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

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

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)

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%

Governance mechanisms for chronic disease diagnosis and treatment systems in the post-pandemic era

“Re-visits and drug renewal” is difficult for chronic disease patients during COVID-19 and will continue in the post-pandemic era. To overcome this dilemma, the scenario of chronic disease diagnosis and treatment systems was set, and an evolutionary game model participated by four stakeholder groups including physical medical institutions, medical service platforms, intelligent medical device providers, and chronic disease patients, was established. Ten possible evolutionary stabilization strategies (ESSs) with their mandatory conditions were found based on Lyapunov's first method. Taking cardiovascular and cerebrovascular diseases, the top 1 prevalent chronic disease, as a specific case context, and resorting to the MATLAB simulation, it is confirmed that several dual ESSs and four unique ESS circumstances exist, respectively, and the evolution direction is determined by initial conditions, while the evolution speed is determined by the values of the conditions based on the quantitative relations of benefits, costs, etc. Accordingly, four governance mechanisms were proposed. By their adjustment, the conditions along with their values can be interfered, and then the chronic disease diagnosis and treatment systems can be guided toward the desired direction, that is, toward the direction of countermeasure against the pandemic, government guidance, global trends of medical industry development, social welfare, and lifestyle innovation. The dilemma of “Re-visits and drug renewal” actually reflects the uneven distribution problem of qualified medical resources and the poor impact resistance capability of social medical service systems under mass public emergency. Human lifestyle even the way of working all over the world will get a spiral upgrade after experiencing COVID-19, such as consumption, and meeting, while medical habits react not so rapidly, especially for mid or aged chronic disease patients. We believe that telemedicine empowered by intelligent medical devices can benefit them and will be a global trend, governments and the four key stakeholders should act according to the governance mechanisms suggested here simultaneously toward novel social medical ecosystems for the post-pandemic era

Radiation therapy generates platelet-activating factor agonists

Pro-oxidative stressors can suppress host immunity due to their ability to generate oxidized lipid agonists of the platelet-activating factor-receptor (PAF-R). As radiation therapy also induces reactive oxygen species, the present studies were designed to define whether ionizing radiation could generate PAF-R agonists and if these lipids could subvert host immunity. We demonstrate that radiation exposure of multiple tumor cell lines in-vitro, tumors in-vivo, and human subjects undergoing radiation therapy for skin tumors all generate PAF-R agonists. Structural characterization of radiation-induced PAF-R agonistic activity revealed PAF and multiple oxidized glycerophosphocholines that are produced non-enzymatically. In a murine melanoma tumor model, irradiation of one tumor augmented the growth of the other (non-treated) tumor in a PAF-R-dependent process blocked by a cyclooxygenase-2 inhibitor. These results indicate a novel pathway by which PAF-R agonists produced as a byproduct of radiation therapy could result in tumor treatment failure, and offer important insights into potential therapeutic strategies that could improve the overall antitumor effectiveness of radiation therapy regimens