Evaluating the Spectral Response and Yield of Soybean Following Exposure to Sublethal Rates of 2,4-D and Dicamba at Vegetative and Reproductive Growth Stages

The commercialization of synthetic auxin-resistant crops and the commensurate increase in post-emergent auxin-mimic herbicide applications has resulted in millions of hectares of injury to sensitive soybeans in the United States since 2016. Visual yield loss estimations following auxin injury can be difficult. The goal of this research was to determine if spectral variations following auxin injury to soybean allow for more precise yield loss estimations. Identical field experiments were performed in 2018, 2019, and 2020 in Columbia, Missouri to compare the ability of established vegetative indices to differentiate between exposure levels of 2,4-D and dicamba in soybean and predict yield loss. Soybeans were planted at three timings for growth stage separation and were exposed to sublethal rates of 2,4-D and dicamba at the R2, R1, and V3 growth stages. A UAV-mounted multispectral sensor was flown over the trial 14 days after the herbicide treatments. The results of this research found that vegetative indices incorporating the red-edge wavelength were more consistent in estimating yield loss than indices comprised of only visible or NIR wavelengths. Yield loss estimations became difficult when soybean injury occurred during later reproductive stages when soybean biomass was increased. This research also determined that when injury occurs to soybean in vegetative growth stages late in the growing season there is a greater likelihood for yield loss to occur due to decreased time for recovery. The results of this research could provide direction for more objective and accurate evaluations of yield loss following synthetic auxin injury than what is currently available.

Residential flood loss estimated from Bayesian multilevel models

Models for the predictions of monetary losses from floods mainly blend data deemed to represent a single flood type and region. Moreover, these approaches largely ignore indicators of preparedness and how predictors may vary between regions and events, challenging the transferability of flood loss models. We use a flood loss database of 1812 German flood-affected households to explore how Bayesian multilevel models can estimate normalised flood damage stratified by event, region, or flood process type. Multilevel models acknowledge natural groups in the data and allow each group to learn from others. We obtain posterior estimates that differ between flood types, with credibly varying influences of water depth, contamination, duration, implementation of property-level precautionary measures, insurance, and previous flood experience; these influences overlap across most events or regions, however. We infer that the underlying damaging processes of distinct flood types deserve further attention. Each reported flood loss and affected region involved mixed flood types, likely explaining the uncertainty in the coefficients. Our results emphasise the need to consider flood types as an important step towards applying flood loss models elsewhere. We argue that failing to do so may unduly generalise the model and systematically bias loss estimations from empirical data.

Analysis and Design of an Interleaved Switched-Capacitor Multilevel ANPC Converter

This paper presents an interleaved switchedcapacitor multilevel ANPC converter (SCANPC) for high power density applications. To demonstrate the feasibility of the idea, the analysis and design of the converter are made initially for one cell and after for the two cells interleaved configuration. In addition, it is used a power loss estimation methodology for the Gallium Nitride switches. Simulations and power loss estimations are shown for a 4kW power prototype.

Earth Observation Techniques for Spatial Disaggregation of Exposure Data

<p>Exposure describes elements which are imperiled by natural hazards and susceptible to damage. The affiliated vulnerability characterizes the likelihood to experience damage regarding a given level of hazard intensity. Frequently, the compilation of exposure information is the costliest component (in terms of time and labor) in risk assessment. Existing data sets and models often describe exposure in an aggregated manner, e.g., by relying on statistical/census data for given administrative entities. Nowadays, earth observation techniques allow to collect spatially continuous information for large geographic areas while enabling a high geometric and temporal resolution. In parallel, modern data interpretation tools based on Artificial Intelligence concepts enable the extraction of thematic information from such data with a high accuracy and detail. Consequently, we exploit measurements from the earth observation missions TanDEM-X and Sentinel-2, which collect data on a global scale, to characterize the built environment in terms of fundamental morphologic properties, namely built-up density and height. Subsequently, we use this information to constrain existing exposure data in a spatial disaggregation approach. Thereby, we compare different methods for disaggregation and evaluate how different resolution properties of the earth observation data affect the risk assessment result. Results are presented for the city of Santiago de Chile, Chile, which is prone to natural hazards such as earthquakes. We present loss estimations and corresponding sensivity with respect to the resolution properties of the exposure data used in the model. Thereby, it can be noted how loss estimations vary substantially and that aggregated exposure information underestimates losses in our scenarios. As such, this study underlines the benefits of deploying modern earth observation technologies for refined exposure estimation and related loss estimation.</p>

Technical Aspects of Mining Rate Improvement in Steeply Inclined Coal Seams: A Case Study

This paper presents our experience obtained when mining the thick and steeply-inclined Seam 510 in the Polish Kazimierz-Juliusz coal mine with the use of a unique mechanical face mining system. Seam 510, which is 15–20 m thick and inclined at angles of 40°–45°, was initially treated as uneconomical because effective mining systems were not available. However, to extract high-quality coal resources, a completely mechanized variant of the sublevel caving system was designed based on standard machines and equipment applied in coal mining. Extraction was conducted top-down at the levels of the particular mining sub-level drifts with roof caving. The faces in the extracted coal release areas were protected by a single pair of specially designed mechanized mining system sections. One of the basic problems revealed during extraction of subsequent mining panels, was the observed changeability of the resource mining rates. The extraction losses changed in the available resources from less than 10% to about 50%. This paper presents two typical courses of changes in the extractable resource mining rates. Similar rate changes occurred in both cases with continued mining of a single seam section. Our analysis enabled deposit loss estimations and production output planning under the sublevel caving systems applied in the extraction of seam deposits of similar structure.

Influence of shaking intensity attenuation peculiarities on reliability of earthquake loss estimation in emergency mode

The methods and results of seismic hazard zoning are investigated for the Russian Federation territory and abroad. The input data used in the zoning procedure, aimed at revealing the boundaries of areas with stable seismic intensity attenuation parameters have been analyzed. The zoning procedure has been developed for determining the boundaries of territories, within which the macroseismic field parameters (i.e., the coefficients in N.V. Shebalin’s equation; the orientation of the elliptic isoseist axes, as well as the ratio of their semi-axes) show close values in each point. Examples are given in distinguishing zones characterized by quasi-stable parameters for separate regions, as well as in calibrating the computer model of the macroseismic field. The case studies are considered in the presence of a complete set of input data and under conditions of their insufficiency. The efficiency of the macroseismic field calibrated models application in the Extremum system in order to increase the reliability of near real time earthquake loss estimations is shown.