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Tuning Electrocatalytic Properties of Bismuthene by Heteroatom Decoration Toward Overall Water Splitting

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ChemistrySelect 2025年第21期10卷

作者： Yue-Han Ji Jun-Miao Zhang Xiang-Yu Leng Liang-Ze Zhu Bei-Bei Xiao School of Energy and Power Engineering Jiangsu University of Science and Technology Zhenjiang Jiangsu 212003 China Jangho Architecture College Northeastern University Shenyang Liaoning Province 110167 China Department of Computer and Science Technology LyuLiang University LyuLiang Shanxi 033000 China

Developing of effective electrocatalysts for overall water splitting is of importance for the achievement of hydrogen energy cycling. In this work, hydrogen evolution and oxygen evolution of the defective bismuthene with decoration of a transition metal atom have been fully investigated via density functional theory calculations. The results indicate that the fixation of transition metal dopant into defective bismuthene is achieved via the interaction between the Bi sp band and TM sd band. Wherein, Sc@Bi, Ti@Bi, Zn@Bi, Y@Bi, Rh@Bi, Pd@Bi, Ag@Bi, Pt@Bi, and Au@Bi are thermodynamically stable according to the data of the formation energy. Furthermore, Sc@Bi, Ti@Bi, Y@Bi, Rh@Bi, Pd@Bi, and Pt@Bi have good performances toward hydrogen evolution, and the overpotentials η HER are 0.11, 0.22, 0.30, 0.13, 0.27, and 0.01 V, respectively. Furthermore, the optimal candidates toward oxygen evolution are Rh@Bi and Pt@Bi, endowed with the overpotentials η OER of 0.66 and 0.36 V, respectively. Therefore, Pt@Bi and Rh@Bi are bifunctional-active toward overall water splitting. These findings indicate that bismuthene could provide a new platform to explore high-efficiency electrocatalysts in overall water splitting.

关键词： Bismuthene Density functional theory Electrocatalysis Water splitting

Constrained Optimization with Decision-Dependent Distributions

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arXiv 2023年

作者： Wang, Zifan Liu, Changxin Parisini, Thomas Zavlanos, Michael M. Johansson, Karl H. Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden Digital Futures StockholmSE-10044 Sweden The Department of Electrical and Electronic Engineering Imperial College London LondonSW7 2AZ United Kingdom The Department of Engineering and Architecture University of Trieste Trieste34127 Italy The KIOS Research and Innovation Center of Excellence University of Cyprus NicosiaCY-1678 Cyprus The Department of Mechanical Engineering and Materials Science Duke University DurhamNC United States

In this paper we deal with stochastic optimization problems where the data distributions change in response to the decision variables. Traditionally, the study of optimization problems with decision-dependent distributions has assumed either the absence of constraints or fixed constraints. This work considers a more general setting where the constraints can also dynamically adjust in response to changes in the decision variables. Specifically, we consider linear constraints and analyze the effect of decision-dependent distributions in both the objective function and constraints. Firstly, we establish a sufficient condition for the existence of a constrained equilibrium point, at which the distributions remain invariant under retraining. Morevoer, we propose and analyze two algorithms: repeated constrained optimization and repeated dual ascent. For each algorithm, we provide sufficient conditions for convergence to the constrained equilibrium point. Furthermore, we explore the relationship between the equilibrium point and the optimal point for the constrained decision-dependent optimization problem. Notably, our results encompass previous findings as special cases when the constraints remain fixed. To show the effectiveness of our theoretical analysis, we provide numerical experiments on both a market problem and a dynamic pricing problem for parking based on real-world data. Copyright © 2023, The Authors. All rights reserved.

关键词： Constrained optimization

Power Efficient Video Super-Resolution on Mobile NPUs with Deep Learning, Mobile AI & AIM 2022 challenge: Report

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arXiv 2022年

作者： Ignatov, Andrey Timofte, Radu Chiang, Cheng-Ming Kuo, Hsien-Kai Xu, Yu-Syuan Lee, Man-Yu Lu, Allen Cheng, Chia-Ming Chen, Chih-Cheng Yong, Jia-Ying Shuai, Hong-Han Cheng, Wen-Huang Jia, Zhuang Xu, Tianyu Zhang, Yijian Bao, Long Sun, Heng Zhang, Diankai Gao, Si Liu, Shaoli Wu, Biao Zhang, Xiaofeng Zheng, Chengjian Lu, Kaidi Wang, Ning Sun, Xiao Wu, HaoDong Liu, Xuncheng Zhang, Weizhan Yan, Caixia Du, Haipeng Zheng, Qinghua Wang, Qi Chen, Wangdu Duan, Ran Duan, Ran Sun, Mengdi Zhu, Dan Chen, Guannan Cho, Hojin Kim, Steve Yue, Shijie Li, Chenghua Zhuge, Zhengyang Chen, Wei Wang, Wenxu Zhou, Yufeng Cai, Xiaochen Cai, Hengxing Xu, Kele Liu, Li Cheng, Zehua Lian, Wenyi Lian, Wenjing Computer Vision Lab ETH Zurich Switzerland AI Witchlabs Switzerland University of Wuerzburg Germany MediaTek Inc. Taiwan National Yang Ming Chiao Tung University Taiwan Video Algorithm Group Camera Department Xiaomi Inc. China Audio & Video Technology Platform Department ZTE Corp. China China School of Computer Science and Technology Xi'an Jiaotong University China MIGU Video Co. Ltd China BOE Technology Group Co. Ltd. China GenGenAI Korea Republic of North China University of Technology China Institute of Automation Chinese Academy of Sciences China State Key Laboratory of Computer Architecture Institute of Computing Technology China 4Paradigm Inc. Beijing China National University of Defense Technology Changsha China University of Oxford Oxford United Kingdom Uppsala University Sweden Northeastern University China

Video super-resolution is one of the most popular tasks on mobile devices, being widely used for an automatic improvement of lowbitrate and low-resolution video streams. While numerous solutions have been proposed for this problem, they are usually quite computationally demanding, demonstrating low FPS rates and power efficiency on mobile devices. In this Mobile AI challenge, we address this problem and propose the participants to design an end-to-end real-time video super-resolution solution for mobile NPUs optimized for low energy consumption. The participants were provided with the REDS training dataset containing video sequences for a 4X video upscaling task. The runtime and power efficiency of all models was evaluated on the powerful MediaTek Dimensity 9000 platform with a dedicated AI processing unit capable of accelerating floating-point and quantized neural networks. All proposed solutions are fully compatible with the above NPU, demonstrating an up to 500 FPS rate and 0.2 [Watt/30 FPS] power consumption. A detailed description of all models developed in the challenge is provided in this paper. Copyright © 2022, The Authors. All rights reserved.

关键词： Energy utilization

Identifying users with wearable sensors based on activity patterns 11

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Identifying users with wearable sensors based on activity pa...

11th International Conference on Emerging Ubiquitous Systems and Pervasive Networks, EUSPN 2020

作者： Ehatisham-Ul-Haq, Muhammad Malik, Maryam Naseer Azam, Muhammad Awais Naeem, Usman Khalid, Asra Ghazanfar, Mustansar Ali Department of Computer Engineering University of Engineering and Technology Taxila Punjab47050 Pakistan Whitecliffe Technologies Wellington New Zealand School of Electronic Engineering and Computer Science Queen Mary University of London United Kingdom School of Engineering and Computer Science Victoria University of Wellington New Zealand School of Architecture Computing and Engineering University of East London United Kingdom

We live in a world where ubiquitous systems surround us in the form of automated homes, smart appliances and wearable devices. These ubiquitous systems not only enhance productivity but can also provide assistance given a variety of different scenarios. However, these systems are vulnerable to the risk of unauthorized access, hence the ability to authenticate the end-user seamlessly and securely is important. This paper presents an approach for user identification given the physical activity patterns captured using on-body wearable sensors, such as accelerometer, gyroscope, and magnetometer. Three machine learning classifiers have been used to discover the activity patterns of users given the data captured from wearable sensors. The recognition results prove that the proposed scheme can effectively recognize a user's identity based on his/her daily living physical activity patterns. © 2020 The Authors. Published by Elsevier B.V.

关键词： Wearable sensors

Cerebral micro-bleeding identification based on a nine-layer convolutional neural network with stochastic pooling

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Cerebral micro-bleeding identification based on a nine-layer...

作者： Wang, Shuihua Sun, Junding Mehmood, Irfan Pan, Chichun Chen, Yi Zhang, Yu-Dong School of Computer Science and Technology Henan Polytechnic University Jiaozuo China School of Architecture Building and Civil Engineering Loughborough University Loughborough United Kingdom Department of Informatics University of Leicester Leicester United Kingdom Department of Computer Science and Engineering College of Electronics and Information Engineering Sejong University Seoul Korea Republic of School of Computer Science and Technology Nanjing Normal University Nanjing China School of Business Nanjing Normal University Nanjing China Jiangsu Laboratory of Lake Environment Remote Sensing Technologies Huaiyin Institute of Technology Huaian China

Cerebral micro-bleedings are small chronic brain hemorrhages caused by structural abnormalities of the small vessels. CMBs can be found from individuals with stroke at memory clinics and even healthy elderly people. CMBs indicate hemorrhage-prone pathological states. Research shows that CMBs are associated with an increased risk of future ischemic stroke, intra-cerebral hemorrhage (ICH), dementia, and death. Considering that CMBs severely influence people's life, it is necessary to identify the CMBs in an early stage to prevent from further deterioration and to help people live a healthy life. In this paper, we proposed using CNN with stochastic pooling for the CMB detection. CNN has good performance in image and video recognition, recommender system, and nature language processing. Based on the collected subject, the experiment result shows that the six-convolution layer and three fully-connected layer CNN, nine-layers in total, achieved sensitivity, specificity, accuracy, and precision as 97.22%, and 97.35%, 97.28%, and 97.35% in average of ten runs, which shows better performance than five state-of-the-art methods. © 2019 John Wiley & Sons, Ltd.

关键词： Convolution

Solving the multiplication problem of a large language model system using a graph-based method

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arXiv 2023年

作者： Tuncer, Turker Dogan, Sengul Baygin, Mehmet Barua, Prabal Datta Hafeez-Baig, Abdul Tan, Ru-San Chakraborty, Subrata Acharya, U. Rajendra Department of Digital Forensics Engineering Technology Faculty Firat University Elazig Turkey Department of Computer Engineering Faculty of Engineering and Architecture Erzurum Technical University Erzurum Turkey University of Southern Queensland Australia School of Management and Enterprise University of Southern Queensland ToowoombaQLD Australia Department of Cardiology National Heart Centre Singapore Singapore169609 Singapore Duke-NUS Medical School Singapore169857 Singapore School of Science and Technology Faculty of Science Agriculture Business and Law University of New England ArmidaleNSW2351 Australia Center for Advanced Modelling and Geospatial Information Systems Faculty of Engineering and IT University of Technology Sydney SydneyNSW2007 Australia School of Mathematics Physics and Computing University of Southern Queensland Springfield Australia

The generative pre-trained transformer (GPT)-based chatbot software ChatGPT possesses excellent natural language processing capabilities but is inadequate for solving arithmetic problems, especially multiplication. Its GPT structure uses a computational graph for multiplication, which has limited accuracy beyond simple multiplication operations. We developed a graph-based multiplication algorithm that emulated human-like numerical operations by incorporating a ×10k operator, where k represents the maximum power to base 10 of the larger of two input numbers. Our proposed algorithm attained 100% accuracy for 1,000,000 large number multiplication tasks, effectively solving the multiplication challenge of GPT-based and other large language models. Our work highlights the importance of blending simple human insights into the design of artificial intelligence algorithms. Copyright © 2023, The Authors. All rights reserved.

关键词： Blending

Securing isosceles triangular formations under heterogeneous sensing and mixed constraints

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arXiv 2021年

作者： Chan, Nelson P.K. Jayawardhana, Bayu de Marina, Hector Garcia Engineering and Technology Institute Groningen University of Groningen Nijenborgh 4 Groningen9747AG Netherlands Department of Computer Architecture and Automatic Control Faculty of Physics Universidad Complutense de Madrid Madrid28040 Spain

This paper focuses on securing a triangular shape (up to translation) for a team of three mobile robots that uses heterogeneous sensing mechanism. Based on the available local information, each robot employs the popular gradient-based control law to attain the assigned individual task(s). In the current work, robots are assigned either distance and signed area task(s) or bearing task(s). We provide a sufficient condition on the gain ratio RAd between the signed area and the distance control term such that the desired formation shape, an isosceles triangle, is reached from all feasible starting positions. Numerical simulations are provided to support the theoretical *** Codes 93D99 © 2021, CC BY-NC-SA.

关键词： Robots

FLP: Factor lattice pattern-based automated detection of Parkinson's disease and specific language impairment using recorded speech

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computers in Biology and Medicine 2024年 173卷 108280-108280页

作者： Tuncer, Turker Dogan, Sengul Baygin, Mehmet Barua, Prabal Datta Palmer, Elizabeth Emma March, Sonja Ciaccio, Edward J. Tan, Ru-San Acharya, U. Rajendra Department of Digital Forensics Engineering Technology Faculty Firat University Elazig Turkey Department of Computer Engineering Faculty of Engineering and Architecture Erzurum Technical University Erzurum Turkey University of Southern Queensland Australia Centre of Clinical Genetics Sydney Children's Hospitals Network Randwick2031 Australia School of Women's and Children's Health University of New South Wales Randwick2031 Australia School of Psychology and Counselling and Centre for Health Research University of Southern Queensland Springfield Australia Department of Medicine Columbia University Irving Medical Center United States Department of Cardiology National Heart Centre Singapore Singapore Duke-NUS Medical School Singapore School of Mathematics Physics and Computing University of Southern Queensland Springfield Australia Centre for Health Research University of Southern Queensland Australia

Background: Timely detection of neurodevelopmental and neurological conditions is crucial for early intervention. Specific Language Impairment (SLI) in children and Parkinson's disease (PD) manifests in speech disturbances that may be exploited for diagnostic screening using recorded speech signals. We were motivated to develop an accurate yet computationally lightweight model for speech-based detection of SLI and PD, employing novel feature engineering techniques to mimic the adaptable dynamic weight assignment network capability of deep learning architectures. Materials and methods: In this research, we have introduced an advanced feature engineering model incorporating a novel feature extraction function, the Factor Lattice Pattern (FLP), which is a quantum-inspired method and uses a superposition-like mechanism, making it dynamic in nature. The FLP encompasses eight distinct patterns, from which the most appropriate pattern was discerned based on the data structure. Through the implementation of the FLP, we automatically extracted signal-specific textural features. Additionally, we developed a new feature engineering model to assess the efficacy of the FLP. This model is self-organizing, producing nine potential results and subsequently choosing the optimal one. Our speech classification framework consists of (1) feature extraction using the proposed FLP and a statistical feature extractor;(2) feature selection employing iterative neighborhood component analysis and an intersection-based feature selector;(3) classification via support vector machine and k-nearest neighbors;and (4) outcome determination using combinational majority voting to select the most favorable results. Results: To validate the classification capabilities of our proposed feature engineering model, designed to automatically detect PD and SLI, we employed three speech datasets of PD and SLI patients. Our presented FLP-centric model achieved classification accuracy of more than 95% and 99.79%

关键词： Feature extraction

Pricing Strategy for Household Energy-Saving Option (Heso): A Novel Option-Based Intervention for Promoting Household Energy Efficiency

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SSRN

SSRN 2022年

作者： Xu, Qian Li, Shengping Shen, Liyin Chang, Ruidong Wang, Qian-Cheng Liu, Xuan Department of the Built Environment College of Design and Engineering National University of Singapore 4 Architecture Drive Singapore117566 Singapore Department of Infrastructure Engineering Faulty of Engineering and Information Technology The University of Melbourne VIC3010 Australia School of Spatial Planning and Design Zhejiang University City College Hangzhou China School of Management Science and Real Estate Chongqing University Chongqing China School of Architecture and Built Environment Faculty of Engineering Computer and Mathematical Sciences The University of Adelaide SA5005 Australia Department of Land Economy University of Cambridge CambridgeCB3 9EP United Kingdom Department of the Built Environment Eindhoven University of Technology Eindhoven5600MB Netherlands

Household energy-saving interventions are essential in reducing energy consumption in residential buildings. One of the effective interventions is Household Energy-Saving Option (HESO). However, the pricing strategy of this innovative intervention has not been explored. This study aims to establish a feasible valuation strategy for HESO to facilitate the application of market-based energy-saving interventions among households. This study first provides a pricing strategy of HESO from a market zero-profit perspective. It continues by developing a price cap and floor for HESO's market price. The theoretical pricing model was validated by a field experiment consisting of two-tiered HESO trading among 67 households in Singapore. The results revealed decisive implications for both environmental policymakers and HESO suppliers. Policymakers are suggested to launch HESO in countries or regions with stable and relatively high electricity prices and low discount rates. HESO suppliers may choose to adjust rewards and duration accordingly when the market price deviates from the zero-profit equilibrium price of HESO. The valuation strategy of HESO also helps quantitative estimation of households’ perceived value of HESO. © 2022, The Authors. All rights reserved.

关键词： Costs