Ecophysiological Crop Modelling Combined with Genetic Analysis Is a Powerful Tool for Ideotype Design

Improving the grain yield of crops in both favourable and stressful environments is the main breeding objective required to ensure food security. In this review, I outline a genotype-to-phenotype approach that exploits the potential values of quantitative genetics and process-based crop modelling in developing new plant types with high yields. The effects of quantitative trait locus (QTL), for traits typically at the single-organ level over a short time scale, were projected for their impact on crop growth during the whole growing season in the field. This approach can provide more markers for selection programmes for specific environments whilst also allowing for prioritization. Crop modelling is thus a powerful tool for ideotyping under contrasting conditions, i.e., use of single-environment information for predicting phenotypes under different environments.

Important powertrain dynamics for developing models for control of connected and automated electrified vehicles

Connected and Automated Vehicles (CAV) technology presents significant opportunities for energy saving in the transportation sector. CAV technology forecasts vehicle and powertrain power needs under various terrain, ambient, and traffic conditions. Integration of the CAV technology in Hybrid Electric Vehicles (HEVs) provides the opportunity for optimal vehicle operation. Indeed, Hybrid Electric Vehicle powertrains present high degrees of flexibility and possibility for choosing optimum powertrain modes based on the predicted traction power needs. In modeling complex CAV powertrain dynamics, the modeler needs to consider short-time scale powertrain dynamics, such as engine transients, and hysteresis of mode-switching for a multi-mode HEV. Therefore, the powertrain dynamics essential for developing powertrain controllers for a class of connected HEVs is presented. To this end, control-oriented powertrain dynamic models for a test vehicle consisting of full electric, hybrid, and conventional engine operating modes are developed. The resulting powertrain model can forecast vehicle traction torque and energy consumption for the specified prediction horizon of the test vehicle. The model considers different operating modes and associated energy penalty terms for mode switching. Thus, the vehicle controller can determine the optimum powertrain mode, torque, and speed for forecasted vehicle operation via utilizing connectivity data. The powertrain model is validated against the experimental data and shows prediction error of less than 5% for predicting vehicle energy consumption. The model is used to create energy penalty maps that can be used for CAV control, for example fuel penalty map for engine torque changes (10–40 Nm) at each engine speed. The results of model-based optimization show optimum switching delays ranging from 0.4 to 1.4 s to avoid hysteresis in mode switching.

Characteristics of Lake Sediment from Southwestern Mongolia and Comparison with Meteorological Data

To understand how the climate system works in the continental interior, sediment cores that are approximately 30-cm long were taken from Olgoy, Boontsagaan, and Orog lakes, Mongolia. These cores were analyzed and compared with meteorological data (air temperature, precipitation, and wind) from climate stations in the study area. Comparison of metrological data from four stations shows similar climate fluctuations. When the temperature was high, less precipitation occurred in general. The sedimentary features measured in this study were water content, organic matter, carbonate, amorphous silica contents, whole and mineral grain size, and grain density. Excess 210Pb measurements were used to estimate sedimentary ages. According to principal component analysis (PCA), temperature correlates well to sediment characteristics in Olgoy Lake. Whole and mineral grain sizes are coarser when the temperature is high, while the amorphous-silica concentration is lower. A coarse grain size is interpreted to reflect low lake levels due to evaporation under high temperature with less precipitation. Amorphous silica may be from surrounding plants and reflects less vegetation when the temperature is high. However, in the recent 30 years, after the social system changed and overgrazing became a problem, the amount of amorphous silica has positively correlated with temperature on a short time scale. In the past 30 years, with less vegetation, amorphous silica has mainly come from weathered mineral particles. High temperature caused a thick, weathered mantle for each mineral particle, resulting in high amorphous-silica concentration. In Boontsagaan Lake, whole and mineral grain sizes are coarser when the wind speed is increased. Low precipitation correlates with a decrease in organic matter and an increase in carbonate and amorphous silica. In Orog Lake, it is difficult to establish an age model due to dried-up events. Some fluctuations in sedimentary characteristics may correspond to extreme events, such as earthquakes, and natural hazards, such as dzuds (harsh winters).

Behavioral evidence for nested central pattern generator control of Drosophila grooming

Central pattern generators (CPGs) are neurons or neural circuits that produce periodic output without requiring patterned input. More complex behaviors can be assembled from simpler subroutines, and nested CPGs have been proposed to coordinate their repetitive elements, organizing control over different time scales. Here, we use behavioral experiments to establish that Drosophila grooming may be controlled by nested CPGs. On a short time scale (5–7 Hz, ~ 200 ms/movement), flies clean with periodic leg sweeps and rubs. More surprisingly, transitions between bouts of head sweeping and leg rubbing are also periodic on a longer time scale (0.3–0.6 Hz, ~2 s/bout). We examine grooming at a range of temperatures to show that the frequencies of both oscillations increase—a hallmark of CPG control—and also that rhythms at the two time scales increase at the same rate, indicating that the nested CPGs may be linked. This relationship holds when sensory drive is held constant using optogenetic activation, but oscillations can decouple in spontaneously grooming flies, showing that alternative control modes are possible. Loss of sensory feedback does not disrupt periodicity but slow down the longer time scale alternation. Nested CPGs simplify the generation of complex but repetitive behaviors, and identifying them in Drosophila grooming presents an opportunity to map the neural circuits that constitute them.

Simulations of dynamically cross-linked actin networks: Morphology, rheology, and hydrodynamic interactions

Cross-linked actin networks are the primary component of the cell cytoskeleton and have been the subject of numerous experimental and modeling studies. While these studies have demonstrated that the networks are viscoelastic materials, evolving from elastic solids on short timescales to viscous fluids on long ones, questions remain about the duration of each asymptotic regime, the role of the surrounding fluid, and the behavior of the networks on intermediate timescales. Here we perform detailed simulations of passively cross-linked non-Brownian actin networks to quantify the principal timescales involved in the elastoviscous behavior, study the role of nonlocal hydrodynamic interactions, and parameterize continuum models from discrete stochastic simulations. To do this, we extend our recent computational framework for semiflexible filament suspensions, which is based on nonlocal slender body theory, to actin networks with dynamic cross linkers and finite filament lifetime. We introduce a model where the cross linkers are elastic springs with sticky ends stochastically binding to and unbinding from the elastic filaments, which randomly turn over at a characteristic rate. We show that, depending on the parameters, the network evolves to a steady state morphology that is either an isotropic actin mesh or a mesh with embedded actin bundles. For different degrees of bundling, we numerically apply small-amplitude oscillatory shear deformation to extract three timescales from networks of hundreds of filaments and cross linkers. We analyze the dependence of these timescales, which range from the order of hundredths of a second to the actin turnover time of several seconds, on the dynamic nature of the links, solvent viscosity, and filament bending stiffness. We show that the network is mostly elastic on the short time scale, with the elasticity coming mainly from the cross links, and viscous on the long time scale, with the effective viscosity originating primarily from stretching and breaking of the cross links. We show that the influence of nonlocal hydrodynamic interactions depends on the network morphology: for homogeneous meshworks, nonlocal hydrodynamics gives only a small correction to the viscous behavior, but for bundled networks it both hinders the formation of bundles and significantly lowers the resistance to shear once bundles are formed. We use our results to construct three-timescale generalized Maxwell models of the networks.

The Impact of the COVID-19 Pandemic on Suicide Rate Trends in the Tsunami-Disaster-Affected Area Following the Great East Japan Earthquake

Background: People who experienced the Great East Japan Earthquake (GEJE) were expected to have additional levels of psychological burden resulting from the stressful conditions imposed during the coronavirus disease 2019 (COVID-19) pandemic; consequently, suicide rates may increase. Aim: We aimed to carry out continuous monitoring of suicide rates in the affected area following the GEJE under COVID-19 pandemic conditions. Method: This descriptive study monitored the suicide rates of the coastal area of Miyagi Prefecture, where disaster-related mental health activities have been continuing following severe damage caused by the tsunami disaster. An exponential smoothing time-series analysis that converted suicide rates into a smooth trend was conducted. Results: Although the suicide rate in the affected area was higher than the national average in February 2020, it showed a declining trend during the COVID-19 pandemic, while showing an increase trend in the national and non-affected areas. Limitations: Uncertainty about the direct reasons for suicide and the short time-scale observation are the limitations of this study. Conclusion: Although the national suicide rate increased, this was not the case for the affected area. Our findings may provide important lessons for suicide prevention during the COVID-19 pandemic, which needs careful regional monitoring of the state of suicide and of high-risk approaches such as disaster-related mental health activities.

Interaction of cavitation bubbles with the interface of two immiscible fluids on multiple time scales

We experimentally, numerically and theoretically investigate the nonlinear interaction between a cavitation bubble and the interface of two immiscible fluids (oil and water) on multiple time scales. The underwater electric discharge method is utilized to generate a cavitation bubble near or at the interface. Both the bubble dynamics on a short time scale and the interface evolution on a much longer time scale are recorded via high-speed photography. Two mechanisms are found to contribute to the fluid mixing in our system. First, when a bubble is initiated in the oil phase or at the interface, an inertia-dominated high-speed liquid jet generated from the collapsing bubble penetrates the water–oil interface, and consequently transports fine oil droplets into the water. The critical standoff parameter for jet penetration is found to be highly dependent on the density ratio of the two fluids. Furthermore, the pinch-off of an interface jet produced long after the bubble dynamics stage is reckoned as the second mechanism, carrying water droplets into the oil bulk. The dependence of the bubble jetting behaviours and interface jet dynamics on the governing parameters is systematically studied via experiments and boundary integral simulations. Particularly, we quantitatively demonstrate the respective roles of surface tension and viscosity in interface jet dynamics. As for a bubble initiated at the interface, an extended Rayleigh–Plesset model is proposed that well predicts the asymmetric dynamics of the bubble, which accounts for a faster contraction of the bubble top and a downward liquid jet.

Chaperones drive in vitro evolution of uracil glycosylase towards misfolded states

Evolution is driven by random mutations, whose fitness outcome is tested over time. In vitro evolution of a library of a randomly mutated protein mimics this process, however, on a short time scale, driven by a specific outcome (such as binding to a bait). Here, we used directed in vitro evolution to investigate the role of molecular chaperones in curbing promiscuity in favor of specificity of protein-protein interactions. Using yeast surface display, we generated a random library of the E. coli protein Uracil glycosylase (UNG), and selected it against various baits. Those included the purified chaperones GroEL, DnaK+DnaJ+ATP, or total protein extracts from WT or delta DnaK+DnaJ cells. We show that in-vitro evolution differs from natural evolution in cells, both physically and thermodynamically. We found that chaperones, whether purified or as part of the protein extract, select for and thus enrich uracil glycosylase (UNG) misfolded species during this in vitro evolution process. In a more general context, our results show that chaperones purge promiscuous misfolded clones from the system, and thereby avoiding their detrimental effects, such as forming wrong interactions with other macromolecules, including proteins, which can harm proteostasis.

Tidal variability of water quality parameters in a mesotidal estuary (Sado Estuary, Portugal)

To establish effective water quality monitoring strategies in estuaries, it is imperative to identify and understand the main drivers for the variation of water quality parameters. The tidal effect is an important factor of the daily and fortnightly variability in several estuaries. However, the extent of that influence on the different physicochemical and biological parameters is still overlooked in some estuarine systems, such as the Sado Estuary, a mesotidal estuary located on the west coast of Portugal. The main objective of this study was to determine how the water quality parameters of the Sado Estuary varied with the fortnightly and the semidiurnal tidal variation. To achieve this goal, sampling campaigns were conducted in May/18, Nov/18 and Jun/19, under neap and spring tidal conditions, with data collection over the tidal cycle. Results were observed to be significantly influenced by the tidal variation, in a large area of the estuary. Flood seemed to mitigate possible effects of nutrient enrichment in the water column. Additionally, significant differences were also observed when considering the different sampling stations. Temperature, Suspended Particulate Matter (SPM) and nutrients showed the highest values at low water. Lastly, the implications of the tidal variability in the evaluation of the water quality according to Water Framework Directive were also discussed, highlighting the importance of studying short-time scale variations and the worst-case scenario to ensure water quality is maintained. These findings are relevant for the implementation of regional management plans and to promote sustainable development.

Dynamic optimal power flow calculates intermittent wind turbine using ant colony method

Intermittent is electrical energy that is not available continuously due to uncontrollable external factors generated by a power plant which conditions vary in a reasonably short time scale. Intermittent can be limited or even mitigated by electricity storage, which is a rapidly growing area of research. In this research, the renewable energy used is the wind turbine. This study aims to schedule an economic generator by considering the intermittent wind turbine. Dynamic optimal power flow calculate Intermittent wind turbine uses ant colony method to determine the value of optimizing system operation with the integrated wind turbine. To determine the optimization value of the system operation, this study use a south sulawesi system consisting of 76 buses, 21 generators, and two wind power plant. From the results of the dynamic optimal power flow simulation, it is found that the generation costs are reduced from the real system costs using the ant colony method when the peak load time is 18.28% and the out peak load time is 18.08%, so that in only two times the ant colony optimization method, can reduce the cost of generation by Rp. 121,123,830.