Notes

Optimal Rectification without having Forward-Current Elimination by Biological Molecular Generator.
mer exposure and risk screening, and high-throughput chemical prioritization.Recent research suggests that service dogs may have clinically-relevant benefits for military veterans with posttraumatic stress disorder (PTSD). However, the effects of PTSD service dogs on veterans' medication use has been largely unexplored. The objective of this study was to quantify the effect of PTSD service dogs on medication use among a population of military veterans with PTSD. In a cross-sectional design, United States post-9/11 military veterans with PTSD were recruited from a single service dog provider including veterans living with a PTSD service dog (n = 52) and veterans on the waitlist (n = 44). Both populations of veterans received treatment as usual. Participants completed an online survey of self-reported medication regimens and medication changes. Regression models quantified the effect of having a service dog on physical health, mental health, pain, and sleep medications while controlling for confounding variables (age, sex, relationship status, traumatic brain injuries, and physical health). Results indicated that there were no significant effects of having a service dog on overall self-reported medication use nor any specific medication category (p's > 0.06). However, veterans with a service dog were more likely than those on the waitlist to report that their doctor had decreased dosage or removed medications since getting their service dog. The results of this preliminary cross-sectional research should be interpreted with caution, as future within-subject and pharmacy-verified research is necessary to understand the causality of these findings.In the eastern Indo-Gangetic Plains (EIGP), conventional rice-wheat system has led to a decline in productivity, input-use efficiency, and profitability. To address these, a four-year field study was conducted to evaluate the performance of tillage and crop establishment (TCE) methods in rice-wheat-greengram rotation. The treatments included 1) random puddled transplanted rice (RPTR) - conventional-till broadcast wheat (BCW) - zero-till greengram (ZTG); 2) line PTR (LPTR) - conventional-till drill sown wheat (CTW) - ZTG; 3) machine transplanted rice in puddled soil (CTMTR) - zero tillage wheat (ZTW) - ZTG; 4) machine transplanted rice in zero-till wet soil (ZTMTR) - ZTW - ZTG; 5) system of rice intensification (SRI) - system of wheat intensification (SWI) - ZTG; 6) direct-seeded rice (DSR) - ZTW - ZTG; and 7) zero-till DSR - ZTW - ZTG. During the initial two years, conventional rice system (PTR) recorded a 16.2 % higher rice grain yield than DSR system. Whereas in the fourth year, the rice yields under DSR anred for the second green revolution.Intra-plot heterogeneity in yield is often observed in smallholder farming systems, although its implications for yield measurement remain under-investigated. Using a unique dataset on smallholder maize production in Ethiopia, we quantify the magnitude of inter- and intra-plot heterogeneity, describe the relationship between intra-plot heterogeneity and maize productivity, and document the implications of intra-field heterogeneity on the accuracy of alternative yield estimation protocols. Our data include five common yield estimation protocols, as well as full plot harvests of 230 smallholder maize fields. We surveyed agronomic decisions, biophysical variables, and accessibility characteristics of the surveyed fields. We quantify intra-plot heterogeneity using the coefficient of variation (CV) of stand density, cob weight, and maize grain yield. A generalized linear mixed model is used to explore the relationship between these variables and the method- and heterogeneity-dependence of yield estimation accuracyesults of such estimations should be considered with caution when used as the basis of decision-making.Cassava is an important crop in the developing world. The goal of this study was to review published cassava models (18) for their capability to simulate storage root biomass and to categorize them into static and dynamic models. The majority (14) are dynamic and capture within season growth dynamics. Most (13) of the dynamic models consider environmental factors such as temperature, solar radiation, soil water and nutrient restrictions. More than half (10) have been calibrated for a distinct genotype. Only one of the four static models includes environmental variables. While the static regression models are useful to estimate final yield, their application is limited to the locations or varieties used for their development unless recalibrated for distinct conditions. Dynamic models simulate growth process and provide estimates of yield over time with, in most cases, no fixed maturity date. The dynamic models that simulate the detailed development of nodal units tend to be less accurate in determining final yield compared to the simpler dynamic and statistic models. However, they can be more safely applied to novel environmental conditions that can be explored in silico. Deficiencies in the current models are highlighted including suggestions on how they can be improved. IPI145 None of the current dynamic cassava models adequately simulates the starch content of fresh cassava roots with almost all models based on dry biomass simulations. Further studies are necessary to develop a new module for existing cassava models to simulate cassava quality.Approximately 2.8 billion people rely on polluting fuels (e.g. wood, kerosene) for cooking. With affordability being a key access barrier to clean cooking fuels, such as liquefied petroleum gas (LPG), pay-as-you-go (PAYG) LPG smart meter technology may help resource-poor households adopt LPG by allowing incremental fuel payments. To understand the potential for PAYG LPG to facilitate clean cooking, objective evaluations of customers' cooking and spending patterns are needed. This study uses novel smart meter data collected between January 2018-June 2020, spanning COVID-19 lockdown, from 426 PAYG LPG customers living in an informal settlement in Nairobi, Kenya to evaluate stove usage (e.g. cooking events/day, cooking event length). Seven semi-structured interviews were conducted in August 2020 to provide context for potential changes in cooking behaviours during lockdown. Using stove monitoring data, objective comparisons of cooking patterns are made with households using purchased 6 kg cylinder LPG in peri-urban Eldoret, Kenya.
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