The Relationship of Metabolic Syndrome Traits with Beta-Cell Function and Insulin Sensitivity by Oral Minimal Model Assessment in South Asian and European Families Residing in the Netherlands

Background. There are different metabolic syndrome traits among patients with different ethnicities. Methods. We investigated this by studying 44 South Asians and 54 Europeans and classified them in three groups according to the occurrence of metabolic syndrome (MetS) and Type 2 Diabetes (T2D). Insulin sensitivity index (ISI), static, dynamic, and total beta-cell responsivity indices (Φ), and disposition indices (DIs) were calculated with the use of oral minimal model (

Impact of unhealthy lifestyle on cardiorespiratory fitness and heart rate recovery of medical science students

Background: Medical science students represent valuable labour resources for better future medicine and medical technology. However, little attention was given to the health and well-being of these early career medical science professionals. The aim of this study is to investigate the impact of lifestyle components on cardiorespiratory fitness and heart rate recovery measured after moderate exercise in this population. Methods: Volunteers without documented medical condition were recruited randomly and continuously from the first-year medical science students during 2011-2014 at the University of Surrey, UK. Demographics and lifestyle components (the levels of smoking, alcohol intake, exercise, weekend outdoor activity and screen-time, daily sleep period, and self-assessment of fitness) were gathered through pre-exercise questionnaire. Cardiorespiratory fitness (VO2max) and heart rate recovery were determined using Åstrand–Rhyming submaximal cycle ergometry test. Data were analysed using SPSS version 25. Results: Among 614 volunteers, 124 had completed both lifestyle questionnaire and the fitness test and were included for this study. Within 124 participants (20.6±4 years), 46.8% were male and 53.2% were female, 11.3% were overweight and 8.9% were underweight, 8.9% were current smokers and 33.1% consumed alcohol beyond the UK recommendation. There were 34.7% of participants admitted to have <3 h/week of moderate physical activity assessed according to UK Government National Physical Activity Guidelines and physically not fit (feeling tiredness). Fitness test showed that VO2max distribution was inversely associated with heart rate recovery at 3 min and both values were significantly correlated with the levels of exercise, self-assessed fitness and BMI. Participants who had <3h/week exercise, or felt not fit or were overweight had significantly lower VO2max and heart rate recovery than their peers. Conclusion: One in three new medical science students were physically inactive along with compromised cardiorespiratory fitness and heart rate recovery, which put them at risk of cardiometabolic diseases. Promoting healthy lifestyle at the beginning of career is crucial in keeping medical science professionals healthy

Object Detection Through Exploration With A Foveated Visual Field

We present a foveated object detector (FOD) as a biologically-inspired alternative to the sliding window (SW) approach which is the dominant method of search in computer vision object detection. Similar to the human visual system, the FOD has higher resolution at the fovea and lower resolution at the visual periphery. Consequently, more computational resources are allocated at the fovea and relatively fewer at the periphery. The FOD processes the entire scene, uses retino-specific object detection classifiers to guide eye movements, aligns its fovea with regions of interest in the input image and integrates observations across multiple fixations. Our approach combines modern object detectors from computer vision with a recent model of peripheral pooling regions found at the V1 layer of the human visual system. We assessed various eye movement strategies on the PASCAL VOC 2007 dataset and show that the FOD performs on par with the SW detector while bringing significant computational cost savings.Comment: An extended version of this manuscript was published in PLOS Computational Biology (October 2017) at https://doi.org/10.1371/journal.pcbi.100574

Can disordered mobile phone use be considered a behavioral addiction? An update on current evidence and a comprehensive model for future research

Despite the many positive outcomes, excessive mobile phone use is now often associated with potentially harmful and/or disturbing behaviors (e.g., symptoms of deregulated use, negative impact on various aspects of daily life such as relationship problems, and work intrusion). Problematic mobile phone use (PMPU) has generally been considered as a behavioral addiction that shares many features with more established drug addictions. In light of the most recent data, the current paper reviews the validity of the behavioral addiction model when applied to PMPU. On the whole, it is argued that the evidence supporting PMPU as an addictive behavior is scarce. In particular, it lacks studies that definitively show behavioral and neurobiological similarities between mobile phone addiction and other types of legitimate addictive behaviors. Given this context, an integrative pathway model is proposed that aims to provide a theoretical framework to guide future research in the field of PMPU. This model highlights that PMPU is a heterogeneous and multi-faceted condition

I-Support: A robotic platform of an assistive bathing robot for the elderly population

In this paper we present a prototype integrated robotic system, the I-Support bathing robot, that aims at supporting new aspects of assisted daily-living activities on a real-life scenario. The paper focuses on describing and evaluating key novel technological features of the system, with the emphasis on cognitive human–robot interaction modules and their evaluation through a series of clinical validation studies. The I-Support project on its whole has envisioned the development of an innovative, modular, ICT-supported service robotic system that assists frail seniors to safely and independently complete an entire sequence of physically and cognitively demanding bathing tasks, such as properly washing their back and their lower limbs. A variety of innovative technologies have been researched and a set of advanced modules of sensing, cognition, actuation and control have been developed and seamlessly integrated to enable the system to adapt to the target population abilities. These technologies include: human activity monitoring and recognition, adaptation of a motorized chair for safe transfer of the elderly in and out the bathing cabin, a context awareness system that provides full environmental awareness, as well as a prototype soft robotic arm and a set of user-adaptive robot motion planning and control algorithms. This paper focuses in particular on the multimodal action recognition system, developed to monitor, analyze and predict user actions with a high level of accuracy and detail in real-time, which are then interpreted as robotic tasks. In the same framework, the analysis of human actions that have become available through the project’s multimodal audio–gestural dataset, has led to the successful modeling of Human–Robot Communication, achieving an effective and natural interaction between users and the assistive robotic platform. In order to evaluate the I-Support system, two multinational validation studies were conducted under realistic operating conditions in two clinical pilot sites. Some of the findings of these studies are presented and analyzed in the paper, showing good results in terms of: (i) high acceptability regarding the system usability by this particularly challenging target group, the elderly end-users, and (ii) overall task effectiveness of the system in different operating modes