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In situ characterization of particle formation in spray flame synthesis using wide-angle light scattering

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Particuology 2024年第3期86卷 304-312页

作者： Simon Aβmann franz J.T.Huber Stefan Will Lehrstuhl für Technische Thermodynamik(LTT) Friedrich-Alexander-Universitat Erlangen-Nürnberg(FAU)Erlangen91058Germany Erlangen Graduate Schoolin Advanced Optical Technologies(SAOT) Friedrich-Alexander-Universitat Erlangen-Nurnberg(FAU)Erlangen91052Germany Competence Unit Engineering of Advanced Materials(EAM) Friedrich-Alexander-Universitat Erlangen-Nürnberg(FAU)Erlangen91052Germany

Wide-angle light scattering(WALS)was used for in situ measurements of droplet and nanoparticle size distributions during the synthesis of titania and iron oxide particles from liquid precursor solutions in the standardized SpraySyn burner for spray flame *** was synthesized from titanium tetraisopropoxide(TTIP)and iron oxide from iron(II)nitrate nonahydrate(INN)using ethanol(EtOH)as *** images were taken at heights up to 120 mm above the burner surface and classified into droplet and particle *** size distributions were derived from a sequential analysis of scattering data containing the oscillating Mie pattern,the lognormal size distribution parameters for spherical and fractal particle fractions from a multivariate approach on averaged particle scattering *** results show that the precursor addition leads to altered evaporation behavior and even droplet disruption probably induced by puffing or micro-explosions compared to pure *** the case of TTIP(a hygroscopic alkoxide),the synthesis of a large fraction of spheres was observed,while the nitrate INN leads to the formation of mostly fractal aggregates.

关键词： Spray flame synthesis Metal oxide particles Elastic light scattering Droplet size distribution Nanoparticle morphology Particle size distribution

Nuance of inward rectifying potassium(Kir)channel dysfunctions in neurodegenerative diseases

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Neural Regeneration Research 2024年第6期19卷 1195-1196页

作者： benjamin Garland Linlin Ma Griffith Institute for Drug Discovery&School of Environment and Science Griffith UniversityNathanBrisbaneQLDAustralia

Neurodegenerative disorders are highly prevalent and diverse in *** manifestation largely depends on the cell types involved,with aberrant inflammatory episodes progressively inducing a constellation of phenotypes that are classified into specific diseases based on their neuropathological *** two most prevalent neurodegenerative diseases worldwide,Alzheimer’s disease(AD)and Parkinson’s disease(PD),for example,share notable similarities,yet they differ in terms of the specific cell types lost within the central nervous system(CNS).The significant and progressive loss of cortical and certain subcortical neurons in various regions is a major defining trait of *** contrast,the specific loss of dopaminergic neurons(DA)within the substantial nigra pars compacta(SNpc)is sufficient to cause motor symptoms associated with *** devastating condition arising from neurodegeneration within the CNS,amyotrophic lateral sclerosis(ALS),results in the progressive death of upper and lower motor *** degeneration originates in oligodendrocytes,whose defective myelination abilities lead to the denervation of the anterior horn,aggravating motor neuron death.

关键词： diseases degenerative degeneration

Modeling tuberous sclerosis complex with human induced pluripotent stem cells

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World Journal of Pediatrics 2024年第3期20卷 208-218页

作者： Weibo Niu benjamin Siciliano Zhexing Wen Department of Psychiatry and Behavioral Sciences Emory University School of MedicineWhitehead Research Building 447615 Michael StreetAtlantaGA 30322USA The Graduate Program in Molecular and Systems Pharmacology Laney Graduate SchoolEmory UniversityAtlanta.GA 30322.USA Department of Cell Biology Emory University School of MedicineWhitehead Research Building 447615 Michael StreetAtlantaGA30322USA Department of Neurology Emory University School of MedicineWhitehead Research Building 447.615 Michael StreetAtlantaGA 30322USA

Background Tuberous sclerosis complex(TSC)is an autosomal dominant genetic disorder with a birth incidence of I:6000 in the United States that is characterized by the growth of non-cancerous tumors in multiple organ systems including the brain,kidneys,lungs,and ***,TSCis also associated with signicant neurological manifestations including epilepsy TSC-associated neuropsychiatric disorders,intellectual disabilities,and autism spectrum *** in the TSCI or TSC2 genes are well-established causes of TSC,which lead to TSC1/TSC2 deficiency in organs and hyper-activation of the mammalian target of rapamycin signaling *** models have been widely used to study the effect of TSCl/2 genes on the development and function of the *** considerable progress in understanding the molecular mechanisms underlying TSC in animal models,a human-specific model is urgently needed to investigate the effects of TSCl/2 mutations that are unique to human *** sources Literature reviews and research articles were published in PubMed-indexed *** Human-induced pluripotent stem cells(iPSCs),which capture risk alleles that are identical to their donors and have the capacity to differentiate into virtually any cell type in the human body,pave the way for the empirical study of previously inaccessible biological systems such as the developing human *** In this review,we present an overview of the recent progress in modeling TSC with human iPSC models,the existing limitations,and potential directions for future research.

关键词： Induced pluripotent stem cells Three-dimensional cultures Tuberous sclerosis complex Two-dimensional cultures

Autonomous Vehicle Platoons In Urban Road Networks:A Joint Distributed Reinforcement Learning and Model Predictive Control Approach

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 141-156页

作者： Luigi D’Alfonso Francesco Giannini Giuseppe franzè Giuseppe Fedele Francesco Pupo Giancarlo Fortino IEEE the Department of Computer Engineering ModelingElectronics and SystemsUniversitàdella CalabriaVia Pietro BucciCubo 42-CRende(CS)87036Italy the Department of Mechanical Engineering Energy Engineering and ManagementUniversitàdella CalabriaVia Pietro BucciCubo 42-CRende(CS)87036Italy

In this paper, platoons of autonomous vehicles operating in urban road networks are considered. From a methodological point of view, the problem of interest consists of formally characterizing vehicle state trajectory tubes by means of routing decisions complying with traffic congestion criteria. To this end, a novel distributed control architecture is conceived by taking advantage of two methodologies: deep reinforcement learning and model predictive control. On one hand, the routing decisions are obtained by using a distributed reinforcement learning algorithm that exploits available traffic data at each road junction. On the other hand, a bank of model predictive controllers is in charge of computing the more adequate control action for each involved vehicle. Such tasks are here combined into a single framework:the deep reinforcement learning output(action) is translated into a set-point to be tracked by the model predictive controller;conversely, the current vehicle position, resulting from the application of the control move, is exploited by the deep reinforcement learning unit for improving its reliability. The main novelty of the proposed solution lies in its hybrid nature: on one hand it fully exploits deep reinforcement learning capabilities for decisionmaking purposes;on the other hand, time-varying hard constraints are always satisfied during the dynamical platoon evolution imposed by the computed routing decisions. To efficiently evaluate the performance of the proposed control architecture, a co-design procedure, involving the SUMO and MATLAB platforms, is implemented so that complex operating environments can be used, and the information coming from road maps(links,junctions, obstacles, semaphores, etc.) and vehicle state trajectories can be shared and exchanged. Finally by considering as operating scenario a real entire city block and a platoon of eleven vehicles described by double-integrator models, several simulations have been performed with the a

关键词： Distributed model predictive control distributed reinforcement learning routing decisions urban road networks

A nerve-like self-healable conductive wire

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National Science Review 2024年第6期11卷 89-90页

作者： Xuemei Fu benjamin C.K.Tee Department of Materials Science and Engineering National University of Singapore Institute for Health Innovation and Technology National University of Singapore

In wearables and robotics, it is often required to deploy electronic devices at different spatially distributed locations for multi-functionality [1–3]. Thus, conductive wires for efficient interconnection of various electronic devices are ***, in practical applications, the frequent motion of wearers and robots will result in high-strain deformations of these wires, which could cause irreparable damage.

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Effect of thermo-mechanical conditions during constrained friction processing on the particle refinement of AM50 Mg-alloy phases

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Journal of Magnesium and Alloys 2024年第6期12卷 2298-2311页

作者： Camila Caroline de Castro AndréMartins Neves benjamin Klusemann Helmholtz-Zentrum Hereon Institute of Material and Process DesignSolid-State Materials Processing21502 GeesthachtGermany Helmholtz-Zentrum Hereon Institute of Hydrogen TechnologySystem Design for Mobility21502 GeesthachtGermany Helmut Schmidt University/University of the German Federal Armed Forces Hamburg Department of Mechanical and Civil Engineering22043 HamburgGermany Leuphana University Lüneburg Institute for Production Technology and Systems21335 LüneburgGermany

Constrained Friction Processing(CFP)is a novel solid-state processing technique suitable for lightweight materials,such Mg-and *** technique enables grain size refinement to fine or even ultrafine *** this study,the effect of CFP on the microstructural refinement of AM50 rods is investigated in terms of particle size and morphology of the eutectic and secondary phases originally present in the base material,in particular the eutecticβ-Mg_(17)Al_(12)and Al-Mn *** that purpose,as-cast and solution heat-treated base material and processed samples were *** Al_(8)Mn_(5) intermetallic phase was identified as the main secondary phase present in all samples before and after the processing.A notorious refinement of these particles was observed,starting from particles with an average equivalent length of a few micrometers to around 560 nm after the *** refinement of the secondary phase refinement is attributed to a mechanism analogous to the attrition comminution,where the combination of temperature increase and shearing of the material enables the continuous breaking of the brittle intermetallic particles into smaller *** for the eutectic phase,the results indicate the presence of the partially divorcedβ-Mg_(17)Al_(12)particles exclusively in the as-cast base material,indicating that no further phase transformations regarding the eutectic phase,such as dynamic precipitation,occurred after the *** the case of the processed as-cast material analyzed after the CFP,the thermal energy generated during the processing led to temperature values above the solvus limit of the eutectic phase,which associated with the mechanical breakage of the particles,enabled the complete dissolution of this ***,CFP was successfully demonstrated to promote an extensive microstructure refinement in multiple aspects,in terms of grain sizes of theα-Mg phase and presence and morphology of the Al-Mn and eutecticβ-Mg_(17)Al_(12).

关键词： Constrained friction processing AM50 Refill friction stir spot welding Extrusion β-Mg_(17)Al_(12) Al-Mn phases

Analysis of synthetic parameters for coating aluminum powders with phenyltriethoxysilane coupling agent and their effects on powder flow behavior

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Particuology 2024年第7期90卷 412-417页

作者： Lillian M.Mawby Bellamarie Ludwig benjamin J.Lear Department of Chemistry The Pennsylvania State UniversityUniversity ParkPA16802USA Applied Research Laboratory The Pennsylvania State UniversityUniversity ParkPA16802USA

Though silanization of aluminum powder is currently used to improve its flow properties,for use as an alternative fuel source,there are a wide range of experimental parameters for the process and not all of them have been thoroughly *** this is complete,it is unknown if the process is optimized in terms of time,efficiency,and ***,we report on a study into the effects of changes in humidity,degree of agitation,reaction temperature,and curing time upon the deposition of phenyl triethoxysilane into 20μm(d50)aluminum *** confirm the deposition of the coating via diffuse reflectance infrared spectroscopy and x-ray photoelectron *** then characterize the coated particles using apparent density measurements and Carney flow *** analysis of variance,we find that,of the parameters explored,only changes in cure time and reaction temperature provide meaningful changes to the apparent density,while none of our parameters produced statistically significant changes in Carney flow ***,we conclude that,when optimizing silanization of aluminum particles,environmental control of humidity is unneeded and that the reaction can be run with minimal *** ability to largely ignore these parameters is a benefit to large-scale processing.

关键词： Aluminum powder Silane Fluidization Apparent density Carney flow

Generation of meaningful synthetic sensor data—Evaluated with a reliable transferability methodology

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Energy and AI 2024年第1期15卷 248-264页

作者： Michael Meiser benjamin Duppe Ingo Zinnikus Deutsches Forschungszentrum für künstliche Intelligenz(DFKI) Stuhlsatzenhausweg 3Saarbrücken66123SaarlandGermany

As households are equipped with smart meters,supervised Machine Learning(ML)models and especially Non-Intrusive Load Monitoring(NILM)disaggregation algorithms are becoming increasingly *** be robust,these models require a large amount of data,which is difficult to ***,the generation of meaningful synthetic data is becoming more *** use a simulation framework to generate multiple datasets using different techniques and evaluate their quality statistically by measuring the performance of NILM models for *** demonstrate that the method of data generation is crucial to train ML models in a meaningful *** experiments conducted reveal that adding noise to the synthetic smart meter data is essential to train robust NILM models for *** best results are obtained when this noise is derived from unknown appliances for which no ground truth data is *** we observed that NILM models can provide unstable results,we develop a reliable evaluation methodology,based on Cochran’s sample ***,we compare the quality of the generated synthetic data with real data and observe that multiple NILM models trained on synthetic data perform significantly better than those trained on real data.

关键词： Smart home Synthetic sensor data Energy data Transfer learning Evaluation methodology Machine learning Neural networks NILM Seq2point WindowGRU DAE Seq2seq RNN

Laser-induced plasma formation in water with up to 400 mJ double-pulse LIBS

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Plasma Science and Technology 2024年第1期26卷 93-100页

作者： Marion HENKEL Michelle SIEMENS Ralf METHLING benjamin EMDE Jörg HERMSDORF Steffen FRANKE Diego GONZALEZ Leibniz Institute for Plasma Science and Technology(INP) Felix-Hausdorff-Straße 2Greifswald 17489Germany Laser Zentrum Hannover e.V.(LZH) Hollerithallee 8Hannover 30419Germany

Double-pulse LIBS is a promising technique for deep-sea *** measurements in shallow water with up to 400 mJ each pulse were done to select laser parameters which promote optimized spectral line emission from plasma even at elevated pressures,where line broadening until loss of most of the spectral information can *** emission spectroscopy,using a Czerny-Turner spectrometer,has been applied to investigate the dependence of the emitted radiation on laser parameters and hydrostatic *** has been found,that higher laser pulse energies,especially with short pulse delay as required in high water pressure,can also have an adverse effect on the measured spectrum.

关键词： double-pulse LIBS underwater plasma formation emission spectrosocpy