Dual-purpose sorghum response to anthracnose disease, growth, and yield was undertaken in Derashe and Arba Minch trial sites during March–June 2018 and 2019. Five sorghum varieties and Rara (local check) were arranged in a randomized complete block design with four replications. Variety Chelenko exhibited the tallest main crop plant height (430 cm) while Dishkara was the tallest (196.65 cm) at ratoon crop harvesting. Rara had a higher tiller number (main = 6.73, ratoon = 9.73) among the varieties. Dishkara and Chelenko varieties produced 50 and 10% more dry biomass yield (DBY) than the overall mean DBY, while Konoda produced 40% less. Although the anthracnose infestation was highest on the varieties Konoda (percentage severity index [PSI] = 20.37%) and NTJ_2 (PSI = 32.19%), they produced significantly (p < .001) higher grain yield (3.89 t/ha) than others. Under anthracnose pressure, Chelenko and Dishkara varieties are suggested for dry matter yield while NTJ_2 for grain yield production in the study area and similar agroecology.

During military operations, soldiers are required to successfully complete numerous physical and cognitive tasks concurrently. Understanding the typical variance in research tools that may be used to provide insight into the interrelationship between physical and cognitive performance is therefore highly important. This study assessed the inter-day variability of two military-specific cognitive assessments: a Military-Specific Auditory N-Back Task (MSANT) and a Shoot-/Don’t-Shoot Task (SDST) in 28 participants. Limits of agreement ±95% confidence intervals, standard error of the mean, and smallest detectable change were calculated to quantify the typical variance in task performance. All parameters within the MSANT and SDST demonstrated no mean difference for trial visit in either the seated or walking condition, with equivalency demonstrated for the majority of comparisons. Collectively, these data provided an indication of the typical variance in MSANT and SDST performance, while demonstrating that both assessments can be used during seated and walking conditions.

Statistical learning—the skill to pick up probability-based regularities of the environment—plays a crucial role in adapting to the environment and learning perceptual, motor, and language skills in healthy and clinical populations. Here, we developed a new method to measure statistical learning without any manual responses. We used the Alternating Serial Reaction Time (ASRT) task, adapted to eye-tracker, which, besides measuring reaction times (RTs), enabled us to track learning-dependent anticipatory eye movements. We found robust, interference-resistant learning on RT; moreover, learning-dependent anticipatory eye movements were even more sensitive measures of statistical learning on this task. Our method provides a way to apply the widely used ASRT task to operationalize statistical learning in clinical populations where the use of manual tasks is hindered, such as in Parkinson’s disease. Furthermore, it also enables future basic research to use a more sensitive version of this task to measure predictive processing.

Tungsten (W) films have many applications in the semiconducting industry for sensor technology. Deposition conditions can significantly impact the resulting W films in terms of the phases present (α-BCC or β-A12), microstructural grain orientation (texture), and residual strain. Tilt-A-Whirl methodology has been employed for the evaluation of a W film showing both texture and residual strain. Sin2(ψ) analysis of the film was performed to quantify the strongly tensile in-plane strain (+0.476%) with an estimated in-plane tensile stress of ~1.9 GPa. The 3D dataset was also evaluated qualitatively via 3D visualization. Visualization of 3D texture/strain data poses challenges due to peak broadening resulting from defocusing of the beam at high ψ tilt angles. To address this issue, principal component analysis (PCA) was employed to diagnose, model, and remove the broadening component from the diffraction data. Evaluation of the raw data and subsequent corrected data (after removal of defocusing effects) has been performed through projection of the data into a virtual 3D environment (via CAD2VR software) to qualitatively detect the impact of residual strain on the observed pole figure.

Cement references were reviewed and whole pattern methods were developed for the quantitative phase analysis (QPA) of Type I Portland Cements. A set of control references were established for phase identification and quantitative analysis using laboratory diffractometers. Both RIR and Rietveld whole pattern fitting methods were used in the analyses. A block refined, parameter restricted, Rietveld method produced the best QPA results by comparison with known mixtures. Similar to prior literature findings, care has to be taken because of the severe peak overlap of the major calcium silicate and calcium aluminate phases in Portland cement and the complexity of the chemistry and structures involved. Two of the four major phases identified are doped supercells and the major C3S phase is also disordered.