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

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 *** 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 *** 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 *** 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 *** 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 *** affecting evapotranspiration,temperature,wind speed,and sunshine hours(used in the Penman-Monteith method),increased but precipitation *** 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

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Pore-scale study of the effects of DTPA chelating agent flooding on oil recovery utilizing a clay-coated micromodel

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Petroleum Research 2024年第2期9卷 228-237页

作者： Hojjat Mohammadzadeh Jamshid Moghadasi khalil Shahbazi Shahin Kord Department of Petroleum Engineering Ahwaz Faculty of Petroleum EngineeringPetroleum University of TechnologyAhwazIran

The use of diethylenetriaminepentaacetic acid(DTPA)chelating agent has shown promising results for enhanced oil recovery(EOR)in prior *** mechanisms,mainly resulting from rock-fluid interaction,have been proposed for chelating agent flooding;however,little attention has been paid to fluid-fluid interaction thus *** assessment of these mechanisms has primarily relied on macroscopic techniques such as core *** paper aims to investigate the injection of DTPA brine and its dominant mechanisms at the pore scale using a clay-coated *** micromodel tests were performed under oil-wet and water-wet *** a more precise examination of fluid/fluid interactions,the dynamic interfacial tension(IFT)and Zeta potential were *** was observed that the injection of DTPA brine in water-wet state changed the saturation distribution and increased oil *** on visual inspections,this change in saturation distribution could potentially be linked to the formation of micro-dispersions and viscoelastic interfacial ***-dispersions facilitate flow to unswept areas,and viscoelastic interface formation reshapes the interface between oil and brine,causing disconnected oil droplets to coalesce and thus increase *** the oil-wet state,the micro-dispersion formation and wettability alteration can be the dominant mechanisms,and the amount of recovered oil was higher than that observed in the water-wet ***,Zeta potential measurements at the interface between brine and oil showed a more negative value for DTPA brine,which is effective in wettability alteration and micro-dispersions *** results indicate that IFT reduction was not significant enough to be considered the dominant mechanism,although it assists in DTPA brine penetration into the crude oil and subsequent micro-dispersion formation.

关键词： Enhanced oil recovery technique Chelating agent Micromodel Fluid/fluid interaction Micro-dispersions Viscoelastic interface

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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 *** 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 effectiv

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

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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 *** mechanical behavior of the brain tissue plays an essential role in regulating brain morphology and brain ***,traumatic brain injury(TBI)and various brain diseases are also greatly influenced by the brain's mechanical *** white matter or grey matter,brain tissue contains multiscale structures composed of neurons,glial cells,fibers,blood vessels,etc.,each with different mechanical *** such,brain tissue exhibits complex mechanical behavior,usually with strong nonlinearity,heterogeneity,and directional *** a constitutive law for multiscale brain tissue using traditional function-based approaches can be very ***,this paper proposes a data-driven approach to establish the desired mechanical model of brain *** focus on blood vessels with internal pressure embedded in a white or grey matter matrix material to demonstrate our *** 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 *** 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 ***,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 *** with a direct numerical simulation that employs a reference material model,our proposed approach greatly reduces the computational cost and improves modeling *** predictions made by our trained model demonstrate sufficient ***,we find that the level of internal blood pressur

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

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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 *** conventional classification of mycorrhizal associations emphasizes specialized fu... 详细信息

关键词： editor specialized interface

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Strong coupling and catenary field enhancement in the hybrid plasmonic metamaterial cavity and TMDC monolayers

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Opto-Electronic Advances 2024年第5期7卷 20-32页

作者： Andergachew Mekonnen Berhe khalil As’ham Ibrahim Al-Ani Haroldo T.Hattori Andrey E.Miroshnichenko School of Engineering and Technology University of New South Wales at CanberraNorthcott DriveCanberra ACT 2610Australia

Strong coupling between resonantly matched surface plasmons of metals and excitons of quantum emitters results in the formation of new plasmon-exciton hybridized energy *** plasmon-exciton strong coupling,plasmonic nanocavities play a significant role due to their ability to confine light in an ultrasmall ***,two-dimensional transition metal dichalcogenides(TMDCs) have a significant exciton binding energy and remain stable at ambient conditions,making them an excellent alternative for investigating light-matter *** a result,strong plasmon-exciton coupling has been reported by introducing a single metallic ***,single nanoparticles have lower spatial confinement of electromagnetic fields and limited tunability to match the excitonic ***,we introduce the concept of catenary-shaped optical fields induced by plasmonic metamaterial cavities to scale the strength of plasmon-exciton *** demonstrated plasmon modes of metallic metamaterial cavities offer high confinement and tunability and can match with the excitons of TMDCs to exhibit a strong coupling regime by tuning either the size of the cavity gap or *** calculated Rabi splitting of Au-MoSe_2 and Au-WSe_2 heterostructures strongly depends on the catenary-like field enhancement induced by the Au cavity,resulting in room-temperature Rabi splitting ranging between 77.86 and 320 me *** plasmonic metamaterial cavities can pave the way for manipulating excitons in TMDCs and operating active nanophotonic devices at ambient temperature.

关键词： catenary-shaped field enhancement strong coupling plasmon exciton Rabi splitting

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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 *** 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 *** 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 *** major objective of this investigation is to formulate the q-rung orthopair fuzzy soft Einstein hybrid weighted average(q-ROFSEHWA)operator and its specific ***,our stated operator is implementing intelligentmulti-criteria group decision-making(MCGDM)*** 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 *** 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

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Cervical Cancer Prediction Empowered with Federated Machine Learning

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Computers, Materials & Continua 2024年第4期79卷 963-981页

作者： Muhammad Umar Nasir Omar Kassem khalil Karamath Ateeq Bassam SaleemAllah Almogadwy M.A.Khan Khan Muhammad Adnan Department of Computer Sciences Bahria University Lahore CampusLahore54000Pakistan Faculty of Information Technology Liwa CollegeAbu Dhabi20009UAE Department of Computing Skyline University CollegeSharjah999041UAE Department of Computer Science Taibah UniversityMedina42315Saudi Arabia Riphah School of Computing and Innovation Faculty of ComputingRiphah International UniversityLahore54000Pakistan Department of Software Faculty of Artificial Intelligence and SoftwareGachon UniversitySeongnam13120Korea

Cervical cancer is an intrusive cancer that imitates various women around the world. Cervical cancer ranks in thefourth position because of the leading death cause in its premature stages. The cervix which is the lower end of thevagina that connects the uterus and vagina forms a cancerous tumor very slowly. This pre-mature cancerous tumorin the cervix is deadly if it cannot be detected in the early stages. So, in this delineated study, the proposed approachuses federated machine learning with numerous machine learning solvers for the prediction of cervical cancer totrain the weights with varying neurons empowered fuzzed techniques to align the neurons, Internet of MedicalThings (IoMT) to fetch data and blockchain technology for data privacy and models protection from hazardousattacks. The proposed approach achieves the highest cervical cancer prediction accuracy of 99.26% and a 0.74%misprediction rate. So, the proposed approach shows the best prediction results of cervical cancer in its early stageswith the help of patient clinical records, and all medical professionals will get beneficial diagnosing approachesfrom this study and detect cervical cancer in its early stages which reduce the overall death ratio of women due tocervical cancer.

关键词： Cervical cancer federated machine learning neurons blockchain technology

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Federated Machine Learning Based Fetal Health Prediction Empowered with Bio-Signal Cardiotocography

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Computers, Materials & Continua 2024年第3期78卷 3303-3321页

作者： Muhammad Umar Nasir Omar Kassem khalil Karamath Ateeq Bassam SaleemAllah Almogadwy Muhammad Adnan Khan Muhammad Hasnain Azam Khan Muhammad Adnan Department of Computer Sciences Bahria University Lahore CampusLahore54000Pakistan Faculty of Information Technology Liwa CollegeAbu Dhabi00000United Arab Emirates Department of Computing Skyline University CollegeSharjah1797United Arab Emirates Department of Computer Science Taibah UniversityMedina42353Saudi Arabia Riphah School of Computing and Innovation Faculty of ComputingRiphah International UniversityLahore CampusLahore54000Pakistan Department of Engineering and Development Dubizzle LabsLahore54000Pakistan Department of Software Faculty of Artificial Intelligence and SoftwareGachon UniversitySeongnam-si13120Korea

Cardiotocography measures the fetal heart rate in the fetus during pregnancy to ensure physical health because cardiotocography gives data about fetal heart rate and uterine shrinkages which is very beneficial to detect whether the fetus is normal or suspect or *** cardiotocography measures infer wrongly and give wrong predictions because of human *** traditional way of reading the cardiotocography measures is the time taken and belongs to numerous human errors as *** condition is very important to measure at numerous stages and give proper medications to the fetus for its *** the current period Machine learning(ML)is a well-known classification strategy used in the biomedical field on various issues because ML is very fast and gives appropriate results that are better than traditional *** techniques play a pivotal role in detecting fetal disease in its early *** research article uses Federated machine learning(FML)and ML techniques to classify the condition of the *** study proposed a model for the detection of bio-signal cardiotocography that uses FML and ML techniques to train and test the ***,the proposed model of FML used numerous data preprocessing techniques to overcome data deficiency and achieves 99.06%and 0.94%of prediction accuracy and misprediction rate,respectively,and parallel the proposed model applying K-nearest neighbor(KNN)and achieves 82.93%and 17.07%of prediction accuracy and misprediction accuracy,***,by comparing both models FML outperformed the KNN technique and achieved the best and most appropriate prediction results as compared with previous studies the proposed study achieves the best and most accurate results.

关键词： Cardiotocography ML FML fetal disease bio-signal

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Hetero-phase zirconia encapsulated with Au nanoparticles for boosting electrocatalytic nitrogen reduction

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Chinese Chemical Letters 2024年第5期35卷 509-513页

作者： Xue Xin Qiming Qu Islam E.khalil Yuting Huang Mo Wei Jie Chen Weina Zhang Fengwei Huo Wenjing Liu Key Laboratory of Flexible Electronics(KLOFE)&Institute of Advanced Materials(IAM) Nanjing Tech UniversityNanjing 211816China

Electrocatalytic nitrogen reduction reaction(NRR)is considered as an attractive approach for ammonia synthesis under mild conditions.A bottleneck of NRR is the exploration of efficient catalysts for accelerating reaction kinetics,among which heterogeneous structures possessing distinct atomic arrangement could modify electronic structure,and therefore altering their NRR ***,we report a facile strategy for fabricating hetero-phase metal oxides derived from metal organic framework that are further integrated with Au nanoparticles as NRR *** phase composition of zirconia can be easily adjusted by simply changing the reaction temperature,where the monoclinic and tetragonal phases with the roughly close proportions have a distinct interface,leading to a strong interaction between Au and ZrO_(2).The enhanced interaction renders Au to be more electropositive and facilitates stronger binding to N_(2).As a result,a remarkable ammonia yield of 22.32μg h^(-1)mg_(cat.)^(-1) and a Faradaic efficiency of 31.92%can be achieved at low *** work is expected to pave the way for the design of heterogeneous structures and the exploration of hetero-phase nanostructures in boosting the electrocatalytic NRR.

关键词： Hetero-phase Metal-organic framework derivatives Zirconia Nitrogen reduction reaction Electrochemistry

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