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The dynamics of external contributions to the geomagnetic field is investigated by applying time-frequency methods to magnetic observatory data. Fractal models and multiscale analysis enable obtaining maximum quantitative information related to the short-term dynamics of the geomagnetic field activity. The stochastic properties of the horizontal component of the transient external field are determined by searching for scaling laws in the power spectra. The spectrum fits a power law with a scaling exponent β, a typical characteristic of self-affine time-series. Local variations in the power-law exponent are investigated by applying wavelet analysis to the same time-series. These analyses highlight the self-affine properties of geomagnetic perturbations and their persistence. Moreover, they show that the main phases of sudden storm disturbances are uniquely characterized by a scaling exponent varying between 1 and 3, possibly related to the energy contained in the external field. These new findings suggest the existence of a long-range dependence, the scaling exponent being an efficient indicator of geomagnetic activity and singularity detection. These results show that by using magnetogram regularity to reflect the magnetosphere activity, a theoretical analysis of the external geomagnetic field based on local power-law exponents is possible.
In this paper, we determine necessary and sufficient conditions for Bruck-Reilly and generalized Bruck-Reilly ∗-extensions of arbitrary monoids to be regular, coregular and strongly π-inverse. These semigroup classes have applications in various field of mathematics, such as matrix theory, discrete mathematics and p-adic analysis (especially in operator theory). In addition, while regularity and coregularity have so many applications in the meaning of boundaries (again in operator theory), inverse monoids and Bruck-Reilly extensions contain a mixture fixed-point results of algebra, topology and geometry within the purposes of this journal.
The genetic code is degenerate; thus, protein evolution does not uniquely determine the coding sequence. One of the puzzles in evolutionary genetics is therefore to uncover evolutionary driving forces that result in specific codon choice. In many bacteria, the first 5-10 codons of protein-coding genes are often codons that are less frequently used in the rest of the genome, an effect that has been argued to arise from selection for slowed early elongation to reduce ribosome traffic jams. However, genome analysis across many species has demonstrated that the region shows reduced mRNA folding consistent with pressure for efficient translation initiation. This raises the possibility that unusual codon usage is a side effect of selection for reduced mRNA structure. Here we discriminate between these two competing hypotheses, and show that in bacteria selection favours codons that reduce mRNA folding around the translation start, regardless of whether these codons are frequent or rare. Experiments confirm that primarily mRNA structure, and not codon usage, at the beginning of genes determines the translation rate.
TRAPID
(2013)
Transcriptome analysis through next-generation sequencing technologies allows the generation of detailed gene catalogs for non-model species, at the cost of new challenges with regards to computational requirements and bioinformatics expertise. Here, we present TRAPID, an online tool for the fast and efficient processing of assembled RNA-Seq transcriptome data, developed to mitigate these challenges. TRAPID offers high-throughput open reading frame detection, frameshift correction and includes a functional, comparative and phylogenetic toolbox, making use of 175 reference proteomes. Benchmarking and comparison against state-of-the-art transcript analysis tools reveals the efficiency and unique features of the TRAPID system. TRAPID is freely available at http://bioinformatics.psb.ugent.be/webtools/trapid/.
Growing out of the crisis
(2013)
Greece’s currently planned institutional reforms will help to get the country going with limited economic growth. With an economy based primarily on tourism, trade, and agriculture, Greece lacks an established competitive industry and an innovation-friendly environment, resulting in a low export ratio given the small size of the country and its long-time EU-membership. Instead, Greece exports only its nation's talent, with low returns. To become prosperous, the country must better capitalize on its Eurozone membership and add innovative sectors to its economic structure. Given Greece's hidden assets, such as the attractiveness of the country, a small number of strong research centers and an impressive diaspora in research, finance and business, we envision a Greek “Silicon Valley” and propose a ten point policy plan to achieve that goal.
Background: The linear noise approximation (LNA) is commonly used to predict how noise is regulated and exploited at the cellular level. These predictions are exact for reaction networks composed exclusively of first order reactions or for networks involving bimolecular reactions and large numbers of molecules. It is however well known that gene regulation involves bimolecular interactions with molecule numbers as small as a single copy of a particular gene. It is therefore questionable how reliable are the LNA predictions for these systems.
Results: We implement in the software package intrinsic Noise Analyzer (iNA), a system size expansion based method which calculates the mean concentrations and the variances of the fluctuations to an order of accuracy higher than the LNA. We then use iNA to explore the parametric dependence of the Fano factors and of the coefficients of variation of the mRNA and protein fluctuations in models of genetic networks involving nonlinear protein degradation, post-transcriptional, post-translational and negative feedback regulation. We find that the LNA can significantly underestimate the amplitude and period of noise-induced oscillations in genetic oscillators. We also identify cases where the LNA predicts that noise levels can be optimized by tuning a bimolecular rate constant whereas our method shows that no such regulation is possible. All our results are confirmed by stochastic simulations.
Conclusion: The software iNA allows the investigation of parameter regimes where the LNA fares well and where it does not. We have shown that the parametric dependence of the coefficients of variation and Fano factors for common gene regulatory networks is better described by including terms of higher order than LNA in the system size expansion. This analysis is considerably faster than stochastic simulations due to the extensive ensemble averaging needed to obtain statistically meaningful results. Hence iNA is well suited for performing computationally efficient and quantitative studies of intrinsic noise in gene regulatory networks.
Research indicates that evidence-based policy making is most successful when public administrators refer to diversified information portfolios. With the rising prominence of social media in the last decade, this paper argues that governments can benefit from integrating this publically available, user-generated data through the technique of social media analytics (SMA). There are already several initiatives set up to predict future policy issues, e.g. for the policy fields of crisis mitigation or migrant integration insights. The authors analyse these endeavours and their potential for providing more efficient and effective public policies. Furthermore, they scrutinise the challenges to governmental SMA usage in particular with regards to legal and ethical aspects. Reflecting the latter, this paper provides forward-looking recommendations on how these technologies can best be used for future policy making in a legally and ethically sound manner.
Background: With increasing age neuromuscular deficits (e.g., sarcopenia) may result in impaired physical performance and an increased risk for falls. Prominent intrinsic fall-risk factors are age-related decreases in balance and strength / power performance as well as cognitive decline. Additional studies are needed to develop specifically tailored exercise programs for older adults that can easily be implemented into clinical practice. Thus, the objective of the present trial is to assess the effects of a fall prevention program that was developed by an interdisciplinary expert panel on measures of balance, strength / power, body composition, cognition, psychosocial well-being, and falls self-efficacy in healthy older adults. Additionally, the time-related effects of detraining are tested.
Methods/Design: Healthy old people (n = 54) between the age of 65 to 80 years will participate in this trial. The testing protocol comprises tests for the assessment of static / dynamic steady-state balance (i.e., Sharpened Romberg Test, instrumented gait analysis), proactive balance (i.e., Functional Reach Test; Timed Up and Go Test), reactive balance (i.e., perturbation test during bipedal stance; Push and Release Test), strength (i.e., hand grip strength test; Chair Stand Test), and power (i.e., Stair Climb Power Test; countermovement jump). Further, body composition will be analysed using a bioelectrical impedance analysis system. In addition, questionnaires for the assessment of psychosocial (i.e., World Health Organisation Quality of Life Assessment-Bref), cognitive (i.e., Mini Mental State Examination), and fall risk determinants (i.e., Fall Efficacy Scale -International) will be included in the study protocol. Participants will be randomized into two intervention groups or the control / waiting group. After baseline measures, participants in the intervention groups will conduct a 12-week balance and strength / power exercise intervention 3 times per week, with each training session lasting 30 min. (actual training time). One intervention group will complete an extensive supervised training program, while the other intervention group will complete a short version (` 3 times 3') that is home-based and controlled by weekly phone calls. Post-tests will be conducted right after the intervention period. Additionally, detraining effects will be measured 12 weeks after program cessation. The control group / waiting group will not participate in any specific intervention during the experimental period, but will receive the extensive supervised program after the experimental period.
Discussion: It is expected that particularly the supervised combination of balance and strength / power training will improve performance in variables of balance, strength / power, body composition, cognitive function, psychosocial well-being, and falls self-efficacy of older adults. In addition, information regarding fall risk assessment, dose-response-relations, detraining effects, and supervision of training will be provided. Further, training-induced health-relevant changes, such as improved performance in activities of daily living, cognitive function, and quality of life, as well as a reduced risk for falls may help to lower costs in the health care system. Finally, practitioners, therapists, and instructors will be provided with a scientifically evaluated feasible, safe, and easy-to-administer exercise program for fall prevention.
Deutsche Universitäten erweitern ihre E-Learning-Angebote als Service für die Studierenden und Lehrenden. Diese sind je nach Fakultät unterschiedlich ausgeprägt. Dieser Artikel zeigt, wie durch technische Erweiterung der Infrastruktur, einer Anpassung der Organisationsstruktur und einer gezielten Inhaltsentwicklung eine durchgängige und personalisierbare Lehr- und Lernumgebung (Personal Learning Environment, PLE) geschaffen und damit die Akzeptanz bei den Lehrenden und Studierenden für E-Learning erhöht werden kann. Aus der vorausgehenden, systematischen Anforderungsanalyse können Kennzahlen für die Qualitätssicherung von E-Learning-Angeboten abgeleitet werden.