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The special features inherent in the development of high-temperature deformation and structural evolution in materials are investigated, using a VT22 titanium alloy of the transition class (Ti - 4.74 mass% Al - 5.57 mass% Mo - 5.04 mass% V) subjected to helical rolling + aging as an example. This treatment is found to give rise to an intragrain fine acicular martensite structure with fine inclusions of α-phase particles of size ~1 μm. It is shown that in the alloy undergoing plastic deformation at temperatures approaching the polymorphic transformation temperature, the elongation to failure is in excess of 300%. The high plasticity of the alloy in the conditions considered is likely to be due to vigorous development of phase transformations and intensification of diffusion-controlled processes, including the effects of the evolution of the dislocation structure, growth of subgrains, and formation of new grains in the bulk of the pre-existing ones during plastic deformation. [ABSTRACT FROM AUTHOR]

Previous studies have found that both high temperature and low temperature increase the risk of childhood hand, foot and mouth disease (HFMD). However, little is known about whether temperature variation between neighboring days has any effects on childhood HFMD. A Poisson generalized linear regression model, combined with a distributed lag non-linear model, was applied to examine the relationship between temperature change and childhood HFMD in Hefei, China, from 1st January 2010 to 31st December 2012. Temperature change was defined as the difference of current day's mean temperature and previous day's mean temperature. Late spring and early summer (April-July) were chosen as the main study period due to it having the highest childhood HFMD incidence. There was a statistical association between temperature change between neighboring days and childhood HFMD. The effects of temperature change on childhood HFMD increased below a temperature change of 0 °C (temperature drop). The temperature change has the greatest adverse effect on childhood HFMD at 7 days lag, with 4 % (95 % confidence interval 2-7 %) increase per 3 °C drop of temperature. Male children and urban children appeared to be more vulnerable to the effects of temperature change. Temperature change between adjacent days might be an alternative temperature indictor for exploring the temperature-HFMD relationship. [ABSTRACT FROM AUTHOR]

In this paper, we present the application of neuro-fuzzy system-ANFIS for air conditioning systems to reduce electricity consumption. The current buildings have automation systems that provide data on lighting, electrical system, air conditioning system, etc. We studied the air conditioning system, in particular, to reduce energy consumption as air conditioning has a high consumption value. Our main goal in this study is the application of neuro-fuzzy system-ANFIS with the adjustment of the rules made by a decision tree-CART algorithm in air conditioning system. We compared the results of the application of the ANFIS-CART system with the application of PID controllers and fuzzy control system for a central air conditioning. [ABSTRACT FROM AUTHOR]

The integration of three-dimensional spatial distributions into building simulations is of significant interest, and computational fluid dynamics (CFD) analysis is widely employed in building design processes. For example, based on the experience of architects and engineers, CFD analyses are often conducted under steady boundary conditions to determine the degree of attainment of indoor environments. However, CFD analyses have large calculation costs and cannot be often used for simulations with unsteady boundary conditions such as energy simulations in the building design processes. Thus, we developed a method that calculates sensitivities from heat sources to an arbitrary point in an indoor environment and integrates them into simulations with unsteady boundary conditions. In the proposed method, CFD analysis is employed under steady boundary conditions to calculate the response factors, and the resulting sensitivities are integrated into simulations under unsteady boundary conditions. In the present study, the proposed method was applied to optimize the variables of an air conditioning control system. With our method, temperature changes at a sensor over time are calculated from the time series of air supply temperature. In total, 800 calculations were conducted, and the optimal variables that allow the temperature at the sensor to reach the target value quickly were obtained. Except for the time required to calculate the response factors, the optimization in the present study took only a few seconds. If only CFD analysis was used for the optimization, the calculations would take a year. Thus, calculating the sensitivities via CFD analysis and utilizing the results in simulations is a useful approach for solving optimization problems. Moreover, the proposed method is applicable to simulations that require three-dimensional spatial distributions to enhance the accuracy of the calculation such as energy simulations. [ABSTRACT FROM AUTHOR]