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The acceleration of a high-charge electron bunch to 10 GeV in a 10-cm nanoparticle-assisted wakefield accelerator

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Matter and Radiation at Extremes 2024年第1期9卷 15-24页

作者： Constantin Aniculaesei Thanh Ha Samuel Yoffe Lance Labun Stephen Milton Edward McCary Michael M.Spinks Hernan J.Quevedo Ou Z.Labun Ritwik Sain Andrea Hannasch Rafal Zgadzaj Isabella Pagano Jose A.Franco-Altamirano Martin L.Ringuette Erhart Gaul Scott V.Luedtke Ganesh Tiwari Bernhard Ersfeld Enrico Brunetti Hartmut Ruhl Todd Ditmire Sandra Bruce Michael E.Donovan Michael C.Downer Dino A.Jaroszynski Bjorn Manuel Hegelich University of Texas at Austin AustinTexas 78712USA SUPA Department of Physics University of StrathclydeGlasgowScotland G4 ONGUnited Kingdom Tau systems Inc.AustinTexas 78701USA Lawrence Livermore National Laboratory LivermoreCalifornia 94550USA Los Alamos National Laboratory Los AlamosNew Mexico 87545USA Brookhaven National Laboratory UptonNew York 11973USA Ludwig-Maximilians-Universität MunichGermany

An intense laser pulse focused onto a plasma can excite nonlinear plasma *** appropriate conditions,electrons from the background plasma are trapped in the plasma wave and accelerated to ultra-relativistic *** scheme is called a laser wakefield *** this work,we present results from a laser wakefield acceleration experiment using a petawatt-class laser to excite the wakefields as well as nanoparticles to assist the injection of electrons into the accelerating phase of the *** find that a 10-cm-long,nanoparticle-assisted laser wakefield accelerator can generate 340 pC,10±1.86 GeV electron bunches with a 3.4 GeV rms convolved energy spread and a 0.9 mrad rms *** can also produce bunches with lower energies in the 4–6 GeV range.

关键词： acceleration nanoparticle charge

Accurate Distinc.ion of Weak and Strong AC Grids for Emerging Hierarchical-Infeed LCC-UHVDC systems

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CSEE Journal of Power and Energy systems 2024年第2期10卷 772-777页

作者： Hao Xiao Xianzhong Duan Yi Zhang Department of Electrical and Computer Engineering University of ManitobaWinnipeg R3T 2N2ManitobaCanada State Key Laboratory of Advanced Electromagnetic Engineering and Technology Hubei Electric Power Security and High Efficiency Key LaboratorySchool of Electrical and Electronic EngineeringHuazhong University of Science and TechnologyWuhan 430074HubeiChina RTDS Technologies inc. Winnipeg R3T 2E1ManitobaCanada

Distinc.ion of weak and strong AC grids for emerging hierarchical-infeed LCC-UHVDC systems is important for planning and operation departments. However, accuracy of earlier distinc.ion methods is limited as they were developed by empirical reasoning without rigorous theoretical analysis. Hence in this letter, hierarchical-infeed interactive effective short-circuit ratio (HIESCR) index is first used for strength evaluation of HIDC systems with complex inter-inverter interactions considered. Boundary HIESCR (BHIESCR) is also introduced in the proposed distinc.ion method of weak and strong AC grids. That is, weak (or strong) AC grids are, respectively, identified when HIESCR is less (or greater) than BHIESCR. Second, it is shown BHIESCR remains almost unchanged as 3.0 versus various system parameters and rated operation variables based on rigorous theoretical analysis. This salient feature makes the proposed method more accurate than earlier methods. Finally, the proposed method is validated by simulations based on the PSCAD/EMTDC program.

关键词： Hierarchical-Infeedinteractive effective short-circuit ratio hierarchical-infeed LCC-UHVDC systems inter-inverter interactions strong AC grids weak AC grids

Event-based optimization with random packet dropping

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Science China(Information Sciences) 2020年第11期63卷 175-194页

作者： Qing-Shan JIA Jing-Xian TANG Zhenning LANG Center for Intelligent and Networked systems Department of AutomationTsinghua University NetEase inc.

Event-based optimization(EBO) provides a general framework for policy optimization in many discrete event dynamic systems where decision making is triggered by events that represent state transitions with common features. Because the number of events can be defined by the user and usually inc.eases linearly with respect to the system scale, EBO has good potential to address large-scale problems where the state space grows exponentially. However, in many practical systems, sensors are geographically distributed and connected to a central controller through imperfect communication channels. Therefore, events observed by the sensors may not reach the controller. Optimization methods of event-based policies in these cases have not yet been identified. In this paper, we consider this important problem and make three major contributions. First, we formulate a mathematical EBO model in which the communication between sensors and controllers is subject to random packet dropping. Second, we show that this EBO model can be converted to another EBO model with perfect communication. Then, the performance difference equation and the performance derivative equation for event-based policies are straightforward to develop. One gradient-based policy iteration algorithm is developed for problems where the state transition probabilities are explicitly known, while another for problems where they are unknown. Third, the performance of the algorithms and the impact of the packet dropping probability on policy performance are numerically demonstrated on a single-zone occupant level estimation problem in buildings.

关键词： event-based optimization packet dropping discrete event dynamic systems

Mucosal vaccine development for respiratory viral infections

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hLife 2024年第2期2卷 50-63页

作者： Yifan Lin Zhenxiang Hu Yang-Xin Fu Hua Peng Department of Basic Medical Sciences School of MedicineTsinghua UniversityBeijingChina LivzonBio inc. GuangdongChina Guangzhou Laboratory Guangzhou International Bio IslandGuangdongChina

Mucosal vaccines have risen to prominence in the corona virus disease 2019(COVID-19)pandemic due to their ability to elicit both local antibody and tissue-resident T cell responses,affording a dual-layered defense against infection and transmission at respiratory entry *** intramuscular vaccines predominantly focus on systemic immunity,mucosal vaccines offer a more nuanced,site-specific ***,the field faces a dearth of mucosal vaccine options for respiratory diseases,starkly contrasting to the extensive array of well-characterized injectable *** unique features of mucosal surfaces necessitate specialized adjuvants and delivery systems,adding complexity to adapting injectable vaccine technologies for mucosal ***,we review the recent insights into the specificities of respiratory mucosal immunology that provide a foundation for future innovations besides the emerging vaccine platforms,newly discovered adjuvants,and vaccine delivery systems,which may open promising avenues for developing mucosal vaccines targeting respiratory pathogens.

关键词： mucosal immunology respiratory viruses vaccine adjuvants

Simulating hydrodynamics of hot and large Group A particle systems at cold conditions to obtain data for scale-up

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Particuology 2010年第6期8卷 501-502页

作者： Ted M.Knowlton Particulate Solid Research Inc.4201 W.36th StreetChicagoILUSA

Scaling laws based on the concept of dimensional similitude are proposed to simulate the hydrodynamics of hot and large particle systems at conditions of cold and small particle systems. This technique uses the concept of dimensional similitude to accomplish this by maintaining certain dimensional groups constant in the large, hot and small, cold systems. However, there are certain limitations with this technique. One of them is that the particle size in the small, cold system is usually smaller than in the large, hot system. Because particle size is such a dominant parameter in fluidized systems, this can certainly affect the simulation. An alternative method of simulating hot hydrodynamics in ambient-temperature Group A particle systems has been proposed. In this method, the same calculated drag force is maintained between the two systems. The drag force is varied by changing the gas density of the cold system so that it matches the drag force in the hot system.

关键词： Drag Drag force Simulation Modeling

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Deep Reinforcement Learning or Lyapunov Analysis?A Preliminary Comparative Study on Event-Triggered Optimal Control

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IEEE/CAA Journal of Automatica Sinica 2024年第7期11卷 1702-1704页

作者： Jingwei Lu Lefei Li Qinglai Wei Fei-Yue Wang IEEE the Department of Industrial Engineering Tsinghua UniversityBeijing 100084China The State Key Laboratory for Management and Control of Complex systems Institute of AutomationChinese Academy of SciencesBeijing 100190China

Dear Editor,This letter develops a novel method to implement event-triggered optimal control(ETOC) for discrete-time nonlinear systems using parallel control and deep reinforcement learning(DRL), referred to as Deep-ETOC. The developed Deep-ETOC method introduces the communication cost into the performance index through parallel control, so that the developed method enables control systems to learn ETOC policies directly without triggering conditions.

关键词： Deep letter enable

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Robust Machine Learning Mapping of sEMG Signals to Future Actuator Commands in Biomechatronic Devices

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Journal of Bionic Engineering 2024年第1期21卷 270-287页

作者： Ali Nasr Sydney Bell Rachel L.Whittaker Clark R.Dickerson John McPhee systems Design Engineering University of WaterlooWaterloo N2L 3G1Canada Kinesiology and Health Sciences University of WaterlooWaterloo N2L3G3Canada

A machine learning model for regression of interrupted Surface Electromyography(sEMG)signals to future control-oriented signals(e.g.,robot’s joint angle and assistive torque)of an active biomechatronic device for high-level myoelectric-based hierarchical control is proposed.A Recurrent Neural Network(RNN)was trained using output data,initially obtained from offline optimization of the biomechatronic(human–robot)device and shifted by the prediction *** input of the RNN consisted of interrupted sEMG signals(to mimic signal disconnections)and previous kinematic signals of the assistive *** RNN with a 0.1-s prediction horizon could predict the control-oriented joint angle and assistive torque with 92%and 86.5%regression accuracy,respectively,for the test *** proposed approach permits a fast,predictive,and direct estimation of control-oriented signals instead of an iterative process that optimizes assistive torque in the inverse dynamic simulation of a multibody human–robot *** with these interrupted input signals significantly improves the regression accuracy in the case of sEMG signal *** Robust Predictive Control-oriented Machine Learning(Robust-MuscleNET)model can support volitional high-level myoelectric-based control of biomechatronic devices,such as exoskeletons,prostheses,and assistive/resistive *** work should study the application to prosthesis control as well as the repeatability of the high-level controller with electrode *** low-level hierarchical controller that manages the human–robot interaction,the assistance/resistance strategy,and the actuator coordination should also be studied.

关键词： Myoelectric-based control-Surface electromyography Machine learning Multibody system dynamics Exoskeleton Bionic

U-Net Inspired Deep Neural Network-Based Smoke Plume Detection in Satellite Images

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Computers, Materials & Continua 2024年第4期79卷 779-799页

作者： Ananthakrishnan Balasundaram Ayesha Shaik Japmann Kaur Banga Aman Kumar Singh Centre for Cyber Physical systems Vellore Institute of Technology(VIT)ChennaiTamil Nadu600127India School of Computer Science and Engineering Vellore Institute of Technology(VIT)ChennaiTamil Nadu600127India

Industrial activities, through the human-induced release of Green House Gas (GHG) emissions, have beenidentified as the primary cause of global warming. Accurate and quantitative monitoring of these emissions isessential for a comprehensive understanding of their impact on the Earth’s climate and for effectively enforcingemission regulations at a large scale. This work examines the feasibility of detecting and quantifying industrialsmoke plumes using freely accessible geo-satellite imagery. The existing systemhas so many lagging factors such aslimitations in accuracy, robustness, and efficiency and these factors hinder the effectiveness in supporting timelyresponse to industrial fires. In this work, the utilization of grayscale images is done instead of traditional colorimages for smoke plume detection. The dataset was trained through a ResNet-50 model for classification and aU-Net model for segmentation. The dataset consists of images gathered by European Space Agency’s Sentinel-2 satellite constellation from a selection of industrial sites. The acquired images predominantly capture scenesof industrial locations, some of which exhibit active smoke plume emissions. The performance of the abovementionedtechniques and models is represented by their accuracy and IOU (Intersection-over-Union) *** images are first trained on the basic RGB images where their respective classification using the ResNet-50model results in an accuracy of 94.4% and segmentation using the U-Net Model with an IOU metric of 0.5 andaccuracy of 94% which leads to the detection of exact patches where the smoke plume has occurred. This work hastrained the classification model on grayscale images achieving a good inc.ease in accuracy of 96.4%.

关键词： Smoke plume ResNet-50 U-Net geo satellite images early warning global monitoring

An emerging terpolymeric nanoparticle pore former as an internal recrystallization inhibitor of celecoxib in controlled release amorphous solid dispersion beads:Experimental studies and molecular dynamics analysis

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Acta Pharmaceutica Sinica B 2024年第6期14卷 2669-2684页

作者： Jamie Anne Lugtu-Pe Xuning Zhang Sako Mirzaie Hao Han R.Chang Nour AL-Mousawi Kuan Chen Yongqiang Li Anil Kane Daniel Bar-Shalom Xiao Yu Wu Advanced Pharmaceutics and Drug Delivery Laboratory Leslie Dan Faculty of PharmacyUniversity of TorontoToronto M5S 3M2Canada Candoo Pharmatech Company inc. Mississauga L5N 5M1Canada Department of Pharmacy University of CopenhagenCopenhagen DK-2100Denmark Patheon by Thermo Fisher Scientific Toronto Region Operations(TRO)Mississauga L5N 3X4Canada

Solid oral controlled release formulations feature numerous clinical advantages for drug candidates with adequate solubility and dissolution ***,most new chemical entities exhibit poor water solubility,and hence are exempt from such *** combining drug amorphization with controlled release formulation is promising to elevate drug solubility,like other supersaturating systems,the problem of drug recrystallization has yet to be resolved,particularly within the dosage ***,we explored the potential of an emerging,non-leachable terpolymer nanoparticle(TPN)pore former as an internal recrystallization inhibitor within controlled release amorphous solid dispersion(CRASD)beads comprising a poorly soluble drug(celecoxib)reservoir and insoluble polymer(ethylcellulose)*** to conventional pore former,polyvinylpyrrolidone(PVP),TPN-containing membranes exhibited superior structural integrity,less crystal formation at the CRASD bead surface,and greater extent of celecoxib ***-atom molecular dynamics analyses revealed that in the presence of TPN,intra-molecular bonding,crystal formation tendency,diffusion coefficient,and molecular flexibility of celecoxib were reduced,while intermolecular H-bonding was inc.eased as compared to *** work suggests that selection of a pore former that promotes prolonged molecular separation within a nanoporous controlled release membrane structure may serve as an effective strategy to enhance amorphicity preservation inside CRASD.

关键词： Controlled release amorphous solid dispersion Poorly soluble drug Internal recrystallization Membrane-reservoir coated beads Molecular dynamics simulation Effect of pore formers Terpolymer nanogel Drug-polymer interactions