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Exploring the nano-fungicidal efficacy of green synthesized magnesium oxide nanoparticles(MgO NPs)on the development,physiology,and infection of carrot(Daucus carota L.)with Alternaria leaf blight(ALB):Molecular docking

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Journal of Integrative Agriculture 2023年第10期22卷 3069-3080页

作者： Lukman AHAMAD Azmat ALI KHAN Masudulla KHAN orudzhev farid Mahboob ALAM Plant Pathology/Nematology Laboratory Department of BotanyAligarh Muslim UniversityAligarh 202002India Regional Plant Quarantine Station Salt LakeKolkata 700097India Pharmaceutical Biotechnology Laboratory Department of Pharmaceutical ChemistryCollege of PharmacyKing Saud UniversityRiyadh 11451Saudi Arabia Botany Section Women’s CollegeAligarh Muslim UniversityAligarh 202002India Amirkhanov Institute of Physics Dagestan Federal Scientific CenterRussian Academy of SciencesMakhachkala 367003Russia Department of Safety Engineering Dongguk UniversityGyeongju-si 780714Republic of Korea

In this research,green synthesized magnesium oxide nanoparticles(MgO NPs)from lemon fruit extracts and their fungicidal potential was evaluated against Alternaria dauci infection on carrot(Daucus carota L.)under greenhouse *** scanning and transmission electron microscopy(SEM and TEM)and ultra-violet(UV)visible spectroscopy were used to validate and characterize MgO *** crystalline nature of MgONPs was determined using selected area electron diffraction(SAED).MgO NPs triggered substantial antifungal activity against *** when exposed to 50 and 100 mg L^(–1)concentrations but the higher antifungal potential was noticed in 100 mg L^(–1)under invitro *** fungal inoculated plants,a marked decrease in growth,photosynthetic pigments,and an increase in phenol,proline contents,and defense-related enzymes of carrot were seen over control(distilled water).However,foliar application of MgO NPs at 50 and 100 mg L^(–1)resulted in significant improvement of plant growth,photosynthetic pigments,phenol and proline contents,and defense enzymes activity of carrots with and without *** *** of MgO NPs at 100 mg L^(–1)had more plant length(17.11%),shoot dry weight(34.38%),plant fresh weight(20.46%),and root dry weight(49.09%)in carrots when challenged with *** over inoculated *** leaf blight indices and percent disease severity were also reduced in *** inoculated plants when sprayed with MgO *** non-bonding interactions of Alternaria genus protein with nanoparticles were studied using molecular docking.

关键词： green synthesis MgO nanoparticles alternaria leaf blight photosynthetic pigments defense enzymes carrot

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Numerical study of the near-wall vortical structures in particle-laden turbulent flow by a new vortex identification method-Liutex

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Journal of Hydrodynamics 2024年第1期36卷 53-60页

作者： farid Rousta Goodarz Ahmadi Bamdad Lessani Chaoqun Liu Department of Mechanical and Aerospace Engineering Clarkson UniversityPotsdamNYUSA Mechanical Engineering and Engineering Science The University of North Carolina at CharlotteNCUSA Department of Mathematics University of Texas at ArlingtonArlingtonTXUSA

This study investigates turbulent particle-laden channel flows using direct numerical simulations employing the Eulerian-Lagrangian method.A two-way coupling approach is adopted to explore the mutual interaction between particles and fluid *** considered cases include flow with particle Stokes number varying from St=2 up to St=100 while maintaining a constant Reynolds number of Reτ=180 across all cases.A novel vortex identification method,Liutex(Rortex),is employed to assess its efficacy in capturing near-wall turbulent coherent structures and their interactions with *** Liutex method provides valuable information on vortex strength and vectors at each location,enabling a detailed examination of the complex interaction between fluid and particulate *** widely acknowledged,the interplay between clockwise and counterclockwise vortices in the near-wall region gives rise to low-speed streaks along the *** low-speed streaks serve as preferential zones for particle concentration,depending upon the particle Stokes *** is shown that the Liutex method can capture these vortices and identify the location of low-speed ***,it is observed that the particle Stokes number(size)significantly affects both the strength of these vortices and the streaky structure exhibited by ***,a quantitative analysis of particle behavior in the near-wall region and the formation of elongated particle lines was carried *** involved examining the average fluid streamwise velocity fluctuations at particle locations,average particle concentration,and the normal velocity of particles for each set of particle Stokes *** investigation reveals the intricate interplay between particles and near-wall structures and the significant influence of particles Stokes *** study contributes to a deeper understanding of turbulent particle-laden channel flow dynamics.

关键词： Turbulent channel flow particle-laden flow direct numerical simulation(DNS) Eulerian-Lagrangian vortex identification turbulence coherent structures Liutex

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Triboelectric nanogenerators for self-powered neurostimulation

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Nano Research 2024年第10期17卷 8926-8941页

作者： Shumao Xu farid Manshaii Xiao Xiao Junyi Yin Jun Chen Department of Bioengineering University of CaliforniaLos AngelesLos AngelesCA 90095USA

The burgeoning field of soft bioelectronics heralds a new dawn in medical treatment for neurological and psychiatric conditions,presenting innovative methods for the stimulation,inhibition,and precise sensing of neuronal *** to these advancements is the challenge of power supply;devices dependent on traditional batteries face limitations regarding miniaturization and require invasive surgeries for battery *** nanogenerators(TENGs),which generate power from biomechanical movements,offer a promising solution for developing self-powered neurostimulation devices without the need for an external power *** review delves into recent progress in TENGs,with a focus on their application in selfpowered neurostimulation *** utility of TENGs across various nervous systems—including the center,autonomic,and somatic nervous systems—is explored and presented,highlighting the potential for these devices to facilitate neurological *** summarizing TENGs’operational details and the potential for clinical translation,this review also identifies challenges associated with the implantation and integration of neural electrodes and presents recent advances in solutions,aiming to reshape electric treatments for neurological diseases.

关键词： triboelectric nanogenerators neurostimulation self-powered soft bioelectronics biomechanical energy harvesting

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Integrated hazard assessment of rockfall incidents in the Cap Aokas Cliff Region

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Journal of Mountain Science 2024年第6期21卷 1916-1929页

作者： Zohra LADJEL farid ZAHRI Riheb HADJI Younes HAMED Karim ZIGHMI Kaddour BENMARCE Department of Earth Sciences Institute of Architecture and Earth SciencesFerhat Abbas UniversitySetif 19137Algeria Unit of Emerging Materials Research Ferhat Abbes UniversitySétif 19137Algeria Laboratory of Applied Research in Engineering Geology GeotechnicsWater Sciencesand EnvironmentFerhat Abbas UniversitySetif 19137Algeria International Association of Water Resources in the Southern Mediterranean Basin Gafsa 2112Tunisia Department of Earth Sciences Faculty of SciencesUniversity of GafsaGafsa 2112Tunisia

Rock fall accidents in mountainous cliff areas have significant consequences for human life and *** study aimed to evaluate the rockfall hazard in the Cap Aokas cliff region located along the northeast coast of Algeria by identifying the key factors contributing to rockfall *** employed a combination of kinematic analysis,Matterocking method,and 3D trajectory simulations to determine zones that are susceptible to rockfall *** using a probabilistic and structural approach in conjunction with photogrammetry,we identified the controlling *** kinematic analysis revealed the presence of five discontinuity families,which indicated both plane and wedge failure *** 3D trajectory simulations demonstrated that the falling blocks followed the stream *** then validated the susceptibility maps generated from the analysis using aerial photos and historical rockfall *** findings of this study enhance our understanding of rockfall phenomena and provide valuable insights for the development of effective strategies to mitigate rockfall hazards.

关键词： Trajectory simulations Probabilistic analysis Structural approach Rockfall hazard Cap Aokas cliff

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Addressing metallosis in knee arthroplasty:From diagnostic challenges to innovative treatments

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World Journal of Orthopedics 2024年第5期15卷 386-389页

作者： Yvon Maurice Bogdonoff farid Amirouche Department of Orthopedics Surgery University of Illinois at ChicagoChicagoIL 60612United States Department of Orthopedics Surgery Northshore University Health SystemSkokieIL 60076United States

In this editorial,we comment on the article by Toro et al published in the recent issue of World Journal of *** editorial review provides a comprehensive exploration of the landscape surrounding knee arthroplasty metallosis,focusing on key aspects ranging from the mechanisms influencing susceptibility to clinical implications and advanced treatment *** elucidate the complex interplay of implant design,patient-specific variables,and wear-related processes contributing to ***,we seek to shed light on diagnostic challenges,the necessity of a multidisciplinary approach,and the imperative for vigilant implant ***-on-uni revision,as a targeted treatment modality,is discussed,highlighting its potential to address metallosis in unicompartmental knee arthroplasty(UKA).There is a need for heightened awareness among clinicians regarding the subtle presentations of metallosis,coupled with the limitations of traditional imaging *** metallosis requires a collaborative,multidisciplinary approach to effectively navigate the complexities associated with this ***,the review emphasizes the evolving paradigm of personalized care,with uni-on-uni revision emerging as a promising surgical *** conclusion,the editorial outlines the dynamic nature of knee arthroplasty metallosis and its multifaceted impact on clinical *** calls for ongoing collaboration,education,and integration of innovative solutions to enhance diagnostic accuracy,proactive management,and overall patient outcomes in the realm of UKA.

关键词： Ultrasound X-ray Total knee arthroplasty Case report Review Editorial

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Predicting grain size-dependent superplastic properties in friction stir processed ZK30 magnesium alloy with machine learning methods

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Journal of Magnesium and Alloys 2024年第5期12卷 1931-1943页

作者： farid Bahari-Sambran Fernando Carreno C.M.Cepeda-Jiménez Alberto Orozco-Caballero Physical Metallurgy Department CENIM-CSICAv.Gregorio del Amo 828040 MadridSpain Department of Mechanical Engineering Chemistry and Industrial DesignPolytechnic University of MadridRonda de Valencia 328012MadridSpain

The aim of this work is to predict,for the first time,the high temperature flow stress dependency with the grain size and the underlaid deformation mechanism using two machine learning models,random forest(RF)and artificial neural network(ANN).With that purpose,a ZK30 magnesium alloy was friction stir processed(FSP)using three different severe conditions to obtain fine grain microstructures(with average grain sizes between 2 and 3μm)prone to extensive superplastic *** three friction stir processed samples clearly deformed by grain boundary sliding(GBS)deformation mechanism at high *** maximum elongations to failure,well over 400% at high strain rate of 10^(-2)s^(-1),were reached at 400℃ in the material with coarsest grain size of 2.8μm,and at 300℃ for the finest grain size of 2μ***,the superplastic response decreased at 350℃ and 400℃ due to thermal instabilities and grain coarsening,which makes it difficult to assess the operative deformation mechanism at such *** work highlights that the machine learning models considered,especially the ANN model with higher accuracy in predicting flow stress values,allow determining adequately the superplastic creep behavior including other possible grain size scenarios.

关键词： Machine learning Artificial intelligence Magnesium alloys Superplasticity Friction stir processing Grain coarsening

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An integrated computational method for calculating dynamic thermal bridges of building facades in tropical countries

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Frontiers of Architectural Research 2024年第1期13卷 201-218页

作者： Miktha farid Alkadri Muhammad Rafif Cahyadi Agung Francesco De Luca Research Cluster of Architectural Sciences and Building Technology Department of ArchitectureFaculty of EngineeringUniversitas IndonesiaDepok 16425Indonesia Department of Civil Engineering and Architecture Tallinn University of TechnologyTallinn 19086Estonia

Identifying thermal bridges on building façades has been a great challenge for architects,especially during the conceptual design *** is not only due to the complexity of parameters when calculating thermal bridges,but also lack of feature integration between building energy simulation(BES)tools and the actual building *** example,existing BES tools predominantly calculate thermal bridges only in steady state without considering the temperature dynamic behaviour of building ***,relevant features such as thermal delay,decrement factor,and operative temperature are often neglected,and this can lead to miscalculation of energy *** study then proposes an integrated method to calculate dynamic thermal bridges under transient conditions by incorporating field observations and computational simulations of thermal *** specifically,the proposed method employs several measurement tools such as HOBO data logger to record the actual conditions of indoor and outdoor room temperature and thermal cameras to identify the surface temperature of selected building *** actual datasets are then integrated with the simulation workflow developed in BES *** study ultimately enables architects not only to identify potential thermal bridges on existing building façades but also to support material and geometric exploration in early design phase.

关键词： Thermal bridges Dynamic calculation Thermal delay Cooling load Computational design method

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Deep learning automation of radiographic patterns for hallux valgus diagnosis

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World Journal of Orthopedics 2024年第2期15卷 105-109页

作者： Angela Hussain Cadence Lee Eric Hu farid Amirouche Department of Orthopaedic Surgery University of Illinois College of MedicineChicagoIL 60612United States Department of Orthopaedics Surgery University of Illinois at ChicagoChicagoIL 60612United States Department of Orthopaedic Surgery Northshore University Health SystemSkokieIL 6007United States

Artificial intelligence(AI)and deep learning are becoming increasingly powerful tools in diagnostic and radiographic *** learning has already been utilized for automated detection of pneumonia from chest radiographs,diabetic retinopathy,breast cancer,skin carcinoma classification,and metastatic lymphadenopathy detection,with diagnostic reliability akin to medical *** the World Journal of Orthopedics article,the authors apply an automated and AIassisted technique to determine the hallux valgus angle(HVA)for assessing HV foot *** the U-net neural network,the authors constructed an algorithm for pattern recognition of HV foot deformity from anteroposterior highresolution *** performance of the deep learning algorithm was compared to expert clinician manual performance and assessed alongside clinician-clinician *** authors found that the AI tool was sufficient in assessing HVA and proposed the system as an instrument to augment clinical *** further sophistication is needed to establish automated algorithms for more complicated foot pathologies,this work adds to the growing evidence supporting AI as a powerful diagnostic tool.

关键词： Artificial intelligence Hallux valgus Deep learning Automated radiography

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The combined effects of farm yard manure and boron application on growth,and oil quality of Canola grown under newly reclaimed soils

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Oil Crop Science 2024年第1期9卷 53-59页

作者： farid Hellal Saied El Sayed Amany Abdel Mohsen Ramadan Doaa M.Abobasha Plant Nutrition Department National Research Centre33 El-Behouth St12622DokkiCairoEgypt Botany Department National Research Centre33 El-Behouth St12622DokkiCairoEgypt

Two field experiments were conducted during the main seasons of 2021/2022 at the Research and Production Station of National Research Centre in Egypt to investigate the effects of farmyard manure(FYM)and boron on Canola growth,yield,oil yield,and *** results unequivocally demonstrated that the combined application of FYM at a rate of 14.4 ton ha^(-1)with a foliar spray of boron at 100 ppm positively influenced plant characteristics,leading to enhanced growth rates and higher yields compared to the control ***,this integrated approach significantly improved nutrient content by enhancing levels of oil content,carbohydrates,proteins,phenolics,flavonoids,and total soluble *** findings provide compelling evidence that utilizing farm manure along with boron can effectively enhance Canola properties in newly reclaimed soils while promoting sustainable agricultural practices.

关键词： Oil quality Farmyard manure Phytochemical content Canola Yield production

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CapsNet-FR: Capsule Networks for Improved Recognition of Facial Features

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Computers, Materials & Continua 2024年第5期79卷 2169-2186页

作者： Mahmood Ul Haq Muhammad Athar Javed Sethi Najib Ben Aoun Ala Saleh Alluhaidan Sadique Ahmad Zahid farid Department of Computer System Engineering University of Engineering&TechnologyPeshawar25000Pakistan College of Computer Science and Information Technology Al-Baha UniversityAlaqiq65779-7738Saudi Arabia REGIM-Lab:Research Groups in Intelligent Machines National School of Engineers of Sfax(ENIS)University of SfaxSfax3038Tunisia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh84428Saudi Arabia EIAS:Data Science and Blockchain Laboratory College of Computer and Information SciencesPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Computer Sciences Bahria University Karachi CampusKarachi541004Pakistan Department of Electrical Engineering Abasyn UniversityPeshawar25000Pakistan

Face recognition (FR) technology has numerous applications in artificial intelligence including biometrics, security,authentication, law enforcement, and surveillance. Deep learning (DL) models, notably convolutional neuralnetworks (CNNs), have shown promising results in the field of FR. However CNNs are easily fooled since theydo not encode position and orientation correlations between features. Hinton et al. envisioned Capsule Networksas a more robust design capable of retaining pose information and spatial correlations to recognize objects morelike the brain does. Lower-level capsules hold 8-dimensional vectors of attributes like position, hue, texture, andso on, which are routed to higher-level capsules via a new routing by agreement algorithm. This provides capsulenetworks with viewpoint invariance, which has previously evaded CNNs. This research presents a FR model basedon capsule networks that was tested using the LFW dataset, COMSATS face dataset, and own acquired photos usingcameras measuring 128 × 128 pixels, 40 × 40 pixels, and 30 × 30 pixels. The trained model outperforms state-ofthe-art algorithms, achieving 95.82% test accuracy and performing well on unseen faces that have been blurred orrotated. Additionally, the suggested model outperformed the recently released approaches on the COMSATS facedataset, achieving a high accuracy of 92.47%. Based on the results of this research as well as previous results, capsulenetworks perform better than deeper CNNs on unobserved altered data because of their special equivarianceproperties.

关键词： CapsNet face recognition artificial intelligence

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