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Background
Wearables, as small portable computer systems worn on the body, can track user fitness and health data, which can be used to customize health insurance contributions individually. In particular, insured individuals with a healthy lifestyle can receive a reduction of their contributions to be paid. However, this potential is hardly used in practice.
Objective
This study aims to identify which barrier factors impede the usage of wearables for assessing individual risk scores for health insurances, despite its technological feasibility, and to rank these barriers according to their relevance.
Methods
To reach these goals, we conduct a ranking-type Delphi study with the following three stages. First, we collected possible barrier factors from a panel of 16 experts and consolidated them to a list of 11 barrier categories. Second, the panel was asked to rank them regarding their relevance. Third, to enhance the panel consensus, the ranking was revealed to the experts, who were then asked to re-rank the barriers.
Results
The results suggest that regulation is the most important barrier. Other relevant barriers are false or inaccurate measurements and application errors caused by the users. Additionally, insurers could lack the required technological competence to use the wearable data appropriately.
Conclusion
A wider use of wearables and health apps could be achieved through regulatory modifications, especially regarding privacy issues. Even after assuring stricter regulations, users’ privacy concerns could partly remain, if the data exchange between wearables manufacturers, health app providers, and health insurers does not become more transparent.
We present the results of Monte Carlo mass-loss predictions for massive stars covering a wide range of stellar parameters. We critically test our predictions against a range of observed massloss rates – in light of the recent discussions on wind clumping. We also present a model to compute the clumping-induced polarimetric variability of hot stars and we compare this with observations of Luminous Blue Variables, for which polarimetric variability is larger than for O and Wolf-Rayet stars. Luminous Blue Variables comprise an ideal testbed for studies of wind clumping and wind geometry, as well as for wind strength calculations, and we propose they may be direct supernova progenitors.
Children’s physical fitness development and related moderating effects of age and sex are well documented, especially boys’ and girls’ divergence during puberty. The situation might be different during prepuberty. As girls mature approximately two years earlier than boys, we tested a possible convergence of performance with five tests representing four components of physical fitness in a large sample of 108,295 eight-year old third-graders. Within this single prepubertal year of life and irrespective of the test, performance increased linearly with chronological age, and boys outperformed girls to a larger extent in tests requiring muscle mass for successful performance. Tests differed in the magnitude of age effects (gains), but there was no evidence for an interaction between age and sex. Moreover, “physical fitness” of schools correlated at r = 0.48 with their age effect which might imply that "fit schools” promote larger gains; expected secular trends from 2011 to 2019 were replicated.
The optical density of human macular pigment was measured for 50 observers ranging in age from 10 to 90 years. The psychophysical method required adjusting the radiance of a 1°, monochromatic light (400–550 nm) to minimize flicker (15 Hz) when presented in counterphase with a 460 nm standard. This test stimulus was presented superimposed on a broad-band, short-wave background. Macular pigment density was determined by comparing sensitivity under these conditions for the fovea, where macular pigment is maximal, and 5° temporally. This difference spectrum, measured for 12 observers, matched Wyszecki and Stiles's standard density spectrum for macular pigment. To study variation in macular pigment density for a larger group of observers, measurements were made at only selected spectral points (460, 500 and 550 nm). The mean optical density at 460 nm for the complete sample of 50 subjects was 0.39. Substantial individual differences in density were found (ca. 0.10–0.80), but this variation was not systematically related to age.
Wild bee species are important pollinators in agricultural landscapes. However, population decline was reported over the last decades and is still ongoing. While agricultural intensification is a major driver of the rapid loss of pollinating species, transition zones between arable fields and forest or grassland patches, i.e., agricultural buffer zones, are frequently mentioned as suitable mitigation measures to support wild bee populations and other pollinator species. Despite the reported general positive effect, it remains unclear which amount of buffer zones is needed to ensure a sustainable and permanent impact for enhancing bee diversity and abundance. To address this question at a pollinator community level, we implemented a process-based, spatially explicit simulation model of functional bee diversity dynamics in an agricultural landscape. More specifically, we introduced a variable amount of agricultural buffer zones (ABZs) at the transition of arable to grassland, or arable to forest patches to analyze the impact on bee functional diversity and functional richness. We focused our study on solitary bees in a typical agricultural area in the Northeast of Germany. Our results showed positive effects with at least 25% of virtually implemented agricultural buffer zones. However, higher amounts of ABZs of at least 75% should be considered to ensure a sufficient increase in Shannon diversity and decrease in quasi-extinction risks. These high amounts of ABZs represent effective conservation measures to safeguard the stability of pollination services provided by solitary bee species. As the model structure can be easily adapted to other mobile species in agricultural landscapes, our community approach offers the chance to compare the effectiveness of conservation measures also for other pollinator communities in future.
As mid-19th-century American Jews introduced radical changes to their religious observance and began to define Judaism in new ways, to what extent did they engage with European Jewish ideas? Historians often approach religious change among Jews from German lands during this period as if Jewish immigrants had come to America with one set of ideas that then evolved solely in conversation with their American contexts. Historians have similarly cast the kinds of Judaism Americans created as both unique to America and uniquely American. These characterizations are accurate to an extent. But to what extent did Jewish innovations in the United States take place in conversation with European Jewish developments? Looking to the 19th-century American Jewish press, this paper seeks to understand how American Jews engaged European Judaism in formulating their own ideas, understanding themselves, and understanding their place in world Judaism.
Two dimensional gas chromatography coupled to time-of-flight mass spectrometry (GCxGC-TOF-MS) is a promising technique to overcome limits of complex metabolome analysis using one dimensional GC-TOF-MS. Especially at the stage of data export and data mining, however, convenient procedures to cope with the complexity of GCxGC-TOF-MS data are still in development. Here, we present a high sample throughput protocol exploiting first and second retention index for spectral library search and subsequent construction of a high dimensional data matrix useful for statistical analysis. The method was applied to the analysis of 13 C-labelling experiments in the unicellular green alga Chlamydomonas reinhardtii. We developed a rapid sampling and extraction procedure for Chlamydomonas reinhardtii laboratory strain (CC503), a cell wall deficient mutant. By testing all published quenching protocols we observed dramatic metabolite leakage rates for certain metabolites. To circumvent metabolite leakage, samples were directly quenched and analyzed without separation of the medium. The growth medium was adapted to this rapid sampling protocol to avoid interference with GCxGC-TOF-MS analysis. To analyse batches of samples a new software tool, MetMax, was implemented which extracts the isotopomer matrix from stable isotope labelling experiments together with the first and second retention index (RI1 and RI2). To exploit RI1 and RI2 for metabolite identification we used the Golm metabolome database (GMD [1] with RI1/ RI2-reference spectra and new search algorithms. Using those techniques we analysed the dynamics of (CO2)-C-13 and C-13- acetate uptake in Chlamydomonas reinhardtii cells in two different steady states namely photoautotrophic and mixotrophic growth conditions.
Background: The prevalence of diabetes worldwide is predicted to increase from 2.8% in 2000 to 4.4% in 2030. Diabetic neuropathy (DN) is associated with damage to nerve glial cells, their axons, and endothelial cells leading to impaired function and mobility.
Objective: We aimed to examine the effects of an endurance-dominated exercise program on maximum oxygen consumption (VO2max), ground reaction forces, and muscle activities during walking in patients with moderate DN.
Methods: Sixty male and female individuals aged 45–65 years with DN were randomly assigned to an intervention (IG, n = 30) or a waiting control (CON, n = 30) group. The research protocol of this study was registered with the Local Clinical Trial Organization (IRCT20200201046326N1). IG conducted an endurance-dominated exercise program including exercises on a bike ergometer and gait therapy. The progressive intervention program lasted 12 weeks with three sessions per week, each 40–55 min. CON received the same treatment as IG after the post-tests. Pre- and post-training, VO2max was tested during a graded exercise test using spiroergometry. In addition, ground reaction forces and lower limbs muscle activities were recorded while walking at a constant speed of ∼1 m/s.
Results: No statistically significant baseline between group differences was observed for all analyzed variables. Significant group-by-time interactions were found for VO2max (p < 0.001; d = 1.22). The post-hoc test revealed a significant increase in IG (p < 0.001; d = 1.88) but not CON. Significant group-by-time interactions were observed for peak lateral and vertical ground reaction forces during heel contact and peak vertical ground reaction force during push-off (p = 0.001–0.037; d = 0.56–1.53). For IG, post-hoc analyses showed decreases in peak lateral (p < 0.001; d = 1.33) and vertical (p = 0.004; d = 0.55) ground reaction forces during heel contact and increases in peak vertical ground reaction force during push-off (p < 0.001; d = 0.92). In terms of muscle activity, significant group-by-time interactions were found for vastus lateralis and gluteus medius during the loading phase and for vastus medialis during the mid-stance phase, and gastrocnemius medialis during the push-off phase (p = 0.001–0.044; d = 0.54–0.81). Post-hoc tests indicated significant intervention-related increases in vastus lateralis (p = 0.001; d = 1.08) and gluteus medius (p = 0.008; d = 0.67) during the loading phase and vastus medialis activity during mid-stance (p = 0.001; d = 0.86). In addition, post-hoc tests showed decreases in gastrocnemius medialis during the push-off phase in IG only (p < 0.001; d = 1.28).
Conclusions: This study demonstrated that an endurance-dominated exercise program has the potential to improve VO2max and diabetes-related abnormal gait in patients with DN. The observed decreases in peak vertical ground reaction force during the heel contact of walking could be due to increased vastus lateralis and gluteus medius activities during the loading phase. Accordingly, we recommend to implement endurance-dominated exercise programs in type 2 diabetic patients because it is feasible, safe and effective by improving aerobic capacity and gait characteristics.
We launched an original large-scale experiment concerning informatics learning in French high schools. We are using the France-IOI platform to federate resources and share observation for research. The first step is the implementation of an adaptive hypermedia based on very fine grain epistemic modules for Python programming learning. We define the necessary traces to be built in order to study the trajectories of navigation the pupils will draw across this hypermedia. It may be browsed by pupils either as a course support, or an extra help to solve the list of exercises (mainly for algorithmics discovery). By leaving the locus of control to the learner, we want to observe the different trajectories they finally draw through our system. These trajectories may be abstracted and interpreted as strategies and then compared for their relative efficiency. Our hypothesis is that learners have different profiles and may use the appropriate strategy accordingly. This paper presents the research questions, the method and the expected results.