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The purpose of this paper is to explore the relationship between corporate social responsibility (CSR) and firm value in the Chinese market and identify factors that may influence it. We discuss the relationship between CSR engagement in Chinese firms and firm value from a nonlinear perspective. In addition, we examine how the degree of internationalization in a firm may affect the relationship between CSR and firm value. We employ the Hausman test to compare a random-effects and a fixed-effects model, and after testing and comparison, the fixed-effects model was chosen in our paper. Using data from 314 firms listed in China's A-shares market from 2010 to 2017, we verify the U-shaped relationship between CSR and firm value. Meanwhile, the degree of internationalization will affect firm value but cannot positively regulate the relationship between corporate social responsibility and firm value., Competing Interests: The authors declare that there are no conflicts of interest., (Copyright © 2023 Renhong Wu et al.)

Even if developing nations are entitled to take part in the attempts of decreasing carbon emissions to elude alarming environment change, the consequences of carbon lessening goals in Human Development Index of developing nations continue an issue of dispute. Based on the decoupling relationship and index decomposition, the aim of the study is for determining the nexus between the Human Development Index and CO 2 emissions from the year 1990 to 2018 in Bangladesh. The outcomes exposed that Bangladesh accomplished weak and strong decoupling all through the analysis time. From the index decomposition of different factors point of view, it is revealed that variation in economic activity factor produces a significant amount of CO 2 emissions which is 0.0623 tonnes, and in terms of percentage, it stands for 105%. While energy intensity and economic structure factors act an indiscernible part in the rise of CO 2 emissions and in terms of percentage, it stands for 10.77% and 2.77%, respectively. Contrary, CO 2 emissions' coefficient and energy structure factors are liable for decrease carbon emissions to some extent, and in terms of percentage, it replicates 7.27% and 11.97%, respectively. Based on the outcomes, the paper offers regulations for the energy policymaker of Bangladesh on carbon emissions' alleviation policies and an important decision-making indication to speed up low-carbon growth., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Originating in December 2019 in China, SARS-CoV-2 has emerged as the deadliest pandemic in humankind's history. Along with direct contact and droplet contaminations, the possibility of infections through contaminated surfaces and fomites is investigating. This study aims to assess SARS-CoV-2 viral RNA's prevalence by real-time one-step reverse transcriptase PCR on banknotes circulating in Bangladesh. We also evaluated the persistence of the virus on banknotes spiked with SARS-CoV-2 positive diluted human nasopharyngeal samples. Among the 425 banknote samples collected from different entities, 7.29% (n = 31) were tested positive for targeted genes. Twenty-four positive representative samples were assessed for n gene fragments by conventional PCR and sequenced. All the samples that carry viral RNA belonged to the GR clade, the predominantly circulating clade in Bangladesh. In the stability test, the n gene was detected for up to 72 h on banknotes spiked with nasopharyngeal samples, and CT values increase significantly with time (p < 0.05). orf1b gene was observed to be less stable, especially on old banknotes, and usually went beyond detectable limit within 8 to 10 h. The stability of virus RNA well fitted by the Weibull model and concave curve for new banknotes and convex curve for old banknotes revealed. Handling banknotes is unavoidable; hence, these findings imply that proper hygiene practice is needed to limit SARS-CoV-2 transmission through banknotes., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have influenced the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Background: Osteoporosis is a gradually recognized health problem with risks related to disease history and living habits. This study aims to establish the optimal prediction model by comparing the performance of four prediction models that incorporated disease history and living habits in predicting the risk of Osteoporosis in Chongqing adults., Methods: We conduct a cross-sectional survey with convenience sampling in this study. We use a questionnaire From January 2019 to December 2019 to collect data on disease history and adults' living habits who got dual-energy X-ray absorptiometry. We established the prediction models of osteoporosis in three steps. Firstly, we performed feature selection to identify risk factors related to osteoporosis. Secondly, the qualified participants were randomly divided into a training set and a test set in the ratio of 7:3. Then the prediction models of osteoporosis were established based on Artificial Neural Network (ANN), Deep Belief Network (DBN), Support Vector Machine (SVM) and combinatorial heuristic method (Genetic Algorithm - Decision Tree (GA-DT)). Finally, we compared the prediction models' performance through accuracy, sensitivity, specificity, and the area under the receiver operating characteristic curve (AUC) to select the optimal prediction model., Results: The univariate logistic model found that taking calcium tablet (odds ratio [OR] = 0.431), SBP (OR = 1.010), fracture (OR = 1.796), coronary heart disease (OR = 4.299), drinking alcohol (OR = 1.835), physical exercise (OR = 0.747) and other factors were related to the risk of osteoporosis. The AUCs of the training set and test set of the prediction models based on ANN, DBN, SVM and GA-DT were 0.901, 0.762; 0.622, 0.618; 0.698, 0.627; 0.744, 0.724, respectively. After evaluating four prediction models' performance, we selected a three-layer back propagation neural network (BPNN) with 18, 4, and 1 neuron in the input layer, hidden and output layers respectively, as the optimal prediction model. When the probability was greater than 0.330, osteoporosis would occur., Conclusions: Compared with DBN, SVM and GA-DT, the established ANN model had the best prediction ability and can be used to predict the risk of osteoporosis in physical examination of the Chongqing population. The model needs to be further improved through large sample research.

The transportation sector has a dominant contribution to the fast-growing economy of the developing country Bangladesh. However, the nature of operating the transportation sector in the country requires an excessive amount of fossil energy which causes the rise of CO 2 emissions. Ascertaining the impending factors and technologically to conserve energy, as well as governing CO 2 emissions from this sector, are essential to attain sustainable development. The paper endeavors to determine the decomposition of driving factors that affect the relationship between Bangladesh's transport sector development and CO 2 emissions due to energy consumption from the year 1990 to 2017 using the Logarithmic-Mean Divisia Index (LMDI) model. The decomposition factors are fragmented into five elements through consideration of five fossil energies which are used in Bangladesh's transportation sector. The result reveals a 106.94% growth of aggregate CO 2 emissions in the transportation sector of Bangladesh. The results also show that aggregate influence of economic activity factor, population factor, economic structure factor, and energy intensity factor liable in increase CO 2 emissions to 66.03%, 23.56%, 7.64%, and 6.25% respectively. On the contrary, the energy structure factor is accountable for the decrease in CO 2 emissions to - 0.80%. Thus, the Bangladesh Government should proliferate mass responsiveness programs and cope with economic development through emphasizing quality of development rather than quantity which will ensure sustainable transport sector development.

The objective of this paper is to appraise the decomposition along with decoupling elements that affected the nexus between energy-related CO 2 emissions and the economic development of Bangladesh by applying the logarithmic mean Divisia index and Tapio model. The paper provides an effective policy that will enable Bangladesh to improve its environmental aspect and stimulate sustainable economic development. The analysis comprehends three economic sectors, and the decoupling determinative is fragmented into five elements. The results revealed that Bangladesh achieved weak decoupling throughout the analysis cycles except between the cycles of 1990-1991, 1992-1993, 1995-1996, 1997-1999, 2003-2004, 2012-2013, and 2015-2017 in which a strong decoupling occurred. From the disintegration of various components' frame of reference, it can be seen that change in scale effect causes a substantial increase in carbon emissions and economic structure together, whereas energy intensity plays an imperceptible role in the increase in carbon emissions. On the other hand, the emission is the only element that is responsible for a decrease in carbon emissions. From a comparative sectoral analysis point of view, scale effects are liable for increasing carbon emissions in all three sectors. Hence, precautionary information campaign should be taken to communicate a comprehensive countrywide moderation strategy and appropriate modification engagements for initiating a low-carbon community.

Objective: To investigate the prevalence and mechanisms of fluoroquinolone resistance in Shigella species isolated in Bangladesh and to compare with similar strains isolated in China., Methods: A total of 3789 Shigella isolates collected from Clinical Microbiology Laboratory of icddr,b, during 2004-2010 were analyzed for antibiotic susceptibility. Analysis of plasmids, plasmid-mediated quinolone-resistance genes, PFGE, and sequencing of genes of the quinolone-resistance-determining regions (QRDR) were conducted in representative strains isolated in Bangladesh and compared with strains isolated in Zhengding, China. In addition, the role of efflux-pump was studied by using the efflux-pump inhibitor carbonyl cyanide-m-chlorophenylhydrazone (CCCP)., Results: Resistance to ciprofloxacin in Shigella species increased from 0% in 2004 to 44% in 2010 and S. flexneri was the predominant species. Of Shigella spp, ciprofloxacin resistant (CipR) strains were mostly found among S. flexneri (8.3%), followed by S. sonnei (1.5%). Within S. flexneri (n = 2181), 14.5% were resistance to ciprofloxacin of which serotype 2a was predominant (96%). MIC of ciprofloxacin, norfloxacin, and ofloxacin were 6-32 mg/L, 8-32 mg/L, and 8-24 mg/L, respectively in S. flexneri 2a isolates. Sequencing of QRDR genes of resistant isolates showed double mutations in gyrA gene (Ser83Leu, Asp87Asn/Gly) and single mutation in parC gene (Ser80Ile). A difference in amino acid substitution at position 87 was found between strains isolated in Bangladesh (Asp87Asn) and China (Asp87Gly) except for one. A novel mutation at position 211 (His→Tyr) in gyrA gene was detected only in the Bangladeshi strains. Susceptibility to ciprofloxacin was increased by the presence of CCCP indicating the involvement of energy dependent active efflux pumps. A single PFGE type was found in isolates from Bangladesh and China suggesting their genetic relatedness., Conclusions: Emergence of fluoroquinolone resistance in Shigella undermines a major challenge in current treatment strategies which needs to be followed up by using empirical therapeutic strategies.