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Exploring University Campus Community’s Perceptions and Barriers toward Biking: A Case Study of the University of Tennessee Knoxville

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Journal of Transportation Technologies 2024年第2期14卷 161-178页

作者： sheikh muhammad usman muhammad Adeel Department of Civil & Environmental Engineering The University of Tennessee Knoxville USA

Bicycling constitutes an integral component of sustainable non-motorized means of travel. Despite the immense benefits of bicycling, the modal share of bicycling is quite low, specifically among young and low-income commuters e.g., college and university students. This study explores the perceptions of and barriers to bicycling of the campus community at the University of Tennessee, Knoxville with the aim to identify the factors that could enhance bike use among students at the university campus as well as highlight the barriers that keep young population away from biking. An online survey about bike use at the university campus was administered and responses to the survey were recorded. On the methodological front, a binary logit model was estimated with students’ willingness to use bikes at campus as the dependent variable. The survey results revealed that about 47% of the students considered vehicular traffic as the reason for feeling unsafe while biking and emphasized having separate bike routes. Most of the respondents highlighted the need to change clothes after biking in summer or carry things as the reason for not selecting bikes as a mode of transport at the campus, whereas inadequate bike lanes, paths, or trails, insufficient lighting along bike routes, and the lack of adequate bicycle parking were highlighted as the major barriers deterring bike use within the campus. The study suggests development of a campus bike network with proper bike lanes, bike runnels, installation of safety cameras and better lighting at the campus, and bike-supporting infrastructure such as communal showers to be provided in campus buildings to encourage bike use among university students. The study findings can assist campus transportation planners in devising a sustainable campus transportation plan incorporating the influencing factors and deterrents of bike use in a university campus setting.

关键词： Bike use Bike Infrastructure Educational Institutes Survey Binary Logit Model

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Exploring University Campus Community’s Perceptions and Barriers toward Biking:A Case Study of the University of Tennessee Knoxville

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Journal of Transportation Technologies（交通科技期刊） 2024年第2期 161页

作者： sheikh muhammad usman muhammad Adeel

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Consequences of Rényi entropy on the thermal geometries and Hawking evaporation of topological dyonic dilaton black hole

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Communications in Theoretical Physics 2024年第2期76卷 102-110页

作者： muhammad Yasir Xia Tiecheng muhammad usman Shahid Chaudhary Department of Mathematics Shanghai University and Newtouch Center for Mathematics of Shanghai UniversityShanghai200444China Department of Natural Sciences and Humanities University of Engineering and Technology LahoreNew CampusPakistan

The thermodynamics of black holes(BHs)has had a profound impact on theoretical physics,providing insight into the nature of gravity,the quantum structure of spacetime and the fundamental laws governing the *** this study,we investigate thermal geometries and Hawking evaporation of the recently proposed topological dyonic dilaton BH in anti-de Sitter(Ad S)*** consider Rényi entropy and obtain the relations for pressure,heat capacity and Gibbs free energy and observe that the Rényi parameter and dilaton field play a vital role in the phase transition and stability of the ***,we use Weinhold,Ruppeiner and Hendi Panahiyah Eslam Momennia models to evaluate the scalar curvature of the BH and find out that the divergence points of the scalar curvature coincides with the zero of specific ***,using Stefan–Boltzmann law,we determine that the BH without a dilaton field evaporates far more quickly compared to the dilaton BH in Ad S space.

关键词： topological dyonic dilaton black hole phase transition thermal geometry Hawking evaporation

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Model Agnostic Meta-Learning(MAML)-Based Ensemble Model for Accurate Detection of Wheat Diseases Using Vision Transformer and Graph Neural Networks

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Computers, Materials & Continua 2024年第5期79卷 2795-2811页

作者： Yasir Maqsood Syed muhammad usman Musaed Alhussein Khursheed Aurangzeb Shehzad Khalid muhammad Zubair Department of Creative Technologies Faculty of Computing and Artificial IntelligenceAir UniversityIslamabad44000Pakistan Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia Department of Computer Engineering Bahria School of Engineering and Applied SciencesBahria UniversityIslamabad44000Pakistan Laboratory for Neuro&Psychophysiology KU LeuvenLeuven3000Belgium

Wheat is a critical crop,extensively consumed worldwide,and its production enhancement is essential to meet escalating *** presence of diseases like stem rust,leaf rust,yellow rust,and tan spot significantly diminishes wheat yield,making the early and precise identification of these diseases vital for effective disease *** advancements in deep learning algorithms,researchers have proposed many methods for the automated detection of disease pathogens;however,accurately detectingmultiple disease pathogens simultaneously remains a *** challenge arises due to the scarcity of RGB images for multiple diseases,class imbalance in existing public datasets,and the difficulty in extracting features that discriminate between multiple classes of disease *** this research,a novel method is proposed based on Transfer Generative Adversarial Networks for augmenting existing data,thereby overcoming the problems of class imbalance and data *** study proposes a customized architecture of Vision Transformers(ViT),where the feature vector is obtained by concatenating features extracted from the custom ViT and Graph Neural *** paper also proposes a Model AgnosticMeta Learning(MAML)based ensemble classifier for accurate *** proposedmodel,validated on public datasets for wheat disease pathogen classification,achieved a test accuracy of 99.20%and an F1-score of 97.95%.Compared with existing state-of-the-art methods,this proposed model outperforms in terms of accuracy,F1-score,and the number of disease pathogens *** future,more diseases can be included for detection along with some other modalities like pests and weed.

关键词： Wheat disease detection deep learning vision transformer graph neural network model agnostic meta learning

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A Systematic Literature Review of Machine Learning and Deep Learning Approaches for Spectral Image Classification in Agricultural Applications Using Aerial Photography

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Computers, Materials & Continua 2024年第3期78卷 2967-3000页

作者： usman Khan muhammad Khalid Khan muhammad Ayub Latif muhammad Naveed muhammad Mansoor Alam Salman A.Khan Mazliham Mohd Su’ud College of Computing and Information Sciences Karachi Institute of Economics and TechnologyKarachi75190Pakistan Faculty of Computing and Informatics(FCI) Multimedia UniversityCyberjaya63100Malaysia Faculty of Computing Riphah International UniversityIslamabad46000Pakistan Faculty of Engineering and Information Technology School of Computer ScienceUniversity of Technology SydneySydneyAustralia

Recently,there has been a notable surge of interest in scientific research regarding spectral *** potential of these images to revolutionize the digital photography industry,like aerial photography through Unmanned Aerial Vehicles(UAVs),has captured considerable *** encouraging aspect is their combination with machine learning and deep learning algorithms,which have demonstrated remarkable outcomes in image *** a result of this powerful amalgamation,the adoption of spectral images has experienced exponential growth across various domains,with agriculture being one of the prominent *** paper presents an extensive survey encompassing multispectral and hyperspectral images,focusing on their applications for classification challenges in diverse agricultural areas,including plants,grains,fruits,and *** meticulously examining primary studies,we delve into the specific agricultural domains where multispectral and hyperspectral images have found practical ***,our attention is directed towards utilizing machine learning techniques for effectively classifying hyperspectral images within the agricultural *** findings of our investigation reveal that deep learning and support vector machines have emerged as widely employed methods for hyperspectral image classification in ***,we also shed light on the various issues and limitations of working with spectral *** comprehensive analysis aims to provide valuable insights into the current state of spectral imaging in agriculture and its potential for future advancements.

关键词： Machine learning deep learning unmanned aerial vehicles multi-spectral images image recognition object detection hyperspectral images aerial photography

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Circulating tumor DNA and its role in detection, prognosis and therapeutics of hepatocellular carcinoma

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Chinese Journal of Cancer Research 2024年第2期36卷 195-214页

作者： Sana Rashid Yingchuan Sun Umair Ali Khan Saddozai Sikandar Hayyat muhammad usman Munir muhammad usman Akbar muhammad Babar Khawar Zhiguang Ren Xinying Ji Malik Ihsan Ullah Khan Institute of Molecular Biology and Biotechnology University of LahoreLahore 54590Pakistan Department of Internal Oncology(Section Ⅰ) Xuchang Municipal Central HospitalXuchang 461000China Institute of Translational Medicine Medical CollegeYangzhou UniversityYangzhou 225001China Australian Institute for Bioengineering&Nanotechnology the University of QueenslandBrisbane 4072Australia Gomal Center of Biochemistry and Biotechnology Gomal UniversityDera Ismail Khan 29111Pakistan Applied Molecular Biology and Biomedicine Lab Department of ZoologyUniversity of NarowalNarowal Punjab 51600Pakistan Kaifeng Municipal Key Laboratory for Infection and Biosafety Henan International Joint Laboratory of Nuclear Protein RegulationSchool of Basic Medical SciencesHenan UniversityKaifeng 475004China Faculty of Basic Medical Subjects Shu-Qing Medical College of ZhengzhouZhengzhou 450064China Department of Medicine Huaxian County People's HospitalHuaxian 456400China

Hepatocellular carcinoma(HCC) is considered the fifth most prevalent cancer among all types of cancers and has the third most morbidity value. It has the most frequent duplication time and a high recurrence rate. Recently, the most unique technique used is liquid biopsies, which carry many markers;the most prominent is circulating tumor DNA(ctDNA). Varied methods are used to investigate ctDNA, including various forms of polymerase chain reaction(PCR) [emulsion PCR(ePCR), digital PCR(dPCR), and bead, emulsion, amplification, magnetic(BEAMing) PCR]. Hence ctDNA is being recognized as a potential biomarker that permits early cancer detection,treatment monitoring, and predictive data on tumor burden are subjective to therapy or surgery. Numerous ctDNA biomarkers have been investigated based on their alterations such as 1) single nucleotide variations(either insertion or deletion of a nucleotide) markers including TP53, KRAS, and CCND1;2) copy number variations which include markers such as CDK6, EFGR, MYC and BRAF;3) DNA methylation(RASSF1A, SEPT9, KMT2C and CCNA2);4) homozygous mutation includes ctDNA markers as CDKN2A, AXIN1;and 5) gain or loss of function of the genes, particularly for HCC. Various researchers have conducted many studies and gotten fruitful ***, there are some drawbacks to ctDNA namely low quantity, fragment heterogeneity, less stability, limited mutant copies and standards, and differential sensitivity. However, plenty of investigations demonstrate ctDNA's significance as a polyvalent biomarker for cancer and can be viewed as a future diagnostic, prognostic and therapeutic agent. This article overviews many conditions in genetic changes linked to the onset and development of HCC, such as dysregulated signaling pathways, somatic mutations, single-nucleotide polymorphisms, and genomic instability. Additionally, efforts are also made to develop treatments for HCC that are molecularly targeted and to unravel some of the genetic pathways that f

关键词： Hepatocellular carcinoma circulating tumor DNA biomarkers single nucleotide variations diagnosis prognosis

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Carbon Dioxide （CO2） Hydrogenation with Cerium Oxide-Based Composite

Carbon Dioxide （CO2） Hydrogenation with Cerium Oxide-Based...

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作者： muhammad usman aslam（乌斯曼）中国石油大学(北京)

学位级别：硕士

Cerium oxide（CeO）based catalyst have emerged as promising materials for the catalytic hydrogenation of carbon dioxide（CO）,a vital process in the quest to mitigate climate change and produce valuable chemicals and *** provides a critical development in CeO-based catalysts for *** unique specification of CeO,such as high oxygen storage capacity,redox properties,and surface oxygen vacancies,make it an excellent candidate for *** interplay between CeOand COpromotes the activation of CO,facilitating its conversion to valuable ***,the synergistic effects of metal nanoparticles,typically supported on CeO,further enhance catalytic *** crucial factors influencing CeO-based catalyst activity include metal loading,type,support morphology,and reaction *** highlights the various reaction pathways,such as the hydrogenation of carbon dioxide（CO）to methane（CH）and Ethane（CH）,elucidating the role of CeOin promoting specific product ***,the abstract touches upon the challenges and prospects of CeO-based catalysts for COhydrogenation,including catalyst stability,poisoning,and potential applications in renewable energy and chemical *** techniques,such as advanced characterization methods and catalyst design,are essential to address these challenges and unlock the full potential of CeO-based *** conclusion,CeO-based catalysts have shown great promise in COhydrogenation,with their exceptional properties and tenability offering a path towards sustainable carbon *** R&D in this area is essential to harness the full potential of CeO-based catalysts and contribute to a greener and more sustainable future.

关键词： Carbon dioxide Cerium oxide hydrogenation Thermal catalysis Photo catalysis Conversion Selectivity Yield

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Data Temperature Informed Streaming for Optimising Large-Scale Multi-Tiered Storage

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Big Data Mining and Analytics 2024年第2期7卷 371-398页

作者： Dominic Davies-Tagg Ashiq Anjum Ali Zahir Lu Liu muhammad usman Yaseen Nick Antonopoulos Department of Computing University of DerbyDerbyDE221GBUK Department of Informatics University of LeicesterLeicesterLE17RHUK Department of Computer Science COMSATS University IslamabadIslamabad 45550Pakistan Edinburgh Napier University EdinburghEH114BNUK

Data temperature is a response to the ever-growing amount of *** data have to be stored,but they have been observed that only a small portion of the data are accessed more frequently at any one *** leads to the concept of hot and cold *** data can be migrated away from high-performance nodes to free up performance for higher priority *** studies classify hot and cold data primarily on the basis of data age and usage *** present this as a limitation in the current implementation of data *** is due to the fact that age automatically assumes that all new data have priority and that usage is purely *** propose new variables and conditions that influence smarter decision-making on what are hot or cold data and allow greater user control over data location and their *** identify new metadata variables and user-defined variables to extend the current data temperature *** further establish rules and conditions for limiting unnecessary movement of the data,which helps to prevent wasted input output(I/O)*** also propose a hybrid algorithm that combines existing variables and new variables and conditions into a single data *** proposed system provides higher accuracy,increases performance,and gives greater user control for optimal positioning of data within multi-tiered storage solutions.

关键词： data temperature hot and cold data multi-tiered storage metadata variable multi-temperature system

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Vision based intelligent traffic light management system using Faster R‐CNN

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CAAI Transactions on Intelligence Technology 2024年第4期9卷 932-947页

作者： Syed Konain Abbas muhammad usman Ghani Khan Jia Zhu Raheem Sarwar Naif R.Aljohani Ibrahim A.Hameed muhammad Umair Hassan Department of Computer Science and Engineering University of Engineering and TechnologyLahorePakistan Zhejiang Key Laboratory of Intelligent Education Technology and Application Zhejiang Normal UniversityJinhuaChina OTHEM Manchester Metropolitan UniversityManchesterUK Faculty of Computing and Information Technology King Abdulaziz UniversityJeddahSaudi Arabia Department of ICT and Natural Sciences Norwegian University of Science and Technology(NTNU)ÅlesundNorway

Transportation systems primarily depend on vehicular flow on roads. Developed coun-tries have shifted towards automated signal control, which manages and updates signal synchronisation automatically. In contrast, traffic in underdeveloped countries is mainly governed by manual traffic light systems. These existing manual systems lead to numerous issues, wasting substantial resources such as time, energy, and fuel, as they cannot make real‐time decisions. In this work, we propose an algorithm to determine traffic signal durations based on real‐time vehicle density, obtained from live closed circuit television camera feeds adjacent to traffic signals. The algorithm automates the traffic light system, making decisions based on vehicle density and employing Faster R‐CNN for vehicle detection. Additionally, we have created a local dataset from live streams of Punjab Safe City cameras in collaboration with the local police authority. The proposed algorithm achieves a class accuracy of 96.6% and a vehicle detection accuracy of 95.7%. Across both day and night modes, our proposed method maintains an average precision, recall, F1 score, and vehicle detection accuracy of 0.94, 0.98, 0.96 and 0.95, respectively. Our proposed work surpasses all evaluation metrics compared to state‐of‐the‐art methodologies.

关键词： access control artificial intelligence computer vision intelligent control

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A review on marine collagen:sources,extraction methods,colloids properties,and food applications

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胶原与皮革（英文） 2024年第1期6卷 1-27页

作者： Shahzad Farooq muhammad Ijaz Ahmad Shijie Zheng usman Ali Yang Li Cui Shixiu Hui Zhang Jiaxing Institute of Future Food Jiaxing 314050China College of Biosys-tems Engineering and Food Science Zhejiang Key Laboratory for Agro-Food ProcessingZhejiang UniversityHangzhou 310058China Jiaxing Institute of Future Food Jiaxing 314050China College of Biosys-tems Engineering and Food Science Zhejiang Key Laboratory for Agro-Food ProcessingZhejiang UniversityHangzhou 310058China

The growing interest in valorizing industrial by-products has led researchers to focus on exploring different sources and optimizing collagen extraction conditions over the past *** bovine hide,cattle bones,pork,and pig skins remain the most abundant collagen sources,there is a growing trend in the industrial utilization of collagen from non-mammalian *** review explores alternative marine collagen sourcesand summarizes emerging trends in collagen recovery from marine sources,with a particular focus on environmentally friendly ***-tionally,this review covers the colloidal structure-forming properties of marine collagens,including foam,film,gel,and emulsion *** also highlights the potential and important applications of marine collagen in various food *** on the currently reported marine sources,collagens extracted from fish,jellyfish,and sea cucumbers were found to have the highest yield and mostly comprised type-l collagen,while crustaceans and mollusks yielded lower percentages of *** extraction techniques isolate collagen based on acetic acid and pepsin treatment,but they come with drawbacks such as being time-consuming,causing sample destruction,and using ***,marine collagen extracted using conventional methods assisted with ultrasonication resulted in higher yields and strengthened the triple-stranded helical ***,an increasing number of new applications have been found in the food industry for marine collagens,such as biodegradable film-forming materi-als,colloid stabilizers,foaming agents,and micro-encapsulating ***,collagen is a modern foodstuff and is extensively used in the beverage,dairy,and meat industries to increase the stability,consistency,and elasticity of products.

关键词： Marine collagen Jellyfish Sea cucumber Colloid stabilizer Edible film Dairy product

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