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Metal-organic framework-based single-atom electro-/ photocatalysts: Synthesis, energy applications, and opportunities

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Carbon Energy 2024年第1期6卷 1-43页

作者： Munir Ahmad Jiahui Chen Jianwen Liu Yan Zhang Zhongxin Song Shahzad Afzal Waseem Raza Liaqat Zeb Andleeb Mehmood Arshad hussain Jiujun Zhang Xian-Zhu Fu Jing-Li Luo Shenzhen Key Laboratory of Energy Electrocatalytic Materials Guangdong Research Center for Interfacial Engineering of Functional MaterialsCollege of Materials Science and EngineeringShenzhen UniversityShenzhenGuangdongChina College of Physics and Optoelectronic Engineering Shenzhen UniversityShenzhenGuangdongChina College of Chemistry and Environmental Engineering Shenzhen UniversityShenzhenGuangdongChina Department of Environmental Engineering China Jiliang UniversityHangzhouZhejiangChina Institute for Advanced Study Shenzhen UniversityShenzhenGuangdongChina School of Bioengineering Dalian University of TechnologyDalianLiaoningChina College of Materials Science and Engineering Fuzhou UniversityFuzhouFujianChina Institute for Sustainable Energy Shanghai UniversityShanghaiChina

Single-atom catalysts(SACs)have gained substantial attention because of their exceptional catalytic ***,the high surface energy limits their synthesis,thus creating significant challenges for further *** the last few years,metal–organic frameworks(MOFs)have received significant consideration as ideal candidates for synthesizing SACs due to their tailorable chemistry,tunable morphologies,high porosity,and chemical/thermal *** this perspective,this review thoroughly summarizes the previously reported methods and possible future approaches for constructing MOF-based(MOF-derived-supported and MOF-supported)***,MOF-based SAC's identification techniques are briefly assessed to understand their coordination environments,local electronic structures,spatial distributions,and catalytic/electrochemical reaction *** review systematically highlights several photocatalytic and electrocatalytic applications of MOF-based SACs for energy conversion and storage,including hydrogen evolution reactions,oxygen evolution reactions,O_(2)/CO_(2)/N_(2) reduction reactions,fuel cells,and rechargeable *** light is also shed on the future development of this highly exciting field by highlighting the advantages and limitations of MOF-based SACs.

关键词： carbon energy generation MOF-derived-supported MOF-supported single atoms

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An Efficient Long Short-TermMemory and Gated Recurrent Unit Based Smart Vessel Trajectory Prediction Using Automatic Identification System Data

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Computers, Materials and Continua 2024年第1期81卷 1789-1808页

作者： Zaman U. Khan J. Lee E. hussain S. Balobaid A.S. Aburasain R.Y. Kim K. Department of Computer Engineering Chungnam National University Daejeon 34134 South Korea Department of Environmental IT Engineering Chungnam National University Daejeon 34134 South Korea Autonomous Ship Research Center Samsung Heavy Industries Daejeon 34051 South Korea ICAROS Center (PRISMA Lab) University of Naples Federico II Naples 80131 Italy Department of Computer Science College of Computer Science and Information Technology Jazan University Jazan 45142 Saudi Arabia

Maritime transportation, a cornerstone of global trade, faces increasing safety challenges due to growing sea traffic volumes. This study proposes a novel approach to vessel trajectory prediction utilizing Automatic Identification System (AIS) data and advanced deep learning models, including Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), Bidirectional LSTM (DBLSTM), Simple Recurrent Neural Network (SimpleRNN), and Kalman Filtering. The research implemented rigorous AIS data preprocessing, encompassing record deduplication, noise elimination, stationary simplification, and removal of insignificant trajectories. Models were trained using key navigational parameters: latitude, longitude, speed, and heading. Spatiotemporal aware processing through trajectory segmentation and topological data analysis (TDA)was employed to capture dynamic *** using a three-month AIS dataset demonstrated significant improvements in prediction accuracy. The GRU model exhibited superior performance, achieving training losses of 0.0020 (Mean Squared Error, MSE) and 0.0334 (Mean Absolute Error, MAE), with validation losses of 0.0708 (MSE) and 0.1720 (MAE). The LSTM model showed comparable efficacy, with training losses of 0.0011 (MSE) and 0.0258 (MAE), and validation losses of 0.2290 (MSE) and 0.2652 (MAE). Both models demonstrated reductions in training and validation losses, measured by MAE, MSE, Average Displacement Error (ADE), and Final Displacement Error (FDE). This research underscores the potential of advanced deep learning models in enhancing maritime safety through more accurate trajectory predictions, contributing significantly to the development of robust, intelligent navigation systems for the maritime industry. © 2024 The Authors. Published by Tech Science Press.

关键词： AIS data deep learning GRU LSTM smart vessel Trajectory prediction

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Flow of Oldroyd-B fluid with nanoparticles and thermal radiation

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Applied Mathematics and Mechanics(English Edition) 2015年第1期36卷 69-80页

作者： T.HAYAT T.hussain S.A.shehzad A.ALSAEDI Department of Mathematics Quaid-i-Azam University Nonlinear Analysis and Applied Mathematics (NAAM) Research Group Faculty of ScienceKing Abdulaziz University Department of Mathematics Faculty of Computing Mohammad Ali Jinnah University Department of Mathematics COMSATS Institute of Information Technology

The two-dimensional boundary layer flow of an Oldroyd-B fluid in the presence of nanoparticles is investigated. Convective heat and mass conditions are considered in the presence of thermal radiation and heat generation. The Brownian motion and thermophoresis effects are retained. The nonlinear partial differential equations are reduced into the ordinary differential equation （ODE） systems. The resulting ODE systems are solved for the series solutions. The results are analyzed for various physical parameters of interest. Numerical values of the local Nusselt and Sherwood numbers are also computed and analyzed.

关键词： nanoparticle Oldroyd-B fluid heat generation convective condition

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Deep Transfer Learning Techniques in Intrusion Detection System-Internet of Vehicles: A State-of-the-Art Review

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Computers, Materials & Continua 2024年第8期80卷 2785-2813页

作者： Wufei Wu Javad Hassannataj Joloudari Senthil Kumar Jagatheesaperumal Kandala N.V.P.SRajesh Silvia Gaftandzhieva Sadiq hussain Rahimullah Rabih Najibullah Haqjoo Mobeen Nazar Hamed Vahdat-Nejad Rositsa Doneva School of Information Engineering Nanchang UniversityNanchang330031China Department of Computer Engineering Technical and Vocational University(TVU)Tehran***Iran Department of Computer Engineering University of BirjandBirjand***Iran Department of Computer Engineering Babol BranchIslamic Azad UniversityBabol***Iran Department of Electronics&Communication Engineering Mepco Schlenk Engineering CollegeSivakasi626005India School of Electronics Engineering VIT-AP UniversityNear Vijayawada522237India Faculty of Mathematics and Informatics University of Plovdiv Paisii HilendarskiPlovdiv4000Bulgaria Examination Branch Dibrugarh UniversityDibrugarh786004India Department of Computer Engineering Faculty of EngineeringUniversity of BirjandBirjand***Iran Faculty of Electrical and Computer Engineering University of BirjandBirjand***Iran Malaysian Institute of Information Technology Universiti Kuala LumpurKuala Lumpur50250Malaysia Faculty of Physics and Technology University of Plovdiv Paisii HilendarskiPlovdiv4000Bulgaria

The high performance of IoT technology in transportation networks has led to the increasing adoption of Internet of Vehicles(IoV)*** functional advantages of IoV include online communication services,accident prevention,cost reduction,and enhanced traffic *** these benefits,IoV technology is susceptible to cyber-attacks,which can exploit vulnerabilities in the vehicle network,leading to perturbations,disturbances,non-recognition of traffic signs,accidents,and vehicle *** paper reviews the state-of-the-art achievements and developments in applying Deep Transfer Learning(DTL)models for Intrusion Detection Systems in the Internet of Vehicles(IDS-IoV)based on anomaly ***-IoV leverages anomaly detection through machine learning and DTL techniques to mitigate the risks posed by *** systems can autonomously create specific models based on network data to differentiate between regular traffic and *** these techniques,transfer learning models are particularly promising due to their efficacy with tagged data,reduced training time,lower memory usage,and decreased computational *** evaluate DTL models against criteria including the ability to transfer knowledge,detection rate,accurate analysis of complex data,and *** review highlights the significant progress made in the field,showcasing how DTL models enhance the performance and reliability of IDS-IoV *** examining recent advancements,we provide insights into how DTL can effectively address cyber-attack challenges in IoV environments,ensuring safer and more efficient transportation networks.

关键词： Cyber-attacks internet of things internet of vehicles intrusion detection system

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Sulfone-functionalized stable molecular single crystals for photocatalytic hydrogen evolution

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SusMat 2024年第3期4卷 240-250页

作者： Xunliang Hu Xiaoju Yang Bingyi Song Zhen Zhan Ruixue Sun Yantong Guo Li-Ming Yang Xuan Yang Chun Zhang Irshad hussain Xiaoyan Wang Bien Tan Key Laboratory of Material Chemistry for Energy Conversion and Storage Ministry of Education Hubei Key Laboratory of Material Chemistry and Service FailureSchool of Chemistry and Chemical EngineeringHuazhong University of Science and TechnologyWuhanChina Department of Applied Physics The Hong Kong Polytechnic UniversityKowloonHong KongChina College of Life Science&Technology Huazhong University of Science and TechnologyWuhanChina Department of Chemistry and Chemical Engineering SBA School of Science and EngineeringLahore University of Management SciencesLahorePakistan

Highly crystalline organic semiconductors are ideal materials for photocatalytic hydrogen evolution in water ***,the instability and complex synthesis processes of most reported organic molecule-based photocatalysts restrict their *** this study,we introduce benzo[1,2-b:4,5-bʹ]bis[1]benzothiophene-3,9-dicarboxylic acid,5,5,11,11-tetraoxide(FSOCA),a highly crystalline,stable molecular crystal that is easy to synthesize and serves as an efficient photocatalyst for the hydrogen evolution *** exhibits high efficiency in sacrificial hydrogen evolution reaction(760μmol h^(−1),76 mmol g^(−1)h^(−1)at 330 mW cm^(−2);570μmol h^(−1),57 mmol g^(−1)h^(−1)at 250 mW cm^(−2)),and FSOCA remains stable during photocatalysis for up to 400 *** and theoretical studies confirmed the presence of hydrogen bonds between the sulfone group and the sacrificial agent(ascorbic acid).This interaction significantly improved the oxidation reaction kinetics and boosted the photocatalytic *** study presents a scalable and convenient approach to synthesize highly crystalline,active,and stable organic photocatalysts with potential applications in large-scale photocatalysis.

关键词： exceptional durability molecular single crystals photocatalytic water splitting

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Impact of liver metastasis on immunotherapy in gastric carcinoma

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World Journal of Gastrointestinal Surgery 2024年第10期16卷 3084-3086页

作者： Mushtaq Chalkoo Mohd Yaqoob Bhat Yaser hussain Wani Department of Surgery Government Medical CollegeSrinagar 190014Jammu and KashmirIndia Department of General Surgery Government Medical College SrinagarSrinagar 190010Jammu and KashmirIndia Post Graduate Department of Minimal Access and General Surgery Government Medical College SrinagarSrinagar 190010Jammu and KashmīrIndia

The editorial discusses the impact of liver metastasis on immunotherapy efficacy in gastric cancer(GC)*** metastasis can hinder the effectiveness of immunotherapy by altering the immune microenvironment,leading to systemic loss of T-cells and reduced treatment *** suggest that liver meta-stases serve as a negative baseline factor for immunotherapy efficacy,resulting in poorer progression-free survival and objective response *** such as liver-mediated radiotherapy may help improve treatment outcomes by reshaping the liver’s immune microenvironment and reducing T-cell ***-ing the complex interplay between liver metastasis and immunotherapy response is crucial for optimising patient care in GC.

关键词： Immunotherapy Liver metastasis Immune tolerance Gastric carcinoma Hepatic Siphoning

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Boundary layer flow of third grade nanofluid with Newtonian heating and viscous dissipation

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Journal of Central South University 2015年第1期22卷 360-367页

作者： S.A.shehzad Tariq hussain T.Hayat M.Ramzan A.Alsaedi Department of Mathematics Comsats Institute of Information Technology Department of Mathematics Faculty of Computing Mohammad Ali Jinnah University Department of Mathematics Faculty of Science King Abdulaziz University Department of Mathematics Quaid-i-Azam University 45320

Two-dimensional boundary layer flow of an incompressible third grade nanofluid over a stretching surface is *** of thermophoresis and Brownian motion is considered in the presence of Newtonian heating and viscous *** nonlinear problems of velocity, temperature and nanoparticle concentration are solved via homotopic *** is examined graphically and numerically. Results of temperature and nanoparticle concentration are plotted and discussed for various values of material parameters, Prandtl number, Lewis number, Newtonian heating parameter, Eckert number and thermophoresis and Brownian motion parameters. Numerical computations are performed. The results show that the change in temperature and nanoparticle concentration distribution functions is similar when we use higher values of material parameters β1 andβ2. It is seen that the temperature and thermal boundary layer thickness are increasing functions of Newtonian heating parameter γ.An increase in thermophoresis and Brownian motion parameters tends to an enhancement in the temperature.

关键词： third grade nanofluid Newtonian heating viscous dissipation

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Combined Application of Biostimulants and EDTA Improved Wheat Productivity under Cadmium Stress

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Phyton-International Journal of Experimental Botany 2024年第7期93卷 1647-1665页

作者： Abida Aziz Shafiqa Bano Mubshar hussain Muhammad Farooq Azhar Ghulam Yasin Naila Hadayat Iqra Arooj Abeer Hashem Ajay Kumar Elsayed Fathi Abd_Allah Qamar uz Zaman Department of Botany The Women UniversityMultan54500Pakistan Institute of Agronomy Bahauddin Zakariya UniversityMultan60800Pakistan Department of Forestry and Range Management Bahauddin Zakariya UniversityMultan60800Pakistan Department of Botany Division of Science&TechnologyUniversity of EducationLahore54770Pakistan Department of Microbiology&Molecular Genetics The Women UniversityMultan54500Pakistan Botany and Microbiology Department College of ScienceKing Saud UniversityRiyadh201313Saudi Arabia Amity Institute of Biotechnology Amity UniversityNoida201313India Plant Production Department College of Food and Agricultural SciencesKing Saud UniversityRiyadh11451Saudi Arabia School of Agriculture Yunnan UniversityKunmingYunan650504China Department of Environmental Sciences The University of LahoreLahore54590Pakistan

Wheat(Triticum aestivum L.)exhibits a greater capacity for cadmium(Cd)absorption compared to other cereal crops,leading to elevated daily Cd intake,and posing a signiﬁcant threat to public *** the mitigation of Cd stress in sustainable and environmentally friendly way,a pot study was designed by using exogenous application of various biostimulants,i.e.,Nigella sativa and Ocimum sanctum extracts:0%,10%,and 20%in combination with the chelating agent ethylenediaminetetraacetic acid(EDTA)using 0 and 5 mg kg^(-1) under various levels of Cd stress(i.e.,0,5,10,and 15 mg kg^(-1) soil).Results revealed that Cd stress signiﬁcantly reduced the seed emergence,growth,root,and allometric characters and yield-related parameters of wheat *** most observable reduc-tion was documented in wheat plants exposed to a higher Cd concentration(15 mg kg^(-1)),followed by the lower Cd level(control).The combined application of bio-stimulants and EDTA minimized the negative impacts of Cd *** highest increase in seedling emergence(5.44%),leaf area(50.60%),number of tillers(31.02%),grain yield per plant(24.28%),biological yield(13.97%),and decrease in Cd levels in grains(40%)was noticed where 20%foliar application of *** and 10%of *** biostimulants were done using 5 mg kg^(-1) of soil-applied *** intervention demonstrated a notable reduction in Cd-induced negative effects,highlighting the potential of these substances in promoting sustainable wheat cultivation in contaminated ***,it is an eco-friendly and approachable method at theﬁeld level able to ensure food safety.

关键词： Abiotic stress allometric characters antioxidant activity crop yield seed emergence grain yield

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Intrusion Detection System for Smart Industrial Environments with Ensemble Feature Selection and Deep Convolutional Neural Networks

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Intelligent Automation & Soft Computing 2024年第3期39卷 545-566页

作者： Asad Raza Shahzad Memon Muhammad Ali Nizamani Mahmood hussain Shah Dr.AHS Bukhari Postgraduate Centre of Information and Communication Technology Faculty of Engineering and TechnologyUniversity of SindhJamshoro76060Pakistan Newcastle Business School Northumbria UniversityNewcastleNE1UK

Smart Industrial environments use the Industrial Internet of Things(IIoT)for their routine operations and transform their industrial operations with intelligent and driven ***,IIoT devices are vulnerable to cyber threats and exploits due to their connectivity with the *** signature-based IDS are effective in detecting known attacks,but they are unable to detect unknown emerging ***,there is the need for an IDS which can learn from data and detect new *** Machine Learning(ML)and individual Deep Learning(DL)based IDS have been developed,and these individual models achieved low accuracy;however,their performance can be improved with the ensemble stacking *** this paper,we have proposed a Deep Stacked Neural Network(DSNN)based IDS,which consists of two stacked Convolutional Neural Network(CNN)models as base learners and Extreme Gradient Boosting(XGB)as the meta *** proposed DSNN model was trained and evaluated with the next-generation dataset,TON_*** pre-processing techniques were applied to prepare a dataset for the model,including ensemble feature selection and the SMOTE ***,precision,recall,F1-score,and false positive rates were used to evaluate the performance of the proposed ensemble *** experimental results showed that the accuracy for binary classification is 99.61%,which is better than in the baseline individual DL and ML *** addition,the model proposed for IDS has been compared with similar *** proposed DSNN achieved better performance metrics than the other *** proposed DSNN model will be used to develop enhanced IDS for threat mitigation in smart industrial environments.

关键词： Industrial internet of things smart industrial environment cyber-attacks convolutional neural network ensemble learning

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Flow of Casson nanofluid with viscous dissipation and convective conditions: A mathematical model

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Journal of Central South University 2015年第3期22卷 1132-1140页

作者： T.hussain S.A.shehzad A.ALSAEDI T.HAYAT M.RAMZAN Department of Mathematics Faculty of Computing Mohammad Ali Jinnah University Department of Mathematics Comsats Institute of Information Technology Department of Mathematics Faculty of Science King Abdulaziz University Department of Mathematics Quaid-i-Azam University

The magnetohydrodynamic(MHD) boundary layer flow of Casson fluid in the presence of nanoparticles is *** conditions of temperature and nanoparticle concentration are employed in the formulation. The flow is generated due to exponentially stretching surface. The governing boundary layer equations are reduced into the ordinary differential equations. Series solutions are presented to analyze the velocity, temperature and nanoparticle concentration fields. Temperature and nanoparticle concentration fields decrease when the values of Casson parameter enhance. It is found that the Biot numbers arising due to thermal and concentration convective conditions yield an enhancement in the temperature and concentration fields. Further, we observed that both the thermal and nanoparticle concentration boundary layer thicknesses are higher for the larger values of thermophoresis parameter. The effects of Brownian motion parameter on the temperature and nanoparticle concentration are reverse.

关键词： nanoparticles Casson fluid concentration convective condition

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