Multiple Density Maps Information Fusion for Effectively Assessing Intensity Pattern of Lifelogging Physical Activity

Physical activity (PA) measurement is a crucial task in healthcare technology aimed at monitoring the progression and treatment of many chronic diseases. Traditional lifelogging PA measures require relatively high cost and can only be conducted in controlled or semi-controlled environments, though they exhibit remarkable precision of PA monitoring outcomes. Recent advancement of commercial wearable devices and smartphones for recording one’s lifelogging PA has popularized data capture in uncontrolled environments. However, due to diverse life patterns and heterogeneity of connected devices as well as the PA recognition accuracy, lifelogging PA data measured by wearable devices and mobile phones contains much uncertainty thereby limiting their adoption for healthcare studies. To improve the feasibility of PA tracking datasets from commercial wearable/mobile devices, this paper proposes a lifelogging PA intensity pattern decision making approach for lifelong PA measures. The method is to firstly remove some irregular uncertainties (IU) via an Ellipse fitting model, and then construct a series of monthly based hour-day density map images for representing PA intensity patterns with regular uncertainties (RU) on each month. Finally it explores Dempster-Shafer theory of evidence fusing information from these density map images for generating a decision making model of a final personal lifelogging PA intensity pattern. The approach has significantly reduced the uncertainties and incompleteness of datasets from third party devices. Two case studies on a mobile personalized healthcare platform MHA [1] connecting the mobile app Moves are carried out. The results indicate that the proposed approach can improve effectiveness of PA tracking devices or apps for various types of people who frequently use them as a healthcare indicator

Development of A “PharmaComm” Serious Game for Teaching Pharmacist Communication and Drug Administration in a Virtual Hospital Setting

Practical experience is crucial in pharmacy education, but it can be difficult to provide pharmacy students with a sufficient level of experience during their education due to a number of challenges. Video games might provide a platform where students can gain positive learning experience in a virtual environment. Serious games have been used successfully across many industries, which suggest that a well-designed serious game can have positive learning outcomes. Increased engagement and motivation are mentioned by experts as some of the main benefits of serious games. Being able to practise skills before utilising them in real-world scenarios is another advantage identified. In this paper, we present a virtual patient simulator which is designed specifically teaching pharmacy students patient communication and administration of drugs. A pilot study and an expert review were carried out to evaluate the effectiveness of the application and its findings are presented

Using Serious Games to Create Awareness on Visual Impairments

Visual impairments define a wide spectrum of disabilities that vary in severity, from the need to wear glasses, to permanent loss of vision or blindness. This paper discusses the process undertaken in creating two simulators, one which emulates partially-sighted visual impairment and another focused on full -blindness. In order to create the simulators, extensive research was conducted surrounding the effects of partially-sightedness and blindness, highlighting existing software and games that promote awareness for visual impairments. This paper underlines the necessity of raising awareness for visual impairments and the effectiveness of applying serious games for this very goal. After developing the simulators, experiments were conducted to evaluate the effectiveness of it. Findings from the experiments were analysed and documented

Uncertainty Investigation for Personalised Lifelogging Physical Activity Intensity Pattern Assessment with Mobile Devices

Lifelogging physical activity (PA) assessment is crucial to healthcare technologies and studies for the purpose of treatments and interventions of chronic diseases. Traditional lifelogging PA monitoring is conducted in non-naturalistic settings by means of wearable devices or mobile phones such as fixed placements, controlled durations or dedicated sensors. Although they achieved satisfactory outcomes for healthcare studies, the practicability become the key issues. Recent advance of mobile devices make lifelogging PA tracking for healthy or unhealthy individuals possible. However, owning to diverse physical characteristics, immaturity of PA recognition techniques, different settings from manufactories and a majority of uncertainties in real life, the results of PA measurement is leading to be inapplicable for PA pattern detection in a long range, especially hardly exploited in the wellbeing monitoring or behaviour changes. This paper investigates and compares uncertainties of existing mobile devices for individual’s PA tracking. Irregular uncertainties (IU) are firstly removed by exploiting Ellipse fitting model, and then monthly density maps that contain regular uncertainties (RU) are constructed based on metabolic equivalents (METs) of different activity types. Five months of four subjects PA intensity changes using the mobile app tracker Moves [1] and Google Fit app on wearable device Samsung wear S2 are carried out from a mobile personalised healthcare platform MHA [2]. The result indicates that uncertainty of PA intensity monitored by mobile phone is 90% lower than wearable device, where the datasets tend to be further explored by healthcare/fitness studies. Whilst PA activity monitoring by mobile phone is still a challenging issue by far due to much more uncertainties than wearable devices

A 3D Security Modelling Platform for Social IoT Environments

Social IoT environment comprises not just smart devices, but also the humans to interact with these IoT devices. The benefits of such system are overshadowed by the issues of cyber security. A new approach is required for us to understand the security implication under such dynamic environment, while taking both the social and technical aspects into consideration. This paper proposed a 3D security modelling platform that can capture and model security requirements in Social IoT environment. The modelling process is graphical notation based, working as a security extension to Business Process Model and Notation. Still, it utilises the latest 3D game technology thus the security extensions are generated through the third dimension. In this way, the introduction of security extensions will not increase the complexity of the original SIoT scenario, while keeping all the key information in the same platform. Together with the security ontology we have proposed, these comprehensive security notations created a unique platform that aiming at addressing the ever complicated security issues in SIoT envorinment

N-Nervonoylsphingomyelin (C24:1) prevents lateral heterogeneity in cholesterol-containing membranes

This study was conducted to explore how the nature of the acyl chains of sphingomyelin (SM) influence its lateral distribution in the ternary lipid mixture SM/cholesterol/1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC), focusing on the importance of the hydrophobic part of the SM molecule for domain formation. Atomic force microscopy (AFM) measurements showed that the presence of a double bond in the 24:1 SM molecule in mixtures with cholesterol (CHO) or in pure bilayers led to a decrease in the molecular packing. Confocal microscopy and AFM showed, at the meso- and nanoscales respectively, that unlike 16:0 and 24:0 SM, 24:1 SM does not induce phase segregation in ternary lipid mixtures with DOPC and CHO. This ternary lipid mixture had a nanomechanical stability intermediate between those displayed by liquid-ordered (Lo) and liquid-disordered (Ld) phases, as reported by AFM force spectroscopy measurements, demonstrating that 24:1 SM is able to accommodate both DOPC and CHO, forming a single phase. Confocal experiments on giant unilamellar vesicles made of human, sheep, and rabbit erythrocyte ghosts rich in 24:1 SM and CHO, showed no lateral domain segregation. This study provides insights into how the specific molecular structure of SM affects the lateral behavior and the physical properties of both model and natural membranes. Specifically, the data suggest that unsaturated SM may help to keep membrane lipids in a homogeneous mixture rather than in separate domains.Instituto de Investigaciones Bioquímicas de La PlataFacultad de Ciencias Exacta

Flodoard of Rheims and the Historiography of the Tenth-Century West

Flodoard of Rheims is one of the most important authors of tenth-century Europe, and the only contemporary historian to document the momentous struggles between kings and nobles in Francia in the wake of the demise of the Carolingian Empire. Flodoard’s era stands at the center of major historiographical debates concerning the nature of political and social change and the origins of European institutions. Yet, despite his singularity, his substantial histories have received little attention from scholars examining the profound transformations of the period. Exploring this discrepancy, this article offers an overview of Flodoard’s career and reviews how his histories have been invoked in some of the great scholarly debates about tenth-century Europe. It further proposes to recontextualize Flodoard and to reread his histories from the bottom up in order to gain a subtler understanding of how one contemporary perceived and represented the dramatic events and changes taking place around him

Long-term monitoring of wildlife populations for protected area management in Southeast Asia

Long-term monitoring of biodiversity in protected areas (PAs) is critical to assess threats, link conservation action to species outcomes, and facilitate improved management. Yet, rigorous longitudinal monitoring within PAs is rare. In Southeast Asia (SEA), there is a paucity of long-term wildlife monitoring within PAs, and many threatened species lack population estimates from anywhere in their range, making global assessments difficult. Here, we present new abundance estimates and population trends for 11 species between 2010 and 2020, and spatial distributions for 7 species, based on long-term line transect distance sampling surveys in Keo Seima Wildlife Sanctuary in Cambodia. These represent the first robust population estimates for four threatened species from anywhere in their range and are among the first long-term wildlife population trend analyses from the entire SEA region. Our study revealed that arboreal primates and green peafowl (Pavo muticus) generally had either stable or increasing population trends, whereas ungulates and semiarboreal primates generally had declining trends. These results suggest that ground-based threats, such as snares and domestic dogs, are having serious negative effects on terrestrial species. These findings have important conservation implications for PAs across SEA that face similar threats yet lack reliable monitoring data