The changes in carotid artery structure during the natural longevity of the Uighurs people were compared with other ethnic groups. The 419 subjects were divided into (1) longevity and (2) older groups as follows: Uighurs longevity group in Hotan (ULH); and Uighurs, Hans and Kazaks older groups in Hotan or Balikun (UOH, HOH, HOB and KOB). The wall thickness of the common carotid artery (CCA) was measured by ultrasonography. Risk factors were evaluated by measuring total cholesterol (T-C), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), triglyceride (TG) and fasting glucose, and by 24-h ambulatory blood pressure monitoring. Wall thickness and blood pressure were greater in the Balikun groups than in the Hotan groups. The CCA wall was thicker in Uighurs and Kazaks than in Hans, in the ULH than in the UOH. There was no significant difference in blood pressure among the Hotan groups. LDL-C and glucose were higher and HDL-C was lower in the Hotan groups than in the Balikun groups. T-C, LDL-C, TG and glucose were higher in the HOH than in the ULH and UOH. Systolic blood pressure and LDL-C were higher and TG was lower in the KOB than in the HOB. These results suggest that an increased CCA wall thickness can be attributed to age in Hotan, and to a higher blood pressure level in Balikun, and that the higher blood pressure affected the Balikun groups more than the Hotan groups.

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An improved optimization adjustment strategy for building heating ventilation and air conditioning (Heating Ventilation and Air Conditioning, HVAC) is proposed. The energy consumption model of building heating/refrigeration is established by using the instantaneous energy balance of heat, and then the optimal operation strategy of building HVAC energy based on weather forecast data is constructed in the range of user temperature comfort. Finally, the MATLAB and TRNSYS simulation techniques are used to verify the example. Simulation results show that the optimal operation strategy of building HVAC energy based on weather forecast data can not only significantly reduce the cost of energy use, but also effectively improve the absorption capacity of renewable energy on the building side.

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In this paper, regression-tree based spectral peak alignment is proposed for rapid speaker adaptation using the linearization of VTLN. Two different regression classes are investigated: phonetic classes (using combined knowledge and data-driven techniques) and mixture classes. Compared to MLLR and VTLN, improved performance can be obtained for both supervised and unsupervised adaptations on both medium vocabulary and connected digits recognition tasks. To further improve the performance, MLLR was integrated into this regression-tree based peak alignment. Experimental results show that the performance improvements can be achieved even with limited adaptation data.