A general statistical framework for dissecting parent-of-origin effects underlying endosperm traits in flowering plants

Genomic imprinting has been thought to play an important role in seed development in flowering plants. Seed in a flowering plant normally contains diploid embryo and triploid endosperm. Empirical studies have shown that some economically important endosperm traits are genetically controlled by imprinted genes. However, the exact number and location of the imprinted genes are largely unknown due to the lack of efficient statistical mapping methods. Here we propose a general statistical variance components framework by utilizing the natural information of sex-specific allelic sharing among sibpairs in line crosses, to map imprinted quantitative trait loci (iQTL) underlying endosperm traits. We propose a new variance components partition method considering the unique characteristic of the triploid endosperm genome, and develop a restricted maximum likelihood estimation method in an interval scan for estimating and testing genome-wide iQTL effects. Cytoplasmic maternal effect which is thought to have primary influences on yield and grain quality is also considered when testing for genomic imprinting. Extension to multiple iQTL analysis is proposed. Asymptotic distribution of the likelihood ratio test for testing the variance components under irregular conditions are studied. Both simulation study and real data analysis indicate good performance and powerfulness of the developed approach.Comment: Published in at http://dx.doi.org/10.1214/09-AOAS323 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Learning Residual Model of Model Predictive Control via Random Forests for Autonomous Driving

One major issue in learning-based model predictive control (MPC) for autonomous driving is the contradiction between the system model's prediction accuracy and computation efficiency. The more situations a system model covers, the more complex it is, along with highly nonlinear and nonconvex properties. These issues make the optimization too complicated to solve and render real-time control impractical.To address these issues, we propose a hierarchical learning residual model which leverages random forests and linear regression.The learned model consists of two levels. The low level uses linear regression to fit the residues, and the high level uses random forests to switch different linear models. Meanwhile, we adopt the linear dynamic bicycle model with error states as the nominal model.The switched linear regression model is added to the nominal model to form the system model. It reformulates the learning-based MPC as a quadratic program (QP) problem and optimization solvers can effectively solve it. Experimental path tracking results show that the driving vehicle's prediction accuracy and tracking accuracy are significantly improved compared with the nominal MPC.Compared with the state-of-the-art Gaussian process-based nonlinear model predictive control (GP-NMPC), our method gets better performance on tracking accuracy while maintaining a lower computation consumption.Comment: 8 pages, 8 figure

A Novel Approach to Wideband Spectrum Compressive Sensing Based on DST for Frequency Availability in LEO Mobile Satellite Systems

In LEO mobile satellite network, the L/S frequency availability is an essential task for global communication but entails several major technical challenges: high sampling rate required for wideband sensing, limited power and computing resources for processing load, and frequency-selective wireless fading. This paper investigates the issue of frequency availability in LEO mobile satellite system, and a novel wideband spectrum compressed signal detection approach is proposed to obtain active primary users (PUs) subbands and their locations that should be avoided during frequency allocation. We define the novel wideband spectrum compressed sensing method based on discrete sine transform (DST-WSCS), which significantly improves the performance of spectrum detection and recovery accuracy compared with conventional discrete Fourier transform based wideband spectrum compressed sensing scheme (DFT-WSCS). Additionally, with the help of intersatellite links (ISL), the scheme of multiple satellites cooperative sensing according to OR and MAJ decision fusion rules is presented to achieve spatial diversity against wireless fading. Finally, in-depth numerical simulations are performed to demonstrate the performance of the proposed scheme in aspect of signal detection probability, reconstruction precision, processing time, and so forth

Analysis of the genetic diversity of morphological traits of oat germplasms

[Objective] The study of genetic diversity in oat germplasm resources not only contributes to the collection and evaluation of germplasm resources, but also has important guiding significance for the production and breeding of oats. [Methods] This study analyzed the diversity, variation, and clustering of 20 morphological traits in 260 oat germplasm resources, evaluated the genetic variation level of their morphological traits, and examined the traits and genetic diversity of oat germplasm resources, aiming to provide a basis for oat germplasm innovation and variety improvement. [Results] There was a significant genetic diversity of morphological traits in the 260 oat germplasm resources. The genetic diversity index of the qualitative traits was the highest in grain color (1.53) and the lowest in awn color (0.76). The genetic diversity index of the 12 quantitative traits was normally distributed, and that of the quantitative traits was the largest in thousand grain weight (2.03) and the smallest in effective tillers (1.22). The highest variable coefficient was the effective tillering number (89.02%), while the lowest was the plant height (11.19%). According to genetic difference of each characteristic varieties, the 260 accessions should be classified into 6 categories by cluster analysis. Germplasm group Ⅰ included 42 accessions which could be used as parent materials for seed type selection. Germplasm group Ⅱ had 31 accessions that could be used as parent materials for breeding high-yield forage varieties. Germplasm group Ⅳ includes 41 accessions that could be used for breeding large grain varieties. Germplasm group Ⅴ includes 46 accessions that could be used as parents for oat dwarfing. Germplasm group Ⅲ included 46 accessions and group Ⅵ included 54 accessions, and both were not outstanding in comprehensive characters analyzed. [Conclusion] This study could provide theoretical basis for the protection, development and utilization of oat germplasm resources in eastern Inner Mongolia

All-polymer nanocomposites having superior strength, toughness and ultralow energy dissipation

Toughening polymers has attracted significant interest. Traditionally, polymer toughness is enhanced by constructing polymer networks or introducing sacrificial bonds into the chains between crosslink points. These strategies, though, introduce pronounced energy dissipation and associated heat, both of which are undesirable under long-term cyclic loading, for example at the interface of implants in the human body. By incorporating single-chain nanoparticles (SCNPs) into linear polymer chains to generate all-polymer nanocomposites (APNCs), we have been able to achieve high strength, high toughness with low energy dissipation. Using a combination of simulation and experimental results, we are advancing a “SCNPs effect” where tightly cross-linked SCNPs produce a modulus contrast to achieve strengthening and toughening. Benefitting from the soft interface, the penetrable and deformable SCNPs cause the surrounding polymer chains to move in concert, significantly reducing the interfacial friction to achieve low energy dissipation. The intramolecular cross-linking of the SCNPs and adhesion between the SCNPs and polymer matrix are critical for realizing such high-performance systems. Based on a Gaussian regression model and back propagation (BP) neural network, the mechanical strength can be predicted and is supported by simulations. The APNC concept described can be applied to elastomers and gels, broadening its utilization in high-cycle and low-dissipation applications, like soft robots, flexible sensors and cartilage replacements, and artificial heart valves

The comparison between effects of Taichi and conventional exercise on functional mobility and balance in healthy older adults: a systematic literature review and meta-analysis

BackgroundTaichi is beneficial for functional mobility and balance in older adults. However, such benefits of Taichi when comparing to conventional exercise (CE) are not well understood due to large variance in study protocols and observations.MethodsWe reviewed publications in five databases. Eligible studies that examined the effects of Taichi on the outcomes of functional mobility and balance in healthy older adults as compared to CE were included. Subgroup analyses compared the effects of different types of CE (e.g., single and multiple-type exercise) and different intervention designs (e.g., Taichi types) on those outcomes (Registration number: CRD42022331956).ResultsTwelve studies consisting of 2,901 participants were included. Generally, compared to CE, Taichi induced greater improvements in the performance of Timed-Up-and-Go (SMD = −0.18, [−0.33 to −0.03], p = 0.040, I2 = 59.57%), 50-foot walking (MD = −1.84 s, [−2.62 to −1.07], p < 0.001, I2 = 0%), one-leg stance with eyes open (MD = 6.00s, [2.97 to 9.02], p < 0.001, I2 = 83.19%), one-leg stance with eyes closed (MD = 1.65 s, [1.35 to 1.96], p < 0.001, I2 = 36.2%), and functional reach (SMD = 0.7, [0.32 to 1.08], p < 0.001, I2 = 86.79%) tests. Subgroup analyses revealed that Taichi with relatively short duration (<20 weeks), low total time (≤24 h), and/or using Yang-style, can induce significantly greater benefits for functional mobility and balance as compared to CE. Uniquely, Taichi only induced significantly greater improvements in Timed-Up-and-Go compared to single- (SMD = −0.40, [−0.55 to −0.24], p < 0.001, I2 = 6.14%), but not multiple-type exercise. A significant difference between the effects of Taichi was observed on the performance of one-leg stance with eyes open when compared to CE without balance (MD = 3.63 s, [1.02 to 6.24], p = 0.006, I2 = 74.93%) and CE with balance (MD = 13.90s, [10.32 to 17.48], p < 0.001, I2 = 6.1%). No other significant difference was shown between the influences of different CE types on the observations.ConclusionTaichi can induce greater improvement in functional mobility and balance in older adults compared to CE in a more efficient fashion, especially compared to single-type CE. Future studies with more rigorous design are needed to confirm the observations here

Effects of electron acceptors on CH4 emission in alpine wetlands

Alpine wetlands are an important source of methane (CH4) and play a key role in the global carbon cycle. Their CH4 emissions largely depend on microbial CH4 production and oxidation processes that involve external electron acceptors. Seasonal precipitation drives redox cycles of humic acids (HAs), iron oxide and sulfur species, which will in turn affect CH4 production and oxidation. To investigate the effects of electron acceptors on CH4 emissions, soil samples from a typical alpine wetland on the Tibetan Plateau were incubated with the addition of ferrihydrite (HFO), HAs, sodium sulfate (SO42-) or combinations (HAs-HFO, HAs-SO42- and HAs-HFO-SO42-). During long-term anaerobic incubation, CH4 concentrations showed similar trends, increasing rapidly from 0 to 60 days, decreasing from 60 to 240 days, and finally slowly increasing again after 240 days, in all treatments except the sterilised control. Thus, the incubation period was divided into the production, consumption and reproduction phases. The addition of HFO, HAs or HAs-containing electron acceptors promoted the rates of both production and consumption of CH4, increasing the production potential of CH4 by 65–100 % and the oxidation potential of CH4 by 58–115 %. On the other hand, SO42- inhibited the production and consumption of CH4, reducing the production potential by 35 % and the oxidation potential by 50 %. Electron acceptors such as HFO, HAs and SO42- play important roles in CH4 emissions. HAs are the dominant factor affecting CH4 emissions in alpine wetlands. From a broader ecological perspective, organic and inorganic electron acceptors play a key role in CH4 production and oxidation under anaerobic conditions, influencing CH4 emissions from alpine wetlands

Research on the ablation characteristics of combined lasers for glass fiber reinforced plastic composites

Glass fiber reinforced plastic (GFRP) composites have been applied to the manufacture of missile shields and unmanned aerial vehicle (UAV) shells. It is of great significance to explore the ablation characteristics of different lasers for these composites. Currently, most existing studies on the ablation characteristics of lasers for Glass fiber reinforced plastic composites are conducted under a single laser output mode, such as continuous wave (CW) laser or pulsed laser. However, the ablation characteristics of combined lasers for Glass fiber reinforced plastic composites have not been clarified. Therefore, the ablation characteristics of single lasers (continuous wave, millisecond (ms) pulsed, or nanosecond (ns) pulsed laser) and combined laser (CW/ms or CW/ns combined pulsed lasers) were investigated by experimental and simulation methods in this study. Additionally, the ablation mechanisms of Glass fiber reinforced plastic under different laser irradiation conditions were compared and analyzed. The results demonstrated that the ablation rates of single lasers for Glass fiber reinforced plastic composites were all within an order of magnitude of 10 μg/J, which was not significantly correlated with the light source system. The ablation efficiency of the single laser was determined by the incident laser energy. The continuous wave laser was found to be the optimal light source for the ablation and destruction of Glass fiber reinforced plastic composites. Nevertheless, there were some obstacles in the ablation process of continuous wave lasers. Applying pulsed lasers during the irradiation of the continuous wave laser may generate a synergistic effect. Under the conditions in this study, the CW/ns pulsed combined laser increased the ablation efficiency by 53.8%

Large-scale risk prediction applied to Genetic Analysis Workshop 17 mini-exome sequence data

We consider the application of Efron’s empirical Bayes classification method to risk prediction in a genome-wide association study using the Genetic Analysis Workshop 17 (GAW17) data. A major advantage of using this method is that the effect size distribution for the set of possible features is empirically estimated and that all subsequent parameter estimation and risk prediction is guided by this distribution. Here, we generalize Efron’s method to allow for some of the peculiarities of the GAW17 data. In particular, we introduce two ways to extend Efron’s model: a weighted empirical Bayes model and a joint covariance model that allows the model to properly incorporate the annotation information of single-nucleotide polymorphisms (SNPs). In the course of our analysis, we examine several aspects of the possible simulation model, including the identity of the most important genes, the differing effects of synonymous and nonsynonymous SNPs, and the relative roles of covariates and genes in conferring disease risk. Finally, we compare the three methods to each other and to other classifiers (random forest and neural network)