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MANY-SERVER QUEUES WITH CUSTOMER ABANDONMENT:A SURVEY OF DIFFUSION AND FlUID APPROXIMATIONS

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journal of Systems Science and Systems Engineering 2012年第1期21卷 1-36页

作者： j. G. DAI Shuangchi he H. Milton Stewart School of Industrial and Systems Engineering Georgia Institute of Technology Atlanta GA 30332 USA. Department of Industrial and Systems Engineering National University of Singapore Singapore 11757

The performance of a call center is sensitive to customer abandonment. In this survey paper, we focus on G/GI/n ＋ GI parallel-server queues that serve as a building block to model call center operations. Such a queue has a general arrival process （the G ）, independent and identically distributed （iid） service times with a general distribution （the first G1 ）, and iid patience times with a general distribution （the ＋GI）. Following the square-root safety staffing rule, this queue can be operated in the quality- and efficiency-driven （QED） regime, which is characterized by large customer volume, the waiting times being a fraction of the service times, only a small fraction of customers abandoning the system, and high server utilization. Operational efficiency is the central target in a system whose staffing costs dominate other expenses. If a moderate fraction of customer abandonment is allowed, such a system should be operated in an overloaded regime known as the efficiency-driven （ED） regime. We survey recent results on the many-server queues that are operated in the QED and ED regimes. These results include the performance insensitivity to patience time distributions and diffusion and fluid approximate models as practical tools for performance analysis.

关键词： heavy traffic square-root safety staffing quality- and efficiency-driven regime efficiency-driven regime piecewise OU process

Brain-penetrating neurotrophic factor mimetics: heR-096 as a disease-modifying therapy for Parkinson’s disease

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Neural Regeneration Research 2025年第4期20卷 1094-1095页

作者： Natalia Kulesskaya Kira M.Holmström henri j.Huttunen herantis Pharma Plc EspooFinland

Neurotrophic factors as a therapeutic approach in neurodegenerative diseases:A major unmet need in the field of central nervous system diseases is disease-modifying *** for decades there have been various symptomatic treatments available to alleviate the symptoms of the disease,disease-modification,*** that stop,significantly delay,or reverse the progression of the disease,has been turned out to a difficult goal to achieve.

关键词： diseases treatment therapeutic

Temporal dynamics of neonatal hypoxic-ischemic encephalopathy injuries on magnetic resonance imaging

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Neural Regeneration Research 2025年第11期20卷 3144-3150页

作者： Holly Flyger Samantha j.Holdsworth Alistair j.Gunn laura Bennet Hamid Abbasi Mātai Medical Research Institute Tairāwhiti GisborneNew Zealand Department of Anatomy&Medical Imaging Faculty of Medical and Health SciencesThe University of AucklandAucklandNew Zealand Center for Brain Research The University of AucklandAucklandNew Zealand Auckland Bioengineering Institute The University of AucklandAucklandNew Zealand

Moderate to severe perinatal hypoxic-ischemic encephalopathy occurs in~1 to 3/1000 live births in high-income countries and is associated with a significant risk of death or neurodevelopmental *** assessment is important to help identify highrisk infants,to help families,and to support appropriate interventions.A wide range of monitoring tools is available to assess changes over time,including urine and blood biomarkers,neurological examination,and *** present,magnetic resonance imaging is unique as although it is expensive and not suited to monitoring the early evolution of hypoxic-ischemic encephalopathy by a week of life it can provide direct insight into the anatomical changes in the brain after hypoxic-ischemic encephalopathy and so offers strong prognostic information on the long-term outcome after hypoxic-ischemic *** review investigated the temporal dynamics of neonatal hypoxic-ischemic encephalopathy injuries,with a particular emphasis on exploring the correlation between the prognostic implications of magnetic resonance imaging scans in the first week of life and their relationship to long-term outcome prediction,particularly for infants treated with therapeutic hypothermia.A comprehensive literature search,from 2016 to 2024,identified 20 pertinent *** review highlights that while the optimal timing of magnetic resonance imaging scans is not clear,overall,it suggests that magnetic resonance imaging within the first week of life provides strong prognostic *** challenges limit the timing consistency,particularly the need for intensive care and clinical ***,although most reports examined the prognostic value of scans taken between 4 and 10 days after birth,there is evidence from small numbers of cases that,at times,brain injury may continue to evolve for weeks after *** suggests that in the future it will be important to explore a wider range of times after hypo

关键词： magnetic resonance imaging neonatal hypoxic-ischemic encephalopathy neurodevelopmental outcomes prognostic biomarkers in neuroimaging scan timing therapeutic hypothermia

Partial least square modeling of hydrolysis: analyzing the impacts of pH and acetate

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journal of Environmental Sciences 2006年第4期18卷 805-809页

作者： lü Fan he Pin-jing SHAO li-ming State Key laboratory of Pollution Control and Resources Reuse Tongji University Shanghai 200092 China

pH and volatile fatty acids both might affect the further hydrolysis of particulate solid waste, which is the limiting-step of anaerobic digestion. To clarify the individual effects of pH and volatile fatty acids, batch experiments were conducted at fixed pH value （pH 5-9） with or without acetate （20 g/l）. The hydrolysis efficiencies of carbohydrate and protein were evaluated by carbon and nitrogen content of solids, amylase activity and proteinase activity. The trend of carbohydrate hydrolysis with pH was not affected by the addition of acetate, following the sequence ofpH 7〉pH 8〉pH 9〉pH 6〉pH 5; but the inhibition of acetate （20 g/l） was obvious by 10%-60 %. The evolution of residual nitrogen showed that the effect of pH on protein hydrolysis was minor, while the acetate was seriously inhibitory especially at alkali condition by 45%-100 %. The relationship between the factors （pH and acetate） and the response variables was evaluated by partial least square modeling （PlS）. The PlS analysis demonstrated that the hydrolysis of carbohydrate was both affected by pH and acetate, with pH the more important factor. Therefore, the inhibition by acetate on carbohydrate hydrolysis was mainly due to the corresponding decline of pH, but the presence of acetate species, while the acetate species was the absolutely important factor for the hydrolysis of protein.

关键词： inhibition hydrolysis pH volatile fattyacids partial least square

A Survey of Human-centered Intelligent Robots:Issues and Challenges

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IEEE/CAA journal of Automatica Sinica 2017年第4期4卷 602-609页

作者： Wei he Zhijun li C.l.Philip Chen IEEE School of Automation and Electrical Engineering University of Science and Technology Beijing College of Automation Science and Engineering South China University of Technology Department of Computer and Information Science Faculty of Science and Technology University of Macao

Intelligent techniques foster the dissemination of new discoveries and novel technologies that advance the ability of robots to assist and support humans. The human-centered intelligent robot has become an important research field that spans all of the robot capabilities including navigation, intelligent control, pattern recognition and human-robot interaction. This paper focuses on the recent achievements and presents a survey of existing works on human-centered robots. Furthermore, we provide a comprehensive survey of the recent development of the human-centered intelligent robot and discuss the issues and challenges in the field.

关键词： Human-centered robots human-robot interaction intelligent control navigation path planning pattern recognition

Small extrachromosomal circular DNA in amyotrophic lateral sclerosis matter

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Neural Regeneration Research 2025年第5期20卷 1411-1413页

作者： Marcos j.Arauzo-Bravo Daniela Gerovska Matthias Schwab Alexandra Kretz Computational Biology and Systems Biomedicine Biodonostia Health Research InstituteSan SebastianSpain Basque Foundation for Science IKERBASQUEBilbaoSpainMax Planck Institute for Molecular BiomedicineComputational Biology and Bioinformatics GroupMünsterNorth Rhine-WestphaliaGermany Department of Cell Biology and Histology Faculty of Medicine and NursingUniversity of Basque Country(UPV/EHU)LeioaSpain Department of Neurology Jena University HospitalJenaThuringiaGermany

Comprehensive studies identify motor neuron spectrum disorders including amyotrophic lateral sclerosis(AlS)as globally rising fatal disorders with the highest prevalence in aging populations,influenced by ethnicity and ancestry(GBD 2016 Motor Neuron Disease Colla borators,2018).While~10% of diagnoses involve a family history(fAlS),most cases are considered sporadic(sAlS).However,population-based studies suggest that even cases without a common index mutation impart heritability(Ryan et al.,2019),indicating a crucial role of rare and as yet unknown genetic denominators.

关键词： amyotrophic sclerosis

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企业网络地位对数据资产信息披露的影响研究

工业技术经济 2025年第1期44卷 75-84页

作者：何地赵唱庞铭辽宁大学经济学部亚澳商学院沈阳110136 大连财经学院会计学院大连116122

随着数据资产作为重要战略资源的价值日益凸显,数据资产信息披露已经成为学术界和实业界共同关注的重要议题。本文基于2009~2023年A股上市公司数据,实证检验了企业网络地位对数据资产信息披露的影响及作用机制。研究结果发现,企业网络... 详细信息

随着数据资产作为重要战略资源的价值日益凸显,数据资产信息披露已经成为学术界和实业界共同关注的重要议题。本文基于2009~2023年A股上市公司数据,实证检验了企业网络地位对数据资产信息披露的影响及作用机制。研究结果发现,企业网络地位对其数据资产信息披露水平具有正向影响。机制分析结果表明,客户集中度在企业网络地位对其数据资产信息披露水平的影响中发挥调节作用,即客户集中度越低,企业网络地位对其数据资产信息披露水平的影响越强。异质性分析结果发现,对于非国有企业、多阶(长链)结构和小规模企业而言,企业网络地位对数据资产信息披露的影响效果尤为明显。本文揭示了企业网络地位影响数据资产信息披露的微观机制,为我国完善数据要素市场制度以及促进数字经济高质量发展提供了政策启示。

关键词：企业网络地位数字资产信息披露客户集中度文本分析法信号传递理论数字经济数字化转型企业竞争力

Polarisation optics for biomedical and clinical applications:a review

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light(Science & Applications) 2021年第11期10卷 2028-2047页

作者： Chao he Honghui he jintao Chang Binguo Chen Hui Ma Martin j.Booth Department of Engineering Science University of OxfordParks RoadOxford OX13PJUK Guangdong Engineering Center of Polarisation Imaging and Sensing Technology Tsinghua Shenzhen International Graduate SchoolTsinghua University518055 ShenzhenChina Institute of Biopharmaceutical and health Engineering Tsinghua Shenzhen International Graduate SchoolTsinghua University518055 ShenzhenChina Department of Physics Tsinghua University100084 BeijingChina Department of Biomedical Engineering Tsinghua University100084 BeijingChina

Many polarisation techniques have been harnessed for decades in biological and clinical research,each based upon measurement of the vectorial properties of light or the vectorial transformations imposed on light by *** advanced vector measurement/sensing techniques,physical interpretation methods,and approaches to analyse biomedically relevant information have been developed and *** this review,we focus mainly on summarising methodologies and applications related to tissue polarimetry,with an emphasis on the adoption of the Stokes-Mueller *** recent breakthroughs,development trends,and potential multimodal uses in conjunction with other techniques are also *** primary goal of the review is to give the reader a general overview in the use of vectorial information that can be obtained by polarisation optics for applications in biomedical and clinical research.

关键词： clinical optics breakthrough

Prediction of mechanical properties for deep drawing steel by deep learning

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International journal of Minerals,Metallurgy and Materials 2023年第1期30卷 156-165页

作者： Gang Xu jinshan he Zhimin lü Min li jinwu Xu Collaborative Innovation Center of Steel Technology University of Science and Technology BeijingBeijing 100083China Suzhou Baolian heavy Industry Co. Suzhou 215131China

At present,iron and steel enterprises mainly use“after spot test ward”to control final product ***,it is impossible to realize on-line quality predetermining for all products by this traditional approach,hence claims and returns often occur,resulting in major eco-nomic losses of *** order to realize the on-line quality predetermining for steel products during manufacturing process,the predic-tion models of mechanical properties based on deep learning have been proposed in this ***,the mechanical properties of deep drawing steels were predicted by using lSTM(long short team memory),GRU(gated recurrent unit)network,and GPR(Gaussian process regression)model,and prediction accuracy and learning efficiency for different models were also ***,on-line re-learning methods for transfer learning models and model parameters were *** experimental results show that not only the prediction accuracy of optimized trans-fer learning models has been improved,but also predetermining time was shortened to meet real time requirements of on-line property *** industrial production data of interstitial-free(IF)steel was used to demonstrate that R2 value of GRU model in training stage reaches more than 0.99,and R2 value in testing stage is more than 0.96.

关键词： machine learning recurrent natural network transfer learning on-line prediction deep drawing steel mechanical properties