Statistics and Probability Commons^™

Measuring The Performance Of Sdgs In Provincial Level Using Regional Sustainable Development Index, Nurafiza Thamrin, Ika Yuni Wulansari, Puguh Bodro Irawan

Journal of Environmental Science and Sustainable Development

Measuring the national and sub-national progress in achieving such globally adopted development agendas as Sustainable Development Goals (SDGs) is particularly challenging due to data availability and compatibility of indicators to measure SDGs, especially in Indonesia. This paper attempts to measure the performance of sustainable development at the regional level in Indonesia by newly constructing a multidimensional composite index called the Regional Sustainable Development Index (RSDI). RSDI comprises four dimensions, covering comprehensive economic, social, environmental, and governance indicators. By applying factor analysis, the paper assesses the uncertainty of RSDI and the sensitivity of its composing indicators, then further investigates the relationship …

Reducing Food Scarcity: The Benefits Of Urban Farming, S.A. Claudell, Emilio Mejia

Journal of Nonprofit Innovation

Urban farming can enhance the lives of communities and help reduce food scarcity. This paper presents a conceptual prototype of an efficient urban farming community that can be scaled for a single apartment building or an entire community across all global geoeconomics regions, including densely populated cities and rural, developing towns and communities. When deployed in coordination with smart crop choices, local farm support, and efficient transportation then the result isn’t just sustainability, but also increasing fresh produce accessibility, optimizing nutritional value, eliminating the use of ‘forever chemicals’, reducing transportation costs, and fostering global environmental benefits.

Imagine Doris, who is …

Genome-Wide Search Algorithms For Identifying Dynamic Gene Co-Expression Via Bayesian Variable Selection, Wenda Zhang, Zichen Ma, Lianming Wang, Daping Fan, Yen Yi Ho

Faculty Publications

A wealth of gene expression data generated by high-throughput techniques provides exciting opportunities for studying gene-gene interactions systematically. Gene-gene interactions in a biological system are tightly regulated and are often highly dynamic. The interactions can change flexibly under various internal cellular signals or external stimuli. Previous studies have developed statistical methods to examine these dynamic changes in gene-gene interactions. However, due to the massive number of possible gene combinations that need to be considered in a typical genomic dataset, intensive computation is a common challenge for exploring gene-gene interactions. On the other hand, oftentimes only a small proportion of gene …

Cabozantinib Plus Atezolizumab In Previously Untreated Advanced Hepatocellular Carcinoma And Previously Treated Gastric Cancer And Gastroesophageal Junction Adenocarcinoma: Results From Two Expansion Cohorts Of A Multicentre, Open-Label, Phase 1b Trial (Cosmic-021)., Daneng Li, Yohann Loriot, Adam Burgoyne, James Cleary, Armando Santoro, Daniel Lin, Santiago Ponce Aix, Ignacio Garrido-Laguna, Ramu Sudhagoni, Xiang Guo, Svetlana Andrianova, Scott Paulson

Kimmel Cancer Center Faculty Papers

BACKGROUND: Cabozantinib is approved for previously treated advanced hepatocellular carcinoma (aHCC) and has been investigated in gastric cancer (GC) and gastroesophageal junction adenocarcinoma (GEJ). Atezolizumab plus bevacizumab is approved for unresectable or metastatic HCC untreated with prior systemic therapy. We evaluated efficacy and safety of cabozantinib plus atezolizumab in aHCC previously untreated with systemic anticancer therapy or previously treated GC/GEJ.

METHODS: COSMIC-021 (ClinicalTrials.gov, NCT03170960) is an open-label, phase 1b study in solid tumours with a dose-escalation stage followed by tumour-specific expansion cohorts, including aHCC (cohort 14) and GC/GEJ (cohort 15). Eligible patients were aged ≥18 years with measurable locally advanced, …

Cancer Survivorship And Subjective Cognitive Decline In The Us: Results From A Nationally Representative Sample, Monique J. Brown, Ally Hucek, Jingkai Wei, Loretta Anderson, Muzi Na

Faculty Publications

Cancer may be associated with objective cognitive decline. However, studies examining the link between cancer and subjective cognitive decline (SCD), which occurs earlier during cognitive trajectories, are lacking. In addition, research assessing risk factors for SCD among cancer survivors is scant. Therefore, this study aimed to examine the association between cancer and SCD in the past year, and assess the association between age of diagnosis, cancer treatment, and SCD among cancer survivors. Data were obtained from the 2021 Behavioral Risk Factor Surveillance System (N=15,447). Crude and adjusted logistic regression models, controlling for sociodemographic characteristics, were used to determine the association …

Market Making In Limit Order Books With Latency And Running Inventory Control, Chang Liu

Arts & Sciences Graduate Student Theses and Dissertations

In this thesis, we delve into the intricate optimization challenges of market making, the concurrent provision of buy and sell prices in financial assets. The focus is particularly on the complexities inherent in high-frequency trading scenarios, addressing optimal market making in the presence of latency and incorporating a running inventory penalty. The initial exploration involves the formulation of a stochastic control model that aptly captures the actions of an electronic market maker navigating a trading environment influenced by latency. The main objective of the market maker lies in the maximization of expected terminal wealth. To systematically address and resolve this …

Challenges And Countermeasures For Treatment And Remediation Of Contaminated Mega-Sites In China, Xiaoyong Liao, Yixuan Hou, You Li, Tianyi Wang

Bulletin of Chinese Academy of Sciences (Chinese Version)

The treatment and remediation of pollution at contaminated mega-sites poses a significant challenge in the environmental science both domestically and internationally. Contaminated mega-sites are characterized by their widespread impact, multiple types of pollutants, and significant ecological and environmental threats. The environmental behavior cognition and efficient remediation at contaminated mega-sites face enormous challenges, among which key technological issues such as the formation mechanism of soil and groundwater pollution, accurate identification of pollution sources, and intelligent decision-making optimization urgently need to be solved. In China, contaminated mega-sites are concentrated in economically developed regions such as Beijing-Tianjin-Hebei, the Yangtze River Economic Belt, and …

Atmospheric 14Co2 Observation: A Novel Method To Evaluate Carbon Emissions, Zhenchuan Niu, Peng Wang, Shugang Wu, Weijian Zhou

Bulletin of Chinese Academy of Sciences (Chinese Version)

As an important carbon emitter, China faces the stress of carbon peaking and carbon neutrality goals and international carbon reduction duty. The accurate data of carbon emissions are important to evaluate the carbon peaking and carbon neutrality goals and fulfill the international duty of carbon reduction. The Intergovernmental Panel on Climate Change (IPCC) report recommends the combination of top-down atmospheric CO₂ observation with atmospheric inversion to verify the bottom-up inventory of carbon emissions, and the atmospheric ¹⁴CO₂ observation can make the verification more accurate. Radiocarbon (14C) is the most precise tracer of fossil fuel CO₂ and …

Spatial Agglomeration And Environmental Effects Of Heavy Polluting Industries In China: Characteristics And Enlightenment, Hongyang Chen, Jianhui Yu, Wenzhong Zhang

Bulletin of Chinese Academy of Sciences (Chinese Version)

Heavy polluting industries are the important sources of industrial pollutant. Understanding the spatial agglomeration characteristics, influencing factors, agglomeration mechanism and environmental effects of China’s heavy polluting industries can help identify potential pollution risk areas to cope with increasingly severe environmental pollution problems. Based on the industrial economic data from 1999 to 2021, the spatial distribution and agglomeration characteristics of heavy polluting industries are characterized. It is found that: (1) Shandong, Jiangsu, Zhejiang, and Guangdong are the regions with high output value of the development of heavy polluting industries in the past 20 years, while Xinjiang, Inner Mongolia, Shanxi, Shaanxi, Henan, …

Prt543, A Protein Arginine Methyltransferase 5 Inhibitor, In Patients With Advanced Adenoid Cystic Carcinoma: An Open-Label, Phase I Dose-Expansion Study, Renata Ferrarotto, Paul Swiecicki, Dan Zandberg, Robert Baiocchi, Robert Wesolowski, Cristina Rodriguez, Meredith Mckean, Hyunseok Kang, Varun Monga, Rajneesh Nath, Neil Palmisiano, Naveen Babbar, William Sun, Glenn Hanna

Department of Medical Oncology Faculty Papers

OBJECTIVES: Currently, no systemic treatments are approved for patients with recurrent and/or metastatic (R/M) adenoid cystic carcinoma (ACC). PRT543, a protein arginine methyltransferase 5 inhibitor that downregulates NOTCH1 and MYB signalling in tumours, is a potential candidate for R/M ACC treatment. We report the safety, tolerability and preliminary efficacy of PRT543 in a dose-expansion cohort of patients with R/M ACC.

MATERIALS AND METHODS: This phase I multicentre, open-label, sequential-cohort, dose-escalation and dose-expansion study (NCT03886831) enrolled patients with advanced solid tumours and select haematologic malignancies. Dose-escalation study design and results were reported previously. In the dose expansion, patients with R/M ACC …

Stereotactic Mr-Guided On-Table Adaptive Radiation Therapy (Smart) For Borderline Resectable And Locally Advanced Pancreatic Cancer: A Multi-Center, Open-Label Phase 2 Study, Michael Chuong, Percy Lee, Daniel Low, Joshua Kim, Kathryn Mittauer, Michael Bassetti, Carri Glide-Hurst, Ann Raldow, Yingli Yang, Lorraine Portelance, Kyle Padgett, Bassem Zaki, Rongxiao Zhang, Hyun Kim, Lauren Henke, Alex Price, Joseph Mancias, Christopher Williams, John Ng, Ryan Pennell, M Raphael Pfeffer, Daphne Levin, Adam Mueller, Karen Mooney, Patrick Kelly, Amish Shah, Luca Boldrini, Lorenzo Placidi, Martin Fuss, Parag Jitendra Parikh

Department of Radiation Oncology Faculty Papers

BACKGROUND AND PURPOSE: Radiation dose escalation may improve local control (LC) and overall survival (OS) in select pancreatic ductal adenocarcinoma (PDAC) patients. We prospectively evaluated the safety and efficacy of ablative stereotactic magnetic resonance (MR)-guided adaptive radiation therapy (SMART) for borderline resectable (BRPC) and locally advanced pancreas cancer (LAPC). The primary endpoint of acute grade ≥ 3 gastrointestinal (GI) toxicity definitely related to SMART was previously published with median follow-up (FU) 8.8 months from SMART. We now present more mature outcomes including OS and late toxicity.

MATERIALS AND METHODS: This prospective, multi-center, single-arm open-label phase 2 trial (NCT03621644) enrolled 136 …

Bitcoin Price Modeling Using Machine Learning Algorithms, Azadeh Golduzian

Mathematics & Statistics ETDs

Forecasting in financial markets with various technologies is critical nowadays. The Bitcoin cryptocurrency has grown in popularity in recent years, and as a result, many people all around the world have attempted to forecast its price. To improve forecast accuracy, we must employ multiple types of data and diverse approaches. This thesis combines textual and financial data and employs statistical methods and machine learning to forecast Bitcoin's price as precisely as possible. We show the performance of each strategy using Bitcoin data at the end of each chapter.

Interpretable Word-Level Sentiment Analysis With Attention-Based Multiple Instance Classification Models, Chenyu Yang

Statistical Science Theses and Dissertations

In this study, our main objective is to tackle the black-box nature of popular machine learning models in sentiment analysis and enhance model interpretability. We aim to gain more insight into the decision-making process of sentiment analysis models, which is often obscure in those complex models. To achieve this goal, we introduce two word-level sentiment analysis models.

The first model is called the attention-based multiple instance classification (AMIC) model. It combines the transparent model structure of multiple instance classification and the self-attention mechanism in deep learning to incorporate the contextual information from documents. As demonstrated by a wine review dataset …

Deep Learning For Microbiome-Based Integrative Modeling And Microbial Biomarkers Identification, Sen Yang

Statistical Science Theses and Dissertations

The human microbiome, comprising trillions of microorganisms, plays a pivotal role in modulating host physiology via molecular and metabolite exchanges. One of the major challenges in this field lies in the effective integration of microbiome and metabolomics data, an achievement that holds the promise of substantially enhancing the precision of disease prediction. However, many datasets prioritize microbiome data while neglecting paired metabolome information. Additionally, the prevalent analytical tools face challenges in effectively merging these intricate datasets, leading to possible misinterpretations and reduced prediction accuracies.

To address these challenges, the first part of this research introduces the Microbiome-based Supervised Contrastive Learning …

Microplate-Like Metal Pyrophosphate Engineered On Ni-Foam Towards Multifunctional Electrode Material For Energy Conversion And Storage, Rishabh Srivastava

Electronic Theses & Dissertations

High clean energy demand, dire need for sustainable development, and low carbon footprints are the few intuitive challenges, leading researchers to aim for research and development for high-performance energy devices. The development of materials used in energy devices is currently focused on enhancing the performance, electronic properties, and durability of devices. Tunning the attributes of transition metals using pyrophosphate (P₂O₇) ligand moieties can be a promising approach to meet the requirements of energy devices such as water electrolyzers and supercapacitors, although such a material’s configuration is rarely exposed for this purpose of study.

Herein, we grow …

Test Event Example 12/14/23, Metzalli Demolastname

Annual Research Symposium

No abstract provided.

Ohio Recovery Housing: Resident Risk And Outcomes Assessment, Elyjiah Potter, Bivin Sadler

SMU Data Science Review

Addiction and substance abuse disorder is a significant problem in the United States. Over the past two decades, the United States has faced a boom in substance abuse, which has resulted in an increase in death and disruption of families across the nation. The State of Ohio has been particularly hard hit by the crisis, with overdose rates nearly doubling the national average. Established in the mid 1970’s Sober Living Housing is an alcohol and substance use recovery model emphasizing personal responsibility, sober living, and community support. This model has been adopted by the Ohio Recovery Housing organization, which seeks …

Differentiation Of Human, Dog, And Cat Hair Fibers Using Dart Tofms And Machine Learning, Laura Ahumada, Erin R. Mcclure-Price, Chad Kwong, Edgard O. Espinoza, John Santerre

SMU Data Science Review

Hair is found in over 90% of crime scenes and has long been analyzed as trace evidence. However, recent reviews of traditional hair fiber analysis techniques, primarily morphological examination, have cast doubt on its reliability. To address these concerns, this study employed machine learning algorithms, specifically Linear Discriminant Analysis (LDA) and Random Forest, on Direct Analysis in Real Time time-of-flight mass spectra collected from human, cat, and dog hair samples. The objective was to develop a chemistry- and statistics-based classification method for unbiased taxonomic identification of hair. The results of the study showed that LDA and Random Forest were highly …

The Dose-Response Effect Of Aerobic Exercise On Inflammation In Colon Cancer Survivors, Justin C. Brown, Stephanie L.E. Compton, Jeffrey A. Meyerhardt, Guillaume Spielmann, Shengping Yang

School of Medicine Faculty Publications

Background; Physical activity after surgical resection for colon cancer is associated with significantly longer disease-free survival. Inflammation is hypothesized to mediate the association between physical activity and disease-free survival in colon cancer. Methods; In this exploratory analysis of a randomized dose-response trial, 39 colon cancer survivors who completed standard therapy were stratified by cancer stage and randomized in a 1;1;1 ratio to one of three treatment groups for 24 weeks of usual-care control, 150 min/wk of moderate-intensity aerobic exercise (low-dose), or 300 min/wk of moderate-intensity aerobic exercise (high-dose). Inflammation outcomes included high-sensitivity C-reactive protein (hs-CRP), interleukin-6 (IL6), and soluble tumor …

Occupational And Environmental Factors Influencing Morale Of United States Federal Wildland Firefighters, Rachel M. Granberg, Ting Shen, Seth W. Pearson, Robin M. Verble

Psychological Science Faculty Research & Creative Works

Background. Wildland firefighters have physically and psychologically demanding jobs that can result in social, economic and health-related stress. Previous studies have examined the physiological and physical effects of a career in wildland fire, but fewer studies have addressed psychological effects, and to date, none have directly analyzed the hiring and work experiences of wildland firefighters. Aims. We surveyed work experiences, health and well-being, and morale of wildland firefighters, explored factors that can improve recruitment and retention, and summarized broad patterns. Methods. We conducted a voluntary anonymous survey of 708 federal wildland firefighters via an online platform over 2 months in …

Developing A Precision Agriculture Framework To Assess Financial Viability Of Decisions In Farming And Conservation, Jennifer Sublett

Theses and Dissertations

Agricultural producers are invested in managing the impacts of crop damage on their yields and profit. When damage occurs early enough in an agricultural growing season, farmers have the option to replant their corn stand in an effort to recoup some of the lost profits. In this thesis two different types of naturally occurring damage, wildlife depredation and persistent weed or insect patches, were simulated on two representative regions of Mississippi. These data were then used to assess the financial viability of a range of damage mitigation methods, including partial replanting, enrollment into a government conservation buffer, and no action. …

Investigating The Effects Of A Southward Flow In The Southeastern Florida Shelf Using Robotic Instruments, Alfredo Quezada

All HCAS Student Capstones, Theses, and Dissertations

We deployed a Slocum G3 glider fitted with an acoustic Doppler current profiler (ADCP), a Conductivity-Temperature-Depth sensor (CTD), optics sensor channels, and a propeller on the Southeastern Florida shelf. The ADCP and CTD provide continuous measurements of Northern and Eastern current velocity components, salinity, temperature, and density, throughout the water column in a high-current environment. The optics sensor channels are able to provide measurements of chlorophyll concentrations, colored dissolved organic matter (CDOM), and backscatter particle counts. Additionally, for one of the glider deployments, we deployed a Wirewalker wave-powered profiling platform system also fitted with an ADCP and a CTD in …

Climate Change Impact On Bridge Scour Risk In Ny State: A Gis-Based Risk Analysis Model, Muhammad Hassan Butt

Publications and Research

Bridge scour, the primary cause of bridge failure in the United States, escalates post-severe storms, necessitating effective mitigation. This study employs a GIS-based risk analysis model to assess climate change's impact on bridge scour and associated risks in New York State. Data from the National Bridge Inventory, climate hazard maps, and geospatial data are integrated.

Optimal Stopping And Related Topics, Jackson Scott Hebner

Honors Scholar Theses

Suppose we are observing a randomly evolving system and have the ability to freeze it at any time. If we want to maximize some function of the state of the system, how can we determine the best time to freeze the system based on observations only up until the present moment? That is, without seeing the future, how can we form a rule for stopping the system such that we optimize the expected value of the function of interest to us? This is an informal statement of the concept of optimal stopping, a topic with deep theory and numerous applications. …

Development Of An App For The Kalamazoo Nature Center, Ernest Au

Honors Theses

Kalamazoo Nature Center (KNC), which has been recognized by its peers as one of the top nature centers in the country, is home to over 14 miles of hiking trails winding through woods, wetlands, and prairies. There are numerous places/plots in KNC that have an interesting and impressive history besides being home to a variety of animals and hundreds of wildflowers and other plant life. To improve the visitor’s experience at KNC, we will design a software app via the senior capstone project at the department of Computer Science at WMU. As the first step towards establishing a reference model …

Teaching Reproducibility To First Year College Students: Reflections From An Introductory Data Science Course, Brennan L. Bean

Journal on Empowering Teaching Excellence

Access the online Pressbooks version of this article here.

Modern technology threatens traditional modes of classroom assessment by providing students with automated ways to write essays and take exams. At the same time, modern technology continues to expand the accessibility of computational tools that promise to increase the potential scope and quality of class projects. This paper presents a case study where students are asked to complete a “reproducible” final project in an introductory data science course using the R programming language. A reproducible project is one where an instructor can easily regenerate the results and conclusions from the submitted …

Analyzing The Efficacy Of Covid-19 Travel Bans: A Regression Analysis Approach, Mallory Kochanek

Honors Projects

Some might associate the term ‘public health’ with the pandemic that occurred in 2020. COVID-19 spread like most have never seen in their lifetime. It is useful to look at the effectiveness of the travel re- strictions in mitigating the spread of the global pandemic. Using linear regression and network regression, we obtain parameter estimates to determine the relation of predictors, such as network effect, percentage of urban population and GDP, on the COVID-19 incidence rate for the months January to April of 2020. Linear regression does not ac- count for the correlation structure of the data. Network regression, on …

Is The Declining Birthrate Really An Issue For The Economy?, Harsh Ramesh Pednekar, Theodore Lee, Darrion Chin

Introduction to Research Methods RSCH 202

This study aims to explore the complex implications of declining birth rates on the economy, focusing on GDP per capita as a crucial metric, and aims to uncover both potential opportunities and challenges stemming from this demographic transformation using regression analysis. Using a quantitative methodology and secondary data from OECD.stat, World Population Review, and World Bank, the study explores the relationship between declining birth rates and economic impacts. GDP per capita serves as an essential dependent variable, and it accounts for control variables such as labour force participation, literacy, and education levels, child dependence ratio, and physical capital. Past studies …

Bitcoin And South African Stock Market Returns During Covid-19 Pandemic: A Test Of The Safe-Haven Hypothesis, Akaninyene U. Udom, Sopuru W. Nnamani

CBN Journal of Applied Statistics (JAS)

This paper tests the safe-haven property of Bitcoin for South African stocks using Full and Diagonal BEKK-GARCH models. The study uses the Johannesburg stock exchange Top40 index, and bitcoin returns data before COVID-19 (August 2018 to December 2019) and during COVID-19 (January 2020 to June 2021). The results show that bitcoin cannot be considered as safe-haven for stocks in South Africa since it is weakly correlated with stock and had a high volatility during the Pandemic. Therefore, the safe-haven hypothesis of bitcoin on South African stocks is not true for the period under study. The policy implication is that bitcoin …

Bingroup2: Statistical Tools For Infection Identification Via Group Testing, Christopher R. Bilder, Brianna D. Hitt, Brad J. Biggerstaff, Joshua M. Tebbs, Christopher S. Mcmahan

Department of Statistics: Faculty Publications

Group testing is the process of testing items as an amalgamation, rather than separately, to determine the binary status for each item. Its use was especially important during the COVID-19 pandemic through testing specimens for SARS-CoV-2. The adoption of group testing for this and many other applications is because members of a negative testing group can be declared negative with potentially only one test. This subsequently leads to significant increases in laboratory testing capacity. Whenever a group testing algorithm is put into practice, it is critical for laboratories to understand the algorithm’s operating characteristics, such as the expected number of …