The phenotypic expression of QTLs for partial resistance to barley leaf rust during plant development

Partial resistance is generally considered to be a durable form of resistance. In barley, Rphq2, Rphq3 and Rphq4 have been identified as consistent quantitative trait loci (QTLs) for partial resistance to the barley leaf rust pathogen Puccinia hordei. These QTLs have been incorporated separately into the susceptible L94 and the partially resistant Vada barley genetic backgrounds to obtain two sets of near isogenic lines (NILs). Previous studies have shown that these QTLs are not effective at conferring disease resistance in all stages of plant development. In the present study, the two sets of QTL–NILs and the two recurrent parents, L94 and Vada, were evaluated for resistance to P. hordei isolate 1.2.1 simultaneously under greenhouse conditions from the first leaf to the flag leaf stage. Effect of the QTLs on resistance was measured by development rate of the pathogen, expressed as latency period (LP). The data show that Rphq2 prolongs LP at the seedling stage (the first and second leaf stages) but has almost no effect on disease resistance in adult plants. Rphq4 showed no effect on LP until the third leaf stage, whereas Rphq3 is consistently effective at prolonging LP from the first leaf to the flag leaf. The changes in the effectiveness of Rphq2 and Rphq4 happen at the barley tillering stage (the third to fourth leaf stages). These results indicate that multiple disease evaluations of a single plant by repeated inoculations of the fourth leaf to the flag leaf should be conducted to precisely estimate the effect of Rphq4. The present study confirms and describes in detail the plant development-dependent effectiveness of partial resistance genes and, consequently, will enable a more precise evaluation of partial resistance regulation during barley developmen

Social-Role Identity Salience and User Participation in Social Networks

This paper studies the effect of social-role identity salience in social networks on user participation in an online community that facilitates user rating, reviewing and discussing of cultural products. Drawing on previous literature on social preference, we develop a model demonstrating how the salience of friendship identity changes equilibrium participation behaviour. Predictions are tested with a differences-in-differences model using data from an online social network community. Results show evidence of positive effect of salience of friendship identity on user participation

Impact of rainstorm weather on urban road capacity

The rainstorm weather seriously affects the operation of urban traffic, and the surface gathered water and its obstruction to vision lead to a decrease of road capacity. Based on the weather data and coil detector data in Shenzhen, this study compared the urban traffic flow characteristics under rainstorm, light rain, moderate rain and normal weather conditions, and their flow-density relationships were analyzed based on the Green-shields model. Moreover, the road capacity reduction coefficients for urban arterial and sub arterial roads were quantitative calculated respectively. The results can provide theoretical support for the emergency management of urban traffic operation under rainstorm weather

Complete Solution for Vehicle Re-ID in Surround-view Camera System

Vehicle re-identification (Re-ID) is a critical component of the autonomous driving perception system, and research in this area has accelerated in recent years. However, there is yet no perfect solution to the vehicle re-identification issue associated with the car's surround-view camera system. Our analysis identifies two significant issues in the aforementioned scenario: i) It is difficult to identify the same vehicle in many picture frames due to the unique construction of the fisheye camera. ii) The appearance of the same vehicle when seen via the surround vision system's several cameras is rather different. To overcome these issues, we suggest an integrative vehicle Re-ID solution method. On the one hand, we provide a technique for determining the consistency of the tracking box drift with respect to the target. On the other hand, we combine a Re-ID network based on the attention mechanism with spatial limitations to increase performance in situations involving multiple cameras. Finally, our approach combines state-of-the-art accuracy with real-time performance. We will soon make the source code and annotated fisheye dataset available.Comment: 11 pages, 10 figures. arXiv admin note: substantial text overlap with arXiv:2006.1650

A music cognition-guided framework for multi-pitch estimation.

As one of the most important subtasks of automatic music transcription (AMT), multi-pitch estimation (MPE) has been studied extensively for predicting the fundamental frequencies in the frames of audio recordings during the past decade. However, how to use music perception and cognition for MPE has not yet been thoroughly investigated. Motivated by this, this demonstrates how to effectively detect the fundamental frequency and the harmonic structure of polyphonic music using a cognitive framework. Inspired by cognitive neuroscience, an integration of the constant Q transform and a state-of-the-art matrix factorization method called shift-invariant probabilistic latent component analysis (SI-PLCA) are proposed to resolve the polyphonic short-time magnitude log-spectra for multiple pitch estimation and source-specific feature extraction. The cognitions of rhythm, harmonic periodicity and instrument timbre are used to guide the analysis of characterizing contiguous notes and the relationship between fundamental frequency and harmonic frequencies for detecting the pitches from the outcomes of SI-PLCA. In the experiment, we compare the performance of proposed MPE system to a number of existing state-of-the-art approaches (seven weak learning methods and four deep learning methods) on three widely used datasets (i.e. MAPS, BACH10 and TRIOS) in terms of F-measure (F1) values. The experimental results show that the proposed MPE method provides the best overall performance against other existing methods

Variability of the boundary layer over an urban continental site based on 10 years of active remote sensing observations in Warsaw

Atmospheric boundary layer height (ABLH) was observed by the CHM15k ceilometer (January 2008 to October 2013) and the PollyXT lidar (July 2013 to December 2018) over the European Aerosol Research LIdar NETwork to Establish an Aerosol Climatology (EARLINET) site at the Remote Sensing Laboratory (RS-Lab) in Warsaw, Poland. Out of a maximum number of 4017 observational days within this period, a subset of quasi-continuous measurements conducted with these instruments at the same wavelength (1064 nm) was carefully chosen. This provided a data sample of 1841 diurnal cycle ABLH observations. The ABLHs were derived from ceilometer and lidar signals using the wavelet covariance transform method (WCT), gradient method (GDT), and standard deviation method (STD). For comparisons, the rawinsondes of the World Meteorological Organization (WMO 12374 site in Legionowo, 25 km distance to the RS-Lab) were used. The ABLHs derived from rawinsondes by the skew-T-log-p method and the bulk Richardson (bulk-Ri) method had a linear correlation coefficient (R2) of 0.9 and standard deviation (SD) of 0.32 km. A comparison of the ABLHs obtained for different methods and instruments indicated a relatively good agreement. The ABLHs estimated from the rawinsondes with the bulk-Ri method had the highest correlations, R2 of 0.80 and 0.70 with the ABLHs determined using the WCT method on ceilometer and lidar signals, respectively. The three methods applied to the simultaneous, collocated lidar, and ceilometer observations (July to October 2013) showed good agreement, especially for the WCT method (R2 of 0.94, SD of 0.19 km). A scaling threshold-based algorithm was proposed to homogenize ceilometer and lidar datasets, which were applied on the lidar data, and significantly improved the coherence of the results (R2 of 0.98, SD of 0.11 km). The difference of ABLH between clear-sky and cloudy conditions was on average below 230 m for the ceilometer and below 70 m for the lidar retrievals. The statistical analysis of the long-term observations indicated that the monthly mean ABLHs varied throughout the year between 0.6 and 1.8 km. The seasonal mean ABLH was of 1.16 ± 0.16 km in spring, 1.34 ± 0.15 km in summer, 0.99 ± 0.11 km in autumn, and 0.73 ± 0.08 km in winter. In spring and summer, the daytime and nighttime ABLHs appeared mainly in a frequency distribution range of 0.6 to 1.0 km. In winter, the distribution was common between 0.2 and 0.6 km. In autumn, it was relatively balanced between 0.2 and 1.2 km. The annual mean ABLHs maintained between 0.77 and 1.16 km, whereby the mean heights of the well-mixed, residual, and nocturnal layer were 1.14 ± 0.11, 1.27 ± 0.09, and 0.71 ± 0.06 km, respectively (for clear-sky conditions). For the whole observation period, the ABLHs below 1 km constituted more than 60% of the retrievals. A strong seasonal change of the monthly mean ABLH diurnal cycle was evident; a mild weakly defined autumn diurnal cycle, followed by a somewhat flat winter diurnal cycle, then a sharp transition to a spring diurnal cycle, and a high bell-like summer diurnal cycle. A prolonged summertime was manifested by the September cycle being more similar to the summer than autumn cycles