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Articles by Q. Yang
Total Records ( 3 ) for Q. Yang
  Z. Zhao , Q. Yang , G. Benoy , T.L. Chow , Z. Xing , H.W. Rees and F.-R Meng
  Soil organic carbon (SOC) content is an important soil quality indicator that plays an important role in regulating physical, chemical and biological properties of soil. Field assessment of SOC is time consuming and expensive. It is difficult to obtain high-resolution SOC distribution maps that are needed for landscape analysis of large areas. An artificial neural network (ANN) model was developed to predict SOC based on parameters derived from digital elevation model (DEM) together with soil properties extracted from widely available coarse resolution soil maps (1:1 000 000 scale). Field estimated SOC content data extracted from high-resolution soil maps (1:10 000 scale) in Black Brook Watershed in northwestern New Brunswick, Canada, were used to calibrate and validate the model. We found that vertical slope position (VSP) was the most important variable that determines distributions of SOC across the landscape. Other variables such as slope steepness, and potential solar radiation (PSR) also had significant influence on SOC distributions. The prediction of the selected two-input-node SOC model (VSP and coarse resolution soil map recorded SOC as inputs) had a correlation coefficient of 0.92 with measured values, and model predicted SOC values had 47.9% of the total points within ±0.5% of the measured values and 70.6% within ±1% of the measured values. The prediction od the selected four-input-node model (VSP, slope steepness, PSR and coarse resolution SOC values as inputs) had a correlation coefficient of 0.98 with measured values and model predicted SOC values had 75% of the total points within ±0.5% of the measured values and 87% within ±1% of the measured values. The prediction of the five-input-nodes model with soil drainage as additional input had a correlation coefficient of 0.99 with measured values, and model predicted SOC values had 87% of the total points within ±0.5% of the measured values and 98% of the total points within ±1% of the measured values. The calibrated SOC prediction model was used to produce a high-resolution SOC map for the Black Brook Watershed and the resulting SOC distribution map is considered to be realistic. Results indicated that DEM-derived hydrological parameters together with widely available coarse resolution soil map data could be used to produce high-resolution SOC maps with the ANN method.
  P Wang , J Liu , Y Li , S Wu , J Luo , H Yang , R Subbiah , J Chatham , O Zhelyabovska and Q. Yang

Rationale: Peroxisome proliferator-activated receptors (PPARs) (, , and /β) are nuclear hormone receptors and ligand-activated transcription factors that serve as key determinants of myocardial fatty acid metabolism. Long-term cardiomyocyte-restricted PPAR deficiency in mice leads to depressed myocardial fatty acid oxidation, bioenergetics, and premature death with lipotoxic cardiomyopathy.

Objective: To explore the essential role of PPAR in the adult heart.

Methods and Results: We investigated the consequences of inducible short-term PPAR knockout in the adult mouse heart. In addition to a substantial transcriptional downregulation of lipid metabolic proteins, short-term PPAR knockout in the adult mouse heart attenuated cardiac expression of both Cu/Zn superoxide dismutase and manganese superoxide dismutase, leading to increased oxidative damage to the heart. Moreover, expression of key mitochondrial biogenesis determinants such as PPAR coactivator-1 were substantially decreased in the short-term PPAR deficient heart, concomitant with a decreased mitochondrial DNA copy number. Rates of palmitate and glucose oxidation were markedly depressed in cardiomyocytes of PPAR knockout hearts. Consequently, PPAR deficiency in the adult heart led to depressed cardiac performance and cardiac hypertrophy.

Conclusions: PPAR is an essential regulator of cardiac mitochondrial protection and biogenesis and PPAR activation can be a potential therapeutic target for cardiac disorders.

  Y.S. Li , Y. Tang , Q. Yang , C. Xiao and A. Hirose
  Synthesis of diamond thin films on aluminum and aluminum-modified Si and steel substrates has been performed at 450 °C with 1%CH4–99%H2 gas mixture in a microwave plasma enhanced chemical vapor deposition (CVD) reactor. A diamond scratching pre-treatment of bulk Al substrate or Al-interlayered Si/steel substrates greatly enhances diamond nucleation, and the diamond films directly synthesized on Al substrate are well faceted, continuous and densely packed. The diamond films synthesized on conventional Fe–Cr and Fe–Cr–Ni type steels are generally of poor quality due to preferential formation of graphitic carbons catalyzed by the base metal iron. An Al thin film interlayer applied on those steel surfaces has markedly enhanced the nucleation and adhesion properties of diamond films, and a direct alloying addition of Al to these steel substrates also promotes the formation of continuous, dense and adherent diamond films.
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