Corporate social responsibility and environmental sustainability: achieving firms sustainable performance supported by plant capability

In the contemporary industrial setting, corporations face direct and indirect pressures from multiple intrinsic and extrinsic environmental constituents, including competitive entities and resource limitations, hindering their continuity and sustainability. Against this backdrop, Corporate social responsibility (CSR) is an industrial dynamic that enables firms to address the pressures imposed by these environmental constituents. Therefore, this study examines the impact of CSR on firm’s sustainable performance conditioned at different plant sizes. In doing so, the data was collected using a survey instrument comprising close-ended items with five-point likert scales on each item for measuring managerial perceptions from manufacturing industries. Through non-probabilistic sampling, a sample of 399 responses from middle to top-level management was collected. Smart PLS was utilized to analyze the data for validating the hypothesized relationships between the latent constructs. To enhance the reliability of the tests used for the analysis, bootstrapping was used to iterate the sample size and refine significance levels. Overall findings indicate that environmental sustainable development is essential to explain the relationship between ‘CSR for consumer’ and ‘Firm sustainable performance’. The relationship between ‘CSR to employees’ and ‘Firm sustainable performance’ is significant both with and without the explanatory role of sustainable environmental performance. The link between CSR to community and firm sustainable performance is not being explained by environmental sustainable development. These results offer valuable policy recommendations

Anti-fungal efficacy of aqueous leaf extracts Neem (Azadirachta indica) in the treatment of tap water

High-quality drinking water coming from treatment plants is susceptible to pollution and severe deterioration due to the drinking water delivery system prior to access to consumers’ faucets. The results of this study confirmed that Neem leaves extract and chlorine at all concentrations had antifungal activity during tap water treatment. This study has provided excellence about the ability of Neem leaves extraction and chlorine as a disinfectant for Rhodotorula mucilaginosa and Aspergillus spp. in treating tap water. The most notable factors were the dosage, time, and agitation selected to evaluate their effects on reducing the development of fungal communities in drinking water using the central composite design (CCD) in the response surface methodology (RSM). The CCD was performed with a 2 complete central composite design with five different stage coordinate components. Because the Neem leaves can be processed locally and should also be encouraged for use in water treatment. This will eventually reduce the high costs and health risks associated with chemical water treatment. This technology is cheap, conventional, readily available, and suitable for rural areas, as nature’s biological methods generate no treatable waste

The antifungal efficiency of Moringa oleifera seed extracts for tap water treatment

Water must be pure and free of any contaminants for human consumption. However, due to indiscriminate human activity, its quality has worsened, resulting in many illnesses that plague humanity, particularly in developing nations. Promising water treatment procedures are considerably more expensive, and many of the disinfectants now in use are toxic, making the hunt for safer organic alternatives even more difficult. Moringa seeds have long been used to clean drinking water and minimize the health concerns associated with microorganisms in rural communities. Using central composite design (CCD) in response surface technique, the parameters identified as the essential components, dose, duration, and agitation, were chosen to assess their influence on eradicating the growth of fungal communities in the drinking water by response surface methodology (RSM). The CCD was done with two complete factorial combination components at five distinct levels. The typical two fungi widespread in the tap water samples have selected Aspergillus sp. (73%) and Rhodotorula mucilaginosa (63%). Fungal mycelia growth gradually decreased with increased concentration of Moringa oleifera seeds extract and chlorine on Rhodotorula mucilaginosa and Aspergillus sp. The modified determination coefficients (adj R2) for the CFU of Moringa seeds were also 0.8122 and 0.8405. This study aims to highlight the performance activity of Moringa seeds while treating tap water instead of using rapid usage of chlorine in the traditional method. This study found that Moringa oleifera extract seeds and chlorine have antifungal action against disinfectants at all concentrations. Using Moringa oleifera seeds extract and chlorine as a disinfectant on Rhodotorula mucilaginosa and Aspergillus spp. in treating tap water is a viable alternative. This method would significantly reduce the high costs and health concerns of current chemical water treatment methods. The method is traditional and simple to apply, making it suitable for rural regions. It also produces no non-treatable wastes because it is biological

Enhancing Optical, Electronic, Crystalline, and Morphological Properties of Cesium Lead Halide by Mn Substitution for High-Stability All-Inorganic Perovskite Solar Cells with Carbon Electrodes

In this work all-inorganic perovskite CsPbIBr2 are doped with Mn to compensate their shortcomings in band structure for the application of perovskite solar cells (PSCs). The novel Mn-doped all-inorganic perovskites, CsPb1-xMnxI1+2xBr2-2x, are prepared in ambient atmosphere. As the concentration of Mn2+ ions increases, the bandgaps of CsPb1-xMnxI1+2xBr2-2x decrease from 1.89 to 1.75 eV. Additionally, when the concentration of Mn dopants is appropriate, this novel Mn-doped all-inorganic perovskite film shows better crystallinity and morphology than its undoped counterpart. These advantages alleviate the energy loss in hole transfer and facilitate the charge-transfer in perovskites, therefore, PSCs based on these novel CsPb1-xMnxI1+2xBr2-2x perovskite films display better photovoltaic performance than the undoped CsPbIBr2 perovskite films. The reference CsPbIBr2 cell reaches a power conversion efficiency (PCE) of 6.14%, comparable with the previous reports. The CsPb1-xMnxI1+2xBr2-2x cells reach the highest PCE of 7.36% (when x= 0.005), an increase of 19.9% in PCE. Furthermore, the encapsulated CsPb0.995Mn0.005I1.01Br1.99 cells exhibit good stability in ambient atmosphere. The storage stability measurements on the encapsulated PSCs reveal that PCE is dropped by only 8% of the initial value after >300 h in ambient. Such improved efficiency and stability are achieved using low-cost carbon electrodes (without expensive hole transport materials and Au electrodes)

Ecological networks: Pursuing the shortest path, however narrow and crooked

International audienceRepresenting data as networks cuts across all sub-disciplines in ecology and evolutionary biology. Besides providing a compact representation of the interconnections between agents, network analysis allows the identification of especially important nodes, according to various metrics that often rely on the calculation of the shortest paths connecting any two nodes. While the interpretation of a shortest paths is straightforward in binary, unweighted networks, whenever weights are reported, the calculation could yield unexpected results. We analyzed 129 studies of ecological networks published in the last decade that use shortest paths, and discovered a methodological inaccuracy related to the edge weights used to calculate shortest paths (and related centrality measures), particularly in interaction networks. Specifically, 49% of the studies do not report sufficient information on the calculation to allow their replication, and 61% of the studies on weighted networks may contain errors in how shortest paths are calculated. Using toy models and empirical ecological data, we show how to transform the data prior to calculation and illustrate the pitfalls that need to be avoided. We conclude by proposing a five-point checklist to foster best-practices in the calculation and reporting of centrality measures in ecology and evolution studies. The last two decades have witnessed an exponential increase in the use of graph analysis in ecological and conservation studies (see refs. 1,2 for recent introductions to network theory in ecology and evolution). Networks (graphs) represent agents as nodes linked by edges representing pairwise relationships. For instance, a food web can be represented as a network of species (nodes) and their feeding relationships (edges) 3. Similarly, the spatial dynamics of a metapopulation can be analyzed by connecting the patches of suitable habitat (nodes) with edges measuring dispersal between patches 4. Data might either simply report the presence/absence of an edge (binary, unweighted networks), or provide a strength for each edge (weighted networks). In turn, these weights can represent a variety of ecologically-relevant quantities, depending on the system being described. For instance, edge weights can quantify interaction frequency (e.g., visitation networks 5), interaction strength (e.g., per-capita effect of one species on the growth rate of another 3), carbon-flow between trophic levels 6 , genetic similarity 7 , niche overlap (e.g., number of shared resources between two species 8), affinity 9 , dispersal probabilities (e.g., the rate at which individuals of a population move between patches 10), cost of dispersal between patches (e.g., resistance 11), etc. Despite such large variety of ecological network representations, a common task is the identification of nodes of high importance, such as keystone species in a food web, patches acting as stepping stones in a dispersal network , or genes with pleiotropic effects. The identification of important nodes is typically accomplished through centrality measures 5,12. Many centrality measures has been proposed, each probing complementary aspects of node-to-node relationships 13. For instance, Closeness centrality 14,15 highlights nodes that are "near" to all othe

Global assessment of genomic variation in cattle by genome resequencing and high-throughput genotyping

<p>Abstract</p> <p>Background</p> <p>Integration of genomic variation with phenotypic information is an effective approach for uncovering genotype-phenotype associations. This requires an accurate identification of the different types of variation in individual genomes.</p> <p>Results</p> <p>We report the integration of the whole genome sequence of a single Holstein Friesian bull with data from single nucleotide polymorphism (SNP) and comparative genomic hybridization (CGH) array technologies to determine a comprehensive spectrum of genomic variation. The performance of resequencing SNP detection was assessed by combining SNPs that were identified to be either in identity by descent (IBD) or in copy number variation (CNV) with results from SNP array genotyping. Coding insertions and deletions (indels) were found to be enriched for size in multiples of 3 and were located near the N- and C-termini of proteins. For larger indels, a combination of split-read and read-pair approaches proved to be complementary in finding different signatures. CNVs were identified on the basis of the depth of sequenced reads, and by using SNP and CGH arrays.</p> <p>Conclusions</p> <p>Our results provide high resolution mapping of diverse classes of genomic variation in an individual bovine genome and demonstrate that structural variation surpasses sequence variation as the main component of genomic variability. Better accuracy of SNP detection was achieved with little loss of sensitivity when algorithms that implemented mapping quality were used. IBD regions were found to be instrumental for calculating resequencing SNP accuracy, while SNP detection within CNVs tended to be less reliable. CNV discovery was affected dramatically by platform resolution and coverage biases. The combined data for this study showed that at a moderate level of sequencing coverage, an ensemble of platforms and tools can be applied together to maximize the accurate detection of sequence and structural variants.</p

Cross-talk between cd1d-restricted nkt cells and γδ cells in t regulatory cell response

CD1d is a non-classical major histocompatibility class 1-like molecule which primarily presents either microbial or endogenous glycolipid antigens to T cells involved in innate immunity. Natural killer T (NKT) cells and a subpopulation of γδ T cells expressing the Vγ4 T cell receptor (TCR) recognize CD1d. NKT and Vγ4 T cells function in the innate immune response via rapid activation subsequent to infection and secrete large quantities of cytokines that both help control infection and modulate the developing adaptive immune response. T regulatory cells represent one cell population impacted by both NKT and Vγ4 T cells. This review discusses the evidence that NKT cells promote T regulatory cell activation both through direct interaction of NKT cell and dendritic cells and through NKT cell secretion of large amounts of TGFβ, IL-10 and IL-2. Recent studies have shown that CD1d-restricted Vγ4 T cells, in contrast to NKT cells, selectively kill T regulatory cells through a caspase-dependent mechanism. Vγ4 T cell elimination of the T regulatory cell population allows activation of autoimmune CD8+ effector cells leading to severe cardiac injury in a coxsackievirus B3 (CVB3) myocarditis model in mice. CD1d-restricted immunity can therefore lead to either immunosuppression or autoimmunity depending upon the type of innate effector dominating during the infection