Adoption of AI in response to COVID-19-a configurational perspective.

Although the importance of artificial intelligence (AI) has often been highlighted in strategic agility and decision outcomes, whether it helps firms strengthen their competitiveness and the means firms use to achieve such competitiveness are still under-researched. Our research thus joins the recent discussion on digitalization trends and strategic responses to COVID-19 to better understand how firms strengthen their competitiveness during such challenging times. Namely, this study incorporates the strategic responses to COVID-19 into the technology-organization-environment (TOE) framework by investigating the impacts of different configurations of TOE contexts and strategic responses on a firm's competitive advantage. We used fuzzy-set qualitative comparative analysis to investigate how TOE contexts and strategic responses integrate into configurations and impact a firm's competiveness. By applying a configurational approach with data from 514 exporting firms in China, we find a strong indication of the equifinality of different strategies, indicating that multiple strategic paths can be used to respond to crises. The adoption of AI, while important, is not sufficient to enhance a firm's competitiveness. Our results stress the significance of data quality, organizational resources and capabilities, and digital business model innovation for AI adoption. We also identify successful strategic paths of AI adoption aversion and ambidextrous strategies. The findings have practical implications for firms seeking effective strategies to respond to future crises and sustain their competitive advantages.

The employment effects of environmental regulation: Evidence from eleventh five-year plan in China.

The balance between environmental pollution control and full employment is of practical significance in developing countries. In this article, by taking Chinese total volume control of SO2 emissions in Eleventh Five-Year Plan as a quasi-natural experiment, we are able to identify the influence of environmental regulation on the labor demand of manufacturing enterprises. The findings show that the labor demand of pollution-intensive enterprises has fallen significantly as a result of environmental regulation, which means that the higher the intensity of environmental control, the less the labor demand. This indicates that China has a long way to go to achieve a win-win of emission reduction and full employment through the total volume control of pollutants. Interestingly, environmental regulation plays a significant negative role in corporate salaries, but a significant positive impact on per capita salaries. This may imply that although environmental regulation crowds out the labor demand to a certain degree, those affected are mainly low-skilled workers. Mechanism analysis reveals that the total volume control of pollutant has both job creation and job destruction effects on enterprises. Job creation is caused by technological innovation. As for job destruction, it comes from the reduction of production scale and the substitution of capital for manpower.

Inhibiting 3ßHSD1 to eliminate the oncogenic effects of progesterone in prostate cancer.

Prostate cancer continuously progresses following deprivation of circulating androgens originating from the testis and adrenal glands, indicating the existence of oncometabolites beyond androgens. In this study, mass-spectrometry-based screening of clinical specimens and a retrospective analysis on the clinical data of prostate cancer patients indicate the potential oncogenic effects of progesterone in patients. High doses of progesterone activate canonical and non-canonical androgen receptor (AR) target genes. Physiological levels of progesterone facilitate cell proliferation via GATA2. Inhibitors of 3ß-hydroxysteroid dehydrogenase 1 (3ßHSD1) has been discovered and shown to suppress the generation of progesterone, eliminating its transient and accumulating oncogenic effects. An increase in progesterone is associated with poor clinical outcomes in patients and may be used as a predictive biomarker. Overall, we demonstrate that progesterone acts as an oncogenic hormone in prostate cancer, and strategies to eliminate its oncogenic effects may benefit prostate cancer patients.

The race to zero emissions: Can renewable energy be the path to carbon neutrality?

When taking into account the general terms on which the global green and low-carbon transition takes place, it can be affirmed that the use of clean and renewable energy, including wind, hydro, solar, etc., is an alternative to the traditional energy sources. The renewable energy industry possesses considerable potential, and has recently become the centre of the global energy landscape. Therefore, this article refers to the rolling-window Granger causality test, in order to explore the role of renewable energy (RE) in reducing the greenhouse gas emissions. By studying the interactions that take place between RE consumption and carbon dioxide (CO2) emissions, we find that the negative impact of RE on CO2 indicates that the replacement role of RE has become increasingly prominent, for it to effectively contribute towards the realization of carbon emission reduction. The results in this regard are consistent with the energy-environment model, suggesting that RE has an excellent performance in achieving carbon neutrality. In fact, CO2 usually exhibits a negative effect on RE, which indicates towards the predictability of environmental quality to the development potential of renewable energy. Carbon emission reduction has become a game of interest among the countries around the world. And hence, in relation to these turn of events in the last few decades, RE is now expected to usher in the required acceleration. While eventually it is believed that the green energy competition will reshape the geopolitics of the world.

Does environmental and renewable energy R&D help to achieve carbon neutrality target? A case of the US economy.

The current study investigates carbon neutrality targets for the US's case while analyzing the role of environmental-related research and development (ERR&D) and renewable energy research and development (RER&D). This study also considered economic growth (GDP) and energy productivity (EP) as controlled variables. Utilizing the time series data over the period from 1990 to 2019, this study used various econometric approaches, such as unit root tests and cointegration tests for stationarity and the long-run association between variables, respectively. This study's main econometric regression tools, such as dynamic ordinary least square (DOLS) and fully modified ordinary least square (FMOLS), are utilized. The empirical findings reveal that economic growth played a negative role in achieving carbon neutrality targets. However, EP, RER&D, and ERR&D positively contribute to carbon neutrality target achievement by reducing atmospheric CO2 emissions. Moreover, this study found a cointegration relationship between the study variables. The bidirectional causality is found between ERR&D and CO2 emissions, while a unidirectional causality is observed, running from exogenous variables towards CO2 emissions. Based on the empirical findings, this study recommends expanding the investment and expenditures in both ERR&D and RER&D sectors to attain carbon neutrality.

Modeling the effect of green technology innovation and renewable energy on carbon neutrality in N-11 countries? Evidence from advance panel estimations.

After the Paris Climate Conference (Conference of the Paris COP: 21), most developing countries face challenges to attain a sustainable economy and carbon neutrality targets with minimum CO2 emission. The next eleven (N-11) economies are in line with the global phenomena of environmental degradation; very few studies have analyzed the effects of green technology innovation on environmental degradation in N-11 countries. Therefore, the present study addresses the gap and examines green technology innovation and renewable energy with CO2 emission from 1980 to 2018. The present study considers all the issues related to panel data analysis, such as cross-sectional dependence, stationarity, heterogeneity in slope parameters, and structural break with advanced panel estimators. Moreover, the cross-sectional augmented autoregressive distributed lags (CS-ARDL) test results show the negative and significant impact of green technology innovation and renewable energy with CO2 emission in the long run. However, the short-run association of green technology innovation is not significant-further, the results endorsed by the robustness tests such as AMG and CCEMG. To reduce environmental deterioration in N-11 countries, governments are suggested implementing some policies to support green innovation technologies and renewable energy resources.

The role of green innovation and tourism towards carbon neutrality in Thailand: Evidence from bootstrap ADRL approach.

The recent years have been marked by the role of green tech innovation in decreasing carbon emissions worldwide to attain the carbon neutrality target. Despite many studies examining the nexus between the former and energy consumption, tech innovation's effects on CO2 releases have not been extensively researched, and the extant empirical findings are often contradictory. Also, a major concern regarding the available literature is the scarcity of papers that scan the impact of tourism on carbon emissions, even though the industry has a high potential to affect ambient air pollution. In this case, the evidence is mixed, and no consensus among academics on the relationships between the two. Therefore, this study seeks to investigate the relevance of green innovation and tourism in decreasing environmental damage in Thailand based on the bootstrapping ARDL causality model suggested by (McNown et al., 2018). This specification includes a new cointegration feature and conventional ARDL bounds tests, which increases the power of the t- and of the f-test and has several advantages, being more adequate for dynamic models with more than one explanatory variable. Our findings reveal that green innovation and tourism lead to lower environmental damage by reducing CO2 emissions, similar to foreign investments and that green tech innovation improves the environmental quality via lower carbon emissions.

Klotho Regulates Epithelial-to-Mesenchymal Transition In Vitro via Wnt/ß-Catenin Pathway and Attenuates Chronic Allograft Dysfunction in a Rat Renal Transplant Model.

BACKGROUND Klotho deficiency has been implicated in various kidney diseases and has been associated with renal fibrosis. However, the role of Klotho in renal allograft fibrosis still remains undetermined. MATERIAL AND METHODS A 24-week-old rat renal transplant model with chronic allograft dysfunction (CAD) was carried out by orthotopic kidney transplantation using F344 donor rats to Lewis recipient rats. Successful establishment of the model was verified by HE and Masson staining and renal allograft function assessment. HK-2 cells were cultured and treated with TGF-ß1 and/or siRNA-Klotho at various time points. Total proteins and RNA were extracted from the cultured cells and kidney tissues. Western blot assay and quantitative RT-PCR were used to analyze the expression of Klotho, fibronectin, and ß-catenin pathways. RESULTS We successfully established and identified a 24-week-old rat renal transplant model with CAD. Loss of Klotho was identified to be associated with epithelial-to-mesenchymal transition (EMT), renal allograft fibrosis, and CAD. In HK-2 cells, a significant decrease of Klotho protein was observed in the renal fibrosis induced by TGF-ß1 in a time-dependent manner. Moreover, intervention of siRNA-Klotho remarkably promoted the progression of renal fibrosis and activation of the Wnt/ß-catenin signaling pathway. CONCLUSIONS Our results show that Klotho has a significant protective role against EMT, renal allograft fibrosis, and CAD following kidney transplantation, which is mediated by inhibition of the Wnt/ß-catenin signaling pathway.

Multistage implementation framework for smart supply chain management under industry 4.0.

The true potential of the industry 4.0, which is a byproduct of the fourth industrial revolution, cannot be actually realized. This is, of course true, until the smart factories in the supply chains get connected to each other, with their systems and the machines linked to a common networking system. The last few years have experienced an increase in the adoption and acceptance of the industry 4.0's components. However, the next stage of smart factories, which will be the smart supply chains, is still in its period of infancy. Moreover, there is a simultaneous need to maintain a focus on the supply chain level implementation of the concept that industry 4.0 puts forth. This is important in order to gain the end to end benefits, while also avoiding the organization to organization compatibility issues that may follow later on. When considering this concept, limited research exists on the issues related to the implementation of industry 4.0, at the supply chain level. Hence, keeping in mind this lack of literature and research available, on a phenomenon that will define the future of business and industry, this study uses an exploratory approach to capture the implementation of industry 4.0 concepts across multiple tiers of the supply chain. Based on this research, the study proposes a multistage implementation framework that highlights the organizational enablers such as culture, cross-functional approach, and the continuous improvement activities. Furthermore, it also highlights the staged implementation of the advanced tools, starting from the focal organization with the subsequent integration with the partner organizations.

Trade and technological innovation: The catalysts for climate change and way forward for COP21.

Following the adaptation of the Paris Agreement at COP21, it was noted that the traditional measures of carbon emissions have several limitations; and a reliable and relevant carbon emissions measurement is important to formulate a response to the challenge of climate change. This study, therefore, explores the relationship between international trade and consumption-based carbon emissions, which is a trade adjusted indicator; and measures the outflow and the inflow of emissions through exports and imports separately. We also include technological innovation in the model to understand its impact on consumption-based carbon emissions. The results show that exports and consumption-based carbon emissions are negatively associated, and technological innovation helps reducing the adverse effect of CO2 growth. In contrast, Imports and gross domestic product are positively linked with consumption-based carbon emissions. The findings also suggest the countries which embraced the Paris Climate Agreement must focus on consumption-based carbon emissions rather than the production-based carbon emissions.

Effect of Patient Participation on Nurse and Patient Outcomes in Inpatient Healthcare.

Using service-dominant logic as a theoretical lens, this study investigated the co-production of healthcare service and service value co-creation between nurses and patients. The main objective of this study was to: (1) examine the effect of patient participation on patient satisfaction and nurses' attitudes and behaviors; (2) examine boundary conditions of the effect of patient participation on patients and nurses. We proposed that patient participation positively impacted patient satisfaction and nurse job satisfaction, work engagement, and helping behaviors. We further proposed that first inpatient stay and length of stay moderated the effect of patient participation on patient satisfaction, and nurses' sociodemographic characteristics moderated the effect of patient participation on nurse job satisfaction, work engagement, and helping behaviors. Using survey data from 282 nurses and 522 inpatients from a public hospital in China, we found that the effect of patient participation on patient satisfaction was contingent upon first inpatient stay and length of stay. We also found that patient participation improved nurse job satisfaction, work engagement, and helping behaviors. Furthermore, nurses' sociodemographic characteristics, namely age and organizational tenure, moderated the effect of patient participation on nurse job satisfaction, but not on work engagement and helping behaviors. Theoretical and practical implications of our findings were discussed.

Clinical Evaluation of Urine Prostatic Exosomal Protein in the Diagnosis of Chronic Prostatitis.

OBJECTIVE: To evaluate the clinical potential of urine prostatic exosomal protein (PSEP) as a diagnostic biomarker of chronic prostatitis (CP). Materials andmethods: Using an enzyme-linked immunosorbent assay kit, urine PSEP levels were detected in 103 control cases as well as 283 cases of CP, with 82 cases fulfilling the definition of the USA National Institutes of Health category II (NIH-II), 108 cases of NIH-IIIa and 93 cases of NIH-IIIb. The values of age, body mass index, prostate volume, serum prostatic specific antigen (PSA) urine PSEP levels, and seminal parameters were analyzed. RESULTS: The PSEP levels were significantly higher in patients of NIH-II (2.09 [2.35] ng/mL), NIH-IIIa (1.80 [2.95] ng/mL) and NIH-IIIb (1.64 [2.48] ng/mL) compared to the value of 0.24 (0.76) ng/mL in the controls. ROC identified a cutoff value of 1.387 ng/mL, with a sensitivity of 59.0% and specificity of 94.2%. The area under the ROC curve was 0.833. PSEP levels positively correlated with serum PSA levels in the NIH-IIIb group, and with EPS WBC count in the NIH-IIIa group, and with semen WBC count in each CP subgroups but negatively correlated with sperm motility in both the NIH-IIIa group and the NIH-IIIb group. CONCLUSION: Urine PSEP could be a potential biomarker for CP.

Increasing entropy for colloidal stabilization.

Stability is of paramount importance in colloidal applications. Attraction between colloidal particles is believed to lead to particle aggregation and phase separation; hence, stability improvement can be achieved through either increasing repulsion or reducing attraction by modifying the fluid medium or by using additives. Two traditional mechanisms for colloidal stability are electrostatic stabilization and steric stabilization. However, stability improvement by mixing attractive and unstable particles has rarely been considered. Here, we emphasize the function of mixing entropy in colloidal stabilization. Dispersion stability improvement is demonstrated by mixing suspensions of attractive nanosized titania spheres and platelets. A three-dimensional phase diagram is proposed to illustrate the collaborative effects of particle mixing and particle attraction on colloidal stability. This discovery provides a novel method for enhancing colloidal stability and opens a novel opportunity for engineering applications.

BRCA2 N372H Polymorphism and Risk of Epithelial Ovarian Cancer: An Updated Meta-Analysis With 2344 Cases and 9672 Controls.

The BRCA2 N372H is the only common polymorphism that leads to the amino acid change based on the reports up to date. Previous studies explored the relationship between the single nucleotide polymorphism and ovarian cancer risk, but the results were inconsistent or inconclusive.To investigate the association between N372H in BRCA2 gene and ovarian cancer susceptibility, a systematic literature search was performed for related publications in the databases of PubMed, Gene, and Google Scholar.Total 2344 cases and 9672 controls in eligible studies were included in this meta-analysis. χ -based Q test and an I index were used to identify the heterogeneous records. Potential publication biases were assessed by Begg and Egger tests.In the overall analysis, the results showed a significant association between BRCA2 codon 372 polymorphism and increased risk of ovarian cancer (HH versus NN: odds ratio (OR) = 1.22, 95% confidence interval (CI) 1.01-1.48, P = 0.037). In the Australia subgroup analysis, significant association was also detected (HH versus NN: OR = 1.40, 95% CI 1.04-1.87, P = 0.026). The subgroup analysis for serous cancer subgroup showed that the significant association could be detected under recessive model (OR = 1.38, 95% CI, 1.01-1.89, P = 0.04) and under homozygote comparison (OR = 1.46, 95% CI, 1.06-2.01, P = 0.022).Our meta-analysis suggests that the N372H polymorphism is associated with susceptibility of ovarian cancer. The allele H might increase the risk of ovarian cancer, especially, for ovarian cancers of the serous subtype.

Quantitative analysis of cell-free DNA in ovarian cancer.

The aim of the present study was to investigate the association between cell-free DNA (cf-DNA) levels and clinicopathological characteristics of patients with ovarian cancer using a branched DNA (bDNA) technique, and to determine the value of quantitative cf-DNA detection in assisting with the diagnosis of ovarian cancer. Serum specimens were collected from 36 patients with ovarian cancer on days 1, 3 and 7 following surgery, and additional serum samples were also collected from 22 benign ovarian tumor cases, and 19 healthy, non-cancerous ovaries. bDNA techniques were used to detect serum cf-DNA concentrations. All data were analyzed using SPSS version 18.0. The cf-DNA levels were significantly increased in the ovarian cancer group compared with those of the benign ovarian tumor group and healthy ovarian group (P<0.01). Furthermore, cf-DNA levels were significantly increased in stage III and IV ovarian cancer compared with those of stages I and II (P<0.01). In addition, cf-DNA levels were significantly increased on the first day post-surgery (P<0.01), and subsequently demonstrated a gradual decrease. In the ovarian cancer group, the area under the receiver operating characteristic curve of cf-DNA and the sensitivity were 0.917 and 88.9%, respectively, which was higher than those of cancer antigen 125 (0.724, 75%) and human epididymis protein 4 (0.743, 80.6%). There was a correlation between the levels of serum cf-DNA and the occurrence and development of ovarian cancer in the patients evaluated. bDNA techniques possessed higher sensitivity and specificity than other methods for the detection of serum cf-DNA in patients exhibiting ovarian cancer, and bDNA techniques are more useful for detecting cf-DNA than other factors. Thus, the present study demonstrated the potential value for the use of bDNA as an adjuvant diagnostic method for ovarian cancer.