mlsa-iai-msu-lab/ru_sci_bench_zho_cite_reranking huggingface dataset:
Use of regression trees to predict overweight trucks from historical weigh-in-motion data

The traffic of overloaded trucks is a critical problem in highways. It affects pavement performance life, reduces the service life of bridges, and has a negative impact on road safety, average speed and level of service. There are several practices to prevent the truck overloading issue, i.e., enforcement activities to verify the truck's compliance with the legal weight limits. This paper investigates the development of a method that uses available weigh-in-motion (WIM) data to identify overloaded truck weight and travel patterns. The proposed approach is based on regression trees method, a simple and easily understandable analytic tool used to build prediction models from a large set of data. An overall analysis of the overloaded truck regression tree model shows that the most important variable to classify and predict overloading is the truck type. Regarding the axle overloading, the most significant variable is the time of the day (most of the overloaded trucks travel at late night or early morning). The regression tree results can be used to optimize the efficiency of administration activities by planning truck enforcement operations based on the more critical scenarios. Also, the results improve the knowledge about the load characteristics of trucks, which can lead to more effective pavement management systems and more assertive pavement structure designs.
Lane departure warning systems and lane line detection methods based on image processing and semantic segmentation: A review

Recently, the development and application of lane line departure warning systems have been in the market. For any of the systems, the key part of lane line tracking, lane line identification, or lane line departure warning is whether it can accurately and quickly detect lane lines. Since 1990s, they have been studied and implemented for the situations defined by the good viewing conditions and the clear lane markings on road. After then, the accuracy for particular situations, the robustness for a wide range of scenarios, time efficiency and integration into higher-order tasks define visual lane line detection and tracking as a continuing research subject. At present, these kinds of lane marking line detection methods based on machine vision and image processing can be divided into two categories: the traditional image processing and semantic segmentation (includes deep learning) methods. The former mainly involves feature-based and model-based steps, and which can be classified into similarity-and discontinuity-based ones; and the model-based step includes different parametric straight line, curve or pattern models. The semantic segmentation includes different machine learning, neural network and deep learning methods, which is the new trend for the research and application of lane line departure warning systems. This paper describes and analyzes the lane line departure warning systems, image processing algorithms and semantic segmentation methods for lane line detection.
Unconventional Hall effect induced by Berry curvature

Berry phase and Berry curvature play a key role in the development of topology in physics and do contribute to the transport properties in solid state systems. In this paper, we report the finding of novel nonzero Hall effect in topological material ZrTe5 flakes when the in-plane magnetic field is parallel and perpendicular to the current. Surprisingly, both symmetric and antisymmetric components with respect to magnetic field are detected in the in-plane Hall resistivity. Further theoretical analysis suggests that the magnetotransport properties originate from the anomalous velocity induced by Berry curvature in a tilted Weyl semimetal. Our work not only enriches the Hall family but also provides new insights into the Berry phase effect in topological materials.
Control over π-π stacking of heteroheptacene-based nonfullerene acceptors for 16% efficiency polymer solar cells

Nonfullerene acceptors are being investigated for use in polymer solar cells (PSCs), with their advantages of extending the absorption range, reducing the energy loss and therefore enhancing the power conversion efficiency (PCE). However, to further boost the PCE, mobilities of these nonfullerene acceptors should be improved. For nonfullerene acceptors, the π-π stacking distance between cofacially stacked molecules significantly affects their mobility. Here, we demonstrate a strategy to increase the mobility of heteroheptacene-based nonfullerene acceptors by reducing their π-π stacking distances via control over the bulkiness of lateral side chains. Incorporation of 2-butyloctyl substituents into the nonfullerene acceptor (M36) leads to an increased mobility with a reduced π-π stacking distance of 3.45 A. Consequently, M36 affords an enhanced PCE of 16%, which is the highest among all acceptor-donor-acceptor-type nonfullerene acceptors to date. This strategy of control over the bulkiness of side chains on nonfullerene acceptors should aid the development of more efficient PSCs.
Development of a space cold atom clock

Atomic clocks with cold atoms play important roles in the field of fundamental physics as well as primary frequency standards. Operating such cold atom clocks in space paves the way for further exploration in fundamental physics, for example dark matter and general relativity. We developed a space cold atom clock (SCAC), which was launched into orbit with the Space Lab TG-2 in 2016. Before it deorbited with TG-2 in 2019,the SCAC had been working continuously for almost 3 years. During the period in orbit, many scientific experiments and engineering tests were performed. In this article, we summarize the principle, development and in-orbit results. These works provide the basis for construction of a space-borne time-frequency system in deep space.
New freshwater plesiosaurian materials from the Middle Jurassic Xintiangou Formation of the Sichuan Basin, southwestern China

Sichuan Basin is very famous for the Mesozoic reptiles, especially the Jurassic dinosaurs. Here, we report some isolated plesiosaurian teeth and vertebrae newly excavated from the Middle Jurassic Xintiangou Formation in Yunyang county, Chongqing City, the northeastern region of the Sichuan Basin, southwestern China. The specimens are referred to Pliosauroidea based on the combination of the following features: the circular cross-section of the tooth crown, apicobasal ridges fully covering the enamel surface and reaching to the apex, the short and amphicoelous centrum, the centrum shorter than wide or tall, and the absence of a keel on the lateral surface of the cervical centrum. With the fragmentary nature, it is undetermined whether the Yunyang specimens belong to a known taxon or represent a new species of Plesiosauria. These plesiosaurian specimens further demonstrate that the freshwater plesiosaurians are common in the Jurassic deposits of the Sichuan Basin. For a comprehensive knowledge of the plesiosaurians of the basin in origin, distribution and diversity, to discover new and more complete specimens is necessarily the first priority.
A milestone in single-atom catalysis for direct formic acid fuel cell

Single-atom catalysts (SACs) have opened up an era of great opportunities for catalytic science and industrial technology, and have fueled the rapid progress of catalytic research. SACs not only represent the ultimate atomic utilization efficiency of metal materials, but have also driven the quantitative-to-qualitative evolution of catalytic properties of materials brought about by size reduction. Thus, single-atom catalysis is a breakthrough in catalysis science towards atomically precise catalysis.
Evaluation of a novel Asymmetric Genetic Algorithm to optimize the structural design of 3D regular and irregular steel frames

We propose a new algorithm,named Asymmetric Genetic Algorithm (AGA),for solving optimization problems of steel frames.The AGA consists of a developed penalty function,which helps to find the best generation of the population.The objective function is to minimize the weight of the whole steel structure under the constraint of ultimate loads defined for structural steel buildings by the American Institute of Steel Construction (AISC).Design variables are the cross-sectional areas of elements (beams and columns) that are selected from the sets of side-flange shape steel sections provided by the AISC.The finite element method (FEM) is utilized for analyzing the behavior of steel frames.A 15-storey three-bay steel planar frame is optimized by AGA in this study,which was previously optimized by algorithms such as Particle Swarm Optimization (PSO),Particle Swarm Optimizer with Passive Congregation (PSOPC),Particle Swarm Ant Colony Optimization (HPSACO),Imperialist Competitive Algorithm (ICA),and Charged System Search (CSS).The results of AGA such as total weight of the structure and number of analyses are compared with the results of these algorithms.AGA performs better in comparison to these algorithms with respect to total weight and number of analyses.In addition,five numerical examples are optimized by AGA,Genetic Algorithm (GA),and optimization modules of SAP2000,and the results of them are compared.The results show that AGA can decrease the time of analyses,the number of analyses,and the total weight of the structure.AGA decreases the total weight of regular and irregular steel frame about 11.1% and 26.4% in comparing with the optimized results of SAP2000,respectively.
Matching user identities across social networks with limited profile data

Privacy preservation is a primary concern in social networks which employ a variety of privacy preservations mechanisms to preserve and protect sensitive user information including age, location, education, interests, and others. The task of matching user identities across different social networks is considered a challenging task. In this work, we propose an algorithm to reveal user identities as a set of linked accounts from different social networks using limited user profile data, i.e., user-name and friendship. Thus, we propose a framework, ExpandUIL, that includes three standalone algorithms based on (i) the percolation graph matching in ExpandFullName algorithm, (ii) a supervised machine learning algorithm that works with the graph embedding, and (iii) a combination of the two, ExpandUserLinkage algorithm. The proposed framework as a set of algorithms is significant as, (i) it is based on the network topology and requires only name feature of the nodes, (ii) it requires a considerably low initial seed, as low as one initial seed suffices, (iii) it is iterative and scalable with applicability to online incoming stream graphs, and (iv) it has an experimental proof of stability over a real ground-truth dataset. Experiments on real datasets, Instagram and VK social networks, show upto 75% recall for linked accounts with 96% accuracy using only one given seed pair.
Cross-stacked super-aligned carbon nanotube/activated carbon composite electrodes for efficient water purification via capacitive deionization enhanced ultrafiltration

The practical application of the capacitive deionization (CDI) enhanced ultrafiltration (CUF) technology is hampered due to low performance of electrodes.The current study demonstrated a novel super-aligned carbon nanotube (SACNT)/activated carbon (AC) composite electrode, which was prepared through coating AC on a cross-stacked SACNT film.The desalination capability and water purification performance of the prepared electrode were systematically investigated at different applied voltages (0.8-1.2 V) with a CDI system and a CUF system, respectively.In the CDI tests, as compared with the control AC electrode, the SACNT/AC electrode achieved an approximately 100% increase in both maximum salt adsorption capacity and average salt adsorption rate under all the applied voltage conditions, demonstrating a superior desalination capability.Meanwhile, a conspicuous increase by an average of ~26% in charge efficiency was also achieved at all the voltages.In the CUF tests, as compared with the control run at 0 V, the treatment runs at 0.8, 1.0, and 1.2 V achieved a 2.40-fold, 2.08-fold, and 2.43-fold reduction in membrane fouling (calculated according to the final transmembrane pressure (TMP) data at the end of every purification stage), respectively.The average TMP increasing rates at 0.8, 1.0, and 1.2 V were also roughly two times smaller than that at 0 V, indicating a dramatical reduction of membrane fouling.The SACNT/AC electrode also maintained its superior desalination capability in the CUF process, resulting in an overall improved water purification efficiency.
Metabonomic analysis of plasma biochemical changes in pyrexia rats after treatment with Gegenqinlian decoction, aspirin and itraconazole by UHPLC-FT-ICR-MS

A metabonomic approach involving an ultrahigh-performance liquid chromatography combined with Fourier transform ion cyclotron resonance mass spectrometry (UHPLC-FT-ICR-MS) was used to investigate the changes in the endogenous metabolites in the plasma of rats with yeast-induced pyrexia treated with Gegenqinlian decoction (GQLD), aspirin and itraconazole. The differences in the small molecule profiles of treatment using traditional Chinese medicine, etiological treatment and symptomatic treatment were elucidated. Thirty-six plasma metabolites were identified or putatively identified, and the effects of the three medicines on the thirty-six metabolites were studied. Their metabolic pathways indicated that GQLD, aspirin and itraconazole ameliorated the rats with yeast-induced pyrexia predominantly by regulating the metabolisms of phospholipid, sphingolipid, fatty acid oxidation, fatty acid amides, amino acid and glycerolipid in vivo. The pharmacodynamics and metabonomic results showed that the three medicines exhibited the therapeutic effects on pyrexia by regulating the perturbations of multiple metabolisms. The study provided a scientific basis for an in-depth understanding of the therapeutic effects of GQLD, aspirin and itraconazole on rats with yeast-induced pyrexia.
Experimental investigation of a novel micro gas turbine with flexible switching function for distributed power system

Micro gas turbine (MGT) is widely used in small-scale distributed power systems because of its low emissions and fuel flexibility.However, the under-utilization of its exhaust heat and the low electric efficiency are the main bottlenecks that restrict its application.Additionally, the flexible switching between the power generated by the MGTand the power grid is also a key factor for keeping the secure operation of a distributed power station.Therefore, this paper conducted some experimental investigations of a 30 kW MGT to provide reference solutions for the above issues.This MGT is located at Shanghai Jiao Tong University (SJTU), which is designed by the Gas Turbine Research Institute of SJTU, and is manufactured by a turbo-machinery factory in Chongqing, China.The demonstration prototype is mainly composed of a single stage centrifugal compressor, a radial turbine, a combustor, a high-speed permanent magnet generator, and a control system.The results show that the MGT can achieve steady operation at a low rotational speed from 10000 r/min to 34000 r/min in the case of using oil lubricated bearings, which can greatly reduce the economic cost compared with the use of air bearings.At the same time, the ignition success rate of combustion chamber (CC) reaches 98% at a low rotational speed, and a wide range of stable combustion area can be obtained, because of the novel design method of combustor by referencing the way applied in an axial flow aero-engine.The MGT generating set can achieve functions, such as starting up, ignition, stable operation, loaded operation, grid-connection and stopping.This system also can realize flexibly switching from the start motor mode to the generator mode, and from grid-connected mode to off-grid mode, because the innovative multi-state switching control system is adopted.The above research work can make our state master independent intellectual property rights of micro gas turbine, rather than continue to be subject to the technological monopoly of the developed states, which can provide theoretical and experimental support for the industrialization of MGT in China.
Thermal annealing synthesis of double-shell truncated octahedral Pt-Ni alloys for oxygen reduction reaction of polymer electrolyte membrane fuel cells

Shape-controlled Pt-Ni alloys usually offer an exceptional electrocatalytic activity toward the oxygen reduction reaction (ORR) of polymer electrolyte membrane fuel cells (PEMFCs), whose tricks lie in welldesigned structures and surface morphologies.In this paper, a novel synthesis of truncated octahedral PtNi3.5 alloy catalysts that consist of homogeneous Pt-Ni alloy cores enclosed by NiO-Pt double shells through thermally annealing defective heterogeneous PtNi3.5 alloys is reported.By tracking the evolution of both compositions and morphologies, the outward segregation of both PtOx and NiO are first observed in Pt-Ni alloys.It is speculated that the diffusion of low-coordination atoms results in the formation of an energetically favorable truncated octahedron while the outward segregation of oxides leads to the formation of NiO-Pt double shells.It is very attractive that after gently removing the NiO outer shell, the dealloyed truncated octahedral core-shell structure demonstrates a greatly enhanced ORR activity.The as-obtained truncated octahedral Pt_(2.1)Ni core-shell alloy presents a 3.4-folds mass-specific activity of that for unannealed sample, and its activity preserves 45.4% after 30000 potential cycles of accelerated degradation test (ADT).The peak power density of the dealloyed truncated octahedral Pt_(2.1)Ni core-shell alloy catalyst based membrane electrolyte assembly (MEA) reaches 679.8 mW/cm~2, increased by 138.4 mW/cm~2 relative to that based on commercial Pt/C.
Erosion-deposition patterns and depo-center movements in branching channels at the near-estuary reach of the Yangtze River

Channel evolution and depo-center migrations in braided reaches are significantly influenced by variations in runoff.This study examines the effect of runoff variations on the erosion-deposition patterns and depocenter movements within branching channels of the nearestuary reach of the Yangtze River.We assume that variations in annual mean duration days of runoff discharges, ebb partition ratios in branching channels,and the erosional/depositional rates of entire channels and sub-reaches are representative of variations in runoff intensity, flow dynamics in branching channels, and morphological features in the channels.Our results show that the north region of Fujiangsha Waterway, the Liuhaisha branch of Rugaosha Waterway, the west branch of Tongzhousha Waterway, and the west branch of Langshansha Waterway experience deposition or reduced erosion under low runoff intensity, and erosion or reduced deposition under high runoff intensity, with the depocenters moving upstream and downstream, respectively.Other waterway branches undergo opposite trends in erosion-deposition patterns and depo-center movements as the runoff changes.These morphological changes may be associated with trends in ebb partition ratio as the runoff discharge rises and falls.By flattening the intra-annual distribution of runoff discharge, dam construction in the Yangtze Basin has altered the ebb partition ratios in waterway branches, affecting their erosion-deposition patterns and depo-center movements.Present trends are likely to continue into the future due to the succession of large cascade dams under construction along the upper Yangtze and ongoing climate change.
Different sites of extranodal involvement may affect the survival of patients with relapsed or refractory non-Hodgkin lymphoma after chimeric antigen receptor T cell therapy

Factors associated with complete and durable remissions after anti-CD19 chimeric antigen receptor T (CAR-T) cell immunotherapy for relapsed or refractory non-Hodgkin lymphoma (r/r NHL) have not been well characterized.In this study,we found that the different sites of extranodal involvement may affect response,overall survival (OS),and progression-free survival (PFS) in patients with r/r NHL treated with anti-CD19 CAR-T cells.In a cohort of 32 treated patients,12 (37.5%) and 8 (25%) patients exhibited soft tissue lymphoma and bone marrow (BM) infiltrations,respectively,and 13 (41%) patients exhibited infiltration at other sites.The factors that may affect prognosis were identified through multivariable analysis.As an independent risk factor,soft tissue infiltration was the only factor significantly correlated with adverse prognosis (P <0.05),whereas other factors did not reach statistical significance.Furthermore,the site of extranodal tumor infiltration significantly and negatively affected OS and PFS in patients with r/r NHL treated with anti-CD19 CAR-Tcell therapy.PFS and OS in patients with BM involvement were not significantly different from those of patients with lymph node involvement alone.Thus,anti-CD19 CAR-T cell therapy may improve the prognosis of patients with BM infiltration.
Analysis of driving forces of water demand in Jing-Jin-Ji district in recent years based on water demand field theory

In recent years,urbanization has accelerated and the gap between urban water supply and demand has become more significant.This phenomenon has led to greater demands on urban water resource management.Thus,analyses of the forces that drive urban water demand growth can help efficient management of urban water resources."Jing-Jin-Ji" refers to the district composed of Beijing and Tianjin,municipality as well as Hebei Province,which is among the political and economic centers of China.The traditional analysis of driving force for water resources often consider cities as independent individuals and ignores the interaction between them.Such method cannot describe the spatial distribution of regional water demand.In this study,the water demand field theory is used to construct water demand and social development fields for the Jing-Jin-Ji district with relevant indicators.The distribution trends of the two fields,and the correlation of their intensities,are then analyzed.Principal component analysis is used to specifically determine the forces that drive water demand at different stages of development.Results indicate that the water demand field theory can accurately describe spatial variations in water demand intensity in the study area.The main driving force for water demand in the Jing-Jin-Ji district from 2000 to 2014 is the growth of urban population.However,in 2015 and 2016,"GDP of the tertiary industry" overtook it.The results of this study can serve as a basis for regional water demand forecasting,with large potential to be applied to urban water resource management.