Open Access

Objective We aimed to investigate the proportion of young patients not returning to work (NRTW) at 1 year after ischemic stroke (IS) and during follow-up, and clinical factors associated with NRTW. Methods Patients from the Helsinki Young Stroke Registry with an IS occurring in the years 1994–2007, who were at paid employment within 1 year before IS, and with NIH Stroke Scale score ≤15 points at hospital discharge, were included. Data on periods of payment came from the Finnish Centre for Pensions, and death data from Statistics Finland. Multivariate logistic regression analyses assessed factors associated with NRTW 1 year after IS, and lasagna plots visualized the proportion of patients returning to work over time. Results We included a total of 769 patients, of whom 289 (37.6%) were not working at 1 year, 323 (42.0%) at 2 years, and 361 (46.9%) at 5 years from IS. When adjusted for age, sex, socioeconomic status, and NIH Stroke Scale score at admission, factors associated with NRTW at 1 year after IS were large anterior strokes, strokes caused by large artery atherosclerosis, high-risk sources of cardioembolism, and rare causes other than dissection compared with undetermined cause, moderate to severe aphasia vs no aphasia, mild and moderate to severe limb paresis vs no paresis, and moderate to severe visual field deficit vs no deficit. Conclusions NRTW is a frequent adverse outcome after IS in young adults with mild to moderate IS. Clinical variables available during acute hospitalization may allow prediction of NRTW.

Nitric oxide adsorption on a Au(100) single crystal has been investigated to identify the type of adsorption, the adsorption site, and the orientation and alignment of the adsorbed NO relative to the surface. This was done using a combination of 3D-surface velocity map imaging, near-ambient pressure X-ray photoelectron spectroscopy, and density functional theory. NO was observed to be molecularly adsorbed on gold at ~200 K. Very narrow angular distributions and cold rotational distributions of photodesorbed NO indicate that NO adsorbs on high-symmetry sites on the Au crystal, with the N–O bond axis close to the surface normal. Our density functional theory calculations show that NO preferentially adsorbs on the symmetric bridge (2f) site, which ensures efficient overlap of the NO π* orbital with the orbitals on the two neighbouring Au atoms, and with the N–O bond axis aligned along the surface normal, in agreement with our conclusions from the rotational state distributions. The combination of XPS, which reveals the orientation of NO on gold, with 3D-surface velocity map imaging and density functional theory thus allowed us to determine the adsorption site, orientation and alignment of nitric oxide adsorbed on Au(100).

Agility is considered the silver bullet for survival in the VUCA world. However, many organisations are afraid of endangering their ISO 9001 certificate when introducing agile processes. A joint research project of the University of Applied Sciences and Arts Hannover and the DGQ has set itself the goal of providing more security in this area. The findings were based on interviews with managers and team members from various organisations of different sizes and industries working in an agile manner as well as on common audit practices and a literature analysis. The outcome presents a clear distinction of agility from flexibility as well as useful guidelines for the integration of agile processes in QM systems - for QM practitioners and auditors alike.

Semantic classification of words using distributional features is usually based on the semantic similarity of words. We show on two different datasets that a trained classifier using the distributional features directly gives better results. We use Support Vector Machines (SVM) and Multirelational Matrix Factorization (MRMF) to train classifiers. Both give similar results. However, MRMF, that was not used for semantic classification with distributional features before, can easily be extended with more matrices containing more information from different sources on the same problem. We demonstrate the effectiveness of the novel approach by including information from WordNet. Thus we show, that MRMF provides an interesting approach for building semantic classifiers that (1) gives better results than unsupervised approaches based on vector similarity, (2) gives similar results as other supervised methods and (3) can naturally be extended with other sources of information in order to improve the results.

In distributional semantics words are represented by aggregated context features. The similarity of words can be computed by comparing their feature vectors. Thus, we can predict whether two words are synonymous or similar with respect to some other semantic relation. We will show on six different datasets of pairs of similar and non-similar words that a supervised learning algorithm on feature vectors representing pairs of words outperforms cosine similarity between vectors representing single words. We compared different methods to construct a feature vector representing a pair of words. We show that simple methods like pairwise addition or multiplication give better results than a recently proposed method that combines different types of features. The semantic relation we consider is relatedness of terms in thesauri for intellectual document classification. Thus our findings can directly be applied for the maintenance and extension of such thesauri. To the best of our knowledge this relation was not considered before in the field of distributional semantics.

Background: After kidney transplantation, immunosuppressive therapy causes impaired cellular immune defense leading to an increased risk of viral complications. Trough level monitoring of immunosuppressants is insufficient to estimate the individual intensity of immunosuppression. We have already shown that virus-specific T cells (Tvis) correlate with control of virus replication as well as with the intensity of immunosuppression. The multicentre IVIST01-trial should prove that additional steering of immunosuppressive and antiviral therapy by Tvis levels leads to better graft function by avoidance of over-immunosuppression (for example, viral infections) and drug toxicity (for example, nephrotoxicity). Methods/design: The IVIST-trial starts 4 weeks after transplantation. Sixty-four pediatric kidney recipients are randomized either to a non-intervention group that is only treated conservatively or to an intervention group with additional monitoring by Tvis. The randomization is stratified by centre and cytomegalovirus (CMV) prophylaxis. In both groups the immunosuppressive medication (cyclosporine A and everolimus) is adopted in the same target range of trough levels. In the non-intervention group the immunosuppressive therapy (cyclosporine A and everolimus) is only steered by classical trough level monitoring and the antiviral therapy of a CMV infection is performed according to a standard protocol. In contrast, in the intervention group the dose of immunosuppressants is individually adopted according to Tvis levels as a direct measure of the intensity of immunosuppression in addition to classical trough level monitoring. In case of CMV infection or reactivation the antiviral management is based on the individual CMV-specific immune defense assessed by the CMV-Tvis level. Primary endpoint of the study is the glomerular filtration rate 2 years after transplantation; secondary endpoints are the number and severity of viral infections and the incidence of side effects of immunosuppressive and antiviral drugs. Discussion: This IVIST01-trial will answer the question whether the new concept of steering immunosuppressive and antiviral therapy by Tvis levels leads to better future graft function. In terms of an effect-related drug monitoring, the study design aims to realize a personalization of immunosuppressive and antiviral management after transplantation. Based on the IVIST01-trial, immunomonitoring by Tvis might be incorporated into routine care after kidney transplantation.

The network security framework VisITMeta allows the visual evaluation and management of security event detection policies. By means of a "what-if" simulation the sensitivity of policies to specific events can be tested and adjusted. This paper presents the results of a user study for testing the usability of the approach by measuring the correct completion of given tasks as well as the user satisfaction by means of the system usability scale.

For anomaly-based intrusion detection in computer networks, data cubes can be used for building a model of the normal behavior of each cell. During inference an anomaly score is calculated based on the deviation of cell metrics from the corresponding normality model. A visualization approach is shown that combines different types of diagrams and charts with linked user interaction for filtering of data.

Objective The study’s objective was to assess factors contributing to the use of smart devices by general practitioners (GPs) and patients in the health domain, while specifically addressing the situation in Germany, and to determine whether, and if so, how both groups differ in their perceptions of these technologies. Methods GPs and patients of resident practices in the Hannover region, Germany, were surveyed between April and June 2014. A total of 412 GPs in this region were invited by email to participate via an electronic survey, with 50 GPs actually doing so (response rate 12.1%). For surveying the patients, eight regional resident practices were visited by study personnel (once each). Every second patient arriving there (inclusion criteria: of age, fluent in German) was asked to take part (paper-based questionnaire). One hundred and seventy patients participated; 15 patients who did not give consent were excluded. Results The majority of the participating patients (68.2%, 116/170) and GPs (76%, 38/50) owned mobile devices. Of the patients, 49.9% (57/116) already made health-related use of mobile devices; 95% (36/38) of the participating GPs used them in a professional context. For patients, age (P < 0.001) and education (P < 0.001) were significant factors, but not gender (P > 0.99). For doctors, neither age (P = 0.73), professional experience (P > 0.99) nor gender (P = 0.19) influenced usage rates. For patients, the primary use case was obtaining health (service)-related information. For GPs, interprofessional communication and retrieving information were in the foreground. There was little app-related interaction between both groups. Conclusions GPs and patients use smart mobile devices to serve their specific interests. However, the full potentials of mobile technologies for health purposes are not yet being taken advantage of. Doctors as well as other care providers and the patients should work together on exploring and realising the potential benefits of the technology.

Die folgende Studie befasst sich mit den Auswirkungen der Corona-Pandemie und deren Effekt – ein verminderter CO2-Ausstoß in Deutschland. Für einen übersichtlichen Vergleich wird im weiteren Verlauf in unterschiedlichen Szenarien darauf eingegangen, wie sich der CO2-Ausstoß im Vergleich zu 2020 ohne die Corona-Pandemie in Deutschland verändern könnte. Grundbasis für die Ermittlungen der folgenden Szenarien ist der CO2-Trend ohne die Corona-Pandemie im Jahr 2020, in dem Deutschland das Emissionsziel von -40 % gegenüber 1990 mit einer Reduktion von lediglich 37 % verfehlt hätte. Im zweiten Szenario wird dargestellt, wie sich die aktuelle Corona-Pandemie mit verschiedenen Lockdown-Phasen auf den CO2-Ausstoß auswirkt. Deutlich wird hierbei, dass trotz der aktuellen Maßnahmen eine längere Lockdown-Phase benötigt wird, um das Klimaziel von -40 % langfristig gesichert zu erreichen. In den Szenarien 3 und 4 liegt der Fokus auf möglichen Handlungs- und Verhaltensweisen nach der Pandemie. Das Szenario 3 betrachtet die Folgen von wirtschaftsfördernden Maßnahmen nach dem Lockdown und dem damit einhergehenden CO2-Anstieg. Wie viel CO2 zusätzlich aufgrund von nachhaltigem und klimaorientiertem Verhalten eingespart werden kann, erläutert das Szenario 4 „CO2 Entwicklung unter Berücksichtigung der Corona-Pandemie 2020 und möglicher positiver Umweltentwicklungen aus dem Lockdown“. Faktoren, wie die wachsende Bevölkerung, sich verändernde Produktionsfaktoren oder Umwelteinflüsse wurden vernachlässigt. Die Studie zeigt, dass die Chancen, die durch die wirtschaftlichen Einschnitte und die Verhaltensänderungen, die durch die Corona-Pandemie bzw. deren Folgen hervorgerufen wurden, einen maßgeblichen Einfluss auf den CO2-Ausstoß der Bundesrepublik Deutschland haben können.