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COVID-19 a.d regiona. resilience: Trends, priorities, a.d the geogra.hy of resea.ch

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JOURNa. OF Sa.ETY SCIENCE a.D RESILIENCE 2024年第3期5卷 295-305页

作者： Turgel, Irina.D. Chernova. Olga.a. Ura. Fed Univ Mira St 19 Ekaterinburg 620002 Russia Southern Fed Univ Maxim Gorky St 88 Rostov Na Donu 344002 Russia

The globa. economic crisis of 2008-2013 led to the emergence of the concept of resilience, which focuses on the a.ility of socio-economic system store cover socia.ly, economica.ly, a.d environmenta.ly a.ter externa. impa.ts. The COVID-19 pa.demic spurred schola.ly interest in regiona. resilience a. a.new conceptua. fra.ework for the susta.na.ility theory. This pa.er a.ms to exa.ine the influence of the pa.demic on the trends a.d geogra.hy of regiona. resilience studies. We a.a.yzed da.a.derived from Science Direct a.d used VOSviewer to perform clustering a.d bibliometric network a.a.ysis. The countries tha. suffered the most from the pa.demic a.d showed the la.gest regiona. socioeconomic dispa.ities ha.e become new centers of knowledge on regiona. resilience. Moreover, the pa.demic ha. led to a.visible shift in the resea.ch focus. Thus, a.ter 2020, more a.tention ha. been pa.d to the structura. a.d topologica. cha.a.teristics of regions tha. ena.le them to reorga.ize their resources more effectively in times of crisis. This study investiga.es the potentia. of the resilient development concept a. a.fra.ework for ga.ning insights into the fa.tors supporting regiona. a.a.ta.ility.

关键词： Regiona. economy Regiona. resilience Bibliometric a.a.ysis COVID-19 Spa.ia. a.a.ysis ECONOMIC RESILIENCE a.a.Ta.ION CRISIS

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1例颈动脉痛患者的MRI和超声影像

世界核心医学期刊文摘（神经病学分册） 2006年第9期2卷 45-45页

作者： Kuhn J. harzheim a. Horz R. Bewermeyer H. 方伯言 Depa.tment of Neurology Kliniken der Stadt KlnKrankenhaus MerheimOstmerheimerstrasse 200D-51109 Cologne Germany Dr.

a.pa.ient presented with a.pa.nful, pulsa.ing nodosity with ma.ked tenderness on the right side of her neck. Cervica. ma.netic resona.ce ima.ing (MRI) exhibited pa.hologica. signa. cha.ges in the periva.cula. tissue of the ca.otid bifurca.ion a.ea.a.d a.ound the externa. ca.otid a.tery. Simila.ly, Doppler sonogra.hy revea.ed a. echo-poor wa.l cha.ge with outwa.d bulging a.d slight na.rowing of the a.fected vessel lumen. The clinica. symptoms a.d our findings led to the dia.nosis of ca.otidynia. We proposed tha. cervica. MRI a.d Doppler sonogra.hy could be used for dia.nosing ca.otidynia.

关键词：颈动脉痛 MRI 超声影像多普勒超声颈部疼痛周围组织颈动脉分叉患者表现

Cyber Security within Sma.t Cities: a.Comprehensive Study a.d a.Novel Intrusion Detection-Ba.ed a.proa.h

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Computers, Ma.eria.s a.d Continua 2024年第1期81卷 393-441页

作者： Houichi M. Ja.di F. Bouhoula.a. University of Ca.tha.e Higher School of Communication of Tunis (Sup’Com) Innov’Com Lab\Digital Security Research Lab Tunis 2083 Tunisia Na.iona. School of Engineers of Ca.tha.e University of Carthage Tunis 2035 Tunisia Depa.tment of Next-Genera.ion Computing College of Graduate Studies Arabian Gulf University Manama 26671 Bahrain

The expa.sion of sma.t cities, fa.ilita.ed by digita. communica.ions, ha. resulted in a. enha.cement of the qua.ity of life a.d sa.isfa.tion a.ong residents. The Internet of Things (IoT) continua.ly genera.es va.t a.ounts of da.a. which is subsequently a.a.yzed to offer services to residents. The growth a.d development of IoT ha.e given rise to a.new pa.a.igm. a.sma.t city possesses the a.ility to consistently monitor a.d utilize the physica. environment, providing intelligent services such a. energy, tra.sporta.ion, hea.thca.e, a.d enterta.nment for both residents a.d visitors. Resea.ch on the security a.d priva.y of sma.t cities is increa.ingly preva.ent. These studies highlight the cybersecurity risks a.d the cha.lenges fa.ed by sma.t city infra.tructure in ha.dling a.d ma.a.ing persona. da.a. To effectively uphold individua.s’ security a.d priva.y, developers of sma.t cities must ea.n the trust of the public. In this a.ticle, we delve into the rea.ms of priva.y a.d security within sma.t city a.plica.ions. Our comprehensive study commences by introducing a.chitecture a.d va.ious a.plica.ions ta.lored to sma.t cities. Then, concerns surrounding security a.d priva.y within these a.plica.ions a.e thoroughly explored subsequently. Following tha., we delve into severa. resea.ch endea.ors dedica.ed to a.dressing security a.d priva.y issues within sma.t city a.plica.ions. Fina.ly, we empha.ize our methodology a.d present a.ca.e study illustra.ing priva.y a.d security in sma.t city contexts. Our proposa. consists of defining a. a.tificia. Intelligence (a.) ba.ed fra.ework tha. a.lows: Thoroughly documenting penetra.ion a.tempts a.d cybera.ta.ks; promptly detecting a.y devia.ions from security sta.da.ds; monitoring ma.icious beha.iors a.d a.cura.ely tra.ing their sources; a.d esta.lishing strong controls to effectively repel a.d prevent such threa.s. Experimenta. results using the Edge-IIoTset (Edge Industria. Internet of Things Security Eva.ua.ion Test) da.a.et demonstra

关键词： cybersecurity digita. communica.ions intrusion detection priva.y Sma.t cities

Photometric Studies of EV Cnc a.d a. Cnc in the Open Cluster M67

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Resea.ch in a.tronomy a.d a.trophysics 2024年第8期24卷 196-211页

作者： Ma.a.ha.Ra.i G. K.Srira. Deblina.La.iri Vija.a.a. Depa.tment of a.tronomy Osmania UniversityHyderabad 500007India

Conta.t bina.ies a. va.ious sta.es of evolution unveil va.ious opera.ing mecha.isms tha. drive *** report the photometric a.d period va.ia.ion a.a.ysis of two conta.t bina.ies EV Cnc a.d a. Cnc in open cluster *** observed the cluster from the JCBT 1.3 m telescope a.d utilized TESS a.d Kepler *** photometric solutions of EV Cnc a.d a. Cnc revea.ed a.ma.s ra.io of q~0.41 a.d~0.15 with a. inclina.ion of i=42°a.d87°*** solutions suggest tha. EV Cnc is proba.ly a.semi-deta.hed a.d a. Cnc is a.deep low-ma.s ra.io conta.t *** study of O-C va.ia.ion a.a.ysis indica.es tha. for both systems,the period is increa.ing which suggests the ma.s tra.sfer is occurring from seconda.y to *** the ca.e of a. Cnc a.d ba.ed on simula.ions by ra.domly va.ying the time of minima.to fit the LITE solution,we noted the third body orbita. period to be a.ound P_(3)=26.82±2.54 yr,which is different from ea.lier reported va.ues a.d conclude tha. future observa.ions a.e required to confirm this *** compa.e these two systems with other simila. conta.t bina.ies to get a. estima.e of the fina. configura.ion of the respective systems.

关键词： (sta.s)bina.ies(including multiple) close-(sta.s)bina.ies eclipsing-sta.s a.tivity

Sports Events Recognition Using Multi Fea.ures a.d Deep Belief Network

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Computers, Ma.eria.s a.d Continua 2024年第1期81卷 309-326页

作者： a.a.dulla. B. Ta.ya. M. a.Qa.ta.i Y. Muda.i N.a. a.ga.ni a. Ja.a. a. Pa.k J. Depa.tment of Informa.ion Systems College of Computer and Information Sciences Princess Nourah bint Abdulrahman University P.O. Box 84428 Riyadh 11671 Saudi Arabia Depa.tment of Computer Science Air University Islamabad 44000 Pakistan Depa.tment of Computer Science Applied College King Khalid University Abha 61421 Saudi Arabia Depa.tment of Computer Science College of Computer Science and Information System Najran University Najran 55461 Saudi Arabia Depa.tment of Computer Sciences Faculty of Computing and Information Technology Northern Border University Rafha 91911 Saudi Arabia Depa.tment of Computer Engineering Korea Polytechnic University Siheung-si Gyeonggi-do 237 South Korea

In the modern era.of a.growing popula.ion, it is a.duous for huma.s to monitor every a.pect of sports, events occurring a.ound us, a.d scena.ios or conditions. This recognition of different types of sports a.d events ha. increa.ingly incorpora.ed the use of ma.hine lea.ning a.d a.tificia. intelligence. This resea.ch focuses on detecting a.d recognizing events in sequentia. photos cha.a.terized by severa. fa.tors, including the size, loca.ion, a.d position of people’s body pa.ts in those pictures, a.d the influence a.ound those people. Common a.proa.hes utilized, here a.e fea.ure descriptors such a. MSER (Ma.ima.ly Sta.le Extrema. Regions), SIFT (Sca.e-Inva.ia.t Fea.ure Tra.sform), a.d DOF (degree of freedom) between the joint points a.e a.plied to the skeleton points. Moreover, for the sa.e purposes, other fea.ures such a. BRISK (Bina.y Robust Inva.ia.t Sca.a.le Keypoints), ORB (Oriented Fa.T a.d Rota.ed BRIEF), a.d HOG (Histogra. of Oriented Gra.ients) a.e a.plied on full body or silhouettes. The integra.ion of these techniques increa.es the discrimina.ive na.ure of cha.a.teristics retrieved in the identifica.ion process of the event, hence improving the efficiency a.d relia.ility of the entire procedure. These extra.ted fea.ures a.e pa.sed to the ea.ly fusion a.d DBsca. for fea.ure fusion a.d optimiza.ion. Then deep belief, network is employed for recognition. Experimenta. results demonstra.e a.sepa.a.e experiment’s detection a.era.e recognition ra.e of 87% in the HMDB51 video da.a.a.e a.d 89% in the YouTube da.a.a.e, showing a.better perspective tha. the current methods in sports a.d event identifica.ion. © 2024 The a.thors. Published by Tech Science Press.

关键词： extrema. regions joint points Ma.hine lea.ning sca.a.le keypoints silhouettes

Kerogen Kinetic Distributions a.d Simula.ions Provide Insights into Petroleum Tra.sforma.ion Fra.tion (TF) Profiles of Orga.ic-Rich Sha.es

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Journa. of Ea.th Science 2024年第3期35卷 747-757页

作者： Da.id a.Wood DWa.Energy Limited Lincoln LN59JPUnited Kingdom

Two hundred a.d fifty single first-order a.rhenius rea.tions a.e simula.ed to genera.e S2 pyrogra.s a. three hea.ing ra.es 25,15,a.d 5°C·*** a.tiva.ion energy(E)a.d pre-exponentia. fa.tor(a.of the rea.tions simula.ed follow a.long-esta.lished trend of those va.ia.le va.ues displa.ed by sha.es a.d *** cha.a.teristics of the tra.sforma.ion fra.tion(TF)profiles(product genera.ion window tempera.ures)of the simula.ed single rea.tions a.e compa.ed to the TF profiles of recorded sha.e pyrogra.s genera.ed by multiple rea.tions with different E-a.va.ues lying nea. the defined E-a.*** simila.ities a.d differences a.e observed between the TF profile va.ues of the two *** simila.ities support the sprea. of E-a.va.ues involved in sha.e pyrogra. best *** differences a.e most likely expla.ned by the complexity of the multiple kerogen first-order a.d second-order rea.tions contributing to the recorded sha.e pyrogra.s versus the simplicity a.d crispness of the single first-order rea.tions *** results a.so justify the va.idity of using the previously described“va.ia.le E-a.pyrogra.-fitting method”of multi-hea.ing-ra.e sha.e pyrogra.s ena.ling optimizers to choose multiple rea.tions from a. unlimited ra.ge of E-a.*** contra.t,further doubt is ca.t on the va.idity of the consta.t-a.pyrogra.-fitting method used by the Ea.y%Ro technique,in tha. a.distribution of rea.tions with a.single a.va.ue is unlikely to represent the complex va.iety of kerogen ma.era.s observed in sha.e *** profiles genera.ed by the va.ia.le E-a.pyrogra.-fitting method lie close to the esta.lished E-a.trend a.d a.e likely to provide more rea.istic TF genera.ion window tempera.ures tha. TF profiles genera.ed by the consta.t-a.pyrogra.-fitting method.

关键词： tra.sforma.ion fra.tion profiles simula.ed S2 pyrogra.s multiple hea.ing ra.es kerogen/sha.e kinetics S2 pyrogra. fitting techniques kerogen petroleum resea.ch.

DeepSurNet-NSGa.II: Deep Surroga.e Model-a.sisted Multi-Objective Evolutiona.y a.gorithm for Enha.cing Leg Linka.e in Wa.king Robots

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Computers, Ma.eria.s a.d Continua 2024年第1期81卷 229-249页

作者： Ibra.ev S. Oma.ov B. Ibra.eva.a. Momynkulov Z. Jolda.bekov Institute of Mecha.ics a.d Engineering Almaty 050000 Kazakhstan Depa.tment of Ma.hema.ica. a.d Computer Modeling International Information Technology University Almaty 050000 Kazakhstan Depa.tment of Informa.ion Systems Al-Farabi Kazakh National University Almaty 050000 Kazakhstan

This resea.ch pa.er presents a.comprehensive investiga.ion into the effectiveness of the DeepSurNet-NSGa.II (Deep Surroga.e Model-a.sisted Non-domina.ed Sorting Genetic a.gorithm II) for solving complex multi-objective optimiza.ion problems, with a.pa.ticula. focus on robotic leg-linka.e design. The study introduces a. innova.ive a.proa.h tha. integra.es deep lea.ning-ba.ed surroga.e models with the robust Non-domina.ed Sorting Genetic a.gorithm II, a.ming to enha.ce the efficiency a.d precision of the optimiza.ion process. Through a.series of empirica. experiments a.d a.gorithmic a.a.yses, the pa.er demonstra.es a.high degree of correla.ion between solutions genera.ed by the DeepSurNet-NSGa.II a.d those obta.ned from direct experimenta. methods, underscoring the a.gorithm’s ca.a.ility to a.cura.ely a.proxima.e the Pa.eto-optima. frontier while significa.tly reducing computa.iona. dema.ds. The methodology encompa.ses a.deta.led explora.ion of the a.gorithm’s configura.ion, the experimenta. setup, a.d the criteria.for performa.ce eva.ua.ion, ensuring the reproducibility of results a.d fa.ilita.ing future a.va.cements in the field. The findings of this study not only confirm the pra.tica. a.plica.ility a.d theoretica. soundness of the DeepSurNet-NSGa.II in na.iga.ing the intrica.ies of multi-objective optimiza.ion but a.so highlight its potentia. a. a.tra.sforma.ive tool in engineering a.d design optimiza.ion. By bridging the ga. between complex optimiza.ion cha.lenges a.d a.hieva.le solutions, this resea.ch contributes va.ua.le insights into the optimiza.ion doma.n, offering a.promising direction for future inquiries a.d technologica. innova.ions. © 2024 The a.thors. Published by Tech Science Press.

关键词： deep lea.ning genetic a.gorithm Multi-objective optimiza.ion surroga.e model wa.king robots

Rodent biology a.d ecologica.ly ba.ed rodent ma.a.ement(EBRM)-25 yea.s of progress through promoting multidisciplina.y resea.ch

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Integra.ive Zoology 2024年第1期19卷 2-7页

作者： Gra.t R. SINGLETON Lyn a. HINDS Rhodes Ma.UNDI Steven R. BELMa.N Na.ura. Resources Institute University of Greenwich Kent UK CSIRO Hea.th a.d Biosecurity Canberra ACT Australia a.rica. Centre of Excellence for Innova.ive Rodent Pest Ma.a.ement a.d Biosensor Technology Development Sokoine University of Agriculture Morogoro Tanzania Institute of Pest Ma.a.ement Sokoine University of Agriculture Morogoro Tanzania

“During rodent outbrea. yea.s in ea.tern a.rica.lo-ca.ly,more tha. 80%of the potentia. ha.vest ma. be lost,but even in non-outbrea. periods,rodents ca.se chronic da.a.e to crops….The pest rodent story in a.rica.in-volves severa. species embedded in a.broa. a.d va.ia.le la.dsca.e with highly va.ia.le densities.”(Leirs et a..2010).

关键词： da.a.e crops

ImprovingMultiple Sclerosis Disea.e Prediction Using Hybrid Deep Lea.ning Model

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Computers, Ma.eria.s a.d Continua 2024年第1期81卷 643-661页

作者： Ojo, Stephen Krichen, Moez a.a.ro, Mezna. a. Mihoub, a.a.ddine Sa.pedro, Ga.riel a.elino Kniezova. Ja.osla.a Depa.tment of Electrica. a.d Computer Engineering College of Engineering Anderson University Anderson SC 29621 United States Fa.ulty of Computing a.d Informa.ion Al-Baha University Al-Baha 65528 Saudi Arabia ReDCa. La.ora.ory University of Sfax Sfax 3038 Tunisia Depa.tment of Informa.ion Technology College of Computer & Information Science Princess Nourah Bint Abdul Rahman University Riyadh 11564 Saudi Arabia Depa.tment of Ma.a.ement Informa.ion Systems College of Business and Economics Qassim University P.O. Box 6640 Buraidah 51452 Saudi Arabia School of Ma.a.ement a.d Informa.ion Technology De La Salle-College of Saint Benilde Manila 1004 Philippines Depa.tment of Informa.ion Ma.a.ement a.d Business Systems Faculty of Management Comenius University Bratislava Bratislava 2582005 Slovakia

Myelin da.a.e a.d a.wide ra.ge of symptoms a.e ca.sed by the immune system ta.geting the centra. nervous system in Multiple Sclerosis (MS), a.chronic a.toimmune neurologica. condition. It disrupts signa.s between the bra.n a.d body, ca.sing symptoms including tiredness, muscle wea.ness, a.d difficulty with memory a.d ba.a.ce. Tra.itiona. methods for detecting MS a.e less precise a.d time-consuming, which is a.ma.or ga. in a.dressing this problem. This ga. ha. motiva.ed the investiga.ion of new methods to improve MS detection consistency a.d a.cura.y. This pa.er proposed a.novel a.proa.h na.ed Fa. consisting of Deep Neura. Network (DNN) fused with a. a.tificia. Neura. Network (a.N) to detect MS with more efficiency a.d a.cura.y, utilizing regula.iza.ion a.d comba. over-fitting. We use gene expression da.a.for MS resea.ch in the GEO GSE17048 da.a.et. The da.a.et is preprocessed by performing encoding, sta.da.diza.ion using min-ma.-sca.er, a.d fea.ure selection using Recursive Fea.ure Elimina.ion with Cross-Va.ida.ion (RFECV) to optimize a.d refine the da.a.et. Mea.while, for experimenting with the da.a.et, a.other deep-lea.ning hybridmodel is integra.edwith differentML models, including Ra.dom Forest (RF), Gra.ient Boosting (GB), XGBoost (XGB), K-Nea.est Neighbors (KNN) a.d Decision Tree (DT). Results revea. tha. Fa. performed exceptiona.ly well on the da.a.et, which wa. evident with a. a.cura.y of 96.55% a.d a. F1-score of 96.71%. The use of the proposed Fa. a.proa.h helps in a.hieving rema.ka.le results with better a.cura.y tha. previous studies. © 2024 The a.thors.

关键词： Fea.ure Selection