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TMs-Induced Changes in Global brain Dynamics: Insights from EEG Microstate Analysis

brain stimulation 2025年第1期18卷 363-364页

作者： Kabir, Amin Dhami, Prabhjot Chatterjee, Raaj blumberger, Daniel M. Daskalakis, Zafiris J. Moreno, sylvain Farzan, Faranak Centre for Engineering-Led Brain Research School of Mechatronic Systems Engineering Simon Fraser University 250-13450 102 Avenue Surrey British Columbia V3T 0A3 Canada Temerty Centre for Therapeutic Brain Intervention Centre for Addiction and Mental Health 1001 Queen St. W Toronto Ontario M6J 1A8 Canada Institute of Medical Science Faculty of Medicine University of Toronto Medical Sciences Building 1 King's College Circle Toronto Ontario M5S 1A8 Canada Department of Psychiatry University of Toronto 250 College Street 8th floor Toronto Ontario M5T 1R8 Canada Department of Psychiatry University of California San Diego 9500 Gilman Dr La Jolla CA 92093 USA School of Interactive Arts and Technology Simon Fraser University 250-13450 102 Avenue Surrey BC V3T 0A3 Canada Circle Innovation 1200-555 W. Hastings Street Vancouver BC V6B 4N6 Canada

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Roadmapping the Next Generation of silicon Photonics

arXiv

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arXiv 2023年

作者： shekhar, sudip bogaerts, Wim Chrostowski, Lukas bowers, John E. Hochberg, Michael soref, Richard shastri, bhavin J. Department of Electrical & Computer Engineering University of British Columbia 2332 Main Mall VancouverBCV6T1Z4 Canada Department of Information Technology Ghent University IMEC Technologiepark-Zwijnaarde 126 Ghent9052 Belgium Department of Electrical & Computer Engineering University of California Santa Barbara Santa BarbaraCA93106 United States Luminous Computing 4750 Patrick Henry Drive Santa ClaraCA95054 United States College of Science and Mathematics University of Massachusetts Boston 100 William T. Morrissey Blvd. BostonMA02125 United States Department of Physics Engineering Physics & Astronomy Queen’s University 64 Bader Lane KingstonONK7L3N6 Canada

silicon photonics has developed into a mainstream technology driven by advances in optical communications. The current generation has led to a proliferation of integrated photonic devices from thousands to millions—mainly in the form of communication transceivers for data centers. Products in many exciting applications, such as sensing and computing, are around the corner. What will it take to increase the proliferation of silicon photonics from millions to billions of units shipped? What will the next generation of silicon photonics look like? What are the common threads in the integration and fabrication bottlenecks that silicon photonic applications face, and which emerging technologies can solve them? This perspective article is an attempt to answer such questions. We chart the generational trends in silicon photonics technology, drawing parallels from the generational definitions of CMOs technology. We identify the crucial challenges that must be solved to make giant strides in CMOs-foundry-compatible devices, circuits, integration, and packaging. We identify challenges critical to the next generation of systems and applications - in communication, signal processing, and sensing. by identifying and summarizing such challenges and opportunities, we aim to stimulate further research on devices, circuits, and systems for the silicon photonics ecosystem. Copyright © 2023, The Authors. All rights reserved.

关键词： silicon photonics

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Unifying femtosecond and picosecond single-pulse magnetic switching in Gd-Fe-Co

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Physical Review b 2021年第10期103卷 104422-104422页

作者： F. Jakobs T. A. Ostler C.-H. Lambert Y. Yang s. salahuddin R. b. Wilson J. Gorchon J. bokor U. Atxitia Dahlem Center for Complex Quantum Systems and Fachbereich Physik Freie Universität Berlin 14195 Berlin Germany Département de Physique Universitè de Liége (B5) B-4000 Liége Belgium College of Business Technology and Engineering Sheffield Hallam University Howard Street Sheffield S1 1WB United Kingdom Department of Electrical Engineering and Computer Sciences University of California Berkeley California 94720 USA Department of Materials Science and Engineering University of California Berkeley California 94720 USA Lawrence Berkeley National Laboratory 1 Cyclotron Road Berkeley California 94720 USA Department of Mechanical Engineering and Materials Science and Engineering Program University of California Riverside California 92521 USA

Many questions are still open regarding the physical mechanisms behind the magnetic switching in Gd-Fe-Co alloys by single optical pulses. Phenomenological models suggest a femtosecond scale exchange relaxation between sublattice magnetization as the driving mechanism for switching. The recent observation of thermally induced switching in Gd-Fe-Co by using both several picosecond optical laser pulse as well as electric current pulses has questioned this previous understanding. This has raised the question of whether or not the same switching mechanics are acting at the femtosecond and picosecond scales. In this work, we aim at filling this gap in the understanding of the switching mechanisms behind thermal single-pulse switching. To that end, we have studied experimentally thermal single-pulse switching in Gd-Fe-Co alloys, for a wide range of system parameters, such as composition, laser power, and pulse duration. We provide a quantitative description of the switching dynamics using atomistic spin dynamics methods with excellent agreement between the model and our experiments across a wide range of parameters and timescales, ranging from femtoseconds to picoseconds. Furthermore, we find distinct element-specific damping parameters as a key ingredient for switching with long picosecond pulses and argue that switching with pulse durations as long as 15 ps is possible due to a low damping constant of Gd. Our findings can be easily extended to speed up dynamics in other contexts where ferrimagnetic Gd-Fe-Co alloys have been already demonstrated to show fast and energy-efficient processes, e.g., domain-wall motion in a track and spin-orbit torque switching in spintronics devices.

关键词： Demagnetization Magnetic interactions Magnetic order Magnetism spin dynamics Ultrafast magnetic effects

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AlexNet-based deep convolutional neural network optimized with group teaching optimization algorithm (GTOA) for paediatric bone age assessment from hand X-ray images

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The Journal of Photographic science 2024年第3期72卷

作者： E. P. Hemand Mohandass G. Francis H. shajin D. Kirubakaran a Department of Computer science and Engineering NIT Calicut Kozhikode India b Department of Biomedical Engineering Agni College of Technology Chennai India c Research and Development Xpertmindz Innovative Solutions Private Limited Kuzhithurai Tamil Nadu India d Department of Electrical and Electronics Engineering St. Joseph's Institute of Technology Chennai India

AbsTRACTbone age assessment is used to diagnose paediatric growth because some types of bone diseases occur in childhood. To overcome these issues, AlexNet-based Deep Convolutional Neural Network Optimized with the Group Teaching Optimization Algorithm is proposed. First, input images are gathered via RsNA paediatric bone age dataset. These images are preprocessed using Wavelet Packet Transform Cochlear Filter bank. Then input hand X-ray images’ ROI is segmented using bayesian fuzzy clustering. Then segmented ROI region is fed to ADCNN that accurately predicts bAA. In general, ADCNN does not divulge any optimization techniques adopted for determining the optimal parameters and ensuring accurate classification. Therefore, the GTOA is used to optimize the ADCNN weight parameters. The proposed approach is done in MATLAb and various performance metrics such as accuracy, F-score, sensitivity, precision, specificity, CCC and CC. The bAA-ADCNN-GTOA method provides higher accuracy 23.75%, 17.97%, 31.65% compared with existing methods, like bAA-CNN-RRNN, bAA-RNN-AF-sFO, bAA-U-Net-CTO- WOA, respectively.

关键词： AlexNet-based deep convolutional neural network (ADCNN) bayesian fuzzy clustering bone age assessment group teaching optimization algorithm (GTOA) Wavelet Packet Transform Cochlear Filter bank region of Interest RsNA paediatric bone age dataset X-ray images

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Expression of Concern for: Deep Learning Model to Predict Pneumonia Disease based on Observed Patterns in Lung X-rays

Expression of Concern for: Deep Learning Model to Predict Pn...

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International conference of Electronics, Communication and Aerospace Technology (ICECA)

作者： Utkarsh singh Aditi Totla Dr. Prakash Kumar Dept. of Computer Science and Engineering R. V. College of Engineering Bengaluru Karnataka Dept. of Electronics and Electrical Engineering R. V. College of Engineering Bengaluru Karnataka Dept. of Production Engineering B. I. T. Sindri Dhanbad Jharkhand

ISBN: (数字)9781728163871

ISBN: (纸本)9781728163888

Due to the recent technological advancements, healthcare industry is also undergoing some major changes. The volume of medical data continues to increase at a staggering rate and artificial intelligence is poised to be the engine that drives improvements across the care continuum. Pneumonia is a serious disease, which can range from mild to life-threatening as it causes inflammation and fluid accumulation in the lungs and making it hard to breathe. It remains as the most serious for infants, children, and people older than 65 years. It is also considered to be a potential complication of the COvID-19 disease. Chest X-ray is an important pneumonia diagnosis worldwide. To help detect patients, who require intense medical care, artificial intelligence can be used to analyse lung imaging as a part of the clinical research study. The primary goal is to reduce the complex task of understanding scans through experts and provides easy prediction by developing a model that can predict the possibility of the disease in a patient through their lung X-ray images.

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Recent advances in nanomaterial-based drug delivery systems

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Nano-structures and Nano-Objects 2024年 37卷

作者： Jadhav, vikram Roy, Arpita Kaur, Kirtanjot Rai, Ashutosh Kumar Rustagi, sarvesh Department of Chemistry M.V.P. Samaj's K.K. Wagh Arts Science And Commerce College Pimpalgaon (B.) Maharashtra Nashik 422209 India Department of Biotechnology Sharda School of Engineering & Technology Sharda University Greater Noida India University Centre for Research & Development Department of Chemistry Chandigarh University Gharuan Punjab Mohali India Department of Biochemistry College of Medicine Imam Abdulrahman Bin Faisal University Dammam 31441 Saudi Arabia School of Applied and Life sciences Uttaranchal University Uttarakhand Dehradun India

Nanotechnology is crucial to the chemical, physical and medicinal fields. Nanotechnology necessitates an understanding of the atomic and molecular structures of materials, so their application may be assessed. Due to their unique morphology, nanomaterials can be used as drug delivery systems for safe and effective therapies, where drugs can be given productively with minimal adverse effects. Nanomaterial drug carriers facilitate the transfer of proteins, nucleic acids and small biological molecules. They may help encapsulate drugs and enable more particular targeting with the controlled release of the drugs. Interest in developing and refining drug delivery agents has been sparked by the complexity of some illnesses and the inherent toxicity of some drugs;synthetic nanomaterials are generally preferable due to their unique physicochemical characteristics, such as easy preparation methods, superior biocompatibility and storage stability. There are several drug delivery systems built on inorganic-based nanomaterials. Even though there are still many challenges to be solved, tremendous progress has been achieved recently. The review presented here focuses on the state and development of inorganic-based nanomaterials, such as carbon-based, silica-based and iron oxide, that may transport chemical and biological drug molecules. This article outlines the development of nanomaterials for drug delivery systems and information about the most recent products in drug delivery research and technology. © 2024 Elsevier b.v.

关键词： bioavailability Drug delivery systems Inorganic-based nanomaterials Nanocarriers

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Leveraging Dynamic Embeddings and Reinforcement Learning with bayesian Networks for Ransomware Resiliences

Cyber Security and Applications

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Cyber security and Applications 2025年

作者： sudhakar Kumar sunil K. singh saket sarin Chandra Kumari subba varsha Arya N. Nandhini brij b. Gupta Kwok Tai Chui Department of CSE Chandigarh College of Engineering and Technology Panjab University Chandigarh India Sikkim University India Hong Kong Metropolitan University (HKMU) Hong Kong China Department of Information Technology P. S. V College of Engineering and Technology Krishnagiri Tamilnadu India Department of Computer Science and Information Engineering Asia University Taichung 413 Taiwan China Hong Kong Metropolitan University (HKMU) Hong Kong

Ransomware has emerged as a formidable cybersecurity menace, targeting organizations and individuals with devastating consequences. This research paper delves into the multifaceted domain of ransomware resilience, investigating advancements in detection and mitigation strategies to combat realworld threats effectively. The study begins with a comprehensive literature review, shedding light on the evolving tactics of ransomware perpetrators and the limitations of traditional security measures. Drawing insights from diverse data sources, including incident reports and surveys, the research analyzes historical ransomware attacks, uncovering trends, attack vectors, and vulnerable sectors. In pursuit of improved detection capabilities, the paper explores cutting-edge approaches such as behavior-based analysis and machine learning algorithms. Deception methods and honeypots are investigated as additional layers of defense to divert attackers and minimize the impact of potential breaches.

关键词： Ransomware Cybersecurity Detection strategies Mitigation strategies behavior-based Analysis Honeypots

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Retraction Note to: Modified adaptive neuro fuzzy inference system based load balancing for virtual machine with security in cloud computing environment

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Journal of Ambient Intelligence and Humanized Computing 2022年第1期14卷 189-189页

作者： Durga Devi, T. J. b. subramani, A. Anitha, P. Department of Computer Applications K.S.R. College of Engineering Tiruchengode India Department of Computer Science M.V.Muthiah Government Arts College for Women Dindigul India

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study of thermal radiation and dissipation effects on MHD Prandtl hybrid nanofluid flow past an exponential stretched porous device

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Thermal science and engineering Progress 2025年 62卷

作者： Mane, Parshuram s. Patil, vishwambhar s. Patil, Amar b. Humane, Pooja P. Maharudrappa, Ishwar sankad, G.C. Department of Mathematics Shivaji University Kolhapur 416004 India Department of Mathematics Govt. College of Engineering Karad415124 India Department of Mathematics The New College Kolhapur416012 India Department of Mathematics School of Computer Science and Artificial Intelligence SR University Telangana Warangal506371 India Basaveshwar Engineering College Bagalkote587102 India Department of Mathematics BLDEA's V.P. Dr. P. G. Halakatti College of Engineering and Technology Vijayapur586103 India

Fluid dynamics requires a comprehensive understanding of energy dissipation, heat and mass transfer phenomena, since it directly impacts thermal efficiency, flow stability, and energy conservation in various industrial and engineering applications. With this motivation, the present study investigates the magnetized flow of Prandtl mixed hybrid nanofluids across an exponentially stretched surface. The hybrid nanofluid is formed with nanoparticles of Titanium oxide (TiO2) and Copper (Cu) in water as the base fluid. The governing set of equations is formulated as an extension of the Prandtl fluid model to investigate the physical effects of chemical processes, heat radiation, bioconvection, and energy dissipation. The nonlinear ordinary differential equations are derived after successfully implementing appropriate transformations on governing equations and are solved numerically via the Differential Transform Method (DTM). The graphical illustration of non-dimensional velocity, temperature, and concentration is obtained through MATLAb and discussed with proper physical justification for various terms such as magnetic parameter, chemical reaction, radiation parameter, sherwood number, Nusselt number, and friction parameter. The outcomes are validated with a comparison of previous published work. Results reveal that hybrid nanofluids significantly enhance heat transfer efficiency compared to conventional nanofluids. Increasing the Eckert and biot numbers raises temperature, while a stronger magnetic field reduces fluid velocity. Increasing magnetic parameter reduces velocity by 42 % (NF) and 37.5 % (HNF), while increasing Eckert number raises temperature by 67 % (NF) and 53 % (HNF), highlighting strong magnetic and viscous dissipation effects. The findings of this study have significant applications in oil extraction, heat exchanger optimization, and MHD propulsion systems, where energy dissipation and thermal radiation play a crucial role. © 2025 Elsevier Ltd

关键词： Magnetohydrodynamics

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synthesis and characterization of tritendate schiff base rare earth nano metal complexes

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Materials Today: Proceedings 2021年 34卷 453-459页

作者： A. Kavitha D. Easwaramoorthy T. Thangeeswari G. Parthipan s. shanmugan Thamean Ansari Department of Chemistry Vel Tech Multitech Dr. Rangarajan Dr. Sakunthala Engineering College Avadi Chennai Tamil Nadu 600 062 India Department of Chemistry B.S. Abdur Rahman University Vandalur Chennai 600 048 Tamil Nadu India Department of Physics Vel Tech Multitech Dr. Rangarajan Dr. Sakunthala Engineering College Avadi Chennai Tamil Nadu 600 062 India Department of Computer Science Engineering Vel Tech Multitech Dr. Rangarajan Dr. Sakunthala Engineering College Avadi Chennai Tamil Nadu 600 062 India

The tridentate schiff base ligand (1-pyridin-3-ylimino-ethyl benzene-1,3-diol were synthesized using precursor source 3-aminopyridine with 2,4-dihydroxyacetophenone in methanol at 60 °C. The prepared schiff base ligand doped with rare earth metal complex such as Ce(III), Pr(III) and Er (III) ion, respectively and it is denoted as [Ln(L)(NO 3 ) 2 (H 2 O)]·NO 3 . The schiff base ligand and nano metal complexes have been characterized by Uv–v.s.ble, FTIR, 1 H NMR, fluorescence spectrum (FL). Also the thermal properties of synthesized rare earth metal complexes were analysed by using TGA & DTA thermal analysis. These characterisation results given exact structural elucidation and optical properties of synthesized rare earth metal ions doped schiff base nano metal complex. In Uv spectra of the cerium, praseodymium and erbium nitrate complexes, there is no noticeable absorption in the v.s.ble region (380–700 nm) due to the shielding effect of rare earth 4f orbital electrons. FTIR spectra prove that the various functional groups present in doped schiff base metal complexes. The blue shift in the, fluorescence spectra of lanthanide (III) complex indicates that the doped lanthanum ions have an apparent influence on the energy absorption of the complex system through well co-ordination with ligand. The purity and molecular formulae of synthesized schiff base ligands and Ce(III), Pr(III) and Er (III) metal complexes were identified by H 1 NMR, C 13 NMR spectroscopy. Thermal analysis (TGA & DTA) concludes that synthesized rare earth metal complexes with schiff base ligand have adequate thermal stability.

关键词： schiff Nano Metal complexes Antimicrobial activity benzene-1 3-diol

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