Semi-automatic Data Annotation System for Multi-Target Multi-Camera Vehicle Tracking

Multi-target multi-camera tracking (MTMCT) plays an important role in intelligent video analysis, surveillance video retrieval, and other application scenarios. Nowadays, the deep-learning-based MTMCT has been the mainstream and has achieved fascinating improvements regarding tracking accuracy and efficiency. However, according to our investigation, the lacking of datasets focusing on real-world application scenarios limits the further improvements for current learning-based MTMCT models. Specifically, the learning-based MTMCT models training by common datasets usually cannot achieve satisfactory results in real-world application scenarios. Motivated by this, this paper presents a semi-automatic data annotation system to facilitate the real-world MTMCT dataset establishment. The proposed system first employs a deep-learning-based single-camera trajectory generation method to automatically extract trajectories from surveillance videos. Subsequently, the system provides a recommendation list in the following manual cross-camera trajectory matching process. The recommendation list is generated based on side information, including camera location, timestamp relation, and background scene. In the experimental stage, extensive results further demonstrate the efficiency of the proposed system.Comment: 9 pages, 10 figure

Modeling habitat suitability for Yunnan Snub-nosed monkeys in Laojun Mountain National Park

We provide new information on Yunnan snub-nosed monkey (Rhinopithecus bieti) behavioral ecology, contributing to future conservation efforts within the Laojun Mountain National Park. Habitat evaluation procedures are used to quantify the value of land as a habitat for a species. We analyzed environmental variables hypothesized to influence habitat suitability for Yunnan snub-nosed monkeys, and mapped the distribution of suitable habitats across the study area and adjacent areas. Spatial analysis with GPS data was conducted to investigate home-range change of these monkeys. Predictor variables were generated using ArcMap and R programming language. We prepared 34 environmental variables at 30-m spatial resolution. Maxent was used to analyze environmental variables that contributed to suitability. Using satellite remote sensing and GIS, we modeled the distribution of suitable habitat for Yunnan snub-nosed monkeys in the Jinsichang area of the Laojun Mountains in China. This study did not describe the frequency or intensity of habitat use. Habitat suitability was affected by several variables, the most influential, as determined by permutation importance, being mean diurnal temperature range (31.6%), precipitation during the wettest quarter of the year (30.4%), average annual precipitation (17%), normalized difference vegetation index (5%), wetness (4.6%), and aspect (4.5%). This habitat suitability model provides information about the current distribution of Yunnan snub-nosed monkeys, which is important for appropriate implementation of conservation actions

Transcription factor EB (TFEB) improves ventricular remodeling after myocardial infarction by inhibiting Wnt/β-catenin signaling pathway

Background Adverse left ventricular remodeling after myocardial infarction (MI) compromises cardiac function and increases heart failure risk. Until now, comprehension of the role transcription factor EB (TFEB) plays after MI is limited. Objectives The purpose of this study was to describe the effects of TFEB on fibroblasts differentiation and extracellular matrix expression after MI. Methods AAV9 (adeno-associated virus) mediated up- and down-regulated TFEB expressions were generated in C57BL/6 mice two weeks before the MI modeling. Echocardiography, Masson, Sirius red staining immunofluorescence, and wheat germ agglutinin staining were performed at 3 days, and 1, 2, and 4 weeks after MI modeling. Fibroblasts collected from SD neonatal rats were transfected by adenovirus and siRNA, and cell counting kit-8 (CCK8), immunofluorescence, wound healing and Transwell assay were conducted. Myocardial fibrosis-related proteins were identified by Western blot. PNU-74654 (100 ng/mL) was used for 12 hours to inhibit β-catenin-TCF/LEF1 complex. Results The up-regulation of TFEB resulted in reduced fibroblasts proliferation and its differentiation into myofibroblasts in vitro studies. A significant up-regulation of EF and down-regulation of myocyte area was shown in the AAV9-TFEB group. Meanwhile, decreased protein level of α-SMA and collagen I were observed in vitro study. TFEB didn’t affect the concentration of β-catenin. Inhibition of TFEB, which promoted cell migration, proliferation and collagen I expression, was counteracted by PNU-74654. Conclusions TFEB demonstrated potential in restraining fibrosis after MI by inhibiting the Wnt/β-catenin signaling pathway