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Electrical Charge Polarization Induced by Alternating Temperature Gradient to Promote Z-Scheme Photocatalytic Hydrogen Evolution and Imine Production

SSRN

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SSRN 2024年

作者： He, Zuming Yi, Jun Wong, Ngie Hing Sunarso, Jaka Xia, Yongmei Fu, Xiaofei Huang, Zhengyi Chen, Guihua Yang, Hanpei Zhou, Wei School of Microelectronics and Control Engineering Changzhou University Changzhou213164 China Huaide School Changzhou University Jingjiang214500 China Research Centre for Sustainable Technologies Faculty of Engineering Computing and Science Swinburne University of Technology Jalan Simpang Tiga Sarawak Kuching93350 Malaysia School of Materials and Engineering Jiangsu University of Technology Changzhou213001 China School of Pharmaceutical and Chemical Engineering Taizhou University Jiaojiang318000 China Key Laboratory of Integrated Regulation and Resource Development on Shallow Lakes Ministry of Education College of Environment Hohai University Nanjing210098 China Shandong Provincial Key Laboratory of Molecular Engineering School of Chemistry and Chemical Engineering Qilu University of Technology Shandong Academy of Sciences Jinan250353 China

Here, reported photothermal-pyroelectric-Fe0.9Ni0.1S2/ZnSnO3 photocatalytic system via hydrothermal and annealing methods. Fe0.9Ni0.1S2 nanoparticles (NPs) could convert most of near-infrared (NIR) light energy into heat energy to drive the pyroelectric effect of ZnSnO3, causing natural polarization and thermoelectric effects under the condensed water circulation. As a result, the as-designed Fe0.9Ni0.1S2/ZnSnO3-2 composites could yield up to 7.194 mmol g-1 h-1) with exceptional photocatalytic performance under simulated sunlight. This result was 5.41 and 4.92-fold those of Fe0.9Ni0.1S2 and ZnSnO3, respectively, with 16.66% apparent quantum yield under 365 nm monochromatic light. At the same time, the composites could also oxidize BA and yield up to 6.640 mmol g-1 h-1) n-benzylidene benzylamine with a 90.2% selectivity. Due to the synergistic effect of Z-scheme's built-in electric field and photothermal-pyroelectric of Fe0.9Ni0.1S2/ZnSnO3, the surface charges released on them could direct the charge transfer pathways and restrain their recombination with accelerated electron transfer kinetics, thus extending the carrier lifetime. © 2024, The Authors. All rights reserved.

关键词： Thermal gradients

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USLR: an open-source tool for unbiased and smooth longitudinal registration of brain MRI

arXiv

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arXiv 2023年

作者： Casamitjana, Adrià Sala-Llonch, Roser Lekadir, Karim Iglesias, Juan Eugenio Universitat Politècnica de Catalunya Barcelona08034 Spain Institut de Neurociències Department of Biomedicine Faculty of Medicine University of Barcelona Barcelona08036 Spain Barcelona08036 Spain Barcelona08036 Spain Barcelona Spain Martinos Center for Biomedical Imaging Massachusetts General Hospital Harvard Medical School United States Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology United States Centre for Medical Image Computing University College London United Kingdom

We present USLR, a computational framework for longitudinal registration of brain MRI scans to estimate nonlinear image trajectories that are smooth across time, unbiased to any timepoint, and robust to imaging artefacts. It operates on the Lie algebra parameterisation of spatial transforms (which is compatible with rigid transforms and stationary velocity fields for nonlinear deformation) and takes advantage of log-domain properties to solve the problem using Bayesian inference. USRL estimates rigid and nonlinear registrations that: (i) bring all timepoints to an unbiased subject-specific space;and (ii) compute a smooth trajectory across the imaging time-series. We capitalise on learning-based registration algorithms and closed-form expressions for fast inference. A use-case Alzheimer’s disease study is used to showcase the benefits of the pipeline in multiple fronts, such as time-consistent image segmentation to reduce intra-subject variability, subject-specific prediction or population analysis using tensor-based morphometry. We demonstrate that such approach improves upon cross-sectional methods in identifying group differences, which can be helpful in detecting more subtle atrophy levels or in reducing sample sizes in clinical trials. The code is publicly available in https://***/acasamitjana/uslr © 2023, CC BY.

关键词： Image segmentation

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The EMPOWER blended digital intervention for relapse prevention in schizophrenia: a feasibility cluster randomised controlled trial in Scotland and Australia

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The Lancet Psychiatry 2022年第6期9卷 477-486页

作者： Gumley, Andrew I Bradstreet, Simon Ainsworth, John Allan, Stephanie Alvarez-Jimenez, Mario Aucott, Lorna Birchwood, Maximillian Briggs, Andrew Bucci, Sandra Cotton, Sue M Engel, Lidia French, Paul Lederman, Reeva Lewis, Shôn Machin, Matthew MacLennan, Graeme McLeod, Hamish McMeekin, Nicola Mihalopoulos, Cathy Morton, Emma Norrie, John Schwannauer, Matthias Singh, Swaran P Sundram, Suresh Thompson, Andrew Williams, Chris Yung, Alison R Farhall, John Gleeson, John Glasgow Institute of Health and Wellbeing University of Glasgow Glasgow United Kingdom Division of Psychology and Mental Health School of Health Sciences Faculty of Biology Medicine and Health Manchester Academic Health Science Centre University of Manchester Manchester United Kingdom Division of Informatics Imaging and Data Sciences School of Health Sciences Faculty of Biology Medicine and Health Manchester Academic Health Science Centre University of Manchester Manchester United Kingdom Orygen Melbourne Melbourne VIC Australia Centre for Youth Mental Health University of Melbourne Melbourne VIC Australia School of Computing and Information Systems Faculty of Engineering and Information Technology University of Melbourne Melbourne VIC Australia Centre for Healthcare Randomised Trials (CHaRT) University of Aberdeen Aberdeen United Kingdom Centre for Mental Health and Wellbeing Research Warwick Medical School University of Warwick Warwick United Kingdom Department of Health Services Research and Policy London School of Hygiene & Tropical Medicine London United Kingdom Greater Manchester Mental Health NHS Foundation Trust Manchester United Kingdom School of Public Health and Preventive Medicine Monash University Melbourne VIC Australia Department of Psychiatry School of Clinical Sciences Monash University Melbourne VIC Australia School of Medicine Deakin University Melbourne VIC Australia Department of Psychiatry Manchester Metropolitan University Manchester United Kingdom Department of Psychiatry University of British Columbia Vancouver BC Canada The Usher Institute University of Edinburgh Edinburgh United Kingdom School for Health in Social Sciences University of Edinburgh Edinburgh United Kingdom Mental Health Program Monash Health Melbourne VIC Australia Department of Psychology and Counselling La Trobe University Melbourne VIC Australia NorthWestern Mental Health The Royal Melbourne Hospital Epping VIC Australia Healthy Brain and Mi

Background: Early warning signs monitoring by service users with schizophrenia has shown promise in preventing relapse but the quality of evidence is low. We aimed to establish the feasibility of undertaking a definitive randomised controlled trial to determine the effectiveness of a blended digital intervention for relapse prevention in schizophrenia. Methods: This multicentre, feasibility, cluster randomised controlled trial aimed to compare Early signs Monitoring to Prevent relapse in psychosis and prOmote Well-being, Engagement, and Recovery (EMPOWER) with treatment as usual in community mental health services (CMHS) in Glasgow and Melbourne. CMHS were the unit of randomisation, selected on the basis of those that probably had five or more care coordinators willing to participate. Participants were eligible if they were older than 16 years, had a schizophrenia or related diagnosis confirmed via case records, were able to provide informed consent, had contact with CMHS, and had had a relapse within the previous 2 years. Participants were randomised within stratified clusters to EMPOWER or to continue their usual approach to care. EMPOWER blended a smartphone for active monitoring of early warning signs with peer support to promote self-management and clinical triage to promote access to relapse prevention. Main outcomes were feasibility, acceptability, usability, and safety, which was assessed through face-to-face interviews. App usage was assessed via the smartphone and self-report. Primary end point was 12 months. Participants, research assistants and other team members involved in delivering the intervention were not masked to treatment conditions. Assessment of relapse was done by an independent adjudication panel masked to randomisation group. The study is registered at ISRCTN (99559262). Findings: We identified and randomised eight CMHS (six in Glasgow and two in Melbourne) comprising 47 care coordinators. We recruited 86 service users between Jan 19 and Au

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ICRRM 2019 – System Reliability, Quality Control, Safety, Maintenance and Management 1

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2020年

作者： Vinit Kumar Gunjan Sri Niwas Singh Tran Duc-Tan Gloria Jeanette Rincon Aponte Amit Kumar

ISBN: (数字)9789811385070

ISBN: (纸本)9789811385063

Content of this proceedings discusses emerging trends in structural reliability, safety and disaster management, covering topics like total quality management, risk maintenance and design for reliability. Some papers also address chemical process reliability, reliability analysis and engineering applications in chemical process equipment systems and includes a chapter on reliability evaluation models of chemical systems. Accepted papers from 2019 International Conference on Reliability, Risk Maintenance and Engineering Management (ICRRM 2019) are part of this conference proceeding. It offers useful insights to road safety engineers, disaster management professionals involved in product design and probabilistic methods in manufacturing systems.

关键词： Security science and technology Building Repair and Maintenance Industrial Chemistry Operations Research, Management science

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Design of photonic crystal fiber for thermal sensing applications using thermo-optical liquids

Design of photonic crystal fiber for thermal sensing applica...

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2020 Frontiers in Optics Conference, FiO 2020

作者： Qiao, Dun Guang, Zhe Zhang, Yani Xue, Lu Wireless and Optoelectronics Research and Innovation Centre Faculty of Computing Engineering and Science University of South Wales PontypriddCF37 1DL United Kingdom School of Physics Georgia Institute of Technology 837 State Street AtlantaGA30332 United States School of Arts and Sciences Shaanxi University of Science& Technology Xi'anShaanxi710021 China School of Physics and Optoelectronics Technology Baoji University of Arts and Science BaojiShaanxi721016 China

A temperature sensor based on photonic crystal fiber was designed with infiltrated thermo-optical liquids. Propagation properties with respect to temperature were simulated by the full vectorial-finite element method ... 详细信息

ISBN: (纸本)9781943580804

关键词： Photonic crystal fibers

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An overview of uni- and multi-biometric identification of identical twins

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IEIE Transactions on Smart Processing and computing 2019年第1期8卷 71-84页

作者： Mohammed, Bayan Omar Shamsuddin, Siti Mariyam Hasan, Shafaatunnur UTM Big Data Centre IbnuSina Institute for Scientific and Industrial Research UniversitiTeknologi Malaysia Johor Malaysia Faculty of Computing UniversitiTeknologi Malaysia Johor Malaysia College of Science and Technology University of Human Development Sulaymaniyah Iraq

Biometric techniques can differentiate identical twins, and this makes the techniques a subject of interest. Studies on biometric techniques have been conducted in many disciplines. Unimodal biometric systems with twins, however, have issues including intra-class variations, noisy data, limited freedom levels, non-universality, vulnerability to spoof attacks, and intolerable rates of error. Several of these limitations are manageable through the use of multimodal biometric systems that combine the evidence brought by many sources of information. This survey highlights the relevant literature, the accessible datasets for research, and the subjects of uncertainty, and proposes future research. Copyrights © 2019 The Institute of Electronics and Information Engineers.

关键词： Biometrics

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Short-Term and Long-Term Context Aggregation Network for Video Inpainting 16th

Short-Term and Long-Term Context Aggregation Network for Vid...

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16th European Conference on Computer Vision, ECCV 2020

作者： Li, Ang Zhao, Shanshan Ma, Xingjun Gong, Mingming Qi, Jianzhong Zhang, Rui Tao, Dacheng Kotagiri, Ramamohanarao School of Computing and Information Systems The University of Melbourne Melbourne Australia UBTECH Sydney AI Centre School of Computer Science Faculty of Engineering The University of Sydney Darlington2008 Australia School of Information Technology Deakin University Geelong Australia School of Mathematics and Statistics The University of Melbourne Melbourne Australia

ISBN: (纸本)9783030585471

Video inpainting aims to restore missing regions of a video and has many applications such as video editing and object removal. However, existing methods either suffer from inaccurate short-term context aggregation or rarely explore long-term frame information. In this work, we present a novel context aggregation network to effectively exploit both short-term and long-term frame information for video inpainting. In the encoding stage, we propose boundary-aware short-term context aggregation, which aligns and aggregates, from neighbor frames, local regions that are closely related to the boundary context of missing regions into the target frame (The target frame refers to the current input frame under inpainting.). Furthermore, we propose dynamic long-term context aggregation to globally refine the feature map generated in the encoding stage using long-term frame features, which are dynamically updated throughout the inpainting process. Experiments show that it outperforms state-of-the-art methods with better inpainting results and fast inpainting speed. © 2020, Springer Nature Switzerland AG.

关键词： Encoding (symbols)

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Magnetoencephalography Brain Spectral Biomarkers of Alzheimer's Disease: A Promising Approach Demonstrated with the BioFIND Dataset

Magnetoencephalography Brain Spectral Biomarkers of Alzheime...

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IEEE EMBS Conference on Biomedical Engineering and sciences (IECBES)

作者： Alwani Liyana Ahmad Zamzuri Idris Ibrahima Faye Jose Sanchez-Bornot Roberto C. Sotero Damien Coyle Department of Fundamental and Applied Sciences Faculty of Science and Information Technology Universiti Teknologi PETRONAS Perak Malaysia Department of Neurosciences Hospital Universiti Sains Malaysia Kelantan Malaysia Brain and Behaviour Cluster School of Medical Sciences Universiti Sains Malaysia Kelantan Malaysia Department of Neurosciences School of Medical Sciences Universiti Sains Malaysia Kelantan Malaysia Centre for Intelligent Signal & Imaging Research (CISIR) Universiti Teknologi PETRONAS Perak Malaysia Intelligent Systems Research Centre School of Computing Engineering and Intelligent Systems Ulster University Derry~Londonderry UK Department of Radiology and Hotchkiss Brain Institute University of Calgary Calgary AB Canada The Bath Institute for the Augmented Human University of Bath Bath UK

ISBN: (数字)9798350383409

ISBN: (纸本)9798350383416

Introduction: Magnetoencephalography (MEG) is widely used to study neurodegenerative diseases, particularly Alzheimer's disease (AD). MEG is valuable for examining functional changes in the AD brain due to its non-invasive nature and excellent spatial and temporal resolution. AD is characterized by amyloid-beta and tau protein formation, which disrupts brain networks and leads to memory and cognitive impairments. Objective: This study aimed to evaluate power spectra analysis of brain activity using various source localization methods and machine learning (ML) classification analysis based on GLMNET and correlation thresholds to identify MEG-based features that improve differentiation between healthy controls (HC) and mild cognitive impairment (MCI). Methods: We used the BioFIND dataset, including MEG data from 324 participants (158 MCI, 166 HC). MEG data were analyzed using custom MATLAB scripts with SPM12 and OSL toolboxes. Source localization methods included Bayesian LORETA (COH), Multiple Sparse Priors (MSP), Empirical Bayesian Beamformer (EBB), exact Low-Resolution Tomography Analysis (eLORETA), and Linearly Constrained Minimum Variance (LCMV). Sensor-based analyses were also conducted. Logistic Regression with L1 penalty (GLMNET) was applied in both sensor and source spaces, with different correlation thresholds for magnetometer (MAG) and gradiometer (GRAD) signals separately. We used 20 Monte Carlo iterations with 10-fold nested cross-validation to assess classifier performance. Results: Optimal performance was achieved using the LCMV method on GRAD sensors with a 0.1 correlation threshold, resulting in 74.57% accuracy, 71.55% sensitivity, and a 73.29% F1 score. Conclusions: This study demonstrates the potential of MEG as a robust tool for distinguishing between individuals with MCI and HC. By evaluating various source localization methods and correlation thresholds, we identified that the LCMV beamformer applied to GRAD signals with a 0.1 correlation thresho

关键词： Location awareness Brain Correlation Monte Carlo methods Magnetoencephalography Tomography Bayes methods Alzheimer's disease Spatial resolution Spectral analysis

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Artificial intelligent approach for flow stability in Eyring Powell hybrid nanofluids via porous shrinking sheets

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Journal of Molecular Liquids 2025年 422卷

作者： Fatima, Nahid Kouki, Marouan Khan, Muhammad Imran Amjad, Arslan Bin Asghar, Zaheer Zeeshan, Ahmad Ijaz, Nouman Department of Mathematics and Sciences Prince Sultan University Riyadh11586 Saudi Arabia Department of Information System Faculty of Computing and Information Technology Northern Border University Rafha Saudi Arabia Department of Mathematics and Statistics International Islamic University Islamabad 44000 Pakistan Centre for Mathematical Sciences Pakistan Institute of Engineering and Applied Sciences Nilore Islamabad45650 Pakistan Department of Physics and Applied Mathematics Pakistan Institute of Engineering and Applied Sciences Nilore Islamabad45650 Pakistan Department of Mathematics College of Science Korea University 145 Anam-ro Seongbuk-gu Seoul02841 Korea Republic of Department of Mathematics and Statistics Punjab Group of Colleges G.T. Road Jada Jhelum49600 Pakistan

This study aims to analyze flow stability using a computational intelligence technique that integrates a Levenberg-Marquardt approach utilizing artificial intelligence implemented through a backpropagation neural network. AI-based LMS-BPNN approach is utilized to examine the flow behavior of Eyring Powell hybrid nanofluid over a porous shrinking sheet. By applying skillful transformations, a set of ordinary differential equations is obtained from the partial differential equations that describe the hybrid nanofluid. Scenarios 1–5 illustrate how the built-in MATLAB function, bvp4c, solves ordinary differential equations systems by carefully modifying input parameters to get the initial or reference solution. The numerical data was split into three groups: 10 % for testing, 10 % for validation, and 80 % for training. The LMS-BPNN was used to find approximate solutions for these scenarios. To verify the effectiveness and reliability of LMS-BPNN, we employed regression analysis, error metrics, and correlation index (R)-based fitness curves. In each scenario, the temperature and velocity profiles gradually approached the boundary conditions as expected. The flow performance outcomes for the dual solution (Cfx and Nux) are also analyzed using the LMS-BPNN method. The perturbation scheme is applied to the boundary layer problem to obtain the eigenvalues problem. The unsteady solution f(η,τ) converges to steady solution fo(η) for τ→∞ when γ≥0. However, an unsteady solution f(η,τ) diverges to a steady solution fo(η) for τ→∞ when γ © 2025 Elsevier B.V.

关键词： Eigenvalues and eigenfunctions

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A New 4-D Multi-Stable Hyperchaotic Two-Scroll System with No-Equilibrium and its Hyperchaos Synchronization 2

A New 4-D Multi-Stable Hyperchaotic Two-Scroll System with N...

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2nd International Conference on Computer, science, Engineering, and technology, ICComSET 2019

作者： Vaidyanathan, S. Lien, C.-H. Fuadi, W. Mujiarto Mamat, M. Subiyanto Research and Development Centre Vel Tech University Avadi Chennai India Department of Marine Engineering National Kaohsiung University of Science and Technology Kaohsiung811 Taiwan Department of Informatic Universitas Malikussaleh Aceh Utara Indonesia Department of Mechanical Engineering Universitas Muhammadiyah Tasikmalaya Indonesia Faculty of Informatics and Computing Universiti Sultan Zainal Abidin Kuala Terengganu Malaysia Department of Marine Science Faculty of Fishery and Marine Science Universitas Padjadjaran Indonesia

A new 4-D multi-stable hyperchaotic two-scroll system with four quadratic nonlinearities is proposed in this paper. The dynamical properties of the new hyperchaotic system are described in terms of finding equilibrium points, phase portraits, Lyapunov exponents, Kaplan-Yorke dimension, dissipativity, etc. We discover that the new hyperchaotic system has no equilibrium point and hence it exhibits a hidden attractor. Furthermore, we show that the new hyperchaos system has multi-stability by the coexistence of hyperchaotic attractors for different values of initial conditions. As a control application, we use integral sliding mode control (ISMC) to derive new results for the hyperchaos synchronization of the new 4-D multi-stable hyperchaotic two-scroll system with hidden attractor. © Published under licence by IOP Publishing Ltd.

关键词： Sliding mode control

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