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Effect of operational parameters on the performance of an anaerobic sequencing batch reactor(AnSBR)treating protein-rich wastewater

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Environmental Science and Ecotechnology 2024年第1期17卷 89-99页

作者： Zhe Deng Julian Muñoz Sierra Ana Lucia Morgado Ferreira daniel cerqueda-garcia Henri Spanjers Jules B.van Lier Delft University of Technology Faculty of Civil Engineering and GeosciencesStevinweg 12628 CNDelftthe Netherlands Veolia Water Technologies Techno Center Netherlands B.V.-Biothane Tanthofdreef 212623 EWDelftthe Netherlands KWR Water Research Institute Groningenhaven 7P.O.Box 10723430 BBNieuwegeinthe Netherlands Institute of Ecology.A.C Cluster Cientifico y Tecnologico BioMimic®Carretera Antigua a Coatepec 351El Haya91073XalapaVeracruzMexico

Treating protein-rich wastewater using cost-effective and simple-structured single-stage reactors presents several *** this study,we applied an anaerobic sequencing batch reactor(AnSBR)to treat protein-rich wastewater from a *** focused on identifying the key factors influencing the removal of chemical oxygen demand(COD)and the settling performance of the *** AnSBR achieved a maximum total COD removal of 90%,a protein degradation efficiency exceeding 80%,and a COD to methane conversion efficiency of over 70%at organic loading rates of up to 6.2 g COD L^(-1)d^(-1).We found that the variations in both the organic loading rate within the reactor and the hydraulic retention time in the buffer tank had a significant effect on COD *** hydraulic retention time in the buffer tank and the reactor,which determined the ammonification efficiencies and the residual carbohydrate concentrations in the reactor liquid,affected the sludge ***,the genus Clostridium sensu stricto 1,known as protein-and lipids-degraders,was predominant in the *** analysis showed a significant correlation between the core microbiome and ammonification efficiency,highlighting the importance of protein degradation as the governing process in the *** results will provide valuable insights to optimise the design and operation of AnSBR for efficient treatment of protein-rich wastewater.

关键词： Anaerobic digestion Anaerobic sequencing batch reactor (AnSBR) Protein Microbial community Slaughterhouse wastewater

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Give progesterone a chance

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Neural Regeneration Research 2014年第15期9卷 1422-1424页

作者： Florencia Labombarda daniel garcia-Ovejero Laboratory of Neuroendocrine Biochemistry Institute of Biology and Experimental Medicine CONICET Vuelta de Obligado 2490Buenos AiresArgentina Departament of Human Biochemistry School of MedicineBuenos Aires University Paraguay 2155Buenos AiresArgentina Neuroinflammation Laboratory National Hospital For Paraplegics(SESCAM) ToledoSpain

There is currently no standard pharmacological treatment for spinal cord injury. Here, we suggest that progesterone, a steroid hormone, may be a promising therapeutical candidate as it is already for traumatic brain injury, where it has reached phase II clinical trials. We rely on previous works showing anti-inflammatory, neuroprotective and promyelinating roles for progesterone after spinal cord injury and in our recent paper, in which we demonstrate that progesterone diminishes lesion, preserves white matter integrity and improves locomotor recovery in a clinically relevant model of spinal cord lesion.

关键词： spinal cord injury myelin trauma neuroprotection progesterone

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Visual analytics tool for the interpretation of hidden states in recurrent neural networks

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Visual Computing for Industry,Biomedicine,and Art 2021年第1期4卷 233-245页

作者： Rafael garcia Tanja Munz daniel Weiskopf VISUS University of Stuttgart70569 StuttgartGermany

In this paper,we introduce a visual analytics approach aimed at helping machine learning experts analyze the hidden states of layers in recurrent neural *** technique allows the user to interactively inspect how hidden states store and process information throughout the feeding of an input sequence into the *** technique can help answer questions,such as which parts of the input data have a higher impact on the prediction and how the model correlates each hidden state configuration with a certain *** visual analytics approach comprises several components:First,our input visualization shows the input sequence and how it relates to the output(using color coding).In addition,hidden states are visualized through a nonlinear projection into a 2-D visualization space using t-distributed stochastic neighbor embedding to understand the shape of the space of the hidden *** are also employed to show the details of the evolution of the hidden state ***,a time-multi-class heatmap matrix visualizes the evolution of the expected predictions for multi-class classifiers,and a histogram indicates the distances between the hidden states within the original *** different visualizations are shown simultaneously in multiple views and support brushing-and-linking to facilitate the analysis of the classifications and debugging for misclassified input *** demonstrate the capability of our approach,we discuss two typical use cases for long short-term memory models applied to two widely used natural language processing datasets.

关键词： Visual analytics Visualization Machine learning Classification Recurrent neural networks Long shortterm memory Hidden states Interpretability Natural language processing Nonlinear projection

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Thermo-electro-mechanical microstructural interdependences in conductive thermoplastics

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npj Computational Materials 2023年第1期9卷 955-965页

作者： Javier Crespo-Miguel Sergio Lucarini Angel Arias daniel garcia-Gonzalez Department of Continuum Mechanics and Structural Analysis Universidad Carlos III de MadridAvda.de la Universidad 3028911 LeganésMadridSpain Department of Civil and Environmental Engineering Imperial College of LondonSouth Kensington CampusLondon SW72AZUK

Additive manufacturing has enabled the design of thermoplastic components that provide structural support,electrical conductivity and heat generation modulated by mechanical *** mechanisms and interplays that govern the material response at the microstructural level remain,however,***,we develop an experimental method to characterise conductive filaments from a combined mechanical,electrical and thermal *** approach is used to unravel exciting material interplays of conductive polylactic *** overcome experimental limitations that prevent a complete microstructural analysis of the problem,we develop a full-field homogenisation framework and implement it for finite *** framework accounts for viscoplasticity,electrical and thermal conduction,convection and heat generation via Joule effect,as well as for the interdependences between *** experimental validation,the framework is applied to virtually optimise fabrication requirements to obtain desired properties in final products,i.e.,stiffer products,filaments with higher conductivities or with better sensing capabilities.

关键词： conductive electrical overcome

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Hybrid magnetorheological elastomers enable versatile soft actuators

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npj Computational Materials 2022年第1期8卷 1546-1559页

作者： Miguel Angel Moreno-Mateos Mokarram Hossain Paul Steinmann daniel garcia-Gonzalez Department of Continuum Mechanics and Structural Analysis Universidad Carlos III de MadridAvda.de la Universidad 3028911LeganésMadridSpain Zienkiewicz Centre for Computational Engineering Faculty of Science and EngineeringSwansea UniversitySA18ENSwanseaUK Institute of Applied Mechanics University of Erlangen-NurembergEgerland Str.5ErlangenGermany Glasgow Computational Engineering Centre School of EngineeringUniversity of GlasgowG128QQGlasgowUK

Recent advances in magnetorheological elastomers(MREs)have posed the question on whether the combination of both soft-and hard-magnetic particles may open new routes to design versatile multifunctional ***,we conceptualise ultra-soft hybrid MREs(≈1–10 kPa stiffness)combining experimental and computational ***,a comprehensive experimental characterisation is *** results unravel that the magneto-mechanical performance of hybrid MREs can be optimised by selecting an adequate mixing ratio between ***,a multi-physics computational framework provides insights into the synergistic magneto-mechanical interactions at the *** particles amplify the magnetisation and hard particles contribute to torsional *** numerical results suggest that the effective response of hybrid MREs emerges from these intricate ***,we uncover exciting possibilities to push the frontiers of MRE *** are demonstrated by simulating a bimorph beam that provides actuation flexibility either enhancing mechanical bending or material stiffening,depending on the magnetic stimulation.

关键词： versatile magneto enable

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Charting the course to solid-state dual-ion batteries

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Carbon Energy 2024年第3期6卷 132-177页

作者： Habtom D.Asfaw Antonia Kotronia Nuria garcia-Araez Kristina Edström daniel Brandell Department of Chemistry Ångström LaboratoryUppsala UniversityUppsalaSweden Department of Chemistry University of SouthamptonSouthamptonUK

An electrolyte destined for use in a dual-ion battery(DIB)must be stable at the inherently high potential required for anion intercalation in the graphite electrode,while also protecting the Al current collector from anodic dissolution.A higher salt concentration is needed in the electrolyte,in comparison to typical battery electrolytes,to maximize energy density,while ensuring acceptable ionic conductivity and operational *** recent years,studies have demonstrated that highly concentrated organic electrolytes,ionic liquids,gel polymer electrolytes(GPEs),ionogels,and water-in-salt electrolytes can potentially be used in *** can help reduce the use of solvents and thus lead to a substantial change in the Coulombic efficiency,energy density,and long-term cycle life of ***,GPEs are suited to manufacture compact DIB designs without separators by virtue of their mechanical strength and electrical *** this review,we highlight the latest advances in the application of different electrolytes in DIBs,with particular emphasis on GPEs.

关键词： anion intercalation concentrated electrolytes dual-ion battery graphite ionic liquids polymer electrolyte

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Diabetes Type 2: Poincaré Data Preprocessing for Quantum Machine Learning

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Computers, Materials & Continua 2021年第5期67卷 1849-1861页

作者： daniel Sierra-Sosa Juan D.Arcila-Moreno Begonya garcia-Zapirain Adel Elmaghraby Department of Computer Science and Engineering University of LouisvilleLouisvilleKYUSA Apolo Scientific Computing Center Universidad EAFITMedellínColombia eVida Research Group University of DeustoBilbaoSpain

Quantum Machine Learning(QML)techniques have been recently attracting massive *** reported applications usually employ synthetic or well-known *** of these techniques based on using a hybrid approach combining quantum and classic devices is the Variational Quantum Classifier(VQC),which development seems *** being largely studied,VQC implementations for“real-world”datasets are still challenging on Noisy Intermediate Scale Quantum devices(NISQ).In this paper we propose a preprocessing pipeline based on Stokes parameters for data *** pipeline enhances the prediction rates when applying VQC techniques,improving the feasibility of solving classification problems using NISQ *** including feature selection techniques and geometrical transformations,enhanced quantum state preparation is ***,a representation based on the Stokes parameters in the PoincaréSphere is possible for visualizing the *** results show that by using the proposed techniques we improve the classification score for the incidence of acute comorbid diseases in Type 2 Diabetes Mellitus *** used the implemented version of VQC available on IBM’s framework Qiskit,and obtained with two and three qubits an accuracy of 70%and 72%respectively.

关键词： Quantum machine learning data preprocessing stokes parameters Poincarésphere

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Exploiting Deep Learning Techniques for Colon Polyp Segmentation

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Computers, Materials & Continua 2021年第5期67卷 1629-1644页

作者： daniel Sierra-Sosa Sebastian Patino-Barrientos Begonya garcia-Zapirain Cristian Castillo-Oleam Adel Elmaghraby Department of Computer Science and Engineering University of LouisvilleLouisvilleKYUSA Centro de Computacion Cientifica Apolo at Universidad EAFIT MedelinColombia eVida Research Group University of DeustoBilbaoSpain

As colon cancer is among the top causes of death, there is a growinginterest in developing improved techniques for the early detection of colonpolyps. Given the close relation between colon polyps and colon cancer,their detection helps avoid cancer cases. The increment in the availability ofcolorectal screening tests and the number of colonoscopies have increasedthe burden on the medical personnel. In this article, the application of deeplearning techniques for the detection and segmentation of colon polyps incolonoscopies is presented. Four techniques were implemented and evaluated:Mask-RCNN, PANet, Cascade R-CNN and Hybrid Task Cascade (HTC).These were trained and tested using CVC-Colon database, ETIS-LARIBPolyp, and a proprietary dataset. Three experiments were conducted to assessthe techniques performance: (1) Training and testing using each databaseindependently, (2) Mergingd the databases and testing on each database independently using a merged test set, and (3) Training on each dataset and testingon the merged test set. In our experiments, PANet architecture has the bestperformance in Polyp detection, and HTC was the most accurate to segmentthem. This approach allows us to employ Deep Learning techniques to assisthealthcare professionals in the medical diagnosis for colon cancer. It is anticipated that this approach can be part of a framework for a semi-automatedpolyp detection in colonoscopies.

关键词： Colon polyps deep learning image segmentation

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Enclosure enhancement of flight performance

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Theoretical & Applied Mechanics Letters 2014年第6期4卷 42-48页

作者： Mehdi Ghommem daniel garcia Victor M.Calo Center for Numerical Porous Media (Num Por) King Abdullah University of Science and Technology Thuwal 23955-6900 Kingdom of Saudi Arabia Mechanical Engineering Center for Numerical Porous Media (Num Por)King Abdullah University of Science and Technology Thuwal 23955-6900Kingdom of Saudi Arabia Applied Mathematics & Computational Science Earth Science & Engineering Center for Numerical Porous Media (Num Por) King Abdullah University of Science and Technology Thuwal 23955-6900 Kingdom of Saudi Arabia

We use a potential flow solver to investigate the aerodynamic aspects of flapping flights in enclosed spaces. The enclosure effects are simulated by the method of images. Our study complements previous aerodynamic analyses which considered only the near-ground flight. The present results show that flying in the proximity of an enclosure affects the aerodynamic performance of flapping wings in terms of lift and thrust generation and power consumption. It leads to higher flight efficiency and more than 5% increase of the generation of lift and thrust.

关键词： flapping flight enclosure effects unsteady aerodynamics

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HERBICIDES THAT INHIBIT ACETOLACTATE SYNTHASE

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Frontiers of Agricultural Science and Engineering 2022年第1期9卷 155-160页

作者： Thierry LONHIENNE Mario daniel garcia Yu Shang LOW Luke W.GUDDAT School of Chemistry and Molecular Bioscience The University of QueenslandQueensland 4072Australia

1 INTRODUCTION Herbicides are an essential pillar in modern agricultural *** are used to selectively reduce the growth of weeds in crops and natural *** weed mitigating chemicals date back to Roman times and include substances as simple as table salt,sulfuric acid and carbon ***,these were non-selective,required high application rates and could be toxic not only to the target weeds but to other plants and to *** first major advance in the development of tailored herbicides began in the mid 1940s with the development of the first organic growth regulators such as 2,4 dichlorophenoxyacetic acid(2,4-D)[1].The next major advance came in the 1970s with the discovery of glyphosate[2],marketed as Roundup,a herbicide that is routinely used to eradicate broad leaf weeds and grasses.

关键词： crops weed routine

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