Evaluation of MODIS Land Surface Temperature Data to Estimate Near-Surface Air Temperature in Northeast China

Air temperature (Tair) near the ground surface is a fundamental descriptor of terrestrial environment conditions and one of the most widely used climatic variables in global change studies. The main objective of this study was to explore the possibility of retrieving high-resolution Tair from the Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) products, covering complex terrain in Northeast China. The All Subsets Regression (ASR) method was adopted to select the predictors and build optimal multiple linear regression models for estimating maximum (Tmax), minimum (Tmin), and mean (Tmean) air temperatures. The relative importance of predictors in these models was evaluated via the Standardized Regression Coefficients (SRCs) method. The results indicated that the optimal models could estimate the Tmax, Tmin, and Tmean with relatively high accuracies (Model Efficiency ≥ 0.90). Both LST and day length (DL) predictors were important in estimating Tmax (SRCs: daytime LST = 0.53, DL = 0.35), Tmin (SRCs: nighttime LST = 0.74, DL = 0.23), and Tmean (SRCs: nighttime LST = 0.72, DL = 0.28). Models predicting Tmin and Tmean had better performance than the one predicting Tmax. Nighttime LST was better at predicting Tmin and Tmean than daytime LST data at predicting Tmax. Land covers had noticeable influences on estimating Tair, and even seasonal vegetation greening could result in temporal variations of model performance. Air temperature could be accurately estimated using remote sensing, but the model performance was varied across different spatial and temporal scales. More predictors should be incorporated for the purpose of improving the estimation of near surface Tair from the MODIS LST production

Does Environment Filtering or Seed Limitation Determine Post-Fire Forest Recovery Patterns in Boreal Larch Forests?

Wildfire is a primary natural disturbance in boreal forests, and post-fire vegetation recovery rate influences carbon, water, and energy exchange between the land and atmosphere in the region. Seed availability and environmental filtering are two important determinants in regulating post-fire vegetation recovery in boreal forests. Quantifying how these determinants change over time is helpful for understanding post-fire forest successional trajectory. Time series of remote sensing data offer considerable potential in monitoring the trajectory of post-fire vegetation recovery dynamics beyond current field surveys about structural attributes, which generally lack a temporal perspective across large burned areas. We used a time series of the normalized difference vegetation index (NDVI) and normalized difference shortwave infrared reflectance index (NDSWIR) derived from Landsat images to investigate post-fire dynamics in a Chinese boreal larch forest. An adjacent, unburned patch of a similar forest type and environmental conditions was selected as a control to separate interannual fluctuation in NDVI and NDSWIR caused by climate from changes due to wildfire. Temporal anomalies in NDVI and NDSWIR showed that more than 10 years were needed for ecosystems to recover to a pre-fire state. The boosted regression tree analysis showed that fire severity exerted a persistent, dominant influence on vegetation recovery during the early post-fire successional stage and explained more than 60% of variation in vegetation recovery, whereas distance to the nearest unburned area and environmental conditions exhibited a relatively small influence. This result indicated that the legacy effects of fire disturbance, which control seed availability for tree recruitment, would persist for decades. The influence of environmental filtering could increase with succession and could mitigate the initial heterogeneity in recovery caused by wildfire

Origin of the different conductive behavior in pentavalent-ion-doped anatase and rutile TiO2_2

The electronic properties of pentavalent-ion (Nb$^{5+}$, Ta$^{5+}$, and I$^{5+}$) doped anatase and rutile TiO$_2$ are studied using spin-polarized GGA+\emph{U} calculations. Our calculated results indicate that these two phases of TiO$_2$ exhibit different conductive behavior upon doping. For doped anatase TiO$_2$, some up-spin-polarized Ti 3\emph{d} states lie near the conduction band bottom and cross the Fermi level, showing an \emph{n}-type half-metallic character. For doped rutile TiO$_2$, the Fermi level is pinned between two up-spin-polarized Ti 3\emph{d} gap states, showing an insulating character. These results can account well for the experimental different electronic transport properties in Nb (Ta)-doped anatase and rutile TiO$_2$.Comment: 4 pages, 5 figure

STAT5a/b contribute to sex bias in vascular disease: A neuroendocrine perspective

Previous studies have elucidated a neuroendocrine mechanism consisting of the hypothalamus (growth hormone releasing hormone, GHRH) – pituitary (growth hormone, GH) – STAT5a/b axis that underlies sex-biased gene expression in the liver. It is now established that male vs female patterned secretion of GHRH, and thus of circulating GH levels (“pulsatile” vs “more continuous” respectively), leading to differently patterned activation of PY-STAT5a/b in hepatocytes results in sex-biased gene expression of cohorts of hundreds of downstream genes. This review outlines new data in support of a STAT5a/b-based mechanism of sex bias in the vascular disease pulmonary hypertension (PH). Puzzling observations in PH include its 2-4-fold higher prevalence in women but a male-dominance in many rodent models, and, paradoxically, inhibition of PH development by estrogens in such models. We observed that conditional deletion of STAT5a/b in vascular smooth muscle cells (SMC) in mice converted the male-dominant model of chronic hypoxia-induced PH into a female-dominant phenotype. In human idiopathic PH, there was reduced STAT5a/b and PY-STAT5 in cells in late-stage obliterative pulmonary arterial lesions in both men and women. A juxtaposition of the prior liver data with the newer PH-related data drew attention to the hypothalamus-GH-STAT5 axis, which is the major target of estrogens at the level of the hypothalamus. This hypothesis explains many of the puzzling aspects of sex bias in PH in humans and rodent models. The extension of STAT5-anchored mechanisms of sex bias to vascular disease emphasizes the contribution of central neuroendocrine processes in generating sexual dimorphism in different tissues and cell types

H-Dihyperon in Quark Cluster Model

The H dihyperon (DH) is studied in the framework of the SU(3) chiral quark model. It is shown that except the $\sigma$ chiral field, the overall effect of the other SU(3) chiral fields is destructive in forming a stable DH. The resultant mass of DH in a three coupled channel calculation is ranged from 2225 $MeV$ to 2234 $MeV$.Comment: 9 pages, emte