Impacts of Regulating Greenhouse Gas Emissions on Livestock Trade Flows

The policies that regulate greenhouse gas emissions would provide a significant burden to emission industries as well as final consumers, which can lead to a strong influence on international trade flows of commodities. This study examines the impact of regulating greenhouse gas emissions on livestock trade flows using a commodity specific gravity model approach. This study finds that regulating greenhouse gas emissions has a negative effect on livestock trade flows from countries restricting greenhouse gas emissions to unrestricting countries, from restricting to restricting countries, and from unrestricting to restricting countries.gravity model, livestock, regulating greenhouse gas emission, trade, Environmental Economics and Policy, Livestock Production/Industries,

Titanium nitride and silicon nitride films grown by pulsed laser deposition

Titanium nitride, silicon nitride, and their multilayered films grown on Si (100) by Pulsed Laser Deposition (PLD) have been studied. The crystal structure and orientation of films were investigated by XRD and TEM. Titanium nitride film produced at room temperature was a polycrystal with 0.426 nm lattice constant whereas silicon nitride film grown at same condition was the amorphous. Particulates, one of the disadvantages of the PLD technique, were examined in the silicon nitride films varying the laser energy density, the repetition rate, and the target-substrate distance. The effect of laser ablation on the target was studied by SEM and XPS. The silicon nitride target after ablation for 25,000 pulses at Ed = 2.5 J/cm2 produced nitrogen-deficient cones that were aligned along the direction of the incident laser beam. The hardness and elastic modulus of the films grown at room temperature in vacuum and at 500 °C in nitrogen background gas (10-3 torr) were determined using the Nano Indenter®II. The highest hardness and elastic modulus in this study were obtained from the TiN film grown at room temperature in vacuum: 26.44 GPa and 265 GPa, respectively. Multi-layered films consisting of titanium nitride and silicon nitride films had intermediate hardness values. Titanium nitride and silicon nitride film grown at different temperature and pressure were examined by XPS to determine the effect of nitrogen content in films on the hardness. The more nitrogen the higher the hardness for both titanium nitride and silicon nitride films, regardless of deposition temperature

INTEGRATED AQUIFER VULNERABILITY ASSESSMENT OF NITRATE CONTAMINATION IN CENTRAL INDIANA

Groundwater is not easily contaminated, but it is difficult to restore once contaminated. Therefore, groundwater management is important to prevent pollutants from reaching groundwater. A common step in developing groundwater management plans is assessment of aquifer risk using computational models. Groundwater modeling with a geographic information system (GIS) for efficient groundwater management can provide maps of regions where groundwater is contaminated or may be vulnerable and also can help select the optimal number of groundwater monitoring locations

Simulation-aided Design of Thread Milling Cutter

AbstractThread milling has become quite popular in recent years as an alternative to tapping or other forms of threading because of diversity and complexity of parts and flexibility of the process in industries such as biomedical applications, aerospace and die-mold manufacturing. Today the design of the tooth profile is, however, predominantly feasible by the expertise and “trial and error” principle. Presented in this paper are a novel methodology to design the tooth profile of the thread mill by comparing the “to-be” thread profile and the “as-is” thread profile which is analyzed by means of NC cutting simulation. The simulation kernel enables to continually subtract the swept volume of thread milling cutter undergoing helical movement from the workpiece and to calculate the virtual workpiece (VWP). Combined with the standardized “to-be” thread profile, the tooth profile of to-be-designed thread mill is adaptively modified until the thread profile on VWP and the “to-be” thread profile become congruent with each other. The proposed methodology could be integrated into CAD/CAM systems

GaIA: Graphical Information Gain based Attention Network for Weakly Supervised Point Cloud Semantic Segmentation

While point cloud semantic segmentation is a significant task in 3D scene understanding, this task demands a time-consuming process of fully annotating labels. To address this problem, recent studies adopt a weakly supervised learning approach under the sparse annotation. Different from the existing studies, this study aims to reduce the epistemic uncertainty measured by the entropy for a precise semantic segmentation. We propose the graphical information gain based attention network called GaIA, which alleviates the entropy of each point based on the reliable information. The graphical information gain discriminates the reliable point by employing relative entropy between target point and its neighborhoods. We further introduce anchor-based additive angular margin loss, ArcPoint. The ArcPoint optimizes the unlabeled points containing high entropy towards semantically similar classes of the labeled points on hypersphere space. Experimental results on S3DIS and ScanNet-v2 datasets demonstrate our framework outperforms the existing weakly supervised methods. We have released GaIA at https://github.com/Karel911/GaIA.Comment: WACV 2023 accepted pape