Modeling Revenue and Visitation Patterns of Agritourism Operations in Oklahoma

With agritourism increasingly promoted as a way to generate income in rural areas, information is needed on the potential performance of agritourism operations. Currently, existing research provides little information about the business characteristics that can affect agritourism revenue. This manuscript presents research on the business characteristics associated with differences in agritourism revenue of Oklahoma businesses. This research also identifies whether offering wedding services financially benefit agritourism businesses. Ordinary least squares (OLS) and interval regression techniques are used to estimate the revenue model. In the latter case, tests are performed to gauge the effects of different interval sizes on model estimates. There is also a lack of information relating the use of different marketing methods and agritourism visitation. This manuscript presents research examining the effect that different marketing methods have on the number of visitors a business receives. A visitation model is developed that measures the significance of seven distinct marketing methods. Three different specifications of the visitation model are considered: a linear model, a log-linear model and an exponential model estimated using a quasi-maximum likelihood (QML) estimator. The exponential method is based off research performed by Santos Silva and Tenreyro (2006) that shows log models can produce inconsistent parameter estimates when heteroscedasticity exists.Agricultural Economic

Comparison of Wild-Type versus Mutant L1CAM Expression in Cultured Neurons

The correct targeting of proteins to axons and dendrites of neurons is essential for the proper development of the nervous system. L1CAM is a cell-adhesion molecule responsible for multiple aspects of neuronal development; mutations are known to result in a developmental syndrome characterized by cognitive and motor disabilities. We expressed wild-type L1CAM and known L1CAM mutant proteins, P941L and D544N, in cultured embryonic chick forebrain neurons and compared their cellular distributions. Preliminary data suggests that both the wild-type L1CAM and the P941L L1CAM mutant are targeted to axons in a similar fashion. In contrast, the D544N L1CAM mutant does not appear to reach the cell surface of the neuron

Know your customers: Oklahoma agritourism visitor characteristics and opinions about a new liability law

The Oklahoma Cooperative Extension Service periodically issues revisions to its publications. The most current edition is made available. For access to an earlier edition, if available for this title, please contact the Oklahoma State University Library Archives by email at [email protected] or by phone at 405-744-6311

Creating a Resilient Watering System to Benefit Kids with Exceptional Needs at Farm and Nature-Based School

Research shows exposure to nature is critical for child development. Turn Back Time, Inc., (TBT) provides farm and nature-based programs for children, including those with exceptional needs, to learn and develop through play in nature. The farm’s gardens provide the context, materials, tools, and opportunities needed to run TBT’s programs. A drought in 2016 dried up the farm’s water source, killing the gardens. The purpose of this project was to engineer a resilient watering system to reduce the gardens’ vulnerability to drought while ensuring TBT’s programs, and their associated benefits, can continue

Hidden Markov Models and their Application for Predicting Failure Events

We show how Markov mixed membership models (MMMM) can be used to predict the degradation of assets. We model the degradation path of individual assets, to predict overall failure rates. Instead of a separate distribution for each hidden state, we use hierarchical mixtures of distributions in the exponential family. In our approach the observation distribution of the states is a finite mixture distribution of a small set of (simpler) distributions shared across all states. Using tied-mixture observation distributions offers several advantages. The mixtures act as a regularization for typically very sparse problems, and they reduce the computational effort for the learning algorithm since there are fewer distributions to be found. Using shared mixtures enables sharing of statistical strength between the Markov states and thus transfer learning. We determine for individual assets the trade-off between the risk of failure and extended operating hours by combining a MMMM with a partially observable Markov decision process (POMDP) to dynamically optimize the policy for when and how to maintain the asset.Comment: Will be published in the proceedings of ICCS 2020; @Booklet{EasyChair:3183, author = {Paul Hofmann and Zaid Tashman}, title = {Hidden Markov Models and their Application for Predicting Failure Events}, howpublished = {EasyChair Preprint no. 3183}, year = {EasyChair, 2020}

The Causes and Consequences of Nonenzymatic Protein Acylation.

Thousands of protein acyl modification sites have now been identified in vivo. However, at most sites the acylation stoichiometry is low, making functional enzyme-driven regulation in the majority of cases unlikely. As unmediated acylation can occur on the surface of proteins when acyl-CoA thioesters react with nucleophilic cysteine and lysine residues, slower nonenzymatic processes likely underlie most protein acylation. Here, we review how nonenzymatic acylation of nucleophilic lysine and cysteine residues occurs; the factors that enhance acylation at particular sites; and the strategies that have evolved to limit protein acylation. We conclude that protein acylation is an unavoidable consequence of the central role of reactive thioesters in metabolism. Finally, we propose a hypothesis for why low-stoichiometry protein acylation is selected against by evolution and how it might contribute to degenerative processes such as aging

Agritourism in Oklahoma

The Oklahoma Cooperative Extension Service periodically issues revisions to its publications. The most current edition is made available. For access to an earlier edition, if available for this title, please contact the Oklahoma State University Library Archives by email at [email protected] or by phone at 405-744-6311