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Journal of Energy Chemistry 2024年第10期97卷 498-512,I0010页

作者： Fouzia Mashkoor Mohd Shoeb Hongjun Jeong Mohammad Naved khan Changyoon Jeong School of Mechanical Engineering Yeungnam UniversityGyeongsanGyeongbuk 38541Republic of Korea

Multi-metal hydroxides possess unique physical and chemical properties,making them promising candidates for supercapacitor working *** their electrochemical performance can be achieved through a combination with carbon *** this study,we synthesized a composite material by hydrothermally dispersed 4,6,and 10 wt%carbon nanotubes(CNT)into ternary cobaltbismuth-samarium hydroxide(CoBiSm-TOH).These nanocomposites were employed as the material for the working electrode in a *** findings reveal that at 1.5 A/g,the specific capacitance of CNT3@CoBiSm-TOH,using a three-electrode system,was found to be 852.91 F/g,higher than that of CoBi-BOH,CoBiSm-TOH,CNT1@CoBiSm-TOH and CNT5@CoBiSm-TOH-measuring 699.69,750.34,789.54 and 817.79 F/g,***,CNT3@CoBiSm-TOH electrodes exhibited a capacitance retention of around 88%over 10,000 *** demonstrate practical applicability,CNT3@CoBiSm-TOH was grown on woven carbon fiber(WCF),and a solid-state supercapacitor device was developed using the VARTM(vacuum-assisted resin transfer molding).This device displayed a specific capacitance of 272.67 F/g at 2.25 A/***,it achieved a maximum energy density of 53.01 Wh/kg at a power density of 750 W/kg and sustained excellent cycle stability over 50,000 cycles,maintaining 70%of its initial *** results underscore the importance of interfacial nanoengineering and provide crucial insights for the development of future energy storage devices.

关键词： Ternary hydroxide Carbon nanotube Synergistic effect VARTM Supercapacitor

Earliest megafossils of scandent calamoid palms from the Deccan Intertrappean Beds of Central India and their paleobiogeographic implications

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Journal of Palaeogeography 2024年第3期13卷 509-527页

作者： Sanchita Kumar Kaustav Roy Robert A.Spicer Mahasin Ali khan Palaeobotany and Palynology Laboratory Department of BotanySidho-Kanho-Birsha UniversityRanchi RoadPurulia-723104India CAS Key Laboratory of Tropical Forest Ecology Xishuangbanna Tropical Botanical GardenChinese Academy of SciencesMengla 666303Yunnan ProvinceChina School of Environment Earth and Ecosystem SciencesThe Open UniversityMilton KeynesMK76AAUK State Key Laboratory of Tibetan Plateau Earth System Resources and Environment(TPESRE)Institute of Tibetan Plateau ResearchChinese Academy of SciencesBeijing 100101China

Two well-preserved petrified palm stems from the latest Maastrichtian(Late Cretaceous) to earliest Danian(Early Paleocene) sediments of the Deccan Intertrappean Beds of Madhya Pradesh, Central India are described. Their significant anatomical characteristics include a Calamus-type general stem pattern,the presence of well-preserved fibrovascular bundles(fvbs) with two wide metaxylem vessel elements(230 μm-250 μm) and one phloem strand, uniform density of fvbs, lack of continuity between protoxylem and metaxylem vessel elements, and an absence of centrifugal differentiation of sclerenchymatous fibrous *** features reveal a close resemblance to those of extant genera of scandent Calamoideae. The permineralized stems are described as a new species namely, Palmoxylon calamoides Kumar, Roy et khan sp. *** fossils represent the oldest reliable fossil records of this family, supporting their Gondwanan origin, their importance in tracing their migration pathways from India to Europe and other continents after the docking of the Indian subcontinent with Eurasia during the Paleocene, and an “Out-of-India” dispersal hypothesis. Today the subfamily Calamoideae is disjunctly occurred in Africa, Asia, Australia, Europe, and South America, but the poor deep-time fossil record of this subfamily with a small number of Cenozoic fossils makes hypotheses concerning its origin and dispersal difficult to evaluate. The present study has significant implications for the origin and migration of this subfamily and the paleoclimate.

关键词： Scandent Calamoideae Stem anatomy K-Pg Paleobiogeography Paleoclimate Central India

Tribological properties of Al-GNP composites at elevated temperature

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Friction 2024年第5期12卷 1028-1041页

作者： Sunil POUDEL Rizwan BAJWA Yongde XIA Zakir khan Yi ZHANG Yanqiu ZHU College of Engineering Mathematics and Physical SciencesUniversity of ExeterExeterEX44QFUK European Technical Centre Daido Metal Co.Ltd.Iliminster SomersetTA199PHUK

Lighter and more powerful next generation vehicles and other rotary machinery demand bearings to operate in harsher conditions for higher efficiency,and the continuous development of advanced low-wear and friction materials is thus becoming even more important to meet these *** aluminium composites reinforced with high performance lubricate phases such as graphene nanoplatelets(GNPs)are very promising and have been vigorously *** maintaining a low coefficient of friction(COF)and offering great strength against wear due to their self-lubricating capability,the solid lubricant like GNPs protect the bearing surface from wear damage and prevent change in metallurgical properties during temperature *** paper first studies the high-temperature tribological performance of aluminium matrix composites reinforced with GNP,consolidated via powder metallurgy,then elucidates their tribological *** report that the best tribological performance is achieved by the composite containing 2.0 wt%GNP,with an extraordinarily low COF of 0.09 and a specific wear rate of 3.5×10^(−2)mm^(3)·N^(−1)·m^(−1),which represent 75%and 40%reduction respectively,against the plain aluminium consolidated under identical *** in-track and out-of-track Raman analysis have confirmed the role of GNPs in creating a tribofilm on the counterpart surface which contributed to the excellent performance.

关键词： nanocomposite graphene nanoplatelet(GNP) tribology powder metallurgy

A Novel Layered Double Hydroxide and Dodecyl Alcohol Assisted PCM Composite with High Latent Heat Storage Capacity and Thermal Conductivity

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Journal of Thermal Science 2024年第2期33卷 537-547页

作者： AL-AHMED Amir SARI Ahmet khan Firoz AL-RASHEIDI Masoud Hekimoğlu Gökhan AFZAAL Mohammad A.ALSULAMI Ahmed DAFALLA Hatim SALHI Billel A.ALSULAIMAN Fahad Interdisciplinary Research Center for Renewable Energy and Power Systems(IRC-REPS) King Fahd University of Petroleum&MineralsDhahran31261Saudi Arabia Department of Metallurgical and Material Engineering Karadeniz Technical UniversityTrabzon61080Turkey Maths and Natural Sciences Division Higher Colleges of TechnologyP.O.Box 7947SharjahUnited Arab Emirates Department of Mechanical Engineering King Fahd University of Petroleum&MineralsDhahran31261Saudi Arabia Core Research Facilities King Fahd University of Petroleum&MineralsDhahran31261Saudi Arabia Interdisciplinary Research Center for Membranes and Water Security King Fahd University of Petroleum&MineralsDhahran31261Saudi Arabia

Dodecyl alcohol(DDA) is a promising solid-liquid phase change material(PCM) due to its favorable latent heat storage(LHS) ***,the leakage issue of PCM in a melted state during the heating period and low thermal conductivity restricts its utilization potential in thermal energy storage(TES) *** the same context,the present work aims to overcome the leakage issue and improve the thermal conductivity of the *** this in mind,a novel leak-proof layered double hydroxide(LDH)/DDA composite PCM is proposed through a solution-based impregnation *** leak-proof impregnation ratio of the DDA impregnated within the cavities of the synthesized Al/Fe-LDH was determined to be 60%.Detailed morphological,physicochemical,and thermal properties of the fabricated composite were studied by scanning electron microscopy(SEM),Fourier transforms infrared(FTIR) spectroscopy,X-ray diffraction(XRD)spectroscopy,differential scanning calorimetry(DSC),thermalgravimetric analysis(TGA),and thermal cycling *** results show that the LDH/DDA composite has a suitable phase change temperature(about 20℃) for passive solar thermal management of building *** composite PCM showed high LHS enthalpy(about136 J/g),good thermal stability,and cycling LHS *** also showed nearly 152% higher thermal conductivity compared to that of pure DDA,ultimately reducing the melting and solidification time of the pure DDA by 44.9% and 45.5%,respectively.

关键词： dodecyl alcohol layered double hydroxide composite PCM thermal conductivity thermal energy storage(TES)

Enhancing Security and Privacy in Distributed Face Recognition Systems through Blockchain and GAN Technologies

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Computers, Materials & Continua 2024年第5期79卷 2609-2623页

作者： Muhammad Ahmad Nawaz Ul Ghani Kun She Muhammad Arslan Rauf Shumaila khan Javed Ali khan Eman Abdullah Aldakheel Doaa Sami Khafaga School of Information and Software Engineering University of Electronic Science and Technology of ChinaChengdu611731China Department of Computer Science University of Science&TechnologyBannu28100Pakistan Department of Computer Science University of HertfordshireHatfieldAL109ABUK Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia

The use of privacy-enhanced facial recognition has increased in response to growing concerns about data securityand privacy in the digital age. This trend is spurred by rising demand for face recognition technology in a varietyof industries, including access control, law enforcement, surveillance, and internet communication. However,the growing usage of face recognition technology has created serious concerns about data monitoring and userprivacy preferences, especially in context-aware systems. In response to these problems, this study provides a novelframework that integrates sophisticated approaches such as Generative Adversarial Networks (GANs), Blockchain,and distributed computing to solve privacy concerns while maintaining exact face recognition. The framework’spainstaking design and execution strive to strike a compromise between precise face recognition and protectingpersonal data integrity in an increasingly interconnected environment. Using cutting-edge tools like Dlib for faceanalysis,Ray Cluster for distributed computing, and Blockchain for decentralized identity verification, the proposedsystem provides scalable and secure facial analysis while protecting user privacy. The study’s contributions includethe creation of a sustainable and scalable solution for privacy-aware face recognition, the implementation of flexibleprivacy computing approaches based on Blockchain networks, and the demonstration of higher performanceover previous methods. Specifically, the proposed StyleGAN model has an outstanding accuracy rate of 93.84%while processing high-resolution images from the CelebA-HQ dataset, beating other evaluated models such asProgressive GAN 90.27%, CycleGAN 89.80%, and MGAN 80.80%. With improvements in accuracy, speed, andprivacy protection, the framework has great promise for practical use in a variety of fields that need face recognitiontechnology. This study paves the way for future research in privacy-enhanced face recognition systems, emphasizingt

关键词： Facial recognition privacy protection blockchain GAN distributed systems

Geometry and 3D seismic characterisation of post-rift normal faults in the Pearl River Mouth Basin,northern South China Sea

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Acta Oceanologica Sinica 2024年第4期43卷 25-39页

作者： Yuanhang Liu Jinwei Gao Wanli Chen Jiliang Wang Umair khan Laboratory of Marine Geophysics and Georesources Institute of Deep-sea Science and EngineeringChinese Academy of SciencesSanya 572000China University of Chinese Academy of Sciences Beijing 100049China

Based on high-resolution 3D seismic data acquired in the Pearl(Zhujiang)River Mouth Basin of the northern South China Sea,this study investigated the geometry,spatial extension,and throw distribution of the post-rift normal fault through detailed seismic interpretation and fault modeling.A total of 289 post-rift normal faults were identified in the study area and can be classified into four types:(1)isolated normal faults above the carbonate platform;(2)isolated normal faults cutting through the carbonate platform;(3)conjugate normal faults,and(4)connecting normal *** distribution analysis on the fault planes show that the vertical throw profiles of most normal fault exhibit flat-topped *** normal faults above the carbonate platform exhibit roughly concentric ellipses with maximum throw zones in the central section whereas the normal faults cutting through the carbonate platform miss the lowermost section due to the chaotic seismic reflections in the interior of the carbonate *** vertical throws of conjugate normal faults anomalously decrease toward their intersection region on the fault plane whereas the connecting normal faults present two maximum throw zones in the central section of the fault *** to the symmetric elliptical distribution model of fault throw,an estimation was made indicating that normal faults cutting through the carbonate platform extended downward between-1308 s and-1780 s(two-way travel time)in depth and may not penetrate the entire Liuhua carbonate ***,it is observed that the distribution of karst caves on the top of the carbonate platform disaccord with those of hydrocarbon reservoirs and the post-rift normal faults cutting through the carbonate platform in the study *** propose that these karst caves formed most probably by corrosive fluids derived from magmatic activities during the Dongsha event,rather than pore waters or hydrocarbons.

关键词： Post-rift normal faults fault throw Karst caves Corrosive fluids Pearl River Mouth Basin South China Sea

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

Machine learning-based multi-objective optimization and thermal assessment of supercritical CO_(2) Rankine cycles for gas turbine waste heat recovery

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Energy and AI 2024年第2期16卷 363-384页

作者： Asif Iqbal Turja Ishtiak Ahmed khan Sabbir Rahman Ashraf Mustakim Mohammad Ishraq Hossain M Monjurul Ehsan Yasin khan Department of Mechanical and Production Engineering(MPE) Islamic University of Technology(IUT)Board BazarGazipur1704Bangladesh

Technologies for utilizing waste heat for power generation have attracted significant attention in recent years due to their potential to enhance energy efficiency and reduce greenhouse gas *** research focuses on the comparative and optimization analysis of three supercritical carbon dioxide(sCO_(2))Rankine cycles(simple,cascade,and split)for gas turbine waste heat *** study begins with parametric analysis,investigating the significant effects of key variables,including turbine inlet temperature,condenser inlet temperature,and pinch point temperature,on the thermal performance of advanced sCO_(2) power *** identify the most efficient cycle configuration,a multi-objective optimization approach is *** approach combines a Genetic Algorithm with machine learning regression models(Random Forest,XGBoost,Artificial Neural Network,Ridge Regression,and K-Nearest Neighbors)to predict cycle performance using a dataset extracted from cycle *** decision-making process for determining the optimal cycle configuration is facilitated by the TOPSIS(technique for order of preference by similarity to the ideal solution)*** study's major findings reveal that the split cycle outperforms the simple and cascade configurations in terms of power generation across various operating *** optimized split cycle not only demonstrates superior power output but also exhibits enhanced net power output,heat recovery,system and exergy efficiency of 7.99 MW,76.17%,26.86%and 57.96%,respectively,making it a promising choice for waste heat recovery *** research has the potential to contribute to the advancement and widespread adoption of waste heat recovery in energy technologies boosting system efficiency and economic *** provides a new perspective for future research,contributing to the improvement of energy generation infrastructure.

关键词： Supercritical co2 Rankine cycle Waste heat recovery Gas turbine Thermodynamic analysis Machine Learning Optimization

A Novel Hybrid Ensemble Learning Approach for Enhancing Accuracy and Sustainability in Wind Power Forecasting

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Computers, Materials & Continua 2024年第5期79卷 3373-3395页

作者： Farhan Ullah Xuexia Zhang Mansoor khan Muhammad Abid Abdullah Mohamed School of Electrical Engineering Southwest Jiaotong UniversityChengdu611756China College of Intelligent Manufacturing and Control Engineering Qilu Institute of TechnologyJinan250200China College of Aerospace and Civil Engineering Harbin Engineering UniversityHarbin150001China Research Centre Future University in EgyptNew Cairo11835Egypt

Accurate wind power forecasting is critical for system integration and stability as renewable energy reliance *** approaches frequently struggle with complex data and non-linear connections. This article presentsa novel approach for hybrid ensemble learning that is based on rigorous requirements engineering *** approach finds significant parameters influencing forecasting accuracy by evaluating real-time Modern-EraRetrospective Analysis for Research and Applications (MERRA2) data from several European Wind farms usingin-depth stakeholder research and requirements elicitation. Ensemble learning is used to develop a robust model,while a temporal convolutional network handles time-series complexities and data gaps. The ensemble-temporalneural network is enhanced by providing different input parameters including training layers, hidden and dropoutlayers along with activation and loss functions. The proposed framework is further analyzed by comparing stateof-the-art forecasting models in terms of Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE),respectively. The energy efficiency performance indicators showed that the proposed model demonstrates errorreduction percentages of approximately 16.67%, 28.57%, and 81.92% for MAE, and 38.46%, 17.65%, and 90.78%for RMSE for MERRAWind farms 1, 2, and 3, respectively, compared to other existingmethods. These quantitativeresults show the effectiveness of our proposed model with MAE values ranging from 0.0010 to 0.0156 and RMSEvalues ranging from 0.0014 to 0.0174. This work highlights the effectiveness of requirements engineering in windpower forecasting, leading to enhanced forecast accuracy and grid stability, ultimately paving the way for moresustainable energy solutions.

关键词： Ensemble learning machine learning real-time data analysis stakeholder analysis temporal convolutional network wind power forecasting

Mechanistic insights toward identification and interaction of plant parasitic nematodes:A review

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Soil Ecology Letters 2024年第1期6卷 11-27页

作者： Bisma Jan Ali Haider Shah Mudasir Ahmad Bhat Arif Tasleem Jan Ishfaq Ahmad Wani Ali asghar Shah Section of Microbiology Baba Ghulam Shah Badshah UniversityRajouriJ&K185234India Department of Biotechnology Baba Ghulam Shah Badshah University RajouriJ&K185234India Department of Botany Baba Ghulam Shah Badshah University RajouriJ&K185234India Department of Zoology School of Biosciences and BiotechnologyBaba Ghulam Shah Badshah University RajouriJ&K185234India

Nematode identification serves as an important param-eter to study their behaviour,importance and *** of classical morphometric based identifica-tion methods prove to be lacking due to insufficient knowledge on morphological variations among closely related *** approaches such as DNA and protein-based information,microarray,probing,sequence-based methods and others have been used to supplement morphology-based methods for nematode *** and certain protein-based nematode-associated molecular patterns(NAMPs),can be perceived by the host plants,and can initiate a signalling *** review primarily emphasizes on an updated account of different classical and modern tools used for the identification of *** we also summa-rize the mechanism of some important signalling pathways which are involved in the different plant nematode *** constitute most diverse and least studied group of soil inhabiting *** are ecologically and physiologically important,however,wide range of nematodes show harmful impact on the individuals that live within their *** parasitic nematodes(PPNs)are transparent,pseudocoelomate,free living or parasitic *** lack morphometric identification methods due to insufficient knowl-edge on morphological variations among closely related *** such,molecular approaches such as DNA and protein-based information,microarray,probing,sequence-based methods and others have been used to supplement morphology-based methods for their *** invade the defense response of different plant species,parasitic nematodes have evolved different molecular *** and certain protein-based nematode-associated molecular patterns(NAMPs),can be perceived by the host plants,and can initiate a signaling *** overcome the host confrontation and develop certain nematode feeding sites,some members can inject effectors into

关键词： nematode identification plant nematode interaction DNA fingerprinting nematode-associated molecular patterns signaling path-ways