Large-scale computational and statistical analyses of high transcription potentialities in 32 prokaryotic genomes

This article compares 32 bacterial genomes with respect to their high transcription potentialities. The σ70 promoter has been widely studied for Escherichia coli model and a consensus is known. Since transcriptional regulations are known to compensate for promoter weakness (i.e. when the promoter similarity with regard to the consensus is rather low), predicting functional promoters is a hard task. Instead, the research work presented here comes within the scope of investigating potentially high ORF expression, in relation with three criteria: (i) high similarity to the σ70 consensus (namely, the consensus variant appropriate for each genome), (ii) transcription strength reinforcement through a supplementary binding site—the upstream promoter (UP) element—and (iii) enhancement through an optimal Shine-Dalgarno (SD) sequence. We show that in the AT-rich Firmicutes’ genomes, frequencies of potentially strong σ70-like promoters are exceptionally high. Besides, though they contain a low number of strong promoters (SPs), some genomes may show a high proportion of promoters harbouring an UP element. Putative SPs of lesser quality are more frequently associated with an UP element than putative strong promoters of better quality. A meaningful difference is statistically ascertained when comparing bacterial genomes with similarly AT-rich genomes generated at random; the difference is the highest for Firmicutes. Comparing some Firmicutes genomes with similarly AT-rich Proteobacteria genomes, we confirm the Firmicutes specificity. We show that this specificity is neither explained by AT-bias nor genome size bias; neither does it originate in the abundance of optimal SD sequences, a typical and significant feature of Firmicutes more thoroughly analysed in our study

Domain specific software architectures: Command and control

GTE is the Command and Control contractor for the Domain Specific Software Architectures program. The objective of this program is to develop and demonstrate an architecture-driven, component-based capability for the automated generation of command and control (C2) applications. Such a capability will significantly reduce the cost of C2 applications development and will lead to improved system quality and reliability through the use of proven architectures and components. A major focus of GTE's approach is the automated generation of application components in particular subdomains. Our initial work in this area has concentrated in the message handling subdomain; we have defined and prototyped an approach that can automate one of the most software-intensive parts of C2 systems development. This paper provides an overview of the GTE team's DSSA approach and then presents our work on automated support for message processing

SDH6 and SDH7 contribute to anchoring succinate dehydrogenase to the inner mitochondrial membrane in arabidopsis thaliana

The succinate dehydrogenase complex (complex II) is a highly conserved protein complex composed of the SDH1 to SDH4 subunits in bacteria and in the mitochondria of animals and fungi. The reason for the occurrence of up to four additional subunits in complex II of plants, termed SDH5 to SDH8, so far is a mystery. Here, we present a biochemical approach to investigate the internal subunit arrangement of Arabidopsis (Arabidopsis thaliana) complex II. Using low-concentration detergent treatments, the holo complex is dissected into subcomplexes that are analyzed by a three-dimensional gel electrophoresis system. Protein identifications by mass spectrometry revealed that the largest subcomplex (IIa) represents the succinate dehydrogenase domain composed of SDH1 and SDH2. Another subcomplex (IIb) is composed of the SDH3, SDH4, SDH6, and SDH7 subunits. All four proteins include transmembrane helices and together form the membrane anchor of complex II. Sequence analysis revealed that SDH3 and SDH4 lack helices conserved in other organisms. Using homology modeling and phylogenetic analyses, we present evidence that SDH6 and SDH7 substitute missing sequence stretches of SDH3 and SDH4 in plants. Together with SDH5, which is liberated upon dissection of complex II into subcomplexes, SDH6 and SDH7 also add some hydrophilic mass to plant complex II, which possibly inserts further functions into this smallest protein complex of the oxidative phosphorylation system (which is not so small in plants)

A qualitative analysis of the networks of tourism SMEs in Germany: managing business networks for knowledge transfer

Theoretically, it is said that social capital encourages individuals and entrepreneurs to engage in business networks. Social capital is the sum of the resource benefits an organisation derives from its network of relationships. These external knowledge sources are particularly relevant for small and medium-sized enterprises (SMEs) because of their lack of internal knowledge stock. Yet, social capital theories have primarily been investigated from a structural perspective to measure benefits through centrality and position in structural holes. To understand the resource benefits, however, it is first necessary to understand what knowledge is available, second the content of the relationship, and third the context and conditions that influence these inter-organisational knowledge transfer relationships. Thus, in this thesis, a relational approach is adopted to generate knowledge on inter-firm relationships at the SME level in order to explore how tourism business networks are operated and managed in such a way that enables the knowledge transfer. This study looks into the business networks in which the SMEs of the tourism industry engage, explains the meaning they ascribe to the knowledge transfer potential among these networks, how they exploit the networks, what knowledge is made available, and the managerial as well as contextual factors that influence the network operation and management. A multi-method qualitative strategy was used to investigate naturally emerging business networks in North-East Germany’s tourism industry. A snowball network sampling procedure was applied, from which two network zones emerged, a closed coordinated small network and the members’ individually built business relationships beyond this network. The research was informed by three rounds of qualitative data generation and collection. In total, 12 first-round interviews were used to enter the field, a second-round workshop and discussion group with 31 participants was used to generate preliminary findings and facilitate access, and in the third round 38 semi-structured qualitative interviews were conducted to generate data for the main empirical study. This qualitative data analysis was complemented and supported with data from informal conversations and observations, collected documents and field notes, as well as a secondary data review. The study contributes to the body of knowledge on tourism SME networks and the availability and transfer of knowledge. Its original contribution is in providing a greater knowledge and understanding of the cognitive and relational component of social capital, particularly in the formation of a network. It further adds to both literature and theory on network coordinators by unpacking and circumscribing their boundaries. The study also theorises the cult of personality in a network context. In addition, it contributes to the understanding of the role of regional tourism organisations (RTO) in that it explored how different strategies lead to a collaborative environment, effective communication and member exchange. Thus, this research contributes to the conversation of SMEs, tourism business networks, coordination, and knowledge transfer

Essays on Frictional Labor Markets and Measurement

This dissertation consists of three works which consider how frictional labor market models align with data, as well as how labor market data should be combined and used in applications of theoretical models. What unifies these essays is the underlying goal to further the consolidation of theoretical labor market models with empirical observations of worker and firm behavior in order to better understand and influence policy. The first essay asks the question: How do changes in the minimum wage affect criminal activity? I answer this question by describing a frictional world in which a worker's criminal actions are linked to his labor market outcomes. The model is calibrated to match labor market outcomes and crime decisions of workers from the National Longitudinal Survey of Youth 1997, and shows that the relationship between the aggregate crime rate and the minimum wage is U-shaped. The results from the calibrated model as well as empirical evidence from county level crime data and state level minimum wage changes from 1995 to 2014 suggest that the crime minimizing minimum to median wage ratio for 16-19 year olds is 0.91. However, the welfare maximizing minimum to median wage ratio is 0.87, not equal to the crime minimizing value.The second essay, joint with Ben Griffy, Bryan Engelhardt and Peter Rupert, asks the question: Is the arrival rate of a job independent of the wage that it pays? We answer this question by testing how, and to what extent, unemployment insurance changes the hazard rate of leaving unemployment across the wage distribution using a Mixed Proportional Hazard Competing Risk Model and data from the 1997 National Longitudinal Survey of Youth. Controlling for worker characteristics we reject that job arrival rates are independent of the wages offered. We apply the results to several prominent job-search models and interpret how our findings are key to determining the efficacy of unemployment insurance.Finally, the third essay, joint with Finn Kydland and Peter Rupert argues that not all hours are created equally. In this paper we present a method for adjusting aggregate hours to account for changes in the quality of hours worked. Average human capital has rapidly increased since 1980 as better educated cohorts enter the workforce and the baby boomers continue to work and gather experience. We construct an aggregate labor input series from 1979 to adjust for changes in the experience and education levels of the workforce using the Current Population Survey's Outgoing Rotation Groups. We show that a decrease in labor productivity beginning in 2004, the "productivity slowdown," is understated by 23 percentage points when using aggregate hours instead of labor input to calculate productivity, and that 80% of the average quarterly growth rate of labor productivity can be attributed to increases in education and experience since 2004

Long-Term Effects of Clinical Intervention: An In-Depth Study

Numerous longitudinal studies attest to the concern regarding the long-term effectiveness of remedial programs (Balow, 1965; Balow & Blomquist, 1965; Buerger, 1968; Muehl &\u27 Forell, 1973; Robinson & Smith, 1962; Shearer, 1966). While short-term improvement has been demonstrated repeatedly, the majority of the reported studies fail to demonstrate maintenance of achievement gains (Spache, 1980). The fact that follow-up studies persist (Bessai & Cozac, 1980; Gottesman, 1979; Ito, 1981; Miles, Foreman & Irwine, 1978) demonstrates an intuitive belief that remedial treatment should have lasting beneficial effects

LET\u27S GET PHYSIC(AI)L – TRANSFORMING AI-REQUIREMENTS OF HEALTHCARE INTO DESIGN PRINCIPLES

As healthcare\u27s digitization advances, artificial intelligence (AI) techniques offer opportunities to improve medical care. In addition to the much-discussed potential in diagnostics, AI-based systems can further support processes in clinics or comparable healthcare facilities, helping to improve medical, organizational, and administrative processes. Nevertheless, apart from single use-cases, AI in healthcare is still not unleashing its full potential. To empower the technology and provide a guideline for developers but also other entities such as medical institutions, we derive and plan to validate design principles guiding the design of AI-based systems specifically operating in clinics and healthcare facilities. In this research in progress study, we conduct the first two phases of the DSR approach by identifying requirements in literature and transforming these into design principles. By doing so, we provide a collection of literature-based design principles that need to be considered when implementing AI-based systems into healthcare contexts