Corporate social responsibility (CSR) and leadership: validation of a multi-factor framework in the United Kingdom (UK)

Global surveys indicate that employee engagement costs nearly £70 billion per year in the UK alone with nascent improvement from 2011 to this date. Recognising employee disengagement as a threat to global socio-economic sustainability, experts and scholars offer CSR and employee-centric leadership as practical solutions. Visionary and servant leadership incite superior employee efforts through fair and ethical work values, but past theory and research show limited research on micro-processes that link CSR to employee outcomes. This study tested a value-centered model to examine if the two leadership styles and overall fairness can explain the positive relationship between CSR and extra effort. Data analysis of 512 employee self-reports using the structural equation modelling (SEM), the PROCESS approach and other techniques showed that executive’s CSR values cue to employee visionary and servant leadership, which influence extra effort both directly and indirectly (through overall fairness). Even though employees strongly endorsed the positive influence of universal visionary prototype, overall fairness was more strongly perceived in servant leadership. The paper offers practical implications for organizational theorists and practitioners

Mapping winter wheat with combinations of temporally aggregated Sentinel-2 and Landsat-8 data in Shandong Province, China

Winter wheat is one of the major cereal crops in China. The spatial distribution of winter wheat planting areas is closely related to food security; however, mapping winter wheat with time-series finer spatial resolution satellite images across large areas is challenging. This paper explores the potential of combining temporally aggregated Landsat-8 OLI and Sentinel-2 MSI data available via the Google Earth Engine (GEE) platform for mapping winter wheat in Shandong Province, China. First, six phenological median composites of Landsat-8 OLI and Sentinel-2 MSI reflectance measures were generated by a temporal aggregation technique according to the winter wheat phenological calendar, which covered seedling, tillering, over-wintering, reviving, jointing-heading and maturing phases, respectively. Then, Random Forest (RF) classifier was used to classify multi-temporal composites but also mono-temporal winter wheat development phases and mono-sensor data. The results showed that winter wheat could be classified with an overall accuracy of 93.4% and F1 measure (the harmonic mean of producer’s and user’s accuracy) of 0.97 with temporally aggregated Landsat-8 and Sentinel-2 data were combined. As our results also revealed, it was always good to classify multi-temporal images compared to mono-temporal imagery (the overall accuracy dropped from 93.4% to as low as 76.4%). It was also good to classify Landsat-8 OLI and Sentinel-2 MSI imagery combined instead of classifying them individually. The analysis showed among the mono-temporal winter wheat development phases that the maturing phase’s and reviving phase’s data were more important than the data for other mono-temporal winter wheat development phases. In sum, this study confirmed the importance of using temporally aggregated Landsat-8 OLI and Sentinel-2 MSI data combined and identified key winter wheat development phases for accurate winter wheat classification. These results can be useful to benefit on freely available optical satellite data (Landsat-8 OLI and Sentinel-2 MSI) and prioritize key winter wheat development phases for accurate mapping winter wheat planting areas across China and elsewhere

Research on Surface Water Quality Assessment and Its Driving Factors: A Case Study in Taizhou City, China

It is necessary to assess and analyze the factors that influence surface water since they are crucial to human activities such as agriculture, raising livestock, and industry. Previous research has mostly focused on how land use and landscape patterns affect the quality of surface waters; it has seldom addressed the industrial and agricultural production activities that are directly connected to human society. Therefore, the research area’s surface water quality was assessed by single factor index (SFI) and composite water quality index (WQI), divided into flood and non-flood periods, and water quality indicators with severe pollution and significant seasonal variations were selected; A total of 28 indicators were selected from three main factors-topography, socio-economic, and land use type-and analyzed using the Spearman correlation coefficient model. (1) SFI data reveal substantial seasonal changes in pH, DO, NH3-N, TN, and TP water quality indicators. The well-developed agricultural and aquaculture in the studied region is the primary cause of the excess TN and NH3-N concentrations; (2) The sample points’ water quality index (WQI) scores range from 50 to 80, with 62% of them having “medium” water quality; (3) The study area’s seasonal variation in water quality is primarily caused by human socio-economic activities (GDP, industrial effluent discharge, COD discharge, aquatic product quality, and the proportion of primary, secondary, and tertiary industries), as well as land use type (forest, shrubland, and cropland). Topography has little effect on the study area’s surface water quality. This study offers a fresh viewpoint on surface water quality management and driver analysis, and a new framework for managing and safeguarding aquatic ecosystems

Rotations improve the diversity of rhizosphere soil bacterial communities, enzyme activities and tomato yield.

The use of rotations is an effective strategy to control crop diseases and improve plant health. The soil bacterial communities in the rhizosphere are highly important for maintaining soil productivity. However, the composition and structure of soil bacterial communities in the rotations of vegetable crops remain unclear. In this study, we explored the bacterial diversity and community structure of the tomato rhizosphere, including enzyme activities, yield, and fruit quality, under three different cropping systems: tomato-tomato (Solanum lycopersicum) continuous cropping (TY1), eggplant (Solanum melongena)-tomato rotation (TY2) and arrowhead (Sagittaria trifolia)-tomato rotation (TY3). The composition and diversity of the rhizosphere bacterial communities differed significantly. The diversity was more in the TY2 and TY3 treatments than those in the TY1 treatment. Chujaibacter and Rhodanobacter were two predominant and unique strains detected only in TY1, while the relative abundances of Curvibacter and Luteimonas were the highest in TY2 and TY3, respectively. Moreover, Lysobacter was a relatively abundant type of biocontrol bacterium found only in the TY3 treatment, which could contribute to alleviating the obstacle of tomato continuous cropping. Compared with the TY1 treatment, the activities of catalase were significantly higher in the TY2 and TY3 treatments. In addition, compared with TY1, the TY2 and TY3 plots increased the following parameters: tomato yields by 24-46%, total soluble solids by 37-93%, total organic acid by 10-15.7% and soluble protein by 10-21%, while the content of nitrate was significantly reduced by 23%. Altogether, compared with the tomato monoculture, the rotations of tomato with eggplant and arrowhead shifted the rhizosphere bacterial communities and improved the yield and quality of the tomato. Moreover, a tomato rotation, particularly with arrowhead, was an effective way to alleviate the obstacles of continuous cropping

Digital image processing technology under backpropagation neural network and K-Means Clustering algorithm on nitrogen utilization rate of Chinese cabbages.

The purposes are to monitor the nitrogen utilization efficiency of crops and intelligently evaluate the absorption of nutrients by crops during the production process. The research object is Chinese cabbage. The Chinese cabbage population with different agricultural parameters is constructed through different densities and nitrogen fertilizer application rates based on digital image processing technology, and an estimation NC (Nitrogen Content) model is established. The population is classified through the K-Means Clustering algorithm using the feature extraction method, and the Chinese cabbage population quality BPNN (Backpropagation Neural Network) model is constructed. The nonlinear mapping relationship between different agricultural parameters and population quality, and the contribution rate of each indicator, are studied. The nitrogen utilization of Chinese cabbage is monitored effectively. Results demonstrate that the proposed NC estimation model has correlation coefficients above 0.70 in different growth stages. This model can accurately estimate the NC of the Chinese cabbage population. The results of the Chinese cabbage population quality BPNN model show that the population planting density based on the seedling number is reasonable. The constructed population quality evaluation model has a high R2 value and a comparatively low RMSE (Root Mean Square Error) value for the quality evaluation of Chinese cabbage in different periods, showing that it applies to evaluate the population quality of Chinese cabbage in different growth stages. The constructed nitrogen utilization model and quality evaluation model can monitor the nutrient utilization of crops in different growth stages, ascertain the agricultural characteristics of other yield groups in different growth stages, and clarify the performance of agricultural parameters in different growth stages. The above results can provide some ideas for crop growth intelligent detection

Rotations improve the diversity of rhizosphere soil bacterial communities, enzyme activities and tomato yield

The use of rotations is an effective strategy to control crop diseases and improve plant health. The soil bacterial communities in the rhizosphere are highly important for maintaining soil productivity. However, the composition and structure of soil bacterial communities in the rotations of vegetable crops remain unclear. In this study, we explored the bacterial diversity and community structure of the tomato rhizosphere, including enzyme activities, yield, and fruit quality, under three different cropping systems: tomato-tomato (Solanum lycopersicum) continuous cropping (TY1), eggplant (Solanum melongena)-tomato rotation (TY2) and arrowhead (Sagittaria trifolia)-tomato rotation (TY3). The composition and diversity of the rhizosphere bacterial communities differed significantly. The diversity was more in the TY2 and TY3 treatments than those in the TY1 treatment. Chujaibacter and Rhodanobacter were two predominant and unique strains detected only in TY1, while the relative abundances of Curvibacter and Luteimonas were the highest in TY2 and TY3, respectively. Moreover, Lysobacter was a relatively abundant type of biocontrol bacterium found only in the TY3 treatment, which could contribute to alleviating the obstacle of tomato continuous cropping. Compared with the TY1 treatment, the activities of catalase were significantly higher in the TY2 and TY3 treatments. In addition, compared with TY1, the TY2 and TY3 plots increased the following parameters: tomato yields by 24–46%, total soluble solids by 37-93%, total organic acid by 10-15.7% and soluble protein by 10-21%, while the content of nitrate was significantly reduced by 23%. Altogether, compared with the tomato monoculture, the rotations of tomato with eggplant and arrowhead shifted the rhizosphere bacterial communities and improved the yield and quality of the tomato. Moreover, a tomato rotation, particularly with arrowhead, was an effective way to alleviate the obstacles of continuous cropping

Study on Tensile Properties of CFRP Plates under Elevated Temperature Exposure

Elevated temperature exposure has a negative effect on the performance of the matrix resin in Carbon Fiber Reinforced Plastics (CFRP) plates, whereas limited quantitative research focuses on the deteriorations. Therefore, 30 CFRP specimens were designed and tested under elevated temperatures (10, 30, 50, 70, and 90 °C) to explore the degradations in tensile properties. The effect of temperature on the failure mode, stress-strain curve, tensile strength, elastic modulus and elongation of CFRP plates were investigated. The results showed that elevated temperature exposure significantly changed the failure characteristics. When the exposed temperature increased from 10 °C to 90 °C, the failure mode changed from the global factures in the whole CFRP plate to the successive fractures in carbon fibers. Moreover, with temperatures increasing, tensile strength and elongation of CFRP plates decreases gradually while the elastic modulus shows negligible change. Finally, the results of One-Way Analysis of Variance (ANOVA) show that the degradation of the tensile strength of CFRP plates was due to the impact of elevated temperature exposure, rather than the test error

Internet Penetration and Regional Financial Development in China: Empirical Evidence Based on Chinese Provincial Panel Data

The Internet has revolutionized the patterns of financial development and economic growth. To assess the impacts of internet penetration on the financial industry, this paper analyzed ten-year Chinese provincial panel data and concluded that regional Internet penetration accelerates financial development. Furthermore, the efficiency of Internet investment in underdeveloped provinces is better than that in developed provinces. More meaningfully, Internet penetration promotes the transparency of the securities market and regional financial participation. This indicates that Internet technology facilitates the advancement of the finance industry and the securities market

Conquering Gender Stereotype Threat in “Digit Sports”: Effects of Gender Swapping on Female Players’ Continuous Participation Intention in ESports

As a sportification form of human-computer interaction, eSports is facing great gender stereotype threat and causing female players’ withdraw. This study aims to investigate the relationship between gender-swapping and females’ continuous participation intention in eSports, the mediating effect of self-efficacy, and the moderating effect of discrimination. The results demonstrate (1) that the effect of gender-swapping on continuous participation intention in eSports was not significant, while gender-swapping had a significant association with self-efficacy, and self-efficacy had a significant association with continuous participation intention in eSports; (2) that gender-swapping had an indirect effect (via self-efficacy) on continuous participation intention in eSports; and (3) that discrimination moderated the effect of self-efficacy on continuous participation intention. Female players who had experienced discrimination displayed higher continuous participation intention in the context of self-efficacy enhanced by gender-swapping

Environmental Assessment of Soils and Crops Based on Heavy Metal Risk Analysis in Southeastern China

Heavy metal pollution in soil–crop systems has attracted great attention globally, caused by rapid urbanization and intensive industrialization. The research aims to investigate the environmental quality of the agricultural production area in Taizhou City, a typical economic region that is along the Yangtze River in the Southeast of China. A total of 370 sampling sites were chosen, with 370 soil, rice (Oryza sativa L.) and wheat (Triticum aestivum L.) samples collected, respectively, for measuring and analyzing the status, spatial distribution and pollution level of different heavy metals. The mean values of soil Cr, Pb, Cd, As and Hg were 66.78, 32.88, 0.23, 8.16 and 0.16 mg/kg, which were lower than the risk control standard values (RCV). However, the mean values of Pb, Cd and Hg were 1.25-, 1.77- and 2-fold larger than their soil background values (SBV) due to the intensive anthropogenic activities. The average content of Cd in rice exceeded its food safety limiting values (FCV) by 0.05 mg/kg, and the average contents of Pb in rice and wheat both exceeded the relevant FSV by 0.42 and 0.186 mg/kg, respectively. In addition, the maximum As and Cr contents in rice and wheat could be 0.13, 0.46 mg/kg and 0.63, 3.5 mg/kg larger than the relative FCVs in certain areas. Most of the high-value areas of soil and crop heavy metals were mainly located in Xinghua City, Taixing City and Jiangyan District, which had a similar distribution pattern with local industries or anthropogenic activities. The heavy metal pollution in soils and crops was found to be inconsistent, as 8.94% of the arable land possessed lightly metal pollution, while 3.18% of the area of rice and 4.0% of the area of wheat suffered severe pollution, with excessive accumulation of Cr, Pb and Cd. Based on the heavy metal pollution assessment of soil–crop systems, approximately 83% of the study area possessed medium or higher environmental quality, which was preferable for agricultural production. Our results implied that the spatial distribution and pollution level of the heavy metals in soil–crop systems were significantly influenced by industrial activities, followed by agricultural sources, transportation emissions and so on. Therefore, continuous monitoring and source control of heavy metals, especially for Cr, Pb and Cd, should be conducted to ensure the regional environmental quality and food security