Industrial co-agglomeration, Internet utilization, and the development of green and low-carbon cycle - based on the empirical study of 41 cities in the Yangtze River Delta of China.

The construction of green and low-carbon circular (GLC) development economic system is conducive to the promotion of "carbon peaking and carbon neutral." The level of GLC development in the Yangtze River Delta (YRD) region is related to the realization of the ambitious goal of "carbon peaking and carbon neutrality" in the region. This paper use principal component analysis (PCA) to process GLC development level of 41 cities in the YRD from 2008 to 2020. Then, we constructed panel Tobit model and threshold model from the perspective of industrial co-agglomeration and Internet utilization and empirically tested the influence of the two key variables on GLC development of the YRD. We found that (1) the YRD's level of GLC development showed a dynamic evolution trend of "fluctuation, convergence, and rise." The four provincial-level administrative regions of the YRD are in the order of  GLC development level: Shanghai, Zhejiang, Jiangsu, and Anhui. (2) There is an inverted "U" Kuznets curve (KC) between industrial co-agglomeration and the development of GLC of the YRD. In the left segment of KC, the industrial co-agglomeration promotes GLC development of the YRD. In the right segment of KC, the industrial co-agglomeration inhibits GLC development of the YRD. Internet utilization enhances GLC development of the YRD. And the interaction of industrial co-agglomeration and Internet utilization cannot significantly enhance GLC development. (3) Double-threshold effect of opening-up is manifested as follows: industrial co-agglomeration on GLC development of the YRD goes through an insignificant-inhibited-improved evolutionary trajectory. Single-threshold effect of government intervention is manifested as follows: the impact of Internet utilization on GLC development of the YRD shifts from insignificant role to significant enhancement. In addition, there is an inverted-N type KC effect between industrialization and GLC development. Based on the above findings, we proposed suggestions in terms of industrial co-agglomeration, Internet-like digital technology application, anti-monopoly, and rational industrialization.

Experimental study on the permeability of crushed coal medium based on the Ergun equation.

Accurate determination of the permeability of crushed coal medium is the basis for the study of their permeability characteristics. To investigate the permeability characteristics of this special porous medium composed of crushed coal particles, the permeability parameters of crushed coal specimens of different initial porosities were measured by designing a lateral-limit compression seepage test system. Parameters were determined separately for specimens of different initial porosities. (1) the Reynolds number distribution region characterising the seepage state was determined and obtained. Specimens with initial porosity distribution between 0.02 and 0.08, and seepage Reynolds number distribution in the low-permeability zone, under Darcy flow; (2) the intrinsic permeability of the crushed coal medium was obtained by using the Ergun equation. The complex inverse proportional relationship between the drag coefficient and Reynolds number was derived; (3) Through the determination of the permeability of the crushed coal medium, the mean value of ßK value was obtained to be about 45.7, and the analysis of the permeability of porous medium can determine its critical permeability. The relationship between the Forchheimer number Fo and critical Reynolds number was measured. The results indicate that it conforms to a linear distribution. In-depth analysis of these two parameters can be used to explore the flow transition process between laminar, transition, and turbulent flow. This study provides insight into the permeability characteristics of the media in fractured coal bodies.

Prevalence of porcine respiratory pathogens in slaughterhouses in Shanxi Province, China.

BACKGROUND: Porcine respiratory diseases remain the biggest challenge in pig-based food production and are a public health concern. Despite control measures, persistent outbreaks have been reported worldwide. OBJECTIVE: To establish an early detection mechanism for pig farm disease outbreaks based on slaughterhouse risk and environmental assessment. METHODS: We investigated the prevalence and risk factors of porcine respiratory disease-causing pathogens including Mycoplasma hyopneumoniae (MHP), porcine circovirus type 2 (PCV2), porcine reproductive and respiratory syndrome virus (PRRSV) and Haemophilus parasuis (HPS). Polymerase chain reaction (PCR) was used to analyse the lungs of 491 pigs from 19 slaughterhouses across 11 cities in Shanxi Province, China. RESULTS: PCR detected MHP, PCV2, PPRSV and HPS in 76.99%, 67.00%, 11.82% and 19.55% of the samples, respectively; 10.12% were negative for all four pathogens. Co-positivity rates for two and three pathogens were identified. The results confirmed significant correlations between PCV2 and MHP (p = .001, p < .05), HPS and PCV2 (p = .01, p < .05) and MHP and PRRSV (p = .01, p < .05). No significant correlation was observed between HPS and MHP (p = .067, p > .05). Positive MHP and PCV2 rates were low in areas with high vegetation coverage. The overall pathogen positivity rate was higher in both lower and higher temperature environments. CONCLUSIONS: Interactions among pathogens may increase disease severity. Furthermore, environmental assessment and pathogen surveillance within pig slaughterhouses can be an effective approach for early detection and mitigation of new disease threats before broad dissemination occurs among a herd.

Serological evidence of bovine viral diarrhea virus and peste des petits ruminants virus infection in alpacas (Vicugna pacos) in Shanxi Province, northern China.

Bovine viral diarrhea virus (BVDV) and peste des petits ruminants virus (PPRV) are two important pathogens associated with a variety of disease syndromes that result in substantial financial losses in animal husbandry. This study was performed to assess the seroprevalence of antibodies to BVDV and PPRV among alpacas raised in Shanxi Province of northern China. Serum samples were obtained from 246 alpacas in Taiyuan (n=182), Xinzhou (n=31), and Jinzhong cities (n=33) of Shanxi Province, and serological testing was carried out using the competitive enzyme-linked immunosorbent assay. Overall seroprevalence to BVDV was 3.25% (95% CI 1.03-5.47), and seropositive alpacas were found only in Taiyuan City. The overall PPRV seroprevalence in alpacas was 28.86% (95% CI 23.20-34.52). While no PPRV-seropositive alpacas were found in Xinzhou City, the seroprevalence of PPRV was 90.91% (95% CI 81.10-100.72) in Jinzhong City and 22.53% (95% CI 16.46-28.60) in Taiyuan City, respectively, which showed a statistically significant difference. To our knowledge, the present work is the first report on seroprevalence of BVDV and PPRV in alpacas in China, which provides baseline information for the control of infection.