检索结果-南通市图书馆

Effects of bacteriocin-producing Lactiplantibacillus plantarum on bacterial community and fermentation profile of whole-plant corn silage and its in vitro ruminal fermentation,microbiota,and CH_(4) emissions

同方学位论文库评论

在线全文

同方学位论文库

学校读者我要写书评

暂无评论

Journal of Animal Science and Biotechnology 2024年第6期15卷 2625-2638页

作者： Ziqian Li Samaila usman Jiayao Zhang Yixin Zhang Rina Su Hu Chen Qiang Li Mengya Jia Tunde Adegoke Amole Xusheng Guo School of Life Sciences Lanzhou UniversityLanzhou 730000P.R.China Probiotics and Life Health Research Institute Lanzhou UniversityLanzhou 730000P.R.China International Livestock Research Institute(ILRI) IITA Campus PMBOyo RoadIbadan 5320Nigeria

Background Silage is widely used to formulate dairy cattle rations,and the utilization of antibiotics and methane emissions are 2 major problems for a sustainable and environmentally beneficial ruminant production *** has received considerable attention because of its potential as an alternative to antibiotics in animal ***,the impact of bacteriocin-producing lactic acid bacteria on the microbiological conversion process of whole-plant corn silage and rumen fermentation remains *** purpose of this study was to assess the effect of 2 classⅡa bacteriocin-producing strains Lactiplantibacillusplontarum ATCC14917 and CICC24194 on bacterial community composition and ensiling profiles of whole-plant corn silage and its in vitro rumen fermentation,microbiota,and CH_(4) *** Both bacteriocin-producing strains increased the lactic acid concentration in silage fermented for 7 d,whereas the lowest lactic acid was observed in the ATCC14917 inoculated silage fermented for 90 d(PdM content was observed in the CICC24194 treatment(Pd the silages treated with both strains had the lowest dM loss(Pducing strains promoted the growth of Levilactobacillus brevis on d 60of *** addition,treatment with bacteriocin-producing strains increased the in vitro dM digestibility(Pd decreased the CH_(4) production(Pdom forest and clustering analyses at the genus level showed that ATCC14917 increased the relative abundance of the influential variable Bacillus compared to that in the control group,whereas CICC24194 decreased the relative abundance of the influential variable Ruminococcaceae *** CICC24194 treatment had the lowest total bacterial,fungal,protozoan,and methanogen populations(Pducing *** strains improved the fermentation quality of wholeplant corn silage by regulating the bacterial communi

关键词： Bacteriocin-producing Lactiplantibacillus plantarum Fermentation Methane emissions Microbiota Rumen Whole-plant corn silage

Recognition and Tracking of Objects in a Clustered Remote Scene Environment

在线全文

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2022年第1期70卷 1699-1719页

作者： Haris Masood Amad Zafar Muhammad Umair Ali Muhammad Attique Khan Salman Ahmed usman Tariq Byeong-Gwon Kang Yunyoung Nam Wah Engineering College University of WahWah CanttPakistan department of Electrical Engineering University of LahoreIslamabad CampusPakistan department of Unmanned Vehicle Engineering Sejong UniversitySeoul05006Korea department of Computer Science HITEC University TaxilaTaxila47040Pakistan College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz UniversityAl-KhrajSaudi Arabia department of ICT Convergence Soonchunhyang UniversityAsan31538Korea

Object recognition and tracking are two of the most dynamic research sub-areas that belong to the field of Computer *** vision is one of the most active research fields that lies at the intersection of deep learning and machine *** paper presents an efficient ensemble algorithm for the recognition and tracking of fixed shapemoving objects while accommodating the shift and scale invariances that the object may *** first part uses the Maximum Average Correlation Height(MACH)filter for object recognition and determines the bounding box *** case the correlation based MACH filter fails,the algorithms switches to a much reliable but computationally complex feature based object recognition technique i.e.,affine scale invariant feature transform(ASIFT).ASIFT is used to accommodate object shift and scale object *** extracts certain features from the object of interest,providing invariance in up to six affine parameters,namely translation(two parameters),zoom,rotation and two camera axis ***,in this paper,only the shift and scale invariances are *** second part of the algorithm demonstrates the use of particle filters based Approximate Proximal Gradient(APG)technique to periodically update the coordinates of the object encapsulated in the bounding *** the end,a comparison of the proposed algorithm with other stateof-the-art tracking algorithms has been presented,which demonstrates the effectiveness of the proposed algorithm with respect to the minimization of tracking errors.

关键词： Object racking MACH filter ASIFT particle filter recognition

Confined van der Waals Epitaxial Growth of Two-dimensional Large Single-Crystal In_(2)Se_(3) for Flexible Broadband Photodetectors

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Research 2019年第1期2019卷 1096-1105页

作者： Lei Tang Changjiu Teng Yuting Luo usman Khan Haiyang Pan Zhengyang Cai Yue Zhao Bilu Liu Hui-Ming Cheng Shenzhen Geim Graphene Center Tsinghua-Berkeley Shenzhen InstituteTsinghua UniversityShenzhen 518055China Shenzhen Institute for Quantum Science and Engineering and department of Physics Southern University of Science and TechnologyShenzhen 518055China Shenzhen Key Laboratory of Quantum Science and Engineering Shenzhen 518055China Shenyang National Laboratory for Materials Sciences Institute of Metal ResearchChinese Academy of SciencesShenyang 110016China

The controllable growth of two-dimensional(2d)semiconductors with large domain sizes and high quality is much needed in order to reduce the detrimental efect of grain boundaries on device performance but has proven to be ***,we analyze the precursor concentration on the substrate surface which signifcantly infuences nucleation density in a vapor deposition growth process and design a confned micro-reactor to grow 2d In_(2)Se_(3) with large domain sizes and high *** uniqueness of this confned micro-reactor is that its size is∼102-103 times smaller than that of a conventional *** a remarkably small reactor causes a very low precursor concentration on the substrate surface,which reduces nucleation density and leads to the growth of 2d In_(2)Se_(3) grains with sizes larger than 200�*** experimental results show large domain sizes of the 2d In_(2)Se_(3) with high *** fexible broadband photodetectors based on the as-grown In_(2)Se_(3) show rise and decay times of 140 ms and 25 ms,efcient response(5.6 A/W),excellent detectivity(7×10^(10) Jones),high external quantum efciency(251%),good fexibility,and high *** study,in principle,provides an efective strategy for the controllable growth of high quality 2d materials with few grain boundaries.

关键词： stability grain sizes

COVId19 Classification Using CT Images via Ensembles of deep Learning Models

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2021年第10期69卷 319-337页

作者： Abdul Majid Muhammad Attique Khan Yunyoung Nam usman Tariq Sudipta Roy Reham R.Mostafa Rasha H.Sakr department of Computer Science HITEC University TaxilaTaxila47080Pakistan department of Computer Science and Engineering Soonchunhyang UniversityAsanKorea College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz UniversityAl-KhrajSaudi Arabia PRTTL Washington University in Saint LouisSaint LouisMO 63110USA department of Information Systems Faculty of Computers and Information SciencesMansoura UniversityMansoura35516Egypt department of Computer Science Faculty of Computers and Information SciencesMansoura UniversityMansoura35516Egypt

The recent COVId-19 pandemic caused by the novel coronavirus,severe acute respiratory syndrome coronavirus 2(SARS-CoV-2),has had a significant impact on human life and the economy around the world.A reverse transcription polymerase chain reaction(RT-PCR)test is used to screen for this disease,but its low sensitivity means that it is not sufficient for early detection and *** RT-PCR is a time-consuming procedure,there is interest in the introduction of automated techniques for *** learning has a key role to play in the field of medical *** most important issue in this area is the choice of key ***,we propose a set of deep learning features based on a system for automated classification of computed tomography(CT)images to identify ***,this method was used to prepare a database of three classes:Pneumonia,COVId19,and *** dataset consisted of 6000 CT images refined by a hybrid contrast stretching *** the next step,two advanced deep learning models(ResNet50 and darkNet53)were fine-tuned and trained through transfer *** features were extracted from the second last feature layer of both models and further optimized using a hybrid optimization *** each deep model,the Rao-1 algorithm and the PSO algorithm were combined in the hybrid ***,the selected features were merged using the new minimum parallel distance non-redundant(PMdNR)*** final fused vector was finally classified using the extreme machine *** experimental process was carried out on a set of prepared data with an overall accuracy of 95.6%.Comparing the different classification algorithms at the different levels of the features demonstrated the reliability of the proposed framework.

关键词： COVId19 preprocessing deep learning information fusion firefly algorithm extreme learning machine

dynamic Hand Gesture Recognition Using 3d-CNN and LSTM Networks

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2022年第3期70卷 4675-4690页

作者： Muneeb Ur Rehman Fawad Ahmed Muhammad Attique Khan usman Tariq Faisal Abdulaziz Alfouzan Nouf M.Alzahrani Jawad Ahmad department of Electrical Engineering HITEC University TaxilaPakistan department of Computer Science HITEC University TaxilaPakistan College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz UniversityAl-KhrajSaudi Arabia department of Forensic Sciences College of Criminal JusticeNaif Arab University for Security SciencesRiyadhSaudi Arabia department of Information Technology Albaha UniversityAlbahaSaudi Arabia School of Computing Edinburgh Napier UniversityUK

Recognition of dynamic hand gestures in real-time is a difficult task because the system can never know when or from where the gesture starts and ends in a video *** researchers have been working on visionbased gesture recognition due to its various *** paper proposes a deep learning architecture based on the combination of a 3d Convolutional Neural Network(3d-CNN)and a Long Short-Term Memory(LSTM)*** proposed architecture extracts spatial-temporal information from video sequences input while avoiding extensive *** 3d-CNN is used for the extraction of spectral and spatial features which are then given to the LSTM network through which classification is carried *** proposed model is a light-weight architecture with only 3.7 million training *** model has been evaluated on 15 classes from the 20BN-jester dataset available *** model was trained on 2000 video-clips per class which were separated into 80%training and 20%validation *** accuracy of 99%and 97%was achieved on training and testing data,*** further show that the combination of 3d-CNN with LSTM gives superior results as compared to MobileNetv2+LSTM.

关键词： Convolutional neural networks 3d-CNN LSTM spatiotemporal jester real-time hand gesture recognition

Integrated Weed Management Through Tillage and Herbicides for Wheat Production in Rice-Wheat Cropping System in Northwestern Pakistan

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal of Integrative Agriculture 2012年第6期11卷 946-953页

作者： Khalid usman Inayat Ullah Said Mir Khan Muhammad Umar Khan Said Ghulam Muhammad Anwar Khan department of Agronomy Faculty of AgricultureGomal University department of Entomology Faculty of AgricultureGomal University department of Agriculture Chemistry Faculty of AgricultureGomal University department of Soil and Environmental Sciences Faculty of AgricultureGomal University

Conservational tillage （CT） in combination with broad spectrum herbicide may be more efficient and economical in controlling weeds, reducing cost of cultivation, and enhancing wheat yield. Field experiments were carried out to evaluate the effect of tillage and herbicides on weeds and wheat yield under rice-wheat cropping system （RWCS）. The results indicated that broad spectrum herbicides particularly, carfentrazone ethyl ester＋ isoproturon （Affinity 50 WdG） reduced weeds density by 93 and 95% compared to control and also produced the maximum grain yield （6 818 and 6 996 kg ha-l） and HI （harvest index, 44.7 and 44.6%） in 2007-2008 and 2008-2009 growing seasons, respectively. The maximum weeds infestation and the lowest yield were recorded in control. Tillage methods significantly influenced grain yield and HI, while no significant effect on all other parameters. The overall mean yield was significantly higher in zero tillage （5 575 kg ha-l） and reduced tillage （5 584 kg ha-l） compared to CT （5 479 kg ha-^-1）. Besides increasing wheat yield, Affinity 50 WdG and zero tillage are important weed management practices that can be integrated into wheat production in RWCS. However, in case of perennial weeds or insect pests＇ infestation, CT in combination with Affinity 50 WdG would be more productive than conservation tillage.

关键词： herbicides tillage weed population wheat yield

3d geo-cellular static virtual outcrop model and its implications for reservoir petro-physical characteristics and heterogeneities

在线全文

学校读者我要写书评

暂无评论

Petroleum Science 2021年第5期18卷 1357-1369页

作者： Muhammad usman Numair A.Siddiqui Shi-Qi Zhang Manoj J.Mathew Ya-Xuan Zhang Muhammad Jamil Xue-Liang Liu Nisar Ahmed School of Geosciences China University of Petroleum(East China)Qingdao266580ShandongChina department of Geosciences Universiti Teknologi PETRONASBandar Seri IskandarPerakMalaysia Laboratoire Géosciences Océan IUEMUniversitéde BrestUMR 6538 CNRS/UBO/UBSRueDumont D'Urville29280PlouzaneFrance School of Geosciences The University of EdinburghEdinburghUK Lukeqin Oil Producion Plant Petro China Tuha OilfieldShanshan838202XinjiangChina

Geostatistical data plays a vibrant role for surface-based reservoir modeling through outcrop analogues,which is used to understand three-dimensional(3d)variability of petrophysical *** main purpose of this study is to improvise the surface-based 3d geo-modeling to demonstrate petrophysical characteristics and heterogeneities of Sandakan reservoirs,NW *** used point cloud data from Light detection and Ranging(Li dAR)to build high-resolution virtual outcrop modeling(VOM)onto which we mapped 6 different *** and permeability of core plugs were measured to determine the average variance of petrophysical properties for each *** utilizing the integration of VOMs analogues and petrophysical properties in Petrel^(TM),we demonstrated the distribution and associations of all lithofacies in pseudo wells that have inherent thin beds heterogeneities in 3d geocellular *** results concluded that the heterogeneity of thin beds in lithofacies is dependent on porosity and permeability with input *** to the final model,cross-bedding sandstone(CBS),hummocky cross-stratified sandstone(HCSS)and trough cross-bedding sandstone(TCBS)show good reservoir quality due to high porosity ranging from:25.6%to 20.4%and,19.3%-14.5%,and permeability ranging from:74.03 md to 66.84 md and,64.86 md to 21.01 *** contrast,massive to weak laminae sandstone(MWLS)and bioturbated sandstone(BS)show fair to poor reservoir quality,caused baffling of surrounding mud sediments in the reservoir *** also revealed that Li dAR based VOM with petrophysical properties can significantly reduce the risk and minimize the cost of reservoir modeling in petroleum industry.

关键词： Virtual outcrop modeling Lithofacies 3d geo-cellular model Petrophysical properties Reservoir heterogeneities

Relationship between Neuropsychological Functioning, Behavioral Inhibition, and Glycemic Control in Type 2 diabetes： Findings from Task-switching Study

在线全文

学校读者我要写书评

暂无评论

Chinese Medical Journal 2017年第4期130卷 487-489页

作者： Amara Gui Memoona Sehar usman Jawad department of Applied Psychology The Islamia University of Bahawalpur Bahawalpur Pakistan department of Family Medicine University of Health Sciences Lahore Lahore Pakistan

INTROdUCTIONType 2 diabetes （T2d） is one of the fastest growing medical conditions associated with cognitive dysfunctions. Less attention is paid to the effects of diabetes on task switching （TS）. Switching between tasks is a higher-order cognitive function which is executed through prefrontal cortex. Given that there are brain structural abnormalities （i.e., atrophy in cortical/subcortical gray matter volume and hyperintensities in cerebral white matter）, reduced connectivity between hippocampus and adjacent brain regions （frontal and temporal gyri）,

关键词： Behaviour Cognition diabetes Inhibition Task Switching

An Ensemble of Optimal deep Learning Features for Brain Tumor Classification

在线全文

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2021年第11期69卷 2653-2670页

作者： Ahsan Aziz Muhammad Attique usman Tariq Yunyoung Nam Muhammad Nazir Chang-Won Jeong Reham R.Mostafa Rasha H.Sakr department of Computer Science HITEC UniversityTaxilaPakistan College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz UniversityAl-KhrajSaudi Arabia department of ICT Convergence Soonchunhyang UniversityAsanKorea Medical Convergence Research Center Wonkwang UniversityIksanKorea department of Information Systems Faculty of Computers and Information SciencesMansoura UniversityMansouraEgypt department of Computer Science Faculty of Computers and Information SciencesMansoura UniversityMansouraEgypt

Owing to technological developments,Medical image analysis has received considerable attention in the rapid detection and classification of *** brain is an essential organ in *** tumors cause loss of memory,vision,and *** 2020,approximately 18,020 deaths occurred due to brain *** cases can be minimized if a brain tumor is diagnosed at a very early *** vision researchers have introduced several techniques for brain tumor detection and ***,owing to many factors,this is still a challenging *** challenges relate to the tumor size,the shape of a tumor,location of the tumor,selection of important features,among *** this study,we proposed a framework for multimodal brain tumor classification using an ensemble of optimal deep learning *** the proposed framework,initially,a database is normalized in the form of high-grade glioma(HGG)and low-grade glioma(LGG)patients and then two pre-trained deep learning models(ResNet50 and densenet201)are *** deep learning models were modified and trained using transfer ***,the enhanced ant colony optimization algorithm is proposed for best feature selection from both deep *** selected features are fused using a serial-based approach and classified using a cubic support vector *** experimental process was conducted on the BraTs2019 dataset and achieved accuracies of 87.8%and 84.6%for HGG and LGG,*** comparison is performed using several classification methods,and it shows the significance of our proposed technique.

关键词： Brain tumor data normalization transfer learning features optimization features fusion