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Synergistic effect of adsorption and photocatalytic degradation of oilfield-produced water by electrospun photocatalytic fibers of Polystyrene/Nanorod-Graphitic carbon nitride

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Journal of Environmental Sciences 2024年第7期141卷 287-303页

作者： Parisa Azmoon Mehrdad Farhadian Alireza Pendashteh amir h.Navarchian Department of Chemical Engineering Faculty of EngineeringUniversity of IsfahanIsfahanIran Department of Chemical Engineering Faculty of EngineeringUniversity of GuilanRashtIran Department of Water and Environmental Engineering Caspian Sea Basin Research CenterUniversity of GuilanRashtIran

Graphitic carbon nitride with nanorod structure(Nr-GCN)was synthesized using melamine as a precursor without any other reagents by hydrothermal pretreatment ***,FTIR,SEM,N_(2)adsorption-desorption from BET,UV-Vis DRS spectroscopy,and photoluminescence were used to characterize the prepared ***,the photoelectrochemical behavior of nanoparticles was studied by photocurrent transient response and cyclic voltammetry ***(PS)fibrous mat was fabricated by electrospinning technique and used as a support for the stabilization of the *** performance of the synthesized nanoparticles and photocatalytic fibers(PS/Nr-GCN)was evaluated in oilfield-produced water treatment under visible light *** this process,oil contaminants were adsorbed by hydrophobic polystyrene fibers and simultaneously degraded by *** removal efficiency of chemical oxygen demand(COD)has been obtained 96.6%and 98.4%by Nr-GCN and PS/Nr-GCN,respectively,at the optimum conditions of ph4,photocatalyst dosage 0.5 g/L,COD initial concentration 550 mg/L,and illumination time 150 *** gas chromatography-mass spectroscopy analysis results showed 99.3%removal of total petroleum hydrocarbons using photocatalytic fibers of PS/*** results demonstrated that the GCN has outstanding features like controllable morphology,visible-light-driven,and showing high potential in oily wastewater ***,the synergistic effect of adsorption and photocatalytic degradation is an effective technique in oilfield-produced water treatment.

关键词： Graphitic carbon nitride(GCN) Nanorod structure Polystyrene fibrous mat Photocatalytic fibers Oilfield-produced water(OPW)

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Prediction of vertical displacement for a buried pipeline subjected to normal fault using a hybrid FEM-ANN approach

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Frontiers of Structural and Civil Engineering 2024年第3期18卷 428-443页

作者： hedye JALALI Reza YEGANEh KhAKSAR Danial MOhAMMADZADEh S. Nader KARBALLAEEZADEh amir h.GANDOMI Department of Civil Engineering Architecture and UrbanismSadjad University of TechnologyPO Box ***MashhadIran Department of Civil Engineering Faculty of EngineeringEqbal Lahoori Institute of Higher EducationPO Box ***MashhadIran Faculty of Civil Engineering Architectureand ArtScience and Research Branch of Islamic Azad UniversityPO Box ***TehranIran Faculty of Engineering&Information Technology University of Technology SydneyUltimoNSW 2007Australia University Research and Innovation Center(EKIK) Óbuda UniversityBudapest 1034Hungary

Fault movement during earthquakes is a geotechnical phenomenon threatening buried pipelines and with the potential to cause severe damage to critical ***,effective prediction of pipe displacement is crucial for preventive management *** study aims to develop a fast,hybrid model for predicting vertical displacement of pipe networks when they experience *** this study,the complex behavior of soil and a buried pipeline system subjected to a normal fault is analyzed by using an artificial neural network(ANN)to generate predictions the behavior of the soil when different parameters of it are *** this purpose,a finite element model is developed for a pipeline subjected to normal fault *** data bank used for training the ANN includes all the critical soil parameters(cohesion,internal friction angle,Young’s modulus,and faulting).Furthermore,a mathematical formula is presented,based on biases and weights of the ANN *** results show that the maximum error of the presented formula is 2.03%,which makes the proposed technique efficiently predict the vertical displacement of buried pipelines and hence,helps to optimize the upcoming pipeline projects.

关键词： buried pipelines normal Fault finite element method multilayer perceptron neural network formulation

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Machine learning based models for predicting compressive strength of geopolymer concrete

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Frontiers of Structural and Civil Engineering 2024年第7期18卷 1028-1049页

作者： Quang-huy LE Duy-hung NGUYEN Thanh SANG-TO Samir KhATIR hoang LE-MINh amir h.GANDOMI Thanh CUONG-LE Center for Engineering Application and Technology Solutions Ho Chi Minh City Open UniversityHo Chi Minh 700000Vietnam Institute of Civil Engineering Ho Chi Minh City University of TransportHo Chi Minh 700000Vietnam Faculty of Engineering&Information Technology University of Technology SydneyUltimoNSW 2007Australia

Recently,great attention has been paid to geopolymer concrete due to its advantageous mechanical and environmentally friendly *** effort has been made in experimental studies to advance the understanding of geopolymer concrete,in which compressive strength is one of the most important *** facilitate engineering work on the material,an efficient predicting model is *** this study,three machine learning(ML)-based models,namely deep neural network(DNN),K-nearest neighbors(KNN),and support vector machines(SVM),are developed for forecasting the compressive strength of the geopolymer concrete.A total of 375 experimental samples are collected from the literature to build a database for the development of the predicting models.A careful procedure for data preprocessing is implemented,by which outliers are examined and removed from the database and input variables are standardized before feeding to the fitting *** standard K-fold cross-validation approach is applied for evaluating the performance of the models so that overfitting status is well managed,thus the generalizability of the models is *** effectiveness of the models is assessed via statistical metrics including root mean squared error(RMSE),mean absolute error(MAE),correlation coefficient(R),and the recently proposed performance index(PI).The basic mean square error(MSE)is used as the loss function to be minimized during the model fitting *** three ML-based models are successfully developed for estimating the compressive strength,for which good correlations between the predicted and the true values are obtained for DNN,KNN,and *** numerical results suggest that the DNN model generally outperforms the other two models.

关键词： geopolymer concrete compressive strength prediction machine-learning based model deep neural network K-nearest neighbor support vector machines

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Davidson base as an appropriate base for the shell model in the case of 1p- and 1h- nuclei

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Communications in Theoretical Physics 2024年第10期76卷 94-100页

作者： hadi Sobhani Yan-An Luo amir Jalili hassan hassanabadi School of Physics Nankai University Department of Physics Zhejiang Sci-Tech University Institute of Theoretical Physics Faculty of Physics University of Warsaw Institute of Actuarial Science and Data Analytics UCSI University

This study endeavors to develop an improved set of basis functions for nuclear shell-model calculations. The shell model, a well-established approach to understanding nuclear structure,typically employs the harmonic oscillator potential within the mean-field approximation. Given the extensive validation and consistency of harmonic oscillator results with experimental data,we propose a modification by incorporating a centrifugal term that converges toward the Davidson potential. This potential has been extensively studied, and we aim to extract relevant experimental data for the simplest cases in the shell model, namely one-particle and one-hole nuclei. A comprehensive comparison between the Davidson-based results and the harmonic oscillator calculations is presented to demonstrate the effectiveness of the new basis functions.

关键词： beta decay gamma transition nuclear structure shell-model calculations

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high-Performance Flow Classification of Big Data Using hybrid CPU-GPU Clusters of Cloud Environments

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Tsinghua Science and Technology 2024年第4期29卷 1118-1137页

作者： Azam Fazel-Najafabadi Mahdi Abbasi hani h.Attar Ayman Amer amir Taherkordi Azad Shokrollahi Mohammad R.Khosravi Ahmed A.Solyman Department of Computer Engineering Faculty of EngineeringBu-Ali Sina UniversityHamedan ***Iran Department of Energy Engineering Zarqa UniversityZarqa 13132Jordan Department of Informatics University of OsloOslo 0316Norway Department of Computer Science MalmöUniversityMalmö20506Sweden Shandong Provincial University Laboratory for Protected horticulture Weifang University of Science and TechnologyWeifang 261100China Department of Electrical and Electronics Engineering NişantaşıUniversityIstanbul 34481742Türkiye

The network switches in the data plane of Software Defined Networking (SDN) are empowered by an elementary process, in which enormous number of packets which resemble big volumes of data are classified into specific flows by matching them against a set of dynamic rules. This basic process accelerates the processing of data, so that instead of processing singular packets repeatedly, corresponding actions are performed on corresponding flows of packets. In this paper, first, we address limitations on a typical packet classification algorithm like Tuple Space Search (TSS). Then, we present a set of different scenarios to parallelize it on different parallel processing platforms, including Graphics Processing Units (GPUs), clusters of Central Processing Units (CPUs), and hybrid clusters. Experimental results show that the hybrid cluster provides the best platform for parallelizing packet classification algorithms, which promises the average throughput rate of 4.2 Million packets per second (Mpps). That is, the hybrid cluster produced by the integration of Compute Unified Device Architecture (CUDA), Message Passing Interface (MPI), and OpenMP programming model could classify 0.24 million packets per second more than the GPU cluster scheme. Such a packet classifier satisfies the required processing speed in the programmable network systems that would be used to communicate big medical data.

关键词： OpenMP Compute Unified Device Architecture(CUDA) Message Passing Interface(MPI) packet classification medical data tuple space algorithm Graphics Processing Unit(GPU)cluster

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Boron Nitride-Integrated Lithium Batteries: Exploring Innovations in Longevity and Performance

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ENERGY & ENVIRONMENTAL MATERIALS 2024年第6期7卷 13-40页

作者： Angizi, Shayan Alem, Sayed Ali Ahmad Torabian, Mahdi Khalaj, Maryam Golberg, Dmitri Pakdel, amir McMaster Univ Dept Chem Engn 1280 Main St W Hamilton ON L8S 4L7 Canada Montan Univ Leoben Inst Chem Polymer Mat Otto Glockel Str 2 A-8700 Leoben Austria Politecn Milan Dept Chem Mat & Chem Engn Piazza Leonardo Vinci 32 I-20133 Milan Italy Northwestern Univ Dept Mat Sci & Engn Evanston IL 60208 USA Queensland Univ Technol QUT Ctr Mat Sci 2 George Brisbane Qld 4000 Australia Queensland Univ Technol QUT Sch Chem & Phys 2 George Brisbane Qld 4000 Australia Natl Inst Mat Sci NIMS Res Ctr Mat Nanoarchitecton MANA Namiki 1 Ibaraki 3050044 Japan Univ Dublin Trinity Coll Dublin Dept Mech Mfg & Biomed Engn Dublin D02PN40 Ireland

The current global warming, coupled with the growing demand for energy in our daily lives, necessitates the development of more efficient and reliable energy storage devices. Lithium batteries (LBs) are at the forefront of emerging power sources addressing these challenges. Recent studies have shown that integrating hexagonal boron nitride (h-BN) nanomaterials into LBs enhances the safety, longevity, and electrochemical performance of all LB components, including electrodes, electrolytes, and separators, thereby suggesting their potential value in advancing eco-friendly energy solutions. This review provides an overview of the most recent applications of h-BN nanomaterials in LBs. It begins with an informative introduction to h-BN nanomaterials and their relevant properties in the context of LB applications. Subsequently, it addresses the challenges posed by h-BN and discusses existing strategies to overcome these limitations, offering valuable insights into the potential of BN nanomaterials. The review then proceeds to outline the functions of h-BN in LB components, emphasizing the molecular-level mechanisms responsible for performance improvements. Finally, the review concludes by presenting the current challenges and prospects of integrating h-BN nanomaterials into battery research. Integrating h-BN into lithium batteries enhances safety, longevity, and mechanical integrity of battery components by mitigating dendritic growth and side reactions. Its high ionic and thermal conductivities improve lithium transference and heat management, enhancing performance and reliability. image

关键词： electrode electrolyte hexagonal boron nitride lithium battery separator METAL BATTERIES h-BN ION BATTERIES 2-DIMENSIONAL MATERIALS POLYMER ELECTROLYTE hIGh-TEMPERATURE ANODES NANOShEETS DENDRITE FUNCTIONALIZATION

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Analysis of Ch_(4) and h_(2) Adsorption on heterogeneous Shale Surfaces Using aMolecular Dynamics Approach

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Fluid Dynamics & Materials Processing 2024年第1期20卷 31-44页

作者： Surajudeen Sikiru hassan Soleimani amir Rostami Mohammed Falalu hamza Lukmon Owolabi Afolabi Centre of Subsurface Imaging(CSI) Universiti Teknologi PETRONASTronohPerakMalaysia Department of Geosciences Universiti Teknologi PETRONASBandar Seri IskandarTronohPerakMalaysia Department of Pure&Industrial Chemistry Faculty of Physical SciencesBayero University KanoKanoNigeria Department of Mechanical Engineering Engineering Institute of TechnologyMelbourne Campus VictoriaMelbourneAustralia

Determining the adsorption of shale gas on complex surfaces remains a challenge in molecular simulation *** essentially stem from the need to create a realistic shale structure model in terms of mineral heterogeneityand ***,precise characterization of the competitive adsorption of hydrogen andmethane in shale generally requires the experimental determination of the related adsorptive *** thisstudy,the adsorption of adsorbates,methane(Ch_(4)),and hydrogen(h_(2))on heterogeneous shale surface modelsof Kaolinite,Orthoclase,Muscovite,Mica,C_(60),and Butane has been simulated in the frame of a moleculardynamic’s numerical *** results show that these behaviors are influenced by pressure and *** increasing the pressure from 500 to 2000 psi,the sorption effect for Ch_(4)significantly increasesbut shows a decline at a certain stage(if compared to h_(2)).The research findings also indicate that raw shalehas a higher capacity to adsorb Ch_(4)compared to ***,in shale,this difference is negligible.

关键词： Shale gas adsorption methane hydrogen molecular dynamic sorption

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Predicting short-term thromboembolic risk following Roux-en-Y gastric bypass using supervised machine learning

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World Journal of Gastrointestinal Surgery 2024年第4期16卷 1097-1108页

作者： hassam Ali Faisal Inayat Vishali Moond Ahtshamullah Chaudhry Arslan Afzal Zauraiz Anjum hamza Tahir Muhammad Sajeel Anwar Dushyant Singh Dahiya Muhammad Sohaib Afzal Gul Nawaz amir h Sohail Muhammad Aziz Department of Gastroenterology East Carolina University Brody School of MedicineGreenvilleNC 27834United States Department of Internal Medicine Allama Iqbal Medical CollegeLahorePunjab 54550Pakistan Department of Internal Medicine Saint Peter's University Hospital and Robert Wood Johnson Medical SchoolNew BrunswickNJ 08901United States Department of Internal Medicine St.Dominic's HospitalJacksonMS 39216United States Department of Internal Medicine Rochester General HospitalRochesterNY 14621United States Department of Internal Medicine Jefferson Einstein HospitalPhiladelphiaPA 19141United States Department of Internal Medicine UHS Wilson Medical CenterJohnsonNY 13790United States Division of Gastroenterology Hepatology and MotilityThe University of Kansas School of MedicineKansasKS 66160United States Department of Internal Medicine Louisiana State University HealthShreveportLA 71103United States Department of Surgery University of New Mexico School of MedicineAlbuquerqueNM 87106United States Department of Gastroenterology and hepatology The University of ToledoToledoOH 43606United States

BACKGROUND Roux-en-Y gastric bypass(RYGB)is a widely recognized bariatric procedure that is particularly beneficial for patients with class III *** aids in significant weight loss and improves obesity-related medical *** its effectiveness,postoperative care still has *** evidence shows that venous thromboembolism(VTE)is a leading cause of 30-d morbidity and mortality after ***,a clear unmet need exists for a tailored risk assessment tool for VTE in RYGB *** To develop and internally validate a scoring system determining the individualized risk of 30-d VTE in patients undergoing *** Using the 2016–2021 Metabolic and Bariatric Surgery Accreditation Quality Improvement Program,data from 6526 patients(body mass index≥40 kg/m^(2))who underwent RYGB were analyzed.A backward elimination multivariate analysis identified predictors of VTE characterized by pulmonary embolism and/or deep venous thrombosis within 30 d of *** resultant risk scores were derived from the coefficients of statistically significant *** performance of the model was evaluated using receiver operating curves through 5-fold *** Of the 26 initial variables,six predictors were *** included a history of chronic obstructive pulmonary disease with a regression coefficient(Coef)of 2.54(Ph of stay(Coef 0.08,Phrombosis(Coef 1.61,Phemoglobin A1c>7%(Coef 1.19,Phistory(Coef 1.43,Phese variables were weighted according to their regression coefficients in an algorithm that was generated for the model predicting 30-d VTE risk *** risk model's area under the curve(AUC)was 0.79[95%confidence interval(CI):0.63-0.81],showing good discriminatory power,achieving a sensitivity of 0.60 and a specificity of *** training,the same model performed satisfactorily

关键词： Roux-en-Y gastric bypass Venous thromboembolism Machine learning Bariatric surgery Predictive modeling

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Limb Lengthening and Reconstruction Society orthopedic surgeons in the United States:An analysis of geographical distribution,academic,leadership,and demographic characteristics

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World Journal of Orthopedics 2024年第2期15卷 147-155页

作者： amir human hoveidaei Reza Niakan Seyed hossein hosseini-Asl Abijith Annasamudram Janet D Conway International Center for Limb Lengthening Rubin Institute for Advanced OrthopedicsSinai Hospital of BaltimoreBaltimoreMD 21215United States Student Research Committee Shiraz University of Medical SciencesShiraz 73Iran Students’Scientific Research Center Tehran University of Medical SciencesTehran ***Iran

BACKGROUND The Limb Lengthening and Reconstruction Society(LLRS)is a premier orthopedic specialty organization that promotes limb reconstruction for all *** membership characteristics,however,are poorly *** study delineates orthopedic surgeon LLRS members’demographic traits,academic achievement,leadership attainment,and geographical distribution across the United *** To inform aspiring orthopedic professionals,as well as to promote growth and diversity in both the LLRS organization and overarching *** This cross-sectional study examined United States LLRS members’academic,leadership,demographic,and geographical *** reviewing the 2023 LLRS member directory,Google search results were matched to the listings and appended to the compiled *** and ethnicity were evaluated visually utilizing retrieved *** hirsch index(h-index)of academic activity,residency and fellowship training,other graduate degrees,leadership positions,practice type(academic or non-academic),and spoken languages were *** members per state and capita determined geographic *** Mann Whitney U test was applied to compare h-index between males and females,as well as to assess member differences pertaining to affiliation with academic vs non-academic practice *** The study included 101 orthopedic surgeons,78(77.23%)Caucasian and 23(22.77%)non-Caucasian,79(78.22%)male and 22(21.78%)*** with DO degrees comprised only 3.96%(4)of the cohort,while the vast majority held MDs[96.04%(97)].Mean h-index was 10.55,with male surgeons having a significantly higher score(P=0.002).Most orthopedic surgeons(88.12%,)practiced in academic *** those professionals who occupied leadership positions,14%were women,while 86%were ***,19(37.25%)United States regions and the District of Columbia lacked an LLRS-member orthopedic *** per capita rate across the United States was 0.30 LLRS orthopedic

关键词： Limb lengthening and reconstruction Orthopedic surgeon demographics Orthopedic surgeon societal membership Orthopedic fellowships

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Impact of metabolic dysfunction-associated steatotic liver disease on COVID-19 hospitalizations:A propensity-matched analysis of the United States

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World Journal of Virology 2024年第1期13卷 51-60页

作者： Abdullah Sohail hassam Ali Pratik Patel Subanandhini Subramanium Dushyant Singh Dahiya amir h Sohail Manesh Kumar Gangwani Sanjaya K Satapathy Department of Internal Medicine University of Iowa Roy J and Lucille A Carver College of MedicineIowaIA 52242United States Division of Gastroenterology and hepatology East Carolina University/Brody School of MedicineGreenvilleNC 27858United States Department of Gastroenterology Mather Hospital/Hofstra University Zucker School of MedicineNY11777United States Department of Internal Medicine East Carolina University Brody School of MedicineGreenvilleNC 27834United States Division of Gastroenterology Hepatology&MotilityThe University of Kansas School of MedicineKansas CityKS 66160United States Department of Surgery University of New MexicoAlbuquerqueNM 87106United States Department of Internal Medicine The University of ToledoToledoOH 43606United States Section on Gastroenterology and hepatology North Shore University Hospital and Long Island Jewish Medical CenterManhassetNY 11030United States

BACKGROUND Metabolic dysfunction-associated steatotic liver disease(MASLD),formally known as nonalcoholic fatty liver disease,is the most common chronic liver disease in the United *** with MASLD have been reported to be at a higher risk of developing severe coronavirus disease 2019(COVID-19)and ***,most studies are single-center studies,and nationwide data in the AIM To study the influence of MASLD on COVID-19 hospitalizations during the initial phase of the *** We retrospectively analyzed the 2020 National Inpatient Sample(NIS)database to identify primary COVID-19 hospitalizations based on an underlying diagnosis of MASLD.A matched comparison cohort of COVID-19 hospit-alizations without MASLD was identified from NIS after 1:N propensity score matching based on gender,race,and comorbidities,including hypertension,heart failure,diabetes,and *** primary outcomes included inpatient mortality,length of stay,and hospitalization *** outcomes included the prevalence of systemic *** A total of 2210 hospitalizations with MASLD were matched to 2210 hospitalizations without MASLD,with a good comorbidity ***,there was a higher prevalence of severe disease with more intensive care unit admissions(9.5%vs 7.2%,P=0.007),mechanical ventilation(7.2%vs 5.7%,P=0.03),and septic shock(5.2%vs 2.7%,Phe MASLD cohort than in the non-MASLD ***,there was no difference in mortality(8.6%vs 10%,P=0.49),length of stay(5 d vs 5 d,P=0.25),and hospitalization costs(42081.5$vs 38614$,P=0.15)between the MASLD and non-MASLD *** The presence of MAFLD with or without liver cirrhosis was not associated with increased mortality in COVID-19 hospitalizations;however,there was an increased incidence of severe COVID-19 *** data(2020)predates the availability of COVID-19 vaccines,and many MASLD patients have since been *** will be interesting to see if these trends are

关键词： COVID-19 Metabolic dysfunction-associated steatotic liver disease Prevalence hospital charges Inpatient resource utilization

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