How does technological progress affect low carbon economic growth? Evidence from regional heterogeneity in China.

The rapid economic development leads to excessive consumption of fossil energy, resulting in a large number of carbon emissions, which makes the sustainable development of China's economy and society face great challenges. Under the background of global warming and environmental deterioration, developing low-carbon economy has become an inevitable choice for China to change its development model and improve its international competitiveness. Technological progress is the first driving force to promote economic growth. However, the influence degree and mechanism of technological progress on the development of low-carbon economy are still unclear. Based on this, the paper proposes the concept of low-carbon GDP, which is used to measure the low-carbon economic development of 30 Chinese provinces. Then, the panel fixed effect model is used to study the effect degree and mechanism of technological progress on low-carbon GDP and the moderating effect of other factors on the relationship between them. The results show that, first, economically developed provinces and regions have higher per capita low-carbon GDP and low-carbon GDP index, but the speed and quality of low-carbon economic development are not necessarily higher. Second, technological progress can promote the growth of low-carbon GDP and make greater contributions to resources-poor regions. Third, improving local education can make technological progress more effective in low-carbon economic development. China needs to upgrade technological development by developing new and high-tech technologies, promoting new urbanization and strengthening education in order to promote low-carbon economic development.

Assessment of the individual and compounding effects of marginalization factors on injury severity, discharge location, recovery, and employment outcomes at 1 year after traumatic brain injury.

Objective: The aim of this study is to examine the effect of eight distinct marginalized group memberships and explore their compounding effect on injury severity, recovery, discharge location, and employment outcomes 1-year after traumatic brain injury (TBI). Methods: Individuals with medically confirmed, complicated mild-severe TBI (N = 300) requiring inpatient rehabilitation care between the ages of 18 and 65 were recruited at two urban (public and private) health systems between 2013 and 2019. Data were collected from self-report and medical record abstraction. Marginalized group membership (MGM) includes racial and ethnic minority status, less than a high school diploma/GED, limited English proficiency, substance abuse, homelessness, psychiatric hospitalizations, psychiatric disorders, and incarceration history. Membership in four or more of these groups signifies high MGM. In addition, these factors were explored individually. Unadjusted and adjusted linear and logistic regressions and Kruskal-Wallis tests were used to assess the associations of interest in RStudio. Results: After adjusting for age, sex, and cause of injury, compared to TBI patients with low MGM, those with high MGM experience significantly longer post-traumatic amnesia (95% CI = 2.70, 16.50; p = 0.007) and are significantly more likely to have a severe TBI (per the Glasgow-Coma Scale) (95% CI = 1.70, 6.10; p ≤ 0.001) than a complicated mild-moderate injury. Individuals with high MGM also are significantly less likely to be engaged in competitive paid employment 1 year after injury (95% CI = 2.40, 23.40; p = 0.001). Patients with high MGM are less likely to be discharged to the community compared to patients with low MGM, but this association was not significant (95% CI = 0.36, 1.16; p = 0.141). However, when assessing MGMs in isolation, certain associations were not significant in unadjusted or adjusted models. Conclusion: This exploratory study's findings reveal that when four or more marginalization factors intersect, there is a compounding negative association with TBI severity, recovery, and employment outcomes. No significant association was found between high MGM and discharge location. When studied separately, individual MGMs had varying effects. Studying marginalization factors affecting individuals with TBI has critical clinical and social implications. These findings underline the importance of addressing multidimensional factors concurrent with TBI recovery, as the long-term effects of TBI can place additional burdens on individuals and their economic stability.

Digital Economy Development, Industrial Structure Upgrading and Green Total Factor Productivity: Empirical Evidence from China's Cities.

The digital economy is an important engine to promote sustainable economic growth. Exploring the mechanism by which the digital economy promotes economic development, industrial upgrading and environmental improvement is an issue worth studying. This paper takes China as an example for study and uses the data of 286 cities from 2011 to 2019. In the empirical analysis, the direction distance function (DDF) and the Global Malmquist-Luenberger (GML) productivity index methods are used to measure the green total factor productivity (GTFP), while Tobit, quantile regression, impulse response function and intermediary effect models are used to study the relationship among digital economy development, industrial structure upgrading and GTFP. The results show that: (1) The digital economy can significantly improve China's GTFP; however, there are clear regional differences. (2) The higher the GTFP, the greater the promotion effect of the digital economy on the city's GTFP. (3) From a dynamic long-term perspective, the digital economy has indeed positively promoted China's GTFP. (4) The upgrading of industrial structures is an intermediary transmission mechanism for the digital economy to promote GTFP. This paper provides a good reference for driving green economic growth and promoting the environment.

Comparison of SSRs and SNPs in assessment of genetic relatedness in maize.

Advances in high-throughput SNP genotyping and genome sequencing technologies have enabled genome-wide association mapping in dissecting the genetic basis of complex quantitative traits. In this study, 82 SSRs and 884 SNPs with minor allele frequencies (MAF) over 0.20 were used to compare their ability to assess population structure, principal component analysis (PCA) and relative kinship in a maize association panel consisting of 154 inbred lines. Compared to SNPs, SSRs provided more information on genetic diversity. The expected heterozygosity (He) of SSRs and SNPs averaged 0.65 and 0.44, and the polymorphic information content of these two markers was 0.61 and 0.34 in this panel, respectively. Additionally, SSRs performed better at clustering all lines into groups using STRUCTURE and PCA approaches, and estimating relative kinship. For both marker systems, the same clusters were observed based on PCA and the first two eigenvectors accounted for similar percentage of genetic variations in this panel. The correlation coefficients of each eigenvector from SSRs and SNPs decreased sharply when the eigenvector varied from 1 to 3, but kept around 0 when the eigenvector were over 3. The kinship estimates based on SSRs and SNPs were moderately correlated (r (2) = 0.69). All these results suggest that SSR markers with moderate density are more informative than SNPs for assessing genetic relatedness in maize association mapping panels.

[Comparison of fluorescence in situ hybridization and immunohistochemistry assessment for Her-2 status in breast cancer and its relationship to clinicopathological characteristics].

OBJECTIVE: To investigate the concordance and correlation between fluorescence in situ hybridization (FISH) and immunohistochemistry (IHC) assessment for HER-2 status in breast cancer patients and analyze their relationship to clinical characteristics. METHODS: A total of 128 samples of breast cancer tissue were analyzed retrospectively. FISH was employed to detect the HER-2 gene amplification. And the FISH findings were compared with IHC test results by analyzing the concordance and correlation between two results. And their relationships to the clinical characteristics were analyzed. RESULTS: The overall coincidence rate of IHC and FISH was 90.6% (kappa = 0.405, P = 0.000). And the discordance was mainly found in the IHC (++) group. A positive correlation was found between the two results (r = 0.655, P = 0.000). The ER (estrogen receptor) expression was negatively correlated with HER-2 gene amplification and the expression of Her-2 protein (r = -0.300, P = 0.001; r = -0.223, P = 0.011). There was a negative correlation between ER/PR status and HER-2 gene amplification (r = -0.213, P = 0.016). The similar results were found in subgroup analysis. Tumor grade was negatively correlated with the expression of Her-2 protein (r = -0.293, P = 0.008), but not with HER-2 gene amplification (P > 0.05). CONCLUSION: IHC is a preferred method to detect the Her-2 status in breast cancer. The strong positive expression (+++) of HER-2 protein tested by IHC is strongly consistent with HER-2 gene amplification by FISH. But HER-2 gene amplification should be further detected by FISH in patients with HER-2 positive expression (+-++) in order to guide the clinical diagnosis and treatment. ER, ER/PR (progesterone receptor) status and tumor grade are correlated with HER-2 gene amplification and/or the expression of Her-2 protein. This study helps improve the accuracy of judging HER-2 gene amplification according to the clinical and pathological features such as ER status and the results of IHC.