Die gesellschaftliche Seite des Phänomens AD(H)S

Der Beitrag beschäftigt sich mit dem Phänomen der Aufmerksamkeitsdefizit-/Hyperaktivitätsstörung AD(H)S. Er zeigt die Schwierigkeit auf, den Begriff zu definieren und die Vielfalt der Ursachen dieser Störung zu bestimmen. Nebst einem Erklärungsansatz, der sich in den psychiatrischen Wissenschaften etabliert hat, wird auch auf die sonst weniger beleuchtete gesellschaftliche Sichtweise des Phänomens eingegangen. Anhand empirischer Befunde aus den Sozialwissenschaften sowie einer Gesellschaftstheorie werden mögliche Konsequenzen für die Praxis diskutiert

Was Pflegefachpersonen erwarten, um langfristig im Beruf zu bleiben

Auch einige Jahre nach Ausbildungsabschluss will die Mehrheit der Pflegefachpersonen langfristig im Beruf bleiben. Dies zeigen Ergebnisse der dritten Befragungswelle einer nationalen Längsschnittstudie zum Berufseinstieg des Abschlussjahrgangs 2011/2012. Damit dies Wirklichkeit bleibt, erwarten sie aber Verbesserungen der Rahmenbedingungen

Digital maturity variables and their impact on the enterprise architecture layers

This study examines the variables of digital maturity of companies. The framework for enterprise architectures Archimate 3.0 is used to compare the variables. The variables are assigned to the six layers of architecture: Strategy, Business Environment, Applications, Technology, Physical and Implementation and Migration. On the basis of a literature overview, 15 “digital maturity models” with a total of 147 variables are analyzed. The databases Scopus, EBSCO – Business Source Premier and ProQuest are used for this purpose

Service Systems, Smart Service Systems and Cyber- Physical Systems—What’s the difference? Towards a Unified Terminology

As businesses and their networks transform towards co-creation, several concepts describing the resulting systems emerge. During the past years, we can observe a rise of the concepts Service Systems, Smart Service Systems and Cyber-Physical Systems. However, distinct definitions are either very broad or contradict each other. As a result, several characteristics appear around these terms, which also miss distinct allocations and relationships to the underlying concepts. Previous research only describes these concepts and related characteristics in an isolated manner. Thus, we perform an inter-disciplinary structured literature review to relate and define the concepts of Service Systems, Smart Service Systems and Cyber-Physical Systems as well as related characteristics. This article can, therefore, serve as a basis for future research endeavors as it delivers a unified terminology

FABIAN-variant: predicting the effects of DNA variants on transcription factor binding.

While great advances in predicting the effects of coding variants have been made, the assessment of non-coding variants remains challenging. This is especially problematic for variants within promoter regions which can lead to over-expression of a gene or reduce or even abolish its expression. The binding of transcription factors to the DNA can be predicted using position weight matrices (PWMs). More recently, transcription factor flexible models (TFFMs) have been introduced and shown to be more accurate than PWMs. TFFMs are based on hidden Markov models and can account for complex positional dependencies. Our new web-based application FABIAN-variant uses 1224 TFFMs and 3790 PWMs to predict whether and to which degree DNA variants affect the binding of 1387 different human transcription factors. For each variant and transcription factor, the software combines the results of different models for a final prediction of the resulting binding-affinity change. The software is written in C++ for speed but variants can be entered through a web interface. Alternatively, a VCF file can be uploaded to assess variants identified by high-throughput sequencing. The search can be restricted to variants in the vicinity of candidate genes. FABIAN-variant is available freely at https://www.genecascade.org/fabian/

Analyzing land use change to identify migration corridors of African elephants (Loxodonta africana) in the Kenyan-Tanzanian borderlands

Context: East African ecosystems are characterized by the migrations of large herbivores that are highly vulnerable to the recent development of anthropogenic land use change. Objectives: We analyzed land cover changes in the Kenyan-Tanzanian borderlands of the greater Amboseli ecosystem to evaluate landscape connectivity using African elephants as an indicator species. Methods: We used multi-temporal Landsat imagery and a post classification approach to monitor land cover changes over a 43-year period. GIS based methods were accompanied by a literature review for spatial data on land cover changes and elephant migrations. Results:Land cover changed considerably between 1975 and 2017. Wood- and bushlands declined by 16.3% while open grasslands increased throughout the study region (+10.3%). Agricultural expansion was observed (+12.2%) occupying important wildlife habitats and narrowing migration corridors. This development has led to the isolation of Nairobi National Park which was previously part of a large contiguous ecosystem. Eight migration corridors were identified of which only one is formally protected. Two others are almost completely blocked by agriculture and three are expected to become endangered under continuing land use changes. Conclusions: Landscape connectivity is still viable for this ecosystem (except for Nairobi National Park). However, the current situation is very fragile as anthropogenic land use changes are threatening most of the identified large mammal migration corridors. Sustainable land use planning with regard to important wildlife habitats and connecting corridors is a crucial task for further conservation work to safeguard a viable future for wildlife populations in the Kenyan-Tanzanian borderlands

QCD Anderson transition with overlap valence quarks on a twisted-mass sea

In this work we probe the QCD Anderson transition by studying spectral distributions of the massless overlap operator on gauge configurations created by the twisted mass at finite temperature collaboration (tmfT) with 2+1+1 flavors of dynamical quarks and the Iwasaki gauge action. We assess finite-size and discretization effects by considering two different lattice spacings and several physical volumes, and mimic the approach to the continuum limit through stereographic projection. Fitting the inflection points of the participation ratios of the overlap Dirac eigenmodes, we obtain estimates of the temperature dependence of the mobility edge, below which quark modes are localized. We observe that it is well-described by a quadradic polynomial and systematically vanishes at temperatures below the pseudo-critical one of the chiral transition. In fact, our best estimates within errors overlap with that of the chiral phase transition temperature of QCD in the chiral limit.Comment: 13 pages, 16 figure

Enabling Inter-organizational Analytics in Business Networks Through Meta Machine Learning

Successful analytics solutions that provide valuable insights often hinge on the connection of various data sources. While it is often feasible to generate larger data pools within organizations, the application of analytics within (inter-organizational) business networks is still severely constrained. As data is distributed across several legal units, potentially even across countries, the fear of disclosing sensitive information as well as the sheer volume of the data that would need to be exchanged are key inhibitors for the creation of effective system-wide solutions -- all while still reaching superior prediction performance. In this work, we propose a meta machine learning method that deals with these obstacles to enable comprehensive analyses within a business network. We follow a design science research approach and evaluate our method with respect to feasibility and performance in an industrial use case. First, we show that it is feasible to perform network-wide analyses that preserve data confidentiality as well as limit data transfer volume. Second, we demonstrate that our method outperforms a conventional isolated analysis and even gets close to a (hypothetical) scenario where all data could be shared within the network. Thus, we provide a fundamental contribution for making business networks more effective, as we remove a key obstacle to tap the huge potential of learning from data that is scattered throughout the network.Comment: Preprint, forthcoming at Information Technology and Managemen