Arkansas producers’ attitudes toward the 2002 Farm Bill and preferences for the 2007 Farm Bill

The Federal Security and Rural Investment Act of 2002, otherwise known at the 2002 Farm Bill, contains current legislation regarding federal public policies and programs for U.S. food and agriculture. This legislation will expire in 2007 and thus new legislation will be developed. It is important to have farm producers’ input for developing this legislation because the policies and programs influence their business practices and livelihoods. The purpose of this study was to determine Arkansas producers’ attitudes toward current and future farm legislation based on an analysis of a survey administered to Arkansas farm producers in summer 2006. The main finding of this research is that Arkansas producers would like to create more incentives for biofuel research. They also indicate through survey preferences that risk management policies such as insurance, disaster assistance, and labeling of foods should be addressed more thoroughly with more funding allocated to these areas. Arkansas producers are not in favor of eliminating current commodity payments although there was a significant difference of opinion in this area between those who produce program crops and those who do not. These study results provide an important assessment of producer preferences for future farm legislation

Participation in evolution and sustainability

The modern synthesis of genetics with evolution slanted our understanding of evolution and of ourselves by rejecting Darwin’s view of animals as participating in their own evolution. Defining evolution in terms of genetics, the modern synthesis indulges excessive individualism and distorted self-images as self-made. At the same time, such gene-centred thought, evoking images of master molecules making us who we are, hollows out volition and so also moral concerns and political alternatives. Drawing on the geography of thought, we argue that stubbornly tacit preformationist biological thought reflects and anchors social processes that limit adaptability in reaching toward sustainable living. We appeal for leveraging sustainability efforts by affirming in theory and in the public square an open image of human nature that recognises the participation of our ancestors in becoming who we are, obliging people to make their history together. Achieving the collective self-regulation sustainability requires may depend on correcting slanted reasoning about ourselves

Bias in the Legal Profession: Self-Assessed versus Statistical Measures of Discrimination

Legal cases are generally won or lost on the basis of statistical discrimination measures, but it is workers’ perceptions of discriminatory behavior that are important for understanding many labor-supply decisions. Workers who believe that they have been discriminated against are more likely to subsequently leave their employers and it is almost certainly workers' perceptions of discrimination that drive formal complaints to the EEOC. Yet the relationship between statistical and self-assessed measures of discrimination is far from obvious. We expand on the previous literature by using data from the After the JD (AJD) study to compare standard Blinder-Oaxaca measures of earnings discrimination to self-reported measures of (i) client discrimination; (ii) other work-related discrimination; and (iii) harassment. Overall, our results indicate that conventional measures of earnings discrimination are not closely linked to the racial and gender bias that new lawyers believe they have experienced on the job. Statistical earnings discrimination is only occasionally related to increases in self-assessed bias and when it is the effects are very small. Moreover, statistical earnings discrimination does not explain the disparity in self-assessed bias across gender and racial groups.Labour market discrimination, lawyers, gender and racial bias, wages

Nucleon-Nucleon Interactions from the Quark Model

We report on investigations of the applicability of non-relativistic constituent quark models to the low-energy nucleon-nucleon (NN) interaction. The major innovations of a resulting NN potential are the use of the $^3$P$_0$ decay model and quark model wave functions to derive nucleon-nucleon-meson form-factors, and the use of a colored spin-spin contact hyperfine interaction to model the repulsive core rather than the phenomenological treatment common in other NN potentials. We present the results of the model for experimental free NN scattering phase shifts, S-wave scattering lengths and effective ranges and deuteron properties. Plans for future study are discussed.Comment: 5 pages, 4 figures, 2 tables. To appear in Proceedings of XIII International Conference on Hadron Spectroscopy, November 29 - December 4, 2009, Florida State Universit

The Cryogenic Bonding Evaluation at the Metallic-Composite Interface of a Composite Overwrapped Pressure Vessel with Additional Impact Investigation

A bonding evaluation that investigated the cryogenic tensile strength of several different adhesives / resins was performed. The test materials consisted of 6061 aluminum test pieces adhered to a wet-wound graphite laminate in order to simulate the bond created at the liner-composite interface of an aluminum lined composite overwrapped pressure vessel. It was found that for cryogenic applications, a flexible, low modulus resin system must be used. Additionally, the samples prepared with a thin layer of cured resin - or prebond - performed significantly better than those without. It was found that it is critical that the prebond surface must have sufficient surface roughness prior to the bonding application. Also, the aluminum test pieces that were prepared using a surface etchant slightly outperformed those that were prepared with a grit blast surface finish and performed significantly better than those which had been scored using sand paper to achieve the desired surface finish. An additional impact investigation studied the post impact tensile strength of composite rings in a cryogenic environment. The composite rings were filament wound with several combinations of graphite and aramid fibers and were prepared with different resin systems. The rings were subjected to varying levels of Charpy impact damage then pulled to failure in tension. It was found that the addition of elastic aramid fibers with the carbon fiber mitigate the overall impact damage and drastically improve the post impact strength of the structure in a cryogenic environment

Applications In Sentiment Analysis And Machine Learning For Identifying Public Health Variables Across Social Media

Twitter, a popular social media outlet, has evolved into a vast source of linguistic data, rich with opinion, sentiment, and discussion. We mined data from several public Twitter endpoints to identify content relevant to healthcare providers and public health regulatory professionals. We began by compiling content related to electronic nicotine delivery systems (or e-cigarettes) as these had become popular alternatives to tobacco products. There was an apparent need to remove high frequency tweeting entities, called bots, that would spam messages, advertisements, and fabricate testimonials. Algorithms were constructed using natural language processing and machine learning to sift human responses from automated accounts with high degrees of accuracy. We found the average hyperlink per tweet, the average character dissimilarity between each individual\u27s content, as well as the rate of introduction of unique words were valuable attributes in identifying automated accounts. We performed a 10-fold Cross Validation and measured performance of each set of tweet features, at various bin sizes, the best of which performed with 97% accuracy. These methods were used to isolate automated content related to the advertising of electronic cigarettes. A rich taxonomy of automated entities, including robots, cyborgs, and spammers, each with different measurable linguistic features were categorized. Electronic cigarette related posts were classified as automated or organic and content was investigated with a hedonometric sentiment analysis. The overwhelming majority (≈ 80%) were automated, many of which were commercial in nature. Others used false testimonials that were sent directly to individuals as a personalized form of targeted marketing. Many tweets advertised nicotine vaporizer fluid (or e-liquid) in various “kid-friendly” flavors including \u27Fudge Brownie\u27, \u27Hot Chocolate\u27, \u27Circus Cotton Candy\u27 along with every imaginable flavor of fruit, which were long ago banned for traditional tobacco products. Others offered free trials, as well as incentives to retweet and spread the post among their own network. Free prize giveaways were also hosted whose raffle tickets were issued for sharing their tweet. Due to the large youth presence on the public social media platform, this was evidence that the marketing of electronic cigarettes needed considerable regulation. Twitter has since officially banned all electronic cigarette advertising on their platform. Social media has the capacity to afford the healthcare industry with valuable feedback from patients who reveal and express their medical decision-making process, as well as self-reported quality of life indicators both during and post treatment. We have studied several active cancer patient populations, discussing their experiences with the disease as well as survivor-ship. We experimented with a Convolutional Neural Network (CNN) as well as logistic regression to classify tweets as patient related. This led to a sample of 845 breast cancer survivor accounts to study, over 16 months. We found positive sentiments regarding patient treatment, raising support, and spreading awareness. A large portion of negative sentiments were shared regarding political legislation that could result in loss of coverage of their healthcare. We refer to these online public testimonies as “Invisible Patient Reported Outcomes” (iPROs), because they carry relevant indicators, yet are difficult to capture by conventional means of self-reporting. Our methods can be readily applied interdisciplinary to obtain insights into a particular group of public opinions. Capturing iPROs and public sentiments from online communication can help inform healthcare professionals and regulators, leading to more connected and personalized treatment regimens. Social listening can provide valuable insights into public health surveillance strategies

COMBINATORIAL ASPECTS OF EXCEDANCES AND THE FROBENIUS COMPLEX

In this dissertation we study the excedance permutation statistic. We start by extending the classical excedance statistic of the symmetric group to the affine symmetric group eSn and determine the generating function of its distribution. The proof involves enumerating lattice points in a skew version of the root polytope of type A. Next we study the excedance set statistic on the symmetric group by defining a related algebra which we call the excedance algebra. A combinatorial interpretation of expansions from this algebra is provided. The second half of this dissertation deals with the topology of the Frobenius complex, that is the order complex of a poset whose definition was motivated by the classical Frobenius problem. We determine the homotopy type of the Frobenius complex in certain cases using discrete Morse theory. We end with an enumeration of Q-factorial posets. Open questions and directions for future research are located at the end of each chapter

Impacts of the Teach For America Investing in Innovation Scale-Up

In 2010, Teach For America (TFA) launched a major expansion effort, funded in part by a five-year Investing in Innovation (i3) scale-up grant of $50 million from the U.S. Department of Education. Using a rigorous random assignment design to examine the effectiveness of TFA elementary school teachers in the second year of the i3 scale-up, Mathematica Policy Research found that first- and second-year corps members recruited and trained during the scale-up were as effective as other teachers in the same high-poverty schools in both reading and math. To estimate the effectiveness of TFA teachers relative to the comparison teachers, we compared end-of-year test scores of students assigned to the TFA teachers and those assigned to the comparison teachers. Because students in the study were randomly assigned to teachers, we can attribute systematic differences in achievement at the end of the study school year to the relative effectiveness of TFA and comparison teachers, rather than to the types of students taught by these two different groups of teachers. In addition to the impact analysis described in this report, the evaluation included an implementation analysis that describes key features of TFA's program model and its implementation of the i3 scale-up