AN APPAREL TRADE QUOTATION ARCHITECTURE BASED ON BPM AND SOA

Based on the analysis of problems and difficulties in apparel quotation system, this paper puts forward the combination of BPM and SOA as a new idea for analysis of apparel quotation system, according to their advantages in business goals and requirements analysis, and the corresponding services’ definition, extraction, optimization and integration. Through the combination, system flexibility, rapidity and accuracy could be achieved. The establishment of Service Repository according to the business requirements, is a crucial part in the architecture, however there are no definite rules for service extraction. In this paper, the detailed activities and steps, as well as a specific establishment case is illustrated. At last, architecture based on BPM and SOA for the apparel trade quotation is put forward, and its composition and implement are also analyzed

Neuropsychiatric Lupus Erythematosus: Future Directions and Challenges; a Systematic Review and Survey

This study aimed to systematically review neuropsychiatric lupus erythematosus (NPSLE) and establish a simplified diagnostic criterion for NPSLE. Publications from 1994 to 2018 in the database (Wanfang data (http://www.wanfangdata.com.cn/index.html) and China National Knowledge Internet (http://www.cnki.net)) were included. In total, 284 original case reports and 24 unpublished cases were collected, and clinical parameters were analyzed. An attempt was made to develop a set of simplified diagnostic criteria for NPSLE based on cases described in the survey and literature; moreover, and pathophysiology and management guidelines were studied. The incidence rate of NPSLE was estimated to be 12.4% of SLE patients in China. A total of 408 NPSLE patients had 652 NP events, of which 91.2% affected the central nervous system and 8.8% affected the peripheral nervous system. Five signs (manifestations, disease activity, antibodies, thrombosis, and skin lesions) showed that negative and positive predictive values were more than 70%, included in the diagnostic criteria. The specificity, accuracy, and positive predictive value (PPV) of the revised diagnostic criteria were significantly higher than those of the American College of Rheumatology (ACR) criteria (w2=13.642, 15.591, 65.010, po0.001). The area under the curve (AUC) for revised diagnostic criteria was 0.962 (standard error=0.015, 95% confidence intervals [CI] =0.933–0.990), while the AUC for the ACR criteria was 0.900 (standard error=0.024, 95% CI=0.853–0.946). The AUC for the revised diagnostic criteria was different from that for the ACR criteria (Z=2.19, po0.05). Understanding the pathophysiologic mechanisms leading to NPSLE is essential for the evaluation and design of effective interventions. The set of diagnostic criteria proposed here represents a simplified, reliable, and costeffective approach used to diagnose NPSLE. The revised diagnostic criteria may improve the accuracy rate for diagnosing NPSLE compared to the ACR criteria

Probabilistic Prediction of Longitudinal Trajectory Considering Driving Heterogeneity with Interpretability

Automated vehicles are envisioned to navigate safely in complex mixed-traffic scenarios alongside human-driven vehicles. To promise a high degree of safety, accurately predicting the maneuvers of surrounding vehicles and their future positions is a critical task and attracts much attention. However, most existing studies focused on reasoning about positional information based on objective historical trajectories without fully considering the heterogeneity of driving behaviors. Therefore, this study proposes a trajectory prediction framework that combines Mixture Density Networks (MDN) and considers the driving heterogeneity to provide probabilistic and personalized predictions. Specifically, based on a certain length of historical trajectory data, the situation-specific driving preferences of each driver are identified, where key driving behavior feature vectors are extracted to characterize heterogeneity in driving behavior among different drivers. With the inputs of the short-term historical trajectory data and key driving behavior feature vectors, a probabilistic LSTMMD-DBV model combined with LSTM-based encoder-decoder networks and MDN layers is utilized to carry out personalized predictions. Finally, the SHapley Additive exPlanations (SHAP) method is employed to interpret the trained model for predictions. The proposed framework is tested based on a wide-range vehicle trajectory dataset. The results indicate that the proposed model can generate probabilistic future trajectories with remarkably improved predictions compared to existing benchmark models. Moreover, the results confirm that the additional input of driving behavior feature vectors representing the heterogeneity of driving behavior could provide more information and thus contribute to improving the prediction accuracy.Comment: 14 pages, 8 figure

Modeling Lane-Changing Behavior in Freeway Off-Ramp Areas from the Shanghai Naturalistic Driving Study

The objective of this study is to investigate lane-changing characteristics in freeway off-ramp areas using Shanghai Naturalistic Driving Study (SH-NDS) data, considering a four-lane freeway stretch in various traffic conditions. In SH-NDS, the behavior of drivers is observed unobtrusively in a natural setting for a long period of time. We identified 433 lane-changing events with valid time series data from the whole dataset. Based on the logit model developed to analyze the choice of target lanes, a likelihood analysis of lane-changing behavior was graphed with respect to three traffic conditions: free flow, medium flow, and heavy flow. The results suggested that lane-changing behavior of exiting vehicles is the consequence of the balance between route plan (mandatory incentive) and expectation to improve driving condition (discretionary incentive). In higher traffic density, the latter seems to play a significant role. Furthermore, we found that lane-change from the slow lane to the fast lane would lead to higher speed variance value, which indicates a higher crash risk. The findings contribute to a better understanding on drivers’ natural driving behavior in freeway off-ramp areas and can provide important insight into road network design and safety management strategies

Enhancing Freeway Safety through Intervening in Traffic Flow Dynamics Based on Variable Speed Limit Control

New technologies and traffic data sources provide great potential to extend advanced strategies in freeway safety research. The High Definition Monitoring System (HDMS) data contribute comprehensive and precise individual vehicle information. This paper proposes an innovative Variable Speed Limit (VSL) based approach to manage crash risks by intervening in traffic flow dynamics on freeways using HDMS data. We first conducted an empirical analysis on real-time crash risk estimation using a binary logistic regression model. Then, intensive microscopic simulations based on AIMSUN were carried out to explore the effects of various intervention strategies with respect to a 3-lane freeway stretch in China. Different speed limits with distinct compliance rates under specified traffic conditions have been simulated. By taking into account the trade-off between safety benefits and delay in travel time, the speed limit strategies were optimized under various traffic conditions and the model with gradient feedback produces more satisfactory performance in controlling real-time crash risks. Last, the results were integrated into lane management strategies. This research can provide new ideas and methods to reveal the freeway crash risk evolution and active traffic management. Document type: Articl

Microplastics alter soil structure and microbial community composition

Microplastics (MPs), including conventional hard-to-biodegrade petroleum-based and faster biodegradable plant-based ones, impact soil structure and microbiota in turn affecting the biodiversity and functions of terrestrial ecosystems. Herein, we investigated the effects of conventional and biodegradable MPs on aggregate distribution and microbial community composition in microhabitats at the aggregate scale. Two MP types (polyethylene (PE) and polylactic acid (PLA) with increasing size (50, 150, and 300 μm)) were mixed with a silty loam soil (0–20 cm) at a ratio of 0.5 % (w/w) in a rice–wheat rotation system in a greenhouse under 25 °C for one year. The effects on aggregation, bacterial communities and their co-occurrence networks were investigated as a function of MP aggregate size. Conventional and biodegradable MPs generally had similar effects on soil aggregation and bacterial communities. They increased the proportion of microaggregates from 17 % to 32 %, while reducing the macroaggregates from 84 % to 68 %. The aggregate stability decreased from 1.4 mm to 1.0–1.1 mm independently of MP size due to the decline in the binding agents gluing soil particles (e.g., microbial byproducts and proteinaceous substances). MP type and amount strongly affected the bacterial community structure, accounting for 54 % of the variance. Due to less bioavailable organics, bacterial community composition within microaggregates was more sensitive to MPs addition compared to macroaggregates. Co-occurrence network analysis revealed that MPs exacerbated competition among bacteria and increased the complexity of bacterial networks. Such effects were stronger for PE than PLA MPs due to the higher persistence of PE in soils. Proteobacteria, Bacteroidetes, Chloroflexi, Actinobacteria, and Gemmatimonadetes were the keystone taxa in macroaggregates, while Actinobacteria and Chloroflexi were the keystone taxa in microaggregates. Proteobacteria, Actinobacteria, and Chloroflexi were the most sensitive bacteria to MPs addition. Overall, both conventional and biodegradable MPs reduced the portion of large and stable aggregates, altering bacterial community structures and keystone taxa, and consequently, the functions

Lunar meteorites: witnesses of the composition and evolution of the Moon

Lunar meteorites are fragments of the Moon that escaped the gravity of the Moon following high-energy impacts by asteroids, subsequently fell to Earth. An inventory of 165 lunar meteorites has been developed since the discovery and identification of the first lunar meteorite, ALHA 81005, in 1979. Although the Apollo samples are much heavier in mass than lunar meteorites, the meteorites are still an important sample supplement for scientific research on the composition and history of the Moon. Apart from a small amount of unbrecciated crystalline rocks, the majority of lunar meteorites are breccias that can be classified into three groups: highland feldspathic breccia, mare basaltic breccia, and mingled(including fledspathic and basaltic clasts) breccia. The petrography of lunar rocks suggests that there are a series of rock types of anorthosite, basalt, gabbro, troctolite, norite and KREEP in the Moon. Although KREEP is rare in lunar rocks, KREEP components have been found in the increasing number of lunar meteorites. KREEP provides important information on lunar magmatic evolution, e.g., the VHK KREEP clasts in SaU 169 may represent the pristine lunar magma (urKREEP). Six launching pairs of lunar meteorites have been proposed now, along with ten possible lunar launching sites. In addition, symplectite is often found in lunar basalts, which is a significant record of shock metamorphism on the lunar surface. Furthermore, isotopic ages and noble gases not only provide information on crystallization processes in lunar rocks and the formation of lunar crust, but also provide insight into shock events on the lunar surface

Meteorite classification for building the Chinese Antarctic Meteorite Depository—Introduction of the classification of 500 Grove Mountains meteorites

Meteorites provide an important window into the origins and evolution of the solar system. Since the first four meteorites were recovered in Grove Mountains, Antarctica, in 1998, a further total of 12665 meteorites have been collected over seven polar seasons in the Grove Mountains. All of these meteorites are owned and managed by the Chinese Antarctic Meteorite Depository (CAMD) at the Polar Research Institute of China (PRIC). In recent years, another 500 Antarctic meteorites have been classified and characterized based on mineralogy and petrology. In this work we examine four samples that have been identified as terrestrial, and a further 496 samples that have been confirmed as meteorites. These meteorites are further divided into different types:488 ordinary chondrites, one eucrite, one ureilite, one CM2 carbonaceous chondrite, one EH4 enstatite chondrite, one mesosiderite and three iron meteorites. The classification of meteorites not only provides an abundance of fundamental scientific data, but is also significant for introducing meteorites and related scientific knowledge to the public, particularly via the website of Chinese Resource-sharing Platform of Polar Samples for scientific research and education

Whole-genome sequencing and comparative genome analysis of Xanthomonas fragariae YM2 causing angular leaf spot disease in strawberry

BackgroundAngular leaf spot disease caused by plant pathogenic bacterium Xanthomonas fragariae seriously threatens strawberry crop production globally.MethodsIn this study, we sequenced the whole genome of X. fragariae YM2, isolated from Yunnan Province, China. In addition, we performed a comparative genome analysis of X. fragariae YM2 with two existing strains of X. fragariae YL19 and SHQP01 isolated from Liaoning and Shanghai, respectively.ResultsThe results of Nanopore sequencing showed that X. fragariae YM2 comprises one single chromosome with a contig size of 4,263,697 bp, one plasmid contig size of 0.39 Mb, a GC content ratio of 62.27%, and 3,958 predicted coding genes. The genome of YM2 comprises gum, hrp, rpf, and xps gene clusters and lipopolysaccharide (LPS), which are typical virulence factors in Xanthomonas species. By performing a comparative genomic analysis between X. fragariae strains YM2, YL19, and SHQP01, we found that strain YM2 is similar to YL19 and SHQP01 regarding genome size and GC contents. However, there are minor differences in the composition of major virulence factors and homologous gene clusters. Furthermore, the results of collinearity analysis demonstrated that YM2 has lower similarity and longer evolutionary distance with YL19 and SHQP01, but YL19 is more closely related to SHQP01.ConclusionsThe availability of this high-quality genetic resource will serve as a basic tool for investigating the biology, molecular pathogenesis, and virulence of X. fragariae YM2. In addition, unraveling the potential vulnerabilities in its genetic makeup will aid in developing more effective disease suppression control measures