Stochastic Transfer Function Model and Neural Networks to Estimate Soil Moisture1

Abstract: A practical methodology is proposed to estimate the three‐dimensional variability of soil moisture based on a stochastic transfer function model, which is an approximation of the Richard’s equation. Satellite, radar and in situ observations are the major sources of information to develop a model that represents the dynamic water content in the soil. The soil‐moisture observations were collected from 17 stations located in Puerto Rico (PR), and a sequential quadratic programming algorithm was used to estimate the parameters of the transfer function (TF) at each station. Soil texture information, terrain elevation, vegetation index, surface temperature, and accumulated rainfall for every grid cell were input into a self‐organized artificial neural network to identify similarities on terrain spatial variability and to determine the TF that best resembles the properties of a particular grid point. Soil moisture observed at 20 cm depth, soil texture, and cumulative rainfall were also used to train a feedforward artificial neural network to estimate soil moisture at 5, 10, 50, and 100 cm depth. A validation procedure was implemented to measure the horizontal and vertical estimation accuracy of soil moisture. Validation results from spatial and temporal variation of volumetric water content (vwc) showed that the proposed algorithm estimated soil moisture with a root mean squared error (RMSE) of 2.31% vwc, and the vertical profile shows a RMSE of 2.50% vwc. The algorithm estimates soil moisture in an hourly basis at 1 km spatial resolution, and up to 1 m depth, and was successfully applied under PR climate conditions.     

Stabilization/solidification of ashes in clays used in the manufacturing of ceramic bricks.

This paper presents the results of the lixiviation of metals from different mixtures of fly and bottom ashes that have been stabilized and solidified in clays used in the manufacture of bricks. The ashes used for this study were obtained from a Hoffmann-type brick furnace adapted for the incineration of municipal solid waste during the manufacturing of ceramic bricks. The ashes were stabilized in clay in different proportions of clay:ash mix (99:1, 95:5, 90:10, 80:20 and 60:40). Such mixes were used to manufacture bricks that were calcined at a temperature ranging from 50 to 1100 degrees C. The clay, ashes and manufactured bricks were characterized using X-ray diffraction, fluorescent X-ray, thermogravimetry, differential thermal analysis, atomic absorption spectroscopy and scanning electronic microscopy. In addition, toxicity characteristic leaching procedure lixiviation tests were performed according to the EPA 1311 method for the determination of heavy metals. The results showed an affinity between clay and ash, and also that the bricks manufactured with these mixtures present low lixiviation levels. The tests also showed the highest decrease in the concentration of arsenic, nickel, chromium, zinc and silver for 99:1 mixtures. The 95:5 mixture was found to be the most favourable for the stabilization (greater concentration decrease) of lead and cadmium. Selenium was the metal with the lowest concentration change whereas arsenic, nickel, chromium, zinc and cadmium showed the greatest concentration change in all mixtures, with the exception of cadmium in the mixture 99:1.     

25 years of higher‐order confirmatory factor analysis in the organizational sciences: A critical review and development of reporting recommendations

We discuss how confirmatory factor analysis results should be used to examine potential higher‐order constructs and advocate that researchers present five types of evidence, which are as follows: (1) the ability of the higher‐order model to reproduce the observed covariation among manifest variables; (2) the ability of the higher‐order model to reproduce the observed covariation among manifest variables better than more parsimonious alternative models—and no less well than less parsimonious alternative models; (3) the ability of the higher‐order model to reproduce the observed covariation among lower‐order factors; (4) the ability of the higher‐order factor to explain variation in lower‐order factors; and (5) the ability of the higher‐order factor to explain variation in manifest variables. We illustrate how this type of evidence could be presented with a worked example and contrast our recommendations with the manner in which higher‐order confirmatory factor analysis has been used in the organizational sciences over the past 25 years to support claims regarding higher‐order constructs such as core self‐evaluations and transformational leadership. Our review shows that a substantial proportion of the 44 examined articles failed to present enough evidence to allow readers to understand the size and importance of higher‐order factors. Copyright © 2015 John Wiley & Sons, Ltd.     

Did Child Restraint Laws Globally Converge? Examining 40 Years of Policy Diffusion

Objective: The objective of the current study is to determine what factors have been associated with the global adoption of mandatory child restraint laws (ChRLs) since 1975.

Methods: In order to determine what factors explained the global adoption of mandatory ChRLs, Weibull models were analyzed. To carry out this analysis, 170 countries were considered and the time risk corresponded to 5,146 observations for the period 1957–2013. The dependent variable was first time to adopt a ChRL. Independent variables representing global factors were the World Health Organization (WHO) and World Bank's (WB) road safety global campaign; the Geneva Convention on Road Traffic; and the United Nation's (UN) 1958 Vehicle Agreement. Independent variables representing regional factors were the creation of the European Transport Safety Council and being a Commonwealth country. Independent variables representing national factors were population; gross domestic product (GDP) per capita; political violence; existence of road safety nongovernmental organizations (NGOs); and existence of road safety agencies. Urbanization served as a control variable. To examine regional dynamics, Weibull models for Africa, Asia, Europe, North America, Latin America, the Caribbean, and the Commonwealth were also carried out.

Results: Empirical estimates from full Weibull models suggest that 2 global factors and 2 national factors are significantly associated with the adoption of this measure. The global factors explaining adoption are the WHO and WB's road safety global campaign implemented after 2004 (P <.01), and the UN's 1958 Vehicle Agreement (P <.001). National factors were GDP (P <.01) and existence of road safety agencies (P <.05). The time parameter ρ for the full Weibull model was 1.425 (P <.001), suggesting that the likelihood of ChRL adoption increased over the observed period of time, confirming that the diffusion of this policy was global. Regional analysis showed that the UN's Convention on Road Traffic was significant in Asia, the creation of the European Transport Safety Council was significant in Europe and North America, and the global campaign was in Africa. In Commonwealth and European and North American countries, the existence of road safety agencies was also positively associated with ChRL adoption.

Conclusions: Results of the world models suggest that the WHO and WB's global road safety campaign was effective in disseminating ChRLs after 2004. Furthermore, regions such as Asia and Europe and North America were early adopters since specific regional and national characteristics anticipated the introduction of this policy before 2004. In this particular case, the creation of the European Transport Safety Council was fundamental in promoting ChRLs. Thus, in order to introduce conditions to more rapidly diffuse road safety measures across lagging regions, the maintenance of global efforts and the creation of road safety regional organizations should be encouraged. Lastly, the case of ChRL convergence illustrates how mechanisms of global and regional diffusion need to be analytically differentiated in order better to assess the process of policy diffusion.     

Managers as drivers of CSR in state-owned enterprises

Corporate social responsibility (CSR) is increasingly required not only of private sector companies, but also of state-owned enterprises (SOEs), whose main function is to provide services to society and not principally to obtain financial reward. The important role played by managers in implementing CSR has been demonstrated by prior research. The objective of this paper is to examine how managers of SOEs perceive the concept of CSR, the reasons for their involvement and how it is integrated into everyday business practices. In addition, we examine whether managers' attitudes towards CSR policies are influenced by their personal profiles and by the sector in which the SOEs work. We find that, although these managers are aware of the importance of the CSR principles underlying their activities and understand the meaning, scope and dimensions of CSR, there remains an evident need to enhance the application of CSR policies among the strategies of SOEs. The manager profile and the sector in which the SOEs work both have a strong influence on their behaviour regarding CSR issues.