mlsa-iai-msu-lab/ru_sci_bench_zho_cite_reranking huggingface dataset:
Feasibility of an innovative long-life molten chloride-cooled reactor

Molten salt-cooled reactor is one of the six Gen- IV reactors with promising characteristics including safety, reliability, proliferation resistance, physical protection, economics, and sustainability. In this paper, a small innovative molten chloride-cooled fast reactor(MCCFR) with 30-year core and a target 120-MWt thermal power was presented. For its feasible study, neutronics, thermal-hydraulics, and radiation damage analysis were performed. The key design properties including kinetics parameters, reactivity swing, reactivity feedback coefficients, maximum accumulated displacement per atom(DPA) of reactor pressure vessel(RPV) and fuel cladding, and maximum coolant, cladding, and fuel temperatures were evaluated. The results showed the MCCFR could operate without refueling for 30 years with overall negative reactivity feedback coefficients up the end of its life. During its 30-year life, the excess reactivity was well managed by constantly pulling out the control rods. The maximum accumulated DPA on RPV and fuel cladding were 8.92 dpa and 197.03 dpa, respectively, which are both below the design limits. Similarly, the maximum coolant, cladding and fuel center temperatures were all below the design limits during its entire lifetime. According to these results, the MCCFR core design with long life is feasible.
数码影像与TLS点云数据融合提取地质结构面方法研究

随着水电、交通、矿采等基础工程建设领域发展步伐的加快,工程地质勘查工作面临任务重、时间紧、难度高等各种新问题。传统接触式岩体结构面获取方式已不能满足地质勘测快速、准确、精细的要求。以TLS点云或数码影像作为数据源的非接触式主动测量方法在数据形式、数据采集和处理等方面具有各自的特点,将两种数据融合可实现空间信息与光学信息的优势互补,对地质信息提取研究具有实际价值。本文针对现有影像与点云提取地质信息存在的问题,以完整、准确和自动化特点为目的,对岩体结构面信息融合提取方法进行研究。
1型糖尿病遗传学研究进展

1型糖尿病(T1DM)是由T淋巴细胞介导的对胰岛β细胞的选择性破坏而导致胰岛素绝对缺乏的器官特异性自身免疫性疾病。遗传因素和环境因素相互作用,共同参与了1型糖尿病的发生发展。通过家系连锁分析、候选基因关联研究以及全基因组关联研究,迄今为止已经定位了60余个T1DM的易感位点。本文回顾了T1DM遗传学方面的研究进展,并对易感基因应用于T1DM的遗传风险预测进行了展望。
郑州市社区居民人体体质特征的调查

目的:调查郑州市社区居民人体体质特征,比较其性别、年龄间的差异及左右侧功能的差异。方法:选取19岁以上健康的郑州社区居民600例,其中,男性283例,女性317例,男、女性别在19~ 34岁、35~ 44岁、45~ 59岁、60 ~ 70岁4个年龄组的人数分布分别为80、79、73、51和83、85、87、62。采用体质测量法、直观判定法收集其11项人体功能类表型基础数据,比较其体质特征的性别、年龄间的差异与左右侧差异。结果:从性别上来看,女性的肩关节、腕关节、髋关节屈伸度和膝关节屈曲度均大于男性( P<0.05);从不同年龄组来看,同性别不同年龄组其关节活动度的差异具有统计学意义( P<0.05), 而同年龄组不同性别间的差异则无统计学意义( P>0.05);从左右侧来看,各年龄段的视力均为左侧好于右侧、握力右侧大于左侧( P<0.05), 肩关节活动度和髋关节的活动度均为右侧大于左侧( P<0.05) 。结论:郑州市社区居民的人体功能,不同性别、不同年龄组间有着不同的体质特征,且一些指标存在左右侧的差异,可为国人体质特征的研究提供基线资料。
Parallel Reinforcement Learning-Based Energy Efficiency Improvement for a Cyber-Physical System

As a complex and critical cyber-physical system(CPS),the hybrid electric powertrain is significant to mitigate air pollution and improve fuel economy.Energy management strategy(EMS)is playing a key role to improve the energy efficiency of this CPS.This paper presents a novel bidirectional long shortterm memory(LSTM)network based parallel reinforcement learning(PRL)approach to construct EMS for a hybrid tracked vehicle(HTV).This method contains two levels.The high-level establishes a parallel system first, which includes a real powertrain system and an artificial system.Then, the synthesized data from this parallel system is trained by a bidirectional LSTM network.The lower-level determines the optimal EMS using the trained action state function in the model-free reinforcement learning(RL)framework.PRL is a fully data-driven and learning-enabled approach that does not depend on any prediction and predefined rules.Finally, real vehicle testing is implemented and relevant experiment data is collected and calibrated.Experimental results validate that the proposed EMS can achieve considerable energy efficiency improvement by comparing with the conventional RL approach and deep RL.
Unified Smith Predictor Based H_∞ Wide-Area Damping Controller to Improve the Control Resiliency to Communication Failure

Inter-area low frequency oscillation in power system is one of the major problems for bulk power transmission through weak tie lines.Use of wide-area signal is more effective than the local area signal in damping out the inter-area oscillations.Wide area measurement system(WAMS)is convenient to transmit the wide area signal through the communication channel to the remote location.Communication failure is one of the disastrous phenomena in a communication channel.In this paper,a dual input single output(DISO)H_∞ controller is designed to build the control resiliency by employing two highest observability ranking wide area signals with respect to the critical damping inter-area mode.The proposed controller can provide sufficient damping to the system and also the system remains stabilized if one of the wide-area signals is lost.The time delay is an unwanted phenomenon that degrades the performance of the controllers.The unified Smith predictor approach is used to design a H_∞ controller to handle the time delay.Kundur's two-area and IEEE-39 bus test systems are considered to verify the effectiveness of the proposed controller.From the simulation results, it is verified that, the proposed controller provides excellent damping performance at normal communication and improves the controller resiliency to counteract the communication failure.
Artificial Intelligence Applications in the Development of Autonomous Vehicles: A Survey

The advancement of artificial intelligence(AI)has truly stimulated the development and deployment of autonomous vehicles(AVs)in the transportation industry.Fueled by big data from various sensing devices and advanced computing resources,AI has become an essential component of AVs for perceiving the surrounding environment and making appropriate decision in motion.To achieve goal of full automation(i.e., self-driving), it is important to know how AI works in AV systems.Existing research have made great efforts in investigating different aspects of applying AI in AV development.However, few studies have offered the research community a thorough examination of current practices in implementing AI in AVs.Thus, this paper aims to shorten the gap by providing a comprehensive survey of key studies in this research avenue.Specifically, it intends to analyze their use of AIs in supporting the primary applications in AVs: 1)perception;2)localization and mapping;and 3)decision making.It investigates the current practices to understand how AI can be used and what are the challenges and issues associated with their implementation.Based on the exploration of current practices and technology advances, this paper further provides insights into potential opportunities regarding the use of AI in conjunction with other emerging technologies: 1)high definition maps, big data, and high performance computing;2)augmented reality(AR)/virtual reality(VR)enhanced simulation platform;and 3)5G communication for connected AVs.This paper is expected to offer a quick reference for researchers interested in understanding the use of AI in AV research.
Proximity Based Automatic Data Annotation for Autonomous Driving

The recent development in autonomous driving involves high-level computer vision and detailed road scene understanding.Today, most autonomous vehicles employ expensive high quality sensor-set such as light detection and ranging(LIDAR)and HD maps with high level annotations.In this paper, we propose a scalable and affordable data collection and annotation framework, image-to-map annotation proximity(I2MAP), for affordance learning in autonomous driving applications.We provide a new driving dataset using our proposed framework for driving scene affordance learning by calibrating the data samples with available tags from online database such as open street map(OSM).Our benchmark consists of 40 000 images with more than 40 affordance labels under various day time and weather even with very challenging heavy snow.We implemented sample advanced driver-assistance systems(ADAS)functions by training our data with neural networks(NN)and cross-validate the results on benchmarks like KITTI and BDD100K, which indicate the effectiveness of our framework and training models.
Evolution of the deformation field and earthquake fracture precursors of strike-slip faults

Seismic hazard analysis is gaining increased attention in the present era because of the catastrophic effects of earthquakes. Scientists always have as a goal to develop new techniques that will help forecast earthquakes before their reoccurrence. In this research, we have performed a shear failure experiment on rock samples with prefabricated cracks to simulate the process of plate movement that forms strike-slip faults. We studied the evolution law of the deformation field to simulate the shear failure experiment, and these results gave us a comprehensive understanding of the elaborate strain distribution law and its formation process with which to identify actual fault zones. We performed uniaxial compression tests on marble slabs with prefabricated double shear cracks to study the distribution and evolution of the deformation field during shear failure. Analysis of the strain field at different loading stages showed that with an increase in the load, the shear strain field initially changed to a disordered-style distribution. Further, the strain field was partially concentrated and finally completely concentrated near the crack and then distributed in the shape of a strip along the crack. We also computed coefficients of variation(CVs)for the physical quantities u, v, and e_(xy), which varied with the load. The CV curves were found to correspond to the different loading stages. We found that at the uniform deformation stage, the CV value was small and changed slowly, whereas at the later nonuniform deformation stage, the CV value increased sharply and changed abruptly. Therefore, the precursor to a rock sample breakdown can be predicted by observing the variation characteristics of CV statistics. The correlation we found between our experimental and theoretical results revealed that our crack evolution and sample deformation results showed good coupling with seismic distribution characteristics near the San Andreas Fault.
Four-quadrant Force Control with Minimal Ripple for Linear Switched Reluctance Machines

Linear switch reluctance machine (LSRM) has been tried to act as an alternative generator for direct drive linear wave energy converter (WEC).Many researchers have proposed new topologies of LSRM to improve the power density,efficiency and reliability.However,the control methods for LSRM applied in direct drive WEC have been paid little attention,especially control methods considering the wave energy generator operating characteristics.In this paper,according to the generator control requirements of the direct drive WEC,force control algorithm for LSRM operating in four quadrants without a speed closed loop is put forward.The force ripple of LSRM is suppressed using force sharing function method.The four-quadrant control is easy to realize requiring only phase currents information.Simulation results validate the proposed method and indicate that LSRM is able to be used as the generator for direct drive WEC.
High Speed SRM Using Vector Control for Electric Vehicle

The high speed motor is effective to realize downsizing motor in an electric vehicle (EV).Switched Reluctance Motor (SRM) is possible to the high speed drive because the rotor structure has simple and robust.However,the vibration and the acoustic noise are large from the drive principle.Moreover,the conventional complicated current excitation results in the difficulty of the torque controller design.To overcome these problems,the vector control has been proposed for SRM drive.However,the vector control has not been applied to the SRM in the high speed drive.In this paper,the drive conditions such as switching frequency,bus voltage for driving the SRM in the high speed region are clarified.It is shown that the proposed SRM can be driven by the vector control in the high speed region and can realize low vibration.
Robustness Criteria for Concurrent Evaluation of the Impact of Tolerances in Multiobjective Electric Machine Design Optimization

This article is about a comparison of different measures for determining the robustness or reliability of electric machine designs in the presence of inevitable tolerances.The selected criteria shall be suitable for concurrent evaluation in the course of solving state-of-the-art large scale multi-objective optimization problems.In the past,besides particularly customized criteria,mainly gradient based measures,worst case information,or standard deviation based quantities were considered.In this work,the quantile measure is introduced for electric machine design optimization and compared with the existing solutions.The evaluation of a design's robustness is typically examined based on finite element simulations.As for most measures a significant number of parameter combinations and thus computations are required,a surrogate model assisted approach is presented to minimize computational effort and runtime.A test problem is defined and analyzed to illustrate the differences of selected robustness measures.Results reveal the importance of considering robustness in the optimization process.Moreover,a careful choice of appropriate measures has to be taken.Selected designs are compared and conclusions and an outlook on future activities are presented.
Electromagnetic Performance Analysis of Flux-Switching Permanent Magnet Tubular Machine with Hybrid Cores

The performance of traditional flux switching permanent magnet tubular machine (FSPMTM) are improved by using new material and structure in this paper.The existing silicon steel sheet making for all mover cores or part of stator cores are replaced by soft magnetic composite (SMC) cores,and the lamination direction of the silicon steel sheet in stator cores have be changed.The eddy current loss of the machine with hybrid cores will be reduced greatly as the magnetic flux will not pass through the silicon steel sheet vertically.In order to reduce the influence of end effect,the unequal stator width design method is proposed.With the new design,the symmetry of the permanent magnet flux linkage has been improved greatly and the cogging force caused by the end effect has been reduced.Both 2-D and 3-D finite element methods (FEM) are applied for the quantitative analysis.
Predictive Current Control for Voltage Source Inverters Considering Dead-Time Effect

This paper proposes a new concept of synthesized voltage vector to address dead-time effect issue for Finite Control Set Model Predictive Control (FCS-MPC) technique.For a voltage source inverter (VSI),dead-time is inevitably inserted between the turn off and turn on instants of power devices to avoid short circuit phenomenon.The influence of dead-time leads to output voltage vector error of three-phase inverters.Furthermore,it will result in computing deviation in cost function,and will deteriorate the performance of the system if not properly dealt with.In this paper,the problem is clearly analyzed,and the solution to this issue is proposed by introducing a synthesized voltage vector.The proposed solution is verified by Hardware-in-the-loop (HiL) test in real time,and results validate the effectiveness of the proposed solution.
Rapid estimation of soil heavy metal nickel content based on optimized screening of near-infrared spectral bands

In near-infrared spectroscopy, the traditional feature band extraction method has certain limitations.Therefore, a band extraction method named the three-step extraction method was proposed.This method combines characteristic absorption bands and correlation coefficients to select characteristic bands corresponding to various spectral forms and then uses stepwise regression to eliminate meaningless variables.Partial least squares regression(PLSR)and extreme learning machine(ELM)models were used to verify the effect of the band extraction method.Results show that the differential transformation of the spectrum can effectively improve the correlation between the spectrum and nickel(Ni)content.Most correlation coefficients were above 0.7 and approximately 20% higher than those of other transformation methods.The model effect established by the feature variable selection method based on comprehensive spectral transformation is only slightly affected by the spectral transformation form.In five types of spectral transformation, the RPD values of the proposed method were all within the same level.The RPD values of the PLSR model were concentrated between 1.6 and 1.8, and those of the ELM model were between 2.5 and 2.9, indicating that this method is beneficial for extracting more complete spectral features.The combination of the three-step extraction method and ELM algorithm can effectively retain important bands associated with the Ni content of the soil.The model based on the spectral band selected by the three-step extraction method has better prediction ability than the other models.The ELM model of the first-order differential transformation has the best prediction accuracy(R_P~2 = 0.923, RPD = 3.634).The research results provide some technical support for monitoring heavy metal content spectrum in local soils.
Rapid generation advance (RGA) in chickpea to produce up to seven generations per year and enable speed breeding

This study was aimed at developing a protocol for increasing the number of generation cycles per year in chickpea(Cicer arietinum L.). Six accessions, two each from early(JG 11 and JG 14), medium(ICCV 10 and JG 16), and late(CDC-Frontier and C 235) maturity groups, were used. The experiment was conducted for two years under glasshouse conditions. The photoperiod was extended to induce early flowering and immature seeds were germinated to further reduce generation cycle time. Compared to control, artificial light caused a reduction in flowering time by respectively 8–19, 7–16, and 11–27 days in early-, medium-,and late-maturing accessions. The earliest stage of immature seed able to germinate was 20–23 days after anthesis in accessions of different maturity groups. The time period between germination and the earliest stage of immature seed suitable for germination was considered one generation cycle and spanned respectively 43–60, 44–64, and 52–79 days in early-, medium-, and late-maturing accessions. However, the late-maturing accession CDCFrontier could not be advanced further after three generation cycles owing to the strong influence of photoperiod and temperature. The mean total number of generations produced per year were respectively 7, 6.2, and 6 in early-, medium-, and late-maturing accessions. These results have encouraging implications for breeding programs: rapid progression toward homozygosity, development of mapping populations, and reduction in time, space and resources in cultivar development(speed breeding).
Age of the earliest transgressive event in the Krishna-Godavari Basin,India:evidence from dinoflagellate cysts and planktonic foraminifera biostratigraphy

A combined biostratigraphic study of dinoflagellate cysts and foraminifera was carried out on Early Cretaceous subsurface well cutting sediments from well A (DNG) (2800–2746 m depth) from the Krishna-Godavari Basin,India.The last appearance datum of marker species of dinoflagellate cysts and planktonic foraminifera was considered for the construction of the biostratigraphic framework.The study shows dominance of Early Cretaceous marker dinoflagellate cysts Cassiculosphaeridia magna,Cribroperidinium perforans,Hystrichodinium voigtii,Kleithriasphaeridium eoinodes,and planktonic foraminifera Hedbergella aptiana,Hedbergella mitra,Hedbergella praelippa,Hedbergella tardita,Microhedbergella miniglobularis and Hedbergella mitra species.In addition to this,the dinoflagellate cyst data were compared with the dinoflagellate biozones of Austral and Tethyan provinces.Based on earlier micropalaeontological records from the Krishna-Godavari Basin and the present study,a latest Barremian-early Aptian age has been determined for the earliest marine transgression in the Krishna-Godavari Basin.The early marine incursion during late Barremian-earliest Aptian in the Krishna-Godavari Basin compared to Albian age in Cauvery Basin suggests the opening of east coast from north to south.
Generation of selectable marker-free soft transgenic rice with transparent kernels by downregulation of SSSII-2

The amylose content(AC) of rice endosperm starch varies from 0 to 35%, and is associated with rice cooking and eating quality. Soft rice has low AC, generally between 6% and 15%,and its eating quality is high whether it is consumed hot or cold. However, the appearance quality of current soft rice cultivars needs to be improved, especially opaque endosperm. Conventional genetic engineering has improved some agronomic traits of soft rice varieties,but not endosperm appearance. In the present study, a RNAi construct of the soluble starch synthase II-2(SSSII-2) and the hygromycin phosphotransferase(HPT) gene were introduced into an elite japonica rice variety, Kangtiaowuyunjing(KWY8) by co-transformation. Several selectable marker-free(SMF) transgenic lines were obtained, and SSSII-2 expression was significantly downregulated in selected transgenic lines, resulting in lower AC of the endosperm. The physicochemical properties of the transgenic rice kernels, including gel consistency(GC) and rapid visco analyzer(RVA) profile, differed significantly from those of wild-type rice and were similar to those of a soft rice variety, Nanjing 46(NJ46). These findings indicate that the cooking, eating, and processing qualities of transgenic rice are comparable to those of NJ46. However, the transgenic rice endosperm retained a transparent appearance under low-moisture conditions. Thus, SMF SSSII-2 RNAi rice provides a resource for breeding soft rice with transparent endosperm.
“瑞草”灵芝之现代研究

“灵芝”一词最早出现于东汉,人们“以为瑞草,服之神仙”,称之为“灵芝”。现指隶属于真菌界Fungi、担子菌门Basidiomycota、伞菌纲Agaricomycetes、多孔菌目Polyporales、灵芝科Ganodermataceae的一类传统药用真菌的统称,具有免疫调节、抗肿瘤、抗氧化、抑菌、保肝护肝、止咳平喘等多种功效(林志彬2015;Gill et al. 2016;Ahmad 2018;Wu et al. 2019)。
Hydro-geochemistry evolution in Ordovician limestone water induced by mountainous coal mining:A case study from North China

This research aimed to investigate the changing mechanism of hydro-geochemistry in Ordovician limestone karst (OL) water induced by mountainous coal mining activities.Thus,the hydrogeochemistry evolution of OL water over 40 years within a typical northern mountainous coal mine named Fengfeng Mine was studied by using Piper diagram,Gibbs scheme,ions correlation and Principal component analysis (PCA) methods.Results showed that,except for HCO_3~-,the ions of Ca~(2+),Mg~(2+),SO_4~(2-),Na~++K~+,Cl~-and total dissolution solids (TDS) values all increased by years as mining continues.Different hydro-geochemical characteristics in different periods can reflect different water-rock interactions.Accordingly,sulfates dissolution gradually took place of carbonates in water-rock interaction.Especially,OL water-rock interactions in different periods were all affected by rock weathering and evaporationconcentration together.At last,evaporationconcentration co-effect dominated the hydrogeochemistry evolution slowly,along with significant cations exchange over years.