Why do you dance? Development of the Dance Motivation Inventory (DMI)

Dancing is a popular form of physical exercise and studies have show that dancing can decrease anxiety, increase self-esteem, and improve psychological wellbeing. The aim of the current study was to explore the motivational basis of recreational social dancing and develop a new psychometric instrument to assess dancing motivation. The sample comprised 447 salsa and/or ballroom dancers (68% female; mean age 32.8 years) who completed an online survey. Eight motivational factors were identified via exploratory factor analysis and comprise a new Dance Motivation Inventory: Fitness, Mood Enhancement, Intimacy, Socialising, Trance, Mastery, Self-confidence and Escapism. Mood Enhancement was the strongest motivational factor for both males and females, although motives differed according to gender. Dancing intensity was predicted by three motivational factors: Mood Enhancement, Socialising, and Escapism. The eight dimensions identified cover possible motives for social recreational dancing, and the DMI proved to be a suitable measurement tool to assess these motives. The explored motives such as Mood Enhancement, Socialising and Escapism appear to be similar to those identified in other forms of behaviour such as drinking alcohol, exercise, gambling, and gaming

Resistance Breeding in Apple at Dresden-Pillnitz

Resistance breeding in apple has a long tradition at the Institute of Fruit Breeding now Julius Kuehn-institute in Dresden-Pillnitz. The breeding was aimed at the production of multiple resistance cultivars to allow a more sustainable and environmentally friendly production of apple. In the last decades a series of resistant cultivars (Re®-cultivars) bred in Dresden-Pillnitz has been released, ‘Recolor’ and ‘Rekarda’ in 2006. The main topic in the resistance breeding programme was scab resistance and the donor of scab resistance in most cultivars was Malus x floribunda 821. Due to the development of strains that are able to overcome resistance genes inherited by M. x floribunda 821 and due to the fact that single resistance genes can be broken easily, pyramiding of resistance genes is necessary. Besides scab, fire blight and powdery mildew are the main disease for which a pyramiding of genes is aspired in Pillnitz. Biotechnical approaches are necessary for the early detection of pyramided resistance genes in breeding clones. This paper will give an overview of the resistance breeding of apple in Pillnitz and the methods used

Machine Learning in Falls Prediction; A cognition-based predictor of falls for the acute neurological in-patient population

Background Information: Falls are associated with high direct and indirect costs, and significant morbidity and mortality for patients. Pathological falls are usually a result of a compromised motor system, and/or cognition. Very little research has been conducted on predicting falls based on this premise. Aims: To demonstrate that cognitive and motor tests can be used to create a robust predictive tool for falls. Methods: Three tests of attention and executive function (Stroop, Trail Making, and Semantic Fluency), a measure of physical function (Walk-12), a series of questions (concerning recent falls, surgery and physical function) and demographic information were collected from a cohort of 323 patients at a tertiary neurological center. The principal outcome was a fall during the in-patient stay (n = 54). Data-driven, predictive modelling was employed to identify the statistical modelling strategies which are most accurate in predicting falls, and which yield the most parsimonious models of clinical relevance. Results: The Trail test was identified as the best predictor of falls. Moreover, addition of any others variables, to the results of the Trail test did not improve the prediction (Wilcoxon signed-rank p < .001). The best statistical strategy for predicting falls was the random forest (Wilcoxon signed-rank p < .001), based solely on results of the Trail test. Tuning of the model results in the following optimized values: 68% (+- 7.7) sensitivity, 90% (+- 2.3) specificity, with a positive predictive value of 60%, when the relevant data is available. Conclusion: Predictive modelling has identified a simple yet powerful machine learning prediction strategy based on a single clinical test, the Trail test. Predictive evaluation shows this strategy to be robust, suggesting predictive modelling and machine learning as the standard for future predictive tools

Arc Simulation at Shunt-Reactor Switching in H.V. Circuit Breakers

High energy re-ignitions occur in h.v. circuit breakers, when interrupting shunt-reactor currents. The es-calating high frequency over-voltages, which are proportional to the arcing time, are stressful both to the reactor and the circuit breakers. We simulated the electric, thermal and flow field inside the thermal chamber and determined the reduced electric field distribution. Analysing the simulation results the main factors to improve the shunt-reactor breaking capacity are demonstrated

Artificial elevation of glutathione contents in salicylic acid-deficient tobacco (Nicotiana tabacum cv. Xanthi NahG) reduces susceptibility to the powdery mildew pathogen Euoidium longipes

The effects of elevated glutathione levels on defence responses to powdery mildew (Euoidium longipes) were investigated in a salicylic acid-deficient tobacco (Nicotiana tabacum cv. Xanthi NahG) and wild-type cv. Xanthi plants, where salicylic acid (SA) contents are normal. Aqueous solutions of reduced glutathione (GSH) and its synthetic precursor R-2-oxothiazolidine-4-carboxylic acid (OTC) were injected into leaves of tobacco plants 3 h before powdery mildew inoculation. SA-deficient NahG tobacco was hyper-susceptible to E. longipes, as judged by significantly more severe powdery mildew symptoms and enhanced pathogen accumulation. Strikingly, elevation of GSH levels in SA-deficient NahG tobacco restored susceptibility to E. longipes to the extent seen in wild-type plants (i.e. enhanced basal resistance). However, expression of the SA-mediated pathogenesis-related gene (NtPR-1a) did not increase significantly in GSH or OTC-pretreated and powdery mildew-inoculated NahG tobacco, suggesting that the induction of this PR gene may not be directly involved in the defence responses induced by GSH. Our results demonstrate that artificial elevation of glutathione content can significantly reduce susceptibility to powdery mildew in SA-deficient tobacco

Prevalence of problematic internet use in Slovenia

BACKGROUND: Internet use is an integral part of our everyday activities; however, Internet use may become problematic and harmful in a minority of cases. The majority of reported prevalence rates of problematic Internet use refer to adolescent samples, whereas epidemiological studies on representative adult populations are lacking. This study aimed to reveal the prevalence and characteristics of problematic Internet use in Slovenia. METHODS: Problematic Internet Use Questionnaire (PIUQ) was included in European Health Interview Study (EHIS) on representative Slovenian sample. The frequency of Internet use and problematic Internet use were both assessed. RESULTS: 59.9% of Slovenian adult population uses the Internet daily, and 3.1% are at risk of becoming problematic Internet users, 11% in the age group from 20 to 24 years. Those being at risk for becoming problematic Internet users are younger (mean age 31.3 vs. 48.3 for non-problematic users), more likely to be males (3.6% of males, whereas 2.6% of females are affected), students (12.0%), unemployed (6.3%) or unable to work (8.7%), single (6.5%), with high education (4.5%). Regression analysis revealed that the strongest predictor of being at risk for problematic Internet use is age (ß=-0.338, p<0.001); followed by high educational level (ß=0.145; p<0.001) and student status (ß=0.136; p<0.001). CONCLUSION: 3.1% of Slovenian adult population are at risk of becoming problematic Internet users, whereas 3 out of 20 Slovenian adolescents aged from 18 to 19 years are at risk (14.6%). Prevention programs and treatment for those affected are paramount, especially for the young generation

On Generalizations of Network Design Problems with Degree Bounds

Iterative rounding and relaxation have arguably become the method of choice in dealing with unconstrained and constrained network design problems. In this paper we extend the scope of the iterative relaxation method in two directions: (1) by handling more complex degree constraints in the minimum spanning tree problem (namely, laminar crossing spanning tree), and (2) by incorporating `degree bounds' in other combinatorial optimization problems such as matroid intersection and lattice polyhedra. We give new or improved approximation algorithms, hardness results, and integrality gaps for these problems.Comment: v2, 24 pages, 4 figure

An Integer Programming Approach to the Student-Project Allocation Problem with Preferences over Projects

The Student-Project Allocation problem with preferences over Projects (SPA-P) involves sets of students, projects and lecturers, where the students and lecturers each have preferences over the projects. In this context, we typically seek a stable matching of students to projects (and lecturers). However, these stable matchings can have different sizes, and the problem of finding a maximum stable matching (MAX-SPA-P) is NP-hard. There are two known approximation algorithms for MAX-SPA-P, with performance guarantees of 2 and 32 . In this paper, we describe an Integer Programming (IP) model to enable MAX-SPA-P to be solved optimally. Following this, we present results arising from an empirical analysis that investigates how the solution produced by the approximation algorithms compares to the optimal solution obtained from the IP model, with respect to the size of the stable matchings constructed, on instances that are both randomly-generated and derived from real datasets. Our main finding is that the 32 -approximation algorithm finds stable matchings that are very close to having maximum cardinality

Juvenile Huntington’s disease skin fibroblasts respond with elevated parkin level and increased proteasome activity as a potential mechanism to counterbalance the pathological consequences of mutant Huntingtin protein

Huntington&rsquo;s disease (HD) is an inherited neurodegenerative disorder, caused by an abnormal polyglutamine (polyQ) expansion in the huntingtin protein (Htt). Mitochondrial dysfunction and impairment of the ubiquitin-proteasome system (UPS) are hallmarks of HD neurons. The extraneural manifestations of HD are still unclear. We investigated the crosstalk between mitochondria and proteolytic function in skin fibroblasts from juvenile HD patients. We found reduced mitosis, increased cell size, elevated ROS and increased mitochondrial membrane potential in juvenile HD fibroblasts, while cellular viability was maintained. Mitochondrial OXPHOS analysis did not reveal significant differences compared to control. However, the level of mitochondrial fusion and fission proteins was significantly lower and branching in the mitochondria network was reduced. We hypothesized that juvenile HD fibroblasts counterbalance cellular damage and mitochondrial network deficit with altered proteasome activity to promote cell survival. Our data reveal that juvenile HD fibroblasts exhibit higher proteasome activity, which was associated with elevated gene and protein expression of parkin. Moreover, we demonstrate elevated proteasomal degradation of the mitochondrial fusion protein Mfn1 in diseased cells compared to control cells. Our data suggest that juvenile HD fibroblasts respond to mutant polyQ expansion of Htt with enhanced proteasome activity and faster turnover of specific UPS substrates to protect cells