mlsa-iai-msu-lab/ru_sci_bench_zho_cite_reranking huggingface dataset:
Conceptual design and neutronic analysis of a megawatt-level vehicular microreactor based on TRISO fuel particles and S-CO_2 direct power generation

With global warming, the demand for diversified energy sources has increased significantly. Transportable microreactors are important potential supplements to the global power market and are a promising development direction. This paper describes a 5 MW integrated long-life S-CO_2 cooled vehicular microreactor(VMR) design based on tristructural isotropic(TRISO) fuel particles that aims to provide electricity for industrial power facilities, remote mines, and remote mountainous areas that are not connected to central power grids. First, to facilitate transportation, flexible deployment, and simplified operation and maintenance requirements, the VMR core and auxiliary system were designed to be reasonably small and as simple as possible. Second, the TRISO fuel particles used in the proposed VMR offer excellent properties, such as high inherent security and nonproliferation, which are vital for reactors in remote areas. In addition, a long core lifetime was achieved using the compact core design and enhanced fuel loading capacity, which is challenging when using TRISO as fuel. Finally, to make the VMR economically competitive in terms of improved neutron performance and fuel efficiency compared to similar designs, large-size TRISO particles and tube-in-duct fuel assembly were utilized and different core configurations were schemed and simulated to obtain the design that best satisfied the proposed criteria. The lifetime and burnup in the final optimized VMR were satisfactory at 21 years and 43.9 MWd/kgU, respectively, with an adequate shutdown margin and excellent safety parameters to ensure safe operation.
Update on lymphocyte-activation gene 3 (LAG-3) in cancers:from biological properties to clinical applications

Immunotherapy that targets checkpoints,especially programmed cell death protein 1 and programmed cell death ligand 1,has revolutionized cancer therapy regimens.The overall response rate to mono-immunotherapy,however,is limited,emphasizing the need to potentiate the efficacy of these regimens.The functions of immune cells are modulated by multiple stimulatory and inhibitory molecules,including lymphocyte activation gene 3 (LAG-3).LAG-3 is co-expressed together with other inhibitory checkpoints and plays key roles in immune suppression.Increasing evidence,particularly in the last 5 years,has shown the potential of LAG-3 blockade in anti-tumor immunity.This review provides an update on the biological properties and clinical applications of LAG-3 in cancers.
Meshless Surface Wind Speed Field Reconstruction Based on Machine Learning

We propose a novel machine learning approach to reconstruct meshless surface wind speed fields, i.e., to reconstruct the surface wind speed at any location, based on meteorological background fields and geographical information. The random forest method is selected to develop the machine learning data reconstruction model (MLDRM-RF) for wind speeds over Beijing from 2015-19. We use temporal, geospatial attribute and meteorological background field features as inputs. The wind speed field can be reconstructed at any station in the region not used in the training process to crossvalidate model performance. The evaluation considers the spatial distribution of and seasonal variations in the root mean squared error (RMSE) of the reconstructed wind speed field across Beijing. The average RMSE is 1.09 m s-1, considerably smaller than the result (1.29 m s-1) obtained with inverse distance weighting (IDW) interpolation. Finally, we extract the important feature permutations by the method of mean decrease in impurity (MDI) and discuss the reasonableness of the model prediction results. MLDRM-RF is a reasonable approach with excellent potential for the improved reconstruction of historical surface wind speed fields with arbitrary grid resolutions. Such a model is needed in many wind applications, such as wind energy and aviation safety assessments.
Ni_3N Modified MOF Heterostructure with Tailored Electronic Structure for Efficient Overall Water Splitting

Exploring bifunctional electrocatalysts with high-efficiency and stability toward overall water splitting is desirable for sustainable energy technologies, yet challenging. Herein, we report the construction of Ni3N on the surface of Ni-MOF-74 through an in-situ nitriding process. The obtained Ni-MOF-74/Ni_3N exhibits remarkable HER activity with an overpotential of 73 mV to deliver 10 mA cm~(–2). Theoretical calculations and experimental study demonstrate the electron transport between Ni_3N and Ni-MOF-74, leading to the improved H_2O adsorption, optimized hydrogen adsorption, and increased Had diffusion, which contributes to the enhanced HER performance. Besides, the obtained Ni-MOF-74/Ni_3N also possesses outstanding activity toward OER and overall water splitting.
Solvent extraction with a three-dimensional reticulated hollow-strut SiC foam microchannel reactor

Recently, there has been considerable interest in the use of microchannel reactors for hydrometallurgy of rare earths (REs). Here, a novel integrated microchannel reactor based on the hollow-strut SiC foam material is presented and demonstrated to extract Ce~(3+) and Pr~(3+) using 2-ethylhexyl phosphoric acid mono-2- ethylhexyl ester (P507) as the extractant. The typical three-dimensional reticulated structure of the hollow-strut SiC foam was characterized by scanning electron microscopy and X-ray micro computed tomography. Since the reactor's structure plays a key role in fluid mixing and mass diffusion during the extraction process, the structure-performance relationship of the foam was studied by extraction experiments combined with numerical simulations. Using the foam with the optimal structure, the influence of the flow rate Q0 of the two liquid phases on the extraction efficiency g and overall volume mass transfer coefficient KLa was discussed. For both RE ions, with increasing Q0, g decreases while KLa increases. For the total flow rate of the two phases of 4 ml·min~(-1), the g values of Pr~(3+) and Ce~(3+) reached 98.7% and 97.0%, respectively. For the total flow rate of 36 ml·min~(-1) which was much higher than that of many other microchannel reactors reported in the literatures, the g values of Pr~(3+) and Ce~(3+) still reached 92.2% and 86.9%, respectively, and the KLa values of Pr~(3+) and Ce~(3+) were 0.198 and 0.161 s~(-1), respectively, similar to the high values reported for other microchannel reactors studied in previous work. These findings indicate that the hollow-strut SiC foam microchannel reactor is suitable for use in REs extraction.
Recent progress in synthesis of composite powders and their applications in low-carbon refractories

The development of low-carbon refractories is of great significance, but it is limited by the deteriorated properties that resulted from the decreased graphite content. Incorporating composite powders has proved to be effective in improving the properties of low-carbon refractories. The recent progress in the synthesis of composite powders including modified graphite, nanocarbon-containing composite powders, oxide/non-oxide and non-oxide composite powders and their applications in low-carbon refractories were reviewed, and the future development of composite powder technology was prospected.
后循环脑梗死合并中枢性高热致多器官功能障碍综合征1例并文献综述

中枢性高热(central hyperthermia)是指人体体温调节中枢损害而引起的高热,常见于脑出血、脑外伤、急性神经损伤等病变,但临床上中枢性高热导致多器官功能障碍综合征(multiple organ dysfunction syndrome,MODS)的病例罕见。本文报道1例大面积脑梗死引起的中枢性高热所致的MODS,并探讨其可能的发病机制及诊治。本病例报道已获得患者家属知情同意。
超声-壳聚糖联用科学养护党参的初步研究

目的通过分时段取样观察药材外观性状,分时段测定各种主要药典指标变化,分析确定超声-壳聚糖(CS)联用养护党参药材的最佳配比方案。方法以普通水洗党参和超声净洗党参为对照组,将党参超声净洗后再利用超声分散作用在含有一定量壳聚糖的养护液中养护后足干,通过肉眼观察和测定各种药典指标及其变化,综合评价养护效果。结果对照组普通水洗党参9个月后发生虫蛀,18 ~ 24个月时逐渐出现严重的虫蛀,并伴有轻微霉变和色变,超声净洗组党参15个月末出现轻微虫蛀,24个月时虫蛀严重并伴有轻微霉变和色变;超声-0.1% ~ 0.2%CS养护党参24个月末出现轻微虫蛀,超声-0.3% ~ 0.5%CS养护党参24个月末仍未出现虫蛀和霉变。各时段所测定的各种主要药典指标,均符合要求。结论超声-壳聚糖(CS)联用养护党参最佳养护条件是超声-0.3% CS,养护后党参药材完好贮藏期超过24个月,超声-壳聚糖联用养护中药材党参具有操作简便,安全、高效、经济、环保的特点。
法医病理学死亡原因分类及死因分析探讨

在法医病理鉴定实践中,作为诉讼主要证据的法医病理学死亡原因鉴定意见经常会存在或引发以下问题:(1)死亡原因与死亡方式、死亡机制等概念不清或相互混用,如把"器官功能衰竭"作为死亡原因等;(2)根本死因与直接死因概念不清或相互混用;(3)直接死因与辅助死因概念混淆;(4)伤病等多因素致死的案件中,各因素相互之间的关系及其在死因构成中的作用区分不清,盲目放大或缩小损伤(疾病)等在死因中的作用力;(5)司法人员及社会大众对法医学死因分析、结论认知存在片面性和局限性。因此,要解决上述客观普遍存在的问题,需要厘清涉及死亡原因和死因分析的法医病理学专业相关概念,才能更好地服务于司法实践。
广东省中山市南朗古镇

南朗古镇位于广东省中山市东部,东临珠江口,西依五桂山,与港澳地区隔海相望。南朗古镇作为我国伟大的民主革命先行者孙中山先生的故乡,亦是著名侨乡,2009年被广东省人民政府公布为第二批省级历史文化名镇。
抗p21Ras蛋白抗体研发及在肿瘤病理和肿瘤治疗中的研究进展

ras基因突变或过表达可导致多种肿瘤的发生,约30%的肿瘤中存在ras基因突变。p21Ras蛋白是ras基因表达的产物。抗p21Ras蛋白抗体的研发,为ras驱动肿瘤的病理诊断和治疗提供了新的研究方向。该文对抗p21Ras蛋白单克隆抗体、单链抗体、细胞内抗体、重组抗体的研发和应用情况进行简要综述。
希氏-浦肯野系统起搏在心力衰竭伴LBBB患者中的应用

左束支传导阻滞(LBBB)可导致心室电传导延迟、收缩不同步,是加重心力衰竭(心衰)的重要因素,亦是心衰治疗的重要靶点。传统双心室起搏可纠正LBBB、改善心功能,但其受到技术及解剖的限制,仍有部分患者难以从中获益:随着对希氏-浦肯野系统认识的深入、导线置入工具的改进及技术的发展,希氏-浦肯野系统起搏作为一种生理性起搏方式,成为当前研究的热点。希氏-浦肯野系统起搏可纠正LBBB、恢复电机械同步性,有望作为传统双心室起搏的替代疗法用于心衰伴LBBB患者。该文对希氏-浦肯野系统起搏在心衰伴LBBB患者中应用的理论及临床进展进行了综述。
Battery Full Life Cycle Management and Health Prognosis Based on Cloud Service and Broad Learning

This letter presents battery full life cycle management and health prognosis based on cloud service and broad learning. Specifically, a cloud-based framework for battery full life cycle management is presented. Then, the broad learning method is proposed for battery state-of-health (SOH) prediction. The features of charging data including the constant current time, constant voltage time, and the total charging time are selected as the input characteristics of the network to estimate SOH. Moreover, the empirical mode decomposition is carried out on the initial data to restore the most essential attenuation trajectory of battery capacity. Experimental results show that the proposed method can provide more accurate battery SOH prediction than several state-of-the-art methods.
Spatial Humanities and Geo-computation for Social Sciences:Advances and Applications

Humanities and Social Sciences (HSS) are undergoing the transformation of spatialization and quantification.Geocomputation,with geoinformatics (including RS:Remote Sensing;GIS:Geographical Information System;GNSS:Global Navigation Satellite System),provides effective computational and spatialization methods and tools for HSS.Spatial Humanities and Geo-computation for Social Sciences (SH&GSS) is a field coupling geo-computation,and geoinformatics,with HSS.This special issue accepted a set of contributions highlighting recent advances in methodologies and applications of SH&GSS,which are related to sentiment spatial analysis from social media data,emotional change spatial analysis from news data,spatial analysis of social media related to COVID-19,crime spatiotemporal analysis,"double evaluation"for Land Use/Land Cover (LUCC),Specially Protected Natural Areas (SPNA) analysis,editing behavior analysis of Volunteered Geographic Information (VGI),electricity consumption anomaly detection,First and Last Mile Problem (FLMP) of public transport,and spatial interaction network analysis for crude oil trade network.Based on these related researches,we aim to present an overview of SH&GSS,and propose some future research directions for SH&HSS.
The Extent and Effectiveness of Protected Areas in the Russian Federation

To tackle environmental challenges and in particular,the problems associated with the high demand for forests and resources,the consequence of which is the degradation of ecological systems,Russia has developed the biggest network of specially protected natural areas in the world.Although the scale of SPNA may look impressive,a recent comprehensive study of the period from 2001 to 2018 brought the spotlight on protected areas in Russia experiencing significant tree loss annually.Since Russia is confronting unprecedented fires that break records every year,the problem of preserving rare animal and plant species,their habitats,and natural ecosystems is acute.This paper is intended to assess the extent and effectiveness of SPNAs with regard to wilderness conservation in the Russian Federation based on the latest data;the main focus being on the period of 2014-2019,before and after the launch of the environmental safety strategies,along with additional analysis of available data for the following year of 2020.With due consideration of unique geographical,economic,and socio-cultural circumstances,as well as historical background and legislative reality of SPNAs in Russia,we have conducted a statistical analysis of data from the official annual reports from the Federal State Statistics Service on SPNAs by territories and significance,expenditures on maintenance and ecotourism,followed by RGB analysis of satellite imagery via means of GIS software for visualization of obtained data and further analytics.Despite the growth of the SPNA network in Russia,resulting in an astonishing 2402 Mha in 2020,an estimated 4 Mha of tree loss accounted for SPNAs over the period of 2014-2019,and 134 Mha in 2020 alone.Our findings indicate a need for the application of a comprehensive GIS approach for further development and effective management of the SPNA network in Russia.Furthermore,the results include recommendations on legislative changes,engagement of locals in SPNA protection,and popularization of ecotourism,all of which can be valuable for policymakers and SPNA development.
Remote Sensing and Forest Carbon Monitoring-a Review of Recent Progress,Challenges and Opportunities

Remote sensing provides key inputs to a wide range of models and methods developed for quantifying forest carbon.In particular,carbon inventory methods recommended by IPCC require biomass data and a suite of forest disturbance products.Significant progress has been made in deriving these products by leveraging publicly available remote sensing assets,including observations acquired by the legendary Landsat mission and new systems launched within the past decade,including Sentinel-2,Sentinel-1,GEDI,and ICESAT-2.With the L-band NISAR and P-band BIOMASS missions to be launched in 2023,the Earth's land surfaces will be imaged by optical and multi-band (including C-,L-,and P-bands) radar systems that can provide global,sub-weekly observations at sub-hectare spatial resolutions for public use.Fine scale products derived from these observations will be crucial for developing monitoring,reporting,and verification (MRV) capabilities needed to support carbon trade,REDD+,and other market-driven tools aimed at achieving climate mitigation goals through forest management at all levels.Following a brief discussion of the roles of forests in the global carbon cycle and the wide range of models and methods available for evaluating forest carbon dynamics,this paper provides an overview of recent progress and forthcoming opportunities in using remote sensing to map forest structure and biomass,detect forest disturbances,determine disturbance attribution,quantify disturbance intensity,and estimate harvested timber volume.Advances in these research areas require large quantities of well-distributed reference data to calibrate remote sensing algorithms and to validate the derived products.In addition,two of the forest carbon pools-dead organic matter and soil carbon-are difficult to monitor using modern remote sensing capabilities.Carefully designed inventory programs are needed to collect the required reference data as well as the data needed to estimate dead organic matter and soil carbon.
Finite-time leader-follower consensus of a discrete-time system via slidingmode control

In this study, we solve the finite-time leader-follower consensus problem of discrete-time second-order multi-agent systems (MASs) under the constraints of external disturbances. First, a novel consensus scheme is designed using a novel adaptive sliding mode control theory. Our adaptive controller is designed using the traditional sliding mode reaching law, and its advantages are chatter reduction and invariance to disturbances. In addition, the finite-time stability is demonstrated by presenting a discrete Lyapunov function. Finally, simulation results are presented to prove the validity of our theoretical results.
Transcriptomics-based identification and characterization of genes related to sugar metabolism in ‘Hongshuijing' pitaya

Sugar composition not only affects fruit flavor but is also an important determinant of fruit taste and consumer preference. In this study, changes in the sugar content and sugar-metabolizing enzymes were investigated from different sections of various fruit development phases of ‘Hongshuijing' pitaya (Hylocereus monacanthus). Genes related to sugarmetabolism were also screened by transcriptome analyses. The results indicated that glucose was the major sugar in mature pitaya fruit, and was mainly regulated by vacuolar acid invertase (VAI) and sucrose synthase (SS) (degradative direction). Sugar accumulation varied in pulp between different sections of the pitaya fruit. VAI, neutral invertase (NI) and SS (degradative direction) are crucial enzymes for sugar accumulation in pitaya. The expression of 17 genes related to sucrose metabolism obtained from seven databases [NCBI non-redundant protein database (Nr), NCBI non-redundant nucleotide sequence database (Nt), EuKaryotic Orthologous Groups (KOG), The Protein Families (Pfam), Kyoto Encyclopedia of Genes and Genomes (KEGG), Swiss-prot, and Gene Ontology (GO)] were analyzed in different pitaya pulp sections. HpVAI1 had the highest relative expression level on the 29th day after pollination (DAP). Positive correlations were found between HpVAI1 expression and VAI activity; HpNI4 and NI activity; HpSS2, HpSS5, and SS activity (synthetic direction), indicating that HpVAI1, HpNI4, and HpSS2 and HpSS5 were involved in the regulation of VAI, NI, and SS (synthetic direction), respectively. HpVAI1 and HpNI4 regulated sucrose degradation and the accumulation of glucose and fructose, while HpSS2 and HpSS5 regulated sucrose synthesis. These results suggest that HpVAI1 plays a key role in sugar metabolism during fruit development of ‘Hongshuijing' pitaya. The results of this study provide new information about sugar metabolism in pitaya fruit that could help improve fruit quality and the breeding of new cultivars.
Multi-perspective analysis on rainfall-induced spatial response of soil suction in a vegetated soil

In this study,an intelligent monitoring platform is established for continuous quantification of soil,vegetation,and atmosphere parameters (e.g.soil suction,rainfall,tree canopy,air temperature,and wind speed) to provide an efficient dataset for modeling suction response through machine learning.Two characteristic parameters representing suction response during wetting processes,i.e.response time and mean reduction rate of suction,are formulated through multi-gene genetic programming (MGGP) using eight selected influential parameters including depth,initial soil suction,vegetation- and atmosphererelated parameters.An error standard-based performance evaluation indicated that MGGP has appreciable potential for model development when working with even fewer than 100 data.Global sensitivity analysis revealed the importance of tree canopy and mean wind speed to estimation of response time and indicated that initial soil suction and rainfall amount have an important effect on the estimated suction reduction rate during a wetting process.Uncertainty assessment indicated that the two MGGP models describing suction response after rainfall are reliable and robust under uncertain conditions.Indepth analysis of spatial variations in suction response validated the robustness of two obtained MGGP models in prediction of suction variation characteristics under natural conditions.
Register Allocation Compilation Technique for ASIP in 5G Micro Base Stations

The currently available compilation techniques are for general computing and are not optimized for physical layer computing in 5G micro base stations. In such cases, the foreseeable data sizes and small code size are application specific opportunities for baseband algorithm optimizations. Therefore, the special attention can be paid, for example, the specific register allocation algorithm has not been studied so far. The compilation for kernel sub-routines of baseband in 5G micro base stations is our focusing point. For applications of known and fixed data size, we proposed a compilation scheme of parallel data accessing, while operands can be mainly allocated and stored in registers. Based on a small register group(48×32b), the target of our compilation scheme is the optimization of baseband algorithms based on 4×4 or smaller matrices, maximizing the utilization of register files, and eliminating the extra register data exchanging. Meanwhile, when data is allocated into register files, we used VLIW(Very Long Instruction Word)machine to hide the time of data accessing and minimize the cost of data accessing, thus the total execution time is minimum. Experiments indicate that for algorithms with small data size, the cost of data accessing and extra addressing can be minimized.
Detection,isolation,and characterization of a novel impurity from several folic acid products

Folic acid belongs to the group of water-soluble B vitamins and naturally exists in multiple forms in a wide variety of foods such as legumes,vegetables,liver,and milk (Iyer and Tomar,2009;Lyon et al.,2020).It is involved in many biochemical reactions critical for cell division,such as purine and pyrimidine biosynthesis,DNA/RNA biosynthesis,and amino acid metabolism (Iyer and Tomar,2009).Mammals cannot synthesize folic acid and thus they must acquire it from food.Although folic acid is ubiquitous in foods,folic acid deficiency still often occurs due to various causes such as unhealthy diet (Hildebrand et al.,2021;Iimura et al.,2022),disease-related malabsorption (Arcot and Shrestha,2005),medication-related depletion (Arcot and Shrestha,2005),or vitamin B12 deficiency (Fishman et al.,2000).Folic acid deficiency has been associated with several health problems,such as anemia (Carmel,2005;Bailey and Caudill,2012),cancer (Duthie,1999),cardiovascular diseases (Wald et al.,2002),neural tube defects in newborns (van der Put et al.,2001),neuropsychiatric dysfunction (Shea et al.,2002),depression (Falade et al.,2021),inflammatory diseases (Suzuki and Kunisawa,2015;Jones et al.,2019),and eye diseases (Sijilmassi,2019).To prevent folic acid deficiency,its daily intake (400 μg/d) has been recommended for adults in the European Union,and its increased intake (600 μg/d) is advised for women before and during pregnancy (FAO/WHO,2002;IOM,2004).The New Zealand government mandated the fortification of non-organic wheat flour with folic acid in July 2021,and the UK government mandated the fortification of non-wholemeal wheat flour with folic acid in September 2021 (Haggarty,2021).
Intelligent service function chain mapping framework for cloud-and-edge-collaborative IoT

With the rapid development of Internet of thing (IoT) technology,it has become a challenge to deal with the increasing number and diverse requirements of IoT services. By combining burgeoning network function virtualization (NFV) technology with cloud computing and mobile edge computing (MEC),an NFV-enabled cloud-and-edge-collaborative IoT (CECIoT) architecture can efficiently provide flexible service for IoT traffic in the form of a service function chain (SFC) by jointly utilizing edge and cloud resources. In this promising architecture, a difficult issue is how to balance the consumption of resource and energy in SFC mapping. To overcome this challenge,an intelligent energy-and-resource-balanced SFC mapping scheme is designed in this paper. It takes the comprehensive deployment consumption as the optimization goal,and applies a deep Q-learning(DQL)-based SFC mapping (DQLBM) algorithm as well as an energy-based topology adjustment (EBTA) strategy to make efficient use of the limited network resources,while satisfying the delay requirement of users. Simulation results show that the proposed scheme can decrease service delay,as well as energy and resource consumption.