检索结果-内蒙古大学图书馆

New strategy for reversal tolerant anode for automotive polymer electrolyte fuel cell

Chinese Chemical Letters 2019年第6期30卷 1186-1189页

作者： Chanho Pak Seung Woo Lee Chaekyung Baik Bong Ho Lee Dae Jong You Eunyoung You Graduate Program of Energy Technology School of Integrated Technology Institute of Integrated Technology Gwangju Institute of Science and Technology Gwangju 61005 Republic of Korea Fuel Cell Engineering Core Technology Team Division of Electric Powertrain Hyundai Mobis Co. Ltd. Yongin Gyeonggi-do 16891 Republic of Korea

Since the commercialization of the fuel cell electric vehicles (FCEVs), the polymer electrolyte membrane fuel cell system has been actively improved as a powertrain for ultimate environment-friendly vehicle. During the FCEV operation, various transient conditions such as start-up/shut-down and fuel starvation occur irregularly, which deteriorates the durability of the membrane electrode assembly. In particular, when fuel starvation occurs, the carbon support in the anode is oxidized within few minutes, thus the mitigation of this phenomenon is essential for securing the durability. This short review introduces the concept of reversal tolerant anode (RTA), which is a mitigation method using an oxygen evolution catalyst and reviews some previous reports. In addition, new approach for RTA suggested by authors recently, which is the replacement of Pt anode catalyst by multifunctional IrRu alloy catalyst that simultaneously exhibits the activities for the hydrogen oxidation reaction and the oxygen evolution reaction is introduced.

关键词： Multifunctional IrRu alloy catalyst Reversal tolerant anode Hydrogen oxidation reaction catalyst Oxygen evolution reaction catalyst Cell reversal durability Polymer electrolyte membrane fuel cell

来源：评论

学校读者我要写书评

暂无评论

Landau Polaritons in a Full-Dielectric Three-Dimensional Photonic-Crystal Cavity

Landau Polaritons in a Full-Dielectric Three-Dimensional Pho...

引用

CLEO: science and Innovations, S and I 2022

作者： Tay, Fuyang Mojibpour, Ali Liang, Shuang Baydin, Andrey Ahmadivand, Arash Peraca, Nicolas Marquez Xu, Hongjing Gardner, Geoff C. Manfra, Michael J. Hagenmüller, David Kono, Junichiro Department of Electrical and Computer Engineering Rice University HoustonTX77005 United States Applied Physics Graduate Program Smalley-Curl Institute Rice University HoustonTX77005 United States Department of Physics and Astronomy Purdue University West LafayetteIN47907 United States Birck Nanotechnology Center Purdue University West LafayetteIN47907 United States Smalley-Curl Institute Rice University HoustonTX77005 United States Department of Physics and Astronomy Rice University HoustonTX77005 United States Microsoft Quantum Purdue Purdue University West LafayetteIN47907 United States School of Electrical and Computer Engineering Purdue University West LafayetteIN47907 United States School of Materials Engineering Purdue University West LafayetteIN47907 United States Université de Strasbourg CNRS Strasbourg67000 France Department of Materials Science and NanoEngineering Rice University HoustonTX77005 United States

ISBN: (纸本)9781557528209

We fabricated a full-dielectric three-dimensional photonic-crystal cavity containing an ultrahigh-mobility two-dimensional electron gas. By applying a strong perpendicular magnetic field, we created Landau polaritons originating from the ultrastrong coupling of electrons with cavity modes. © Optica Publishing Group 2022, © 2022 The Author(s)

关键词： Polariton

来源：评论

学校读者我要写书评

暂无评论

DeepDTAGen: a multitask deep learning framework for drug-target affinity prediction and target-aware drugs generation

引用

Nature Communications 2025年第1期16卷 1-15页

作者： Shah, Pir Masoom Zhu, Huimin Lu, Zhangli Wang, Kaili Tang, Jing Li, Min School of Computer Science and Engineering Central South University Changsha China School of Computer Science and Technology Donghua University Shanghai China Research Program in Systems Oncology Faculty of Medicine University of Helsinki Helsinki Finland Department of Biochemistry and Developmental Biology Faculty of Medicine University of Helsinki Helsinki Finland Xiangjiang Laboratory Changsha China Furong Laboratory Central South University Changsha China

Identifying novel drugs that can interact with target proteins is a highly challenging, time-consuming, and costly task in drug discovery and development. Numerous machine learning-based models have recently been utilized to accelerate the drug discovery process. However, these existing methods are primarily uni-tasking, either designed to predict drug-target interaction (DTI) or generate new drugs. Through the lens of pharmacological research, these tasks are intrinsically interconnected and play a critical role in effective drug development. Therefore, the learning models must be utilized in such a manner to learn the structural properties of drug molecules, the conformational dynamics of proteins, and the bioactivity between drugs and targets. To this end, this paper develops a novel multitask learning framework that can predict drug-target binding affinities and simultaneously generate new target-aware drug variants, using common features for both tasks. In addition, we developed the FetterGrad algorithm to address the optimization challenges associated with multitask learning particularly those caused by gradient conflicts between distinct tasks. Comprehensive experiments on three real-world datasets demonstrate that the proposed model provides an effective mechanism for predicting drug-target binding affinities and generating novel drugs, thus greatly facilitating the drug discovery process. © The Author(s) 2025.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Fast pedestrian detection method based on BING

Fast pedestrian detection method based on BING

引用

3rd Asian Conference on Artificial Intelligence technology, ACAIT 2019

作者： Zhao, Yong Cui, Zhongwei Zhang, Yongjun Xu, Wenbo Liang, Hao Zuo, Yu Big Data Science and Intelligent Engineering Research Institute Guizhou Education University Guiyang550018 China Key Lab of Integrated Microsystems Peking University Shenzhen Graduate School Shenzhen518055 China College of Computer Science and Technology Guizhou University Guiyang550025 China

Pedestrian detection is one of hot topics in the field of computer vision and pattern recognition, which is of great value to video surveillance, intelligent traffic and human-computer interaction, etc. and how to improve detection rate and speed is the key. Most traditional pedestrian detection methods are based on the pyramid sliding window scanning method, and for images in which the majority of the region does not contain a body, the detection is inefficient. This study presents a body window sampling algorithm based on binarised normed gradients, which can quickly and effectively extract the window of the image that most likely contains human body to be identified, thus greatly improving the detection speed and obtaining a lower false alarm rate. The authors employ the histogram of oriented gradient feature and the linear support vector machine to train the classifier. For the same false test case in comparison with the pyramid scanning method, when the authors used 2,000 sampling windows for detection, they observed a detection rate increase of 11%, the detection speed increased 19.6 times. For 5,000 sampling windows, the detection rate increased by 20% and the detection speed increased 7.8 times. © 2020 Institution of Engineering and technology. All rights reserved.

关键词： Human computer interaction

来源：评论

学校读者我要写书评

暂无评论

An Adaptive Weighted QITE-VQE Algorithm for Combinatorial Optimization Problems

arXiv

引用

arXiv 2025年

作者： Xie, Ningyi Lee, Xinwei Chen, Tiejin Saito, Yoshiyuki Asai, Nobuyoshi Cai, Dongsheng Graduate School of Science and Technology University of Tsukuba Ibaraki Japan School of Computing and Information Systems Singapore Management University Singapore Singapore School of Computing and Augmented Intelligence Arizona State University Tempe United States ARGO GRAPHICS Inc. Tokyo Japan School of Computer Science and Engineering University of Aizu Fukushima Japan Faculty of Engineering Information and Systems University of Tsukuba Ibaraki Japan

The variational quantum eigensolver (VQE) is a promising algorithm for finding the ground states of a given Hamiltonian. Its application to binary-formulated combinatorial optimization (CO) has been intensively studied in recent years. However, typical VQE approaches for CO problems often suffer from local minima or barren plateaus, limiting their ability to achieve optimal solutions. The quantum imaginary time evolution (QITE) offers an alternative approach for effective ground-state preparation but requires large circuits to approximate non-unitary operations. Although compressed QITE (cQITE) reduces circuit depth, accumulated errors eventually cause energy increases. To address these challenges, we propose an Adaptive Weighted QITE-VQE (AWQV) algorithm that integrates the VQE gradients with the cQITE updates through an adaptive weighting scheme during optimization. In numerical experiments of MaxCut on unweighted regular graphs, AWQV achieves near-optimal approximation ratios, while for weighted ErdősRényi instances, it outperforms the classical Goemans-Williamson algorithm. © 2025, CC BY.

关键词： Combinatorial optimization

来源：评论

学校读者我要写书评

暂无评论

Deep-Strong Coupling between Cavity Photons and Terahertz TO Phonons in PbTe

Deep-Strong Coupling between Cavity Photons and Terahertz TO...

引用

2023 Conference on Lasers and Electro-Optics, CLEO 2023

作者： Baydin, Andrey Manjappa, Manukumara Mishra, Sobhan Subhra Xu, Hongjing Tay, Fuyang Kim, Dasom Hernandez, Felix G.G. Rappl, Paulo H.O. Abramof, Eduardo Singh, Ranjan Kono, Junichiro Department of Electrical and Computer Engineering Rice University HoustonTX77005 United States Smalley-Curl Institute Rice University HoustonTX77005 United States Instrumentation and Applied Physics Department Indian Institute of Science Bangalore560012 India Center for Disruptive Photonic Technologies The Photonics Institute Nanyang Technological University 639798 Singapore Department of Physics and Astronomy Rice University HoustonTX77005 United States Applied Physics Graduate Program Smalley-Curl Institute Rice University HoustonTX77005 United States Instituto de Física Universidade de Sao Paulo SP Sao Paulo05508-090 Brazil Laboratorio Associado de Sensores e Materiais Instituto Nacional de Pesquisas Espaciais SP Sao Jose dos Campos12201-970 Brazil Division of Physics and Applied Physics School of Physical and Mathematical Sciences Nanyang Technological University 637371 Singapore Department of Material Science and NanoEngineering Rice University HoustonTX77005 United States

We have investigated the resonant coupling of photons with TO phonons in lead telluride in small-mode-volume terahertz cavities, observing a giant vacuum Rabi splitting on the order of the bare cavity-phonon frequency... 详细信息

ISBN: (纸本)9781957171258

关键词： Photons

来源：评论

学校读者我要写书评

暂无评论

Mo-Terminated Edges in Mos2 for Site-Specific Hydrolysis and DNA Cleavage

SSRN

引用

SSRN 2024年

作者： Wang, Cong Wu, Menghan Li, Muqing Zhao, Yingcan Zhao, Mingchuang Zhang, Yunhao Bai, Yichao Gao, Jianxiang Wang, Xiaoxia Tian, Xilin Zhang, Han Chang, Liang Zou, Xiaolong Liu, Bilu Kang, Feiyu Terrones, Mauricio Lei, Yu Institute of Materials Research Shenzhen Key Laboratory of Advanced Layered Materials for Value-added Applications Guangdong Provincial Key Laboratory of Thermal Management Engineering and Materials Center of Double Helix Tsinghua Shenzhen International Graduate School Tsinghua University Shenzhen518055 China Institute of Materials Research Shenzhen Geim Graphene Center Shenzhen Key Laboratory of Advanced Layered Materials for Value-added Applications Tsinghua-Berkeley Shenzhen Institute Tsinghua Shenzhen International Graduate School Tsinghua University Shenzhen518055 China Environmental Science Program Department of Life Sciences Beijing Normal University-Hong Kong Baptist University United International College Guangdong 519087 China Tsinghua Shenzhen International Graduate School Tsinghua University Shenzhen518055 China Department of Physics Department of Chemistry Department of Materials Sciences Center for 2-Dimensional and Layered Materials The Pennsylvania State University University Park PA16802 United States International Collaborative Laboratory of 2D Materials for Optoelectronics Science and Technology Ministry of Education Institute of Microscale Optoelectronics Shenzhen University Shenzhen518060 China Key Laboratory of Optoelectronic Devices and Systems China

The hydrolysis of DNA serves as the foundational principle for gene engineering that enable precise gene cleavage at the molecular level. This process typically occurs in biological nucleases, which exhibit nucleobase-selective and catalytic hydrolysis capabilities rarely replicated in abiotic nanomaterials. Here, we demonstrate that molybdenum-terminated (Mo-terminated) edges of molybdenum disulfide (MoS2) possess the unique ability to abstract a proton (H+) from water molecules, thereby facilitating catalytic hydrolysis reactions that cleave the phosphodiester bonds in DNA through the action of hydroxide ions. The enhanced proton absorption at Mo-terminated edges of MoS2 significantly reduces the activation energy required for the DNA hydrolysis reaction. Furthermore, the favorable interaction between the Mo-terminated edges and thymine nucleobases promotes both charge transfer and P-O bond cleavage, enabling targeted DNA hydrolysis at 'TTTTTTT' sequences under dark conditions. This discovery underscores the potential of MoS2 as a stable, efficient nanosystem for precise genetic editing, heralding advanced applications in the field of gene engineering. © 2024, The Authors. All rights reserved.

关键词： DNA sequences

来源：评论

学校读者我要写书评

暂无评论

Ultrasound-based control of micro-bubbles for exosome delivery in treating COVID-19 lung damage

arXiv

引用

arXiv 2021年

作者： Fonseca, Bruna Fonseca, Caio Barros, Michael White, Mark Abhyankar, Vinay Borkholder, David A. Balasubramaniam, Sasitharan Telecommunication Software & Systems Group Waterford Institute of Technology Waterford Ireland Research Innovation & Graduate Studies Waterford Institute of Technology Waterford Ireland School of Computer Science and Electronic Engineering University of Essex Colchester United Kingdom Kate Gleason College of Engineering Rochester Institute of Technology Rochester United States

The recent COVID-19 pandemic has resulted in high fatality rates, especially for patients who suffer from underlying health issues. One of the more serious symptoms exhibited from patients suffering from an acute COVID-19 infection is breathing difficulties and shortness of breath, which is largely due to the excessive fluid (cellular leakage and cytokine storm) and mucoid debris that have filled lung alveoli, and reduced the surfactant tension resulting in heavy and stiff lungs. In this paper we propose the use of micro-bubbles filled with exosomes that can be released upon exposure to ultrasound signals as a possible rescue therapy in deteriorating COVID-19 patients. Recent studies have shown that exosomes can be used to repair and treat lung damage for patients who have suffered from the viral infection. We have conducted simulations to show the efficacy of the ultrasound signals that will penetrate through layers of tissues reaching the alveoli that contains the micro-bubbles. Our results have shown that ultrasound signals with low frequencies are required to oscillate and rupture the polymer-based micro-bubbles. Our proposed system can be used for patients who require immediate rescue treatments for lung damage, as well as for recovered patients who may suffer from viral relapse infection, where the micro-bubbles will remain dormant for a temporary therapeutic window until they are exposed to the ultrasound signals. © 2021, CC BY-NC-ND.

关键词： Biological organs

来源：评论

学校读者我要写书评

暂无评论

Region-based Convolution Neural Network Approach for Accurate Segmentation of Pelvic Radiograph 26

Region-based Convolution Neural Network Approach for Accurat...

引用

26th National and 4th International Iranian Conference on Biomedical Engineering, ICBME 2019

作者： Jodeiri, Ata Zoroofi, Reza A. Hiasa, Yuta Takao, Masaki Sugano, Nobuhiko Sato, Yoshinobu Otake, Yoshito University of Tehran School of Electrical Computer Engineering Tehran Iran Nara Institute of Science and Technology Graduate School of Information Science Nara Japan Osaka University Graduate School of Medicine Department of Orthopedic Medical Engineering Suita Japan

ISBN: (纸本)9781728156637

With the increasing usage of radiograph images as a most common medical imaging system for diagnosis, treatment planning, and clinical studies, it is increasingly becoming a vital factor to use machine learning-based systems to provide reliable information for surgical pre-planning. Segmentation of pelvic bone in radiograph images is a critical preprocessing step for some applications such as automatic pose estimation and disease detection. However, the encoder-decoder style network known as U-Net has demonstrated limited results due to the challenging complexity of the pelvic shapes, especially in severe patients. In this paper, we propose a novel multi-task segmentation method based on Mask R-CNN architecture. For training, the network weights were initialized by large non-medical dataset and fine-tuned with radiograph images. Furthermore, in the training process, augmented data was generated to improve network performance. Our experiments show that Mask R-CNN utilizing multi-task learning, transfer learning, and data augmentation techniques achieve 0.96 DICE coefficient, which significantly outperforms the U-Net. Notably, for a fair comparison, the same transfer learning and data augmentation techniques have been used for U-net training. © 2019 IEEE.

关键词： Diagnosis

来源：评论

学校读者我要写书评

暂无评论

Largest triangles in a polygon

arXiv

引用

arXiv 2020年

作者： Lee, Seungjun Eom, Taekang Ahn, Hee-Kap Department of Computer Science and Engineering Pohang University of Science and Technology Pohang Korea Republic of Department of Mathematics Pohang University of Science and Technology Pohang Korea Republic of Department of Computer Science and Engineering Graduate School of Artificial Intelligence Pohang University of Science and Technology Pohang Korea Republic of

We study the problem of finding maximum-area triangles that can be inscribed in a polygon in the plane. We consider eight versions of the problem: we use either convex polygons or simple polygons as the container;we require the triangles to have either one corner with a fixed angle or all three corners with fixed angles;we either allow reorienting the triangle or require its orientation to be fixed. We present exact algorithms for all versions of the problem. In the case with reorientations for convex polygons with n vertices, we also present (1 − Ε)-approximation algorithms. Copyright © 2020, The Authors. All rights reserved.

关键词： Machine 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：