Sentiment without Sentiment Analysis: Using the Recommendation Outcome of Steam Game Reviews as Sentiment Predictor

This paper presents and explores a novel way to determine the sentiment of a Steam game review based on the predicted recommendation of the review, testing different regression models on a combination of Term Frequency-Inverse Document Frequency (TF-IDF) and Latent Dirichlet Allocation (LDA) features. A dataset of Steam game reviews extracted from the Programming games genre consisting of 21 games along with other significant features such as the number of helpful likes on the recommendation, number of hours played, and others. Based on the features, they are grouped into three datasets: 1) either having keyword features only, 2) keyword features with the numerical features, and 3) numerical features only. The three datasets were trained using five different regression models: Multilinear Regression, Lasso Regression, Ridge Regression, Support Vector Regression, and Multi-layer Perceptron Regression, which were then evaluated using RMSE, MAE, and MAPE. The review recommendation was predicted from each model, and the accuracy of the predictions were measured using the different error rates. The results of this research may prove helpful in the convergence of Machine Learning and Educational Games

Soil-less Soil Study - A Sustainable Solution for Green Infrastructure Soil Media - Part 1, Life Cycle Assessment

The management of waste glass is of great concern worldwide due to its non-combustible and non-putrescible nature. Additionally, there is an urgent need for more sustainable alternatives and sources for aggregate, as the world is running out of quarried sand for use in construction. The Soil-less Soils Project, which is currently being run by the Philadelphia-based landscape architecture firm, OLIN, in partnership with the University of Pennsylvania and Temple University, is located at the nexus of two pressing environmental issues associated with urban development: a scarcity of sand and an overabundance of post-consumer glass. To solve these problems, the research initiative aims to develop and test a low-carbon footprint, rapidly renewable manufactured soil mix for use in green infrastructure and urban planting applications. The principle components of the mix are Class A biosolids and fine-ground recycled glass cullet. While the primary goals of the Soil-less Soils Project are environmental, the use of glass, an inert material, in place of mineral aggregate may also provide benefits in terms of soil function and uniformity in designed landscapes. To assess the environmental impacts of the substitution of natural sand with glass fines in the Soil-less Soil mix, a comparative cradle-to-gate life cycle analysis (LCA) was performed on the two materials. This is the first ever LCA study on recycled aggregates from waste glass in the landscape architecture industry, which was based on both the database and the first hand data. The results reveal that compared with the conventional sand, recycled aggregates produced from waste glass reduce 67% greenhouse gases (GHGs) emission with a saving of 48% water usage. The positive outcomes of the study will provide guidance on maximizing waste glass recycling and encourage the use of waste glass in the green infrastructure application

Immersive Virtual Reality Training Improved Upper Extremity Function in Patients with Spinal Cord Injuries: A Case Series

Virtual reality (VR) is an emerging treatment tool to engage people in environments that appear and feel similar to real-world objects and events.1 There are various levels of evidence that VR can potentially promote functional activity and neuroplasticity in patients with neurological disorders like spinal cord injury (SCI).2,3 In this case series, we explored the feasibility of using commercially available immersive VR technology as an augmented treatment in the SCI population and compare participant’s suitability for this intervention. Three male SCI participants were recruited in a subacute inpatient rehabilitation facility and participated in VR intervention twice a week in addition to their conventional therapies. Manual strength and functional testing were recorded biweekly until participants discharged. Training includes reaching activities, wrist rotation, gripping, and thumb movement to simulate real-life activities. A questionnaire regarding their experience with VR training was administered at the end. All participants had improvement in strength and functional tests. 9-hole peg test demonstrated clinically meaningful change in two of three participants. Manual muscle test changes were 2, 4.5 and 13.5 points individually. Participants with lower manual muscle test scores at baseline showed more potential to change compared to those who had high scores, which would possibly due to plateau effect. Pinch and grip strength demonstrated small changes which were not clinically important. Participants also rated VR technology of high reality level and great enjoyment in the questionnaire. This case series suggests that immersive VR with head mount display may be viable to provide safe and effective treatment for patients with SCI. VR training appears to be a possible adjunct to physical and occupational therapy as a method of muscle strengthening, improving upper extremity function and improving motivation during subacute rehabilitation