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Investigation of particle-wall interaction in a pseudo-2D fluidized bed using CFD-DEM simulations

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Particuology 2016年第2期14卷 10-22页

作者： Tingwen Li Yongmin Zhang fernando hernandez-Jimenez National Energy Technology Laboratory Morgantown WV26507 USA AECOM Morgantown WV 26507 USA State Key Laboratory of Heavy Oil Processing China University of Petroleum Beijing 102249 China Universidad Carlos III of Madrid Department of Thermal and Fluid Engineering Av. de la Universidad 30 28911 Leganes Madrid Spain

We report on discrete element method simulations of a pseudo-two-dimensional （pseudo-2D） fluidized bed to investigate particle-wall interactions. Detailed information on macroscopic flow field variables, including solids pressure, granular temperature, and normal and tangential wall stresses are analyzed. The normal wall stress differs from the solids pressure because of the strong anisotropic flow behavior in the pseudo-2D system. A simple linear relationship exists between normal wall stress and solids pressure. In addition, an effective friction coefficient can be derived to characterize particle-wall flow interaction after evaluating the normal and tangential wall stresses. The effects of inter-particle and particle-wall friction coefficients are evaluated. Strong anisotropic flow behavior in the pseudo-2D system needs to be considered to validate the two-fluid model where the boundary condition is usually developed based on an isotropic assumption. The conclusion has been confirmed by simulation with different particle stiffnesses. Assumptions in the newly developed model for 2D simulation are further examined against the discrete element method simulation.

关键词： Gas-solid tlow Fluidized bed Computational fluid dynamics Discrete element method Particle-wall interaction Two-dimensional flow

Chemical oxygen demand reduction in coffee wastewater through chemical flocculation and advanced oxidation processes

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Journal of Environmental Sciences 2007年第3期19卷 300-305页

作者： ZAYAS Pérez Teresa GEISSLER Gunther hernandez fernando Postgrade in Environmental Sciences Center of ChemistryInstitute of Science.Meriterious University Autonomous of Puebla.P.O.Box 1613C.P.72000PueblaMexico.

The removal of the natural organic matter present in coffee processing wastewater through chemical coagulation-flocculation and advanced oxidation processes （AOP） had been studied. The effectiveness of the removal of natural organic matter using commercial flocculants and UV/H202, UV/O3 and UV/H2O2/O3 processes was determined under acidic conditions. For each of these processes, different operational conditions were explored to optimize the treatment efficiency of the coffee wastewater. Coffee wastewater is characterized by a high chemical oxygen demand （COD） and low total suspended solids. The outcomes of coffee wastewater treatment using coagulation-flocculation and photodegradation processes were assessed in terms of reduction of COD, color, and turbidity. It was found that a reduction in COD of 67% could be realized when the coffee wastewater was treated by chemical coagulation-flocculation with lime and coagulant T-1. When coffee wastewater was treated by coagulation-flocculation in combination with UV/H2O2, a COD reduction of 86% was achieved, although only after prolonged UV irradiation. Of the three advanced oxidation processes considered, UV/H2O2, UV/O3 and UV/H2O2/O3, we found that the treatment with UV/H2O2/O3 was the most effective, with an efficiency of color, turbidity and further COD removal of 87%, when applied to the flocculated coffee wastewater.

关键词： advanced oxidation processes coagulation-flocculation: coffee wastewater chemical oxygen demand (COD)

E-Commerce Fraud Detection Based on Machine Learning Techniques:Systematic Literature Review

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Big Data Mining and Analytics 2024年第2期7卷 419-444页

作者： Abed Mutemi fernando Bacao NOVA Information Management School(NOVA IMS) Universidade Nova de LisboaCampus de CampolideLisboa 1070-312Portugal

The e-commerce industry’s rapid growth,accelerated by the COVID-19 pandemic,has led to an alarming increase in digital fraud and associated *** establish a healthy e-commerce ecosystem,robust cyber security and anti-fraud measures are ***,research on fraud detection systems has struggled to keep pace due to limited real-world *** in artificial intelligence,Machine Learning(ML),and cloud computing have revitalized research and applications in this *** ML and data mining techniques are popular in fraud detection,specific reviews focusing on their application in e-commerce platforms like eBay and Facebook are lacking *** reviews provide broad overviews but fail to grasp the intricacies of ML algorithms in the e-commerce *** bridge this gap,our study conducts a systematic literature review using the Preferred Reporting Items for Systematic reviews and Meta-Analysis(PRISMA)*** aim to explore the effectiveness of these techniques in fraud detection within digital marketplaces and the broader e-commerce *** the current state of the literature and emerging trends is crucial given the rising fraud incidents and associated *** our investigation,we identify research opportunities and provide insights to industry stakeholders on key ML and data mining techniques for combating e-commerce *** paper examines the research on these techniques as published in the past *** the PRISMA approach,we conducted a content analysis of 101 publications,identifying research gaps,recent techniques,and highlighting the increasing utilization of artificial neural networks in fraud detection within the industry.

关键词： E-commerce Machine Learning(ML) systematic review fraud detection organized retail fraud

Exploring multifaceted factors in chronic kidney disease risk: A comprehensive analysis of biochemistry, lifestyle, and inflammation in elderly Chinese individuals

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World Journal of Clinical Cases 2024年第5期12卷 1033-1035页

作者： fernando Cardona Unitat de Genètica Molecular Instituto de Biomedicina de Valencia–CSICValencia 46010Spain Centro de investigación Biomédica en Red Enfermedades Neurodegenerativas(CIBERNED) Instituto de Salud Carlos IIIMadrid 28029Spain Departamento de Biotecnología Escuela Técnica Superior de Ingeniería Agronómica y del Medio Natural(ETSIAMN)Univeristat Politècnica de ValenciaValencia 46022Spain

This letter praises a recent article in the World Journal of Clinical Cases(Roles of biochemistry data,lifestyle,and inflammation in identifying abnormal renal function in old Chinese),examining factors affecting abnormal renal function in elderly Chinese using advanced machine *** highlights the importance of uric acid,age,hemoglobin,body mass index,sport hours,and systolic blood *** study's holistic approach,integrating lifestyle and inflammation,offers a nuanced understanding of chronic kidney disease risk *** letter suggests exploring mechanistic pathways of hyperuricemia,the link between anemia and renal function,and the connection between body mass index and estimated glomerular filtration *** advocates investigating physical activity's impact on renal health and the independent effects of blood *** study significantly contributes to chronic kidney disease understanding,proposing avenues for further exploration and *** are extended to the authors and the journal.

关键词： Biochemistry data Lifestyle Machine learning Renal function

A new small baurioid therocephalian from the Lower Triassic Jiucaiyuan Formation, Xinjiang, China

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古脊椎动物学报（中英文） 2024年第3期62卷 201-224页

作者： LIU Jun fernando ABDALA Institute of Vertebrate Paleontology and Paleoanthropology Chinese Academy of Sciences Beijing 100044China College of Earth and Planetary Sciences University of Chinese Academy of Sciences Beijing 100049 Área de Paleontología Unidad Ejecutora LilloCONICETFundación Miguel Lillo Miguel Lillo 251TucumánArgentina Evolutionary Studies Institute University of the Witwatersrand Private Bag 3WITSJohannesburg2050South Africa

Several therocephalian species,mainly represented by cranial material from the late Permian,have been reported from China in recent *** we describe a tiny new baurioid therocephalian,Jiucaiyuangnathus confusus *** ***.,from the Jiucaiyuan Formation,Xinjiang,*** new taxon is represented by a partial snout with occluded partial lower jaw and two postcranial *** juvenile in stage,the new species is diagnosed by the following features:round pit in middle of lateral surface of maxilla;lacrimal contact nasal;fossa for dentary tooth on the posterior end of the premaxilla,lateral to the anterior choana;two small vertical triangular ridges extending dorsally and ventrally on the vomerine anterior portion,and bordering a thin vomerine foramen laterally;anterior projection of the lateral part of the frontal on the nasal;symphyseal region of the dentary projected anteriorly;5 upper premaxillary teeth,upper and lower canines absent,diastema between the last premaxillary upper incisor and first maxillary tooth present,no diastema separating anterior from posterior dentition in the mandible,10 maxillary teeth and 12 dentary teeth,posterior postcanine expands mesiodistally,having a main large cusps and tiny anterior and posterior accessory cusps in line;neural arches of the atlas fused by the neural spine,neural spine of the axis projected posteriorly,procoracoid foramen lies between procoracoid and *** of the dentition resembles those of the small baurioid Ericiolacerta parva from South Africa and Silphedosuchus orenburgensis from *** specimens provide the rare opportunity to know in detail the postcranial skeleton of baurioids.

关键词： Jimsar,Xinjiang Early Triassic Jiucaiyuan Formation Therocephalia,Baurioidea

Time-Series Embeddings from Language Models:A Tool for Wind Direction Nowcasting

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Journal of Meteorological Research 2024年第3期38卷 558-569页

作者： Decio ALVES Fabio MENDONCA Sheikh Shanawaz MOSTAFA fernando MORGADO-DIAS University of Madeira Campus Universitário da Penteada9020-105FunchalPortugal Interactive Technologies Institute/Laboratory for Robotics and Engineering Systems and Agência Regional para o Desenvolvimento da Investigação Tecnologia e InovaçãoEdif.Madeira TecnopoloCaminho da Penteada piso-29020-105FunchalPortugal

Wind direction nowcasting is crucial in various sectors,particularly for ensuring aviation operations and *** this context,the TELMo(Time-series Embeddings from Language Models)model,a sophisticated deep learning architecture,has been introduced in this work for enhanced wind-direction *** by using three years of data from multiple stations in the complex terrain of an international airport,TELMo incorporates the horizontal u(east-west)and v(north-south)wind components to significantly reduce forecasting *** a day with high wind direction variability,TELMo achieved mean absolute error values of 5.66 for 2-min,10.59 for 10-min,and 14.79 for 20-min forecasts,processed within a swift 9-ms/step *** degree-based analysis,in comparison,yielded lower performance,emphasizing the effectiveness of the u and v *** contrast,a Vanilla neural network,representing a shallow-learning approach,underperformed in all analyses,highlighting the superiority of deep learning methodologies in wind direction *** is an efficient model,capable of accurately forecasting wind direction for air traffic operations,with an error less than 20°in 97.49%of the predictions,aligning with recommended international *** model design enables its applicability across various geographical locations,making it a versatile tool in global aviation meteorology.

关键词： wind nowcasting wind components wind direction time series prediction deep learning

A Review of State-of-the-art Flexible Power Point Tracking Algorithms in Photovoltaic Systems for Grid Support:Classification and Application

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Journal of Modern Power Systems and Clean Energy 2024年第1期12卷 1-21页

作者： Mina Haghighat Mehdi Niroomand Hossein Dehghani Tafti Christopher D.Townsend Tyrone fernando the Department of Electrical Engineering University of IsfahanIsfahanIran the Department of Electrical Electronic and Computer EngineeringUniversity of Western AustraliaCrawley WA 6009Australia

To maximize conversion efficiency,photovoltaic(PV)systems generally operate in the maximum power point tracking(MPPT)***,due to the increasing penetra tion level of PV systems,there is a need for more developed control functions in terms of frequency support services and voltage control to maintain the reliability and stability of the power ***,flexible active power control is a manda tory task for grid-connected PV systems to meet part of the grid ***,a significant number of flexible pow er point tracking(FPPT)algorithms have been introduced in the existing *** purpose of such algorithms is to real ize a cost-effective method to provide grid support functional ities while minimizing the reliance on energy storage *** paper provides a comprehensive overview of grid support functionalities that can be obtained with the FPPT control of PV systems such as frequency support and volt-var *** of these grid support functionalities necessitates PV sys tems to operate under one of the three control strategies,which can be provided with FPPT *** three control strate gies are classified as:①constant power generation control(CP GC),②power reserve control(PRC),and③power ramp rate control(PRRC).A detailed discussion on available FPPT algo rithms for each control strategy is also *** paper can serve as a comprehensive review of the state-of-the-art FPPT algorithms that can equip PV systems with various grid support functionalities.

关键词： Maximum power point tracking(MPPT) flexi ble power point tracking(FPPT) power reserve control(PRC) power ramp rate control(PRRC) low voltage ride-through(LVRT) constant power generation(CPG)

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

Unveiling the brain’s symphony:exploring the necessity and sufficiency of neural networks in behavior control

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Neural Regeneration Research 2025年第1期20卷 186-187页

作者： fernando Jose Bustos Instituto de Ciencias Biomedicas Facultad de Medicina y Facultad de Ciencias de la VidaUniversidad Andres BelloSantiagoChile Millennium Nucleus of Neuroepigenetics and Plasticity(EpiNeuro) SantiagoChile

Since the pioneering work by Broca and Wernicke in the 19th century,who examined individuals with brain lesions to associate them with specific behaviors,it was evident that behaviors are complex and cannot be fully attributable to specific brain areas ***,they involve connectivity among brain areas,whether close or *** that time,this approach was considered the optimal way to dissect brain circuitry and *** pioneering efforts opened the field to explore the necessity or sufficiency of brain areas in controlling behavior and hence dissecting brain ***,the connectivity of the brain and the mechanisms through which various brain regions regulate specific behaviors,either individually or collaboratively,remain largely *** animal models,researchers have endeavored to unravel the necessity or sufficiency of specific brain areas in influencing behavior;however,no clear associations have been firmly established.

关键词： behavior connectivity neural