Examining the Effect of Personal Classroom Friendships with Online Learning

Friendships within learning environments have been established as valuable aspects of supporting student success. The literature clearly shows that: 1) a student can achieve a better grade depending on how he/she perceives the task in terms of level of difficulty, and 2) a student can perceive the level of difficulty to be more or less difficult, depending on who is in the room with him/her during the task. If task difficulty can be linked to perceived friendships in the room, then fostering friendships in a classroom could play a crucial role to improving performance. As universities continue to embrace online formats, an important question becomes how can friendships be fostered to improve student performance? We surveyed students at Bryant University to study this question. The students had completed the same marketing course, in either a traditional classroom setting, or as an online course, taught by the same professor during the same semester. Students were asked about their perceptions of the course and performance, as well as their interaction with each other and the instructor. We found that this course was able to foster friendships, despite the format, and that students themselves perceived this as a component of their own success

Inference of Gene Co-expression Networks from Single-Cell RNA-Sequencing Data

Single-cell RNA-sequencing is a pioneering extension of bulk-base RNA-sequencing technology. The guilt-by-association heuristic has led to the use of gene co-expression networks to identify genes that are believed to be associated with a common cellular function. Many methods that were developed for bulk-based RNA-sequencing data can continue to be applied to single-cell data, and several of the most widely used methods are explored. Several methods for leveraging the novel time information contained in single-cell data when constructing gene co-expression networks, which allows for the incorporation of directed associations, are also discussed

Making an Impact: Creating a University Student-Driven Statistical Consulting Group for Non-Profits

A common problem in mathematics and statistics departments at academic institutions is providing students with experience working with real data in place of the often sanitized “toy” datasets used in the classroom. A solution can be creating mutually beneficial collaborations with local organizations and businesses. This paper discusses the creation of the Bryant University Statistical Consulting Office (BUSCO), and explores both its successes and challenges, with the purpose of guiding and inspiring other colleges and universities in establishing similar organizations. In particular, we discuss the challenges involved with obtaining funding, identifying and partnering with non-profits, and guiding students through meaningful and purposeful consulting experiences. We also share some note-worthy project outcomes

The Effects of Sampling Methods on Machine Learning Models for Predicting Long-term Length of Stay: A Case Study of Rhode Island Hospitals

The ability to predict the patients with long-term length of stay (LOS) can aid a hospital\u27s admission management, maintain effective resource utilization and provide a high quality of inpatient care. Hospital discharge data from the Rhode Island Department of Health from the time period between 2010 to 2013 reveals that inpatients with long-term stays, i.e. two weeks or more, costs about six times more than those with short stays while only accounting for 4.7% of the inpatients. With the imbalance in the distribution of long-stay patients and short-stay patients, predicting long-term LOS patients becomes an imbalanced classification problem. Sampling methods—balancing the data before fitting it to a traditional classification model—offer a simple approach to the problem. In this work, the authors propose a new resampling method called RUBIES which provides superior predictive ability when compared to other commonly used sampling techniques

Predicting the Length of Stay in Hospital Emergency Rooms in Rhode Island

In this study, the authors focus on the prediction of LOS at the time of admission in emergency departments at Rhode Island hospitals through discharge data obtained from the Rhode Island Department of Health over the time period of 2012 and 2013. This work also explores the distribution of discharge dispositions in an effort to better characterize the resources patients require upon leaving the emergency department

Rab11b-mediated integrin recycling promotes brain metastatic adaptation and outgrowth

Mechanisms governing adaptation of breast cancer to the brain metastatic microenvironment are unclear. Here, the authors use RNA-sequencing and Drosophila screening to identify Rab11b-mediated endosomal recycling as a unique mechanism for adaptation to a challenging metastatic microenvironment, which can be exploited by repurposing statins