A 14-h night-shift in the control room of a fire brigade

All 29 operators in the control room of a fire brigade performed test sessions during work and leisure time at 2-h intervals on a day with a 14-h night-shift, a day off and a day with a 10-h morning shift. The test sessions consisted of a visual search choice reaction time test and two Sternberg memory search tests (1 or 5 letters had to be memorized). Furthermore, the operators recorded their oral temperature and their subjective alertness before each test session. The subject also kept a diary of work and sleep times for 14 days. The circadian rhythm of body temperature was hardly changed by a single night-shift. Parallel to the body temperature, the subjective alertness fell significantly during the night-shift reaching a minimum value at 06:00 h. The mean reaction times increased non-significantly at the end of the night-shift and the results of the two Sternberg memory search tests showed no significant trends. The sleep of the operators after the night-shift was on average reduced to 5 hs 34 min. The results of subjective rating of alertness and reaction time test are interpreted as effects of the combined influences of circadian rhythmicity, sleep loss and time on professional task. Most results support the conclusion that a 14-h night-shift without extensive breaks is not acceptable.     

Supervisionsausbildung als Lernende Organisation oder: Wie weit ist es nach Teplá?

People are changed by organisations and people change organisations. Supervisors are active with their consultancy work on this interface. Organisation is therefore a central topic and learning field which is handled on different levels (systemic-structural, personal-biographic, phenomenal) in the counsellingsupervision training, which the author has been practicing since 20 years. This is not done in a theoretical way but through a concrete approach.     

Nonparametric estimation of discrete hazard functions

A smoothing procedure for discrete time failure data is proposed which allows for the inclusion of covariates. This purely nonparametric method is based on discrete or continuous kernel smoothing techniques that gives a compromise between the data and smoothness. The method may be used as an exploratory tool to uncover the underlying structure or as an alternative to parametric methods when prediction is the primary objective. Confidence intervals are considered and alternative techniques of cross validation based choices of smoothing parameters are investigated.     

The Epileptic: A Study in Status-Role Relationships

The status-role of the epileptic in the United States and elsewhere is such that he is handicapped in gaining employment and education. In fact, it is not epilepsy per se which prevents epileptics from adequately participating in our society, but the beliefs about epilepsy. These beliefs have a long history and are derived from ancient and mythical sources. They have no validity in the light of medical advances made in this field over the past thirty years. Hence it is now necessary to give epileptics those educational and vocational opportunities which others have and of which epileptics have been unjustly deprived.     

Local principal curves

Principal components are a well established tool in dimension reduction. The extension to principal curves allows for general smooth curves which pass through the middle of a multidimensional data cloud. In this paper local principal curves are introduced, which are based on the localization of principal component analysis. The proposed algorithm is able to identify closed curves as well as multiple curves which may or may not be connected. For the evaluation of the performance of principal curves as tool for data reduction a measure of coverage is suggested. By use of simulated and real data sets the approach is compared to various alternative concepts of principal curves.     

On-Line Scheduling of Two-Machine Open Shops Where Jobs Arrive Over Time

We investigate the problem of on-line scheduling two-machine open shops with the objective of minimizing the makespan.Jobs arrive independently over time, and the existence of a job is not known until its arrival. In the clairvoyant on-line model, the processing requirement of every job becomes fully known at the arrival of the job, while inthe non-clairvoyant on-line model, this processing requirement is notknown until the job is processed and completed.In both models, scheduling of a job is irrevocable.We study the two-machine open shop problem for both models in the preemptive and in the non-preemptive version. For each of the four variants, we provide an algorithm that is best possible with respect to the worst-case performance. In the clairvoyant on-line model, the best worst-case performance ratios are 5/4 (preemptive) and 3/2 (non-preemptive), and in the non-clairvoyant on-line model, they are 3/2 (preemptive and non-preemptive).     

Faktorenanalyse als ein Instrument zur Konstruktion von Preisniveauindizes

This paper proposes a solution to the problem of calculating price index numbers based on factor analysis. We present that the construction of price index numbers can be identical with determination of factors within the factor analysis. The price material for FRG during the period 1970 to 1979 (private consumption) shows that a definite identification and estimation for price index numbers in the two and multiple situation case is possible.     

Variable selection for generalized linear mixed models by L 1-penalized estimation

Generalized linear mixed models are a widely used tool for modeling longitudinal data. However, their use is typically restricted to few covariates, because the presence of many predictors yields unstable estimates. The presented approach to the fitting of generalized linear mixed models includes an L ₁-penalty term that enforces variable selection and shrinkage simultaneously. A gradient ascent algorithm is proposed that allows to maximize the penalized log-likelihood yielding models with reduced complexity. In contrast to common procedures it can be used in high-dimensional settings where a large number of potentially influential explanatory variables is available. The method is investigated in simulation studies and illustrated by use of real data sets.     

Analysis of the importance of on-field covariates in the German Bundesliga

In modern football, various variables as, for example, the distance a team runs or its percentage of ball possession, are collected throughout a match. However, there is a lack of methods to make use of these on-field variables simultaneously and to connect them with the final result of the match. This paper considers data from the German Bundesliga season 2015/2016. The objective is to identify the on-field variables that are connected to the sportive success or failure of the single teams. An extended Bradley–Terry model for football matches is proposed that is able to take into account on-field covariates. Penalty terms are used to reduce the complexity of the model and to find clusters of teams with equal covariate effects. The model identifies the running distance to be the on-field covariate that is most strongly connected to the match outcome.     

Self-Exclusion as a Harm Minimization Strategy: Evidence for the Casino Sector from Selected European Countries

As the international gambling market continues to expand, determining effective approaches to prevent gambling-related problems becomes increasingly important. Despite a lack of in-depth research into its benefits, self-exclusion is one such measure already in use around the world in various sectors of the gambling industry. The present study is the first of its kind to examine the effectiveness of self-exclusion schemes in the casino sector in selected European countries. A written survey yielded a sample of N = 152 (self)-excluded gamblers. In addition to this cross-section analysis, a small sub-group (n = 31) was monitored over time by means of follow-up surveys carried out 1, 6, and 12 month(s) after the exclusion agreement came into force. The results reveal that the self-excluded individuals are typically under a great deal of strain and show a relatively pronounced willingness to change. However, this largely reaches its peak at the time the decision to self-exclude is made. From a longitudinal perspective, various parameters indicate a clear improvement in psychosocial functioning; a favorable effect that also starts directly after the exclusion agreement was signed. Finally, considering theoretical and empirical findings, possibilities for optimizing (self-)exclusion schemes will be discussed.