconstruction within the framework, taking generative AI-enabled vehicle-to-vehicle (V2V) as a case study, a deep reinforcement learning (DRL)-based approach is proposed for resource allocation. Finally, we discuss potential research directions and anticipated advancements in the field of generative AI-enabled vehicular networks. Copyright © 2023, The Authors. All rights reserved.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：