Reimbursement of VAT on written-off Receivables

In many OECD countries, a seller has a right to reimbursement of VAT (RVAT) she has paid on goods sold, but for which she has not yet received payment. Such reimbursement of VAT on receivables is economically inefficient. It leads to: * Distortion of credit markets, by subsidizing direct credit at the cost of financial intermediaries. * Price discrimination, by subsidizing buyers with low creditworthiness. * A less efficient collection of bad debts, as trade with bad debts is made extremely expensive. The finance literature presents several "good" arguments in favor of trade credits, e.g. transaction costs and asymmetric information. In contrast RVAT is an economically "bad" argument for trade credit. It is a subsidy that leads to inefficiently high use of trade credit

Descriptive analysis of preschool physical activity and sedentary behaviors - a cross sectional study of 3-year-olds nested in the SKOT cohort

Abstract Background Further collection of surveillance data is warranted, particularly in preschool populations, for optimizing future public health promotion strategies. This study aims to describe physical activity (PA) and sedentary behavior (SB) across different settings, including time in and out of daycare, and to determine the proportion of children complying with suggested PA recommendations in a high income country. Methods Valid PA was assessed in 231 children (36.4 ± 1.1 months) with the Actigraph GT3X accelerometer, and information regarding date and time of dropping-off/picking-up children in daycare was provided by parents. Mean total PA (i.e., counts per minute (CPM)), moderate-to-vigorous physical activity (MVPA), SB time, and non-SB time was generated and compared across settings. Post hoc, PA and SB were examined in subgroups of low-active (1st quartile) and high-active (4th quartile) children. Results Overall, boys and girls spent 1.4 ± 0.3 h/day and 1.2 ± 0.4 h/day in MVPA, respectively. Likewise, boys and girls accumulated 6.7 ± 0.8 h and 6.8 ± 0.9 h of SB time per day, respectively. Higher PA levels consistently co-occurred with lower SB time in the daycare setting. Girls accumulated less SB time in daycare than before and after daycare (β = −12.2%, p < 0.001 & β = −3.8%, p < 0.001, respectively). In boys, daycare-days contained more PA and less SB than non-daycare-days (CPM: β =29, p = 0.046, %MVPA: β = 0.83, p = 0.007, %SB: β = −2.3, p < 0.001, respectively). All children fulfilled recommendations of at least 3 h of daily non-SB. Eighty-nine percent of boys and 72% of girls met the daily 1-h MVPA recommendation for 5 year-olds. Lower proportions of children, especially boys, fulfilled MVPA recommendation on days with no daycare attendance. Generally, large mean differences in MVPA and SB were observed across all settings between the most active and the least active children, and only 7% of the low-active girls and 59% of the low-active boys fulfilled MVPA recommendations. Conclusions Overall, the majority of children fulfilled MVPA guidelines for 5 year-olds, and all children complied with suggested recommendations of 180 min of daily activity. Daycare time was found to represent an important setting for PA. Substantial and consistent differences observed in the amount of time spent physically active between high- and low-active children across all settings indicate substantial variations in young children’s PA levels irrespective of the context

The intensity of physical activity influences bone mineral accrual in childhood:the childhood health, activity and motor performance school (the CHAMPS) study, Denmark

BACKGROUND: Studies indicate genetic and lifestyle factors can contribute to optimal bone development. In particular, the intensity level of physical activity may have an impact on bone health. This study aims to assess the relationship between physical activity at different intensities and Bone Mineral Content (BMC), Bone Mineral Density (BMD) and Bone Area (BA) accretion. METHODS: This longitudinal study is a part of The CHAMPS study-DK. Whole-body DXA scans were performed at baseline and after two years follows up. BMC, BMD, and BA were measured. The total body less head (TBLH) values were used. Physical activity (PA) was recorded by accelerometers (ActiGraph, model GT3X). Percentages of different PA intensity levels were calculated and log odds of two intensity levels of activity relative to the third level were calculated. Multilevel regression analyses were used to assess the relationship between the categories of physical activity and bone traits. RESULTS: Of 800 invited children, 742 (93%) accepted to participate. Of these, 682/742 (92%) participated at follow up. Complete datasets were obtained in 602/742 (81%) children. Mean (range) of age was 11.5 years (9.7-13.9). PA at different intensity levels was for boys and girls respectively, sedentary 62% and 64%, low 29% for both genders and moderate to high 9% and 7% of the total time. Mean (range) BMC, BMD, and BA was 1179 g (563–2326), 0.84 g/cm(2) (0.64-1.15) and 1393 cm(2) (851–2164), respectively. Valid accelerometer data were obtained for a mean of 6.1 days, 13 hours per day. CONCLUSIONS: There 7was a positive relationship between the log odds of moderate to high-level PA versus low level activity and BMC, BMD and BA. Children with an increased proportion of time in moderate to high-level activity as opposed to sedentary and low-level activity achieved positive effects on BMC, BMD and BA

Mechanical and free living comparisons of four generations of the Actigraph activity monitor.

BACKGROUND: More studies include multiple generations of the Actigraph activity monitor. So far no studies have compared the output including the newest generation and investigated the impact on the output of the activity monitor when enabling the low frequency extension (LFE) option. The aims were to study the responses of four generations (AM7164, GT1M, GT3X and GT3X+) of the Actigraph activity monitor in a mechanical setup and a free living environment with and without enabling the LFE option. METHODS: The monitors were oscillated in a mechanical setup using two radii in the frequency range 0.25-3.0 Hz. Following the mechanical study a convenience sample (N = 20) wore three monitors (one AM7164 and two GT3X) for 24 hours. RESULTS: The AM7164 differed from the newer generations across frequencies (p  0.05 for differences between generations) thus attenuated the difference in mean PA (p > 0.05) when the LFE option was enabled. However, it did not attenuate the difference in time spend in vigorous PA and it introduced a difference in time spend in moderate PA (+ 3.0 min (95% CI 0.4 to 5.6)) between the generations. CONCLUSION: We observed significant differences between the AM7164 and the newer Actigraph GT-generations (GT1M, GT3X and GT3X+) in a mechanical setup and in free-living. Enabling the LFE option attenuated the differences in mean PA completely, but induced a bias in the moderate PA intensities.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

45 minutters bevægelse i undervisningen som et led i den danske skolereform

I skoleåret 2014/15 trådte en ny skolereform i kraft, hvor bevægelse fik en fremtrædende rolle med lovkravet om 45 minutters daglig bevægelse integreret i undervisningen. Det er nu snart syv år siden, reformen trådte i kraft, og resultater viser, at mange skoler endnu ikke har formået at få realiseret lovkravet. Det kan der være flere årsager til, men klart er det, at decentralisering af implementeringsansvaret ikke ser ud til at have været tilstrækkeligt. En fælles implementeringsunderstøttelse ville formentlig have været til stor gavn for skolerne

Efficacy of seven and fourteen days of antibiotic treatment in uncomplicated Staphylococcus aureus bacteremia (SAB7):study protocol for a randomized controlled trial

SPIRIT 2013 checklist. (DOC 122 kb

Classification of amyloidosis by model‐assisted mass spectrometry‐based proteomics

Funding Information: Funding: This research was partly funded by a “Center of Clinical Excellence” research grant from the Health Region of Southern Denmark to Odense Amyloidosis Center (AmyC). Publisher Copyright: © 2021 by the authors. Li-censee MDPI, Basel, Switzerland.Amyloidosis is a rare disease caused by the misfolding and extracellular aggregation of proteins as insoluble fibrillary deposits localized either in specific organs or systemically through-out the body. The organ targeted and the disease progression and outcome is highly dependent on the specific fibril‐forming protein, and its accurate identification is essential to the choice of treat-ment. Mass spectrometry‐based proteomics has become the method of choice for the identification of the amyloidogenic protein. Regrettably, this identification relies on manual and subjective inter-pretation of mass spectrometry data by an expert, which is undesirable and may bias diagnosis. To circumvent this, we developed a statistical model‐assisted method for the unbiased identification of amyloid‐containing biopsies and amyloidosis subtyping. Based on data from mass spectrometric analysis of amyloid‐containing biopsies and corresponding controls. A Boruta method applied on a random forest classifier was applied to proteomics data obtained from the mass spectrometric analysis of 75 laser dissected Congo Red positive amyloid‐containing biopsies and 78 Congo Red negative biopsies to identify novel “amyloid signature” proteins that included clusterin, fibulin‐1, vitronectin complement component C9 and also three collagen proteins, as well as the well‐known amyloid signature proteins apolipoprotein E, apolipoprotein A4, and serum amyloid P. A SVM learning algorithm were trained on the mass spectrometry data from the analysis of the 75 amyloid-containing biopsies and 78 amyloid‐negative control biopsies. The trained algorithm performed su-perior in the discrimination of amyloid‐containing biopsies from controls, with an accuracy of 1.0 when applied to a blinded mass spectrometry validation data set of 103 prospectively collected am-yloid‐containing biopsies. Moreover, our method successfully classified amyloidosis patients ac-cording to the subtype in 102 out of 103 blinded cases. Collectively, our model‐assisted approach identified novel amyloid‐associated proteins and demonstrated the use of mass spectrometry‐based data in clinical diagnostics of disease by the unbiased and reliable model‐assisted classification of amyloid deposits and of the specific amyloid subtype.publishersversionpublishe