Complex regional pain syndrome in a competitive athlete and regional osteoporosis assessed by dual-energy X-ray absorptiometry: a case report.

Dual-energy X-ray absorptiometry is rarely utilized in the clinical care of patients with complex regional pain syndrome, but may be useful for the non-invasive determination of regional bone fragility and fracture risk, as well as muscular atrophy and regional body composition. This is the first report in the literature of complex regional pain syndrome and musculoskeletal co-morbidities in an athlete, and is the first to focus on dual-energy X-ray absorptiometry for the clinical assessment of complex regional pain syndrome

Brain Resilience: Shedding Light into the Black Box of Adventure Processes

Understanding of the active beneficial processes of adventure learning remains elusive. Resilience may provide one foundation for understanding the positive adaptation derived from Outdoor Adventure Education (OAE) and Adventure Therapy (AT) programming. From a neurological perspective, resilience may be explained by the brain’s innate capability to adapt its structure (growth of new cells) and function (re-wiring of existing cells) directly in response to environmental exposure. This paper explores the role of known brain responses to experiences analogous to adventure programming based on themes from a key literature review. The fundamental paradigm of ‘stress and recovery’ contends that a balance of neurobiological processes help realign psychosocial equilibrium in the short term and over time. Through progressive, repeated exposure to custom-built outdoor challenges, the concept of brain resilience may provide a scientific platform for understanding the mechanisms of achieving meaningful, authentic and healthy outcomes. It could also help to begin to illuminate a section of the black box of adventure processes

In vivo precision of the GE Lunar iDXA for the measurement of visceral adipose tissue in adults: the influence of body mass index.

CoreScan is a new software for the GE Lunar iDXA, which provides a quantification of visceral adipose tissue (VAT). The objective of this study was to determine the in vivo precision of CoreScan for the measurement of VAT mass in a heterogeneous group of adults. Forty-five adults (aged 34.6 (8.6) years), ranging widely in body mass index (BMI 26.0 (5.2)  kg/m(2); 16.7-42.4 kg/m(2)), received two consecutive total body scans with repositioning. The sample was divided into two subgroups based on BMI, normal-weight and overweight/obese, for precision analyses. Subgroup analyses revealed that precision errors (RMSSD:%CV; root mean square standard deviation:% coefficient of variation) for VAT mass were 20.9 g:17.0% in the normal-weight group and 43.7 g:5.4% in overweight/obese groups. Our findings indicate that precision for DXA-VAT mass measurements increases with BMI, but caution should be used with %CV-derived precision error in normal BMI subjects.European Journal of Clinical Nutrition advance online publication, 15 October 2014; doi:10.1038/ejcn.2014.213

Bone cross-sectional geometry in male runners, gymnasts, swimmers and non-athletic controls: a hip-structural analysis study.

Loading of the skeleton is important for the development of a functionally and mechanically appropriate bone structure, and can be achieved through impact exercise. Proximal femur cross-sectional geometry was assessed in the male athletes (n = 55) representing gymnastics, endurance running and swimming, and non-athletic controls (n = 22). Dual energy X-ray absorptiometry (iDXA, GE Healthcare, UK) measurements of the total body (for body composition) and the left proximal femur were obtained. Advanced hip structural analysis (AHA) was utilised to determine the areal bone mineral density (aBMD), hip axis length (HAL), cross-sectional area (CSA), cross-sectional moment of inertia (CSMI) and the femoral strength index (FSI). Gymnasts and runners had greater age, height and weight adjusted aBMD than in swimmers and controls (p < 0.05). Gymnasts and runners had greater resistance to axial loads (CSA) and the runners had increased resistance against bending forces (CSMI) compared to swimmers and controls (p < 0.01). Controls had a lower FSI compared to gymnasts and runners (1.4 vs. 1.8 and 2.1, respectively, p < 0.005). Lean mass correlated with aBMD, CSA and FSI (r = 0.365-0.457, p < 0.01), particularly in controls (r = 0.657-0.759, p < 0.005). Skeletal loading through the gymnastics and running appears to confer a superior bone geometrical advantage in the young adult men. The importance of lean body mass appears to be of particular significance for non-athletes. Further characterisation of the bone structural advantages associated with different sports would be of value to inform the strategies directed at maximising bone strength and thus, preventing fracture

Transparent Authentication Utilising Gait Recognition

Securing smartphones has increasingly become inevitable due to their massive popularity and significant storage and access to sensitive information. The gatekeeper of securing the device is authenticating the user. Amongst the many solutions proposed, gait recognition has been suggested to provide a reliable yet non-intrusive authentication approach – enabling both security and usability. While several studies exploring mobile-based gait recognition have taken place, studies have been mainly preliminary, with various methodological restrictions that have limited the number of participants, samples, and type of features; in addition, prior studies have depended on limited datasets, actual controlled experimental environments, and many activities. They suffered from the absence of real-world datasets, which lead to verify individuals incorrectly. This thesis has sought to overcome these weaknesses and provide, a comprehensive evaluation, including an analysis of smartphone-based motion sensors (accelerometer and gyroscope), understanding the variability of feature vectors during differing activities across a multi-day collection involving 60 participants. This framed into two experiments involving five types of activities: standard, fast, with a bag, downstairs, and upstairs walking. The first experiment explores the classification performance in order to understand whether a single classifier or multi-algorithmic approach would provide a better level of performance. The second experiment investigated the feature vector (comprising of a possible 304 unique features) to understand how its composition affects performance and for a comparison a more particular set of the minimal features are involved. The controlled dataset achieved performance exceeded the prior work using same and cross day methodologies (e.g., for the regular walk activity, the best results EER of 0.70% and EER of 6.30% for the same and cross day scenarios respectively). Moreover, multi-algorithmic approach achieved significant improvement over the single classifier approach and thus a more practical approach to managing the problem of feature vector variability. An Activity recognition model was applied to the real-life gait dataset containing a more significant number of gait samples employed from 44 users (7-10 days for each user). A human physical motion activity identification modelling was built to classify a given individual's activity signal into a predefined class belongs to. As such, the thesis implemented a novel real-world gait recognition system that recognises the subject utilising smartphone-based real-world dataset. It also investigates whether these authentication technologies can recognise the genuine user and rejecting an imposter. Real dataset experiment results are offered a promising level of security particularly when the majority voting techniques were applied. As well as, the proposed multi-algorithmic approach seems to be more reliable and tends to perform relatively well in practice on real live user data, an improved model employing multi-activity regarding the security and transparency of the system within a smartphone. Overall, results from the experimentation have shown an EER of 7.45% for a single classifier (All activities dataset). The multi-algorithmic approach achieved EERs of 5.31%, 6.43% and 5.87% for normal, fast and normal and fast walk respectively using both accelerometer and gyroscope-based features – showing a significant improvement over the single classifier approach. Ultimately, the evaluation of the smartphone-based, gait authentication system over a long period of time under realistic scenarios has revealed that it could provide a secured and appropriate activities identification and user authentication system

Disparities in Hospital Services Utilization Among Patients with Mental Health Issues: A Statewide Example Examining Insurance Status and Race Factors from 1999-2010

There exist many disconnects between the mental and general health care sectors. However, a goal of the Affordable Care Act (ACA) of 2010 is to change this by improving insurance access and the intersection of mental and general health care. As insurance status intersects with race, the present study examines how race, insurance status, and hospital mental health services utilization differ across groups within the state of New Jersey. The present study aims to determine trends in hospital mental health care utilization by insurance status and race from 1999 to 2010. The rate of self-pay for mental health disorders in the Black population was significantly higher than the rate for Whites and Asians during this period. However, though Asian mental health utilization increased the most over the 11-year period, the Asian population had the slowest growth in self-pay rates. ANOVA tests demonstrated significant differences in the rate of self-pay mental health cases between race groups (

Effect of Hand Positioning on DXA Total and Regional Bone and Body Composition Parameters, Precision Error, and Least Significant Change

Dual-energy X-ray absorptiometry (DXA) body composition measurements are performed in both clinical and research settings for estimations of total and regional fat mass, lean tissue mass, and bone mineral content. Subject positioning influences precision and positioning instructions vary between manufacturers. The aim of the study was to determine the effect of hand position and scan mode on regional and total body bone and body composition parameters and determine protocol-specific body composition precision errors. Thirty-eight healthy subjects (men; mean age: 27.1 ± 12.1 yr) received 4 consecutive total body GE-Lunar iDXA (enCORE v 15.0) scans with re-positioning, and scan mode was dependent on body size. Twenty-three subjects received scans in standard mode and 15 received scans in thick scan modes. Two scans per subject were conducted with subject hands prone and 2 with hands mid-prone. The precision error (root mean squared standard deviation; percentage coefficient of variation) and least significant change for each protocol were determined using the International Society for Clinical Densitometry calculator. Hands placed in the mid-prone position increased arm bone mineral density (BMD) (standard mode: 0.185 g*cm−2, thick mode: 0.265 g*cm−2; p < 0.05), total body BMD (standard mode: 0.051 g*cm−2, thick mode: 0.069 g*cm−2; p < 0.001), and total body BMD Z-score (standard mode: 0.5. thick mode: 0.7; p < 0.001). This was due to reductions in bone area and bone mineral content. In standard mode, hands mid-prone reduced fat mass (0.05 kg, p < 0.05) and increased lean mass (0.11 kg, p < 0.05). There were no differences in body composition for thick mode scans. Hands mid-prone reduced lean mass precision error at the arms, trunk, and total body (p < 0.01). DXA clinical and research centers are advised to maintain consistency in their hand positioning and scan mode protocols, and consideration should be given to the hand positioning used for reference data. As a best practice recommendation, published DXA-based studies and reports for clinic-based total body assessments should ensure that subject positioning is fully described

Regional Boundary Strategic Sensors Characterizations

This paper, deals with the linear infinite dimensional distributed parameter systems in a Hilbert space where the dynamics of system is governed by strongly continuous semi-groups. More precisely, for parabolic distributed systems the characterizations of regional&nbsp; boundary strategic sensors have been discussed and analyzed in different cases of regional&nbsp; boundary observability in infinite time interval. Furthermore, the results so obtained are applied in two-dimensional systems and sensors studied under which conditions guarantee regional boundary observability in a sub-region of the system domain boundary.&nbsp; Also, the authors show that, the existent of a sensor for the diffusion system is not strategic in the usual sense, but it may be regional&nbsp; boundary strategic of this system