Characterization of Candidate Compound for Control of Barnyardgrass and Other Troublesome Weeds In Rice

Barnyardgrass remains one of the most difficult weeds to manage in rice. As herbicide resistance in this species, as well as others, continues to increase new control options are needed. Dow AgroSciences recently discovered and is developing a new herbicide for rice which is the primary focus of this research. Experiments were conducted to characterize this new herbicide for its use and effectiveness in midsouthern U.S. rice systems. The research conducted herein covers various aspects of herbicide characterization including: barnyardgrass dose response, accession testing, spectrum of control and tank-mix capability, application optimization, soil carryover and plant back determination, drift onto susceptible crops, drift onto reproductive soybean and its impact on the subsequent offspring, and radiolabeled isotope absorption, translocation, and metabolism. In a dose-response experiment, susceptible-, acetolactate synthase (ALS)-, propanil-, and quinclorac-resistant barnyardgrass biotypes ED90 values for percent control, plant height, and biomass reductions of all resistant biotypes fell within the anticipated labeled rate of 30 g ha-1. Based on these results, quinclorac-resistant barnyardgrass as well as other resistant biotypes can be controlled with florpyrauxifen-benzyl, even with quinclorac having a similar mechanism of action. Florpyrauxifen-beznyl appeared to have significant tank-mix flexibility with other commonly applied rice herbicides. Increasing the rate of methylated seed oil (MSO) improved weed control with both formulations of florpyraixifen-benzyl. In addition, flooding shortly after application enhanced barnyardgrass and yellow nutsedge control. Plant back study results support a relatively short replant interval for soybean (≤2 months) after florpyrauxifen-benzyl application to rice. Additionally, it is believed that florpyrauxifen-benzyl will only present slight risks for off-target movement to vegetative soybean. However, high drift rates (1/20x) of florpyrauxifen-benzyl during R1 to R4 significantly reduced soybean plant height \u3e25% and yield. Germination, stand, plant height, and yield of the progeny from dicamba- and florpyrauxifen-benzyl-treated soybean plants were significantly affected. Furthermore, research on radiolabeled florpyrauxifen-benzyl suggests that for barnyardgrass, hemp sesbania, and yellow nutsedge soil moisture can play a significant role in absorption, translocation, and metabolism. These results indicate this new herbicide will provide control of numerous problematic weed species, but users will need to be mindful of soybean sensitivity

Innovations in Supervision Reducing Violence and Recidivism Through VRP Aftercare and CBI Open Groups

Nebraska Division of Parole Supervision has created a violence-reduction (VRP) aftercare program and a CBI intervention which maintains an open group structure to effectively reduce the recidivism rate of high-risk parole clients, particularly those who have been identified as likely to reoffend violently and those who have previously failed on community supervision. Long-term goals are to ensure 1) the highest risk parole clients receive a higher dosage of evidence-based interventions, 2) the reduced use of parole sanctions and revocations and 3) a reduced overall recidivism rate for parole clients. The ‘open’ nature of the programs (i.e., clients can begin at any session, rather than periodically as a cohort) facilitates the ability of a smaller parole agency with traditionally fewer resources to provide evidence-based, recidivism reduction programs with fidelity

Functional Genomics of Nervous System Development and Disease

xiii, 145 p. : ill. (some col.)The goal of functional genomics is to elucidate the relationship between an organism's genotype and phenotype. A key characteristic of functional genomics is the use of genome-wide approaches as opposed to more traditional single-gene approaches. Genome-wide expression profiling is used to investigate the dynamic properties of transcriptomes, provides insights into how biological functions are encoded in genomes, and is an important technique in functional genomics. This dissertation describes the use of genome-wide expression profiling and other functional genomics techniques to address a variety of biological questions related to development and disease of the nervous system. Our results reveal novel and important insights into nervous system development and disease and demonstrate the power of functional genomics approaches for the study of nervous system biology. This dissertation also describes a novel technique called TUtagging that facilitates cell type-specific RNA isolation from intact complex tissues. The isolation of RNA from specific cell types within a complex tissue is a major limiting factor in the application of genome-wide expression profiling, and TU-tagging can be used to address a wide array of interesting and important biological questions. This dissertation includes previously published and unpublished co-authored material.Committee in charge: Dr. John Postlethwait， Chair； Dr. Chris Doe， Advisor； Dr. Bruce Bowerman， Member； Dr. Patrick Phillips， Member； Dr. Tom Stevens， Outside Membe

Realistic assumptions about spatial locations and clustering of premises matter for models of foot-and-mouth disease spread in the United States

Spatially explicit livestock disease models require demographic data for individual farms or premises. In the U.S., demographic data are only available aggregated at county or coarser scales, so disease models must rely on assumptions about how individual premises are distributed within counties. Here, we addressed the importance of realistic assumptions for this purpose. We compared modeling of foot and mouth disease (FMD) outbreaks using simple randomization of locations to premises configurations predicted by the Farm Location and Agricultural Production Simulator (FLAPS), which infers location based on features such as topography, land-cover, climate, and roads. We focused on three premises-level Susceptible-Exposed-Infectious-Removed models available from the literature, all using the same kernel approach but with different parameterizations and functional forms. By computing the basic reproductive number of the infection (R0) for both FLAPS and randomized configurations, we investigated how spatial locations and clustering of premises affects outbreak predictions. Further, we performed stochastic simulations to evaluate if identified differences were consistent for later stages of an outbreak. Using Ripley's K to quantify clustering, we found that FLAPS configurations were substantially more clustered at the scales relevant for the implemented models, leading to a higher frequency of nearby premises compared to randomized configurations. As a result, R0 was typically higher in FLAPS configurations, and the simulation study corroborated the pattern for later stages of outbreaks. Further, both R0 and simulations exhibited substantial spatial heterogeneity in terms of differences between configurations. Thus, using realistic assumptions when de-aggregating locations based on available data can have a pronounced effect on epidemiological predictions, affecting if, where, and to what extent FMD may invade the population. We conclude that methods such as FLAPS should be preferred over randomization approaches

DCNFIS: Deep Convolutional Neuro-Fuzzy Inference System

A key challenge in eXplainable Artificial Intelligence is the well-known tradeoff between the transparency of an algorithm (i.e., how easily a human can directly understand the algorithm, as opposed to receiving a post-hoc explanation), and its accuracy. We report on the design of a new deep network that achieves improved transparency without sacrificing accuracy. We design a deep convolutional neuro-fuzzy inference system (DCNFIS) by hybridizing fuzzy logic and deep learning models and show that DCNFIS performs as accurately as three existing convolutional neural networks on four well-known datasets. We furthermore that DCNFIS outperforms state-of-the-art deep fuzzy systems. We then exploit the transparency of fuzzy logic by deriving explanations, in the form of saliency maps, from the fuzzy rules encoded in DCNFIS. We investigate the properties of these explanations in greater depth using the Fashion-MNIST dataset

Effects of regional differences and demography in modelling foot-and-mouth disease in cattle at the national scale

Foot-and-mouth disease (FMD) is a fast-spreading viral infection that can produce large and costly outbreaks in livestock populations. Transmission occurs at multiple spatial scales, as can the actions used to control outbreaks. The US cattle industry is spatially expansive, with heterogeneous distributions of animals and infrastructure. We have developed a model that incorporates the effects of scale for both disease transmission and control actions, applied here in simulating FMD outbreaks in US cattle. We simulated infection initiating in each of the 3049 counties in the contiguous US, 100 times per county. When initial infection was located in specific regions, large outbreaks were more likely to occur, driven by infrastructure and other demographic attributes such as premises clustering and number of cattle on premises. Sensitivity analyses suggest these attributes had more impact on outbreak metrics than the ranges of estimated disease parameter values. Additionally, although shipping accounted for a small percentage of overall transmission, areas receiving the most animal shipments tended to have other attributes that increase the probability of large outbreaks. The importance of including spatial and demographic heterogeneity in modelling outbreak trajectories and control actions is illustrated by specific regions consistently producing larger outbreaks than others

Chronic Wasting Disease and Potential Transmission to Humans

Chronic wasting disease (CWD) of deer and elk is endemic in a tri-corner area of Colorado, Wyoming, and Nebraska, and new foci of CWD have been detected in other parts of the United States. Although detection in some areas may be related to increased surveillance, introduction of CWD due to translocation or natural migration of animals may account for some new foci of infection. Increasing spread of CWD has raised concerns about the potential for increasing human exposure to the CWD agent. The foodborne transmission of bovine spongiform encephalopathy to humans indicates that the species barrier may not completely protect humans from animal prion diseases. Conversion of human prion protein by CWD-associated prions has been demonstrated in an in vitro cell-free experiment, but limited investigations have not identified strong evidence for CWD transmission to humans. More epidemiologic and laboratory studies are needed to monitor the possibility of such transmissions

Radio Sources from a 31 GHz Sky Survey with the Sunyaev-Zel'dovich Array

We present the first sample of 31-GHz selected sources to flux levels of 1 mJy. From late 2005 to mid 2007, the Sunyaev-Zel'dovich Array (SZA) observed 7.7 square degrees of the sky at 31 GHz to a median rms of 0.18 mJy/beam. We identify 209 sources at greater than 5 sigma significance in the 31 GHz maps, ranging in flux from 0.7 mJy to ~200 mJy. Archival NVSS data at 1.4 GHz and observations at 5 GHz with the Very Large Array are used to characterize the sources. We determine the maximum-likelihood integrated source count to be N(>S) = (27.2 +- 2.5) deg^-2 x (S_mJy)^(-1.18 +- 0.12) over the flux range 0.7 - 15 mJy. This result is significantly higher than predictions based on 1.4-GHz selected samples, a discrepancy which can be explained by a small shift in the spectral index distribution for faint 1.4-GHz sources. From comparison with previous measurements of sources within the central arcminute of massive clusters, we derive an overdensity of 6.8 +- 4.4, relative to field sources.Comment: 13 pages, 5 figure

Prescription Drug Abuse: The Pharmacist\u27s Occupational Hazard

Prescription drug abuse within the profession of pharmacy is a rising threat that must be addressed. While familiarity of drugs, work-related stress, family history and enabling may contribute to addiction disorders, chemical impairment by the pharmacist can posse serious risks to patient care. Help is available for the struggling pharmacist in the form of treatment facilities and support networks for recovery