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Background
Recently, the incidence rate of back pain (BP) in adolescents has been reported at 21%. However, the development of BP in adolescent athletes is unclear. Hence, the purpose of this study was to examine the incidence of BP in young elite athletes in relation to gender and type of sport practiced.
Methods
Subjective BP was assessed in 321 elite adolescent athletes (m/f 57%/43%; 13.2 ± 1.4 years; 163.4 ± 11.4 cm; 52.6 ± 12.6 kg; 5.0 ± 2.6 training yrs; 7.6 ± 5.3 training h/week). Initially, all athletes were free of pain. The main outcome criterion was the incidence of back pain [%] analyzed in terms of pain development from the first measurement day (M1) to the second measurement day (M2) after 2.0 ± 1.0 year. Participants were classified into athletes who developed back pain (BPD) and athletes who did not develop back pain (nBPD). BP (acute or within the last 7 days) was assessed with a 5-step face scale (face 1–2 = no pain; face 3–5 = pain). BPD included all athletes who reported faces 1 and 2 at M1 and faces 3 to 5 at M2. nBPD were all athletes who reported face 1 or 2 at both M1 and M2. Data was analyzed descriptively. Additionally, a Chi2 test was used to analyze gender- and sport-specific differences (p = 0.05).
Results
Thirty-two athletes were categorized as BPD (10%). The gender difference was 5% (m/f: 12%/7%) but did not show statistical significance (p = 0.15). The incidence of BP ranged between 6 and 15% for the different sport categories. Game sports (15%) showed the highest, and explosive strength sports (6%) the lowest incidence. Anthropometrics or training characteristics did not significantly influence BPD (p = 0.14 gender to p = 0.90 sports; r2 = 0.0825).
Conclusions
BP incidence was lower in adolescent athletes compared to young non-athletes and even to the general adult population. Consequently, it can be concluded that high-performance sports do not lead to an additional increase in back pain incidence during early adolescence. Nevertheless, back pain prevention programs should be implemented into daily training routines for sport categories identified as showing high incidence rates.
Behavioural Models
(2016)
This textbook introduces the basis for modelling and analysing discrete dynamic systems, such as computer programmes, soft- and hardware systems, and business processes. The underlying concepts are introduced and concrete modelling techniques are described, such as finite automata, state machines, and Petri nets. The concepts are related to concrete application scenarios, among which business processes play a prominent role.
The book consists of three parts, the first of which addresses the foundations of behavioural modelling. After a general introduction to modelling, it introduces transition systems as a basic formalism for representing the behaviour of discrete dynamic systems. This section also discusses causality, a fundamental concept for modelling and reasoning about behaviour. In turn, Part II forms the heart of the book and is devoted to models of behaviour. It details both sequential and concurrent systems and introduces finite automata, state machines and several different types of Petri nets. One chapter is especially devoted to business process models, workflow patterns and BPMN, the industry standard for modelling business processes. Lastly, Part III investigates how the behaviour of systems can be analysed. To this end, it introduces readers to the concept of state spaces. Further chapters cover the comparison of behaviour and the formal analysis and verification of behavioural models.
The book was written for students of computer science and software engineering, as well as for programmers and system analysts interested in the behaviour of the systems they work on. It takes readers on a journey from the fundamentals of behavioural modelling to advanced techniques for modelling and analysing sequential and concurrent systems, and thus provides them a deep understanding of the concepts and techniques introduced and how they can be applied to concrete application scenarios.
Implementation of a plasmodesmata gatekeeper system, and its effect on intercellular transport
(2016)
The title compounds, [(1R,3R,4R,5R,6S)-4,5-bis(acetyloxy)-7-oxo-2-oxabicyclo-
[4.2.0]octan-3-yl]methyl acetate, C14H18O8, (I), [(1S,4R,5S,6R)-5-acetyloxy-7-
hydroxyimino-2-oxobicyclo[4.2.0]octan-4-yl acetate, C11H15NO6, (II), and
[(3aR,5R,6R,7R,7aS)-6,7-bis(acetyloxy)-2-oxooctahydropyrano[3,2-b]pyrrol-5-
yl]methyl acetate, C14H19NO8, (III), are stable bicyclic carbohydrate derivatives.
They can easily be synthesized in a few steps from commercially available
glycals. As a result of the ring strain from the four-membered rings in (I) and
(II), the conformations of the carbohydrates deviate strongly from the ideal
chair form. Compound (II) occurs in the boat form. In the five-membered
lactam (III), on the other hand, the carbohydrate adopts an almost ideal chair
conformation. As a result of the distortion of the sugar rings, the configurations
of the three bicyclic carbohydrate derivatives could not be determined from
their NMR coupling constants. From our three crystal structure determinations,
we were able to establish for the first time the absolute configurations of all new
stereocenters of the carbohydrate rings.
The population structure of the highly mobile marine mammal, the harbor porpoise (Phocoena phocoena), in the Atlantic shelf waters follows a pattern of significant isolation-by-distance. The population structure of harbor porpoises from the Baltic Sea, which is connected with the North Sea through a series of basins separated by shallow underwater ridges, however, is more complex. Here, we investigated the population differentiation of harbor porpoises in European Seas with a special focus on the Baltic Sea and adjacent waters, using a population genomics approach. We used 2872 single nucleotide polymorphisms (SNPs), derived from double digest restriction-site associated DNA sequencing (ddRAD-seq), as well as 13 microsatellite loci and mitochondrial haplotypes for the same set of individuals. Spatial principal components analysis (sPCA), and Bayesian clustering on a subset of SNPs suggest three main groupings at the level of all studied regions: the Black Sea, the North Atlantic, and the Baltic Sea. Furthermore, we observed a distinct separation of the North Sea harbor porpoises from the Baltic Sea populations, and identified splits between porpoise populations within the Baltic Sea. We observed a notable distinction between the Belt Sea and the Inner Baltic Sea sub-regions. Improved delineation of harbor porpoise population assignments for the Baltic based on genomic evidence is important for conservation management of this endangered cetacean in threatened habitats, particularly in the Baltic Sea proper. In addition, we show that SNPs outperform microsatellite markers and demonstrate the utility of RAD-tags from a relatively small, opportunistically sampled cetacean sample set for population diversity and divergence analysis.