Physical Sciences and Mathematics Commons^™

Survey And Adjourn, Kentucky Alfalfa And Stored Forages Conference

Kentucky Alfalfa and Stored Forage Conference

No abstract provided.

How Good Is Our Kentucky Haylage? A Summary Of 2017-18 Farm Results, Jimmy C. Henning, Jeff Lehmkuhler, Levi Berg, April Wilhoit, Corinne Belton, Tommy R. Yankey

Kentucky Alfalfa and Stored Forage Conference

The ability to harvest moist forage as hay gives Kentucky producers many advantages, including timely harvest, higher forage quality, and less weathering loss over hay systems. The baleage system allows producers to utilize commonly available forage equipment (mowers, rakes, balers) rather than requiring choppers and silo structures or bags. Making high quality baleage requires timely access to bale wrappers.

Forward Of Kentucky Alfalfa And Stored Forages Conference [2019], Rehanon Pampell, S. Ray Smith

Kentucky Alfalfa and Stored Forage Conference

No abstract provided.

State Environmental Public Policies And The Interaction With Wholesale Electric Markets, Cynthia L. M. Holland

Sustainability Seminar Series

Several States, including New Jersey, pursued utility restructuring in the late 1990s, transitioning to competitive markets. Recognizing that those markets may not achieve the states’ environmental policy goals, many of these states have enacted legislation that offer incentives to clean or renewable energy sources. This seminar will discuss the jurisdictional tensions that have developed as a result of the integration of state environmental policies into the wholesale market.

Mathematical Modeling Of Lung Cancer Screening Studies, Deborah L. Goldwasser

Mathematics Colloquium Series

Lung cancer has the second highest cancer incidence, second only to prostate cancer in men and breast cancer in women. Furthermore, more cancer deaths are attributable to lung cancer than any other cancer for both genders. There is a high public health need for effective secondary prevention in the form of early detection and early treatment, complementary to smoking cessation efforts. The U.S. National Lung Screening Trial (NLST) demonstrated that non-small cell lung cancer (NSCLC) mortality can be reduced by 20% through a program of annual CT screening in high-risk individuals. However, CT screening regimens and adherence vary, potentially impacting …

Global Sustainability That Respects Cultural Diversity & Individual Health Needs, Meriterese Racanelli

Sustainability Seminar Series

The USA Centers for Disease Control and National Institutes of Health have classified excessive sodium consumption, high blood pressure and diabetes as national health epidemics across various ethnic cultures. The United Nations and other countries classify these as Global Epidemics. Interestingly,some ways to help fix this national and global health crisis can be found in the balance of sustainable environmentally-friendly agriculture, green technologies, and cultural competencies. Learn how sustainability studies, research, and jobs can still respect an individual’s ethnic heritage, culture, and nutritional health needs, while improving the community health at large... from local to global. Sustainability can help us …

Neural Shrubs: Using Neural Networks To Improve Decision Trees, Kyle Caudle, Randy Hoover, Aaron Alphonsus

SDSU Data Science Symposium

Decision trees are a method commonly used in machine learning to either predict a categorical response or a continuous response variable. Once the tree partitions the space, the response is either determined by the majority vote – classification trees, or by averaging the response values – regression trees. This research builds a standard regression tree and then instead of averaging the responses, we train a neural network to determine the response value. We have found that our approach typically increases the predicative capability of the decision tree. We have 2 demonstrations of this approach that we wish to present as …

Session: 4 Multilinear Subspace Learning And Its Applications To Machine Learning, Randy Hoover, Kyle Caudle Dr., Karen Braman Dr.

SDSU Data Science Symposium

Multi-dimensional data analysis has seen increased interest in recent years. With more and more data arriving as 2-dimensional arrays (images) as opposed to 1-dimensioanl arrays (signals), new methods for dimensionality reduction, data analysis, and machine learning have been pursued. Most notably have been the Canonical Decompositions/Parallel Factors (commonly referred to as CP) and Tucker decompositions (commonly regarded as a high order SVD: HOSVD). In the current research we present an alternate method for computing singular value and eigenvalue decompositions on multi-way data through an algebra of circulants and illustrate their application to two well-known machine learning methods: Multi-Linear Principal Component …

Predicting Unplanned Medical Visits Among Patients With Diabetes Using Machine Learning, Arielle Selya, Eric L. Johnson

SDSU Data Science Symposium

Diabetes poses a variety of medical complications to patients, resulting in a high rate of unplanned medical visits, which are costly to patients and healthcare providers alike. However, unplanned medical visits by their nature are very difficult to predict. The current project draws upon electronic health records (EMR’s) of adult patients with diabetes who received care at Sanford Health between 2014 and 2017. Various machine learning methods were used to predict which patients have had an unplanned medical visit based on a variety of EMR variables (age, BMI, blood pressure, # of prescriptions, # of diagnoses on problem list, A1C, …

Toward Unraveling The Mechanisms Of “Green” Mechanochemical Reactions, Richard Chen, Mehmet Kerem Gokus

Undergraduate Research Symposium

The mechanical processing of solids, such as milling or grinding powders, often leads to mechanochemical reactions. Mechanochemistry affords “green” synthetic routes avoiding or reducing the use of solvents, thus providing environmentally friendly and cost-effective synthetic alternatives for many materials. The solid-state reactants are usually ground together with small quantities of organic solvents, called “liquid assisted grinding” (LAG). LAG increases the reaction rates, it can yield products from otherwise unreactive mixtures, it increases the products crystallinity, and it selectively leads to crystal structures (polymorphs) of the products, depending on the quantities and physicochemical properties of the liquids used in LAG.

Mechanochemistry …

Plastics, Degradability, And The Environment, Peter Strom

Sustainability Seminar Series

Harmful environmental effects of plastics have long been condemned by activists, and some of these problems are well documented. However, in seeking to substitute other materials or make changes in the properties of the plastics themselves, it is important that the policies implemented do not worsen existing or create new environmental problems. This seminar will discuss some of the general concerns associated with this issue, such as the environmental impacts of using other materials instead of plastics, and then focus on degradable plastics. What is degradability, when might it be valuable, and will these products in fact degrade? Results of …

2018 Long-Term Summary Of Kentucky Forage Variety Trials, Gene L. Olson, S. Ray Smith, Jimmy C. Henning, Christopher D. Teutsch

Forage Symposium at the Kentucky Cattlemen’s Convention

Forage crops occupy approximately 7 million acres in Kentucky. Forages provide a majority of the nutrition for beef, dairy, horse, goat, sheep, and wildlife in the state. In addition, forage crops play an environmentally friendly role in soil conservation, water quality, and air quality. There are over 60 forage species adapted to the climate and soil conditions of Kentucky. Only 10 to 12 of these species occupy the majority of the acreage, but within these species there is a tremendous variation in varieties.

This publication was developed to provide a user-friendly guide to choosing the best variety for producers based …

A Global Database Of Surface Urban Heat Island Intensity, Tc Chakraborty, Xuhui Lee

Yale Day of Data

The urban heat island (UHI) effect - the phenomenon of higher temperatures in urban environments - is one of the most well-known consequences of urbanization on local climate. We develop the simplified urban-extent (SUE) algorithm, a new algorithm to estimate the urban heat island (UHI) intensity at a global scale. This algorithm is implemented on the Google Earth Engine platform and uses satellite-derived images to calculate the surface UHI intensity for over 9500 urban clusters covering 15 years, making this the most comprehensive global UHI database. The data are validated against previous multi-city studies and then used to estimate the …

Topovar90m: Global High-Resolution Topographic Variables For Environmental Modeling, Giuseppe Amatulli Dr.

Yale Day of Data

Topographical relief involves the vertical and horizontal variation of the Earth's terrain and it drives processes in hydrology, climatology, geography and ecology. Its assessment and characterization is fundamental for various types of modeling and simulation analysis. In this regard, the Multi-Error-Removed Improved Terrain (MERIT) Digital Elevation Model (DEM) currently provides the best high-resolution DEM globally available, at a 3 arc-second resolution (90m), due to the removal of multiple error components from the underlying SRTM3 and AW3D30 DEMs. To depict topographical variations worldwide, we developed a new dataset comprising different terrain features derived from the MERIT-DEM. The fully standardized topographical variables …

Non-Invasive Analysis Of The Sputum Transcriptome Discriminates Clinical Phenotypes Of Asthma, Xiting Yan

Yale Day of Data

Whole transcriptome wide gene expression profiles in the sputum and circulation from 100 asthma patients were measured using the Affymetrix HuGene 1.0ST arrays. Unsupervised clustering analysis based on pathways from KEGG were used to identify TEA clusters of patients from the sputum gene expression profiles. The identified TEA clusters have significantly different pre-bronchodilator FEV1, bronchodilator responsiveness, exhaled nitric oxide levels, history of hospitalization for asthma and history of intubation. Evaluation of TEA clusters in children from Asthma BRIDGE cohort confirmed the identified differences in intubation and hospitalization. Furthermore, evaluation of the TH2 gene signatures suggested a much lower prevalence of …

A Novel Pathway-Based Distance Score Enhances Assessment Of Disease Heterogeneity In Gene Expression, Yunqing Liu, Xiting Yan

Yale Day of Data

Distance-based unsupervised clustering of gene expression data is commonly used to identify heterogeneity in biologic samples. However, high noise levels in gene expression data and the relatively high correlation between genes are often encountered, so traditional distances such as Euclidean distance may not be effective at discriminating the biological differences between samples. In this study, we developed a novel computational method to assess the biological differences based on pathways by assuming that ontologically defined biological pathways in biologically similar samples have similar behavior. Application of this distance score results in more accurate, robust, and biologically meaningful clustering results in both …

Analyzing Neuronal Dendritic Trees With Convolutional Neural Networks, Olivier Trottier, Jonathon Howard

Yale Day of Data

In the biological sciences, image analysis software are used to detect, segment or classify a variety of features encountered in living matter. However, the algorithms that accomplish these tasks are often designed for a specific dataset, making them hardly portable to accomplish the same tasks on images of different biological structures. Recently, convolutional neural networks have been used to perform complex image analysis on a multitude of datasets. While applications of these networks abound in the technology industry and computer science, use cases are not as common in the academic sciences. Motivated by the generalizability of neural networks, we aim …

Health Risk Tolerance As A Key Determinant Of (Un)Willingness To Behavior Change: Conceptualization And Scale Development, Hyoyeun Jun, Yan Jin

International Crisis and Risk Communication Conference

After the study of testing determinants of risk tolerance affecting information sharing, this study was conducted as a second step to actually develop the scale for risk tolerance. Firstly, this study followed qualitative steps, such as in-depth interview and focus group, to capture how public describes the situation when they are tolerating the risk, when they knew what the recommended behavior is to relieve the risk. Secondly, this study collected 1000 U.S. public sample for the survey questionnaire that are the items generated from the qualitative steps.