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Optimizing the utilization of maize silage in forage blends-based rations to improve production performance and reduce methane emissions from fattening calves

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International Journal of Agricultural and Biological Engineering 2024年第3期17卷 75-81页

作者： Khalid Farooq Asad Sultan Assar Ali Shah Rifat Ullah khan Rajwali khan Ghazala Yasmeen nazir ahm.d khan Faculty of Animal Husbandry and Veterinary Sciences The University of AgriculturePeshawar 25130Pakistan Pakistan Scientific and Technological Information Center(PASTIC) Islamabad 44000Pakistan

This research investigated the effect of various mixtures of maize silage and ryegrass fodder on nutrient digestibility,production performance,and methane(CH4)emission of fattening ***-four fattening calves((228±10)kg body weight(BW),(280±5)d of age)were allocated to 8 diets for 84 d,according to a randomized complete block design,and the blocks were balanced for BW,age,and *** diets consisted of 4 levels of maize silages,i.e.,40%(MS40),50%(MS50),60%(MS60),and 70%(MS70)in the maize silage and ryegrass fodder mixture on a dry matter(dM)basis,and each of the mixture was supplemented with either low(LC,1.0%BW)or high(HC,1.5%BW)levels of fattening *** results revealed greater(pdM(8.35 kg/d),organic matter(OM,7.85 kg/d),and metabolizable energy(ME,12.00 Mcal/d)in calves fed with MS70-LC *** highest(pdigestibility(g/100 g)of dM(65.2),OM(67.3),crude protein(69.1),and neutral detergent fibre(56.3)was recorded for MS40-HC *** maximum(pdaily gain(AdG,571 g/d)was recorded for diet *** lowest value(pded in MS70-LC,MS70-HC,and MS60-HC as compared to other *** 70%maize silage in the ryegrass-maize silage based diet improved AdG by 174 g/d with LC *** is concluded that the optimum inclusion level of maize silage and ryegrass in the fattening ration can improve animal production performance and reduces CH4 production and concentrate requirements of fattening calves.

关键词： average daily gain farm-grown forages forage mixture fattening calves maize silage ryegrass fodder

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Brain Tumor Segmentation in Multimodal MRI Using U-Net Layered Structure

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Computers, Materials & Continua 2023年第3期74卷 5267-5281页

作者： Muhammad Javaid Iqbal Muhammad Waseem Iqbal Muhammad Anwar Muhammad Murad khan Abd Jabar Nazimi Mohammad nazir ahm.d department of Information Technology The Superior UniversityLahorePakistan department of Software Engineering The Superior UniversityLahorePakistan department of Information Sciences Division of Science and TechnologyUniversity of EducationLahorePakistan department of Computer Science Government College UniversityFaisalabadPakistan deptment of Oral and Maxillofacial Surgery Faculty of DentistryUniversiti Kebangsaan MalaysiaKuala LumpurMalaysia Institute of IR4.0 Universiti Kebangsaan MalaysiaBangiSelangorMalaysia

The brain tumour is the mass where some tissues become old or damaged,but they do not die or not leave their *** brain tumour masses occur due to malignant *** tissues must die so that new tissues are allowed to be born and take their *** segmentation is a complex and time-taking problem due to the tumour’s size,shape,and appearance *** finding such masses in the brain by analyzing Magnetic Resonance Images(MRI)is a crucial task for experts and *** could not work for large volume images simultaneously,and many errors occurred due to overwhelming image *** main objective of this research study is the segmentation of tumors in brain MRI images with the help of digital image processing and deep learning *** research study proposed an automatic model for tumor segmentation in MRI *** proposed model has a few significant steps,which first apply the pre-processing method for the whole dataset to convert Neuroimaging Informatics Technology Initiative(NIFTI)volumes into the 3d NumPy *** the second step,the proposed model adopts U-Net deep learning segmentation algorithm with an improved layered structure and sets the updated *** the third step,the proposed model uses state-of-the-art Medical Image Computing and Computer-Assisted Intervention(MICCAI)BRATS 2018 dataset withMRI modalities such as T1,T1Gd,T2,and Fluidattenuated inversion recovery(FLAIR).Tumour types in MRI images are classified according to the tumour *** of these masses carried by state-of-the-art approaches such that the first is enhancing tumour(label 4),edema(label 2),necrotic and non-enhancing tumour core(label 1),and the remaining region is label 0 such that edema(whole tumour),necrosis and *** proposed model is evaluated and gets the dice Coefficient(dSC)value for High-grade glioma(HGG)volumes for their test set-a,test set-b,and test set-c 0.9795, 0.9855 and 0.9793, respectively.

关键词： Brain tumour segmentation magnetic resonance images modalities dice coefficient low-grade glioma U-Net

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3d Kronecker Convolutional Feature Pyramid for Brain Tumor Semantic Segmentation in MR Imaging

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Computers, Materials & Continua 2023年第9期76卷 2861-2877页

作者： Kainat nazir Tahir Mustafa Madni Uzair Iqbal Janjua Umer Javed Muhammad Attique khan Usman Tariq Jae-Hyuk Cha Medical Imaging and diagnostics Lab NCAIDepartment of Computer ScienceCOMSATS University IslamabadIslamabad44000Pakistan department of Electrical and Computer Engineering COMSATS University IslamabadWah CampusWahPakistan department of Computer Science HITEC UniversityTaxilaPakistan department of Management Information Systems College of Business AdministrationPrince Sattam Bin Abdulaziz UniversityAl-Kharj16273Saudi Arabia department of Computer Science Hanyang UniversitySeoul04763Korea

Brain tumor significantly impacts the quality of life and changes everything for a patient and their loved *** a brain tumor usually begins with magnetic resonance imaging(MRI).The manual brain tumor diagnosis from the MRO images always requires an expert ***,this process is time-consuming and ***,a computerized technique is required for brain tumor detection in MRI *** the MRI,a novel mechanism of the three-dimensional(3d)Kronecker convolution feature pyramid(KCFP)is used to segment brain tumors,resolving the pixel loss and weak processing of multi-scale lesions.A single dilation rate was replaced with the 3d Kronecker convolution,while local feature learning was performed using the 3d Feature Selection(3dFSC).A 3d KCFP was added at the end of 3dFSC to resolve weak processing of multi-scale lesions,yielding efficient segmentation of brain tumors of different sizes.A 3d connected component analysis with a global threshold was used as a post-processing *** standard Multimodal Brain Tumor Segmentation 2020 dataset was used for model *** 3d KCFP model performed exceptionally well compared to other benchmark schemes with a dice similarity coefficient of 0.90,0.80,and 0.84 for the whole tumor,enhancing tumor,and tumor core,***,the proposed model was efficient in brain tumor segmentation,which may facilitate medical practitioners for an appropriate diagnosis for future treatment planning.

关键词： Brain tumor segmentation connect component analysis deep learning kronecker convolution magnetic resonance imaging

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Advances and challenges of methanol-tolerant oxygen reduction reaction electrocatalysts for the direct methanol fuel cell

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Journal of Energy Chemistry 2023年第2期77卷 499-513,I0013页

作者： Muhammad Aizaz Ud din Muhammad Idrees Sidra Jamil Syed Irfan Ghazanfar nazir Muhammad ahm.d Mudassir Muhammad Shahrukh Saleem Saima Batool Nanpu Cheng Rahman Saidur School of Materials and Energy Southwest UniversityChongqing 400715China Additive Manufacturing Institute College of Mechatronics and Control EngineeringShenzhen UniversityShenzhen 518060GuangdongChina Chongqing Key Lab for Advanced Materials and Clean Energies of Technologies School of Materials and EnergySouthwest UniversityChongqing 400715China School of Materials Science and Engineering Dongguan University of TechnologyDongguan 523808GuangdongChina department of Nanotechnology and Advanced Materials Engineering Sejong UniversitySeoul 05006Republic of Korea department of Chemistry Khawaja Fareed University of Engineering and Information TechnologyRahim Yar Khan 64200Pakistan Laboratory for High Performance Ceramics EmpaSwiss Federal Laboratories for Materials Science and Technology8600 DübendorfSwitzerland Institute for Advanced Study Shenzhen UniversityShenzhen 518060GuangdongChina Research Centre for Nano-Materials and Energy Technology School of Engineering and TechnologySunway UniversityBandar SunwayMalaysia department of Engineering Lancaster UniversityLancasterUnited Kingdom

Methanol cross-over effects from the anode to the cathode are important parameters for reducing catalytic performance in direct methanol fuel cells.A promising candidate catalyst for the cathode in direct methanol fuel cells must have excellent activity toward oxygen reduction reaction and resistance to methanol oxidation *** review focuses on the methanol tolerant noble metal-based electrocatalysts,including platinum and palladium-based alloys,noble metal–carbon based composites,transition metal-based catalysts,carbon-based metal catalysts,and metal-free *** understanding of the correlation between the activity and the synthesis method,electrolyte environment and stability issues are *** the transition metal-based catalyst,their activity,stability and methanol tolerance in direct methanol fuel cells and comparisons with those of platinum are particularly ***,strategies to enhance the methanol tolerance and hinder the generation of mixed potential in direct methanol fuel cells are also *** review provides a perspective for future developments for the scientist in selecting suitable methanol tolerate catalyst for oxygen reduction reaction and designing high-performance practical direct methanol fuel cells.

关键词： Oxygen reducing reaction Methanol tolerant electrocatalyst Portable power sources direct methanol Fuel cell

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The Rotationally Symmetric Flow of Micropolar Fluids in the Presence of an Infinite Rotating disk

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Applied Mathematics 2015年第2期6卷 430-439页

作者： Atif nazir Sajjad Hussain Mohammad Shafique Mathematics Group Coordinator Yanbu Industrial College Yanbu Saudi Arabia department of Mathematics College of Science Al-Zulfi Saudi Arabia Ex-AP department of Mathematics Gomal University D. I. Khan Pakistan

The rotationally symmetric flow of a micropolar fluid in the presence of an infinite rotating disk has been studied numerically. The equations of motion are reduced to a system of ordinary differential equations, which in turn are solved numerically using SOR method and Simpson’s (1/3) rule. The results are calculated for different values of the parameter s (the ratio of angular velocities of disc and fluid) and the suction parameter a. Moreover, three different sets of the values of non-dimensional material constants related to micropolar behavior of the fluid have been chosen arbitrarily. The calculations have been carried out using three different grid sizes to check the accuracy of the results. The research concludes that the micropolar fluids flow resembles with that of Newtonian fluids when the material constants become close to zero. The comparison of these results is presented for possible values of the parameter s.

关键词： Micropolar Fluids Rotating disk and Numerical Study

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