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Advances in DNA methylation and its role in cytoplasmic male sterility in higher plants

Journal of Integrative Agriculture 2024年第1期23卷 1-19页

作者： Atiqur Rahman Hasan Sofiur Rahman Shakil Uddin Naima Sultana Shirin Akhter Ujjal Kumar Nath Shamsun Nahar Begum Mazadul Islam Afroz Naznin Nurul Amin Sharif Ahmed Akbar Hossain Department of Genetics and Plant Breeding Bangladesh Agricultural UniversityMymensingh 2202Bangladesh Plant Breeding Division Bangladesh Institute of Nuclear AgricultureMymensingh 2202Bangladesh Tuber Crop Research Centre Bangladesh Agricultural Research Institute(BARI)Joydebpur 1701Bangladesh Horticulture Research Centre Bangladesh Agricultural Research Institute(BARI)Joydebpur 1701Bangladesh Biotechnology Division Bangladesh Agricultural Research Institute(BARI)Joydebpur 1701Bangladesh International Rice Research Institute Bangladesh OfficeDhaka 1213Bangladesh Division of Soil Science Bangladesh Wheat and Maize Research InstituteDinajpur 5200Bangladesh

The impact of epigenetic modifications like DNA methylation on plant phenotypes has expanded the possibilities for crop *** methylation plays a part in the regulation of both the chromatin structure and gene expression,and the enzyme involved,DNA methyltransferase,executes the methylation process within the plant *** regulating crucial biological pathways,epigenetic changes actively contribute to the creation of the ***,epigenome editing may assist in overcoming some of the drawbacks of genome editing,which can have minor off-target consequences and merely facilitate the loss of a gene’s *** drawbacks include gene knockout,which can have such off-target *** review provides examples of several molecular characteristics of DNA methylation,as well as some plant physiological processes that are impacted by these epigenetic changes in the *** also discuss how DNA alterations might be used to improve crops and meet the demands of sustainable and environmentally-friendly farming.

关键词： DNA methylation epigenetics CMS male sterility chromatin architecture gene expression higher plants

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Vision Intelligence for Smart Sheep Farming: Applying Ensemble Learning to Detect Sheep Breeds

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ARTIFICIAL INTELLIGENCE IN AGRICULTURE 2024年第1期11卷 1-12页

作者： Himel, Galib Muhammad Shahriar Islam, Md. Masudul Rahaman, Mijanur bangladesh Univ Business & Technol Dhaka Bangladesh

The ability to automatically recognize sheep breeds holds significant value for the sheep industry. Sheep farmers often require breed identification to assess the commercial worth of their flocks. However, many farmers specifically the novice one encounter difficulties in accurately identifying sheep breeds without experts in the field. Therefore, there is a need for autonomous approaches that can effectively and precisely replicate the breed identification skills of a sheep breed expert while functioning within a farm environment, thus providing considerable benefits the industry-specific to the novice farmers in the industry. To achieve this objective, we suggest utilizing a model based on convolutional neural networks (CNNs) which can rapidly and efficiently identify the type of sheep based on their facial features. This approach offers a cost-effective solution. To conduct our experiment, we utilized a dataset consisting of 1680 facial images which represented four distinct sheep breeds. This paper proposes an ensemble method that combines Xception, VGG16, InceptionV3, InceptionResNetV2, and DenseNet121 models. During the transfer learning using this pre-trained model, we applied several optimizers and loss functions and chose the best combinations out of them. This classification model has the potential to aid sheep farmers in precisely and efficiently distinguishing between various breeds, enabling more precise assessments of sector-specific classification for different businesses. (c) 2023 The Authors. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co., Ltd. This is an open access article under the CC BY license (http://***/licenses/by/4.0/).

关键词： Computer vision Sheep breed classification Image processing Transfer learning Ensemble learning Meta learner

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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

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Are gender inclusiveness and rural transformation interlinked?The case of bangladesh

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Journal of Integrative Agriculture 2024年第6期23卷 2112-2126页

作者： Maria Fay Rola-Rubzen Mohammad Jahangir Alam Jon Marx Sarmiento Ismat Ara Begum Al Amin Al Abbasi Subrata Saha UWA School of Agriculture and Environment The University of Western AustraliaPerth 6009Australia Department of Agribusiness and Marketing Bangladesh Agricultural UniversityMymensingh-2202Bangladesh Department of Agricultural Economics Bangladesh Agricultural UniversityMymensingh-2202Bangladesh

Gender inclusiveness is important in the rural transformation process of bangladesh as rural women play key roles in both agricultural and non-agricultural *** inclusiveness also leads to gender *** empirically evaluate relationships between rural transformation and gender inclusiveness in *** consider three rural transformation indicators:high-value commodities’share in agricultural output values,non-farm employment’s share in rural labor employment,and non-agricultural GDP’s share in total *** capturing gender inclusiveness include the per capita rural income of males and females,ratio of investments into gender programs,female access to education,access to healthcare,employment participation,land ownership,and asset *** test the effect of the difference in per capita rural income of males and females and the ratio of their incomes and check for the robustness of the gender variables across different model *** 128 district-level observations from 32 districts of bangladesh across four time periods(2000,2005,2010 and 2016),we use both ordinary least squares and fixed effects panel regression *** find that female land and asset ownership and access to education and healthcare are robust determinants of various stages of rural ***,our results suggest that improving women’s ownership of land and assets and investing in women’s education and healthcare will likely contribute to a more inclusive rural transformation.

关键词： rural transformation bangladesh gender inclusiveness investments on women

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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

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Enhancement of coercivity,permeability,and dielectric properties of Co_(0.2)Zn_(0.3)Ni_(0.5)Eu_(x)Fe_(2-x)O_(4) ferrites for memory and high frequency devices

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Journal of Rare Earths 2024年第6期42卷 1128-1135,I0005页

作者： I.Sardar M.D.Hossain M.S.Sikder M.N.I.Khan M.R.Rahman Physics Discipline Khulna UniversityKhulna9208Bangladesh Department of Physics Khulna University of Engineering&TechnologyKhulna9203Bangladesh Department ofComputer Science and Engineering Northern University of Business&Technology KhulnaKhulna9100Bangladesh Material Science Division Atomic Energy CentreDhaka1000Bangladesh

Spinel cubic ferrites have huge applications in me mory and high frequency *** the improvement of these modern devices,the magnetic coercivity,permeability,and dielectric properties of a ferrite are the important *** article focuses on improving the magnetic coercivity,magnetic permeability,and dielectric properties of Co_(0.2)Zn_(0.3)Ni_(0.5)Eu_(x)Fe_(2-x)O_(4) ferrites,where x=0.00,0.06,and *** X-ray diffraction(XRD),Fourier transform infrared spectroscopy(FTIR),field emission scanning electron microscopy(FESEM),energy dispersive X-ray(EDX),vibrating sample magnetometer(VSM),and an impedance analyzer were used to characterize the structural,magnetic,and dielectric properties of the *** XRD patterns indicate the formation of spinel cubic structure of the samples with a secondary peak(EuFeO_(3))for Eu doped *** densities and porosities of the samples follow an inverse trend,where the doped samples’lattice parameters are increased with the increment of rare earth Eu *** FTIR analysis also proves the spinel cubic phase of the *** average grain size of the ferrites is obtained via FESEM images,and it is increased from 121 to 198 *** analysis confirms that doping of the Eu content also changes other hysteresis loop properties of Co_(0.2)Zn_(0.3)Ni_(0.5)Eu_(x)Fe_(2-x)O_(4) ***,the coercivity of the Eu doped samples is greater than that of the mother alloy(x=0.00).The EDX study shows that there is no impurity contamination in the *** permeability and dielectric measurements show an improved quality factor of the Eu-doped samples with low magnetic and dielectric *** dependent resistivity and impedance analysis also show the improved *** the observed properties of the samples,all the investigated ferrites might be strong candidates for potential applications in memory devices,magnetic sensors,and high frequency applications.

关键词： Ferrites Raree arths Coercivity Permeability EDX Resistivity

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Review of construction and demolition waste management tools and frameworks with the classification,causes,and impacts of the waste

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Waste Disposal and Sustainable Energy 2024年第1期6卷 95-121页

作者： Dewan Sabbir Ahammed Rayhan Iftekhar Uddin Bhuiyan Institute of Appropriate Technology(IAT) Bangladesh University of Engineering and Technology(BUET)DhakaBangladesh Department of Industrial and Production Engineering(IPE) National Institute of Textile Engineering and Research(NITER)NayarhatSavarDhakaBangladesh

This review looks over the current construction and demolition waste management(C&DWM)situations by scrutinizing the definition,classification,components,compositions,generated sources and causes,impacts of generated construction and demolition wastes(C&DWs),waste management hierarchy(WMH),3R principles(Reduce,Reuse,and Recycle),Circular Economy(CE),frameworks,tools,and approaches of C&*** reviewing the literature this study contributes to the literature by the following means:(a)suitable working definitions of C&DW and C&DWM are provided,(b)an expanded WMH for construction and demolition operations is presented,(c)frameworks of C&DWM are identified and listed as follows:frameworks based on WMH,including 3R principles and CE concept,frameworks focusing on the quantification,estimation,and prediction of generated C&DW,frameworks focusing on effective and sustainable C&DWM,frameworks focusing economic,social,and environmental performance assessment,frameworks based on multi-criteria analysis(MCA),frameworks based on post-disaster recovery period,and other miscellaneous frameworks,and(d)four categories of tools utilized in C&DWM are identified and explained,namely,approaches employed in C&DWM,information technology(IT)tools employed in C&DWM,multi-criteria decision analysis(MCDA)tools employed in C&DWM,and C&DWM ***,this study also found that CE,and green rating system(GRS)are widely used approaches,Building Information Modeling(BIM),Radio Frequency Identification(RFID),Geographic Information System,and Big Data are the extensively used IT tools,Analytical Hierarchy Process,FUZZY,TOPSIS(Technique for Order Preference by Similarity to the Ideal Solution),Weighted Summation,Elimination and Choice Expressing the Reality II,Elimination and Choice Expressing the Reality III,Evaluation of Mixed Data,and REGIME(REG)are the widely used MCA tools in C&DWM,and Prefabricated Construction and Modular Construction are broadly used C&DWM ***

关键词： Construction and demolition waste Construction and demolition waste management Frameworks and tools 3R principles(Reduce,Reuse,&Recycle) Waste management hierarchy

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Development of a Lightweight Model for Handwritten Dataset Recognition: bangladeshi City Names in Bangla Script

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Computers, Materials & Continua 2024年第8期80卷 2633-2656页

作者： MdMahbubur Rahman Tusher Fahmid Al Farid MdAl-Hasan Abu Saleh Musa Miah Susmita Roy Rinky Mehedi Hasan Jim Sarina Mansor MdAbdur Rahim Hezerul Abdul Karim Department of Computer Science and Engineering Bangladesh Army University of Science and Technology(BAUST)Saidpur5310Bangladesh Faculty of Engineering Multimedia UniversityCyberjaya63100Malaysia Pabna University of Science and Technology Pabna6600Bangladesh

The context of recognizing handwritten city names,this research addresses the challenges posed by the manual inscription of bangladeshi city names in the Bangla *** today’s technology-driven era,where precise tools for reading handwritten text are essential,this study focuses on leveraging deep learning to understand the intricacies of Bangla *** existing dearth of dedicated datasets has impeded the progress of Bangla handwritten city name recognition systems,particularly in critical areas such as postal automation and document ***,no prior research has specifically targeted the unique needs of Bangla handwritten city name *** bridge this gap,the study collects real-world images from diverse sources to construct a comprehensive dataset for Bangla Hand Written City name *** emphasis on practical data for system training enhances *** research further conducts a comparative analysis,pitting state-of-the-art(SOTA)deep learning models,including EfficientNetB0,VGG16,ResNet50,DenseNet201,InceptionV3,and Xception,against a custom Convolutional Neural Networks(CNN)model named“Our CNN.”The results showcase the superior performance of“Our CNN,”with a test accuracy of 99.97% and an outstanding F1 score of 99.95%.These metrics underscore its potential for automating city name recognition,particularly in postal *** study concludes by highlighting the significance of meticulous dataset curation and the promising outlook for custom CNN *** encourages future research avenues,including dataset expansion,algorithm refinement,exploration of recurrent neural networks and attention mechanisms,real-world deployment of models,and extension to other regional languages and *** recommendations offer exciting possibilities for advancing the field of handwritten recognition technology and hold practical implications for enhancing global postal services.

关键词： Handwritten recognition bangladeshi city names Bangla handwritten city name automated postal services

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An Enhanced Hybrid Model Based on CNN and BiLSTM for Identifying Individuals via Handwriting Analysis

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Computer Modeling in Engineering & Sciences 2024年第8期140卷 1689-1710页

作者： Md.Abdur Rahim Fahmid Al Farid Abu Saleh Musa Miah Arpa Kar Puza Md.Nur Alam Md.Najmul Hossain Sarina Mansor Hezerul Abdul Karim Department of Computer Science and Engineering Pabna University of Science and TechnologyPabna6600Bangladesh Faculty of Engineering Multimedia UniversityCyberjaya63100Malaysia Department of Computer Science and Engineering Bangladesh Army University of Science and TechnologySaidpur5311Bangladesh Department of Mathematics Pabna University of Science and TechnologyPabna6600Bangladesh Department of Electrical Electronic and Communication EngineeringPabnaUniversity of Science and TechnologyPabna6600Bangladesh Department of Electrical and Communication Engineering Pabna University of Science and TechnologyPabna6600Bangladesh

Handwriting is a unique and significant human feature that distinguishes them from one *** are many researchers have endeavored to develop writing recognition systems utilizing specific signatures or symbols for person identification through ***,such systems are susceptible to forgery,posing security *** response to these challenges,we propose an innovative hybrid technique for individual identification based on independent handwriting,eliminating the reliance on specific signatures or *** response to these challenges,we propose an innovative hybrid technique for individual identification based on independent handwriting,eliminating the reliance on specific signatures or *** innovative method is intricately designed,encompassing five distinct phases:data collection,preprocessing,feature extraction,significant feature selection,and *** key advancement lies in the creation of a novel dataset specifically tailored for Bengali handwriting(BHW),setting the foundation for our comprehensive ***-preprocessing,we embarked on an exhaustive feature extraction process,encompassing integration with kinematic,statistical,spatial,and composite *** meticulous amalgamation resulted in a robust set of 91 *** enhance the efficiency of our system,we employed an analysis of variance(ANOVA)F test and mutual information scores approach,meticulously selecting the most pertinent *** the identification phase,we harnessed the power of cutting-edge deep learning models,notably the Convolutional Neural Network(CNN)and Bidirectional Long Short-Term Memory(BiLSTM).These models underwent rigorous training and testing to accurately discern individuals based on their handwriting ***,our methodology introduces a groundbreaking hybrid model that synergizes CNN and BiLSTM,capitalizing on fine motor features for enhanced individual ***,our experimental results unde

关键词： Bengali handwriting(BHW) person identification convolutional neural network(CNN) BiLSTM

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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

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