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E-fuel system: a conceptual breakthrough for energy storage

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Science Bulletin 2019年第4期64卷 227-228页

作者： khalil amine Chemical Sciences and Engineering Division Argonne National Laboratory

The demand for renewables such as solar and wind power has become stronger than ever in the past few decades and their numerous advantages have nearly risen to the status of common knowledge. However, as solar and wind power are intermittent in nature, the electricity generated from these renewable sources only comprise a low fraction of global electricity production. Enabling the widespread use of renewables requires energy storage technology that is site-independent, efficient, scalable, stable, cost-effective, safe, energy dense and continuous in operation. To date, none of the existing technologies have adequately met the attributes necessary for storing intermittent and scattered solar, wind and other sources of renewable energy. Pumped hydro and compressed air are scalable and cost-effective, but are limited by geography and geology [1].

关键词： demand technologies attributes

Annual growth of Fagus orientalis is limited by spring drought conditions in Iran’s Golestan Province

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Journal of Forestry Research 2024年第1期35卷 128-142页

作者： khalil Ghorbani Jahangir Mohammadi Laleh Rezaei Ghaleh Department of Water Engineering Faculty of Water and Soil EngineeringGorgan University of Agricultural Sciences and Natural ResourcesGorganIran Department of Forestry Gorgan University of Agricultural Sciences and Natural ResourcesGorganIran Department of Water Engineering Faculty of AgricultureUrmia UniversityUrmiaIran

Due to the lack of a uniform and accurate defi-nition of‘drought’,several indicators have been introduced based on different variables and methods,and the efficiency of each of these is determined according to their relationship with drought.The relationship between two drought indices,SPI(standardized precipitation index)and SPEI(standard-ized precipitation-evapotranspiration index)in different sea-sons was investigated using annual rings of 15 tree samples to determine the effect of drought on the growth of oriental beech(Fagus orientalis Lipsky)in the Hyrcanian forests of northern Iran.The different evapotranspiration calcula-tion methods were evaluated on SPEI efficiency based on Hargreaves-Samani,Thornthwaite,and Penman-Monteith methods using the step-by-step M5 decision tree regression method.The results show that SPEI based on the Penman-Monteith in a three-month time scale(spring)had similar temporal changes and a better relationship with annual tree rings(R^(2)=0.81)at a 0.05 significant level.Abrupt change and a decreasing trend in the time series of annual tree rings are similar to the variation in the SPEI based on the Penman-Monteith method.Factors affecting evapotranspiration,temperature,wind speed,and sunshine hours(used in the Penman-Monteith method),increased but precipitation decreased.Using non-linear modeling methods,SPEI based on Penman-Monteith best illustrated climate changes affecting tree growth.

关键词： Climate change Drought index Hyrcanian forests SPEI'Annual growth rings Fagus orientalis

An energy-degree evaluation metric for clustering purposes in mobile ad hoc networks

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International Journal of Modeling, Simulation, and Scientific Computing 2019年第2期10卷 114-132页

作者： khalil amine MOAD6 Research Team MASI LaboratoryE3S Research Centre Mohammadia School of Engineering Mohammed V University of RabatMorocco

Network clustering is the process of partitioning a network into a number of virtual entities mastered by certain nodes,called cluster centers that are responsible for collecting and maintaining topology information and managing the routing processes.In ad hoc networking,clustering has been introduced to deal with the dynamic topology by providing a temporarily stable network core.Clustering process mainly depends on the metric upon which the selection of cluster centers is performed.A wide range of clustering metrics were introduced in the literature based on network issues including mobility and connectivity degree,giving rise to a variety of clustering schemes.Although clustering provides energy consumption reduction,residual energy has not received enough attention and few studies have addressed the clustering on the basis of this feature.This paper discusses the current clustering metrics and proposes an energy-degree evaluation metric with mobility consideration taking into account the nodes residual energy and the network connectivity as two main keys of clustering.

关键词： Ad hoc networks clustering dominating set energy aware mobility

Exploring the molecular landscape of NNK-induced transformation:A comprehensive genome-wide CRISPR/Cas9 screening

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Genes & Diseases 2024年第4期11卷 42-44页

作者： Trang Dinh Mira Rahm Zhenghe Wang Christopher McFarland Athar khalil Department of Genetics and Genome Sciences Case WesternReserve UniversityClevelandOH44106USA

Lung cancer is the leading cause of cancer-related deaths worldwide,with an estimated 1.8 million deaths in 2020 alone.1 While several risk factors are associated with lung cancer,smoking remains the most significant environmental cause of the disease.1 One of the most potent carcinogens in tobacco smoke is 4-(methylnitrosoamino)-1-(3-pyridyl)-1-butanone(NNK),which is produced from nicotine through a series of metabolic reactions.

关键词： CRISPR/Cas9 NNK lung

Sentiment Analysis of Low-Resource Language Literature Using Data Processing and Deep Learning

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Computers, Materials & Continua 2024年第4期79卷 713-733页

作者： Aizaz Ali Maqbool Khan khalil Khan Rehan Ullah Khan Abdulrahman Aloraini Department of IT and Computer Science Pak-Austria Fachhochschule:Institute of Applied Sciences and TechnologyHaripur22620Pakistan Software Competence Center Hagenberg Softwarepark 32aHagenberg4232Austria Department of Computer Science School of Engineering and Digital SciencesNazarbayev UniversityAstana010000Kazakhstan Department of Information Technology College of ComputerQassim UniversityP.O.Box 1162BuraydahSaudi Arabia

Sentiment analysis, a crucial task in discerning emotional tones within the text, plays a pivotal role in understandingpublic opinion and user sentiment across diverse languages.While numerous scholars conduct sentiment analysisin widely spoken languages such as English, Chinese, Arabic, Roman Arabic, and more, we come to grapplingwith resource-poor languages like Urdu literature which becomes a challenge. Urdu is a uniquely crafted language,characterized by a script that amalgamates elements from diverse languages, including Arabic, Parsi, Pashtu,Turkish, Punjabi, Saraiki, and more. As Urdu literature, characterized by distinct character sets and linguisticfeatures, presents an additional hurdle due to the lack of accessible datasets, rendering sentiment analysis aformidable undertaking. The limited availability of resources has fueled increased interest among researchers,prompting a deeper exploration into Urdu sentiment analysis. This research is dedicated to Urdu languagesentiment analysis, employing sophisticated deep learning models on an extensive dataset categorized into fivelabels: Positive, Negative, Neutral, Mixed, and Ambiguous. The primary objective is to discern sentiments andemotions within the Urdu language, despite the absence of well-curated datasets. To tackle this challenge, theinitial step involves the creation of a comprehensive Urdu dataset by aggregating data from various sources such asnewspapers, articles, and socialmedia comments. Subsequent to this data collection, a thorough process of cleaningand preprocessing is implemented to ensure the quality of the data. The study leverages two well-known deeplearningmodels, namely Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN), for bothtraining and evaluating sentiment analysis performance. Additionally, the study explores hyperparameter tuning tooptimize the models’ efficacy. Evaluation metrics such as precision, recall, and the F1-score are employed to assessthe effectiveness of the models. The research findings revea

关键词： Urdu sentiment analysis convolutional neural networks recurrent neural network deep learning natural language processing neural networks

Numerical Exploration of Asymmetrical Impact Dynamics: Unveiling Nonlinearities in Collision Problems and Resilience of Reinforced Concrete Structures

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Structural Durability & Health Monitoring 2024年第3期18卷 223-254页

作者： AL-Bukhaiti khalil Yanhui Liu Shichun Zhao Daguang Han School of Civil Engineering Southwest Jiaotong UniversityChengdu610031China Faculty of Civil Engineering Southeast UniversityNanjingChina

This study provides a comprehensive analysis of collision and impact problems’ numerical solutions, focusing ongeometric, contact, and material nonlinearities, all essential in solving large deformation problems during a collision.The initial discussion revolves around the stress and strain of large deformation during a collision, followedby explanations of the fundamental finite element solution method for addressing such issues. The hourglassmode’s control methods, such as single-point reduced integration and contact-collision algorithms are detailedand implemented within the finite element framework. The paper further investigates the dynamic responseand failure modes of Reinforced Concrete (RC) members under asymmetrical impact using a 3D discrete modelin ABAQUS that treats steel bars and concrete connections as bond slips. The model’s validity was confirmedthrough comparisons with the node-sharing algorithm and system energy relations. Experimental parameterswere varied, including the rigid hammer’s mass and initial velocity, concrete strength, and longitudinal and stirrupreinforcement ratios. Findings indicated that increased hammer mass and velocity escalated RC member damage,while increased reinforcement ratios improved impact resistance. Contrarily, increased concrete strength did notsignificantly reduce lateral displacement when considering strain rate effects. The study also explores materialnonlinearity, examining different materials’ responses to collision-induced forces and stresses, demonstratedthrough an elastic rod impact case study. The paper proposes a damage criterion based on the residual axialload-bearing capacity for assessing damage under the asymmetrical impact, showing a correlation betweendamage degree hammer mass and initial velocity. The results, validated through comparison with theoreticaland analytical solutions, verify the ABAQUS program’s accuracy and reliability in analyzing impact problems,offering valuable insights into collision and impact problems’ nonlinearities and practic

关键词： Geometric nonlinearity contact nonlinearity material nonlinearity collision problems finite element method stress and strain damage criterion RC members asymmetrical impact

Data-driven modeling on anisotropic mechanical behavior of brain tissue with internal pressure

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Defence Technology（防务技术） 2024年第3期33卷 55-65页

作者： Zhiyuan Tang Yu Wang khalil I.Elkhodary Zefeng Yu Shan Tang Dan Peng State Key Laboratory of Structural Analysis Optimization and CAE Software for Industrial EquipmentDalian University of Technology116023DalianPR China The Department of Mechanical Engineering The American University in CairoNew Cairo11835Egypt Department of Neurology The Second Hospital of Dalian Medical UniversityDalian116023PR China

Brain tissue is one of the softest parts of the human body,composed of white matter and grey matter.The mechanical behavior of the brain tissue plays an essential role in regulating brain morphology and brain function.Besides,traumatic brain injury(TBI)and various brain diseases are also greatly influenced by the brain's mechanical properties.Whether white matter or grey matter,brain tissue contains multiscale structures composed of neurons,glial cells,fibers,blood vessels,etc.,each with different mechanical properties.As such,brain tissue exhibits complex mechanical behavior,usually with strong nonlinearity,heterogeneity,and directional dependence.Building a constitutive law for multiscale brain tissue using traditional function-based approaches can be very challenging.Instead,this paper proposes a data-driven approach to establish the desired mechanical model of brain tissue.We focus on blood vessels with internal pressure embedded in a white or grey matter matrix material to demonstrate our approach.The matrix is described by an isotropic or anisotropic nonlinear elastic model.A representative unit cell(RUC)with blood vessels is built,which is used to generate the stress-strain data under different internal blood pressure and various proportional displacement loading paths.The generated stress-strain data is then used to train a mechanical law using artificial neural networks to predict the macroscopic mechanical response of brain tissue under different internal pressures.Finally,the trained material model is implemented into finite element software to predict the mechanical behavior of a whole brain under intracranial pressure and distributed body forces.Compared with a direct numerical simulation that employs a reference material model,our proposed approach greatly reduces the computational cost and improves modeling efficiency.The predictions made by our trained model demonstrate sufficient accuracy.Specifically,we find that the level of internal blood pressure can greatly influence stress distribution and

关键词： Data driven Constitutive law Anisotropy Brain tissue Internal pressure

The necessity to expand mycorrhizal boundaries:Including the fungal endophytes that possess key mycorrhizal criteria

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Pedosphere 2024年第2期34卷 520-523页

作者： khalil KARIMAN Zed RENGEL Rodica PENA Saleh RAHIMLOU Mark TIBBETT UWA School of Agriculture and Environment The University of Western AustraliaPerth WA 6009Australia Department of Sustainable Land Management&Soil Research Centre School of AgriculturePolicy and DevelopmentUniversity of ReadingReading RG66ARUK Department of Ecology and Evolutionary Biology University of MichiganAnn Arbor MI 48109USA

Dear editor,This letter aims to urge the necessity to expand the boundaries of mycorrhizal symbiosis to include certain root fungal endophytes.The conventional classification of mycorrhizal associations emphasizes spe... 详细信息

关键词： editor specialized interface

Einstein Hybrid Structure of q-Rung Orthopair Fuzzy Soft Set and Its Application for Diagnosis of Waterborne Infectious Disease

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Computer Modeling in Engineering & Sciences 2024年第5期139卷 1863-1892页

作者： Rana Muhammad Zulqarnain Hafiz khalil ur Rehman Imran Siddique HijazAhmad Sameh Askar Shahid Hussain Gurmani School of Mathematical Sciences Zhejiang Normal UniversityJinhua321004China Department of Mathematics Government College UniversityFaisalabad38000Pakistan Department of Mathematics University of SargodhaSargodha40100Pakistan Section of Mathematics International Telematic University UninettunoCorso Vittorio Emanuele IIRoma3900186Italy Near East University Operational Research Center in HealthcareNear East BoulevardNicosia/Mersin 1099138Turkey Department of Statistics and Operations Research College of ScienceKing Saud UniversityPO Box 2455Riyadh11451Saudi Arabia

This research is devoted to diagnosing water-borne infectious diseases caused by floods employing a novel diagnosis approach,the Einstein hybrid structure of q-rung orthopair fuzzy soft set.This approach integrates parts of fuzzy logic and soft set theory to develop a robust alternative for disease detection in stressful situations,especially in areas affected by floods.Compared to the traditional intuitionistic fuzzy soft set and Pythagorean fuzzy soft set,the q-rung orthopair fuzzy soft set(q-ROFSS)adequately incorporates unclear and indeterminate facts.The major objective of this investigation is to formulate the q-rung orthopair fuzzy soft Einstein hybrid weighted average(q-ROFSEHWA)operator and its specific characteristics.Moreover,our stated operator is implementing intelligentmulti-criteria group decision-making(MCGDM)methodology.Floods are severe natural catastrophes that raise the risk of diseases and epidemics,particularly those caused by contaminants in the water,such as gastrointestinal diseases,respiratory infections,vector-borne diseases,skin infections,and water-borne parasites.The designed MCGDM strategy tackles the prevalence of certain conditions in flood-affected patients.A comparative investigation determined that the suggested method for detecting water-borne infectious disease due to floods is more effective and productive than conventional methods because of its logical structure.

关键词： q-rung orthopair fuzzy soft set q-ROFSEHWA operator MCGDM environmental disaster water-born infection disease