Design of a hemispherical shell shaped natural ventilation temperature observation instrument.

Atmospheric temperature is fundamental information for various industries, such as production, life, and scientific research. The temperature error induced by the solar rays can reach 1 °C or even higher. A hemispherical shell-shaped atmospheric temperature measuring instrument that can reduce heat pollution and increase air velocity was designed. First, the instrument was optimized using computational fluid dynamics (CFD) software packages. Then, the CFD software packages were employed to quantify the temperature errors of the instrument with varying situations. A neural network model was employed to develop a temperature error correction model that can be targeted for multi-variable changes. This model provides accurate correction data when the influencing factors change continuously. Finally, field experiments were performed. The experimental data analysis indicates that the mean temperature error and the maximum error of the instrument before correction are 0.08 and 0.25 °C, respectively. The root mean square error, the mean absolute error, and the correlation coefficient between measured temperature errors from experiments and corrected temperature errors from the correction model are 0.099, 0.016, and 0.952 °C, respectively. By utilizing a temperature error correction model, the measuring error of the instrument can be minimized to a range between -0.05 and 0.04 °C. Consequently, the instrument is anticipated to enhance temperature measurement accuracy to ∼0.1 °C.

Population genetic structure and evolutionary history of Psammochloa villosa (Trin.) Bor (Poaceae) revealed by AFLP marker.

Psammochloa villosa is an ecologically important desert grass that occurs in the Inner Mongolian Plateau where it is frequently the dominant species and is involved in sand stabilization and wind breaking. We sought to generate a preliminary demographic framework for P. villosa to support the future studies of this species, its conservation, and sustainable utilization. To accomplish this, we characterized the genetic diversity and structure of 210 individuals from 43 natural populations of P. villosa using amplified fragment length polymorphism (AFLP) markers. We obtained 1,728 well-defined amplified bands from eight pairs of primers, of which 1,654 bands (95.7%) were polymorphic. Results obtained from the AFLPs suggested effective alleles among populations of 1.32, a Nei's standard genetic distance value of 0.206, a Shannon index of 0.332, a coefficient of gene differentiation (G ST) of 0.469, and a gene flow parameter (Nm) of 0.576. All these values indicate that there is abundant genetic diversity in P. villosa, but limited gene flow. An analysis of molecular variance (AMOVA) showed that genetic variation mainly exists within populations (64.2%), and we found that the most genetically similar populations were often not geographically adjacent. Thus, this suggests that the mechanisms of gene flow are surprisingly complex in this species and may occur over long distances. In addition, we predicted the distribution dynamics of P. villosa based on the spatial distribution modeling and found that its range has contracted continuously since the last interglacial period. We speculate that dry, cold climates have been critical in determining the geographic distribution of P. villosa during the Quaternary period. Our study provides new insights into the population genetics and evolutionary history of P. villosa in the Inner Mongolian Plateau and provides a resource that can be used to design in situ conservation actions and prioritize sustainable utilization.