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Description: IJERPH, Vol. 15, Pages 1142: Validity of a Short Food Frequency Questionnaire Assessing Macronutrient and Fiber Intakes in Patients of Han Chinese Descent with Type 2 Diabetes International Journal of Environmental Research and Public Health doi: 10.3390/ijerph15061142 Authors: Meng-Chuan Huang Kun-Der Lin Hung-Jiun Chen Yu-Ju Wu Chiao-I Chang Shyi-Jang Shin Hsin-Chia Hung Chien-Hung Lee Ya-Fang Huang Chih-Cheng Hsu Few food frequency questionnaires (FFQs) have been developed to assess diet in diabetes patients. This cross-sectional study examined the validity of a 45-item FFQ assessing the intake of macronutrients against three 24-h dietary recalls (24-HDRs) in Taiwan, and compared vegetable and fruit intakes with carotenoid biomarkers. We recruited 126 adults with type 2 diabetes who completed the FFQ and three 24-HDRs administered by a registered dietitian. We measured plasma carotenoids (α-carotene, β-carotene and lutein) in 71 subjects. Partial Pearson correlation coefficients derived from the FFQs and three 24-HDRs and adjusted for energy were of 0.651, 0.587, 0.639 and 0.664 for protein, fat, carbohydrate and fiber, respectively. Cross-classification analysis revealed that 71.5–81% of the macronutrients and fiber were categorized into the same or adjacent quartiles by the FFQ and 24-HDRs. Bland–Altman plots revealed good agreement for energy/macronutrients/fiber across the range of intakes. Multiple linear regression of backward elimination revealed that tertile levels of dark- or light-colored vegetables obtained by the FFQ were significantly associated with plasma α-carotene and β-carotene, but not lutein. Fruit consumption did not correlate with carotenoid biomarkers. In conclusion, this short FFQ provided a valid assessment of macronutrients and fiber intake in type 2 diabetes patients. Vegetable consumption estimated by the FFQ corresponded to plasma α-carotene and β-carotene concentrations.

Description: Energies, Vol. 10, Pages 1456: Analysis of Voltage Variation in Silicon Carbide MOSFETs during Turn-On and Turn-Off Energies doi: 10.3390/en10101456 Authors: Hui Li Xinglin Liao Yaogang Hu Zhangjian Huang Kun Wang Due to our limited knowledge about silicon carbide metal–oxide–semiconductor field-effect transistors (SiC MOSFETs), the theoretical analysis and change regularity in terms of the effects of temperature on their switching characteristics have not been fully characterized and understood. An analysis of variation in voltage (dVDS/dt) for SiC MOSFET during turn-on and turn-off has been performed theoretically and experimentally in this paper. Turn-off variation in voltage is not a strong function of temperature, whereas the turn-on variation in voltage has a monotonic relationship with temperature. The temperature dependence is a result of the competing effects between the positive temperature coefficient of the intrinsic carrier concentration and the negative temperature coefficient of the effective mobility of the electrons in SiC MOSFETs. The relationship between variation in voltage and supply voltage, load current, and gate resistance are also discussed. A temperature-based analytical model of dVDS/dt for SiC MOSFETs was derived in terms of internal parasitic capacitances during the charging and discharging processes at the voltage fall period during turn-on, and the rise period during turn-off. The calculation results were close to the experimental measurements. These results provide a potential junction temperature estimation approach for SiC MOSFETs. In SiC MOSFET-based practical applications, if the turn on dVDS/dt is sensed, the device temperature can be estimated from the relationship curve of turn on dVDS/dt versus temperature drawn in advance.

Description: Sustainability, Vol. 9, Pages 1259: The Effects of Greenbelt Policies on Land Development: Evidence from the Deregulation of the Greenbelt in the Seoul Metropolitan Area Sustainability doi: 10.3390/su9071259 Authors: Haoying Han Chen Huang Kun-Hyuck Ahn Xianfan Shu Liyun Lin Derong Qiu Greenbelt policies are important urban containment policies. On the one hand, they can effectively control the disorderly growth of a city; on the other hand, they can cause other social problems because of their strict control over land development. This paper uses data from 2000 and 2010 and the difference-in-differences (DID) method to evaluate the effects of greenbelt deregulation policies on urban land development in the Seoul metropolitan area (SMA) through a quasi-natural experiment. The results show that first, the deregulation of the greenbelt has significantly furthered urban land development that was not caused by economic development or other factors. Second, the greenbelt deregulation had no significant effects on urban land development in the city centers, but has furthered urban land development near the boundary of Seoul City and greenbelt boundaries. Third, in terms of the effects on land development, the greenbelt deregulation has resulted in regional heterogeneity. Specifically, the greenbelt deregulation has had a significant impact on the urban land development in the southern section of the Han River, whereas the effects of the greenbelt deregulation in the northern area of the Han River are not as obvious.

Description: Sensors, Vol. 18, Pages 94: Integrated Temperature and Hydrogen Sensors with MEMS Technology Sensors doi: 10.3390/s18010094 Authors: Hongchuan Jiang Min Huang Yibing Yu Xiaoyu Tian Xiaohui Zhao Wanli Zhang Jianfeng Zhang Yifan Huang Kun Yu In this work, a PdNi thin film hydrogen gas sensor with integrated Pt thin film temperature sensor was designed and fabricated using the micro-electro-mechanical system (MEMS) process. The integrated sensors consist of two resistors: the former, based on Pt film, is used as a temperature sensor, while the latter had the function of hydrogen sensing and is based on PdNi alloy film. The temperature coefficient of resistance (TCR) in both devices was measured and the output response of the PdNi film hydrogen sensor was calibrated based on the temperature acquired by the Pt temperature sensor. The SiN layer was deposited on top of Pt film to inhibit the hydrogen diffusion and reduce consequent disturbance on temperature measurement. The TCR of the PdNi film and the Pt film was about 0.00122/K and 0.00217/K, respectively. The performances of the PdNi film hydrogen sensor were investigated with hydrogen concentrations from 0.3% to 3% on different temperatures from 294.7 to 302.2 K. With the measured temperature of the Pt resistor and the TCR of the PdNi film, the impact of the temperature on the performances of the PdNi film hydrogen sensor was reduced. The output response, response time and recovery time of the PdNi film hydrogen sensors under the hydrogen concentration of 0.5%, 1.0%, 1.5% and 2.0% were measured at 313 K. The output response of the PdNi thin film hydrogen sensors increased with increasing hydrogen concentration while the response time and recovery time decreased. A cycling test between pure nitrogen and 3% hydrogen concentration was performed at 313 K and PdNi thin film hydrogen sensor demonstrated great repeatability in the cycling test.

Description: Sensors, Vol. 18, Pages 388: Feature Extraction of Electronic Nose Signals Using QPSO-Based Multiple KFDA Signal Processing Sensors doi: 10.3390/s18020388 Authors: Tailai Wen Jia Yan Daoyu Huang Kun Lu Changjian Deng Tanyue Zeng Song Yu Zhiyi He The aim of this research was to enhance the classification accuracy of an electronic nose (E-nose) in different detecting applications. During the learning process of the E-nose to predict the types of different odors, the prediction accuracy was not quite satisfying because the raw features extracted from sensors’ responses were regarded as the input of a classifier without any feature extraction processing. Therefore, in order to obtain more useful information and improve the E-nose’s classification accuracy, in this paper, a Weighted Kernels Fisher Discriminant Analysis (WKFDA) combined with Quantum-behaved Particle Swarm Optimization (QPSO), i.e., QWKFDA, was presented to reprocess the original feature matrix. In addition, we have also compared the proposed method with quite a few previously existing ones including Principal Component Analysis (PCA), Locality Preserving Projections (LPP), Fisher Discriminant Analysis (FDA) and Kernels Fisher Discriminant Analysis (KFDA). Experimental results proved that QWKFDA is an effective feature extraction method for E-nose in predicting the types of wound infection and inflammable gases, which shared much higher classification accuracy than those of the contrast methods.