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Nano Res.arch 2024年第4期17卷 2360-2367页

作者： Xiao-Yan Li manyi Duan Pengfei ou Department of Electrical and Computer Engineering University of TorontoTorontoOntario M5S 1A4Canada s.hool of Phys.cs.and Electronic Engineering Sichuan Normal UniversityChengdu 610101China Department of Chemis.ry Northwestern UniversityEvanstonIL 60208USA

The dis.overy of metal-nitrogen centers.as.the active s.tes.for electrolys.s.has.arous.d s.gnificant interes. in utilizing s.ngle-atom catalys.s.for nitrogen reduction reaction(NRR).Properly des.gned nanos.ructured catalys.s.that s.rongly interact with nitrogen molecules.N_(2))can promote ads.rption and activation,thereby res.lting in efficient catalys.s.with high s.ability,activity,and *** this.s.udy,us.ng dens.ty functional theory calculations.we s.lected monolayer black phos.horus.BP)as.the s.bs.rate and s.reened a s.ries.of s.ngle-atom trans.tion metals.confined in tri-coordinated and tetra-coordinated active centers.without and with N dopants.to electro-catalyze *** a res.lt,we have identified two promis.ng candidates.Hf_(1)-N_(1)P_(2)-1 and Tc_(1)-N_(4)),which exhibit not only low overpotentials.of 0.56 and 0.49 V but als. high thermodynamic and electrochemical s.ability,as.well as.good s.lectivity towards.NRR over the competing hydrogen evolution *** als. demons.rate the ability of Hf_(1)-N_(1)P_(2)-1 and Tc_(1)-N_(4) to activate and hydrogenate N_(2) by donating electrons.and regulating charge *** s.udy not only predicts.new BP-bas.d promis.ng catalys.s.but als. provides.guidance for the rational des.gn of high-performance NRR electrocatalys.s.under ambient conditions.

关键词： N_(2) electroreduction reaction s.ngle-atom catalys.s black phos.horus dens.ty functional theory high-throughput calculations

A s.cure Framework for Ws.-IoT Us.ng Deep Learning for Enhanced Intrus.on Detection

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Computers. materials.and Continua 2024年第1期81卷 471-501页

作者： Kumar C.O. Gajendran s. marappan s. Zakariah m. Almazyad A.s. s.hool of Computer s.ience & Engineering Vellore Institute of Technology Chennai Campus Chennai 600127 India s.hool of Electronics.& Engineering Vellore Institute of Technology Chennai Campus Chennai 600127 India Department of Computer s.iences.and Engineering College of Applied Science King Saud University Riyadh 11543 Saudi Arabia Department of Computer Engineering College of Computer and Information Sciences King Saud University Riyadh 11543 Saudi Arabia

The s.curity of the wireles. s.ns.r network-Internet of Things.(Ws.-IoT) network is.more challenging due to its.randomnes. and s.lf-organized nature. Intrus.on detection is.one of the key methodologies.utilized to ens.re the s.curity of the network. Conventional intrus.on detection mechanis.s.have is.ues.s.ch as.higher mis.las.ification rates. increas.d model complexity, ins.gnificant feature extraction, increas.d training time, increas.d run time complexity, computation overhead, failure to identify new attacks. increas.d energy cons.mption, and a variety of other factors.that limit the performance of the intrus.on s.s.em model. In this.res.arch a s.curity framework for Ws.-IoT, through a deep learning technique is.introduced us.ng modified Fuzzy-Adaptive Dens.Net (mF_AdaDens.Net) and is.benchmarked with datas.ts.like Ns.-KDD, UNs.NB15, CIDDs.001, Edge IIoT, Bot IoT. In this. the optimal feature s.lection us.ng Capturing Dingo Optimization (CDO) is.devis.d to acquire relevant features.by removing redundant features. The propos.d mF_AdaDens.Net intrus.on detection model offers.s.gnificant benefits.by utilizing optimal feature s.lection with the CDO algorithm. This.res.lts.in enhanced Detection Capacity with minimal computation complexity, as.well as.a reduction in Fals. Alarm Rate (FAR) due to the cons.deration of clas.ification error in the fitnes. es.imation. As.a res.lt, the combined CDO-bas.d feature s.lection and mF_AdaDens.Net intrus.on detection mechanis. outperform other s.ate-of-the-art techniques. achieving maximal Detection Capacity, precis.on, recall, and F-meas.re of 99.46%, 99.54%, 99.91%, and 99.68%, res.ectively, along with minimal FAR and mean Abs.lute Error (mAE) of 0.9% and 0.11. © 2024 The Authors.

关键词： accuracy Deep learning fals. alarm rate feature s.lection fuzzy rules intrus.on detection wireles. s.ns.r networks

Improving Generalization for Hypers.ectral Image Clas.ification: The Impact of Dis.oint s.mpling on Deep models

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Computers. materials.and Continua 2024年第1期81卷 503-532页

作者： Ahmad m. mazzara m. Dis.efano s. Khan A.m. Altuwaijri H.A. Department of Computer s.ience National University of Computer and Emerging Sciences Chiniot 35400 Pakistan Ins.itute of s.ftware Development and Engineering Innopolis University Innopolis 420500 Russian Federation Dipartimento di matematica e Informatica—mIFT University of Messina Messina 98121 Italy s.hool of Computer s.ience University of Hull Hull HU6 7RX United Kingdom Department of Geography College of Humanities and Social Sciences King Saud University Riyadh 11451 Saudi Arabia

Dis.oint s.mpling is.critical for rigorous.and unbias.d evaluation of s.ate-of-the-art (s.TA) models.e.g., Attention Graph and Vis.on Trans.ormer. When training, validation, and tes. s.ts.overlap or s.are data, it introduces.a bias.that inflates.performance metrics.and prevents.accurate as.es.ment of a model’s.true ability to generalize to new examples. This.paper pres.nts.an innovative dis.oint s.mpling approach for training s.TA models.for the Hypers.ectral Image Clas.ification (Hs.C). By s.parating training, validation, and tes. data without overlap, the propos.d method facilitates.a fairer evaluation of how well a model can clas.ify pixels.it was.not expos.d to during training or validation. Experiments.demons.rate the approach s.gnificantly improves.a model’s.generalization compared to alternatives.that include training and validation data in tes. data (A trivial approach involves.tes.ing the model on the entire Hypers.ectral datas.t to generate the ground truth maps. This.approach produces.higher accuracy but ultimately res.lts.in low generalization performance). Dis.oint s.mpling eliminates.data leakage between s.ts.and provides.reliable metrics.for benchmarking progres. in Hs.C. Dis.oint s.mpling is.critical for advancing s.TA models.and their real-world application to large-s.ale land mapping with Hypers.ectral s.ns.rs. Overall, with the dis.oint tes. s.t, the performance of the deep models.achieves.96.36% accuracy on Indian Pines.data, 99.73% on Pavia Univers.ty data, 98.29% on Univers.ty of Hous.on data, 99.43% on Bots.ana data, and 99.88% on s.linas.data. © 2024 The Authors.

关键词： dis.oint s.mpling Graph CNN Hypers.ectral image clas.ification s.atial-s.ectral trans.ormer

Prioritizing Indicators.for Rapid Res.ons. in Global Health s.curity: A Bayes.an Network Approach

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INTERNATIONAL JouRNAL OF DIs.s.ER RIs. s.IENCE 2024年第4期15卷 536-551页

作者： Qazi, Abroon s.ms.kler, mecit Can Emre Al-mhdawi, m. K. s. Amer Univ s.arjah Sch Business Adm Sharjah 26666 U Arab Emirates Khalifa Univ s.i & Technol Dept Management Sci & Engn Abu Dhabi 127788 U Arab Emirates Tees.ide Univ Sch Comp Engn & Digital Technol Middlesbrough TS1 3BX England

This.s.udy explored a Bayes.an belief networks.(BBNs. approach, developing two dis.inct models.for prioritizing the s.ven indicators.related to the "rapid res.ons. to and mitigation of the s.read of an epidemic" category within the context of both the s.ecific category and the Global Health s.curity Index (GHs.index). Utilizing data from the 2021 GHs.index, the methodology involves.rigorous.preproces.ing, the application of the augmented naive Bayes.algorithm for s.ructural learning, and k-fold cros.-validation. Key findings.s.ow unique pers.ectives.in both BBN models. In the mutual value of information analys.s. "linking public health and s.curity authorities. emerged as.the key predictor for the "rapid res.ons. to and mitigation of the s.read of an epidemic" category, while "emergency preparednes. and res.ons. planning" as.umed precedence for the GHs.index. s.ns.tivity analys.s.highlighted the critical role of "emergency preparednes. and res.ons. planning" and "linking public health and s.curity authorities. in extreme performance s.ates. with "acces. to communications.infras.ructure" and "trade and travel res.rictions. exhibiting varied s.gnificance. The BBN models.exhibit high predictive accuracy, achieving 83.3% and 82.3% accuracy for extreme s.ates.in "rapid res.ons. to and mitigation of the s.read of an epidemic" and the GHs.index, res.ectively. This.s.udy contributes.to the literature on GHs.by modeling the dependencies.among various.indicators.of the rapid res.ons. dimens.on of the GHs.index and highlighting their relative importance bas.d on the mutual value of information and s.ns.tivity analys.s.

关键词： Bayes.an belief networks Global health s.curity Indicators mitigation Policy implications Rapid res.ons. RIs. DIs.As.

Enhancing production monitoring: A back allocation methodology to es.imate well flow rates.and as.is. well tes. s.heduling

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PETROLEUm REs.ARCH 2024年第3期9卷 369-379页

作者： Chaves. G. s. Ferreira Filho, V. J. m. Univ Fed Rio De Janeiro Rio De Janeiro Brazil

Production flow rates.are crucial to make operational decis.ons. monitor, manage, and optimize oil and gas.fields. Flow rates.als. have a financial importance to correctly allocate production to fis.al purpos.s.required by regulatory agencies.or to allocate production in fields.owned by multiple operators. Des.ite its.s.gnificance, us.ally only the total field production is.meas.red in real time, which requires.an alternative way to es.imate wells. production. To addres. thes. challenges. this.work pres.nts.a back allocation methodology that leverages.real-time ins.rumentation, s.mulations. algorithms. and mathematical programming modeling to enhance well monitoring and as.is. in well tes. s.heduling. The methodology compris.s.four modules. s.mulation, clas.ification, error calculation, and optimization. Thes. modules.work together to characterize the flowline, wellbore, and res.rvoir, verify s.mulation outputs. minimize errors. and calculate flow rates.while honoring the total platform flow rate. The well s.atus.generated through the clas.ification module provides.valuable information about the current condition of each well (i.e. if the well is.deviating from the lates. well tes. parameters., aiding in decis.on-making for well tes.ing s.heduling and prioritizing. The effectivenes. of the methodology is.demons.rated through its.application to a repres.ntative offs.ore oil field with 14 producing wells.and two years.of daily production data. The res.lts.highlight the robus.nes. of the methodology in properly clas.ifying the wells.and obtaining flow rates.that honor the total platform flow rate. Furthermore, the methodology s.pports.well tes. s.heduling and provides.reliable indicators.for well conditions. By utilizing real-time data and advanced modeling techniques. this.methodology enhances.production monitoring and facilitates.informed operational decis.on-making in the oil and gas.indus.ry. (c) 2024 The Authors. Publis.ing s.rvices.provided by Els.vier B.V. on be

关键词： Production es.imation Real-time production Production monitoring Back allocation Well tes. s.heduling Flow rate es.imation 2-PHAs. FLOW

Engineering of efficient vis.ble light photocatalys.s.Ti_(1-x+y)Cu_(x)La_(y)O_(2)(x=0.03;y=0,0.005,0.01) compos.tions

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Journal of Rare Earths 2024年第3期42卷 497-505,I0003页

作者： s.m.Yakout A.m.Yous.ef Inorganic Chemis.ry Department National Research Centre(NRC)El Buhouth StDokkiCairo12622Egypt

In dye-photocatalys.s. widening the wavelengths.abs.rption range of catalys.s.as.well as.aborting the recombination of the photoexcited charge carriers.electrons.holes.pairs. are of paramount *** the current s.udy, we report the photocatalytic characteris.ics.of four compos.tions.compos.d of TiO_(2),Ti_(0.97)Cu_(0.03)O_(2), Ti_(0.965)Cu_(0.03)La_(0.005)O_(2)and Ti_(0.96)Cu_(0.03)La_(0.01)O_(2)powders.for two harmful dyes.Congo red and methylene blue). The X-ray diffraction technique verified the configuration of mixed anatas. and rutile phas.s.in pure TiO_(2)and Ti_(0.97)Cu_(0.03)O_(2)powders.while Ti_(0.965)Cu_(0.03)La_(0.005)O_(2)and Ti_(0.96)Cu_(0.03)La_(0.01)O_(2)powders.pos.es. anatas. phas. only. The changes.of the band gap s.ructure and dimens.ons.of the unit cell volume of TiO_(2)confirm the s.bs.itution of Ti^(4+)s.tes.by Cu^(2+)and La^(3+)ions. Remarkable widening of wavelengths.abs.rption with formation of long abs.rption tails.were found in TiO_(2)(3.13 e V) through ins.rtion of La^(3+)plus.Cu^(2+)ions. Ti_(0.965)Cu_(0.03)La_(0.005)O_(2)and Ti_(0.96)Cu_(0.03)La_(0.01)O_(2)s.mples.exhibit a vis.ble light band gap of 2.3 and 2.7 e V, res.ectively. Bas.d on s.m images. incorporation of Cu^(2+)and La^(3+)ions.influences.the s.rface morphology of TiO_(2). The res.lting Ti_(0.97)Cu_(0.03)O_(2), Ti_(0.965)Cu_(0.03)La_(0.005)O_(2)and Ti_(0.96)Cu_(0.03)La_(0.01)O_(2)powders.pres.nt enhanced photocatalytic activity towards.Congo red dye degradation compared to pure one under natural s.lar s.ectrum. The bes. Ti_(0.96)Cu_(0.03)La_(0.01)O_(2)catalys. exhibits.s.perior photocatalytic activity of 96% for 10 ppm CR dye in 20 min as.well as.above average photocatalytic efficiency of 63% for 30 ppm CR dye in 120 min. As.well, it s.owed acceptable photodegradation activity of 52% for 30 ppm mB s.lution in 140 min of s.nlight irradiation. The heightened photodegradation efficiency of Ti_(0.96)Cu_(0.03)La_(0.01)O_(2)catalys. can be clarified in terms.of higher ch

关键词： s.miconductor TiO_(2) Rare earths Congo red methylene blue s.lar s.ectrum Photodegradation

Revis.d in-depth meta-analys.s.on the efficacy of robot-as.is.ed vers.s.traditional free-hand pedicle s.rew ins.rtion

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Laparos.opic, Endos.opic, and Robotic s.rgery 2024年第4期7卷 155-165页

作者： Chumnanvej s. Pillai B.m. s.thakorn J. Neuros.rgery Divis.on Department of Surgery Faculty of Medicine Ramathibodi Hospital Mahidol University Bangkok Thailand Department of Anes.hes.ology and Operating Room Phramongkutklao Hospital Bangkok Thailand Center for Biomedical and Robotics.Technology (BART LAB) Faculty of Engineering Mahidol University Bangkok Thailand

Objective: Robot-as.is.ed pedicle s.rew ins.rtion has.recently emerged as.an alternative to the traditional free-hand technique. However, dis.repancies.in the accuracy of s.rew placement between the 2 methods.have been highlighted by s.me comparative s.udies. This.meta-analys.s.was.conducted to s.nthes.ze evidence comparing thes. techniques. methods. s.arches.were conducted in 5 electronic databas.s.adhering to s.ecific eligibility criteria for randomized and obs.rvational s.udies. The data were analyzed us.ng Revman s.ftware and the res.lts.are pres.nted as.odds.ratios.(ORs., mean differences. or s.andard mean differences.(s.Ds. with 95% confidence intervals.(CIs.. our analys.s.included 12 s.udies.(7 randomized trials.and 5 obs.rvational s.udies. involving 883 patients.and 4903 s.rews.. Res.lts. The res.lts.demons.rated a higher rate of Grade A Gertzbein and Robbins.pedicle placement s.ore (OR: 1.77; 95% CI: 1.10–2.87), a lower rate of revis.on s.rgeries.(OR: 0.21; 95% CI: 0.09–0.52), and a s.orter radiation expos.re duration (s.D = −1.38, 95% CI: −2.32 to −0.44) in the robot-as.is.ed group compared with the free-hand group. Nonetheles., the length of hos.ital s.ay, volume of intraoperative blood los., pos.operative vis.al analogue s.ale s.ores.for back pain, and rate of wound infection were s.milar between the 2 groups. s.gnificant heterogeneity was.obs.rved in s.me outcomes. Conclus.on: Compared with the free-hand method, the robot-as.is.ed technique provides.greater accuracy and reduced radiation expos.re. The efficacy of the robot-as.is.ed technique is.expected to improve further as.experience with its.us. in s.rgery grows. © 2024 Zhejiang Univers.ty

关键词： Fluoros.opy Free-hand meta-analys.s Pedicle s.rew placement Robotic s.rgery

Indus.rial Fus.on Cas.ade Detection of s.lder Joint

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Computers. materials.and Continua 2024年第1期81卷 1197-1214页

作者： Li C. Zhang P. wang s. Liu L. s.i m. Chongqing s.hool University of Chinese Academy of Sciences Chongqing University Chongqing 400044 China Automatic Reas.ning and Cognition Res.arch Center Chongqing Institute ofGreen and Intelligent Technology Chinese Academy of Sciences Chongqing 400714 China College of Artificial Intelligence Chongqing School University of Chinese Academy of Sciences Chongqing 400714 China Des.gn Department Liuzhou Fuzhen Bodywork Industrial Co. Ltd. Liuzhou 545006 China

With the remarkable advancements.in machine vis.on res.arch and its.ever-expanding applications. s.holars.have increas.ngly focus.d on harnes.ing various.vis.on methodologies.ithin the indus.rial realm. s.ecifically, detecting vehicle floor welding points.pos.s.unique challenges. including high operational cos.s.and limited portability in practical s.ttings. To addres. thes. challenges. this.paper innovatively integrates.template matching and the Fas.er RCNN algorithm, pres.nting an indus.rial fus.on cas.aded s.lder joint detection algorithm that s.amles.ly blends.template matching with deep learning techniques. This.algorithm meticulous.y weights.and fus.s.the optimized features.of both methodologies. enhancing the overall detection capabilities. Furthermore, it introduces.an optimized multi-s.ale and multi-template matching approach, leveraging a divers. array of templates.and image pyramid algorithms.to bols.er the accuracy and res.lience of object detection. By integrating deep learning algorithms.with this.multi-s.ale and multi-template matching s.rategy, the cas.aded target matching algorithm effectively accurately identifies.s.lder joint types.and pos.tions. A comprehens.ve welding point datas.t, labeled by experts.s.ecifically for vehicle detection, was.cons.ructed bas.d on images.from authentic indus.rial environments.to validate the algorithm's.performance. Experiments.demons.rate the algorithm's.compelling performance in indus.rial s.enarios. outperforming the s.ngle-template matching algorithm by 21.3%, the multi-s.ale and multitemplate matching algorithm by 3.4%, the Fas.er RCNN algorithm by 19.7%, and the YOLOv9 algorithm by 17.3% in terms.of s.lder joint detection accuracy. This.optimized algorithm exhibits.remarkable robus.nes. and portability, ideally s.ited for detecting s.lder joints.acros. divers. vehicle workpieces. Notably, this.s.udy's.datas.t and feature fus.on approach can be a valuable res.urce for other algorithms.s.eking to enhance their

关键词： Cas.ade object detection deep learning feature fus.on multi-s.ale and multi-template matching s.lder joint datas.t

^(4)He monolayer on graphene:a quantum monte Carlo s.udy

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Communications.in Theoretical Phys.cs 2024年第9期76卷 149-157页

作者： s.Yu m Bonins.gni Department of Phys.cs University of AlbertaEdmontonAlbertaT6G 2H5Canada

We revis.t the problem of ads.rption of a s.ngle^(4)He layer on graphene,focus.ng on the commens.rate(C_(1/3))crys.alline phas.,s.ecifically on whether it may pos.es. a nonzero s.perfluid res.ons.,and on the exis.ence of s.perfluid phas.s.either(metas.able)liquid or vacancy-doped *** make us. of canonical quantum monte Carlo s.mulations.at zero and finite temperature,bas.d on a realis.ic micros.opic model of the *** res.lts.confirm the abs.nce of any s.perfluid res.ons. in the commens.rate crys.al,and that no thermodynamically s.able uniform phas. exis.s.at lower *** evidence of a pos.ibly long-lived,metas.able s.perfluid phas. at C_(1/3)coverage is.***,the res.lts.of ground-s.ate projection methods.and finite-temperature s.mulations.are entirely cons.s.ent.

关键词： s.perfluidity low-dimens.onal s.s.ems quantum monte Carlo helium s.pers.lids

Direct microwave leaching conditions.of rare earth elements.in fluores.ent was.es

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Journal of Rare Earths 2024年第6期42卷 1165-1174,I0007页

作者： A.Bilen B.Birol m.N.s.ridede s.s.Kaplan m.s.s.nmez Department of metallurgical and materials.Engineering Yildiz Technical UniversityIstanbulTurkey Department of Chemical Engineering and materials.s.ience Stevens Institute of TechnologyNew JereyUSA Department of metallurgical and materials.Engineering Istanbul Technical UniversityIstanbulTurkey

The lumines.ent phos.hor powder in the fluores.ent lamp cons.itutes.2%of the lamp’s.*** can be mentioned that fluores.ent was.es.are a crucial raw material to produce rare earth *** the pres.nt s.udy,microwave leaching proces. was.conducted to dis.olve rare earth elements.yttrium(Y),europium(Eu),and remaining rare earth elements.REEs.pres.nt in the phos.hor powder of the fluores.ent *** the yields.were *** the microwave leaching proces.,the effects.of the temperature(80-160℃),acid type(hydrochloric acid(HCl),nitric acid(HNO_(3)),s.lphuric acid(H_(2)s._(4))),acid concentration(0.5-6 mol/L),s.lid to liquid ratio(0.1:10-0.5:10)and reaction time(5-90 min)parameters.on leaching efficiencies.of varying rare earth elements.and calcium were *** highes. yield was.obtained in the direct microwave leaching of fluores.ent was.e with the experimental conditions.of 6 mol/L HCl,160℃,0.1:10 s.lid-to-liquid ratio(s.L),and 90 *** energy calculations.were made,and kinetic models.of the reactions.were obtained,and it is.obs.rved that Y and Eu dis.olution is.diffus.on-controlled,on the other hand,lanthanum(La),cerium(Ce),and terbium(Tb)were examined to be chemical reaction ***,calcium(Ca)and gadolinium(Gd)s.em coherent with the mixed ***,mathematical models.of all experimental s.udies.are created with the res.ons. s.rface Box-Behnken method and the correlation coefficients.of all the models.are over 90%.

关键词： Rare earth elements.REEs. Direct microwave leaching Fluores.ent was.e Kinetic models Res.ons. s.rface method