Abstract

To better solve the complex non-linear problem between the subjective sound quality evaluation results and objective psychoacoustics parameters, a method for the prediction of the sound quality is put forward by using a back propagation neural network (BPNN) based on particle swarm optimization (PSO), which is optimizing the initial weights and thresholds of BP network neurons through the PSO. In order to verify the effectiveness and accuracy of this approach, the noise signals of the B-Class vehicles from the idle speed to 120 km h−1 measured by the artificial head, are taken as a target. In addition, this paper describes a subjective evaluation experiment on the sound quality annoyance inside the vehicles through a grade evaluation method, by which the annoyance of each sample is obtained. With the use of Artemis software, the main objective psychoacoustic parameters of each noise sample are calculated. These parameters include loudness, sharpness, roughness, fluctuation, tonality, articulation index (AI) and A-weighted sound pressure level. Furthermore, three evaluation models with the same artificial neural network (ANN) structure are built: the standard BPNN model, the genetic algorithm-back-propagation neural network (GA-BPNN) model and the PSO-back-propagation neural network (PSO-BPNN) model. After the network training and the evaluation prediction on the three models’ network based on experimental data, it proves that the PSO-BPNN method can achieve convergence more quickly and improve the prediction accuracy of sound quality, which can further lay a foundation for the control of the sound quality inside vehicles.

Diachronic analysis showed no significant changes in the level of genetic diversity occurred over the past 27 years' domestication, which indicated genetic diversity was successfully maintained under on-farm conservation. Rice (Oryza sativa L.) is one of the earliest domesticated crop species. Its genetic diversity has been declining as a result of natural and artificial selection. In this study, we performed the first analysis of the levels and patterns of nucleotide variation in rice genomes under on-farm conservation in Yunnan during a 27-year period of domestication. We performed large-scale sequencing of 600 rice accessions with high diversity, which were collected in 1980 and 2007, using ten unlinked nuclear loci. Diachronic analysis showed no significant changes in the level of genetic diversity occurring over the past 27 years' domestication, which indicated genetic diversity was successfully maintained under on-farm conservation. Population structure revealed that the rice landraces could be grouped into two subpopulations, namely the indica and japonica groups. Interestingly, the alternate distribution of indica and japonica rice landraces could be found in each ecological zone. The results of AMOVA showed that on-farm conservation provides opportunities for continued differentiation and variation of landraces. Therefore, dynamic conservation measures such as on-farm conservation (which is a backup, complementary strategy to ex situ conservation) should be encouraged and enhanced, especially in crop genetic diversity centers. The results of this study offered accurate insights into short-term evolutionary processes and provided a scientific basis for on-farm management practices.

No abstract

Traditional rice landraces grown under on-farm conservation conditions by indigenous farmers are extremely important for future crop improvement. However, little is known about how the natural selection and agriculture practices of indigenous farmers interact to shape and change the population genetics of rice landraces grown under on-farm conservation conditions during the domestication. In this study, we sequenced DNA from 108 core on-farm conserved rice landraces collected from the ethnic minority regions of Yunnan, China, including 56 accessions collected in 1980 and 52 accessions collected in 2007 and obtained 2,771,245 of credible SNPs. Our findings show that most genetic diversity was retained during the 27 years of domestication by on-farm conservation. However, SNPs with marked allele frequency differences were found in some genome regions, particularly enriched in genic regions,indicating changes in genic regions may have played a much more prominent role in the short-term domestication of 27 years. We identified 186 and 183 potential selective-sweep regions in the indica and japonica genomes, respectively. We propose that on-farm conserved rice landraces during the short-term domestication had a highly polygenic basis with many loci responding to selection rather than a few loci with critical changes in response to selection. Moreover, loci affecting important agronomic traits and biotic or abiotic stress responses have been particularly targeted in selection. A genome-wide association study identified 90 significant signals for six traits, 13 of which were in regions of selective sweeps. Moreover, we observed | 291 CUI et al.