Den etniske dimension i arbejdsmarkedspolitikken

Der anvendes en del ressourcer til aktivering af ledige, herunder ledige medetnisk minoritetsbaggrund

Prediction of Permeability of Realistic and Virtual Layered Nonwovens using Combined Application of X-ray μCT and Computer Simulation

Fundamental understanding of transport properties of fibrous porous media is contingent upon in depth knowledge of their internal structure at the micro-scale. In this work computer simulations are explicitly coupled with X-ray micro-computed tomography (μCT) to investigate the effect of micro-structure on permeability of fibrous media. In order to reach this aim, samples of layered nonwoven fabrics were produced and realistic 3D images of their structure were prepared using X-ray μCT. A series of algorithms was developed to extract micro-structural parameters of fibrous media, including fibers population, orientation and diameter of each fiber as well as the local porosity of structure from high-resolution realistic 3D images. A Matlab-based program capable of producing fibrous structures with various fiber diameters, porosities, thicknesses and 3D fiber orientations was developed. The obtained parameters from μCT images were then implemented into the simulation code to generate virtual fibrous structures. Prediction of permeability in realistic and virtual structures was done by fluid flow simulation through the micro-structure of porous media. The results indicated that both through- and in-plane permeabilities are strongly dependent on the porosity of structure. It was established that the anisotropic nature of the geometry creates anisotropic permeability, with a ratio of 1.8. The anisotropy effect was found to be more profound at higher porosity values. Comparison of numerical results with experimentally obtained data and those of empirical, analytical, numerical, and experimental models were made. Considering the porosity of structures, acceptable agreement between the results and previously published findings was observed

Teaching Medical Students to Suture: Evaluation of a Modern Medical School Curriculum

Background: Medical students are traditionally introduced to suturing in a simulated environment using animal products or synthetic materials. However, there is little evidence to support this pedagogy. Our study explored whether a modern suturing curriculum adequately prepares medical students and examined   student preference for learning suturing skills.   Methods: Suturing performance was recorded and assessed by expert raters. Students also completed a survey that inquired about self-perceived knowledge and confidence in suturing, and preferred pedagogical methods.   Results: The majority (79%) of students that completed our suturing curriculum demonstrated competence in basic suturing techniques. There was no correlation between objective abilities and self-perceived knowledge or confidence. Students reported being significantly more confident suturing anesthetized patients and in simulated environments. Students reported a desire for earlier introduction to suturing and more frequent simulation training.   Conclusion: A modern medical school suturing curriculum, comprising online modules and in-person simulation-based learning, adequately develops basic suturing techniques

Are Long-Range Structural Correlations Behind the Aggregration Phenomena of Polyglutamine Diseases?

We have characterized the conformational ensembles of polyglutamine peptides of various lengths (ranging from to ), both with and without the presence of a C-terminal polyproline hexapeptide. For this, we used state-of-the-art molecular dynamics simulations combined with a novel statistical analysis to characterize the various properties of the backbone dihedral angles and secondary structural motifs of the glutamine residues. For (i.e., just above the pathological length for Huntington's disease), the equilibrium conformations of the monomer consist primarily of disordered, compact structures with non-negligible -helical and turn content. We also observed a relatively small population of extended structures suitable for forming aggregates including - and -strands, and - and -hairpins. Most importantly, for we find that there exists a long-range correlation (ranging for at least residues) among the backbone dihedral angles of the Q residues. For polyglutamine peptides below the pathological length, the population of the extended strands and hairpins is considerably smaller, and the correlations are short-range (at most residues apart). Adding a C-terminal hexaproline to suppresses both the population of these rare motifs and the long-range correlation of the dihedral angles. We argue that the long-range correlation of the polyglutamine homopeptide, along with the presence of these rare motifs, could be responsible for its aggregation phenomena

Enhanced Conformational Sampling using Replica Exchange with Collective-Variable Tempering

The computational study of conformational transitions in RNA and proteins with atomistic molecular dynamics often requires suitable enhanced sampling techniques. We here introduce a novel method where concurrent metadynamics are integrated in a Hamiltonian replica-exchange scheme. The ladder of replicas is built with different strength of the bias potential exploiting the tunability of well-tempered metadynamics. Using this method, free-energy barriers of individual collective variables are significantly reduced compared with simple force-field scaling. The introduced methodology is flexible and allows adaptive bias potentials to be self-consistently constructed for a large number of simple collective variables, such as distances and dihedral angles. The method is tested on alanine dipeptide and applied to the difficult problem of conformational sampling in a tetranucleotide

A model for integrating social network's data and enterprise information systems

Nowadays c become part of our life and using them for different purposes such as communities and business finds value. Using power of social network websites in business and enterprise become a dramatic value and made integration of existing Enterprise Information System (EIS) with social networks to use its data value a challenge and new requirement from enterprises. This study investigate on data and it‘s format of social networks beside type and structure of EIS in different level and integration methods to purpose a proper model for integrating them. Next, after comparing different integration strategy and integration technologies besides conducting questionnaire from few companies, Extract, Transform and Load (ETL) technology has been chosen as the main concept to propose Social Network Extract, Transform and Load (SNETL) model. This model can use to enhance an ETL framework for integrating existing EIS functionality and Social Networks in data repository level based on Enterprise requirement by integration project‘s team. Finally, this study used SNETL Model to enhance Talend Open Studio (TOS) as an ETL framework with developing an example Input and Output module to integrate Facebook news and the number of its comments and likes as a social network data Example and news submission in SugarCRM as an EIS example