Experimental Study on Unidirectional Pedestrian Descending and Ascending Stair With a Fixed Obstacle

Staircase is one of the most essential vertical passageway for pedestrians’ timely evacuation, and has distinct constraint on pedestrians’ movement characteristics when compared with corridors and hallways. During evacuation, temporary obstacles can be observed on stairs, e.g., the abruptly stopped pedestrians or the luggage of pedestrians discarded. It is noticed that studies on the effect of obstacles on pedestrian dynamics mainly focused on planar locomotion, the impact of obstacle on the movement characteristics of pedestrians ascending and descending stairs have not been systematically studied yet. Therefore, in this study, a series of unidirectional pedestrian avoid obstacle movement experiments on staircase under controlled laboratory conditions were performed. The avoidance characteristic of pedestrians is observed from trajectory diagram. Target drift angle towards left and right is further calculated and analyzed. The study found that target drift angle curve occur to relatively large fluctuations to avoid obstacle of a pedestrian rather than not appear to obvious variety to avoid obstacle of a suitcase. Meanwhile, the change trend of target drift angle towards left and right for scenarios S3 and S4 is consistent with results of scenarios S1 and S2. Then, an interesting discovery indicates that the pedestrians will accelerate after passing obstacles whether it is ascending process or descending process. Finally, the obstacle of a pedestrian will accelerate the movement efficiency in ascending process from results of flow rates, but the result is contrary to that of descending process. The systematic experimental data can not only be used for the verification and validation of pedestrian models but also can provide a benchmark for the design of related facilities aiming at improving traffic efficiency

Cardinal Optimizer (COPT) User Guide

Cardinal Optimizer is a high-performance mathematical programming solver for efficiently solving largescale optimization problem. This documentation provides basic introduction to the Cardinal Optimizer

HLT-MT: High-resource Language-specific Training for Multilingual Neural Machine Translation

Multilingual neural machine translation (MNMT) trained in multiple language pairs has attracted considerable attention due to fewer model parameters and lower training costs by sharing knowledge among multiple languages. Nonetheless, multilingual training is plagued by language interference degeneration in shared parameters because of the negative interference among different translation directions, especially on high-resource languages. In this paper, we propose the multilingual translation model with the high-resource language-specific training (HLT-MT) to alleviate the negative interference, which adopts the two-stage training with the language-specific selection mechanism. Specifically, we first train the multilingual model only with the high-resource pairs and select the language-specific modules at the top of the decoder to enhance the translation quality of high-resource directions. Next, the model is further trained on all available corpora to transfer knowledge from high-resource languages (HRLs) to low-resource languages (LRLs). Experimental results show that HLT-MT outperforms various strong baselines on WMT-10 and OPUS-100 benchmarks. Furthermore, the analytic experiments validate the effectiveness of our method in mitigating the negative interference in multilingual training.Comment: 7 pages, 7 figures, IJCAI-ECAI 202

AdaptivePose++: A Powerful Single-Stage Network for Multi-Person Pose Regression

Multi-person pose estimation generally follows top-down and bottom-up paradigms. Both of them use an extra stage ($\boldsymbol{e.g.,}$ human detection in top-down paradigm or grouping process in bottom-up paradigm) to build the relationship between the human instance and corresponding keypoints, thus leading to the high computation cost and redundant two-stage pipeline. To address the above issue, we propose to represent the human parts as adaptive points and introduce a fine-grained body representation method. The novel body representation is able to sufficiently encode the diverse pose information and effectively model the relationship between the human instance and corresponding keypoints in a single-forward pass. With the proposed body representation, we further deliver a compact single-stage multi-person pose regression network, termed as AdaptivePose. During inference, our proposed network only needs a single-step decode operation to form the multi-person pose without complex post-processes and refinements. We employ AdaptivePose for both 2D/3D multi-person pose estimation tasks to verify the effectiveness of AdaptivePose. Without any bells and whistles, we achieve the most competitive performance on MS COCO and CrowdPose in terms of accuracy and speed. Furthermore, the outstanding performance on MuCo-3DHP and MuPoTS-3D further demonstrates the effectiveness and generalizability on 3D scenes. Code is available at https://github.com/buptxyb666/AdaptivePose.Comment: Submit to IEEE TCSVT; 11 pages. arXiv admin note: text overlap with arXiv:2112.1363

Efficient Structure Slimming for Spiking Neural Networks

Spiking neural networks (SNNs) are deeply inspired by biological neural information systems. Compared to convolutional neural networks (CNNs), SNNs are low power consumption because of their spike based information processing mechanism. However, most of the current structures of SNNs are fully-connected or converted from deep CNNs which poses redundancy connections. While the structure and topology in human brain systems are sparse and efficient. This paper aims at taking full advantage of sparse structure and low power consumption which lie in human brain and proposed efficient structure slimming methods. Inspired by the development of biological neural network structures, this paper designed types of structure slimming methods including neuron pruning and channel pruning. In addition to pruning, this paper also considers the growth and development of the nervous system. Through iterative application of the proposed neural pruning and rewiring algorithms, experimental evaluations on CIFAR-10, CIFAR-100, and DVS-Gesture datasets demonstrate the effectiveness of the structure slimming methods. When the parameter count is reduced to only about 10% of the original, the performance decreases by less than 1%

A General SIMD-based Approach to Accelerating Compression Algorithms

Compression algorithms are important for data oriented tasks, especially in the era of Big Data. Modern processors equipped with powerful SIMD instruction sets, provide us an opportunity for achieving better compression performance. Previous research has shown that SIMD-based optimizations can multiply decoding speeds. Following these pioneering studies, we propose a general approach to accelerate compression algorithms. By instantiating the approach, we have developed several novel integer compression algorithms, called Group-Simple, Group-Scheme, Group-AFOR, and Group-PFD, and implemented their corresponding vectorized versions. We evaluate the proposed algorithms on two public TREC datasets, a Wikipedia dataset and a Twitter dataset. With competitive compression ratios and encoding speeds, our SIMD-based algorithms outperform state-of-the-art non-vectorized algorithms with respect to decoding speeds

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

Mechanism of chip formation and surface-defects in orthogonal cutting of soft-brittle potassium dihydrogen phosphate crystals

Micromachining repair of surface defects on KH2PO4 (KDP) optics is an emerging technique in the construction of Inertial Confinement Fusion facilities for obtaining clean nuclear fusion energy. However, this method is yet facing considerable challenges owing to the soft-brittle nature of single-crystal KDP, hence it is necessary to understand its ductile-regime cutting mechanism to generate crack-free surfaces. This paper seeks to investigate the evolution of different cutting mechanism with the change of uncut chip thickness (UCT) in KDP orthogonal cutting processes. A transition of cutting modes from plastic cutting to shear-crack cutting and then fracture cutting with the rise of UCT has been revealed. To explain these cutting phenomena, a novel theoretical model was proposed by calculating the specific energy dissipation for crack/fracture propagations during cutting processes based on fracture mechanics. This analytical model was well validated by the analysis of cutting forces and machined surface quality. Nevertheless, three kinds of surface defects have been observed, i.e. micro pits, micro craters and edge chipping. These surface defects were caused by tearing and spalling of materials with elastic recovery, crack propagation along cleavage planes with ploughing effect, and the peeling away of large-size fracture, respectively. The presented results of great significance for promoting the application of micromachining processes in future engineering repair of KDP optics

Tumor cells-derived exosomal PD-L1 promotes the growth and invasion of lung cancer cells <em>in vitro via</em> mediating macrophages M2 polarization

Lung cancer originating from the bronchial epithelium is the most common lung malignancy. It has been reported that programmed cell death 1 ligand 1 (PD-L1) and tumor-associated macrophages are closely related to the development of lung cancer. However, whether tumor-derived exosomal PD-L1 could mediate the regulation of macrophage polarization in lung cancer remains unclear. For this research, the level of PD-L1 in normal tissues and lung cancer tissues was evaluated using RT-qPCR. Next, the apoptosis of lung cancer cells was evaluated using flow cytometry assay. Then, the structure and morphology of vesicles were observed using transmission electron microscopy and nanoparticle tracking analysis. Later on, the internalization of exosomes by macrophage was observed using fluorescence microscopy. Our results showed that the level of PD-L1 was upregulated in tumor tissues and lung cancer cells. Knockdown of PD-L1 notably inhibited the viability, migration and invasion of lung cancer cells. In addition, lung cancer cells-derived exosomal PD-L1 could be absorbed by macrophages. Meanwhile, exosomal PD-L1 was able to promote macrophages M2 polarization. Moreover, macrophages M2 polarization induced by exosomal PD-L1 further remarkably promoted the viability, migration, invasion, and epithelial-mesenchymal transition process of lung cancer cells. Collectively, knockdown of PD-L1 notably inhibited the viability, migration and invasion of lung cancer cells. Tumor cell-derived exosomal PD-L1 could promote the growth of lung cancer cells by mediating macrophages M2 polarization. Thus, inhibiting macrophages M2 polarization might be a promoting therapy for the treatment of lung cancer

Morphological characterization and reconstruction of fractured heat-treated glass

Fracture morphology has insightful information related to the residual effect of fractured structural glass, which is vital in assessing the post-fracture performance of glass members. This study experimentally characterized the fracture morphology of heat-treated glass and developed a novel method of morphology reconstruction, which aims to facilitate the numerical analysis of fractured structural glass. With the development of a computer-vision-based method for transparent objects, the morphology information from fragmentation tests was extracted and systematically investigated for monolithic heat-treated glass with various thicknesses, surface compressive stresses and fracture initiation locations, which are considered as the key influencing factors of heat-treated glass fracture. The geometrical features of fragments and their spatial distribution were quantitatively analysed, identifying their correlations with glass properties. The result indicates that the distribution of fragment centroids shows greater dispersion as the tempering level increases, and the fragments tend to be smaller and more rounded. The strain energy release at fracture was also assessed by fracture patterns, showing it presents high sensitivity to the glass thickness and surface compressive stress. Subsequently, a novel approach was proposed for the stochastic reconstruction of fracture morphology, combining feature points distribution and Voronoi tessellation concept. The control parameters are determined by data from the fragmentation tests and the influence of fracture load could be properly considered. The proposed method shows satisfactory outcomes and good agreement with the experimental records, which has further potential in developing refined numerical models by considering more realistic fracture morphology of glass members