DIVOTrack: A Novel Dataset and Baseline Method for Cross-View Multi-Object Tracking in DIVerse Open Scenes

Cross-view multi-object tracking aims to link objects between frames and camera views with substantial overlaps. Although cross-view multi-object tracking has received increased attention in recent years, existing datasets still have several issues, including 1) missing real-world scenarios, 2) lacking diverse scenes, 3) owning a limited number of tracks, 4) comprising only static cameras, and 5) lacking standard benchmarks, which hinder the investigation and comparison of cross-view tracking methods. To solve the aforementioned issues, we introduce DIVOTrack: a new cross-view multi-object tracking dataset for DIVerse Open scenes with dense tracking pedestrians in realistic and non-experimental environments. Our DIVOTrack has ten distinct scenarios and 550 cross-view tracks, surpassing all cross-view multi-object tracking datasets currently available. Furthermore, we provide a novel baseline cross-view tracking method with a unified joint detection and cross-view tracking framework named CrossMOT, which learns object detection, single-view association, and cross-view matching with an all-in-one embedding model. Finally, we present a summary of current methodologies and a set of standard benchmarks with our DIVOTrack to provide a fair comparison and conduct a comprehensive analysis of current approaches and our proposed CrossMOT. The dataset and code are available at https://github.com/shengyuhao/DIVOTrack

Identification of a peripheral blood long non-coding RNA (Upperhand) as a potential diagnostic marker of coronary artery disease

Background: Long non-coding RNAs (lncRNAs) have been confirmed to be involved in the pathologi­cal processes of multiple diseases. However, the characteristic expression of lncRNAs in peripheral blood of coronary artery disease (CAD) patients and whether some of these lncRNAs can be used as diagnostic biomarkers for CAD requires further investigation. Methods: Six healthy and CAD individuals were selected for microarray analysis, and 5 differentially expressed lncRNAs were selected and confirmed in the second cohort consisting of 30 control individu­als and 30 CAD patients with different SYNTAX scores. Upperhand were verified in the third cohort consisting of 115 controls and 137 CAD patients. Results: Thirty one lncRNAs were differentially expressed between the two groups, among whom, 25 were upregulated in the CAD group and 6 were downregulated. Four of the selected five lncRNAs were significantly upregulated in the CAD group, and Upperhand had the largest area under the curve (AUC). The diagnostic value of Upperhand was tested further, and it remained having a high diagnostic value. Conclusions: The expression level of Upperhand in peripheral blood of CAD patients is significantly higher than in control individuals, and is correlated with severity of CAD. Upperhand is a potential diagnostic biomarker of CAD, and when combined with TCONS_00029157, diagnostic value slightly increased

Reutilizing Waste Iron Tailing Powders as Filler in Mortar to Realize Cement Reduction and Strength Enhancement

Recently, the massive accumulation of waste iron tailings powder (WITP) has resulted in significant environmental pollution. To solve this problem, this paper proposes an original mortar replacement (M) method to reuse waste solids and reduce cement consumption. In the experiment, the author employed an M method which replaces water, cement, and sand with WITP under constant water/cement and found that the strength development can be significantly improved. Specifically, a mortar with 20% WITP replacement can obtain a 30.95% improvement in strength development. To study the internal mechanism, we performed experiments such as thermogravimetric analysis (TGA), mercury intrusion porosimetry (MIP), and SEM. The results demonstrate that the nucleation effect and pozzolanic effect of WITP can help promote cement hydration, and MIP reveals that WITP can effectively optimize pore structure. In addition, 1 kg 20% WITP mortar reduced cement consumption by 20%, which saves 19.98% of the economic cost. Comprehensively, our approach achieves the effective utilization of WITP and provides a favorable reference for practical engineering

Application of Extreme Gradient Boosting Based on Grey Relation Analysis for Prediction of Compressive Strength of Concrete

The prediction of concrete strength is an interesting point of investigation and could be realized well, especially for the concrete with the complex system, with the development of machine learning and artificial intelligence. Therefore, an excellent algorithm should put emphasis to receiving increased attention from researchers. This study presents a novel predictive system as follows: extreme gradient boosting (XGBoost) based on grey relation analysis (GRA) for predicting the compressive strength of concrete containing slag and metakaolin. One of its highlights is a feature selection methodology, i.e., GRA, which was used to determine the main input variables. Another highlight is that its performance was compared with the frequently used artificial neural network (ANN) and genetic algorithm-artificial neural network (GA-ANN) by using random dataset and the same testing datasets. For three same testing datasets, the average R2 values of ANN, GA-ANN, and XGBoost are 0.674, 0.829, and 0.880, respectively, indicating that XGBoost has the highest absolute fraction of variance (R2). XGBoost can provide best result by testing the root mean squared error (RMSE) and mean absolute percentage error (MAPE). The average RMSE values of ANN, GA-ANN, and XGBoost are 15.569 MPa, 10.530 MPa, and 9.532 MPa, respectively, and those of MAPE of ANN, GA-ANN, and XGBoost are 11.224%, 9.140%, and 8.718%, respectively. Thus, the XGBoost definitely performed better than the ANN and GA-ANN. Finally, a type of application software based on XGBoost was developed for practical applications. This vivid software interfaces could help users in prediction and easy and efficient analysis

Design of Reinforced Ribs for Spaceborne Parabolic Cylindrical Reflector Antenna Based on Topology Optimization and Parametric Analysis

The normal operation of spaceborne parabolic cylindrical reflector antennas under various operating conditions relies on maintaining the root mean square (RMS) of the reflector surface’s deformation within reasonable limits. In engineering practice, the designing of reinforced ribs is the primary way to control the RMS of the reflector surface. However, the layout and dimensions of reinforced ribs for many existing designs rely on the experience of the designer and lack a theoretical foundation. This leads to suboptimal layouts and dimensions in many designs, deviating from the optimal design. To address these concerns, this study proposes a comprehensive design approach that combines both topology optimization and parametric analysis. Optimization and parametric analysis were conducted for a large-sized spaceborne composite parabolic cylindrical reflector antenna. The layout and dimensions of the reinforced ribs were reconstructed based on the optimization results and parametric analysis. This study also obtained the influence of the height and thickness of the reinforced ribs on the RMS of the reflector surface. Subsequently, utilizing antenna temperature field simulations as thermal excitation inputs, finite element thermal distortion analyses were conducted for the reflector surfaces without reinforced ribs, with the original reinforced ribs designed based on empirical methods, and with optimized reinforced ribs. In comparison to the original design of the reinforced ribs, the optimized design, without an increase in the volume of the reinforced ribs, reduced the RMS of the reflector surface from 0.6025 mm to 0.5561 mm, resulting in an optimization ratio of 7.7%. Moreover, when compared to the reflector surface without reinforced ribs, the optimized design achieved a 17.9% reduction in RMS

Mitigating Autogenous Shrinkage of Alkali-Activated Slag Mortar by Using Porous Fine Aggregates as Internal Curing Agents

Alkali-activated slag (AAS) is beneficial for resource conservation in that it consumes little primary industrial energy, and it also performs well in terms of its mechanical properties and durability. However, its higher autogenous shrinkage compared to OPC mortars is a serious issue impeding AAS-based binder development for practical applications. This study investigated the feasibility and performance of active recycled aggregates when applied as man-made internal curing agents (MAs) for AAS mortars. They were applied as aggregate replacements for sand in this study to investigate the effects on the autogenous shrinkage, internal relative humidity (IRH), compressive strength, hydration properties and pore structure of AAS mortars. Three MAs with the sizes of 0.63–1.25 mm (MA 0.63), 1.25–2.5 mm (MA 1.25) and 2.5–4.75 mm (MA 2.5) were used. The results showed that MAs have potential as internal curing agents to mitigate the autogenous shrinkage of AAS mortars. When using saturated MAs, the autogenous shrinkage of AAS mortars was reduced by 87.68%. The addition of MAs also significantly prolonged the critical time taken for the IRH to start decreasing from 100%

Mitigating Autogenous Shrinkage of Alkali-Activated Slag Mortar by Using Porous Fine Aggregates as Internal Curing Agents

Alkali-activated slag (AAS) is beneficial for resource conservation in that it consumes little primary industrial energy, and it also performs well in terms of its mechanical properties and durability. However, its higher autogenous shrinkage compared to OPC mortars is a serious issue impeding AAS-based binder development for practical applications. This study investigated the feasibility and performance of active recycled aggregates when applied as man-made internal curing agents (MAs) for AAS mortars. They were applied as aggregate replacements for sand in this study to investigate the effects on the autogenous shrinkage, internal relative humidity (IRH), compressive strength, hydration properties and pore structure of AAS mortars. Three MAs with the sizes of 0.63–1.25 mm (MA 0.63), 1.25–2.5 mm (MA 1.25) and 2.5–4.75 mm (MA 2.5) were used. The results showed that MAs have potential as internal curing agents to mitigate the autogenous shrinkage of AAS mortars. When using saturated MAs, the autogenous shrinkage of AAS mortars was reduced by 87.68%. The addition of MAs also significantly prolonged the critical time taken for the IRH to start decreasing from 100%