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Hybrid Gene selection Methods for High-Dimensional Lung Cancer Data Using Improved Arithmetic Optimization Algorithm

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Computers, Materials & Continua 2024年第6期79卷 5175-5200页

作者： Mutasem k.Alsmadi Department of Management Information systems College of Applied Studies and Community ServiceImam Abdulrahman Bin Faisal UniversityDammamSaudi Arabia

Lung cancer is among the most frequent cancers in the world,with over one million deaths per *** is required for lung cancer diagnosis and therapy to be effective,accurate,and *** expression microarrays have made it possible to find genetic biomarkers for cancer diagnosis and prediction in a high-throughput *** Learning(ML)has been widely used to diagnose and classify lung cancer where the performance of ML methods is evaluated to identify the appropriate *** and selecting the gene expression patterns can help in lung cancer diagnoses and ***,microarrays include several genes and may cause confusion or false ***,the Arithmetic Optimization Algorithm(AOA)is used to identify the optimal gene subset to reduce the number of selected *** can allow the classifiers to yield the best performance for lung cancer *** addition,we proposed a modified version of AOA which can work effectively on the high dimensional *** the modified AOA,the features are ranked by their weights and are used to initialize the AOA *** exploitation process of AOA is then enhanced by developing a local search algorithm based on two neighborhood ***,the efficiency of the proposed methods was evaluated on gene expression datasets related to Lung cancer using stratified 4-fold *** method’s efficacy in selecting the optimal gene subset is underscored by its ability to maintain feature proportions between 10%to 25%.Moreover,the approach significantly enhances lung cancer prediction *** instance,Lung_Harvard1 achieved an accuracy of 97.5%,Lung_Harvard2 and Lung_Michigan datasets both achieved 100%,Lung_Adenocarcinoma obtained an accuracy of 88.2%,and Lung_Ontario achieved an accuracy of 87.5%.In conclusion,the results indicate the potential promise of the proposed modified AOA approach in classifying microarray cancer data.

关键词： Lung cancer gene selection improved arithmetic optimization algorithm and machine learning

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Ren-integrable and ren-symmetric integrable systems

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Communications in Theoretical Physics 2024年第3期76卷 62-69页

作者： s Y Lou school of Physical science and Technology Ningbo UniversityNingbo315211China

A new type of symmetry,ren-symmetry,describing anyon physics and corresponding topological physics,is ***-symmetry is a generalization of super-symmetry which is widely applied in super-symmetric physics such as super-symmetric quantum mechanics,super-symmetric gravity,super-symmetric string theory,super-symmetric integrable systems and so *** and Grassmann numbers are,in some sense,dual conceptions,and it turns out that these conceptions coincide for the ren situation,that is,a similar conception of ren-number(R-number)is devised for *** particular,some basic results of the R-number and ren-symmetry are exposed which allow one to derive,in principle,some new types of integrable systems including ren-integrable models and ren-symmetric integrable *** examples of ren-integrable kdV-type systems and ren-symmetric kdV equations are explicitly given.

关键词： symmetries integrable systems anyon physics extended supersymmetry ren-symmetry

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Continuous Lithium-Ion Extraction From seawater and Mine Water With a Fuel Cell system and Ceramic Membranes

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Energy & Environmental Materials 2024年第6期7卷 254-261页

作者： Cansu kök Lei Wang Jean Gustavo A.Ruthes Antje Quade Matthew E.suss Volker Presser INM–Leibniz Institute for New Materials Campus D2266123Saarbr¨uckenGermany Department of Materials science&Engineering Saarland UniversityCampus D2266123Saarbr¨uckenGermany Leibniz Institute for Plasma science and Technology Felix-Hausdorff-Straße 217489GreifswaldGermany Faculty of Mechanical Engineering Technion–Israel Institute of TechnologyHaifa3200003Israel Wolfson Department of Chemical Engineering Technion–Israel Institute of TechnologyHaifa3200003Israel Grand Technion Energy Program Technion–Israel Institute of TechnologyHaifa3200003Israel saarene–saarland Center for Energy Materials and sustainability Campus C4266123Saarbr¨uckenGermany

The demand for electronic devices that utilize lithium is steadily increasing in this rapidly advancing technological *** high-purity lithium in an environmentally friendly way is challenging by using commercialized ***,we propose the first fuel cell system for continuous lithium-ion extraction using a lithium superionic conductor membrane and advanced *** fuel cell system for extracting lithium-ion has demonstrated a twofold increase in the selectivity of Li^(+)/Na^(+)while producing *** data show that the fuel cell with a titania-coated electrode achieves 95%lithium-ion purity while generating 10.23 Wh of energy per gram of *** investigation revealed that using atomic layer deposition improved the electrode's uniformity,stability,and electrocatalytic *** 2000 cycles determined by cyclic voltammetry,the electrode preserved its stability.

关键词： atomic layer deposition cation selectivity electrochemical lithium-ion extraction fuel cell

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search for production of dark fermion candidates in association with heavy neutral gauge boson decaying to dimuon in proton-proton collisions at√s=8 TeV using CMs open data

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Chinese Physics C 2024年第4期48卷 6-13页

作者： Y.Mahmoud H.Abdallah M.T.Hussein s.Elgammal Centre for theoretical physics The British University in EgyptEgypt Physics Department Faculty of ScienceCairo UniversityEgypt

In this study,we conducted a search for dark matter using a part of the data recorded by the CMs experiment during run-I of the LHC in 2012 with a center of mass energy of 8 TeV and an integrated luminosity of 11.6 fb−*** data were gathered from the CMs open *** matter,in the framework of the simplified model(mono-Z′),can be produced from proton-proton collisions in association with a new hypothetical gauge boson,Z′.Thus,the search was conducted in the dimuon plus large missing transverse momentum *** benchmark scenario of mono-Z′,which is known as light vector,was used for interpreting the CMs open *** evidence of dark matter was observed,and exclusion limits were set on the masses of dark matter and Z′at 95%confidence level.

关键词： dark matter large hadron collider CMs open data search for new physics dark fermion

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Genetic analyses of ancient tea trees provide insights into the breeding history and dissemination of Chinese Assam tea(Camellia sinensis ***)

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Plant Diversity 2024年第2期46卷 229-237页

作者： Miao-Miao Li Muditha k.Meegahakumbura Moses C.Wambulwa kevin s.Burgess Michael Möller Zong-Fang shen De-Zhu Li Lian-Ming Gao CAs key Laboratory for Plant Diversity and Biogeography of East Asia Kunming Institute of BotanyChinese Academy of ScienceKunming650201China Germplasm Bank of Wild species Kunming Institute of BotanyChinese Academy of ScienceKunming650201China kunming College of Life science University of Chinese Academy of SciencesKunming650201YunnanChina Department of Export Agriculture Faculty of Animal Science and Export AgricultureUva Wellassa UniversityBadulla90000Sri Lanka Department of Life sciences School of Science and ComputingSouth Eastern Kenya University170-90200KituiKenya Department of Biology Columbus State UniversityUniversity System of GeorgiaColumbusGA31907-5645USA Royal Botanic Garden Edinburgh 20A Inverleith RowEdinburghEH35LRScotlandUK Lijiang Forest Biodiversity National Observation and Research station Kunming Institute of BotanyChinese Academy of SciencesLijiang674100YunnanChina

Chinese Assam tea(Camellia sinensis ***)is an important tea crop with a long history of cultivation in Yunnan,*** its potential value as a genetic resource,its genetic diversity and domestication/breeding history remain *** address this issue,we genotyped 469 ancient tea plant trees representing 26 *** *** populations,plus two of its wild relatives(six and three populations of *** and ***,respectively)using 16 nuclear microsatellite *** showed that Chinese Assam tea has a relatively high,but comparatively lower gene diversity(H_(s)=0.638)than the wild relative ***(H_s=0.658).Clustering in sTRUCTURE indicated that Chinese Assam tea and its two wild relatives formed distinct genetic groups,with considerable interspecific *** Chinese Assam tea accessions clustered into three gene pools,corresponding well with their geographic ***,New Hybrids analysis indicated that 68.48%of ancient Chinese Assam tea plants from Xishuangbanna were genetic intermediates between the Puer and Lincang gene *** addition,10%of the ancient Chinese Assam tea individuals were found to be hybrids between Chinese Assam tea and *** results suggest that Chinese Assam tea was domesticated separately in three gene pools(Puer,Lincang and Xishuangbanna)in the Mekong River valley and that the hybrids were subsequently selected during the domestication *** the domestication history of Chinese Assam tea in southwestern Yunnan remains complex,our results will help to identify valuable genetic resources that may be useful in future tea breeding programs.

关键词： Tea plant Hybrid origin Genetic diversity Domestication history Camellia sinensis var.assamica Camellia taliensis

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AutoRhythmAI: A Hybrid Machine and Deep Learning Approach for Automated Diagnosis of Arrhythmias

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Computers, Materials & Continua 2024年第2期78卷 2137-2158页

作者： s.Jayanthi s.Prasanna Devi Department of Computer science and Engineering SRM Institute of Science and Technology-Vadapalani CampusChennaiTamil NaduIndia

In healthcare,the persistent challenge of arrhythmias,a leading cause of global mortality,has sparked extensive research into the automation of detection using machine learning(ML)***,traditional ML and AutoML approaches have revealed their limitations,notably regarding feature generalization and automation *** glaring research gap has motivated the development of AutoRhythmAI,an innovative solution that integrates both machine and deep learning to revolutionize the diagnosis of *** approach encompasses two distinct pipelines tailored for binary-class and multi-class arrhythmia detection,effectively bridging the gap between data preprocessing and model *** validate our system,we have rigorously tested AutoRhythmAI using a multimodal dataset,surpassing the accuracy achieved using a single dataset and underscoring the robustness of our *** the first pipeline,we employ signal filtering and ML algorithms for preprocessing,followed by data balancing and split for *** second pipeline is dedicated to feature extraction and classification,utilizing deep learning ***,we introduce the‘RRI-convoluted trans-former model’as a novel addition for binary-class *** ensemble-based approach then amalgamates all models,considering their respective weights,resulting in an optimal model *** our study,the VGGRes Model achieved impressive results in multi-class arrhythmia detection,with an accuracy of 97.39%and firm performance in precision(82.13%),recall(31.91%),and F1-score(82.61%).In the binary-class task,the proposed model achieved an outstanding accuracy of 96.60%.These results highlight the effectiveness of our approach in improving arrhythmia detection,with notably high accuracy and well-balanced performance metrics.

关键词： Automated machine learning neural networks deep learning arrhythmias

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Enhancing Wireless sensor Network Efficiency through Al-Biruni Earth Radius Optimization

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Computers, Materials & Continua 2024年第6期79卷 3549-3568页

作者： Reem Ibrahim Alkanhel Doaa sami khafaga Ahmed Mohamed Zaki Marwa M.Eid Abdyalaziz A.Al-Mooneam Abdelhameed Ibrahim s.k.Towfek Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Computer science and Intelligent systems Research Center BlacksburgVirginia24060USA Delta Higher Institute for Engineering and Technology Mansoura35511Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Artificial Intelligence and Computational Intelligence Research Center MeridenConnecticut06450USA school of ICT Faculty of EngineeringDesign and Information&Communications Technology(EDICT)Bahrain PolytechnicP.O.Box 33349Isa TownBahrain

The networks of wireless sensors provide the ground for a range of applications,including environmental moni-toring and industrial *** the networks can overcome obstacles like power and communication reliability and sensor coverage is the crux of network *** infrastructure planning should be focused on increasing performance,and it should be affected by the detailed data about node *** work recommends the creation of each sensor’s specs and radius of influence based on a particular geographical location,which will contribute to better network planning and *** using the ARIMA model for time series forecasting and the Al-Biruni Earth Radius algorithm for optimization,our approach bridges the gap between successive terrains while seeking the equilibrium between exploration and *** implementing adaptive protocols according to varying environments and sensor constraints,our study aspires to improve overall network *** compare the Al-Biruni Earth Radius algorithm along with Gray Wolf Optimization,Particle swarm Optimization,Genetic Algorithms,and Whale Optimization about performance on real-world *** the most efficient in the optimization process,Biruni displays the lowest error rate at *** two other statistical techniques,like ANOVA,are also useful in discovering the factors influencing the nature of sensor data and network-specific *** to the multi-faceted support the comprehensive approach promotes,there is a chance to understand the dynamics that affect the optimization outcomes better so decisions about network design can be *** delivering better performance and reliability for various in-situ applications,this research leads to a fusion of time series forecasters and a customized optimizer algorithm.

关键词： Wireless sensor networks optimization ARIMA model BER algorithm metaheuristic algorithms

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Machine learning-enhanced Monte Carlo and subset simulations for advanced risk assessment in transportation infrastructure

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Journal of Mountain science 2024年第2期21卷 690-717页

作者： Furquan AHMAD Pijush sAMUI s.s.MIsHRA Department of Civil Engineering National Institute of TechnologyPatna 800006India

The maintenance of safety and dependability in rail and road embankments is of utmost importance in order to facilitate the smooth operation of transportation *** study introduces a comprehensive methodology for soil slope stability evaluation,employing Monte Carlo simulation(MCs)and subset simulation(ss)with the"UPss 3.0 Add-in"in *** on an 11.693-meter embankment with a soil slope(inclination ratio of 2H:1V),the investigation considers earthquake coefficients(kh)and pore water pressure ratios(ru)following Indian zoning *** chance of slope failure showed a considerable increase as the Coefficient of Variation(COV),seismic coefficients(kh),and pore water pressure ratios(ru)experienced an *** ss approach showed exceptional efficacy in calculating odds of failure that are notably *** computational modeling,the study optimized the worst-case scenario using ANFIs-GA,ANFIs-GWO,ANFIs-PsO,and ANFIs-BBO *** ANFIs-PsO model exhibits exceptional accuracy(training R2=0.9011,RMsE=0.0549;testing R2=0.8968,RMsE=0.0615),emerging as the most *** study highlights the significance of conducting thorough risk assessments and offers practical insights into evaluating and improving the stability of soil slopes in transportation *** findings contribute to the enhancement of safety and reliability in real-world situations.

关键词： Monte Carlo simulation subset simulation Machine Learning seismic coefficient

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A new perspective on intervertebral disc calcification—from bench to bedside

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Bone Research 2024年第1期12卷 50-61页

作者： Emanuel J.Novais Rajkishen Narayanan Jose A.Canseco koen van de Wetering Christopher k.kepler Alan s.Hilibrand Alexander R.Vaccaro Makarand V.Risbud Department of Orthopaedic surgery Sidney Kimmel Medical CollegeThomas Jefferson UniversityPhiladelphiaPAUSA Unidade Local de saúde do Litoral Alentejano Orthopedic DepartmentSantiago do CacémPortugal Rothman Orthopedic Institute at Thomas Jefferson University PhiladelphiaPAUSA

Disc degeneration primarily contributes to chronic low back and neck ***,there is an urgent need to understand the spectrum of disc degeneration phenotypes such as fibrosis,ectopic calcification,herniation,or mixed *** these phenotypes,disc calcification is the least *** calcification,by definition,is the pathological mineralization of soft tissues,widely studied in the context of conditions that afflict vasculature,skin,and ***,disc calcification is associated with poor surgical outcomes and back pain refractory to conservative *** is frequently seen as a consequence of disc aging and progressive degeneration but exhibits unique molecular and morphological characteristics:hypertrophic chondrocyte-like cell differentiation;TNAP,ENPP1,and ANk upregulation;cell death;altered Pi and PPi homeostasis;and local *** studies in mouse models have provided a better understanding of the mechanisms underlying this *** is essential to recognize that the presentation and nature of mineralization differ between AF,NP,and EP ***,the combination of anatomic location,genetics,and environmental stressors,such as aging or trauma,govern the predisposition to ***,the systemic regulation of calcium and Pi metabolism is less important than the local activity of PPi modulated by the ANk-ENPP1 axis,along with disc cell death and differentiation *** there is limited understanding of this phenotype,understanding the molecular pathways governing local intervertebral disc calcification may lead to developing disease-modifying drugs and better clinical management of degeneration-related pathologies.

关键词： degeneration metabolism intervertebral

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Interatomic Interaction Models for Magnetic Materials:Recent Advances

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Chinese Physics Letters 2024年第6期41卷 54-66页

作者： Tatiana s.kostiuchenko Alexander V.shapeev Ivan s.Novikov Emanuel Institute of Biochemical Physics RAs 4 Kosygin StreetMoscow119334Russian Federation Independent investigator

Atomistic modeling is a widely employed theoretical method of computational materials *** has found particular utility in the study of magnetic ***,magnetic empirical interatomic potentials or spinpolarized density functional theory(DFT)served as the primary models for describing interatomic interactions in atomistic simulations of magnetic ***,in recent years,a new class of interatomic potentials known as magnetic machine-learning interatomic potentials(magnetic MLIPs)has *** MLIPs combine the computational efficiency,in terms of CPU time,of empirical potentials with the accuracy of DFT *** this review,our focus lies on providing a comprehensive summary of the interatomic interaction models developed specifically for investigating magnetic *** also delve into the various problem classes to which these models can be ***,we offer insights into the future prospects of interatomic interaction model development for the exploration of magnetic materials.

关键词： materials interaction empirical

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