Unique Thermal Properties of Clothing Materials.

Cloth wearing seems so natural that everyone is self-deemed knowledgeable and has some expert opinions about it. However, to clearly explain the physics involved, and hence to make predictions for clothing design or selection, it turns out to be quite challenging even for experts. Cloth is a multiphased, porous, and anisotropic material system and usually in multilayers. The human body acts as an internal heat source in a clothing situation, thus forming a temperature gradient between body and ambient. But unlike ordinary engineering heat transfer problems, the sign of this gradient often changes as the ambient temperature varies. The human body also perspires and the sweat evaporates, an effective body cooling process via phase change. To bring all the variables into analysis quickly escalates into a formidable task. This work attempts to unravel the problem from a physics perspective, focusing on a few rarely noticed yet critically important mechanisms involved so as to offer a clearer and more accurate depiction of the principles in clothing thermal comfort

Association between worldwide dietary and lifestyle patterns with total cholesterol concentrations and DALYs for infectious and cardiovascular diseases: An ecological analysis

Global dietary and lifestyle trends are primary risk factors for communicable and non-communicable diseases. An ecological analysis was conducted to examine the association of global dietary and lifestyle patterns with total cholesterol concentrations. This study also investigated whether total cholesterol modified the association between dietary and lifestyle habits with disability-adjusted-life-years-lost (DALYs) for infectious and cardiovascular diseases (CVDs). Country-specific mean total cholesterol concentrations and DALYs for infectious and CVDs were obtained. Data were then matched to country-specific food and energy availability for consumption and information on obesity, physical inactivity, urbanization, gross domestic product (GDP), life expectancy and smoking. Stepwise multiple regression models were developed to identify significant predictors of total cholesterol concentrations and DALYs for infectious and CVDs. Life expectancy and egg and meat consumption were significantly associated with cholesterol concentrations. DALYs for infectious diseases were associated with smoking, life expectancy and per capita GDP. Smoking was the only predictor of DALYs for CVDs. The improvement of socio-demographic conditions and economic growth is likely to reduce the burden of communicable diseases in developing countries. A concurring increase in non-communicable diseases is expected, and these results have, yet again, identified smoking as a primary risk factor for CVDs

The collateral impact of COVID-19 emergency on neonatal intensive care units and family-centered care: Challenges and opportunities

The ongoing Coronavirus disease 2019 (COVID-19) pandemic is disrupting most specialized healthcare services worldwide, including those for high-risk newborns and their families. Due to the risk of contagion, critically ill infants, relatives and professionals attending neonatal intensive care units (NICUs) are undergoing a profound remodeling of the organization and quality care. In particular, mitigation strategies adopted to combact the COVID-19 pandemic may hinder the implementation of family-centered care within the NICU. This may put newborns at risk for several adverse effects, e.g., less weight gain, more nosocomial infections, increased length of NICU stay as well as long-term worse cognitive, emotional, and social development. This article aims to contribute to deepening the knowledge on the psychological impact of the COVID-19 on parents and NICU staff members based on empirical data from the literature. We also provided evidence-based indications on how to safely empower families and support NICU staffs facing such a threatening emergency, while preserving the crucial role of family-centered developmental care practices

Strengthening gamification studies: Current trends and future opportunities of gamification research

Gamification is now a well-established technique in Human-Computer Interaction. However, research on gamification still faces a variety of empirical and theoretical challenges. Firstly, studies of gamified systems typically focus narrowly on understanding individuals. short-term interactions with the system, ignoring more difficult to measure outcomes. Secondly, academic research on gamification has been slow to improve the techniques through which gamified applications are designed. Third, current gamification research lacks a critical lens capable of exploring unintended consequences of designs. The 14 articles published in this special issue face these challenges with great methodological rigor. We summarize them by identifying three main themes: the determination to improve the quality and usefulness of theory in the field of gamification, the improvements in design practice, and the adoption of a critical gaze to uncover side-effects of gamification designs. We conclude by providing an overview of the questions that we feel must be addressed by future work in gamification. Gamification studies would benefit from a wider use of theories to account for the complexity of human behavior, a more thorough exploration of the many opportunities coming from the world of games, and an ethical reflection on the use of game design elements in serious domains

The value of diastolic function parameters in the prediction of left atrial appendage thrombus in patients with nonvalvular atrial fibrillation

BACKGROUND: Left ventricular diastolic impairment and consequently elevated filling pressure may contribute to stasis leading to left atrial appendage thrombus (LAAT) in nonvalvular atrial fibrillation (AF). We investigated whether transthoracic echocardiographic parameters can predict LAAT independent of traditional clinical predictors. METHODS: We conducted a retrospective cohort study of 297 consecutive nonvalvular AF patients who underwent transthoracic echocardiogram followed by a transesophageal echocardiogram within one year. Multivariate logistic regression analysis models were used to determine factors independently associated with LAAT. RESULTS: Nineteen subjects (6.4%) were demonstrated to have LAAT by transesophageal echocardiography. These patients had higher mean CHADS(2) scores [2.6 ± 1.2 vs. 1.9 ± 1.3, P = 0.009], higher E:e’ ratios [16.6 ± 6.1 vs. 12.0 ± 5.4, P = 0.001], and lower mean e’ velocities [6.5 ± 2.1 cm/sec vs. 9.1 ± 3.2 cm/sec, P = 0.001]. Both E:e’ and e’ velocity were associated with LAAT formation independent of the CHADS(2) score, warfarin therapy, left ventricular ejection fraction (LVEF), and left atrial volume index (LAVI) [E:e’ odds-ratio = 1.14 (95% confidence interval = 1.03 – 1.3), P = 0.009; e’ velocity odds-ratio = 0.68 (95% confidence interval = 0.5 – 0.9), P = 0.007]. Similarly, diastolic function parameters were independently associated with spontaneous echo contrast. CONCLUSION: The diastolic function indices E:e’ and e’ velocity are independently associated with LAAT in nonvalvular AF patients and may help identify patients at risk for LAAT

UMAP 2018 HUM (Holistic User Modeling) Workshop Chairs’ Preface & Organization

It is our great pleasure to welcome you to the UMAP 2018 HUM (Holistic User Modeling) Workshop. According to a recent claim by IBM, 90% of the data available today have been created in the last two years. This exponential growth of online information has given new life to research in the area of user modeling and personalization, since information about users' preferences, sentiment and opinions, as well as signals describing their physical and psychological state, can now be obtained by mining data gathered from many heterogeneous sources. We can distinguish two important classes of such data sources. One of these comes from recent trends in Quantified Self (QS) and Personal Informatics, which has emphasized the use of technology to collect personal data on different aspects of people's daily lives. These data can be internal states (such as mood or glucose level) or indicators of performance (such as the kilometers run). The purpose of collecting these data is self-monitoring, performed to gain self-knowledge or to obtain some change or improvement (behavioral, psychological, therapeutic, etc.). Often these data are also exploited for behavior change purposes, for example to increase the user's physical activity. The other key category comes from the enormous amount of textual content that is continuously spread on social networks. This has driven a strong research effort to investigate to what extent such data can be exploited to infer user interests, personality traits, emotions, and knowledge. Moreover, the recent phenomenon of (Linked) Open Data fueled this research line by making available a huge amount of machine-readable textual data that can be used to connect all the data points spread in different data silos under a uniform representation formalism. The main goal of the workshop is to investigate whether techniques for advanced content representation and methodologies for gathering and modeling personal data (e.g. physiological, behavioral) can be exploited to build a new generation of personalized and intelligent systems in domains as diverse as health, learning, behavior change, e-government, smart cities (e.g., by combining mood data and music preferences data to provide recommendations on music to be listened)

Nonparametric Information Geometry

The differential-geometric structure of the set of positive densities on a given measure space has raised the interest of many mathematicians after the discovery by C.R. Rao of the geometric meaning of the Fisher information. Most of the research is focused on parametric statistical models. In series of papers by author and coworkers a particular version of the nonparametric case has been discussed. It consists of a minimalistic structure modeled according the theory of exponential families: given a reference density other densities are represented by the centered log likelihood which is an element of an Orlicz space. This mappings give a system of charts of a Banach manifold. It has been observed that, while the construction is natural, the practical applicability is limited by the technical difficulty to deal with such a class of Banach spaces. It has been suggested recently to replace the exponential function with other functions with similar behavior but polynomial growth at infinity in order to obtain more tractable Banach spaces, e.g. Hilbert spaces. We give first a review of our theory with special emphasis on the specific issues of the infinite dimensional setting. In a second part we discuss two specific topics, differential equations and the metric connection. The position of this line of research with respect to other approaches is briefly discussed.Comment: Submitted for publication in the Proceedings od GSI2013 Aug 28-30 2013 Pari