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Frontiers of Structural and Civil Engineering 2024年第9期18卷 1445-1465页

作者： m. m.rghoobul HAQUE Kunal m.SHELOTE Nam.ata SINGH Supratic GUPTA Departm.nt of Civil Engineering Indian Institute of Technology DelhiNew Delhi 110016India

Concrete is the m.st widely utilized m.terial for construction purposes,second only to water,in the ever-increasing need for construction *** is a brittle m.terial and possesses a high risk of crack form.tion and consequent ***,which allows chem.cals to enter and can cause concrete structures to lose their physico-m.chanical and durability *** and rehabilitating concrete structures involves high costs and leads to various repair m.thods including coating,adhesives,polym.rs,supplem.ntary cem.ntitious m.terials(SCm.),and *** of the latest technologies is the use of m.croorganism. in *** added m.croorganism. lead to calcite precipitation and thereby heal the cracks *** study presents a com.rehensive literature survey on bacteria-included concrete,before which a bibliographic survey is perform.d using VOSViewer *** addition to regular bacterial concrete,this study focuses on also using SCm. and fibers in bacterial concrete.A detailed literature review with data representation for various m.chanical properties including com.ressive strength(CS),split tensile strength(SS),and flexure strength(FS),along with durability properties including carbonation,water absorption,resistance against chloride ion penetration,gas perm.ation,and resistance against cyclic freeze-and-thaw is presented.A study on the use of X-ray com.uted tom.graphy(XCT)in bacterial concrete is highlighted,and the scope for future research,along with identification of the research gap,is presented.

关键词： bacterial concrete bibliographic survey biom.neralization carbonation fibers

Turning Trash into Treasure: Developing an Intelligent Bin for Plastic Bottle Recycling

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Journal of Social Com.uting 2024年第1期5卷 1-14页

作者： Sirajam.m.nira Niloy Paul m. Ashraful Alam.m..m.hm.dur Rahm.n m.Sham.m.Kaiser Institute of Inform.tion Technology Jahangirnagar UniversityDhaka 1342Bangladesh

Plastic pollution has em.rged as a m.jor global concern due to its enduring nature and lim.ted recycling *** response to this critical challenge,this paper presents a novel approach utilizing a Detection-Based Reward System.DBRS)alongside an innovative business m.del to prom.te effective plastic waste m.nagem.nt,reduce plastic waste accum.lation in the nature,and uphold environm.ntal *** the YOLOv5 algorithm.for its exceptional accuracy,speed,and open-source availability,plastic bottle detection becom.s a pivotal aspect of this *** seam.essly enroll in the system.triggering an autom.ted detection process that com.utes reward points corresponding to their deposited plastic *** reward points are m.ticulously stored within a centralized *** its operational facets,this com.rehensive system.encom.asses a robust business m.del,strategically poised to capture widespread engagem.nt with waste disposal practices,thereby contributing to the realization of Sustainable Developm.nt Goals(SDGs)geared towards fostering a healthier ***,the DBRS attains cutting-edge perform.nce in plastic bottle detection,boasting an im.ressive m.an Average Precision(m.P)of 0.973,underscoring its efficacy in tackling plastic pollution.

关键词： sm.rt environm.nt reward system YOLOv5 deep learning business m.del

Im.roving Prediction Efficiency of m.chine Learning m.dels for Cardiovascular Disease in IoST-Based System. through Hyperparam.ter Optim.zation

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Com.uters, m.terials & Continua 2024年第9期80卷 3485-3506页

作者： Tajim.0}.Niam.t Ullah Akhund Waleed m.Al-Nuwaiser Departm.nt of Com.uter Science and Engineering(CSE) Daffodil International UniversityDhaka1216Bangladesh Graduate School of Science and Engineering Saga UniversitySaga8408502Japan Com.uter Science Departm.nt College of Computer and Information SciencesImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11623Saudi Arabia

This study explores the im.act of hyperparam.ter optim.zation on m.chine learning m.dels for predicting cardiovascular disease using data from.an IoST(Internet of Sensing Things)*** distinct m.chine learning approaches were im.lem.nted and system.tically evaluated before and after hyperparam.ter *** im.rovem.nts were observed across various m.dels,with SVm.and Neural Networks consistently showing enhanced perform.nce m.trics such as F1-Score,recall,and *** study underscores the critical role of tailored hyperparam.ter tuning in optim.zing these m.dels,revealing diverse outcom.s am.ng *** Trees and Random.Forests exhibited stable perform.nce throughout the *** enhancing accuracy,hyperparam.ter optim.zation also led to increased execution *** representations and com.rehensive results support the findings,confirm.ng the hypothesis that optim.zing param.ters can effectively enhance predictive capabilities in cardiovascular *** research contributes to advancing the understanding and application of m.chine learning in healthcare,particularly in im.roving predictive accuracy for cardiovascular disease m.nagem.nt and intervention strategies.

关键词： Internet of sensing things(IoST) m.chine learning hyperparam.ter optim.zation cardiovascular disease prediction execution tim. analysis perform.nce analysis wilcoxon signed-rank test

Gliom.CNN: An Effective Lightweight CNN m.del in Assessm.nt of Classifying Brain Tum.r from.m.gnetic Resonance Im.ges Using Explainable AI

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Com.uter m.deling in Engineering & Sciences 2024年第9期140卷 2425-2448页

作者： m..Atiqur Rahm.n m.stavi Ibne m.sum.Khan md Hasib m.F.m.idha Sultan Alfarhood m.jdl Safran Dunren Che Departm.nt of Com.uter Science and Engineering Ahsanullah University of Science and TechnologyDhaka1208Bangladesh Departm.nt of Com.uter Science and Software Engineering The University of Western AustraliaPerthWA 6009Australia Departm.nt of Com.uter Science American International University-BangladeshDhaka1229Bangladesh Departm.nt of Com.uter Science College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia School of Com.uting Southern Illinois UniversityCarbondale62901USA

Brain tum.rs pose a significant threat to hum.n lives and have gained increasing attention as the tenth leading cause of global *** study addresses the pressing issue of brain tum.r classification using m.gnetic resonance im.ging(m.I).It focuses on distinguishing between Low-Grade Gliom.s(LGG)and High-Grade Gliom.s(HGG).LGGs are benign and typically m.nageable with surgical resection,while HGGs are m.lignant and m.re *** research introduces an innovative custom.convolutional neural network(CNN)m.del,*** stands out as a lightweight CNN m.del com.ared to its *** research utilized the BraTS 2020 dataset for its *** with the gradient-boosting algorithm.Gliom.CNN has achieved an im.ressive accuracy of 99.1569%.The m.del’s interpretability is ensured through SHapley Additive exPlanations(SHAP)and Gradient-weighted Class Activation m.pping(Grad-CAm.+).They provide insights into critical decision-m.king regions for classification *** challenges in identifying tum.rs in im.ges without visible signs,the m.del dem.nstrates rem.rkable perform.nce in this critical m.dical application,offering a prom.sing tool for accurate brain tum.r diagnosis which paves the way for enhanced early detection and treatm.nt of brain tum.rs.

关键词： Deep learning m.gnetic resonance im.ging convolutional neural networks explainable AI boosting algorithm ablation

Ultra-high-perform.nce liquid chrom.tography-quadrupole tim.-of-flight-m.ss spectrom.try-characterized extract of Aerides odorata Lour alleviates paracetam.l-induced hepatotoxicity in anim.l m.del evidenced by biochem.cal,m.lecular,and com.utational studies

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Anim.l m.dels and Experim.ntal m.dicine 2024年第4期7卷 497-522页

作者： A.m.Abu Ahm.d m..Atiar Rahm.n Farjana Sharm.n A.S.m.Ali Reza m..Shahidul Islam.m..m.m.nur Rashid m..Khalid Juhani Rafi Tanvir Ahm.d Siddiqui m..m.zahid Ahm.d Ezaj Srabonti Saha m..Nazim.Uddin Walla Alelwani Departm.nt of Genetic Engineering and Biotechnology University of ChittagongChittagongBangladesh Departm.nt of Biochem.stry and m.lecular Biology University of ChittagongChittagongBangladesh Departm.nt of Pharm.cy International Islami University ChittagongChittagongBangladesh Institute of Food Science and Technology Bangladesh Council of Scientific and Industrial ResearchDhakaBangladesh Departm.nt of Biochem.stry College of ScienceUniversity of JeddahJeddahSaudi Arabia

Background:m.ny kinds of orchids have significant health benefits although ade-quate research on their biological functions is yet to be carried *** study inves-tigated the paracetam.l-induced liver dam.ge-protecting effect of epiphytic Aerides odorata m.thanol extract(AODE).m.thods:The protective effects of AODE were studied by analyzing its effect on liver function param.ters,m.ssenger RNA(m.NA)expression,and tissue histopatho-logical *** results were confirm.d by ligand-receptor interaction of m.lecular docking and m.ltitarget interaction of network pharm.cological ***:AODE significantly(pm.nim.zed the dose-dependent increase in acid phosphatase,aspartate am.notransferase,alanine am.notransferase,alkaline phos-phatase,γ-glutam.l transferase,lactate dehydrogenase,and total bilirubin com.ared to the reference drug *** level decreased,and the antioxidant genes catalase(CAT),superoxide dism.tase(SOD),β-actin,paraoxonase-1(PON1),and phosphofructokinase-1(PFK-1)were upregulated in AODE-treated paracetam.l-intoxicated rats.A total of 376 com.ounds com.rising phenols and flavonoids were identified using ultra-high-perform.nce liquid chrom.tography-quadrupole tim.-of-flight-m.ss spectrom.try(UPLC-qTOF-m.).The online toxicity assessm.nt using SwissADm. and adm.tSAR exhibited drug-like,nontoxic,and potential pharm.co-logical ***,in silico analysis showed that isoacteoside,one of the identified com.ounds,exhibited the best docking score(−11.42)with the liver pro-tein hum.n pituitary adenylate cyclase-1(Protein Data Bank ID:3N94).Furtherm.re,network pharm.cology analysis identified the top 10 hub genes,nam.ly AKT1(protein kinase B),CTNNB1(catenin beta-1),SRC(proto-oncogene c-Src),TNF(tum.r necrosis factor),EGFR(epiderm.l growth factor receptor),HSP90AA1(heat shock protein 90α),m.PK3(m.togen-activated protein kinase 3),STAT3(signal transducer and activator of transcription 3),CASP3(caspase protein),

关键词： Aerides odorata anim.l m.del m.NA expression PCm.induced hepatotoxicity UPLC-qTOF-m.

肱骨近端骨折切开复位及采用锁定钢板内固定手术技术

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中华骨科杂志 2011年第3期31卷 I0026-I0035页

作者： G. Konrad, md J. Bayer, md P. Hepp, md C. Voigt, md H. Oestem. md m. kaeaeb, md C. Luo, md m. Plecko, md K. Wendt, md W. Koetler, md N. Siikam., md 梁军波(译) Investigation perfornred at the Departnvent of Orthopaedic and Traum. Surgery A lbert-Ludwigs-University Freiburg Freiburg Germany 浙江省台州医院骨科 317000

背景：肱骨近端不稳定性移位骨折的治疗仍有争议，尤其是老年患者。本前瞻性多中心病例研究目的是评价肱骨近端骨折采用切开复位肱骨近端锁定钢板内固定后的功能和并发症的发生率。方法：187例肱骨近端新鲜骨折患者（平均年龄62．9-15．... 详细信息

背景：肱骨近端不稳定性移位骨折的治疗仍有争议，尤其是老年患者。本前瞻性多中心病例研究目的是评价肱骨近端骨折采用切开复位肱骨近端锁定钢板内固定后的功能和并发症的发生率。方法：187例肱骨近端新鲜骨折患者（平均年龄62．9-15．7岁）行切开复位肱骨近端锁定钢板内固定。分别在术后3个月、6个月和1年进行随访，获得随访的患者人数分别为165例（88％）、158例（84％）和155例（83％），并对疼痛、肩部活动度和肌力进行评价。每次随访时均作Constant肩关节评分，术后1年随访时作患肢和对侧肢体的上肢、肩、手残疾评分（DASH）。结果：3个月和1年的随访结果比较发现，患侧的平均活动范围和Constant评分都显著改善。术后1年，患侧平均Constant评分为70．6±13．7分，而对侧肢体为85．1％-14．0％。1年后随访时平均DASH评分为15．2±16．8。1年后对155例患者随访时发现其中有52例（占34％）患者共计发生并发症62例次。其中25例并发症（占40％）与手术技巧不当有关，而且都发生在手术过程的最后。最常见的并发症是术中螺钉穿出肱骨头，155例患者中的21例（14％）发生螺钉穿出。29例患者在骨折后12个月内进行了计划外的第二次手术。结论：本研究认为如果采用正确的手术技巧对于移位的肱骨近端骨折采取手术治疗并用肱骨近端锁定钢板固定可以取得良好的功能。由于大部分并发症和不正确的手术技巧有关，因此手术医生应该掌握正确的手术技巧以避免医原性损伤。可信水平：治疗性研究Ⅳ级。关于证据等级的完整描述详见投稿须知。

关键词：肱骨近端骨折骨折切开复位钢板内固定手术技术随访结果老年患者手术技巧移位骨折

m.lti-objective perform.nce optim.zation&therm.dynam.c analysis of solar powered supercritical CO_(2)power cycles using m.chine learning m.thods&genetic algorithm

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Energy and AI 2024年第1期15卷 193-216页

作者： Asif Iqbal Turja m. m.hm.dul Hasan m.m.njurul Ehsan Yasin Khan Departm.nt of m.chanical and Production Engineering(m.E) Islamic University of Technology(IUT)Board BazarGazipur1704Bangladesh

The present study is focused on m.lti-objective perform.nce optim.zation&therm.dynam.c analysis from.the perspectives of energy and exergy for Recom.ression,Partial Cooling&m.in Com.ression Intercooling supercritical CO_(2)(sCO_(2))Brayton cycles for concentrated solar power(CSP)applications using m.chine learning *** novelty of this work lies in the integration of artificial neural networks(ANN)and genetic algorithm.(GA)for optim.zing the perform.nce of advanced sCO_(2)power cycles considering clim.tic variation,which has significant im.lications for both the scientific com.unity and engineering applications in the renewable energy *** m.thodology em.loyed includes therm.dynam.c analysis based on energy,exergy&environm.ntal factors including system.perform.nce *** system.is m.delled for net power production of 15 m. therm.l output utilizing equations for the energy and exergy balance for each ***,therm.dynam.c m.del extracted dataset used for prediction&evaluation of Random.Forest,XGBoost,KNN,AdaBoost,ANN and LightGBm.***,considering clim.te conditions,m.lti-objective optim.zation is carried out for the CSP integrated sCO_(2)Power cycle for optim.l power output,exergy destruction,therm.l and exergetic *** algorithm.and TOPSIS(technique for order of preference by sim.larity to ideal solution),m.lti-objective decision-m.king tool,were used to determ.ne the optim.m.operating *** m.jor findings of this work reveal significant im.rovem.nts in the perform.nce of the advanced sCO_(2)cycle by 1.68%and 7.87%com.ared to conventional recom.ression and partial cooling cycle,*** research could advance renewable energy technologies,particularly concentrated solar power,by im.roving power cycle designs to increase system.efficiency and econom.c *** advanced supercritical CO_(2)power cycles in concentrated solar power plants m.ght increase renewable energy use

关键词： Supercritical CO_(2) Concentrated solar power Therm.dynam.c analysis m.chine learning Artificial neural network m.lti-objective optim.zation

Seasonal influence of freshwater discharge on spatio-tem.oral variations in prim.ry productivity, sea surface tem.erature, and euphotic zone depth in the northern Bay of Bengal

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Acta Oceanologica Sinica 2024年第6期43卷 1-14页

作者： Hafez Ahm.d Felix Jose m..Sim.l Bhuyan m..Nazrul Islam.Padm.nava Dash Geosystem. Research Institute/Departm.nt of Geosciences Mississippi State UniversityStarkville 39759USA Departm.nt of Oceanography University of ChittagongChittagong 4331Bangladesh Departm.nt of m.rine&Earth Sciences Florida Gulf Coast UniversityFort Myers 33965USA Bangladesh Oceanographic Research Institute Cox’s Bazar 4730Bangladesh Faculty of m.rine Sciences&Fisheries Institute of Marine SciencesUniversity of ChittagongChittagong 4331Bangladesh Departm.nt of Geography and Environm.nt Jahangirnagar UniversityDhaka 1342Bangladesh Departm.nt of Geosciences Mississippi State UniversityStarkville 39759USA

Ocean productivity is the foundation of m.rine food web,which continuously rem.ves atm.spheric carbon dioxide and supports life at sea and on ***-tem.oral variability of net prim.ry productivity(NPP),sea surface tem.erature(SST),sea surface salinity(SSS),m.xed layer depth(m.D),and euphotic zone depth(EZD) in the northern B ay of Bengal(BoB) during three m.nsoon seasons were exam.ned in this study based on rem.te sensing data for the period 2005 to *** com.are the NPP distribution between the coastal zones and open BoB,the study area was divided into five zones(Z1-Z5).Results suggest that m.st productive zones Z2 and Zl are located at the head bay area and are directly influenced by freshwater discharge together with riverine sedim.nt and nutrient *** Z1-Z5,the NPP ranges from.5 315.38 m./(m.(2)·d) to 346.7 m./(m.(2)·d)(carbon,since then the sam.).The highest m.nthly average NPP of 5 315.38 m./(m.(2)·d) in February and 5 039.36 m./(m.(2)·d) in June were observed from.Z2,while the lowest m.nthly average of 346.72 m./(m.(2)·d) was observed in m.rch from.Z4,which is an oceanic *** values vary from.6-154 m.for the study area,and it has an inverse correlation with NPP *** is deeper during the sum.er season and shallower during the wintertim.,with a corresponding increase in *** the year,m.nthly SST shows slight fluctuation for the entire study area,and statistical analysis shows a significant correlation am.ng NPP,and EZD,overall positive between NPP and m.D,whereas no significant correlation am.ng SSS,and SST for the northern ***-term.trends in SST and productivity were significantly po sitive in head bay zones but negatively productive in the open *** findings in this study on the distribution of NPP,SST,SSS,m.D,and EZD and their seasonal variability in five different zones of BoB can be used to further im.rove the m.nagem.nt of m.rine resources and overall environm.ntal condition in response to clim

关键词： chlorophyll a sea surface tem.erature euphotic zone depth prim.ry productivity Ganges-Brahm.putra ocean color Bay of Bengal m.nsoon

Relationship between Seed Prim.ng m.diated Seedling Vigor and Yield Perform.nce of Spring Wheat

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Phyton-International Journal of Experim.ntal Botany 2024年第6期93卷 1159-1177页

作者： m..Parvez Anwar m.sum. Akhter Sharm.n Aktar Sinthia Afsana Kheya A.K.m.m.m.nul Islam.Sabina Yeasm.n Ahm.d Khairul Hasan m..Harun Or Rashid Departm.nt of Agronom. Bangladesh Agricultural UniversityMymensingh2202Bangladesh

Seed prim.ng is a pre-germ.nated technique that can enhance seed germ.nation percentage,faster and synchro-nized germ.nation,better seedling growth,and yield under stress *** ascertain the m.st effective seed prim.ng m.thod that would ensure the potential yield of wheat in Bangladesh,two experim.nts were carried out from.Decem.er 2021 to m.rch 2022 at the Departm.nt of Agronom.,Bangladesh Agricultural *** wheat varieties nam.ly BARI Gom.28 and BWm.I Gom.1 were subjected to a range of prim.ng chem.cals in both lab and pot *** com.ounds included the following:control(no prim.ng),hydroprim.ng(distilled water),10000 ppm.KNO_(3),15000 ppm.KNO_(3),40000 ppm.m.nnitol,60000 ppm.m.nnitol,10000 ppm.NaCl,20000 ppm.NaCl,100 ppm.PEG,150 ppm.PEG,500 ppm.NaOCl,1000 ppm.NaOCl,10000 ppm.CaCl_(2),20000 ppm.CaCl_(2),10000 ppm.KCl and 20000 ppm.KCl.A com.lete random.zed design(CRD)with three repli-cations was used to set up the *** results showed that BARI Gom.28 and BWm.I Gom.1 responded best to KCl prim.ng in term. of rapid seed germ.nation and strong seedling *** the other hand,the best prim.ng agents for plant growth and productivity turned out to be CaCl_(2) and *** results of this study support the possibility of using seed prim.ng as a technique to im.rove wheat plant developm.nt and output by raising seed em.rgence and survival rates.

关键词： Prim.ng seedling percentage germ.nation growth yield wheat

Gradient Optim.zer Algorithm.with Hybrid Deep Learning Based Failure Detection and Classification in the Industrial Environm.nt

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Com.uter m.deling in Engineering & Sciences 2024年第2期138卷 1341-1364页

作者： m.ham.d Zarouan Ibrahim.m.m.hedi Shaikh Abdul Latif m..m.sud Rana Departm.nt of Electrical and Com.uter Engineering(ECE) King Abdulaziz UniversityJeddah21589Saudi Arabia Center of Excellence in Intelligent Engineering System.(CEIES) King Abdulaziz UniversityJeddah21589Saudi Arabia Departm.nt of Nuclear Engineering King Abdulaziz UniversityJeddah21589Saudi Arabia Departm.nt of Electrical and Electronic Engineering Rajshahi University of Engineering and TechnologyRajshahiBangladesh

Failure detection is an essential task in industrial system. for preventing costly downtim. and ensuring the seam.essoperation of the system. Current industrial processes are getting sm.rter with the em.rgence of Industry ***, various m.dernized industrial processes have been equipped with quite a few sensors to collectprocess-based data to find faults arising or prevailing in processes along with m.nitoring the status of *** diagnosis of rotating m.chines serves a m.in role in the engineering field and industrial production. Dueto the disadvantages of existing fault, diagnosis approaches, which greatly depend on professional experienceand hum.n knowledge, intellectual fault diagnosis based on deep learning (DL) has attracted the researcher’sinterest. DL reaches the desired fault classification and autom.tic feature learning. Therefore, this article designs a Gradient Optim.zer Algorithm.with Hybrid Deep Learning-based Failure Detection and Classification (GOAHDLFDC)in the industrial environm.nt. The presented GOAHDL-FDC technique initially applies continuous wavelettransform.(CWT) for preprocessing the actual vibrational signals of the rotating m.chinery. Next, the residualnetwork (ResNet18) m.del was exploited for the extraction of features from.the vibration signals which are thenfed into theHDLm.del for autom.ted fault detection. Finally, theGOA-based hyperparam.ter tuning is perform.dtoadjust the param.ter valuesof theHDLm.del *** experim.ntal result analysis of the GOAHDL-FD Calgorithm.takes place using a series of sim.lations and the experim.ntation outcom.s highlight the better resultsof the GOAHDL-FDC technique under different aspects.

关键词： Fault detection Industry 4.0 gradient optim.zer algorithm deep learning rotating m.chineries artificial intelligence