Pasting and Dough Rheological Properties of Ackee (Blighia sapida) Aril Flour: A Contribution to the Search for Wheat Flour Substitutes.

Wheat is one of the most widely used cereals in the world. However, studies consider wheat flour doughs to be of low nutritional quality, as there is now greater public awareness of celiac disease and gluten intolerance. Therefore, consumers are demanding healthier and more varied food products. Consequently, wheat flour is being replaced fully or partially by flours from other sources with higher quality. Hence, the main objective of this work was to report the effect of blending wheat flour with ackee aril flour, until the total replacement of wheat flour, on pasting and dough rheological properties. Five different levels of blending were analyzed: wheat to ackee aril flour mass ratios of 100 : 0, 75 : 25, 50 : 50, 25 : 75, and 0 : 100. Pasting properties (pasting temperature, peak viscosity, ease of cooking, swelling power, final viscosity at 50 °C, and thixotropy) were analyzed; and steady-state shear measurements were used to obtain consistency coefficients (K) and flow behavior indexes (n) after data was fitted to the Power Law and Herschel-Bulkley models. The gradual addition of the ackee aril flour fraction produced an increase in ash, fat, protein, and fiber content; while water and carbohydrate content showed the opposite behavior in the obtained composite flour. Consequently, the partial or full replacement of wheat flour changed the rheological properties of the produced doughs, as well as the quality of the final product. These changes were mostly related to the protein and carbohydrate content of the ackee aril flour fraction. In general, doughs showed a pseudoplastic behavior with thixotropy whose viscosity decreased as the addition of ackee aril flour was increased. Pasting properties of blends involving 25 %-75 % ackee aril flour demonstrate the feasibility of including these flours in products subjected to high processing temperatures such as canned products or even to produce chips and pasta.

Distributed Learning Fractal Algorithm for Optimizing a Centralized Control Topology of Wireless Sensor Network Based on the Hilbert Curve L-System.

Wireless sensor networks (WSNs) consist of a large number of small devices or nodes, called micro controller units (MCUs) and located in homes and/or offices, to be operated through the internet from anywhere, making these devices smarter and more efficient. Quality of service routing is one of the critical challenges in WSNs, especially in surveillance systems. To improve the efficiency of the network, in this article we proposes a distributed learning fractal algorithm (DFLA) to design the control topology of a wireless sensor network (WSN), whose nodes are the MCUs distributed in a physical space and which are connected to share parameters of the sensors such as concentrations of C O 2 , humidity, temperature within the space or adjustment of the intensity of light inside and outside the home or office. For this, we start defining the production rules of the L-systems to generate the Hilbert fractal, since these rules facilitate the generation of this fractal, which is a fill-space curve. Then, we model the optimization of a centralized control topology of WSNs and proposed a DFLA to find the best two nodes where a device can find the highly reliable link between these nodes. Thus, we propose a software defined network (SDN) with strong mobility since it can be reconfigured depending on the amount of nodes, also we employ a target coverage because distributed learning fractal algorithm (DLFA) only consider reliable links among devices. Finally, through laboratory tests and computer simulations, we demonstrate the effectiveness of our approach by means of a fractal routing in WSNs, by using a large amount of WSNs devices (from 16 to 64 sensors) for real time monitoring of different parameters, in order to make efficient WSNs and its application in a forthcoming Smart City.

Effects of people-oriented leadership and subordinate employability on call center withdrawal behaviors / Los efectos del liderazgo centrado en las personas y de la empleabilidad de los subordinados sobre los comportamientos de abandono en el servicio de atención telefónica

Call-center employees are prone to lateness, absenteeism, and turnover because their jobs are low-wage, low-skill, and provoke high levels of stress. Thus, considerate supervisors achieve from them better performance and reduced turnover. This study tested in a Peruvian call center (N= 255) various hypotheses concerned with the effects of people-oriented leadership on withdrawal behaviors, their moderation by subordinate perceived employability, and the nature of the relationships between withdrawal behaviors. The evidence revealed independence of uncertified absenteeism from turnover intention, negative effects of people-oriented leadership on subordinate turnover intention regardless of subordinate level of employability, and leadership x employability crossover interactive effects on subordinate uncertified absenteeism. Since people-oriented supervision is associated with increased absenteeism among highly employable subordinates and decreased absenteeism among low-employability workers, the effects cancel each other. Thus, there is a need for understanding the underlying determinants as a pre-condition to deriving practical recommendations

Los empleados de los servicios de atención telefónica son propensos a retrasos, absentismo y abandono, debido a que sus trabajos son poco remunerados, de baja cualificación y provocan altos niveles de estrés. Por lo tanto, los supervisores considerados obtienen de ellos un mayor rendimiento y un menor abandono. Este estudio que se llevó a cabo en un servicio de atención telefónica peruano (N= 255) probó varias hipótesis relacionadas con los efectos del liderazgo orientado a personas en el comportamiento de abandono, en la moderación por la empleabilidad percibida de los subordinados y en la naturaleza de la relación entre comportamientos de abandono. La evidencia reveló la independencia entre el absentismo no justificado y la intención de abandono, los efectos negativos del liderazgo orientado a las personas sobre la intención de abandono de los subordinados, independientemente del nivel de empleabilidad y los efectos de interacción cruzada de liderazgo y empleabilidad sobre el absentismo no justificado de los subordinados. Dado que la supervisión orientada a las personas se asocia con un aumento del absentismo en los subordinados de alta empleabilidad y una disminución del absentismo entre los trabajadores de baja empleabilidad, los efectos se anulan mutuamente. Por lo tanto, existe una necesidad de comprender los determinantes subyacentes como una condición previa a la obtención de recomendaciones prácticas

A probabilistic characterization of the relationship between fine particulate matter and mortality: elicitation of European experts.

In support of an assessment of the mortality impacts of the Kuwait Oil Fires we interviewed six European experts in epidemiology and toxicology using formal procedures for elicitation of expert judgment. While the primary focus of the elicitations was to characterize the public health impacts of the fires, the experts provided quantitative estimates of the mortality impacts of hypothetical changes in the levels of ambient fine particulate matter (PM2.5) in both the United States and Europe. Uncertainty was assessed by asking each expert to provide the 5th, 25th, 50th, 75th, and 90th percentiles of their subjective cumulative probability density function for each quantity of interest. The results suggest that many regulatory risk assessments underestimate the impacts of PM2.5 mortality; confirm that only a small fraction of the mortality impact occurs within the first few months after exposure; and indicate that it may be important to better address the differential toxicities of particles from various source classes. By providing quantitative estimates of the uncertainty in current estimates of PM2.5 mortality risks, the study facilitates structured analysis of the value of further research on PM2.5 and its impacts.