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

作者： md marghoobul HAQUE Kunal m.SHELOTE Namrata SINGH Supratic GUPTA Department of Civil Engineering Indian Institute of Technology DelhiNew Delhi 110016India

Concrete is the most widely utilized material for construction purposes,second only to water,in the ever-increasing need for construction *** is a brittle material and possesses a high risk of crack formation and consequent ***,which allows chemicals to enter and can cause concrete structures to lose their physico-mechanical and durability *** and rehabilitating concrete structures involves high costs and leads to various repair methods including coating,adhesives,polymers,supplementary cementitious materials(SCms),and *** of the latest technologies is the use of microorganisms in *** added microorganisms lead to calcite precipitation and thereby heal the cracks *** study presents a comprehensive literature survey on bacteria-included concrete,before which a bibliographic survey is performed using VOSViewer *** addition to regular bacterial concrete,this study focuses on also using SCms and fibers in bacterial concrete.A detailed literature review with data representation for various mechanical properties including compressive strength(CS),split tensile strength(SS),and flexure strength(FS),along with durability properties including carbonation,water absorption,resistance against chloride ion penetration,gas permeation,and resistance against cyclic freeze-and-thaw is presented.A study on the use of X-ray computed tomography(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 biomineralization carbonation fibers

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

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Journal of Social Computing 2024年第1期5卷 1-14页

作者： Sirajam munira Niloy Paul md Ashraful Alam md.mahmudur Rahman m.Shamim Kaiser Institute of Information Technology Jahangirnagar UniversityDhaka 1342Bangladesh

Plastic pollution has emerged as a major global concern due to its enduring nature and limited recycling *** response to this critical challenge,this paper presents a novel approach utilizing a Detection-Based Reward System(DBRS)alongside an innovative business model to promote effective plastic waste management,reduce plastic waste accumulation in the nature,and uphold environmental *** the YOLOv5 algorithm for its exceptional accuracy,speed,and open-source availability,plastic bottle detection becomes a pivotal aspect of this *** seamlessly enroll in the system,triggering an automated detection process that computes reward points corresponding to their deposited plastic *** reward points are meticulously stored within a centralized *** its operational facets,this comprehensive system encompasses a robust business model,strategically poised to capture widespread engagement with waste disposal practices,thereby contributing to the realization of Sustainable Development Goals(SDGs)geared towards fostering a healthier ***,the DBRS attains cutting-edge performance in plastic bottle detection,boasting an impressive mean Average Precision(mAP)of 0.973,underscoring its efficacy in tackling plastic pollution.

关键词： smart environment reward system YOLOv5 deep learning business model

Improving Prediction Efficiency of machine Learning models for Cardiovascular Disease in IoST-Based Systems through Hyperparameter Optimization

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Computers, materials & Continua 2024年第9期80卷 3485-3506页

作者： Tajim md.Niamat Ullah Akhund Waleed m.Al-Nuwaiser Department of Computer Science and Engineering(CSE) Daffodil International UniversityDhaka1216Bangladesh Graduate School of Science and Engineering Saga UniversitySaga8408502Japan Computer Science Department College of Computer and Information SciencesImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11623Saudi Arabia

This study explores the impact of hyperparameter optimization on machine learning models for predicting cardiovascular disease using data from an IoST(Internet of Sensing Things)*** distinct machine learning approaches were implemented and systematically evaluated before and after hyperparameter *** improvements were observed across various models,with SVm and Neural Networks consistently showing enhanced performance metrics such as F1-Score,recall,and *** study underscores the critical role of tailored hyperparameter tuning in optimizing these models,revealing diverse outcomes among *** Trees and Random Forests exhibited stable performance throughout the *** enhancing accuracy,hyperparameter optimization also led to increased execution *** representations and comprehensive results support the findings,confirming the hypothesis that optimizing parameters can effectively enhance predictive capabilities in cardiovascular *** research contributes to advancing the understanding and application of machine learning in healthcare,particularly in improving predictive accuracy for cardiovascular disease management and intervention strategies.

关键词： Internet of sensing things(IoST) machine learning hyperparameter optimization cardiovascular disease prediction execution time analysis performance analysis wilcoxon signed-rank test

GliomaCNN: An Effective Lightweight CNN model in Assessment of Classifying Brain Tumor from magnetic Resonance Images Using Explainable AI

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Computer modeling in Engineering & Sciences 2024年第9期140卷 2425-2448页

作者： md.Atiqur Rahman mustavi Ibne masum Khan md Hasib m.F.mridha Sultan Alfarhood mejdl Safran Dunren Che Department of Computer Science and Engineering Ahsanullah University of Science and TechnologyDhaka1208Bangladesh Department of Computer Science and Software Engineering The University of Western AustraliaPerthWA 6009Australia Department of Computer Science American International University-BangladeshDhaka1229Bangladesh Department of Computer Science College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia School of Computing Southern Illinois UniversityCarbondale62901USA

Brain tumors pose a significant threat to human lives and have gained increasing attention as the tenth leading cause of global *** study addresses the pressing issue of brain tumor classification using magnetic resonance imaging(mRI).It focuses on distinguishing between Low-Grade Gliomas(LGG)and High-Grade Gliomas(HGG).LGGs are benign and typically manageable with surgical resection,while HGGs are malignant and more *** research introduces an innovative custom convolutional neural network(CNN)model,*** stands out as a lightweight CNN model compared to its *** research utilized the BraTS 2020 dataset for its *** with the gradient-boosting algorithm,GliomaCNN has achieved an impressive accuracy of 99.1569%.The model’s interpretability is ensured through SHapley Additive exPlanations(SHAP)and Gradient-weighted Class Activation mapping(Grad-CAm++).They provide insights into critical decision-making regions for classification *** challenges in identifying tumors in images without visible signs,the model demonstrates remarkable performance in this critical medical application,offering a promising tool for accurate brain tumor diagnosis which paves the way for enhanced early detection and treatment of brain tumors.

关键词： Deep learning magnetic resonance imaging convolutional neural networks explainable AI boosting algorithm ablation

Ultra-high-performance liquid chromatography-quadrupole time-of-flight-mass spectrometry-characterized extract of Aerides odorata Lour alleviates paracetamol-induced hepatotoxicity in animal model evidenced by biochemical,molecular,and computational studies

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Animal models and Experimental medicine 2024年第4期7卷 497-522页

作者： A.m.Abu Ahmed md.Atiar Rahman Farjana Sharmen A.S.m.Ali Reza md.Shahidul Islam md.mamunur Rashid md.Khalid Juhani Rafi Tanvir Ahmed Siddiqui md.muzahid Ahmed Ezaj Srabonti Saha md.Nazim Uddin Walla Alelwani Department of Genetic Engineering and Biotechnology University of ChittagongChittagongBangladesh Department of Biochemistry and molecular Biology University of ChittagongChittagongBangladesh Department of Pharmacy International Islami University ChittagongChittagongBangladesh Institute of Food Science and Technology Bangladesh Council of Scientific and Industrial ResearchDhakaBangladesh Department of Biochemistry College of ScienceUniversity of JeddahJeddahSaudi Arabia

Background:many kinds of orchids have significant health benefits although ade-quate research on their biological functions is yet to be carried *** study inves-tigated the paracetamol-induced liver damage-protecting effect of epiphytic Aerides odorata methanol extract(AODE).methods:The protective effects of AODE were studied by analyzing its effect on liver function parameters,messenger RNA(mRNA)expression,and tissue histopatho-logical *** results were confirmed by ligand-receptor interaction of molecular docking and multitarget interaction of network pharmacological ***:AODE significantly(pminimized the dose-dependent increase in acid phosphatase,aspartate aminotransferase,alanine aminotransferase,alkaline phos-phatase,γ-glutamyl transferase,lactate dehydrogenase,and total bilirubin compared to the reference drug *** level decreased,and the antioxidant genes catalase(CAT),superoxide dismutase(SOD),β-actin,paraoxonase-1(PON1),and phosphofructokinase-1(PFK-1)were upregulated in AODE-treated paracetamol-intoxicated rats.A total of 376 compounds comprising phenols and flavonoids were identified using ultra-high-performance liquid chromatography-quadrupole time-of-flight-mass spectrometry(UPLC-qTOF-mS).The online toxicity assessment using SwissADmE and admetSAR exhibited drug-like,nontoxic,and potential pharmaco-logical ***,in silico analysis showed that isoacteoside,one of the identified compounds,exhibited the best docking score(−11.42)with the liver pro-tein human pituitary adenylate cyclase-1(Protein Data Bank ID:3N94).Furthermore,network pharmacology analysis identified the top 10 hub genes,namely AKT1(protein kinase B),CTNNB1(catenin beta-1),SRC(proto-oncogene c-Src),TNF(tumor necrosis factor),EGFR(epidermal growth factor receptor),HSP90AA1(heat shock protein 90α),mAPK3(mitogen-activated protein kinase 3),STAT3(signal transducer and activator of transcription 3),CASP3(caspase protein),

关键词： Aerides odorata animal model mRNA expression PCm-induced hepatotoxicity UPLC-qTOF-mS

Seasonal influence of freshwater discharge on spatio-temporal variations in primary productivity, sea surface temperature, 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 Ahmad Felix Jose md.Simul Bhuyan md.Nazrul Islam Padmanava Dash Geosystems Research Institute/Department of Geosciences Mississippi State UniversityStarkville 39759USA Department of Oceanography University of ChittagongChittagong 4331Bangladesh Department of marine&Earth Sciences Florida Gulf Coast UniversityFort Myers 33965USA Bangladesh Oceanographic Research Institute Cox’s Bazar 4730Bangladesh Faculty of marine Sciences&Fisheries Institute of Marine SciencesUniversity of ChittagongChittagong 4331Bangladesh Department of Geography and Environment Jahangirnagar UniversityDhaka 1342Bangladesh Department of Geosciences Mississippi State UniversityStarkville 39759USA

Ocean productivity is the foundation of marine food web,which continuously removes atmospheric carbon dioxide and supports life at sea and on ***-temporal variability of net primary productivity(NPP),sea surface temperature(SST),sea surface salinity(SSS),mixed layer depth(mLD),and euphotic zone depth(EZD) in the northern B ay of Bengal(BoB) during three monsoon seasons were examined in this study based on remote sensing data for the period 2005 to *** compare the NPP distribution between the coastal zones and open BoB,the study area was divided into five zones(Z1-Z5).Results suggest that most productive zones Z2 and Zl are located at the head bay area and are directly influenced by freshwater discharge together with riverine sediment and nutrient *** Z1-Z5,the NPP ranges from 5 315.38 mg/(m^(2)·d) to 346.7 mg/(m^(2)·d)(carbon,since then the same).The highest monthly average NPP of 5 315.38 mg/(m^(2)·d) in February and 5 039.36 mg/(m^(2)·d) in June were observed from Z2,while the lowest monthly average of 346.72 mg/(m^(2)·d) was observed in march 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 summer season and shallower during the wintertime,with a corresponding increase in *** the year,monthly SST shows slight fluctuation for the entire study area,and statistical analysis shows a significant correlation among NPP,and EZD,overall positive between NPP and mLD,whereas no significant correlation among 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,mLD,and EZD and their seasonal variability in five different zones of BoB can be used to further improve the management of marine resources and overall environmental condition in response to clim

关键词： chlorophyll a sea surface temperature euphotic zone depth primary productivity Ganges-Brahmaputra ocean color Bay of Bengal monsoon

Relationship between Seed Priming mediated Seedling Vigor and Yield Performance of Spring Wheat

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Phyton-International Journal of Experimental Botany 2024年第6期93卷 1159-1177页

作者： md.Parvez Anwar masuma Akhter Sharmin Aktar Sinthia Afsana Kheya A.K.m.mominul Islam Sabina Yeasmin Ahmed Khairul Hasan md.Harun Or Rashid Department of Agronomy Bangladesh Agricultural UniversityMymensingh2202Bangladesh

Seed priming is a pre-germinated technique that can enhance seed germination percentage,faster and synchro-nized germination,better seedling growth,and yield under stress *** ascertain the most effective seed priming method that would ensure the potential yield of wheat in Bangladesh,two experiments were carried out from December 2021 to march 2022 at the Department of Agronomy,Bangladesh Agricultural *** wheat varieties namely BARI Gom-28 and BWmRI Gom-1 were subjected to a range of priming chemicals in both lab and pot *** compounds included the following:control(no priming),hydropriming(distilled water),10000 ppm KNO_(3),15000 ppm KNO_(3),40000 ppm mannitol,60000 ppm mannitol,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 complete randomized design(CRD)with three repli-cations was used to set up the *** results showed that BARI Gom-28 and BWmRI Gom-1 responded best to KCl priming in terms of rapid seed germination and strong seedling *** the other hand,the best priming agents for plant growth and productivity turned out to be CaCl_(2) and *** results of this study support the possibility of using seed priming as a technique to improve wheat plant development and output by raising seed emergence and survival rates.

关键词： Priming seedling percentage germination growth yield wheat

Gradient Optimizer Algorithm with Hybrid Deep Learning Based Failure Detection and Classification in the Industrial Environment

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Computer modeling in Engineering & Sciences 2024年第2期138卷 1341-1364页

作者： mohamed Zarouan Ibrahim m.mehedi Shaikh Abdul Latif md.masud Rana Department of Electrical and Computer Engineering(ECE) King Abdulaziz UniversityJeddah21589Saudi Arabia Center of Excellence in Intelligent Engineering Systems(CEIES) King Abdulaziz UniversityJeddah21589Saudi Arabia Department of Nuclear Engineering King Abdulaziz UniversityJeddah21589Saudi Arabia Department of Electrical and Electronic Engineering Rajshahi University of Engineering and TechnologyRajshahiBangladesh

Failure detection is an essential task in industrial systems for preventing costly downtime and ensuring the seamlessoperation of the system. Current industrial processes are getting smarter with the emergence of Industry ***, various modernized industrial processes have been equipped with quite a few sensors to collectprocess-based data to find faults arising or prevailing in processes along with monitoring the status of *** diagnosis of rotating machines serves a main role in the engineering field and industrial production. Dueto the disadvantages of existing fault, diagnosis approaches, which greatly depend on professional experienceand human knowledge, intellectual fault diagnosis based on deep learning (DL) has attracted the researcher’sinterest. DL reaches the desired fault classification and automatic feature learning. Therefore, this article designs a Gradient Optimizer Algorithm with Hybrid Deep Learning-based Failure Detection and Classification (GOAHDLFDC)in the industrial environment. The presented GOAHDL-FDC technique initially applies continuous wavelettransform (CWT) for preprocessing the actual vibrational signals of the rotating machinery. Next, the residualnetwork (ResNet18) model was exploited for the extraction of features from the vibration signals which are thenfed into theHDLmodel for automated fault detection. Finally, theGOA-based hyperparameter tuning is performedtoadjust the parameter valuesof theHDLmodel *** experimental result analysis of the GOAHDL-FD Calgorithm takes place using a series of simulations and the experimentation outcomes highlight the better resultsof the GOAHDL-FDC technique under different aspects.

关键词： Fault detection Industry 4.0 gradient optimizer algorithm deep learning rotating machineries artificial intelligence

Graphene oxide-coated microbottle resonators for relative humidity sensing

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Optoelectronics Letters 2024年第7期20卷 400-405页

作者： Huda Adnan Zain malathy Batumalay md Ashadi md Johari Hazli Rafis Abdul Rahim Sulaiman Wadi Harun Department of Electrical Engineering Faculty of EngineeringUniversity of MalayaKuala Lumpur 50603Malaysia Faculty of Data Science and Information Technology INTI International UniversityNilai 71800Malaysia1 Faculty of Electrical and Electronic Engineering Technology Universiti Teknikal Malaysia MelakaMelaka 76100Malaysia Faculty of Electronic and Computer Engineering Universiti Teknikal Malaysia MelakaMelaka 76100Malaysia

Graphene oxide(GO)is a 2D coating material used to improve fiber optics sensors’response to relative *** resonators(mBRs)have garnered more attention as sensing media *** mBR with a 190μm diameter was coated with ***,tapered fiber light coupling was used to investigate the relative humidity sensing performance in the range of 35—70%RH at 25℃.The mBR showed a higher Q factor before and after GO *** sensitivity of 0.115 dB/%RH was recorded with the 190μm GO-coated mBR sample compared to a sensitivity of 0.022 dB/%RH for the uncoated mBR *** results show that the mBR can be used in fiber optic sensing applications for environmental sensing.

关键词： humidity oxide bottle

Repercussion of salinity on hematological parameters and tissue morphology of gill and kidney at early life of tilapia

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Aquaculture and Fisheries 2024年第2期9卷 256-264页

作者： Azhar Ali md.gol.m Azom Bhakta Supratim Sarker Hasu Rani md Samsul Alam m.sadiqul islam*department of fisheries biology and genetics bangladesh agricultural universitymymensingh2202bangladesh

This study was attempted to reveal the changes in three hematological parameters such as blood hemoglobin,number of white blood cells(WBCs)and number of red blood cells(RBCs)and one biochemical(e.g.,glucose)parameter along with the changes in histomorphological structures of gills and kidney of Nile tilapia fry reared in saline *** experimental set up were used for two different age groups-5 days-after-hatch(5DAH)and 15 days-after-hatch(15DAH)-to test a novel hypothesis:if a little difference in the age during the first exposure to saline water could produce any variation in the *** were placed into 6 plastic drums having six different salinity levels:0,5,10,15,20 and *** 60 days,at least 5 individuals were taken out from each drum to observe the above-hematological and histomorphological parameters.A two-way-ANOVA revealed that,except for hemoglobin,all the observed parameters have been affected the effect of age×salinity interaction(Pmean glucose value,RBC counts and WBC count at different salinities differed significantly from the base mean value of each *** regard to the histomorphological structure of the gills and kidney,various malformations were *** hypertrophy,epithelial uplifting and epithelial necrosis were present as gill degenerations,hyperplasia was prevalent across almost all salinity *** the other hand,glomerular necrosis,pyknotic nucleus,hyaline droplets degeneration,shrinking of the glomeruli,*** observed in kidney *** assisting to understand the effects of salinity stress,all these data on tilapia fry will help to determine the prospects and scope of culturing the species in high-salinity water.

关键词： Nile tilapia Salinity Blood parameters Histomorphology Age groups