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Assessing the pomfret stock for setting catch limits in the northern Bay of Bengal,Bangladesh

Aquaculture and Fisheries 2024年第2期9卷 324-335页

作者： Mohammed Shahidul alam Qun Liu md.Mostafa Monwar md.Enamul Hoque Suman Barua md.Leion Hassan abdullah Munzer College of Fisheries Ocean University of ChinaQingdao266003China Department of Fisheries University of ChittagongChattogram4331Bangladesh Institute of Marine Sciences University of ChittagongChattogram4331Bangladesh Department of Oceanography University of ChittagongChattogram4331Bangladesh Department of Fisheries Ministry of Fisheries and LivestockDhaka1215Bangladesh

Pampus argenteus and Pampus chinensis form the high-value demersal Pomfret fishery of ***,due to a monotonic decline in catches over the last five years,it is essential to explore the current stock status concerning the removal rate to ensure the sustainability of this ***,given the reliability and minimal data requirements,this study employed an extended Bayesian State-Space Surplus Production Model,JABBA(Just Another Bayesian Biomass Assessment),to assess the stock *** results revealed that the stock biomass of the Pomfret fishery in the final year of the time series is significantly lower than BMSY,the biomass required to produce ***,this study recommends a yearly catch limit(TAC)of 10,000 metric tons to prevent further depletion of the stock ***,to avoid growth overfishing by allowing all immature fishes to reproduce at least once before being caught,this study also calculated the optimum length(Lopt)for catch for both species at which biologically maximum yield and revenue can be *** estimated Lopt is 25 cm for *** and 30 cm for ***,and not to capture fishes with lengths lower than these limits,this study further calculated the minimum mesh size limits for gill and set bag nets is 7.5 *** the mesh size regulation was estimated using length-based reference points derived from an empirical equation,this regulation can be used as an associate reference point when TAC is applied to assure the sustainability of this fishery.

关键词： Pomfret fishery Stock assessment JABBA TAC Lower length limits for catches Mesh size regulation

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Multi-species probiotics enhance survival,growth,intestinal microbiota and disease resistance of rohu(Labeo rohita)larvae

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Water Biology and Security 2024年第1期3卷 71-79页

作者： Zannatul Ferdous md.kabir Hossain md.Hadiuzzaman SMRafiquzzaman KM Abdul Halim Tanvir Rahman md.ali Reza Faruk Zulhisyam Abdul Kari md.Shahjahan Laboratory of Fish Ecophysiology Department of Fisheries ManagementBangladesh Agricultural UniversityMymensingh2202Bangladesh Department of Aquaculture Bangladesh Agricultural UniversityMymensingh2202Bangladesh Department of Fisheries Matshoy BhabanDhakaBangladesh Department of Fisheries Biology&Aquatic Environment Bangabandhu Sheikh Mujibur Rahman Agricultural UniversityGazipur1706Bangladesh Department of Agricultural Sciences Faculty of Agro-Based IndustryUniversiti Malaysia KelantanJeli Campus17600JeliKelantanMalaysia

Multi-strain probiotics provide the most dependable approaches to improve health,immune response,and disease resistance in farmed *** the present study,we examined the effects of multi-species probiotics on the survival,growth,immune response,and disease resistance of rohu(Labeo rohita)*** hatched larvae from the day of first feeding(average weight of 0.003 g)were reared with multi-species probiotics having a combination of Bacillus subtilis(109 colony forming units(cfu)/mL)and Lactobacillus spp.(Lactobacillus plantarum,Lactobacillus buchneri-1011 cfu/mL)in water containing doses of 0(control-C),0.5 mL/L(treatment 1-T1),and 1.0 mL/L(treatment 2-T2)in triplicates for 90 *** the experiment,a challenge test was performed to assess the fish's resistance to pathogenic Aeromonas *** higher survival was recorded in larvae of treated groups(87%in T2 and 79%in T1)compared to the control(62%).Significantly higher growth performance(weight gain and specific growth rate—SGR)was shown by the probiotic-treated larval groups compared to the *** supplementation resulted in significantly higher counts of total viable colony(TVC)and lactic acid bacteria(LAB)in the *** immunological parameters(mucosal fold fattening,goblet cell abundance,expansion of lamina propria and enterocytes)of the gut were significantly better in probiotic-treated *** liver of treated fish showed irregular shape nuclei turning into regular shape and reducing spaces between the hepatic ***-treated fish had the highest post-challenge survival rate(90%)against *** *** erythrocytes of challenged fish treated with probiotics had significantly lower frequencies of various nuclear and cellular *** findings suggest that multi-species probiotic supplements could improve the survival,growth,health status,and immune response of rohu in the early stages of its development.

关键词： Aquaculture Disease resistance Immunity Labeo rohita Probiotics

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Heat and Mass Transfer on Non-Newtonian Peristaltic Flow in a Channel in Presence of Magnetic Field: Analytical and Numerical Analysis

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Applied Mathematics 2024年第8期15卷 568-583页

作者： md. Maruf Hasan md. Enamul Karim md. Abdus Samad Department of Mathematics Comilla University Comilla Bangladesh Department of Applied Mathematics University of Dhaka Dhaka Bangladesh

A study has been arranged to investigate the flow of non-Newtonian fluid in a vertical asymmetrical channel using peristalsis. The porous medium allows the electrically conductive fluid to flow in the channel, while a uniform magnetic field is applied perpendicular to the flow direction. The analysis takes into account the combined influence of heat and mass transfer, including the effects of Soret and Dufour. The flow’s non-Newtonian behavior is characterized using a Casson rheological model. The fluid flow equations are examined within a wave frame of reference that has a wave velocity. The analytic solution is examined using long wavelengths and a small Reynolds number assumption. The stream function, temperature, concentration and heat transfer coefficient expressions are derived. The bvp4c function from MATLAB has been used to numerically solve the transformed equations. The flow characteristics have been analyzed using graphs to demonstrate the impacts of different parameters.

关键词： Stream Function Mass Transfer Vertical Channel Casson Fluid

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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

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A Comparative Study of 3D Virtual Pattern and Traditional Pattern Making

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Journal of Textile Science and Technology 2024年第1期10卷 1-24页

作者： md. Ahshan Habib md. Shamsul alam Department of Fashion Design & Technology Sonargaon University Dhaka Bangladesh Department of Apparel Manufacture & Technology Sonargaon University Dhaka Bangladesh

Pattern making plays a key role in the aspect of fashion design and garment production, as it serves as the transformative process that turns a simple drawing into a consistent accumulation of garments. The process of creating conventional or manual patterns requires a significant amount of time and a specialized skill set in various areas such as grading, marker planning, and fabric utilization. This study examines the potential of 3D technology and virtual fashion designing software in optimizing the efficiency and cost-effectiveness of pattern production processes. The proposed methodology is characterized by a higher level of comprehensiveness and reliability, resulting in time efficiency and providing a diverse range of design options. The user is not expected to possess comprehensive knowledge of traditional pattern creation procedures prior to engaging in the task. The software offers a range of capabilities including draping, 3D-to-2D and 2D-to-3D unfolding, fabric drivability analysis, ease allowance calculation, add-fullness manipulation, style development, grading, and virtual garment try-on. The strategy will cause a shift in the viewpoints and methodologies of business professionals when it comes to the use of 3D fashion design software. Upon recognizing the potential time, financial, and resource-saving benefits associated with the integration of 3D technology into their design development process, individuals will be motivated to select for its utilization over conventional pattern making methods. Individuals will possess the capacity to transfer their cognitive processes and engage in introspection regarding their professional endeavors and current activities through the utilization of 3D virtual pattern-making and fashion design technologies. To enhance the efficacy and ecological sustainability of designs, designers have the potential to integrate 3D technology with virtual fashion software, thereby compliant advantages for both commercial enterpri

关键词： Pattern-Making 3D Pattern Making Virtual Fashion 3D-to-2D Unfolding Sustainable Designs

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Adaptive Cloud Intrusion Detection System Based on Pruned Exact Linear Time Technique

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Computers, Materials & Continua 2024年第6期79卷 3725-3756页

作者： Widad Elbakri Maheyzah md.Siraj Bander ali Saleh al-rimy Sultan Noman Qasem Tawfik al-Hadhrami Faculty of Computing Universiti Teknologi MalaysiaJohor BahruJohor81310Malaysia Computer Science Department College of Computer and Information SciencesImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11432Saudi Arabia School of Science and Technology Nottingham Trent UniversityNottinghamNG118NSUK

Cloud computing environments,characterized by dynamic scaling,distributed architectures,and complex work-loads,are increasingly targeted by malicious *** threats encompass unauthorized access,data breaches,denial-of-service attacks,and evolving malware *** security solutions often struggle with the dynamic nature of cloud environments,highlighting the need for robust Adaptive Cloud Intrusion Detection Systems(CIDS).Existing adaptive CIDS solutions,while offering improved detection capabilities,often face limitations such as reliance on approximations for change point detection,hindering their precision in identifying *** can lead to missed attacks or an abundance of false alarms,impacting overall security *** address these challenges,we propose ACIDS(Adaptive Cloud Intrusion Detection System)-*** novel Adaptive CIDS framework leverages the Pruned Exact Linear Time(PELT)algorithm and a Support Vector Machine(SVM)for enhanced accuracy and ***-PELT comprises four key components:(1)Feature Selection:Utilizing a hybrid harmony search algorithm and the symmetrical uncertainty filter(HSO-SU)to identify the most relevant features that effectively differentiate between normal and anomalous network traffic in the cloud environment.(2)Surveillance:Employing the PELT algorithm to detect change points within the network traffic data,enabling the identification of anomalies and potential security threats with improved precision compared to existing approaches.(3)Training Set:Labeled network traffic data forms the training set used to train the SVM classifier to distinguish between normal and anomalous behaviour patterns.(4)Testing Set:The testing set evaluates ACIDS-PELT’s performance by measuring its accuracy,precision,and recall in detecting security threats within the cloud *** evaluate the performance of ACIDS-PELT using the NSL-KDD benchmark *** results demonstrate that ACIDS-PELT outperf

关键词： Adaptive cloud IDS harmony search distributed denial of service(DDoS) PELT machine learning SVM ISOTCID NSL-KDD

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Neural Network-Powered License Plate Recognition System Design

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Engineering（科研） 2024年第9期16卷 284-300页

作者： Sakib Hasan md.Nagib Mahfuz Sunny abdullah al Nahian Mohammad Yasin School of Information and Electronics Beijing Institute of Technology Beijing China Department of Engineering and Technology Trine University Fort Wayne USA Department of Information Technology Management Westcliff University Irvine USA

The development of scientific inquiry and research has yielded numerous benefits in the realm of intelligent traffic control systems, particularly in the realm of automatic license plate recognition for vehicles. The design of license plate recognition algorithms has undergone digitalization through the utilization of neural networks. In contemporary times, there is a growing demand for vehicle surveillance due to the need for efficient vehicle processing and traffic management. The design, development, and implementation of a license plate recognition system hold significant social, economic, and academic importance. The study aims to present contemporary methodologies and empirical findings pertaining to automated license plate recognition. The primary focus of the automatic license plate recognition algorithm was on image extraction, character segmentation, and recognition. The task of character segmentation has been identified as the most challenging function based on my observations. The license plate recognition project that we designed demonstrated the effectiveness of this method across various observed conditions. Particularly in low-light environments, such as during periods of limited illumination or inclement weather characterized by precipitation. The method has been subjected to testing using a sample size of fifty images, resulting in a 100% accuracy rate. The findings of this study demonstrate the project’s ability to effectively determine the optimal outcomes of simulations.

关键词： Intelligent Traffic Control Systems Automatic License Plate Recognition (alPR) Neural Networks Vehicle Surveillance Traffic Management License Plate Recognition algorithms Image Extraction Character Segmentation Character Recognition Low-Light Environments Inclement Weather Empirical Findings algorithm Accuracy Simulation Outcomes Digitalization

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Insights into Manipulation: Unveiling Tampered Images Using Modified ELA, Deep Learning, and Explainable AI

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Journal of Computer and Communications 2024年第6期12卷 135-151页

作者： md. Mehedi Hasan md. Masud Rana Abu Sayed md. Mostafizur Rahaman Department of Information and Communication Technology Bangladesh University of Professionals Dhaka Bangladesh Department of Computer Science and Engineering Jahangirnagar University Dhaka Bangladesh

Digital image forgery (DIF) is a prevalent issue in the modern age, where malicious actors manipulate images for various purposes, including deception and misinformation. Detecting such forgeries is a critical task for maintaining the integrity of digital content. This thesis explores the use of Modified Error Level Analysis (ELA) in combination with a Convolutional Neural Network (CNN), as well as, Feedforward Neural Network (FNN) model to detect digital image forgeries. Additionally, incorporation of Explainable Artificial Intelligence (XAI) to this research provided insights into the process of decision-making by the models. The study trains and tests the models on the CASIA2 dataset, emphasizing both authentic and forged images. The CNN model is trained and evaluated, and Explainable AI (SHapley Additive exPlanation— SHAP) is incorporated to explain the model’s predictions. Similarly, the FNN model is trained and evaluated, and XAI (SHAP) is incorporated to explain the model’s predictions. The results obtained from the analysis reveals that the proposed approach using CNN model is most effective in detecting image forgeries and provides valuable explanations for decision interpretability.

关键词： IFD DIF ELA CNN FNN XAI SHAP CASIA2.0

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Antinociceptive Effect of Ethanolic Extract of Codiaeum variegatum Leaves in Mice

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Pharmacology & Pharmacy 2024年第9期15卷 285-302页

作者： md. Asrafuzzaman Ambia Khatun md. Abdul Mannan Department of Pharmacy Stamford University Bangladesh Dhaka Bangladesh

Background: Codiaeum variegatum, sometimes called garden croton, is a tropical plant in the Euphorbiaceae family. Historically used to cure various conditions, including intestinal infections, fever, ulcers, wounds, and gonorrhea. This work aimed to investigate the antinociceptive effects of ethanolic extract of Codiaeum variegatum leaves (EECV) in animal models. Methods: Five different pain models—the hot plate, tail immersion, acetic acid-induced writhing, formalin, and glutamate-induced nociception tests—were utilized to assess the antinociceptive activity in mice. The traditional drugs such as diclofenac sodium (10 mg/kg, i.p.) and morphine sulphate (5 mg/kg). EECV was administered orally at varying doses of 100, 200, and 300 mg/kg (0.1 mL/mouse), while the control group was given deionized water. Results: The current study found that all mouse models of heat- and chemical-induced pain had robust EECV reflections of their antinociceptive properties (*p Conclusions: The current finding offers a fresh perspective on the ethanolic extract of Codiaeum variegatum leaves’ antinociceptive properties in mice. This plant’s phytochemical analysis revealed the presence of triterpenoids, sterols, alkaloids, flavonoids, and general glycosides, all of which may have antinociceptive properties. More research on the mechanism of action and associated pharmacological studies, such as in vivo analysis, medication formulation, and clinical trials, is strongly advised.

关键词： Codiaeum variegatum Extract Phytochemistry Antinociceptive

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Off-Pump Coronary Artery Bypass Grafting in Patients with Left Ventricular Dysfunction: Short-Term Results from a Single Center in Bangladesh

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World Journal of Cardiovascular Surgery 2024年第9期14卷 145-156页

作者： Muhit abdullah md. Abir Tazim Chowdhury Satyajit Sharma Rehana Akther Munama Magdum Munjerin Refat Synthee md. Zafar-al-Nimari Saikat Das Gupta Saleh Ahmed Samir Kumar Biswas M. Quamrul Islam Talukder Farooque Ahmed Department of Cardiac Surgery National Heart Foundation Hospital and Research Institute (NHFH&RI) Dhaka Bangladesh Department of Cardiothoracic and Vascular Surgery Evercare Hospital Dhaka Dhaka Bangladesh Ispahani Islamia Eye Institute & Hospital Khamarbari Dhaka Bangladesh National Institute of Preventive and Social Medicine Dhaka Bangladesh Square Hospital Dhaka Bangladesh

Background: Off-pump coronary artery bypass grafting (OPCAB) is considered a safer alternative to on-pump surgery, especially in patients with left ventricular dysfunction (LVD). Objectives: This study assessed short-term outcomes and functional improvements in LVD patients post-OPCAB. Methods: The study included 200 coronary artery disease patients who underwent isolated off-pump coronary artery bypass grafting (OPCAB) at the National Heart Foundation Hospital and Research Institute between January 2019 and June 2020. Patients were categorized into Group 1, with a left ventricular ejection fraction (LVEF) of 30% - 39%, and Group 2, with an LVEF of 40% or higher. Echocardiographic assessments of left ventricular dimensions and ejection fraction were performed preoperatively, at discharge, and one month postoperatively. Results: In Group 1, preoperative left ventricular internal dimensions during diastole (LVIDd) and systole (LVIDs) were 53.48 ± 4.40 mm and 44.23 ± 3.93 mm, respectively, with a left ventricular ejection fraction (LVEF) of 35.28% ± 2.26%. At discharge, these values improved to 51.58 ± 4.04 mm (LVIDd), 41.23 ± 5.30 mm (LVIDs), and 39.25% ± 3.75% (LVEF). One month postoperatively, further improvements were observed: 46.29 ± 3.76 mm (LVIDd), 37.45 ± 3.68 mm (LVIDs), and 43.22% ± 4.67% (LVEF). Group 2 showed similar positive outcomes, with preoperative values of 47.09 ± 5.06 mm (LVIDd), 35.11 ± 5.25 mm (LVIDs), and 50.13% ± 7.25% (LVEF), improving to 42.37 ± 4.18 mm (LVIDd), 31.05 ± 4.19 mm (LVIDs), and 55.33% ± 7.05% (LVEF) at one month postoperatively. Both groups demonstrated significant improvements in left ventricular function and NYHA class, with most patients moving from class III/IV to I/II. Complications were minimal, and no mortality was observed. Conclusion: OPCAB is safe and effective for patients with LVEF 30% - 39% and LVEF ≥ 40%, providing significant short-term functional improvements without increased risk.

关键词： Off-Pump Coronary Artery Bypass Grafting Left Ventricular Dysfunction (LVD) Short-Term Outcomes

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