Does playing different game genres affect obesity levels in gamers?

This paper examines the relationship between playing various gaming genres and its effect on obesity. While previous studies have generally associated gaming with obesity, some have highlighted that certain game genres, exergames, require gamers to be physically active to play the game, leading to a reduction in gamers’ weight. To study this relationship, we conducted a survey and analyzed the collected data using ANOVA and Regression Analysis. Our preliminary findings from one-way ANOVA and two-way ANOVA with interaction, indicates significant association between game genre and engagement per session with BMI. The interaction between them suggests that the effect of game genre on BMI is dependent on the engagement per session, as the p-value of 6.54e-10 is less than the 5% significance level. Our regression results suggest that some game genres, such as Action and Multiplayer Online Battle Arena (MOBA), had a significant impact on obesity. However, first-person, puzzle/casual and simulation/sports games were not significantly associated with BMI. Our regression models also found that higher engagement in gaming per week and session correlates with a higher BMI. Our findings may offer game developers to collaborate with field experts, leading to evidence-based interventions that mitigate obesity risks and promote healthier gaming practices across game genres

Analytic approximations, perturbation methods, and their applications

The paper summarizes the parallel session B3 {\em Analytic approximations, perturbation methods, and their applications} of the GR18 conference. The talks in the session reported notably recent advances in black hole perturbations and post-Newtonian approximations as applied to sources of gravitational waves.Comment: Summary of the B3 parallel session of the GR18 conferenc

Analytic approximations, perturbation theory, effective field theory methods and their applications

We summarize the parallel session B4: 'Analytic approximations, perturbation theory effective field theory methods and their applications' and the joint session B2/B4: 'Approximate solutions to Einstein equations: Methods and Applications', of the GR20 & Amaldi10 conference in Warsaw, July 2013. The contributed talks reported significant advances on various areas of research in gravity.Comment: 15 pages. Contribution to the Proceedings of GR20 - Amaldi1

Digital dissection of the model organism Xenopus laevis using contrast-enhanced computed tomography

The African clawed frog, Xenopus laevis, is one of the most widely used model organisms in biological research. However, the most recent anatomical description of X. laevis was produced nearly a century ago. Compared with other anurans, pipid frogs – including X. laevis – exhibit numerous unusual morphological features; thus, anatomical descriptions of more ‘typical’ frogs do not detail many aspects of X. laevis skeletal and soft‐tissue morphology. The relatively new method of using iodine‐based agents to stain soft tissues prior to high‐resolution X‐ray imaging has several advantages over gross dissection, such as enabling dissection of very small and fragile specimens, and preserving the three‐dimensional topology of anatomical structures. Here, we use contrast‐enhanced computed tomography to produce a high‐resolution three‐dimensional digital dissection of a post‐metamorphic X. laevis to successfully visualize: skeletal and muscular anatomy; the nervous, respiratory, digestive, excretory and reproductive systems; and the major sense organs. Our digital dissection updates and supplements previous anatomical descriptions of this key model organism, and we present the three‐dimensional data as interactive portable document format (PDF) files that are easily accessible and freely available for research and educational purposes. The data presented here hold enormous potential for applications beyond descriptive purposes, particularly for biological researchers using this taxon as a model organism, comparative anatomy and biomechanical modelling

Session-based Recommendation with Graph Neural Networks

The problem of session-based recommendation aims to predict user actions based on anonymous sessions. Previous methods model a session as a sequence and estimate user representations besides item representations to make recommendations. Though achieved promising results, they are insufficient to obtain accurate user vectors in sessions and neglect complex transitions of items. To obtain accurate item embedding and take complex transitions of items into account, we propose a novel method, i.e. Session-based Recommendation with Graph Neural Networks, SR-GNN for brevity. In the proposed method, session sequences are modeled as graph-structured data. Based on the session graph, GNN can capture complex transitions of items, which are difficult to be revealed by previous conventional sequential methods. Each session is then represented as the composition of the global preference and the current interest of that session using an attention network. Extensive experiments conducted on two real datasets show that SR-GNN evidently outperforms the state-of-the-art session-based recommendation methods consistently.Comment: 9 pages, 4 figures, accepted by AAAI Conference on Artificial Intelligence (AAAI-19

Modular session types for objects

Session types allow communication protocols to be specified type-theoretically so that protocol implementations can be verified by static type checking. We extend previous work on session types for distributed object-oriented languages in three ways. (1) We attach a session type to a class definition, to specify the possible sequences of method calls. (2) We allow a session type (protocol) implementation to be modularized, i.e. partitioned into separately-callable methods. (3) We treat session-typed communication channels as objects, integrating their session types with the session types of classes. The result is an elegant unification of communication channels and their session types, distributed object-oriented programming, and a form of typestate supporting non-uniform objects, i.e. objects that dynamically change the set of available methods. We define syntax, operational se-mantics, a sound type system, and a sound and complete type checking algorithm for a small distributed class-based object-oriented language with structural subtyping. Static typing guarantees that both sequences of messages on channels, and sequences of method calls on objects, conform to type-theoretic specifications, thus ensuring type-safety. The language includes expected features of session types, such as delegation, and expected features of object-oriented programming, such as encapsulation of local state.Comment: Logical Methods in Computer Science (LMCS), International Federation for Computational Logic, 201

Bridging deep and kernel methods

There has been some exciting major progress in recent years in data analysis methods, including a variety of deep learning architectures, as well as further advances in kernel-based learning methods, which have demonstrated predictive superiority. In this paper we provide a brief motivated survey of recent proposals to explicitly or implicitly combine kernel methods with the notion of deep learning networks.Peer ReviewedPostprint (author's final draft

Lexical Query Modeling in Session Search

Lexical query modeling has been the leading paradigm for session search. In this paper, we analyze TREC session query logs and compare the performance of different lexical matching approaches for session search. Naive methods based on term frequency weighing perform on par with specialized session models. In addition, we investigate the viability of lexical query models in the setting of session search. We give important insights into the potential and limitations of lexical query modeling for session search and propose future directions for the field of session search.Comment: ICTIR2016, Proceedings of the 2nd ACM International Conference on the Theory of Information Retrieval. 201