Assessment of convergent validity of latent variables is one of the steps in conducting structural equation modeling via partial least squares (PLS-SEM). In this paper, we illustrate such an assessment using a loadings-driven approach. The analysis employs WarpPLS, a leading PLSSEM software tool.
Abstract Abundant solar energy is freely available almost round the year in India. As per the current scenario of global warming and climatic change, solar energy is the cleanest source in nature. Concentrated solar power (CSP)has hardly contributed to the overall installed solar power capacity in the country. CSP technologies are Parabolic Trough Collector (PTC), Linear Fresnel Reflector (LFR), Paraboloid Dish and Solar Power Tower. This paper presents a review of CSP in solar parabolic dish concentrator to understand thermal aspect like thermal efficiency, optical efficiency, useful heat gain, heat losses, solar irradiation, etc. for various applications and current development. The current scenario of global CSP is discussed to meet the future challenges and need of the society.
Regression modeling analyses the relationship between two or more variables and can be used to predict the response variable from one or more independent variables. The present study uses linear regression analysis to evaluate the growth in the two fish species of genus Oreochromis, Nile tilapia and Jipe tilapia, under aquaculture conditions. The models were fitted using a collection of functions in the R-software library. The final models were selected using the goodness of fit criteria based on the coefficient of differentiation, the model p- values and Akaike information criteria. The significance of the linear relationship between predictor variables and the mean response was tested by comparing the computed standardized parameter estimates, whereas the confidence intervals were constructed to assess the uncertainty of predicting the response variable and determine outliers in the model. Generally, both species exhibited good condition during growth and all the measured water quality variables significantly afffected growth (p<0.05). However, only temperature and dissolved oxygen produced the most important linear relationship with fish weight. The study recommends that data from a controlled experiment should be used the determine the interactions between the two growth variables.
Micro-level assessment of vulnerability to climate change creates basis for policy formulation. The study specifically ascertained the levels and determinants of vulnerability to climate change among selected food crop farmers. Data collected were analysed using descriptive statistics and ordinary least square regression analysis. The result revealed that 15.95%, 68.97% and 15.08% of the households were highly vulnerable, moderately vulnerable and less vulnerable to climate change respectively. This implies a varied effect on crop farmers. The result also showed that amount saved, extension contacts, household expenditure and value of crop were significant at 1% level. The study recommended the provision of basic amenities and soft loans to farmers as well as an improvement in extension services. It also advocated the introduction of effective climate change mitigation and adaptive measures to boost agricultural output in their area.