The Syntax of Non-syntactic Dependencies

In this dissertation I explore the nature of interpretive dependencies in human language. In particular I investigate the limits of syntactically mediated interpretive dependencies as well as non-syntactic ones. Broadly speaking I investigate the limits of grammatical dependencies and note that current theory cannot possibly handle certain dependencies. That certain dependencies evade grammatical explanation requires a rethinking of the representations of those dependencies. The results of this investigation concern the primacy and the purview of the syntax component of the grammar. In short, the purview of syntactic relations is limited to c-command and if a c-command relation holds between two related elements, a syntactic relation must hold between them, either directly or indirectly. When c-command does not hold between the related elements, a syntactic dependency is not possible and the dependency must hold at a subsequent level of representation. To show this, I explore interpretive dependencies that I argue only superficially resemble standard, syntactically-mediated relations (such as Wh-gap dependencies). I show that these dependencies are not amenable to analysis as syntactically-mediated relations. These include Coordinated-Wh Questions like those explored in Gracanin-Yuksek 2007, Right Node Raising constructions like those explored in Postal 1974, and Across-the-board constructions like those explored in Williams 1978. Each of these involves an interpretive dependency that I claim cannot be derived syntactically. The above constructions evade explanation via traditional syntactic tools as well as semantic and pragmatic means of analysis. If the above constructions involve dependencies that cannot be construed as syntactically-, semantically-, or pragmatically-mediated, it must be the case that these otherwise normal dependencies are captured via other means, whatever that may be

E-government can be good for business

Many developing countries face significant challenges associated with collecting taxes and tendering public contracts. High tax compliance costs due to cumbersome regulations and harassment by tax officials deter investment, encourage tax evasion, and undermine economic growth. The public procurement of goods and services is often rife with collusive practices and corruption, resulting in the misallocation or waste of resources and poor quality infrastructure. One possible solution is to adopt electronic government (e-government) systems that automate and simplify interactions between government and the private sector

Bridging Formal and Informal Learning Environments

Out-of-school time programs that provide science, technology, engineering, and mathematics (STEM) educational content are promising approaches to develop skills and abilities in students. These programs may potentially inspire students with engaging hands-on, minds-on activities that encourages their natural curiosity around STEM content areas. However, it is also important to align out-of-school time learning activities with what is being taught in the formal classroom so that the experiences are congruent. Two examples of congruent programs are described in this article

Animal domestication in the era of ancient genomics

The domestication of animals led to a major shift in human subsistence patterns, from a hunter–gatherer to a sedentary agricultural lifestyle, which ultimately resulted in the development of complex societies. Over the past 15,000 years, the phenotype and genotype of multiple animal species, such as dogs, pigs, sheep, goats, cattle and horses, have been substantially altered during their adaptation to the human niche. Recent methodological innovations, such as improved ancient DNA extraction methods and next-generation sequencing, have enabled the sequencing of whole ancient genomes. These genomes have helped reconstruct the process by which animals entered into domestic relationships with humans and were subjected to novel selection pressures. Here, we discuss and update key concepts in animal domestication in light of recent contributions from ancient genomics

Mature open cows are rarely persistently infected with bovine viral diarrhea virus

Bovine viral diarrhea virus (BVDv) is an immunosuppressive virus affecting cattle in a multitude of ways. The varied presentation makes this disease difficult to identify in cow herds and the signs of a BVD infection may be very subtle. The syndrome causes economic problems by reducing herd fertility and increasing disease rates. The persistently infected (PI) animal is a unique reservoir for BVDv. These cattle are the result of in utero exposure to the noncytopathic biotype of BVDv prior to the development of a competent fetal immune system at about 125 days of gestation. Persistently infected animals are the primary method for the disease to propagate over time. PI cattle consistently shed BVD virus in relatively high levels and this exposure to the breeding herd can result in new PI calves. PI animals propagate BVDv in the herd and decrease pregnancy percentages compared to herds without PI animals. Farms must assess risk and manage for biosecurity when purchasing adult animals with an unknown history of disease exposure. Breeding herds that introduce new animals to the herd face the risk of importing a BVD PI animal. To mitigate this risk, PI animals must be accurately identified prior to herd introduction, but visual appraisal is not an accurate method of discovering these animals. Multiple diagnostic tests are available to determine the BVD status of incoming animals and all have an associated cost. Economic feasibility of determining the BVD PI status of animals depends to a large degree on the frequency with which PI animals occur in a population. Previous research has illustrated that PI calves entering the feedyard phase of production are fairly rare (about three per 1,000 calves); however, very little work has been done in mature animals. This project provides an estimate of BVD PI frequency for a specific population. This assessment should allow the formulation of a BVD-specific risk management plan which addresses the economic efficiency of testing mature females upon arrival. The primary objective of this research is to determine the prevalence of BVD PI animals in a population of young (3- to 6-year-old) cows purchased as non-pregnant mature animals. The results can guide biosecurity decisions for producers when purchasing and introducing this class of animal to the herd

Comparison of classification algorithms to predict outcomes of feedlot cattle identified and treated for Bovine Respiratory Disease

Bovine respiratory disease (BRD) continues to be the primary cause of morbidity and mortality in feedyard cattle. Accurate identification of those animals that will not finish the production cycle normally following initial treatment for BRD would provide feedyard managers with opportunities to more effectively manage those animals. Our objectives were to assess the ability of different classification algorithms to accurately predict an individual calf’s outcome based on data available at first identification of and treatment for BRD and also to identify characteristics of calves where predictive models performed well as gauged by accuracy. Data from 23 feedyards in multiple geographic locations within the U.S. from 2000 to 2009 representing over one million animals were analyzed to identify animals clinically diagnosed with BRD and treated with an antimicrobial. These data were analyzed both as a single dataset and as multiple datasets based on individual feedyards and partitioned into training, testing, and validation datasets. Classifiers were trained and optimized to identify calves that did not finish the production cycle with their cohort. Following classifier training, accuracy was evaluated using validation data. Analysis was also done to identify sub-groups of calves within populations where classifiers performed better compared to other sub-groups. Accuracy of individual classifiers varied by dataset. The accuracy of the best performing classifier by dataset ranged from a low of 63% in one dataset up to 95% in a different dataset. Sub-groups of calves were identified within some datasets where accuracy of a classifiers were greater than 98%; however these accuracies must be interpreted in relation to the prevalence of the class of interest within those populations. We found that by pairing the correct classifier with the data available, accurate predictions could be made that would provide feedlot managers with valuable information

Implementation of an Adaptive Controller System from Concept to Flight Test

The National Aeronautics and Space Administration Dryden Flight Research Center (Edwards, California) is conducting ongoing flight research using adaptive controller algorithms. A highly modified McDonnell-Douglas NF-15B airplane called the F-15 Intelligent Flight Control System (IFCS) was used for these algorithms. This airplane has been modified by the addition of canards and by changing the flight control systems to interface a single-string research controller processor for neural network algorithms. Research goals included demonstration of revolutionary control approaches that can efficiently optimize aircraft performance for both normal and failure conditions, and to advance neural-network-based flight control technology for new aerospace systems designs. Before the NF-15B IFCS airplane was certified for flight test, however, certain processes needed to be completed. This paper presents an overview of these processes, including a description of the initial adaptive controller concepts followed by a discussion of modeling formulation and performance testing. Upon design finalization, the next steps are: integration with the system interfaces, verification of the software, validation of the hardware to the requirements, design of failure detection, development of safety limiters to minimize the effect of erroneous neural network commands, and creation of flight test control room displays to maximize human situational awareness

Interpreting statistics from published research to answer clinical and management questions

Citation: White, B. J., Larson, R. L., & Theurer, M. E. (2016). Interpreting statistics from published research to answer clinical and management questions. Journal of Animal Science, 94(11), 4959-4971. doi:10.2527/jas2016-0706Appropriate statistical analysis is critical in interpreting results from published literature to answer clinical and management questions. Internal validity is an assessment of whether the study design and statistical analysis are appropriate for the hypotheses and study variables while controlling for bias and confounding. External validity is an assessment of the appropriateness of extrapolation of the study results to other populations. Knowledge about whether treatment or observation groups are truly different is unknown, but studies can be broadly categorized as exploratory or discovery, based on knowledge about previous research, biology, and study design, and this categorization affects interpretation. Confidence intervals, P-values, prediction intervals, credible intervals, and other decision aids are used singly or in combination to provide evidence for the likelihood of a given model but can be interpreted only if the study is internally valid. These decision aids do not test for bias, study design, or the appropriateness of applying study results to other populations dissimilar to the population tested. The biologic and economic importance of the magnitude of difference between treatment groups or observation groups as estimated by the study data and statistical interpretation is important to consider in clinical and management decisions. Statistical results should be interpreted in light of the specific question and production system addressed, the study design, and knowledge about pertinent aspects of biology to appropriately aid decisions

Modeling Spiral Galaxy Luminosity Profiles

The distribution of spiral and bar galaxy inclination an- gles is expected to be uniform. However, analysis of sev- eral major galaxy catalogs shows this is not the case; galaxies oriented near edge-on are significantly more common in these catalogs. In an attempt to explain this discrepancy, we have developed a galaxy simulation code to compute the appearance of a spiral type galaxy as a function of its morphological parameters. We examine the dependence of observed brightness upon inclination angle by using smooth luminous mass density and in- terstellar medium (ISM) density distributions. The lu- minous mass component is integrated along a particular line of sight, thus producing a mass distribution, from which a surface luminosity profile is derived. The ISM component is integrated alongside the luminous mass component to account for light extinction. If the de- pendence of the total surface brightness on inclination strongly corresponds to the observed distribution of incli- nation angles, we can attribute much of the discrepancy to a geometrical selection effect