Praxisbericht: Digitalisierung im Talentmanagement

This article of the magazine Gruppe, Interaktion, Organisation (GIO) covers the role of talent management regarding the digitisation of enterprises. Talent Management contributes to this process by identifying, developing and placing talent for the digitisation of enterprises. Deutsche Bahn utilizes a variety of approaches to digitize talent management.     

Breastfeeding practices and parental employment in Japan

Much research shows that breastfeeding provides short- and long-term health benefits for both mothers and their children. However, few studies have yet investigated the factors which may promote or inhibit breastfeeding practices in Japan. To fill this research gap, this paper uses data newly gathered in 2012 on breastfeeding initiation and duration for each child of each mother, which enable us to estimate mother fixed-effects models that control for unobserved differences among mothers. Compared to mothers who leave their jobs after childbirth, mothers who return to work within a year after childbirth do not significantly differ in breastfeeding initiation but have a breastfeeding duration which is shorter by 1.654 months. On the other hand, when fathers work under a flextime system after childbirth, breastfeeding initiation is higher, and the duration is longer by 4.418 months. Therefore, letting fathers work under a flextime system would help promote breastfeeding practices in Japan.     

Association between handgrip strength,walking, age-related illnesses and cognitive status in a sample of Portuguese centenarians

Background

Centenarians are a growing population in Europe and present significant variability in motor and cognitive functions. The aim of our study was to characterize health status, as well as cognitive and motor functions in a group of Portuguese centenarians. In addition, our study also aimed at analyzing the relationship between cognitive functions and the burden of diseases affecting the elderly.

Methods

Fifty-two centenarians were evaluated using the Mini-Mental State Examination, short version. Walking-related parameters (velocity and time spent in the 3 m walk test), grip strength and number of age-related illnesses were also measured. The relationship between cognitive scores and time spent in the three metre walk test, velocity, grip strength and number of diseases was analysed.

Results

Cognitive scores showed a positive correlation with both handgrip strength and time spent in the three metre walk. In contrast, no association was found between cognitive scores and the presence/absence of disease, walking velocity or number of diseases present.

Conclusions

These results suggest that in centenarians, cognitive functions may be related with motor functions.

     

Influence of a home-based exercise program on the urine pH in elderly female subjects: a secondary analysis of a randomized controlled trial

Background

A low urine pH is a characteristic metabolic feature of metabolic syndrome and type 2 diabetes. The purpose of the current study was to investigate the effects of a 12-week home-based bench step exercise on the urine pH status of elderly female subjects.

Methods

The current study is a secondary analysis of a randomized controlled trial (RCT) in which 59 postmenopausal female subjects were randomized to either the exercise group (n?=?29) or the control group (n?=?30). The subjects in the exercise group were instructed to perform home-based exercises using a bench step at the anaerobic threshold (AT), with a goal of performing ≥140 min/week at home for 12 weeks. The subjects in the control group were instructed to not change their normal lifestyle. Urine was collected after overnight fasting, and the urine pH was measured using a urinary test strip. The inter-group-differences at baseline and the pre-post changes within groups were assessed using the Mann-Whitney U test and Wilcoxon’s signed-rank test, respectively. Additionally, the difference in the post-intervention urine pH levels of the two groups, adjusted for the pre-intervention values (the estimated effect size) and the precision (95% confidence intervals) were investigated using an analysis of covariance.

Results

The pre-post comparison of the urine pH data using Wilcoxon’s signed-rank test showed a significant increase in the urine pH levels of the exercise group (p?<?0.05); there was no significant change in the urine pH levels of the control group. However, the estimated effect size (0.15) was small and the confidence interval straddled 0 (?0.25–0.55).

Conclusions

Based on the results of the current secondary analysis of an RCT, we could not clearly conclude that exercise has a beneficial effect on the urine pH. Further well-designed RCTs should be conducted to determine whether aerobic exercise is truly able to ameliorate urine acidification.

Trial registration

The study was retrospectively registered in the University Hospital Medical Information Network (UMIN) as “Effect of step exercise on aerobic fitness and progression of atherosclerosis in the elderly” under the registration number UMIN 000026743 (the date of registration: March 28, 2017).

     

Beyond Google: Bibliographic Transformation to Connect Users to Good Content

ABSTRACT

At the 2017 North Carolina Serials Conference, keynote speaker Regina Romano Reynolds—Director, U.S. ISSN Center and Head, ISSN Section at the Library of Congress—explored how bibliographic transformation can connect users to good-quality content. Offering examples of current and potential serials management projects, Reynolds shared her vision for breaking down information silos, experimenting in the resource management space, and the need for visionary leadership.     

Penalised spline estimation for generalised partially linear single-index models

Generalised linear models are frequently used in modeling the relationship of the response variable from the general exponential family with a set of predictor variables, where a linear combination of predictors is linked to the mean of the response variable. We propose a penalised spline (P-spline) estimation for generalised partially linear single-index models, which extend the generalised linear models to include nonlinear effect for some predictors. The proposed models can allow flexible dependence on some predictors while overcome the “curse of dimensionality”. We investigate the P-spline profile likelihood estimation using the readily available R package mgcv, leading to straightforward computation. Simulation studies are considered under various link functions. In addition, we examine different choices of smoothing parameters. Simulation results and real data applications show effectiveness of the proposed approach. Finally, some large sample properties are established.     

The expected bit complexity of the von Neumann rejection algorithm

In 1952, von Neumann introduced the rejection method for random variate generation. We revisit this algorithm when we have a source of perfect bits at our disposal. In this random bit model, there are universal lower bounds for generating a random variate with a given density to within an accuracy \(\epsilon \) derived by Knuth and Yao, and refined by the authors. In general, von Neumann’s method fails in this model. We propose a modification that insures proper behavior for all Riemann-integrable densities on compact sets, and show that the expected number of random bits needed behaves optimally with respect to universal lower bounds. In particular, we introduce the notion of an oracle that evaluates the supremum and infimum of a function on any rectangle of \({\mathbb {R}}^{d}\), and develop a quadtree-style extension of the classical rejection method.     

Prior specification of neighbourhood and interaction structure in binary Markov random fields

We formulate a prior distribution for the energy function of stationary binary Markov random fields (MRFs) defined on a rectangular lattice. In the prior we assign distributions to all parts of the energy function. In particular we define priors for the neighbourhood structure of the MRF, what interactions to include in the model, and for potential values. We define a reversible jump Markov chain Monte Carlo (RJMCMC) procedure to simulate from the corresponding posterior distribution when conditioned to an observed scene. Thereby we are able to learn both the neighbourhood structure and the parametric form of the MRF from the observed scene. We circumvent evaluations of the intractable normalising constant of the MRF when running the RJMCMC algorithm by adopting a previously defined approximate auxiliary variable algorithm. We demonstrate the usefulness of our prior in two simulation examples and one real data example.     

Parallel and interacting stochastic approximation annealing algorithms for global optimisation

We present the parallel and interacting stochastic approximation annealing (PISAA) algorithm, a stochastic simulation procedure for global optimisation, that extends and improves the stochastic approximation annealing (SAA) by using population Monte Carlo ideas. The efficiency of standard SAA algorithm crucially depends on its self-adjusting mechanism which presents stability issues in high dimensional or rugged optimisation problems. The proposed algorithm involves simulating a population of SAA chains that interact each other in a manner that significantly improves the stability of the self-adjusting mechanism and the search for the global optimum in the sampling space, as well as it inherits SAA desired convergence properties when a square-root cooling schedule is used. It can be implemented in parallel computing environments in order to mitigate the computational overhead. As a result, PISAA can address complex optimisation problems that it would be difficult for SAA to satisfactory address. We demonstrate the good performance of the proposed algorithm on challenging applications including Bayesian network learning and protein folding. Our numerical comparisons suggest that PISAA outperforms the simulated annealing, stochastic approximation annealing, and annealing evolutionary stochastic approximation Monte Carlo.