Search

Understanding the framework of regional urban economic organization and its spatial effect requires a consideration of the networks. Urban network research has increasingly focused on urban spatial interaction and economic spillover effect based on the network externality theory in the context of transition from network research on structural description to performance evaluation. This study focused on Guangdong Province as the research area, built intercity passenger and freight flow networks based on the traffic, people, and express flow, studied the spatial structure of the network using social network analysis and other quantitative methods, and used a spatial Durbin model to estimate the economic spillover effect of the network. The conclusions from the results obtained can be summarized as follows. (1) In the network of traffic and people flow, Guangzhou and Foshan occupy the central positions. The core node of the express flow network spans Guangzhou, Dongguan, and Shenzhen. The spatial distribution of core linkages in the people flow network could be summarized as "the double-channel mode" of Guangzhou-Foshan and Shenzhen-Dongguan, while the corridor distribution of Foshan-Guangzhou-Dongguan-Shenzhen is the dominant flow organization pattern in the traffic flow network. In the express flow network, the dominant flow is dispersed eastward along the coast. (2) Guangzhou serves as the primary controlling entity of the network. Urban nodes clearly differ functionally in the express flow network; however, there is little functional difference in the traffic and people flow networks. (3) According to the spatial regression coefficients based on the SDM of the traffic, people, and the express flow networks, which are -0.974, -1.255, and -8.173, respectively, the economic externality of intercity passenger and freight flow networks reveal a substantial negative spillover. The current growth trend of Guangdong Province is not coordinated or complementary. (4) Coordinated expansion of the regional economy has been facilitated by improved functional connections between urban nodes. In addition, The movement of intercity factors could lower consumer market transaction costs and entrance barriers while allowing regional cities to enjoy the development advantages of borrowed size. However, the improvement of the conditions supporting the business infrastructure has expedited resource siphoning and intensified the province space's agglomeration shadow. This study created urban networks based on the movements of the passenger and freight flows, thereby enriching the empirical investigation of the externality theory in South China. This study also provides some guidance for advancing the regional economic integration and high-quality development.

Background: Inflammatory Bowel Disease (IBD) affects reproductive-aged women. Active disease can lead to decreased fertility. Although the vast majority of international guidelines recommend for the continuation of anti-TNF-α during pregnancy, recent studies have raised concerns about the safety of anti-tumor necrosis factor-α (TNF-α) therapy during pregnancy, both for patients and for physicians. Methods: Studies that evaluate the safety of anti-TNF-α therapy in pregnant women with IBD were identified using bibliographical searches. An updated meta-analysis was performed for pregnancy outcomes, such as live birth, abortion, still birth, preterm birth, low birth weight, congenital abnormalities, and neonatal infection. Odds ratio (OR) with 95% confidence interval (CI) are reported. Data on disease activity, timing of anti-TNF-α therapy were collected for further analysis. Results: Overall, 11 studies were screened from on-line databases and international meeting abstracts. An increased risk of abortion (OR, 1.33; 95% CI, 1.02–1.74; P = 0.04) and preterm birth (OR, 1.16; 95% CI, 1.05–1.28; P = 0.004), and a decreased risk of live birth (OR, 0.83; 95% CI, 0.74–0.94; P = 0.002]) were found in the anti-TNF-α therapy group compared with the control group (no use of anti-TNF-α therapy). The subgroup analyses based on the disease activity showed there is no significant association between the use of anti-TNF-α therapy during pregnancy on adverse pregnancy outcomes of abortion, preterm birth, and live birth. The rates of still birth, low birth weight, and congenital abnormalities in the anti-TNF-α therapy group were not significantly different from those in the control group. Conclusions: Anti-TNF-α therapy does not increase the risks of still birth, low birth weight, and congenital abnormalities; however it may be assicated with increased risks of abortion and preterm birth, which are accompanied by a lower rate of live birth. Although these findings may be confounding by potential disease activity, they offer some opposite viewpoints with biologic agent use. Therefore, more studies are required to further confirm the safety of anti-TNF-α therapy in pregnancy with IBD. [ABSTRACT FROM AUTHOR]

AIM: From the perspective of regulating mitochondrial complex I activity by DJ-1 protein, this study aims to explore the mechanism of DJ-1-mediated resveratrol (RES) preconditioning in protecting against oxidative stress injury induced by myocardial ischemia-reperfusion (I/R) in rats. METHODS: After intramyocardial injection of lentivirus carrying DJ-1 shRNA (sh-DJ-l) or negative control (NC) shRNA, the myocardial I/R model was constructed by ligating the left anterior descending branch of the rat coronary artery. Sprague-Dawley (SD) rats were randomly divided into 6 groups: sham group, I/R group, RES+I/R group, NC+RES+I/R group, sh-DJ-1+RES+I/R group, and IACS-010759 (mitochondrial complex I inhibitor)+RES+I/R group, with 10 rats in each group. The rats in RES treatment groups were given RES (20 mg/kg) via gavage for 7 d prior to the myocardial I/R modeling, once daily. Moreover, the rats in sham and I/R groups received an equivalent volume of normal saline via gavage. Myocardial infarction area and cardiac function were assessed by TTC staining and echocardiography, respectively. The MitoSOX fluorescent probe was used to detect levels of mitochondrial reactive oxygen species (ROS) in the myocardium. The levels of malondialdehyde (MDA), superoxide dis-mutase (SOD) and lactate dehydrogenase (LDH) in the serum were detected using kits. Western blot and co-immunoprecipitation assays were used to observe the interaction between DJ-1 and the two subunits, ND-1 and NDUFA4, of the mitochondrial complex I. RESULTS: Compared with I/R group, RES pretreatment significantly reduced the myocardial infarction area, mitochondrial ROS levels, serum LDH activity, and serum MDA content (P<0. 01). It also elevated left ventricular ejection fraction, left ventricular fractional shortening and serum SOD activity (P<0. 01). Pretreatment with RES increased the expression and mitochondrial translocation of DJ-1 (P<0. 01), promoted the interaction between DJ-1 and ND-1/NDUFA4, which in turn protected the activity of mitochondrial complex I (P<0. 01). However, when the expression of DJ-1 was suppressed, the protective effects of RES against myocardial I/R injury were significantly inhibited compared with RES+I/R group (P<0. 05 or P<0. 01). CONCLUSION: Pretreatment with RES increases the expression and mitochondrial translocation of DJ-1, and facilitates the interaction of DJ-1 with ND1 and NDUFA4 subunits of mito-chondrial complex I, thus preserving the activity of mitochondrial complex I and attenuating myocardial I/R-induced oxidative stress damage. [ABSTRACT FROM AUTHOR]

Smoking and calling are two typical behaviors involved in public and industrial safety that usually need to be strictly monitored and even prohibited on many occasions. To resolve the problems of missed detection and false detection in the existing traditional and deep-learning-based behavior-recognition methods, an intelligent recognition method using a multi-task YOLOv4 (MT-YOLOv4) network combined with behavioral priors is proposed. The original YOLOv4 is taken as the baseline network to be improved in the proposed method. Firstly, a K-means++ algorithm is used to re-cluster and optimize the anchor boxes, which are a set of predefined bounding boxes to capture the scale and aspect ratio of specific objects. Then, the network is divided into two branches with the same blocks but independent tasks after the shared feature extraction layer of CSPDarknet-53, i.e., the behavior-detection branch and the object-detection branch, which predict the behaviors and their related objects respectively from the input image or video frame. Finally, according to the preliminary predicted results of the two branches, comprehensive reasoning rules are established to obtain the final behavior-recognition result. A dataset on smoking and calling detection is constructed for training and testing, and the experimental results indicate that the proposed method has a 6.2% improvement in recall and a 2.4% improvement in F1 score at the cost of a slight loss in precision compared to the baseline method; the proposed method achieved the best performance among the compared methods. It can be deployed to related security surveillance systems for unsafe-behavior monitoring and early-warning management in practical scenarios. [ABSTRACT FROM AUTHOR]

Wire Arc Additive Manufacturing (WAAM) has many applications in fabricating complex metal parts. However, controlling surface roughness is very challenging in WAAM processes. Typically, machining methods are applied to reduce the surface roughness after a part is fabricated, which is costly and ineffective. Therefore, controlling the WAAM process parameters to achieve better surface roughness is important. This paper proposes a machine learning method based on Gaussian Process Regression to construct a model between the WAAM process parameters and top surface roughness. In order to measure the top surface roughness of a manufactured part, a 3D laser measurement system is developed. The experimental datasets are collected and then divided into training and testing datasets. A top surface roughness model is then constructed using the training datasets and verified using the testing datasets. Experimental results demonstrate that the proposed method achieves less than 50 μm accuracy in surface roughness prediction. [ABSTRACT FROM AUTHOR]

Multifunctional materials for water purification have attracted significant attention due to the increased water pollution problems. However, fabricating the low-cost, effective, and recyclable separation material for wastewater containing various hazardous substances is still a challenge. Herein, we developed an Ag/TiO2@PDMS coated cotton fabric with self-cleaning ability, high flux, superior visible-light photocatalytic ability, and recyclability via the "powder + glue" strategy. The composites are superhydrophobic (water contact angle 157°) and show high separation efficiency. After 20 times of repeated use, the separation efficiency remains 16,322 Lm−2 h−1, and methylene blue (MB) 's degradation rate remains almost unchanged. The high oil purification, catalytic property, excellent stability in harsh conditions, and recyclability enable the material as a satisfactory candidate for water purification. [ABSTRACT FROM AUTHOR]

Mariculture is a key protein source and economic driver but traditional methods pollute coastal waters, hindering sustainable development. Current research on the ecological impacts of mariculture mainly focuses on specific pollutants and lacks an assessment of the biogeochemical impacts of mariculture discharge. This study examined Xiangshan Bay, a representative intensive mariculture area in China, to explore the impact of mariculture tailwater discharge on water quality, focusing on dissolved organic matter (DOM) and bacterial communities. Based on the fluorescence excitation-emission matrix combined with parallel factor analysis, a characteristic fluorescence component C4 was identified in mariculture tailwater (intensity of 40 ± 4 %, n = 8), while higher C4 components (47 ± 3 %, n = 15) were found throughout the bay. Humic-like components from riverine input (C1 + C2: 32 ± 3 %, n = 15) and protein-like components from domestic sewage (C5: 2 ± 1 %, n = 15) were significantly lower in the seawater samples, indicating the strong influence of mariculture tailwater on the entire DOM structure of the bay. The bacterial community structure showed a response consistent with DOM, as revealed by nonmetric multidimensional scaling analysis. This showed that bacterial communities in mariculture tailwater and bay water samples clustered together, independent of riverine input. The SourceTracker model indicated that mariculture tailwater (91 ± 5 %) predominantly contributed to the bacterial community, with minimal contributions from riverine input (< 5 %). Co-occurrence network analysis further showed that under long-term high-intensity mariculture discharge, the C4 component became the core DOM and was closely associated with the bacterial community. The results here demonstrate the profound impact of traditional mariculture on coastal water quality and show that riverine input is not the primary pollution source in this region, providing clear directions for coastal environmental restoration efforts., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)