Application-Driven AI Paradigm for Person Counting in Various Scenarios

Person counting is considered as a fundamental task in video surveillance. However, the scenario diversity in practical applications makes it difficult to exploit a single person counting model for general use. Consequently, engineers must preview the video stream and manually specify an appropriate person counting model based on the scenario of camera shot, which is time-consuming, especially for large-scale deployments. In this paper, we propose a person counting paradigm that utilizes a scenario classifier to automatically select a suitable person counting model for each captured frame. First, the input image is passed through the scenario classifier to obtain a scenario label, which is then used to allocate the frame to one of five fine-tuned models for person counting. Additionally, we present five augmentation datasets collected from different scenarios, including side-view, long-shot, top-view, customized and crowd, which are also integrated to form a scenario classification dataset containing 26323 samples. In our comparative experiments, the proposed paradigm achieves better balance than any single model on the integrated dataset, thus its generalization in various scenarios has been proved

A Unified Framework for Mutual Improvement of SLAM and Semantic Segmentation

This paper presents a novel framework for simultaneously implementing localization and segmentation, which are two of the most important vision-based tasks for robotics. While the goals and techniques used for them were considered to be different previously, we show that by making use of the intermediate results of the two modules, their performance can be enhanced at the same time. Our framework is able to handle both the instantaneous motion and long-term changes of instances in localization with the help of the segmentation result, which also benefits from the refined 3D pose information. We conduct experiments on various datasets, and prove that our framework works effectively on improving the precision and robustness of the two tasks and outperforms existing localization and segmentation algorithms.Comment: 7 pages, 5 figures.This work has been accepted by ICRA 2019. The demo video can be found at https://youtu.be/Bkt53dAehj

Variants in genes related to inflammation and endothelial function can increase the risk for carotid atherosclerosis in southwestern China

AimTo investigate the potential association between polymorphisms in genes involved in endothelial function, inflammation and carotid atherosclerosis.MethodsThis was a three-center, population-based sectional survey conducted in Sichuan province of southwestern China. We randomly selected 8 different communities in Sichuan, and the residents in each community volunteered to participate in the survey by face-to-face questionnaire. A total of 2,377 residents with high stroke risk population in the 8 communities were included. Carotid atherosclerosis was evaluated by carotid ultrasound, and the 19 single nucleotide polymorphisms (SNPs) in 10 endothelial function as well as inflammation relevant genes were measured in the high stroke risk population. Carotid atherosclerosis was defined by the presence of carotid plaque or any carotid stenosis ≥15% or mean intima-media thickness (IMT) > 0.9 mm. Generalized multifactor dimensionality reduction (GMDR) approach was used to analyze gene–gene interactions among the 19 SNPs.ResultsAmong the 2,377 subjects with high stroke risk, 1,028 subjects had carotid atherosclerosis (43.2%), of which 852 (35.8%) cases had carotid plaque, 295 (12.4%) cases had ≥15% carotid stenosis, whereas 445 (18.7%) had mean IMT > 0.9 mm. Multivariate logistic regression revealed that IL1A rs1609682 TT and HABP2 rs7923349 TT served as independent risk factors for carotid atherosclerosis (OR, 1.45, 95% CI: 1.034–2.032, p = 0.031, and OR, 1.829, 95% CI: 1.228–2.723, p = 0.003). GMDR analysis indicated that there was a significant gene–gene interaction found among IL1A rs1609682, ITGA2 rs1991013, and HABP2 rs7923349. After adjusting the covariates, the high-risk interactive genotypes in the 3 variants were significantly associated with a significantly higher risk for carotid atherosclerosis (OR, 2.08, 95% CI: 1.257–5.98, p < 0.001).ConclusionThe prevalence of carotid atherosclerosis was observed to be extremely high in the high-risk stroke population in southwestern China. There were associations observed between the specific variants in inflammation and endothelial function relevant genes and carotid atherosclerosis. The high-risk interactive genotypes among IL1A rs1609682, ITGA2 rs1991013, and HABP2 rs7923349 significantly increased the risk of carotid atherosclerosis. These results are expected to provide novel strategies for the prevention of carotid atherosclerosis. The gene–gene interactive analysis used in this study may be very helpful to elucidate complex genetic risk factors for carotid atherosclerosis

DDX60 Is Associated With Glioma Malignancy and Serves as a Potential Immunotherapy Biomarker

DDX60, an interferon (IFN)-inducible gene, plays a promotional role in many tumors. However, its function in glioma remains unknown. In this study, bioinformatic analysis (TCGA, CGGA, Rembrandt) illustrated the upregulation and prognostic value of DDX60 in gliomas. Immunohistochemical staining of clinical samples (n = 49) validated the DDX60 expression is higher in gliomas than in normal tissue (n = 20, P < 0.0001). It also could be included in nomogram as a parameter to predict the 3- and 5-year survival risk (C-index = 0.86). The biological process of DDX60 in glioma was mainly enriched in the inflammatory and immune response by GSEA and GO analysis. DDX60 expression had a positive association with most inflammatory-related functions, such as hematopoietic cell kinase (HCK) (R = 0.31), interferon (R = 0.72), STAT1 (R = 54), and a negative correlation with IgG (R = −0.24). Furthermore, DDX60 expression tends to be positively related to multiple infiltrating immune cells, while negatively related to CD56 dim nature killer cell in glioma. Some important immune checkpoints, like CTLA-4, PD-L1, EGF, CD96, and CD226, were all positively related with DDX60 (all Pearson correlation R > 0.26). The expression and correlation between DDX60, EGF, and PD-L1 were confirmed by western blot in clinical samples (n = 14, P < 0.0001) and GBM cells. These results indicated that DDX60 might have important clinical significance in glioma and could serve as a potential immune therapeutic target

GWAS Identifies Novel Susceptibility Loci on 6p21.32 and 21q21.3 for Hepatocellular Carcinoma in Chronic Hepatitis B Virus Carriers

Genome-wide association studies (GWAS) have recently identified KIF1B as susceptibility locus for hepatitis B virus (HBV)–related hepatocellular carcinoma (HCC). To further identify novel susceptibility loci associated with HBV–related HCC and replicate the previously reported association, we performed a large three-stage GWAS in the Han Chinese population. 523,663 autosomal SNPs in 1,538 HBV–positive HCC patients and 1,465 chronic HBV carriers were genotyped for the discovery stage. Top candidate SNPs were genotyped in the initial validation samples of 2,112 HBV–positive HCC cases and 2,208 HBV carriers and then in the second validation samples of 1,021 cases and 1,491 HBV carriers. We discovered two novel associations at rs9272105 (HLA-DQA1/DRB1) on 6p21.32 (OR = 1.30, P = 1.13×$10^{−19}$) and rs455804 (GRIK1) on 21q21.3 (OR = 0.84, P = 1.86×$10^{−8}$), which were further replicated in the fourth independent sample of 1,298 cases and 1,026 controls (rs9272105: OR = 1.25, P = 1.71×$10^{−4}$; rs455804: OR = 0.84, P = 6.92×$10^{−3}$). We also revealed the associations of HLA-DRB1*0405 and 0901*0602, which could partially account for the association at rs9272105. The association at rs455804 implicates GRIK1 as a novel susceptibility gene for HBV–related HCC, suggesting the involvement of glutamate signaling in the development of HBV–related HCC

Exposure of Elderly People to Indoor Air Pollutants in Wanxia Nursing Home

The elderly residing in nursing homes are typically more advanced in age, have more health issues, and spend more time indoors than other elderly people. This study explored the indoor air quality in the Wanxia nursing home, the largest private nursing home in Chengdu, China, based on long-term measurement data. Air pollutant sensors measured the level of air pollution in the Wanxia nursing home from March 2021 to February 2022. This study obtained several important results: (1) The indoor air quality index (IAQI) of the Wanxia nursing home was at a low pollution level in spring, summer, and autumn, and at a moderate pollution level in winter. PM concentration played the most important role in determining indoor air quality; (2) During winter, the 24 h mean indoor concentrations of PM2.5 and PM10 were close to or even exceeded the standard limits. During winter and summer nights, indoor CO2 levels were very close to or greater than 1000 ppm. During spring and summer nights, the indoor TVOC concentrations exceeded the limit (0.45 mg/m3); (3) Apart from HCHO concentrations in autumn, the levels of other indoor air pollutants were significantly influenced by their outdoor levels. In addition, the seasonal indoor/outdoor (I/O) ratios of CO2 and TVOCs exceeded 1; and (4) Indoor CO2 levels were closely related to indoor temperature (Ta) and relative humidity (RH) in each season. PM10 concentration correlated with Ta and RH in summer, while PM2.5 concentration did not correlate with Ta and RH in winter. The indoor TVOC level positively correlated with RH. Lastly, the indoor HCHO level was minimally influenced by changes in Ta and RH. Due to the above results, this study proposes targeted strategies for improving indoor air quality in nursing homes

Quantitative Evaluation of Leaf Morphology with Different Rice Genotypes Based on Image Processing

Prostrate growth 1 (PROG1) gene is vital in controlling the prostrate growth habit of rice. Studying the effect of PROG1 gene on rice canopy structure is crucial in elucidating the molecular mechanism of rice plant type evolution. Herein, the morphological characteristics of different rice genotypes were collected at different growth stages and leaf nodes using image processing techniques. The morphological characteristics included leaf length, leaf width, and leaf area. The image processing techniques involved boundary mean oscillation (BMO) filtering and minimum bounding rectangle extraction of the target image. On this basis, the effect of the PROG1 gene on rice leaf morphology was quantitatively assessed. Also, the feasibility of image processing techniques in detecting the morphological characteristics of rice leaves was discussed. Under the influence of the PROG1 gene, the length, width, and area of rice leaves decreased by 45.1%, 12.7%, and 44.8%, respectively, at the booting stage. Similarly, the length, width, and area of flag leaves decreased by 15.8%, 32.0%, and 33.7% at the heading stage and by 25.4%, 16.2%, and 19.7% at the filling stage, respectively, and that of secondary leaf reduced by 23.2%, 13.6%, and 54.2% at heading stage and by 24.1%, 17.3%, and 37.0% at filling stage, respectively. Furthermore, the length, width, and area of other leaves reduced by 32.3%, 9.8%, and 51.6% at the heading stage and by 28.6%, 7.3%, and 36.7% at the filling stage, respectively. The leaves in the rice canopy were shorter, narrower, and smaller in leaf area. Notably, no significant differences were found between image processing technology and manual measurement methods regarding the values of leaf morphological characteristics obtained (P<0.05). Thus, these results show that image processing technology is effective in studying the morphological characteristics of rice leaves. This study provides a reliable foundation for molecular breeding studies and will guide the application of the PROG1 gene in molecular breeding

Network Patterns of Zhongyuan Urban Agglomeration in China Based on Baidu Migration Data

As a new product of the Internet and big data era, migration data are of great significance for the revealing of the complex dynamic network patterns of urban agglomerations and for studying the relations between cities by using the “space of flows” model. Based on Baidu migration data of one week in 2021, this paper constructs a 30 × 30 rational data matrix for cities in Zhongyuan Urban Agglomeration and depicts the network pattern from static and dynamic perspectives by using social network analysis and dynamic network visualization. The results show that the network of Zhongyuan Urban Agglomeration is characterized by a circular structure with Zhengzhou as the center, a city belt around Zhengzhou as the connection, subcentral cities as the support and peripheral cities as the extension. Zhengzhou is the core city of the entire network, related to which the central and backbone networks divided in this paper account for nearly 40% of the total migration. Shangqiu, Luoyang, Zhoukou and Handan also play an important role in the structure of the migration network as subcentral cities. For a single city, the migration scale generally peaks on weekends and reaches its minimum during Tuesday to Thursday. Regarding the relations between cities, the migration variation can be divided into four types: peaking on Monday, peaking on weekends, bimodal and stable, and there are obvious phenomena of weekly commuting. In general, the links between cities outside Henan Province and other cities in the urban agglomeration are relatively weak, and the constraints of administrative regionalization on intercity migration are presumed to still exist. According to the results, the location advantage for multi-layer development and construction of Zhongyuan Urban Agglomeration should be made use of. In addition, the status as the core city and the radiation range should be strengthened, and the connections between the peripheral cities and the other cities should be improved, so as to promote the integrated and efficient development of the whole urban agglomeration