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Grain Size Analysis of a Growing Sand Bar at Sonadia Island, Bangladesh

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Open Journal of Soil Science 2013年第2期3卷 71-80页

作者： Md. Enamul Hoque sayedur rahman chowdhury Mohammad Muslem Uddin Mohammed Shahidul Alam Md. Mostafa Monwar Institute of Marine Sciences and Fisheries University of Chittagong Chittagong Bangladesh.

Sonadia is one of the most important islands of Bangladesh. South-eastern shore of the island, which is a growing sand bar, has to encounter continuous and rapid morphological changes. So study of the sediment characteristics of this Sand Bar is very important. In the present study, grain size analysis of this Sand Bar has been done on the basis of laboratory analysis. Sediment samples were collected from 9 (Nine) stations and texture analysis of sediment was completed following a standard procedure of sieve analysis of sand samples. The average value of median (MD), mean (M), standard deviation (s), skewness (SK) and kurtosis (K) of sediment of the Sand Bar of Sonadia Island was 1.93, 1.87, 0.44, 0.11 and 1.88 respectively. Highest median, mean, standard deviation, skewness and kurtosis of Sand Bar of Sonadia Island was 2.98 (Station 2, Lower Shore), 2.68 (Station 1, Lower Shore), 0.83 (Station 1, Middle Shore and Station 2, Lower Shore), 0.65 (Station 2, Lower Shore) and 3.59 (Station 1, Lower Shore) respectively. Lowest median, mean, standard deviation, skewness and kurtosis of Sand Bar of Sonadia Island was 1.42 (Station 9, Middle Shore), 1.45 (Station 9, Middle Shore), 0.30 (Station 5, Lower Shore and Station 8, Lower Shore), 0.04 (Station 5, Upper Shore) and 0.94 (Station 6, Upper Shore) respectively.

关键词： Grain Size Analysis Sonadia Sand Bar Sediment Bay of Bengal

Computer vision-based six layered ConvNeural network to recognize sign language for both numeral and alphabet signs

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Biomimetic Intelligence & Robotics 2024年第1期4卷 45-58页

作者： Muhammad Aminur Rahaman Kabiratun Ummi Oyshe Prothoma Khan chowdhury Tanoy Debnath Anichur rahman Md.Saikat Islam Khan Department of Computer Science and Engineering Green University of BangladeshDhakaBangladesh Department of Computer Science and Engineering National Institute of Textile Engineering and Research(NITER)Constituent Institute of Dhaka UniversityDhakaBangladesh Department of Computer Science and Engineering Mawlana Bhashani Science and Technology UniversityTangailBangladesh

People who have trouble communicating verbally are often dependent on sign language,which can be difficult for most people to understand,making interaction with them a difficult *** Sign Language Recognition(SLR)system takes an input expression from a hearing or speaking-impaired person and outputs it in the form of text or voice to a normal *** existing study related to the Sign Language Recognition system has some drawbacks,such as a lack of large datasets and datasets with a range of backgrounds,skin tones,and *** research efficiently focuses on Sign Language Recognition to overcome previous *** importantly,we use our proposed Convolutional Neural Network(CNN)model,“ConvNeural”,in order to train our ***,we develop our own datasets,“BdSL_OPSA22_STATIC1”and“BdSL_OPSA22_STATIC2”,both of which have ambiguous backgrounds.“BdSL_OPSA22_STATIC1”and“BdSL_OPSA22_STATIC2”both include images of Bangla characters and numerals,a total of 24,615 and 8437 images,***“ConvNeural”model outperforms the pre-trained models with accuracy of 98.38%for“BdSL_OPSA22_STATIC1”and 92.78%for“BdSL_OPSA22_STATIC2”.For“BdSL_OPSA22_STATIC1”dataset,we get precision,recall,F1-score,sensitivity and specificity of 96%,95%,95%,99.31%,and 95.78%***,in case of“BdSL_OPSA22_STATIC2”dataset,we achieve precision,recall,F1-score,sensitivity and specificity of 90%,88%,88%,100%,and 100%respectively.

关键词： Conv NeuralSign language CNN Static Feature extraction Convolution2D Fully connected layer Dropout

Bayesian Optimized LightGBM model for predicting the fundamental vibrational period of masonry infilled RC frames

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Frontiers of Structural and Civil Engineering 2024年第7期18卷 1084-1102页

作者： Taimur rahman Pengfei ZHENG Shamima SULTANA Department of Civil Engineering World University of BangladeshDhaka 1230Bangladesh School of Civil Engineering Zhengzhou UniversityZhengzhou 450001China Department of Computer Science&Engineering University of Asia PacificDhaka 1205Bangladesh

The precise prediction of the fundamental vibrational period for reinforced concrete(RC)buildings with infilled walls is essential for structural design,especially earthquake-resistant *** learning models from previous studies,while boasting commendable accuracy in predicting the fundamental period,exhibit vulnerabilities due to lengthy training times and inherent dependence on pre-trained models,especially when engaging with continually evolving data *** predicament emphasizes the necessity for a model that adeptly balances predictive accuracy with robust adaptability and swift data *** latter should include consistent re-training ability as demanded by realtime,continuously updated data *** research implements an optimized Light Gradient Boosting Machine(LightGBM)model,highlighting its augmented predictive capabilities,realized through the astute use of Bayesian Optimization for hyperparameter tuning on the FP4026 research data set,and illuminating its adaptability and efficiency in predictive *** results show that the R^(2) score of LightGBM model is 0.9995 and RMSE is 0.0178,while training speed is 23.2 times faster than that offered by XGBoost and 45.5 times faster than for Gradient ***,this study introduces a practical application through a streamlit-powered,web-based dashboard,enabling engineers to effortlessly utilize and augment the model,contributing data and ensuring precise fundamental period predictions,effectively bridging scholarly research and practical applications.

关键词： masonry-infilled RC frame fundamental period LightGBM FP4026 research dataset machine learning data-driven approach Bayesian Optimization

Ion-acoustic waves with non-planar wavefronts

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Plasma Science and Technology 2024年第1期26卷 1-7页

作者： Shujaht BUKHARI Muhammad SHAHID Ata-ur rahman Department of Physics The University of Azad Jummu and KashmirMuzaffarabad 13100Azad Kashmir Department of Physics Women University of Azad Jammu&KashmirBagh 12500Pakistan Department of Physics Islamia College PeshawerPeshawar 25120Pakistan

The ion-acoustic(IA) mode exhibiting various orbital angular momentum(OAM) states is examined in a plasma with drifting *** constituent plasma species are modeled with a non-gyrotropic Maxwellian distribution and discussion of dispersion relation and growth rate of twisted IA waves under various conditions is *** the domain of kinetic model,the twisted IA waves are characterized by Laguerre-Gaussian(LG) solutions,where plasma distribution function and electric field are decomposed into axial and azimuthal *** plasma response function is obtained under paraxial approximations and investigated for threshold condition of instability growth rate with helical electric field *** impact of an extra electron specie on the instability is demonstrated through a comparison of twisted waves for single and double electron species.

关键词： instability twist parameter wave excitation orbital angular momentum threshold limit

HVAC energy cost minimization in smart grids: A cloud-based demand side management approach with game theory optimization and deep learning

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Energy and AI 2024年第2期16卷 331-345页

作者： rahman Heidarykiany Cristinel Ababei MESS Laboratory EECE DepartmentMarquette UniversityMilwaukeeWIUSA

In this paper, we present a novel cloud-based demand side management (DSM) optimization approach for the cost reduction of energy usage in heating, ventilation and air conditioning (HVAC) systems in residential homes at the district level. The proposed approach achieves optimization through scheduling of HVAC energy usage within permissible bounds set by house users. House smart home energy management (SHEM) devices are connected to the utility/aggregator via a dedicated communication network that is used to enable DSM. Each house SHEM can predict its own HVAC energy usage for the next 24 h using minimalistic deep learning (DL) prediction models. These predictions are communicated to the aggregator, which will then do day ahead optimizations using the proposed game theory (GT) algorithm. The GT model captures the interaction between aggregator and customers and identifies a solution to the GT problem that translates into HVAC energy peak shifting and peak reduction achieved by rescheduling HVAC energy usage. The found solution is communicated by the aggregator to houses SHEM devices in the form of offers via DSM signals. If customers’ SHEM devices accept the offer, then energy cost reduction will be achieved. To validate the proposed algorithm, we conduct extensive simulations with a custom simulation tool based on GridLab-D tool, which is integrated with DL prediction models and optimization libraries. Results show that HVAC energy cost can be reduced by up to 36% while indirectly also reducing the peak-to-average (PAR) and the aggregated net load by up to 9.97%.

关键词： Day ahead demand side management(DSM) Appliance energy usage prediction Residential energy usage scheduling flexibility Market incentives Non-cooperative game theory(GT) Dynamic price(DP) Energy cost minimization Electricity cost minimization Peak-to-average ratio(PAR)minimization Machine learning(ML) Long short-term memory(LSTM) Smart Home Energy Management(SHEM) Load shifting Internet of Things(ioT)applications Smart grid Heating Ventilation and air conditioning(HVAC)

Effects of multiple shapes for steady flow with transformer oil+Fe_(3)O_(4)+TiO_(2) between two stretchable rotating disks

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Applied Mathematics and Mechanics(English Edition) 2024年第2期45卷 373-388页

作者： M.rahman M.TURKYILMAZOGLU Z.MUSHTAQ Department of Mathematics Mirpur University of Science and TechnologyMirpur 10250Pakistan Department of Mathematics Hacettepe UniversityBeytepeAnkara 06532Turkiye

In this study,we examine the effects of various shapes of nanoparticles in a steady flow of hybrid nanofluids between two stretchable rotating *** steady flow of hybrid nanofluids with transformer oil as the base fluid and Fe_(3)O_(4)+TiO_(2)as the hybrid nanofluid is *** shapes of Fe_(3)O_(4)+TiO_(2)hybrid nanofluids,including sphere,brick,blade,cylinder,and platelet,are *** shape exists in the same volume of a *** leading equations(partial differential equations(PDEs))are transformed to the nonlinear ordinary differential equations(ODEs)with the help of similarity *** system of equations takes the form of ODEs depending on the boundary conditions,whose solutions are computed numerically by the bvp4c MATLAB *** outputs are compared with the previous findings,and an intriguing pattern is discovered,such that the tangential velocity is increased for the rotation parameter,while it is decreased by the stretching values because of the lower *** the reaction rate parameter,the concentration boundary layer becomes shorter,and the activation energy component increases the rate at which mass transfers come to the higher disk but have the opposite effect on the bottom *** ranges of various parameters taken into account are Pr=6.2,Re=2,M=1.0,φ_(1)=φ_(2)=0.03,K=0.5,S=-0.1,Br=0.3,Sc=2.0,α_(1)=0.2,γ=0.1,E_(n)=2.0,and q=1.0,and the rotation factor K is within the range of 0 to 1.

关键词： transformer oil Brinkman number skin friction coefficient double rotating disk Nusselt number Sherwood number

Nature’s Pharmacy under Siege: Investigating Antibiotic Resistance Pattern in Endophytic Bacteria of Medicinal Plants

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Advances in Microbiology 2024年第4期14卷 183-208页

作者： Bonoshree Sarkar Afroza Sultana Nabila Nawar Binti Farhana Tasnim chowdhury Sadia Afrin Mohammad Fahim Taibur rahman Atiqur rahman Infection Biology Laboratory Department of Biochemistry and Molecular Biology University of Dhaka Dhaka Bangladesh Department of Pathology University of Alabama at Birmingham Birmingham USA

Antibiotic resistance poses a significant global health threat, necessitating a thorough understanding of its prevalence in various ecological contexts. Medicinal plants, renowned for their therapeutic properties, host endophytic bacteria that produce bioactive compounds. Understanding antibiotic resistance dynamics in these bacteria is vital for human health and antibiotic efficacy preservation. In this study, we investigated antibiotic resistance profiles in endophytic bacteria from five medicinal plants: Thankuni, Neem, Aparajita, Joba, and Snake plant. We isolated and characterized 113 endophytic bacteria, with varying resistance patterns observed against multiple antibiotics. Notably, 53 strains were multidrug-resistant (MDR), with 14 exhibiting extensive drug resistance (XDR). Thankuni-associated bacteria displayed 44% MDR and 11% XDR, while Neem-associated bacteria showed higher resistance (60% MDR, 13% XDR). Aparajita-associated bacteria had lower resistance (22% MDR, 6% XDR), whereas Joba-associated bacteria exhibited substantial resistance (54% MDR, 14% XDR). Snake plant-associated bacteria showed 7% MDR and 4% XDR. Genus-specific distribution revealed Bacillus (47%), Staphylococcus (21%), and Klebsiella (11%) as major contributors to MDR. Our findings highlight diverse drug resistance patterns among plant-associated bacteria and underscore the complexity of antibiotic resistance dynamics in diverse plant environments. Identification of XDR strains emphasizes the severity of the antibiotic resistance problem, warranting further investigation into contributing factors.

关键词： Antibiotic Resistance Endophytic Bacteria Medicinal Plants Drug Resistance

The link between intracellular calcium signaling and exosomal PD-L1 in cancer progression and immunotherapy

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Genes & Diseases 2024年第1期11卷 321-334页

作者： Md Rakibul Alam Md Mizanur rahman Zhiguo Li Department of Toxicology and Cancer Biology College of MedicineUniversity of KentuckyLexingtonKY 40506USA Department of Medicine(Nephrology) Faculty of Medicine and DentistryUniversity of AlbertaEdmontonAlberta T6E2H7Canada

Exosomes are small membrane vesicles containing microRNA,RNA,DNA fragments,and proteins that are transferred from donor cells to recipient *** cells release exo-somes to reprogram the factors associated with the tumor microenvironment(TME)causing tu-mor metastasis and immune *** evidence revealed that cancer cell-derived exosomes carry immune inhibitory molecule program death ligand 1(PD-L1)that binds with re-ceptor program death protein 1(PD-1)and promote tumor progression by escaping immune ***,some FDA-approved monoclonal antibodies are clinicallyused for cancer treatment by blocking PD-1/PD-L1 *** notable treatment outcomes,some pa-tients show poor drug *** PD-L1 plays a vital role in lowering the treatment response,showing resistance to PD-1/PD-L1 blockage therapy through recapitulating the ef-fect of cell surface *** enhance therapeutic response,inhibition of exosomal PD-L1 is *** signaling is the central regulator of tumorigenesis and can regulate exosome biogenesis and secretion by modulating Rab GTPase family and membrane fusion ***-mune checkpoints are also connected with calcium signaling and calcium channel blockers like amlodipine,nifedipine,lercanidipine,diltiazem,and verapamil were also reported to suppress cellular PD-L1 ***,to enhance the PD-1/PD-L1 blockage therapy response,the reduction of exosomal PD-L1 secretion from cancer cells is in our therapeutic *** this review,we proposed a therapeutic strategy by targeting calcium signaling to inhibit the expression of PD-L1-containing exosome levels that could reduce the anti-PD-1/PD-L1 therapy resistance and increase the patient's drug response rate.

关键词： Calcium signaling CD8^(+)T cells Exosomal PD-L1 Exosomes biogenesis Immunosuppression Immunotherapy

Entrepreneurship training:its influences on innovation potentials among nursing students

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Frontiers of Nursing 2024年第1期11卷 85-98页

作者： Asmaa Abdel rahman Abdel rahman Dalia Abdallah Abdelatief Medical Surgical Nursing Department Faculty of NursingAin Shams UniversityCairoEgypt

Objective:To evaluate the influences of entrepreneurship training on the innovation potential among nursing ***:A quasi-experimental design was utilized to conduct this *** study was conducted in the classroom at the faculty of nursing,and the“i Hub”center at Ain Shams University(ASU)in Cairo,Egypt.A purposive sample of 42 nursing students who participated in the“Ain Shams University-innovate”competition from the Faculty of Nursing of ASU were included in this *** collection tools included(1)Nursing students'innovation skills assessment questionnaire and(2)Innovative projects evaluation ***:There was a statistically significant difference between the mean scores of nursing students'total innovation skills pre-and post-implementation of entrepreneurship training,where P-value<***:The results of the current study support the research hypothesis because the implementation of entrepreneurship training positively affects nursing students'innovation *** entrepreneurship education in nursing and integrating it into nursing programs will stimulate creativity,innovation,and entrepreneurship among nursing students and health care services.

关键词： entrepreneurship training innovation potentials nursing students creative skills energy/motivation