Fairclothhong2012

Accurate identification of pedestrian crossing intention is of great significance to the safe and efficient driving of future fully automated vehicles in the city. This paper focuses on pedestrian intention recognition on the basis of pedestrian detection and tracking. A large number of natural crossing sequence data of pedestrians and vehicles are first collected by a laser scanner and HD camera, then 1980 effective crossing samples of pedestrians are selected. Influencing parameter sets of pedestrian crossing intention are then obtained through statistical analysis. Finally, long short-term memory network with attention mechanism (AT-LSTM) model is proposed. Compared with the support vector machine (SVM) model, results show that when the pedestrian crossing intention is recognized 0 s prior to crossing, the recognition accuracy of the AT-LSTM model for pedestrian crossing intention is 96.15%, which is 6.07% higher than that of SVM model; when the pedestrian crossing intention is recognized 0.6 s prior, the recognition accuracy of AT-LSTM model is 90.68%, which is 4.85% higher than that of the SVM model. The determination of pedestrian crossing intention parameter set and the more accurate recognition of pedestrian intention provided in this work provide a foundation for future fully automated driving vehicles.Here, a nanofiber-exfoliated bacteria cellulose aerogel with improved water affinity and high mass transfer was synthesized. Consequently, poly Schiff base can be uniformly coated within the body of bacteria cellulose aerogel without the traditional dispersion treatment. The composite aerogel has adequate mechanical and thermal stability and high mass transfer efficiency. Such an aerogel can serve as a superior adsorbent for flow through adsorption of pollution. Typically, the adsorption capacity towards Cr(VI), Cu(II), Re(VII), Conga red, and Orange G reaches as high as 321.5, 256.4, 153.8, 333.3, and 370.3 mg g-1, respectively. Moreover, the adsorption by this composite aerogel is very fast, such that, for example, at just 2 s, the adsorption is almost finished with Cr(VI) adsorption. Moreover, the composite aerogel exhibits a good adsorption-desorption capability. This research will hopefully shed light on the preparation of bacteria cellulose-derived macroscopic materials powerful in not only environmental areas, but also other related applications.This paper proposes a new, robust time-delay cooperative adaptive cruise control (CACC) approach for vehicle platooning systems with uncertain dynamics and varying communication delay. The uncertain CACC models with perturbed parameters are used to describe the uncertain dynamics of the vehicle platooning system. By combining the constant time headway strategy and predecessor-following communication topology, a set of robust delay feedback controllers is designed for the uncertain vehicle platoon with varying communication delay. Then, the set of CACC controllers is computed by solving some linear matrix inequalities, which further establish the robust (string) stability of the uncertain platooning system with the varying communication delay. The co-simulation experiment of CarSim and Simulink with a group of a seven-car platoons and varying velocity is used to demonstrate the effectiveness of the presented method.Intelligent methods have long been researched in fault diagnosis. Traditionally, feature extraction and fault classification are separated, and this process is not completely intelligent. In addition, most traditional intelligent methods use an individual model, which cannot extract the discriminate features when the machines work in a complex condition. To overcome the shortcomings of traditional intelligent fault diagnosis methods, in this paper, an intelligent bearing fault diagnosis method based on ensemble sparse auto-encoders was proposed. Three different sparse auto-encoders were used as the main architecture. To improve the robustness and stability, a novel weight strategy based on distance metric and standard deviation metric was employed to assign the weights of three sparse auto-encodes. Softmax classifier is used to classify the fault types of integrated features. The effectiveness of the proposed method is validated with extensive experiments, and comparisons with the related methods and researches on the widely-used motor bearing dataset verify the superiority of the proposed method. The results show that the testing accuracy and the standard deviation are 99.71% and 0.05%.For efficient and effective energy management, accurate energy consumption forecasting is required in energy management systems (EMSs). Recently, several artificial intelligence-based techniques have been proposed for accurate electric load forecasting; moreover, perfect energy consumption data are critical for the prediction. However, owing to diverse reasons, such as device malfunctions and signal transmission errors, missing data are frequently observed in the actual data. Previously, many imputation methods have been proposed to compensate for missing values; however, these methods have achieved limited success in imputing electric energy consumption data because the period of data missing is long and the dependency on historical data is high. In this study, we propose a novel missing-value imputation scheme for electricity consumption data. The proposed scheme uses a bagging ensemble of multilayer perceptrons (MLPs), called softmax ensemble network, wherein the ensemble weight of each MLP is determined by a softmax function. This ensemble network learns electric energy consumption data with explanatory variables and imputes missing values in this data. To evaluate the performance of our scheme, we performed diverse experiments on real electric energy consumption data and confirmed that the proposed scheme can deliver superior performance compared to other imputation methods.Although refill adherence measures (RAMs) are widely reviewed on their use among adult patients, existing reviews on adherence among children have only focused on self-report measures and electronic monitoring. Hence, this systematic review aims to examine the use of RAMs and their association with economic, clinical, and humanistic outcomes (ECHO) among pediatric patients. A literature search was conducted in Pubmed, Embase, CINAHL, and PsycINFO. Studies published in English involving subjects aged ≤18 years were included if RAMs were analyzed with ECHO. Of the 35 included studies, the majority (n = 33) were conducted in high-income countries. Asthma was the most common condition (n = 9) studied. Overall, 60.6% of 33 clinical outcomes reported among 22 studies was positive (improved clinical outcomes with improved adherence), while 21.9% of 32 economic outcomes reported among 16 studies was positive (reduced healthcare utilization or cost outcomes with improved adherence). Only four studies evaluated the relationship of adherence with 11 humanistic outcomes, where the majority (72.7%) were considered unclear. RAMs are associated with ECHO and can be considered for use in the pediatric population. Future studies could explore the use of RAMs in low-income countries, and the association of RAMs with quality of life.miR-371a-3p is currently the most informative reported biomarker for germ cell tumors (GCTs). Another developmental-related biomarker, CRIPTO, is involved in the regulation of pluripotency and germ cell fate commitment. We aimed to assess the value of CRIPTO as a diagnostic and prognostic biomarker of testicular GCTs (TGCTs) and also to assess its presence in seminal plasma samples, compared with miR-371a-3p. In total, 217 and 94 serum/seminal plasma samples were analyzed. CRIPTO was quantified using ELISA and miR-371a-3p using bead-based isolation followed by RT-qPCR. Methylation profiling (EPIC array) for the CRIPTO promoter region was undertaken in 35 TGCT tissues plus four (T)GCT cell lines. Androgen Receptor Antagonist datasheet Significantly higher CRIPTO concentration was found in sera of non-seminomas compared to controls (p = 0.0297), and in stage II/III disease compared to stage I (p = 0.0052, p = 0.0097). CRIPTO concentration was significantly positively correlated with miR-371a-3p levels in serum (r = 0.16) and seminal plasma (r = 0.40). CRIPTO/miR-371a-3p levels were significantly higher in seminal plasma controls when compared to serum controls (p = 0.0001, p less then 0.0001). CRIPTO/miR-371a-3p were detected both in normospermic and azoospermic males, and levels were higher in TGCTs compared to GCNIS-only. We have provided the largest dataset of evaluation of CRIPTO in serum and seminal plasma of GCTs, showing its potential value as a biomarker of the disease.Inflammation-induced processes commence with the activation of signalling pathways at the cellular level, which mobilize inflammatory cells and stimulate the secretion of chemokines, cytokines, and damage-associated molecular pattern molecules (DAMPs). Physical effort stimulates inflammation, contributing to muscle repair and regeneration. We have examined the impact of different protocols of progressive-effort tests on T-cell DAMP levels, extracellular cleavage products (fibronectin and hyaluronan), and Th-cell-related cytokine levels among soccer players. Thirty male soccer players with a median age of 17 (16-22) years performed different defined protocols for progressive exercise until exhaustion (1) YO-YO intermittent recovery test level 1 (YYRL1, n = 10); (2) maximal multistage 20 m shuttle run (Beep, n = 10); and mechanical treadmill (MT, n = 10); and (3) shuttle-run test (n = 10). Blood samples were taken three times as follows at baseline, post effort, and in recovery. Significantly higher post-effort concentrations of IL-4, IL-6, IL-10, and IFN-γ were observed in the Beep group, IL-4 in the YYRL1 group, and IL-6 and IFN-γ in the MT group as compared with the baseline values. Recovery values were significantly higher for concentrations of IL-4, IL-10, and IFN-γ in the YYRL1 group, only for IFN-γ in the Beep group, and for IL-6, IL-10, and INF-γ in the MT group as compared with the baseline values. Post-effort concentrations of DEFβ2, Hsp27, Fn, and UA in the Beep group and Hsp27 and HA in the YYRL1 group were significantly higher as compared with the baseline values. It seems the performed efficiency test protocols caused a short-term imbalance in Th1/Th2 cytokine levels without giving common molecular patterns. The rapidity of these changes was apparently related to specific physical movements and the type of running surface.BACKGROUND Atherosclerotic cardiovascular disease (ASCVD) is a preventable type of disease, thus, specifying factors that increase the occurrence of this type of disease is needed. Heavy metals such as cadmium (Cd), lead (Pb), and mercury (Hg) have been suggested as possible factors influencing the development of cardiovascular disease. We aimed to link blood heavy metal levels (Cd, Pb, Hg) with 10-year ASCVD risk scores. METHODS A population of 993 men and 1431 women who participated in the Korea National Health and Nutrition Examination Survey (KNHANES) were included. The 2013 American College of Cardiology/American Heart Association (ACC/AHA) pooled cohort equations risk prediction model and Korean Risk Prediction Model (KRPM) were used as means for risk prediction. Following multivariate adjustment; blood Cd; Pb; and Hg levels were divided into quartiles for analysis using linear trends estimation and multiple regression models. RESULTS There was an overall positive trend between blood Cd, Pb, and Hg levels and 10-year ASCVD risk scores; KRPM risk score increasing by quartile for blood Cd (men p less then 0.