Statistics and Probability Commons^™

The Relationship Between Pets Owned And Gender Amongst College Students, Eman Asghar, Bryce Camuso, Josh Feirick

Harrisburg University Research Symposium: Highlighting Research, Innovation, & Creativity

There is a gap between the number of men and women that own dogs. The Mintel Press Team states that "71% of men aged 18-44 own a dog compared to 60% of their female counterparts" (Mintel Press Team, 2016, para: 1). While this statistic includes people who are college-aged, it does not mention college students specifically. Thus, research into the relationship between pets owned and gender amongst college students is an important topic that warrants looking into.

The Knowledge Of One's Blood Type, Mackenzie Degroft, Ethan Hall, Scarlet Morillo

Harrisburg University Research Symposium: Highlighting Research, Innovation, & Creativity

An experiment of sample surveys of undergraduate students' knowledge of their blood type.

A Statistical Study Into The Number Of Hours Students At Harrisburg University Spend On Social Media, Nabeel Hakeem-Olowu, Samantha Weaver, Kyla Lea

Harrisburg University Research Symposium: Highlighting Research, Innovation, & Creativity

The aim of the study is to examine the number of hours that Harrisburg University students spent on social media during their spare time. The purpose of the study is to raise awareness among students about the possible negative impacts of excessive social media usage on their academic performance, social interactions, and sleep duration. Additionally, the study explored the relationship between social media use and academic performance. To collect data, we surveyed one hundred and fifty students from Harrisburg University. The survey consisted of questions related to the number of hours spent on social media during spare time. The respondents …

Data Sharing And Ontology Use Among Agricultural Genetics, Genomics, And Breeding Databases And Resources Of The Agbiodata Consortium, Jennifer L. Clarke, Laurel D. Cooper, Monica F. Poelchau, Tanya Z. Berardini, Justin Elser, Andrew D. Farmer, Stephen Ficklin, Sunita Kumari, Marie-Angélique Laporte, Rex T. Nelson, Rie Sadohara, Peter Selby, Anne E. Thessen, Brandon Whitehead, Taner Z. Sen

Department of Statistics: Faculty Publications

Over the last couple of decades, there has been a rapid growth in the number and scope of agricultural genetics, genomics and breeding databases and resources. The AgBioData Consortium (https://www.agbiodata.org/) currently represents 44 databases and resources (https://www.agbiodata.org/databases) covering model or crop plant and animal GGB data, ontologies, pathways, genetic variation and breeding platforms (referred to as ‘databases’ throughout). One of the goals of the Consortium is to facilitate FAIR (Findable, Accessible, Interoperable, and Reusable) data management and the integration of datasets which requires data sharing, along with structured vocabularies and/or ontologies. Two AgBioData working groups, focused on Data Sharing and …

Repurposing The Fda-Approved Anthelmintic Pyrvinium Pamoate For Pancreatic Cancer Treatment: Study Protocol For A Phase I Clinical Trial In Early-Stage Pancreatic Ductal Adenocarcinoma, Francesca M. Ponzini, Christopher W. Schultz, Benjamin E. Leiby, Shawnna Cannaday, T. Yeo, James Posey, Wilbur B. Bowne, Charles Yeo, Jonathan R. Brody, Harish Lavu, Avinoam Nevler

Department of Surgery Faculty Papers

BACKGROUND: Recent reports of the utilisation of pyrvinium pamoate (PP), an FDA-approved anti-helminth, have shown that it inhibits pancreatic ductal adenocarcinoma (PDAC) cell growth and proliferation in-vitro and in-vivo in preclinical models. Here, we report about an ongoing phase I open-label, single-arm, dose escalation clinical trial to determine the safety and tolerability of PP in PDAC surgical candidates.

METHODS AND ANALYSIS: In a 3+3 dose design, PP is initiated 3 days prior to surgery. The first three patients will be treated with the initial dose of PP at 5 mg/kg orally for 3 days prior to surgery. Dose doubling will …

Assessment Of First-Phase Covid-19 Pandemic In Europe Using Hierarchical Clustering Based On Principal Components Analysis, Sanjay Kumar, Evrim Oral

School of Public Health Faculty Publications

It is of great interest for researchers to assess the COVID-19 pandemic in Europe. Grouping of COVID-19-affected regions is an effective way to monitor and optimize planning to combat the disease. This paper applied hierarchical clustering based on principal components analysis (HCPCA) to COVID-19 data from affected European countries. Considering several attribute indices, we obtained a new set of indicators using principal components analysis to aggregate and reduce the dimension of attribute indices of affected countries. Further, we obtained groups of affected countries subject to their similarity using hierarchical clustering to the reduced observations of new attributes indices of these …

Exploring Parameter Sensitivity Analysis In Mathematical Modeling With Ordinary Differential Equations, Viktoria Savatorova

CODEE Journal

This paper presents an exploration into parameter sensitivity analysis in mathematical modeling using ordinary differential equations (ODEs). Taking the first steps in understanding local sensitivity analysis through the direct differential method and global sensitivity analysis using metrics like Pearson, Spearman, PRCC, and Sobol’, we provide readers with a basic understanding of parameter sensitivity analysis for mathematical modeling using ODEs. As an illustrative application, the system of differential equations modeling population dynamics of several fish species with harvest considerations is utilized. The results of employing local and global sensitivity analysis are compared, shedding light on the strengths and limitations of each …

Deep Q-Learning Framework For Quantitative Climate Change Adaptation Policy For Florida Road Network Due To Extreme Precipitation, Orhun Aydin

I-GUIDE Forum

Climate change-induced extreme weather and increasing population are increasing the pressure on the global aging road networks. Adaptation requires designing interventions and alterations to the road networks that consider future dynamics of flooding and increased traffic due to the growing population. This paper introduces a reinforcement learning approach to designing interventions for Florida's road network under future traffic and climate projections. Three climate models and a tide and surge model are used to create flooding and coastal inundation projections, respectively. The optimal sequence of decisions for adapting Florida's road network to minimize flooding-related disruptions is solved by using a graph-based …

Reducing Uncertainty In Sea-Level Rise Prediction: A Spatial-Variability-Aware Approach, Subhankar Ghosh, Shuai An, Arun Sharma, Jayant Gupta, Shashi Shekhar, Aneesh Subramanian

I-GUIDE Forum

Given multi-model ensemble climate projections, the goal is to accurately and reliably predict future sea-level rise while lowering the uncertainty. This problem is important because sea-level rise affects millions of people in coastal communities and beyond due to climate change's impacts on polar ice sheets and the ocean. This problem is challenging due to spatial variability and unknowns such as possible tipping points (e.g., collapse of Greenland or West Antarctic ice-shelf), climate feedback loops (e.g., clouds, permafrost thawing), future policy decisions, and human actions. Most existing climate modeling approaches use the same set of weights globally, during either regression or …

A Classical Fall Statistics Problem, Timothy Meyer

Cornhusker Economics

An evaluation of traditional baseball measures and suggestions for alternatives, centering on statistics related to the offensive quality of a player.

Es/Ph/Ra 626: Statistical Analysis I, Paul D. Loprinzi Ph.D.

GMAS Course Syllabi

No abstract provided.

Math 575: Mathematical Statistics I, Xin Dang

GMAS Course Syllabi

No abstract provided.

Academic Evaluation From The Perspective Of Multi-Source Eterogeneous Data:Connotation, Status And Prospect, Sanhong Deng, Jie Yang, Hao Wang, Jia Shen

Journal of Scientific Information Research

[Purpose/significance]Academic evaluation and scientometric methods of synthesizing multisource heterogeneous data have gradually become hot spots in the field. At present， there is no systematic theoretical discussion on academic evaluation from the perspective of multisource heterogeneous data.[Method/process]In view of insufficient utilization of multi-source heterogeneous data， inappropriate research methods， and unclear research objectives， this paper combs the development of academic evaluation from the perspective of multi-source heterogeneous data， and clarifies the connotation and extension of the field， and analyzes the frontiers and hot spots in the field.[Result/conclusion]The results state clearly that from the perspective of multi-source heterogeneous data， academic evaluation manifests the …

Beyond 365 Days: A Retrospective Evaluation Of Trekkers, Sarah Krichels Goan Mpp, Madison Burke

Publications

The Trekkers program in Rockland, ME is a non-profit outdoor-based mentoring program that has served young people in mid-coast Maine since 1994. Its unique long-term mentoring model supports students over six years that begins when they are in 7th grade and continues until they graduate high school. Trekkers’ model focuses on building social, emotional and intellectual resiliency in young people through one-to-one peer mentoring, as well as the use of expeditionary learning, community service and adventure-based education. Trekkers’ programs are designed to provide an ongoing supportive network for young people in the community by connecting them with caring adults while …

Dental Hygiene Students Reported Physiological Symptoms Associated With Wearing An N95 Respirator Mask, Peyton Shea Butler

Dental Hygiene Theses & Dissertations

Purpose: Physiological symptoms and comfort levels while wearing an N95 respiratory mask has not been examined with dental hygienists. The purpose of this study was to investigate dental hygiene students reported physiological symptoms and comfort perception while wearing an N95 respirator mask during patient care appointments. Methods: After IRB approval (IRB #1987754-2), a 16-item questionnaire was distributed through email to a convenience sample of 65 dental hygiene students. Questions assessed respiratory, dermatologic, cardiac, mask mouth and general physiological symptoms, as well as comfort levels. Additionally, participants were asked to respond to demographic questions and one open ended question inquiring about …

The Prevalence Of Burnout In Saudi Arabia Dental Hygienists, Nouf Hamad Aldayel

Dental Hygiene Theses & Dissertations

Purpose: The purpose of this pilot study was to assess the prevalence of burnout in Saudi Arabian dental hygienists and identify risk factors associated with burnout. Methods: A descriptive survey design using the Copenhagen Burnout Inventory (CBI) assessed burnout among a convenience sample of n=123 Saudi dental hygienists. The survey was disseminated electronically to 1,000 Saudi Arabian dental hygienists. The CBI measures three subscales: personal, work-related, and client/patient-related burnout on a five-point Likert-type scale. The survey also included six demographic questions, two Likert-type, one “yes/no,” and one openended question, related to burnout. Descriptive statistics, one-way between subject’s ANOVA, independent samples …

Bayesian Statistical Modeling Of Spatially Resolved Transcriptomics Data, Xi Jiang

Statistical Science Theses and Dissertations

Spatially resolved transcriptomics (SRT) quantifies expression levels at different spatial locations, providing a new and powerful tool to investigate novel biological insights. As experimental technologies enhance both in capacity and efficiency, there arises a growing demand for the development of analytical methodologies.

One question in SRT data analysis is to identify genes whose expressions exhibit spatially correlated patterns, called spatially variable (SV) genes. Most current methods to identify SV genes are built upon the geostatistical model with Gaussian process, which could limit the models' ability to identify complex spatial patterns. In order to overcome this challenge and capture more types …

Geographic Differences In The Magnitude Of Black-White Disparities In Having Obesity, Steven A. Cohen, Monique J. Brown, Furong Xu, Caitlin C. Nash, Mary L. Greaney

Faculty Publications

Background

Obesity disparities in the United States are well documented, but the limited body of research suggests that geographic factors may alter the magnitude of these disparities. A growing body of evidence has identified a “rural mortality penalty” where morbidity and mortality rates are higher in rural than urban areas, even after controlling for other factors. Black-White differences in health and mortality are more pronounced in rural areas than in urban areas.

Objective

Therefore, the purpose of this study was to explore how rural-urban status and region moderate Black-White health disparities in obesity.

Methods

Data were abstracted from the 2012 …

Multi-Representation Variational Autoencoder Via Iterative Latent Attention And Implicit Differentiation, Nhu Thuat Tran, Hady Wirawan Lauw

Research Collection School Of Computing and Information Systems

Variational Autoencoder (VAE) offers a non-linear probabilistic modeling of user's preferences. While it has achieved remarkable performance at collaborative filtering, it typically samples a single vector for representing user's preferences, which may be insufficient to capture the user's diverse interests. Existing solutions extend VAE to model multiple interests of users by resorting a variant of self-attentive method, i.e., employing prototypes to group items into clusters, each capturing one topic of user's interests. Despite showing improvements, the current design could be more effective since prototypes are randomly initialized and shared across users, resulting in uninformative and non-personalized clusters.To fill the gap, …

Lightning Forecast From Chaotic And Incomplete Time Series Using Wavelet De-Noising And Spatiotemporal Kriging, Jared K. Nystrom, Raymond Hill, Andrew J. Geyer, Joseph J. Pignatiello Jr., Eric Chicken

Faculty Publications

Purpose: Present a method to impute missing data from a chaotic time series, in this case lightning prediction data, and then use that completed dataset to create lightning prediction forecasts.

Design/Methodology/Approach: Using the technique of spatiotemporal kriging to estimate data that is autocorrelated but in space and time. Using the estimated data in an imputation methodology completes a dataset used in lighting prediction.

Findings: The techniques provided prove robust to the chaotic nature of the data, and the resulting time series displays evidence of smoothing while also preserving the signal of interest for lightning prediction.

Abstract © Emerald Publishing …