Radon and moisture impacts from interventions integrated with housing energy retrofits.

Energy retrofits can reduce air exchange, raising the concern of whether indoor radon and moisture levels could increase. This pre/post-intervention study explored whether simple radon interventions implemented in conjunction with energy retrofits can prevent increases in radon and moisture levels. Treatment homes (n = 98) were matched with control (no energy retrofits or radon intervention) homes (n = 12). Control homes were matched by geographic location and foundation type. t-tests were used to determine whether post-energy retrofit radon and moisture level changes in treatment homes significantly differed from those in control homes. The radon interventions succeeded in preventing statistically significant increases in first floor radon using arithmetic (p = 0.749) and geometric means (p = 0.120). In basements, arithmetic (p = 0.060) and geometric (p = 0.092) mean radon levels statistically significantly increased, consistent with previous studies which found that basement radon levels may increase even if first floor levels remain unchanged. Changes in infiltration were related to changes in radon (p = 0.057 in basements; p = 0.066 on first floors). Only 58% of the change in infiltration was due to air sealing, with the rest due to weather changes. There was no statistically significant association between air sealing itself and radon levels on the first floor (p = 0.664). Moisture levels also did not significantly increase.

Sensor fault diagnosis of aero-engine based on divided flight status.

Fault diagnosis and safety analysis of an aero-engine have attracted more and more attention in modern society, whose safety directly affects the flight safety of an aircraft. In this paper, the problem concerning sensor fault diagnosis is investigated for an aero-engine during the whole flight process. Considering that the aero-engine is always working in different status through the whole flight process, a flight status division-based sensor fault diagnosis method is presented to improve fault diagnosis precision for the aero-engine. First, aero-engine status is partitioned according to normal sensor data during the whole flight process through the clustering algorithm. Based on that, a diagnosis model is built for each status using the principal component analysis algorithm. Finally, the sensors are monitored using the built diagnosis models by identifying the aero-engine status. The simulation result illustrates the effectiveness of the proposed method.

[Comparison study on the methods for finding borders between coding and non-coding DNA regions in rice].

Entropy-based divergence measures have provided an impelling tool in evaluating sequence complexity, predicting CpG island, and detecting borders between coding and non-coding DNA regions etc. In this paper, two new divergence measures: the alpha-KL divergence and the alpha-Jensen-Shannon divergence were defined and a coarse-graining vector of amino acids- corresponding codons was proposed according to codons GC-content, in order to improve the computational approach to finding borders between coding and non-coding in rice. A comparison of the accuracies gained by different vectors (the Jensen-Shannon divergence, the Jensen-Renyi divergence, the alpha-KL divergence and the alpha-Jensen -Shannon divergence) showed that recognition efficiency based on the new information measures with the vector coarse-graining increase by 4-5 times than that of Bernaola's method in the 'stop codon' of coding regions in rice.

Molecular phylogeny of coronaviruses including human SARS-CoV.

Phylogenetic tree of coronaviruses (CoVs) including the human SARS-associated virus is reconstructed from complete genomes by using our newly developed K-string composition approach. The relation of the human SARS-CoV to other coronaviruses, i.e. the rooting of the tree is suggested by choosing an appropriate outgroup. SARS-CoV makes a separate group closer but still distant from G2 (CoVs in mammalian host). The relation between different isolates of the human SARS virus is inferred by first constructing an ultrametric distance matrix from counting sequence variations in the genomes. The resulting tree is consistent with clinic relations between the SARS-CoV isolates. In addition to a larger variety of coronavirus genomes these results provide phylogenetic knowledge based on independent novel methodology as compared to recent phylogenetic studies on SARS-CoV.