Owing to the rising concerns about environmental degradation worldwide, firms in several developed and developing countries are pursuing carbon emission reduction targets. In addition, in recent years, there is evidence of a shift in consumer preferences in favour of low-carbon products. 2-Hydroxybenzylamine nmr Using a theoretical model, where the shift in consumer preferences is explicitly incorporated, we evaluate the impact of carbon emission reduction cost-sharing on supply chain profit. In our model, consumers are willing to pay a higher price for low-carbon products and hence the retailer considers sharing the cost of carbon emission reduction with the manufacturer. Our model also includes a carbon trading mechanism. We identify a range of carbon emission reduction cost-sharing such that both supply chain enterprises are better-off. We find that, while achieving the aim of carbon emission reduction, consumer preference for low-carbon products can benefit both supply chain enterprises. Numerical simulations show that carbon emission reduction cost-sharing increases the retailer's order quantity as well as the profit and hence there is an incentive for the two supply chain enterprises to cooperate.The purpose of this research examination is to ascertain the effect of climate change, measured rainfall, temperature, and CO2, on crop production by using data spanning from 1985 to 2016 in Somalia. ARDL bounds testing approach and Granger causality were employed to model the long-run and short-run cointegrations and the causality directions respectively of the scrutinized variables. The empirical results of the study found a long cointegration between the variables. It revealed that rainfall improves crop production in the long-run but hampers in the short-run, whereas temperature has adverse effect on crop production both in the long and short runs. But carbon dioxide emissions do not have any significant effect on crop production. Among other determinants, agriculture labour and land under cereal cultivation have a negative and positive impact on crop productivity in the long-run, respectively. In contrast, unidirectional causality is observed from agriculture and land under cereal cultivation to temperature, while another unidirectional causality is established from carbon dioxide emission to land under cereal cultivation. Hence, the policymakers should formulate coherent adaptation measures and mitigation policies to tackle the already felt effect of the changing climate on the agriculture sector to rebuild resilient and sustainable agriculture production in Somalia.Cement is a basic requirement of today's society and is the only thing that humans consume more volume than water, but cement manufacturing is the most energy- and emission-intensive process. Hence, the cement industry is currently under pressure to reduce greenhouse gases (GHGs) emissions. Climate change mitigation strategies implemented in the industry leads to GHGs reduction, climate risks, pollutants, and another adverse impact on the environment. In order to implement climate change mitigation strategies in the cement industry, a careful analysis of barriers that hinder the emission reduction must be taken. However, most existing research on the barriers to mitigation measures is focused on developed countries. Among the most important emerging economies, India, the second-largest producer and consumer of cement, faces challenges to implement emission reduction measures. To bridge this gap, this paper identifies and evaluates the barriers and solutions to overcome these barriers in the context of India. This study employs a three-phase methodology based on fuzzy analytical hierarchy process (AHP) and fuzzy technique for order performance by similarity to ideal solution (TOPSIS) to identify barriers and solutions to overcome these barriers to climate change mitigation strategies adoption in Indian cement industry. Fuzzy AHP is employed to prioritize these barriers, and to rank solutions of these barriers, Fuzzy TOPSIS is employed. Ten Indian cement manufacturing industry is taken to illustrate the proposed three-phase methodology. Finally, the result of the analysis offers an effective decision support tool to the Indian cement industry to eliminate and overcome barriers to mitigation strategies adoption and build their green image in the market.Protection and restoration of different endangered bird species from pesticide exposure is crucial from the point of safety assessment of ecosystem. Toxicity predictions or risk assessment of pesticides by chemometric tools is one of the challenging fields in recent era. In the present study, classification-based quantitative structure toxicity relationship (QSTR) models were developed for a large dataset (516) of diverse pesticides on multiple avian species mallard duck, bobwhite quail, and zebra finch according to the Organization for Economic Co-operation and Development guidelines. The QSTR models were developed by linear discriminant analysis method with genetic algorithm for feature selection from 2D descriptors using QSAR-Co software. Different statistical metrics assured the reliability and robustness of the developed models. External compound prediction highlighted predictive nature of the models. The mechanistic interpretation suggested that presence of phosphate, halogens (Cl, Br), ether linkage, and NCOO influence the avian toxicity. Furthermore, model reliability was checked by the application of the standardization approach of the applicability domain (AD). Finally, the developed models provided a priori toxic and non-toxic classification for unknown pesticides (inside AD), with particular emphasis on organophosphate pesticides. The interspecies toxicity correlation and predictions encouraged for their further applicability for the fulfilment of data gaps in vital missing species.One of the most common toxicant prevailing in our environment is the arsenic. The present study is an attempt to investigate the effects of some of the common flavonoids, such as biochanin A (BCA), phloretin, and epigallocatechin-3-gallate (EGCG), on arsenic toxicity in the Swiss albino mice. For this purpose, mice were orally treated with sodium meta-arsenite (20 mg/kg bw/day), along with co-administration of BCA (50 mg/kg bw/day), phloretin (50 mg/kg bw/day), and EGCG (40 mg/kg bw/day) for the 2-week duration. All the mice were euthanized at the end of the treatment period, and the observations were made in the following parameters. Arsenic reduced the sperm motility as compared with the control (p less then 0.05) and was restored back to the normal status with the flavonoids treatment significantly (p less then 0.05). The arsenic concentrations in the kidney and liver tissues were found significantly reduced with all the flavonoids co-treatment (p less then 0.001). There was a reduction in the levels of superoxide dismutase (SOD), reduced glutathione (GSH), and glutathione S-transferase (GST) antioxidant markers, with the increased lipid peroxidation (LPO), protein carbonyl content (PCC), and catalase (CAT) levels in the arsenic-intoxicated mice performed in the different tissues.