Implementing collaborative improvement, top-down, bottom-up, or both?

The research presented in this paper was aimed at increasing the current understanding of the process of developing collaborative improvement in Extended Manufacturing Enterprises (EME). Based on action research and action learning of three EMEs involving a total of thirteen companies from five European countries, the present study identifies three different approaches to collaborative improvement (CoI), that is, inter-organisational continuous improvement. One approach to CoI focuses on learning at a practical level, developing this knowledge into strategic and theoretical knowledge. We call this the bottom-up learning-bydoing approach. Another approach focuses on goal alignment and assessment to provide a foundation for improvement before actually improving. We call this the top-down directive approach. Yet another approach focuses on shared goals/vision and meeting on equal terms, and joint work in a non-directive matter. This is the laissez-faire approach. The different approaches influence the collaborative improvement results achieved, and how and why they do so is the question addressed this article

Græsmarksafgrødernes sammensætning – en kompleks sag

Ønsker man at producere mælk med en given sammensætning, er det vigtigt både at fokusere på anvendelsen af forskellige græssorter samt at have fokus på planternes udviklingstrin

Genome sequence of an alphaherpesvirus from a beluga whale (Delphinapterus leucas)

Beluga whale alphaherpesvirus 1 was isolated from a blowhole swab taken from a juvenile beluga whale. The genome is 144,144 bp in size and contains 86 putative genes. The virus groups phylogenetically with members of the genus Varicellovirus in subfamily Alphaherpesvirinae and is the first alphaherpesvirus sequenced from a marine mammal

Phytanic acid stimulates glucose uptake in a model of skeletal muscles, the primary porcine myotubes

BACKGROUND: Phytanic acid (PA) is a chlorophyll metabolite with potentials in regulating glucose metabolism, as it is a natural ligand of the peroxisome proliferator-activated receptor (PPAR) that is known to regulate hepatic glucose homeostasis. This study aimed to establish primary porcine myotubes as a model for measuring glucose uptake and glycogen synthesis, and to examine the impact of physiological amounts of PA on glucose uptake and glycogen synthesis either alone or in combination with insulin. METHODS: Porcine satellite cells were cultured into differentiated myotubes and tritiated 2-deoxyglucose (2-DOG) was used to measure glucose uptake, in relation to PA and 2-DOG exposure times and also in relation to PA and insulin concentrations. The MIXED procedure model of SAS was used for statistical analysis of data. RESULTS: PA increased glucose uptake by approximately 35%, and the presence of insulin further increased the uptake, but this further increase in uptake was non- additive and less pronounced at high insulin concentrations. There was no effect of PA alone on glycogen synthesis, while the insulin stimulation of glycogen was increased by 20% in the presence of PA. PA neither stimulated glucose uptake nor glycogen synthesis in insulin-resistant myotubes generated by excess glucose exposure. CONCLUSIONS: Primary porcine myotubes were established as a model of skeletal muscles for measuring glucose uptake and glycogen synthesis, and we showed that PA can play a role in stimulating glucose uptake at no or inadequate insulin concentrations

Scalable Group Level Probabilistic Sparse Factor Analysis

Many data-driven approaches exist to extract neural representations of functional magnetic resonance imaging (fMRI) data, but most of them lack a proper probabilistic formulation. We propose a group level scalable probabilistic sparse factor analysis (psFA) allowing spatially sparse maps, component pruning using automatic relevance determination (ARD) and subject specific heteroscedastic spatial noise modeling. For task-based and resting state fMRI, we show that the sparsity constraint gives rise to components similar to those obtained by group independent component analysis. The noise modeling shows that noise is reduced in areas typically associated with activation by the experimental design. The psFA model identifies sparse components and the probabilistic setting provides a natural way to handle parameter uncertainties. The variational Bayesian framework easily extends to more complex noise models than the presently considered.Comment: 10 pages plus 5 pages appendix, Submitted to ICASSP 1

Correlated ππ\pi\pi and KKˉK\bar K exchange in the baryon-baryon interaction

A dynamical model for correlated two-pion and two-kaon exchange in the baryon- baryon interaction is presented, both in the scalar-isoscalar ($\sigma$) and the vector-isovector ($\rho$) channel. The correlations between the two pseudoscalar mesons are taken into account by means of $\pi\pi - K\bar K$ amplitudes derived from a meson-exchange model, which is in line with the empirical $\pi\pi$ data. It is found that correlated $K\bar K$ exchange plays an important role in the $\sigma$-channel for baryon-baryon states with non- vanishing strangeness. The strength of correlated $\pi\pi$ plus $K\bar K$ exchange in the $\sigma$-channel decreases with the strangeness of the baryon- baryon system becoming more negative. The results for correlated $\pi\pi$- exchange in the vector-isovector channel deviate from what is expected in the naive SU(3) picture for genuine $\rho$-exchange. Shortcomings of a simplified description in terms of sharp mass $\sigma$- and $\rho$-exchange are pointed out.Comment: 51 pages, Latex file, figures available from [email protected]