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The stratorotational instability of Taylor-Couette flows with moderate Reynolds numbers
In view of new experimental data the instability against adiabatic nonaxisymmetric perturbations of a Taylor-Couette flow with an axial density stratification is considered in dependence of the Reynolds number (Re) of rotation and the Brunt-Väisälä number (Rn) of the stratification. The flows at and beyond the Rayleigh limit become unstable between a lower and an upper Reynolds number (for fixed Rn). The rotation can thus be too slow or too fast for the stratorotational instability. The upper Reynolds number above which the instability decays, has its maximum value for the potential flow (driven by cylinders rotating according to the Rayleigh limit) and decreases strongly for flatter rotation profiles finally leaving only isolated islands of instability in the (Rn/Re) map. The maximal possible rotation ratio μmax only slightly exceeds the shear value of the quasi-uniform flow with Uφ≃const. Along and between the lines of neutral stability the wave numbers of the instability patterns for all rotation laws beyond the Rayleigh limit are mainly determined by the Froude number Fr which is defined by the ratio between Re and Rn. The cells are highly prolate for Fr > 1 so that measurements for too high Reynolds numbers become difficult for axially bounded containers. The instability patterns migrate azimuthally slightly faster than the outer cylinder rotates
An empirical evaluation of prediction by partial matching in assembly assistance systems
Industrial assistive systems result from a multidisciplinary effort that integrates IoT (and Industrial IoT), Cognetics, and Artificial Intelligence. This paper evaluates the Prediction by Partial Matching algorithm as a component of an assembly assistance system that supports factory workers, by providing choices for the next manufacturing step. The evaluation of the proposed method was performed on datasets collected within an experiment involving trainees and experienced workers. The goal is to find out which method best suits the datasets in order to be integrated afterwards into our context-aware assistance system. The obtained results show that the Prediction by Partial Matching method presents a significant improvement with respect to the existing Markov predictors
A Population-Based Survey
Background: Chronic conditions are an increasing challenge for individuals and
the health care system. Smartphones and health apps are potentially promising
tools to change health-related behaviors and manage chronic conditions.
Objective: The aim of this study was to explore (1) the extent of smartphone
and health app use, (2) sociodemographic, medical, and behavioral correlates
of smartphone and health app use, and (3) associations of the use of apps and
app characteristics with actual health behaviors. Methods: A population-based
survey (N=4144) among Germans, aged 35 years and older, was conducted.
Sociodemographics, presence of chronic conditions, health behaviors, quality
of life, and health literacy, as well as the use of the Internet, smartphone,
and health apps were assessed by questionnaire at home visit. Binary logistic
regression models were applied. Results: It was found that 61.25% (2538/4144)
of participants used a smartphone. Compared with nonusers, smartphone users
were younger, did more research on the Internet, were more likely to work
full-time and more likely to have a university degree, engaged more in
physical activity, and less in low fat diet, and had a higher health-related
quality of life and health literacy. Among smartphone users, 20.53% (521/2538)
used health apps. App users were younger, less likely to be native German
speakers, did more research on the Internet, were more likely to report
chronic conditions, engaged more in physical activity, and low fat diet, and
were more health literate compared with nonusers who had a smartphone. Health
apps focused on smoking cessation (232/521, 44.5%), healthy diet (201/521,
38.6%), and weight loss (121/521, 23.2%). The most common app characteristics
were planning (264/521, 50.7%), reminding (188/521, 36.1%), prompting
motivation (179/521 34.4%), and the provision of information (175/521, 33.6%).
Significant associations were found between planning and the health behavior
physical activity, between feedback or monitoring and physical activity, and
between feedback or monitoring and adherence to doctor’s advice. Conclusions:
Although there were many smartphone and health app users, a substantial
proportion of the population was not engaged. Findings suggest age-related,
socioeconomic-related, literacy-related, and health-related disparities in the
use of mobile technologies. Health app use may reflect a user’s motivation to
change or maintain health behaviors. App developers and researchers should
take account of the needs of older people, people with low health literacy,
and chronic conditions
Using Smartphones and Health Apps to Change and Manage Health Behaviors: A Population-Based Survey
Background: Chronic conditions are an increasing challenge for individuals and the health care system. Smartphones and health apps are potentially promising tools to change health-related behaviors and manage chronic conditions. Objective: The aim of this study was to explore (1) the extent of smartphone and health app use, (2) sociodemographic, medical, and behavioral correlates of smartphone and health app use, and (3) associations of the use of apps and app characteristics with actual health behaviors. Methods: A population-based survey (N=4144) among Germans, aged 35 years and older, was conducted. Sociodemographics, presence of chronic conditions, health behaviors, quality of life, and health literacy, as well as the use of the Internet, smartphone, and health apps were assessed by questionnaire at home visit. Binary logistic regression models were applied. Results: It was found that 61.25% (2538/4144) of participants used a smartphone. Compared with nonusers, smartphone users were younger, did more research on the Internet, were more likely to work full-time and more likely to have a university degree, engaged more in physical activity, and less in low fat diet, and had a higher health-related quality of life and health literacy. Among smartphone users, 20.53% (521/2538) used health apps. App users were younger, less likely to be native German speakers, did more research on the Internet, were more likely to report chronic conditions, engaged more in physical activity, and low fat diet, and were more health literate compared with nonusers who had a smartphone. Health apps focused on smoking cessation (232/521, 44.5%), healthy diet (201/521, 38.6%), and weight loss (121/521, 23.2%). The most common app characteristics were planning (264/521, 50.7%), reminding (188/521, 36.1%), prompting motivation (179/521 34.4%), and the provision of information (175/521, 33.6%). Significant associations were found between planning and the health behavior physical activity, between feedback or monitoring and physical activity, and between feedback or monitoring and adherence to doctor’s advice. Conclusions: Although there were many smartphone and health app users, a substantial proportion of the population was not engaged. Findings suggest age-related, socioeconomic-related, literacy-related, and health-related disparities in the use of mobile technologies. Health app use may reflect a user’s motivation to change or maintain health behaviors. App developers and researchers should take account of the needs of older people, people with low health literacy, and chronic conditions
Associations of Health App Use and Perceived Effectiveness in People With Cardiovascular Diseases and Diabetes: Population-Based Survey
Background: Mobile health apps can help to change health-related behaviors and manage chronic conditions in patients with cardiovascular diseases (CVDs) and diabetes mellitus, but a certain level of health literacy and electronic health (eHealth) literacy may be needed. Objective: The aim of this study was to identify factors associated with mobile health app use in individuals with CVD or diabetes and detect relations with the perceived effectiveness of health apps among app users. Methods: The study used population-based Web-based survey (N=1500) among Germans, aged 35 years and older, with CVD, diabetes, or both. A total of 3 subgroups were examined: (1) Individuals with CVD (n=1325), (2) Individuals with diabetes (n=681), and (3) Individuals with CVD and diabetes (n=524). Sociodemographics, health behaviors, CVD, diabetes, health and eHealth literacy, characteristics of health app use, and characteristics of apps themselves were assessed by questionnaires. Linear and logistic regression models were applied. Results: Overall, patterns of factors associated with health app use were comparable in individuals with CVD or diabetes or both. Across subgroups, about every fourth patient reported using apps for health-related purposes, with physical activity and weight loss being the most prominent target behaviors. Health app users were younger, more likely to be female (except in those with CVD and diabetes combined), better educated, and reported more physical activity. App users had higher eHealth literacy than nonusers. Those users who perceived the app to have a greater effectiveness on their health behaviors tended to be more health and eHealth literate and rated the app to use more behavior change techniques (BCTs). Conclusions: There are health- and literacy-related disparities in the access to health app use among patients with CVD, diabetes, or both, which are relevant to specific health care professionals such as endocrinologists, dieticians, cardiologists, or general practitioners. Apps containing more BCTs had a higher perceived effect on people’s health, and app developers should take the complexity of needs into account. Furthermore, eHealth literacy appears to be a requirement to use health apps successfully, which should be considered in health education strategies to improve health in patients with CVD and diabetes
Differences Between US and UK Adults in Stroke Preparedness: Evidence From Parallel Population-Based Community Surveys
Background and Purpose—Although time-dependent treatment is available, most people delay contacting emergency medical services for stroke. Given differences in the healthcare system and public health campaigns, exploring between-country differences in stroke preparedness may identify novel ways to increase acute stroke treatment. Methods—A survey was mailed to population-based samples in Ingham County, Michigan, US (n=2500), and Newcastle upon Tyne, UK (n=2500). Surveys included stroke perceptions and stroke/nonstroke scenarios to assess recognition and response to stroke. Between-country differences and associations with stroke preparedness were examined usingttests and linear mixed models. Results—Overall response rate was 27.4%. The mean age of participants was 55 years, and 58% were female. US participants were better in recognizing stroke (70% versus 63%, d=0.27) and were more likely to call emergency medical services (55% versus 52%, d=0.11). After controlling for demographics and comorbidities, US participants remained more likely to recognize stroke but were not more likely to respond appropriately. A greater belief that medical treatment can help with stroke and understanding of stroke was associated with improved stroke recognition and response. Conclusions—Overall, stroke recognition and response were moderate. US participants were modestly better at recognising stroke, although there was little difference in response to stroke. Future stroke awareness interventions could focus more on stroke outcome expectations and developing a greater understanding of stroke among the public
The stroke ‘Act FAST’ campaign: Remembered but not understood?
Background: The stroke awareness raising campaign ‘Act FAST' (Face, Arms, Speech: Time to call Emergency Medical Services) has been rolled out in multiple waves in England, but impact on stroke recognition and response remains unclear. Purpose: The purpose of this study was to test whether providing knowledge of the FAST acronym through a standard Act FAST campaign leaflet increases accurate recognition and response in stroke-based scenario measures. Methods: This is a population-based, cross-sectional survey of adults in Newcastle upon Tyne, UK, sampled using the electoral register, with individuals randomized to receive a questionnaire and Act FAST leaflet (n = 2500) or a questionnaire only (n = 2500) in 2012. Campaign message retention, stroke recognition, and response measured through 16 scenario-based vignettes were assessed. Data were analyzed in 2013. Results: Questionnaire return rate was 32·3% (n = 1615). No differences were found between the leaflet and no-leaflet groups in return rate or demographics. Participants who received a leaflet showed better campaign recall (75·7% vs. 68·2%, P = 0·003) and recalled more FAST mnemonic elements (66·1% vs. 45·3% elements named correctly, P < 0·001). However, there were no between-group differences for stroke recognition and response to stroke-based scenarios (P > 0·05). Conclusions: Despite greater levels of recall of specific ‘Act FAST' elements among those receiving the Act FAST leaflet, there was no impact on stroke recognition and response measures
development and optimisation of a face-to-face behavioural intervention component
After weight loss, most individuals regain lost weight. Interventions to
support the transition from successful loss to weight loss maintenance (WLM),
regardless of the method of prior weight loss, are needed. The aims of this
study were to (1) develop a face-to-face behavioural intervention session to
support overweight and obese individuals who have recently lost a clinically
significant amount of weight in the transition to WLM; (2) to assess the
single-session intervention for acceptability and feasibility prior to its use
in a larger, 12-month, multi-component trial; and (3) to optimise the
intervention session for future use based on participant feedback.
Participants with a Body Mass Index of ≥25 kg/m2 prior to a ≥5% weight loss in
the previous 12 months were recruited via the local government authority and
community-based advertisements. Each attended the one-hour session with a
trained facilitator, which focused on setting maintenance-relevant weight,
eating, and physical activity goals. Semi-structured interviews were carried
out immediately post-session to obtain feedback on the acceptability of this
intervention component. Data were used to generate recommendations for changes
to the session, which were discussed by the team, and used to optimise the
session. Seventeen participants (13 female; median WL = 13%) were recruited.
All participants evaluated the intervention session positively; 11
participants suggested improvements including reducing information provision
in favour of greater focus on identifying and coping with barriers, and the
inclusion of practical examples. The systematic refinement and optimisation
process resulted in an acceptable and feasible face-to-face behavioural
intervention session (described here), which will be tested as part of a
multi-component intervention. We anticipate the session could be used to
supplement existing support including online services, and has the potential
to benefit people who have lost a clinically significant amount of weight to
achieve WLM over the long term
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