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Lillehammer, Norway

Lillehammer University College is a Norwegian state-run university college located at Storhove in Lillehammer. It was established in 1971 as Oppland College and took its current form in 1995. It is located in the television and radio center built for the 1994 Winter Olympic Games. The college offers undergraduate programs in Travel and Tourism, Business Administration, Organisation and Management, Film and Television, Health and Social Work, Humanities and Social science, and graduate programs in Education, Social Policy, Health and Social Work for Children and Youth, Social Welfare, and Film and TV Science. The Norwegian Film School was founded as part of the college in 1997. Wikipedia.


Tjorve E.,Lillehammer University College
Journal of Theoretical Biology | Year: 2010

The SLOSS debate - whether a single large reserve will conserve more species than several small - of the 1970s and 1980s never came to a resolution. The first rule of reserve design states that one large reserve will conserve the most species, a rule which has been heavily contested. Empirical data seem to undermine the reliance on general rules, indicating that the best strategy varies from case to case. Modeling has also been deployed in this debate. We may divide the modeling approaches to the SLOSS enigma into dynamic and static approaches. Dynamic approaches, covered by the fields of island equilibrium theory of island biogeography and metapopulation theory, look at immigration, emigration, and extinction. Static approaches, such as the one in this paper, illustrate how several factors affect the number of reserves that will save the most species.This article approaches the effect of different factors by the application of species-diversity models. These models combine species-area curves for two or more reserves, correcting for the species overlap between them. Such models generate several predictions on how different factors affect the optimal number of reserves. The main predictions are: Fewer and larger reserves are favored by increased species overlap between reserves, by faster growth in number of species with reserve area increase, by higher minimum-area requirements, by spatial aggregation and by uneven species abundances. The effect of increased distance between smaller reserves depends on the two counteracting factors: decreased species density caused by isolation (which enhances minimum-area effect) and decreased overlap between isolates. The first decreases the optimal number of reserves; the second increases the optimal number. The effect of total reserve-system area depends both on the shape of the species-area curve and on whether overlap between reserves changes with scale.The approach to modeling presented here has several implications for conservational strategies. It illustrates well how the SLOSS enigma can be reduced to a question of the shape of the species-area curve that is expected or generated from reserves of different sizes and a question of overlap between isolates (or reserves). © 2010 Elsevier Ltd. Source


Ronnestad B.R.,Lillehammer University College
European Journal of Applied Physiology | Year: 2013

The aim of the present study was to investigate the effects of the seasonal changes in heavy strength training on maximal strength and vertical jump ability in internationally competing ski jumpers. A repeated-measures design was used to follow-up the changes in strength, vertical jump capacity, and neuromuscular efficiency (expressed as the ratio between squat jump height and the relative isometric force) in the ski jumpers. Measurements were performed in November (pre), January (middle of the competition season), and in March (end of the competition season). The weekly number of strength training sessions, absolute, and relative peak isometric squat force was significantly reduced during the competition period (p < 0.05). The body mass was reduced from pre-season to the middle of the competition season and remained at this level at the end of the competition season (p < 0.05). Squat jump height remained unchanged from pre-season until the end of the competition season (p < 0.05). Neuromuscular efficiency increased from pre-season until the end of the competition season (p < 0.05). The present study shows that maximal strength and body weight is reduced from pre-season to the end of the competitive season in internationally competing ski jumpers. The vertical jump ability did not change from pre-season to the end of the competitive season, while the neuromuscular efficiency increased during the competitive season. These findings indicate that coaches and athletes should emphasize adequate nutritional strategies and to apply a larger focus on strength maintenance training during the competitive season to maximize ski jump performance. © 2013 Springer-Verlag Berlin Heidelberg. Source


Ronnestad B.R.,Lillehammer University College | Mujika I.,University of the Basque Country | Mujika I.,Finis Terrae University
Scandinavian Journal of Medicine and Science in Sports | Year: 2014

Here we report on the effect of combining endurance training with heavy or explosive strength training on endurance performance in endurance-trained runners and cyclists. Running economy is improved by performing combined endurance training with either heavy or explosive strength training. However, heavy strength training is recommended for improving cycling economy. Equivocal findings exist regarding the effects on power output or velocity at the lactate threshold. Concurrent endurance and heavy strength training can increase running speed and power output at VO2max (Vmax and Wmax, respectively) or time to exhaustion at Vmax and Wmax. Combining endurance training with either explosive or heavy strength training can improve running performance, while there is most compelling evidence of an additive effect on cycling performance when heavy strength training is used. It is suggested that the improved endurance performance may relate to delayed activation of less efficient type II fibers, improved neuromuscular efficiency, conversion of fast-twitch type IIX fibers into more fatigue-resistant type IIA fibers, or improved musculo-tendinous stiffness. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd. Source


AIMS-This study investigates the prevalence of use of doping agents and symptoms of eating disorders among patients in drug addiction treatment. The aim is also to look for characteristics of the groups reporting the use of doping agents or symptoms of eating disorders. DESIGN-A survey including questions on exercise, the use of doping agents and Eating Disorder Inventory-2 was administered in a Norwegian drug addiction facility. The study included 109 patients in residential drug treatment, 30 females and 79 males (ranging from 17 to 50 years old). RESULTS-Symptoms of eating disorders were reported by 33 percent of the females and 7.6 percent of the males. Previous use of doping agents (anabolic-androgenic steroids in particular) was reported by 40.5 percent of the men and 20 percent of the women. The results are discussed in light of the theory on emotion regulation, gender and cultural expectations, drug treatment as a liminal phase and similarities to drug addiction. CONCLUSIONS-The symptoms of eating disorders and the use of doping agents are prevalent in this sample of male and female drug addicts in treatment. Drug treatment facilities should be aware of this and take the appropriate actions regarding attention, screening and treatment. Source


Tjorve E.,Lillehammer University College
Journal of Biogeography | Year: 2012

Aim Studies have typically employed species-area relationships (SARs) from sample areas to fit either the power relationship or the logarithmic (exponential) relationship. However, the plots from empirical data often fall between these models. This article proposes two complementary and hybrid models as solutions to the controversy regarding which model best fits sample-area SARs. Methods The two models are S A = (c1 + b log A) dA/A+n · (c 2A z) 1 dA/A+n and S A = (c1 + b log A) 1 dA/A+n · (c 2A z) dA/A+n, where S A is number of species in an area, A, where z, b, c 1 and c 2 are predetermined parameters found by calculation, and where d and n are parameters to be fitted. The number of parameters is reduced from six to two by fixing the model at either end of the scale window of the data set, a step that is justified by the condition that the error or the bias, or both, in the first and the last data points is negligible. The new hybrid models as well as the power model and the logarithmic model are fitted to 10 data sets. Results The two proposed models fit well not only to Arrhenius' and Gleason's data sets, but also to the other six data sets. They also provide a good fit to data sets that follow a sigmoid (or triphasic) shape in log-log space and to data sets that do not fall between the power model and the logarithmic model. The log-transformation of the dependent variable, S, does not affect the curve fit appreciably, although it enhances the performance of the new models somewhat. Main conclusions Sample-area SARs have previously been shown to be convex upward, convex downward (concave), sigmoid and inverted sigmoid in log-log space. The new hybrid models describe successfully data sets with all these curve shapes, and should therefore produce good fits also to what are termed triphasic SARs. © 2011 Blackwell Publishing Ltd. Source

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