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Imprints of a gravitational wave through the weak field deflection of photons

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Chinese Physics C 2024年第8期48卷 240-245页

作者： Reggie C.Pantig ali Övgün Physics Department Mapúa University658 Muralla St.IntramurosManila 1002Philippines Physics Department Eastern Mediterranean UniversityFamagusta99628 North Cyprusvia Mersin 10Turkiye

In this study,we investigate the novel phenomenon of gravitational lensing experienced by gravitational waves traveling past a Schwarzschild black hole perturbed by a specific,first-order,polar gravitational *** apply the Gauss-Bonnet theorem,finding a topological contribution to the deflection of light rays passing near the black *** demonstrate that the deflection angle can be determined by analyzing a region entirely outside the path of the light ray,leading to a calculation based solely on the parameters of the perturbing wave(Legendre polynomial order,l;frequency,σ).This approach offers a unique perspective on gravitational lensing and expands our understanding of black hole interactions with gravitational waves.

关键词： supermassive black holes gravitational waves chaos weak deflection angle Gauss-Bonnet theorem

Model Predictive Control based Motion Cueing Algorithm for Driving Simulator

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Journal of Systems Science and Systems Engineering 2024年第5期33卷 607-626页

作者： Ayesha Hameed ali Soltani Sharif Abadi Andrzej Ordys Institute of Automatic Control and Robotics Warsaw University of TechnologyWarsawPoland Institute of Electronic Systems Warsaw University of TechnologyWarsawPoland

Thanks to the emerging integration of algorithms and simulators, recent Driving Simulators (DS) find enormous potential in applications like advanced driver-assistance devices, analysis of driver’s behaviours, research and development of new vehicles and even for entertainment purposes. Driving simulators have been developed to reduce the cost of field studies, allow more flexible control over circumstances and measurements, and safely present hazardous conditions. The major challenge in a driving simulator is to reproduce realistic motions within hardware constraints. Motion Cueing Algorithm (MCA) guarantees a realistic motion perception in the simulator. However, the complex nature of the human perception system makes MCA implementation challenging. The present research aims to improve the performance of driving simulators by proposing and implementing the MCA algorithm as a control problem. The approach is realized using an actual vehicle model integrated with a detailed model of the human vestibular system, which accurately reproduces the driver’s perception. These perception motion signals are compared with simulated ones. A 2-DOF stabilized platform model is used to test the results from the two proposed control strategies, Proportional Integrator and Derivative (PID) and Model Predictive Control (MPC).

关键词： Driving simulator motion cueing algorithm control theory model predictive control PID

Elevating Image Steganography:A Fusion of MSB Matching and LSB Substitution for Enhanced Concealment Capabilities

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Computers, Materials & Continua 2024年第5期79卷 2923-2943页

作者： Muhammad Zaman ali Omer Riaz Hafiz Muhammad Hasnain Waqas Sharif Tenvir ali Gyu Sang Choi Department of Information Technology The Islamia University of BahawalpurBahawalpur63100Pakistan Department of Computer Science The Islamia University of BahawalpurBahawalpur63100Pakistan School of Computer Science and Engineering Yeungnam UniversityGyeongbuk38541Korea

In today’s rapidly evolving landscape of communication technologies,ensuring the secure delivery of sensitive data has become an essential *** overcome these difficulties,different steganography and data encryption methods have been proposed by researchers to secure *** of the proposed steganography techniques achieve higher embedding capacities without compromising visual imperceptibility using LSB *** this work,we have an approach that utilizes a combinationofMost SignificantBit(MSB)matching andLeast Significant Bit(LSB)*** proposed algorithm divides confidential messages into pairs of bits and connects them with the MSBs of individual pixels using pair matching,enabling the storage of 6 bits in one pixel by modifying a maximum of three *** proposed technique is evaluated using embedding capacity and Peak Signal-to-Noise Ratio(PSNR)score,we compared our work with the Zakariya scheme the results showed a significant increase in data concealment *** achieved results of ourwork showthat our algorithmdemonstrates an improvement in hiding capacity from11%to 22%for different data samples while maintaining a minimumPeak Signal-to-Noise Ratio(PSNR)of 37 *** findings highlight the effectiveness and trustworthiness of the proposed algorithm in securing the communication process and maintaining visual integrity.

关键词： Steganography most significant bit(MSB) least significant bit(LSB) peak signal-to-noise ratio(PSNR)

SnIP-type atomic-scale inorganic double-helix semiconductors: Synthesis, properties, and applications

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Nano Research 2024年第3期17卷 2111-2128页

作者： Mudussar ali Bowen Zhang Muhammad Khurram Qingfeng Yan Engineering Research Center of Advanced Rare Earth Materials(Ministry of Education) Department of ChemistryTsinghua UniversityBeijing 100084China

Flexible inorganic double helical semiconductors similar to DNA have fueled the demand for efficient materials with innovative structures and excellent *** recent discovery of tin phosphide iodide(SnIP),the first carbon-free double helical semiconductor at an atomic level,has opened new avenues of research for semiconducting devices such as thermoelectric and sensor devices,solar cells,and *** has drawn significant academic attention due to its high structural flexibility,band gap in the visible spectrum range,and non-toxic ***,the recent progress in developing SnIP,including its prestigious structure,versatile and intriguing properties,and synthesis,is *** analogues of SnIP and SnIP-based hybrid materials and their applications in photocatalysis are also ***,the review concludes with a critical summary and future aspects of this new inorganic semiconductor.

关键词： tin phosphide iodide(SnIP) inorganic semiconductor inorganic double helix SnIP-based hybrids photocatalysis flexible material

A numerical model to simulate the transient frictional viscoelastic sliding contact

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Friction 2024年第2期12卷 319-339页

作者： Dongze WANG Gregory de BOER Anne NEVILLE ali GHANBARZADEH School of Mechanical Engineering University of LeedsLeeds LS29JTUK

Sliding motion has always been one of the major concerns when it comes to the analysis of viscoelastic contact problems.A new model simulating the transient sliding contact of smooth viscoelastic surfaces is developed in this *** taking the dry contact friction and the coupling between shear tractions and normal pressure into account,the effect of the early partial slip period,which is often neglected in the study of viscoelastic sliding contact problems,is investigated *** with solutions based on the frictionless assumption,the steady-state pressure profile is found to be slightly different under the effect of the partial slip regime,including a lower peak pressure and the shift of the contacting region in the direction opposite to the sliding ***,the time required for the viscoelastic contact to reach its steady state is delayed owing to the partial slip period preceding the global sliding motion.

关键词： contact mechanics frictional sliding viscoelasticity viscoelastic friction

An Improved Binary Quantum-based Avian Navigation Optimizer Algorithm to Select Effective Feature Subset from Medical Data:A COVID-19 Case Study

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Journal of Bionic Engineering 2024年第1期21卷 426-446页

作者： ali Fatahi Mohammad H.Nadimi-Shahraki Hoda Zamani Faculty of Computer Engineering Najafabad BranchIslamic Azad UniversityNajafabad ***Iran Big Data Research Center Najafabad BranchIslamic Azad UniversityNajafabad ***Iran

Feature Subset Selection(FSS)is an NP-hard problem to remove redundant and irrelevant features particularly from medical data,and it can be effectively addressed by metaheuristic ***,existing binary versions of metaheuristic algorithms have issues with convergence and lack an effective binarization method,resulting in suboptimal solutions that hinder diagnosis and prediction *** paper aims to propose an Improved Binary Quantum-based Avian Navigation Optimizer Algorithm(IBQANA)for FSS in medical data preprocessing to address the suboptimal solutions arising from binary versions of metaheuristic *** proposed IBQANA’s contributions include the Hybrid Binary Operator(HBO)and the Distance-based Binary Search Strategy(DBSS).HBO is designed to convert continuous values into binary solutions,even for values outside the[0,1]range,ensuring accurate binary *** the other hand,DBSS is a two-phase search strategy that enhances the performance of inferior search agents and accelerates *** combining exploration and exploitation phases based on an adaptive probability function,DBSS effectively avoids local *** effectiveness of applying HBO is compared with five transfer function families and thresholding on 12 medical datasets,with feature numbers ranging from 8 to 10,***'s effectiveness is evaluated regarding the accuracy,fitness,and selected features and compared with seven binary metaheuristic ***,IBQANA is utilized to detect *** results reveal that the proposed IBQANA outperforms all comparative algorithms on COVID-19 and 11 other medical *** proposed method presents a promising solution to the FSS problem in medical data preprocessing.

关键词： Feature subset selection Optimization Binary metaheuristic algorithms Bioinspired Machine learning Medical datasets

Analysis of cohesive particles mixing behavior in a twin-paddle blender:DEM and machine learning applications

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Particuology 2024年第7期90卷 350-363页

作者： Behrooz Jadidi Mohammadreza Ebrahimi Farhad Ein-Mozaffari ali Lohi Department of Chemical Engineering Toronto Metropolitan University350 Victoria StreetToronto M5B 2K3Canada

This research paper presents a comprehensive discrete element method(DEM)examination of the mixing behaviors exhibited by cohesive particles within a twin-paddle blender.A comparative analysis between the simulation and experimental results revealed a relative error of 3.47%,demonstrating a strong agreement between the results from the experimental tests and the DEM *** main focus centers on systematically exploring how operational parameters,such as impeller rotational speed,blender's fill level,and particle mass ratio,influence the *** investigation also illustrates the significant influence of the mixing time on the mixing *** gain a deeper understanding of the DEM simulation findings,an analytical tool called multivariate polynomial regression in machine learning is *** method uncovers significant connections between the DEM results and the operational parameters,providing a more comprehensive insight into their *** multivariate polynomial regression model exhibited robust predictive performance,with a mean absolute percentage error of less than 3%for both the training and validation sets,indicating a slight deviation from actual *** model's precision was confirmed by low mean absolute error values of 0.0144(80%of the dataset in the training set)and 0.0183(20%of the dataset in the validation set).The study offers valuable insights into granular mixing behaviors,with implications for enhancing the efficiency and predictability of the mixing processes in various industrial applications.

关键词： Machine learning Granular mixing Discrete element method Mixing kinetics and mechanism Cohesive particles

Accelerated Particle Swarm Optimization Algorithm for Efficient Cluster Head Selection in WSN

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Computers, Materials & Continua 2024年第6期79卷 3585-3629页

作者： Imtiaz Ahmad Tariq Hussain Babar Shah Altaf Hussain Iqtidar ali Farman ali Institute of Computer Sciences and Information Technology The University of AgriculturePeshawarPakistan School of Computer Science and Technology Zhejiang Gongshang UniversityHangzhouChina College of Technological Innovation Zayed UniversityDubaiUnited Arab Emirates School of Computer Science and Technology Chongqing University of Posts and TelecommunicationsChongqing400065China Department of Applied AI School of ConvergenceCollege of Computing and InformaticsSungkyunkwan UniversitySeoul03063South Korea

Numerous wireless networks have emerged that can be used for short communication ranges where the infrastructure-based networks may fail because of their installation and *** of them is a sensor network with embedded sensors working as the primary nodes,termed Wireless Sensor Networks(WSNs),in which numerous sensors are connected to at least one Base Station(BS).These sensors gather information from the environment and transmit it to a BS or gathering *** have several challenges,including throughput,energy usage,and network lifetime *** strategies have been applied to get over these *** may,therefore,be thought of as the best way to solve such ***,it is crucial to analyze effective Cluster Head(CH)selection to maximize efficiency throughput,extend the network lifetime,and minimize energy *** paper proposed an Accelerated Particle Swarm Optimization(APSO)algorithm based on the Low Energy Adaptive Clustering Hierarchy(LEACH),Neighboring Based Energy Efficient Routing(NBEER),Cooperative Energy Efficient Routing(CEER),and Cooperative Relay Neighboring Based Energy Efficient Routing(CR-NBEER)*** the help of APSO in the implementation of the WSN,the main methodology of this article has taken *** simulation findings in this study demonstrated that the suggested approach uses less energy,with respective energy consumption ranges of 0.1441 to 0.013 for 5 CH,1.003 to 0.0521 for 10 CH,and 0.1734 to 0.0911 for 15 *** sending packets ratio was also raised for all three CH selection scenarios,increasing from 659 to *** number of dead nodes likewise dropped for the given combination,falling between 71 and *** network lifetime was deemed to have risen based on the results found.A hybrid with a few valuable parameters can further improve the suggested APSO-based *** to underwater,WSN can make use of the proposed *** overall results have been evaluated and

关键词： Wireless sensor network cluster head selection low energy adaptive clustering hierarchy accelerated particle swarm optimization

Metabolic complications of psychotropic medications in psychiatric disorders:Emerging role of de novo lipogenesis and therapeutic consideration

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World Journal of Psychiatry 2024年第6期14卷 767-783页

作者： Mohammad M Khan Zaw ali Khan Mohsin ali Khan Laboratory of Translational Neurology and Molecular Psychiatry Department of BiotechnologyEra’s Lucknow Medical College and Hospitaland Faculty of ScienceEra UniversityLucknow 226003India Era’s Lucknow Medical College and Hospital Era UniversityLucknow 226003India

Although significant advances have been made in understanding the pathophysiology of psychiatric disorders(PDs),therapeutic advances have not been very *** psychotropic medications can reduce classical symptoms in patients with PDs,their long-term use has been reported to induce or exaggerate various pre-existing metabolic abnormalities including diabetes,obesity and non-alcoholic fatty liver disease(NAFLD).The mechanism(s)underlying these metabolic abnormalities is not clear;however,lipid/fatty acid accumulation due to enhanced de novo lipogenesis(DNL)has been shown to reduce membrane fluidity,increase oxidative stress and inflammation leading to the development of the aforementioned metabolic ***,emerging evidence suggest that DNL dysregulation and fatty acid accumulation could be the major mechanisms associated with the development of obesity,diabetes and NAFLD after long-term treatment with psychotropic medications in patients with *** support of this,several adjunctive drugs comprising of anti-oxidants and antiinflammatory agents,that are used in treating PDs in combination with psychotropic medications,have been shown to reduce insulin resistance and development of *** conclusion,the above evidence suggests that DNL could be a potential pathological factor associated with various metabolic abnormalities,and a new avenue for translational research and therapeutic drug designing in PDs.

关键词： Psychotropic medications Metabolic complications De novo lipogenesis Obesity Diabetes Non-alcoholic fatty liver disease