Testing for Common Trends in Semiparametric Panel Data Models with Fixed Effects

This paper proposes a nonparametric test for common trends in semiparametric panel data models with fixed effects based on a measure of nonparametric goodness-of-fit (R^2). We first estimate the model under the null hypothesis of common trends by the method of profile least squares, and obtain the augmented residual which consistently estimates the sum of the fixed effect and the disturbance under the null. Then we run a local linear regression of the augmented residuals on a time trend and calculate the nonparametric R^2 for each cross section unit. The proposed test statistic is obtained by averaging all cross sectional nonparametric R^2's, which is close to zero under the null and deviates from zero under the alternative. We show that after appropriate standardization the test statistic is asymptotically normally distributed under both the null hypothesis and a sequence of Pitman local alternatives. We prove test consistency and propose a bootstrap procedure to obtain p-values. Monte Carlo simulations indicate that the test performs well in finite samples. Empirical applications are conducted exploring the commonality of spatial trends in UK climate change data and idiosyncratic trends in OECD real GDP growth data. Both applications reveal the fragility of the widely adopted common trends assumption.Common trends, Local polynomial estimation, Nonparametric goodness-of-fit, Panel data, Profile least squares

Genome-wide association mapping reveals novel genes associated with coleoptile length in a worldwide collection of barley

Background Drought is projected to become more frequent and severe in a changing climate, which requires deep sowing of crop seeds to reach soil moisture. Coleoptile length is a key agronomic trait in cereal crops such as barley, as long coleoptiles are linked to drought tolerance and improved seedling establishment under early water-limited growing conditions. Results In this study, we detected large genetic variation in a panel of 328 diverse barley (Hordeum vulgare L.) accessions. To understand the overall genetic basis of barley coleoptile length, all accessions were germinated in the dark and phenotyped for coleoptile length after 2 weeks. The investigated barleys had significant variation for coleoptile length. We then conducted genome-wide association studies (GWASs) with more than 30,000 molecular markers and identified 8 genes and 12 intergenic loci significantly associated with coleoptile length in our barley panel. The Squamosa promoter-binding-like protein 3 gene (SPL3) on chromosome 6H was identified as a major candidate gene. The missense variant on the second exon changed serine to alanine in the conserved SBP domain, which likely impacted its DNA-binding activity. Conclusion This study provides genetic loci for seedling coleoptile length along with candidate genes for future potential incorporation in breeding programmes to enhance early vigour and yield potential in water-limited environments

Opportunities for improving waterlogging tolerance in cereal crops—Physiological traits and genetic mechanisms

Waterlogging occurs when soil is saturated with water, leading to anaerobic conditions in the root zone of plants. Climate change is increasing the frequency of waterlogging events, resulting in considerable crop losses. Plants respond to waterlogging stress by adventitious root growth, aerenchyma formation, energy metabolism, and phytohormone signalling. Genotypes differ in biomass reduction, photosynthesis rate, adventitious roots development, and aerenchyma formation in response to waterlogging. We reviewed the detrimental effects of waterlogging on physiological and genetic mechanisms in four major cereal crops (rice, maize, wheat, and barley). The review covers current knowledge on waterlogging tolerance mechanism, genes, and quantitative trait loci (QTL) associated with waterlogging tolerance-related traits, the conventional and modern breeding methods used in developing waterlogging tolerant germplasm. Lastly, we describe candidate genes controlling waterlogging tolerance identified in model plants Arabidopsis and rice to identify homologous genes in the less waterlogging-tolerant maize, wheat, and barley

Multi-locus genome-wide association studies reveal novel alleles for flowering time under vernalisation and extended photoperiod in a barley MAGIC population

Optimal flowering time has a major impact on grain yield in crop species, including the globally important temperate cereal crop barley (Hordeum vulgare L.). Understanding the genetics of flowering is a key avenue to enhancing yield potential. Although bi-parental populations were used intensively to map genes controlling flowering, their lack of genetic diversity requires additional work to obtain desired gene combinations in the selected lines, especially when the two parental cultivars did not carry the genes. Multi-parent mapping populations, which use a combination of four or eight parental cultivars, have higher genetic and phenotypic diversity and can provide novel genetic combinations that cannot be achieved using bi-parental populations. This study uses a Multi-parent advanced generation intercross (MAGIC) population from four commercial barley cultivars to identify genes controlling flowering time in different environmental conditions. Genome-wide association studies (GWAS) were performed using 5,112 high-quality markers from Diversity Arrays Technology sequencing (DArT-seq), and Kompetitive allele-specific polymerase chain reaction (KASP) genetic markers were developed. Phenotypic data were collected from fifteen different field trials for three consecutive years. Planting was conducted at various sowing times, and plants were grown with/without additional vernalisation and extended photoperiod treatments. This study detected fourteen stable regions associated with flowering time across multiple environments. GWAS combined with pangenome data highlighted the role of CEN gene in flowering and enabled the prediction of different CEN alleles from parental lines. As the founder lines of the multi-parental population are elite germplasm, the favourable alleles identified in this study are directly relevant to breeding, increasing the efficiency of subsequent breeding strategies and offering better grain yield and adaptation to growing conditions

Comparative Assessment of the Binding and Neutralisation Activity of Bispecific Antibodies Against SARS-CoV-2 Variants.

Neutralising antibodies against SARS-CoV-2 are a vital component in the fight against COVID-19 pandemic, having the potential of both therapeutic and prophylactic applications. Bispecific antibodies (BsAbs) against SARS-CoV-2 are particularly promising, given their ability to bind simultaneously to two distinct sites of the receptor-binding domain (RBD) of the viral spike protein. Such antibodies are complex molecules associated with multi-faceted mechanisms of action that require appropriate bioassays to ensure product quality and manufacturing consistency. We developed procedures for biolayer interferometry (BLI) and a cell-based virus neutralisation assay, the focus reduction neutralisation test (FRNT). Using both assays, we tested a panel of five BsAbs against different spike variants (Ancestral, Delta and Omicron) to evaluate the use of these analytical methods in assessing binding and neutralisation activities of anti-SARS-CoV-2 therapeutics. We found comparable trends between BLI-derived binding affinity and FRNT-based virus neutralisation activity. Antibodies that displayed high binding affinity against a variant were often followed by potent neutralisation at lower concentrations, whereas those with low binding affinity also demonstrated reduced neutralisation activity. The results support the utility of BLI and FRNT assays in measuring variant-specific binding and virus neutralisation activity of anti-SARS-CoV-2 antibodies

Genetic solutions through breeding counteract climate change and secure barley production in Australia

Climate changes threaten global sustainable food supply by reducing crop yield. Estimates of future crop production under climate change have rarely considered the capacity of genetic improvement in breeding high-yielding and stress-tolerant crop varieties. We believe that technological advancements and developing climate-resilient crop varieties may offset the adverse effects of climate change. In this study, we examined the historical record of barley breeding and yield, and the trends of climate changes over the past 70 years in Australia. We related the selection of fast development varieties to yield improvement, and revealed the genetic connections of fast development and yield potential through genome-wide association studies. Historical records show that Australia's barley yield has experienced a steady growth despite that the seasonal production window has been shortened due to increased risk of frost damage at flowering stage and terminal heat during maturity since the 1970s. The increase in yield is largely the result of higher yield capacity of the more recently developed varieties that develop faster to counteract the impact of increased terminal heat. We also show that the changing temperature may soon reach a critical point that dramatically changes the barley flowering behaviour to impact yield by pushing its growth beyond the seasonal production window to face increasing frost damage. For the first time, we provide evidence that the effects of climate change on crop production might be less severe than what is currently believed because the advancement of technologies and development of climate-resilient crop varieties may mitigate the adverse effect of climate change to some extent. The greater use of genetic techniques in crop breeding will play a vital role in sustainable global food production in the era of climate change

Fluid Driven by Tangential Velocity and Shear Stress: Mathematical Analysis, Numerical Experiment, and Implication to Surface Flow

This paper investigates behaviors of flows driven by tangential velocity and shear stress on their boundaries such as solid walls and water surfaces. In a steady flow between two parallel plates with one of them in motion, analytic solutions are the same when a velocity and a shear stress boundary condition are applied on the moving plate. For an unsteady, impulsively started flow, however, analysis shows that solutions for velocity profiles as well as energy transferring and dissipation are different under the two boundary conditions. In an air-water flow, if either a velocity or a stress condition is imposed at the air-water interface, the problem becomes ill-posed because it has multiple solutions. Only when both of the conditions are specified, it will have a unique solution. Numerical simulations for cavity flows are made to confirm the theoretical results; a tangential velocity and a shear stress boundary condition introduce distinct flows if one considers an unsteady flow, whereas the two conditions lead to a same solution if one simulates a steady flow. The results in this paper imply that discretion is needed on selection of boundary conditions to approximate forcing on fluid boundaries such as wind effects on surfaces of coastal ocean waters

Scaling Behavior of Transverse Kinetic Energy Distributions in Au+Au Collisions at sNN=200\sqrt{s_{\rm NN}}=200 GeV

With the experimental data from STAR on the centrality dependence of transverse momentum $p_T$ spectra of pions and protons in Au+Au collisions at $\sqrt{s_{NN}}=200 {\rm GeV}$, we investigate the scaling properties of transverse energy $E_T$ distributions at different centralities. In the framework of cluster formation and decay mechanism for particle production, the universal transverse energy distributions for pion and proton can be described separately but not simultaneously.Comment: 5 pages, 5 eps figures included, to be appeared in Nucl. Phys.

Towards Reliable Automatic Protein Structure Alignment

A variety of methods have been proposed for structure similarity calculation, which are called structure alignment or superposition. One major shortcoming in current structure alignment algorithms is in their inherent design, which is based on local structure similarity. In this work, we propose a method to incorporate global information in obtaining optimal alignments and superpositions. Our method, when applied to optimizing the TM-score and the GDT score, produces significantly better results than current state-of-the-art protein structure alignment tools. Specifically, if the highest TM-score found by TMalign is lower than (0.6) and the highest TM-score found by one of the tested methods is higher than (0.5), there is a probability of (42%) that TMalign failed to find TM-scores higher than (0.5), while the same probability is reduced to (2%) if our method is used. This could significantly improve the accuracy of fold detection if the cutoff TM-score of (0.5) is used. In addition, existing structure alignment algorithms focus on structure similarity alone and simply ignore other important similarities, such as sequence similarity. Our approach has the capacity to incorporate multiple similarities into the scoring function. Results show that sequence similarity aids in finding high quality protein structure alignments that are more consistent with eye-examined alignments in HOMSTRAD. Even when structure similarity itself fails to find alignments with any consistency with eye-examined alignments, our method remains capable of finding alignments highly similar to, or even identical to, eye-examined alignments.Comment: Peer-reviewed and presented as part of the 13th Workshop on Algorithms in Bioinformatics (WABI2013

Joint task scheduling and multi-UAV deployment for aerial computing in emergency communication networks

This article studies mobile edge computing technologies enabled by unmanned aerial vehicles (UAVs) in disasters. First, considering that the ground servers may be damaged in emergency scenarios, we proposed an air-ground cooperation architecture based on ad-hoc UAV networks. We defined the system cost as the weighted sum of task delay and energy consumption because of different delay sensitivity and energy sensitivity tasks in emergency communication networks. Then, we formulated the system cost-minimization problem of task scheduling and multi-UAV deployments. To solve the proposed mixed integer nonlinear programming problem, we decomposed it to two sub-problems that were solved by proposing a swap matching-based task scheduling sub-algorithm and a successive convex approximation-based multi-UAV deployment sub-algorithm. Accordingly, we propose a joint optimization algorithm by iterating the two sub-algorithms to obtain a low complexity sub-optimal solution. Finally, the simulation results show that (i) the proposed algorithm converges in several iterations, and (ii) compared with the benchmark algorithms, the proposed algorithm has better performance of reducing task delay and energy consumption and achieves a good trade-off between them for diverse tasks