Select and Sequence of a Segregating Sugar Beet Population Provides Genomic Perspective of Host Resistance to Seedling Rhizoctonia solani Infection

Understanding the genetic basis of polygenic traits is a major challenge in agricultural species, especially in non-model systems. Select and sequence (SnS) experiments carried out within existing breeding programs provide a means to simultaneously identify the genomic background of a trait while improving the mean phenotype for a population. Using pooled whole genome sequencing (WGS) of selected and unselected bulks derived from a synthetic outcrossing sugar beet population EL57 (PI 663212), which segregates for seedling rhizoctonia resistance, we identified a putative genomic background involved in conditioning a resistance phenotype. Population genomic parameters were estimated to measure fixation (He), genome divergence (FST), and allele frequency changes between bulks (DeltaAF). We report on the genome wide patterns of variation resulting from selection and highlight specific genomic features associated with resistance. Expected heterozygosity (He) showed an increased level of fixation in the resistant bulk, indicating a greater selection pressure was applied. In total, 1,311 biallelic loci were detected as significant FST outliers (p < 0.01) in comparisons between the resistant and susceptible bulks. These loci were detected in 206 regions along the chromosomes and contained 275 genes. We estimated changes in allele frequency between bulks resulting from selection for resistance by leveraging the allele frequencies of an unselected bulk. DeltaAF was a more stringent test of selection and recovered 186 significant loci, representing 32 genes, all of which were also detected using FST. Estimates of population genetic parameters and statistical significance were visualized with respect to the EL10.2 physical map and produced a candidate gene list that was enriched for function in cell wall metabolism and plant disease resistance, including pathogen perception, signal transduction, and pathogen response. Specific variation associated with these genes was also reported and represents genetic markers for validation and prediction of resistance to Rhizoctonia. Select and sequence experiments offer a means to characterize the genetic base of sugar beet, inform selection within breeding programs, and prioritize candidate variation for functional studies.

Beam Damage Assessment Using Natural Frequency Shift and Machine Learning

Damage detection based on modal parameter changes becomes popular in the last decades. Nowadays are available robust and reliable mathematical relations to predict the natural frequency changes if damage parameters are known. Using these relations, it is possible to create databases containing a large variety of damage scenarios. Damage can be thus assessed by applying an inverse method. The problem is the complexity of the database, especially for structures with more cracks. In this paper, we propose two machine learning methods, namely the random forest (RF) and the artificial neural network (ANN) as search tools. The databases we developed contain damage scenarios for a prismatic cantilever beam with one crack and ideal and non-ideal boundary conditions. The crack assessment is made in two steps. First, a coarse damage location is found from the networks trained for scenarios comprising the whole beam. Afterward, the assessment is made involving a particular network trained for the segment of the beam on which the crack is previously found. Using the two machine learning methods, we succeed to estimate the crack location and severity with high accuracy for both simulation and laboratory experiments. Regarding the location of the crack, which is the main goal of the practitioners, the errors are less than 0.6%. Based on these achievements, we concluded that the damage assessment we propose, in conjunction with the machine learning methods, is robust and reliable.

Capture the variation of acoustic impedance property in the Jaisalmer Formation due to structural deformation based on post-stack seismic inversion study: a case study from Jaisalmer sub-basin, India

The Rajasthan basin situates in the western part of India. The basin architecture comprises three significant sub-basins such as Barmer-Sanchor, Bikaner-Nagaur and Jaisalmer. Barmer-Sanchor and Bikaner-Nagaur sub-basins are intracratonic categories, whereas the Jaisalmer sub-basin comes under intracratonic nature. The current study was conducted in the Jaisalmer sub-basin. The study was conducted in two regions in the Jaisalmer sub-basin through a comparative quantitative interpretation study with the help of two vintages seismic surveys. Ghotaru and Bandha are two adjacent areas in the Jaisalmer sub-basin where Ghotaru has seen few hydrocarbon discoveries; however, no such discoveries are encountered in the Bandha area. The current study was concentrated on the Jaisalmer limestone formation in the Jurassic age. The sub-basin and its related study area have been structurally deformed due to various tectonic activities. Structural deformation was played a crucial role in changing the rock property of limestone facies. A post-stack seismic inversion was carried out to capture the rock property changes in the limestone reservoir based on P-impedance values. Development of high P-impedance was observed in the Ghotaru region compared to the Bandha region from this study. A frequency changes of the limestone lithofacies with structural components was also captured in this study. The high impedance limestone lithofacies is a probable hydrocarbon-bearing reservoir unit in the Jaisalmer Formation of the Ghotaru region.

Characterization of plasma catalytic decomposition of methane: role of atomic O and reaction mechanism

In this work, we investigated atmospheric pressure plasma jet (APPJ)-assisted methane oxidation over a Ni-SiO2/Al2O3 catalyst. We evaluated possible reaction mechanisms by analyzing the correlation of gas phase, surface and plasma-produced species. Plasma feed gas compositions, plasma powers, and catalyst temperatures were varied to expand the experimental parameters. Real-time Fourier-transform infrared spectroscopy (FTIR) was applied to quantify gas phase species from the reactions. The reactive incident fluxes generated by plasma were measured by molecular beam mass spectroscopy (MBMS) using an identical APPJ operating at the same conditions. A strong correlation of the quantified fluxes of plasma-produced atomic oxygen with that of CH4 consumption, and CO and CO2 formation implies that O atoms play an essential role in CH4 oxidation for the investigated conditions. With the integration of APPJ, the apparent activation energy was lowered and a synergistic effect of 30% was observed. We also performed in-situ diffuse reflectance infrared Fourier-transform spectroscopy (DRIFTS) to analyze the catalyst surface. The surface analysis showed that surface CO abundance mirrored the surface coverage of CHn at 25 oC. This suggests that CHn adsorbed on the catalyst surface as an intermediate species that was subsequently transformed into surface CO. We observed very little surface CHn absorbance at 500 oC, while a ten-fold increase of surface CO and stronger CO2 absorption were seen. This indicates that for a nickel catalyst at 500 oC, the dissociation of CH4 to CHn may be the rate-determining step in the plasma-assisted CH4 oxidation for our conditions. We also found the CO vibrational frequency changes from 2143 cm-1 for gas phase CO to 2196 cm-1 for CO on a 25 oC catalyst surface, whereas the frequency of CO on a 500 oC catalyst was 2188 cm-1. The change in CO vibrational frequency may be related to the oxidation of the catalyst.

A Population Genomic Assessment of Three Decades of Evolution in a Natural Drosophila Population

Population genetics seeks to illuminate the forces shaping genetic variation, often based on a single snapshot of genomic variation. However, utilizing multiple sampling times to study changes in allele frequencies can help clarify the relative roles of neutral and non-neutral forces on short time scales. This study compares whole-genome sequence variation of recently collected natural population samples of Drosophila melanogaster against a collection made approximately 35 years prior from the same locality - encompassing roughly 500 generations of evolution. The allele frequency changes between these time points would suggest a relatively small local effective population size on the order of 10,000, significantly smaller than the global effective population size of the species. Some loci display stronger allele frequency changes than would be expected anywhere in the genome under neutrality - most notably the tandem paralogs Cyp6a17 and Cyp6a23, which are impacted by structural variation associated with resistance to pyrethroid insecticides. We find a genome-wide excess of outliers for high genetic differentiation between old and new samples, but a larger number of adaptation targets may have affected SNP-level differentiation versus window differentiation. We also find evidence for strengthening latitudinal allele frequency clines: northern-associated alleles have increased in frequency by an average of nearly 2.5% at SNPs previously identified as clinal outliers, but no such pattern is observed at random SNPs. This project underscores the scientific potential of using multiple sampling time points to investigate how evolution operates in natural populations, by quantifying how genetic variation has changed over ecologically relevant timescales.

Inflation Co-Movement Dynamics: A Cross-Country Investigation Using a Continuous Wavelet Approach

The economic literature provides evidence that inflation rates can co-move across nations because of a host of reasons, ranging from low frequency changes in monetary policy to similar high frequency shocks. Hence, this paper investigates inflation rate co-movements between nine (9) African countries and their bilateral linkages with five (5) developed economies using continuous wavelets at different time scales or frequencies. Specifically, we examine the coherency and the phase relationship in time-frequency space in inflation rates of the selected countries. Several findings are documented. First, inflation rates co-movements in the nine African countries are time varying, multi-scale, and characterized by structural breaks. In addition, we find that inflation co-movements across countries in the Africa sub-region is weak at low frequencies. Furthermore, we find evidence of inflation co-movement between Africa and developed economies, suggesting that central banks and policy-makers in Africa need to monitor international price developments, and analyze their implications for their domestic economies. Second, we find that inflation rates in the selected African countries explain, on average, almost 80% of their own inflation variance over the whole sample period. Spillover analysis reveals that China and Canada account for a greater percentage of inflation variation in Africa.

Statistical inference of prehistoric demography from frequency distributions of radiocarbon dates: a review and a guide for the perplexed

The last decade saw a rapid increase in the number of applications where time-frequency changes of radiocarbon dates have been used as a proxy for inferring past population dynamics. Although its simple and universal premise is appealing and undoubtedly offers some unique opportunities for research on long-term comparative demography, practical applications are far from trivial and riddled by challenges. Here I review: 1) the most common criticisms concerning the nature of radiocarbon time-frequency data as a demographic proxy; 2) the statistical nature of the problem; and 3) three classes of inferential approaches proposed so far in the literature.

Synergistic Modulations of Large-Scale Synoptic Patterns and Local-Scale Urbanization Effects on Summer Rainfall in South China

Using the ERA5 (the fifth major global reanalysis produced by the European Centre for Medium-Range Weather Forecasts) data and the T-PCA (Principal Component Analysis in T-mode) objective classification method to classify the 850-hPa geopotential height, we summarize four conceptual models of large-scale synoptic weather types over East Asia. By combining this with the daily precipitation observation data of 36 meteorological stations in Guangdong, South China, during summer (June to August) of 2014–2018, we found that summer precipitation in Guangdong Province is closely related to the position of the northwestern Pacific subtropical high and the strong upward motion of the warm airflow over the Pearl River Delta. It is further revealed the regulation effect of different weather patterns on summer precipitation in Guangdong Province and their urban–rural differences. More specifically, both urban and rural areas have a decreasing proportion of light rainfall and an increasing proportion of heavy and torrential rainfall, which are mainly regulated by the trend of frequency changes of four different weather types: Type 1 (47.39%) and Type 2 (32.39%) days are decreasing year by year, modulating the trend of light rainfall, while Type 3 (13.26%) and Type 4 (6.96%) days are steadily increasing, dominating the trend of heavy rainfall. In addition, it was further found that the frequency of light rainfall is decreasing more significantly in cities compared to that in rural areas, while the proportion of heavy and stormy rainfall is increasing more significantly, which is closely related to the effects of rapid urbanization.