High-Definition Optical Coherence Tomography for the in vivo Detection of Demodex Mites

Background: Demodex mites are involved in different skin diseases and are commonly detected by skin scrape tests or superficial biopsies. A new high-definition optical coherence tomography (HD-OCT) with high lateral and axial resolution in a horizontal (en-face) and vertical (slice) imaging mode might offer the possibility of noninvasive and fast in vivo examination of demodex mites. Methods: Twenty patients with demodex-related skin diseases and 20 age- and gender-matched healthy controls were examined by HD-OCT. Mites per follicle and follicles per field of view were counted and compared to skin scrape tests. Results: HD-OCT images depicted mites in the en-face mode as bright round dots in groups of 3-5 mites per hair follicle. In the patients with demodex-related disease, a mean number of 3.4 mites per follicle were detected with a mean number of 2.9 infested follicles per area of view compared to a mean of 0.6 mites in 0.4 infested follicles in the controls. The skin scrape tests were negative in 21% of the patients. Conclusion: The innovative HD-OCT enables fast and noninvasive in vivo recognition of demodex mites and might become a useful tool in the diagnosis and treatment monitoring of demodex-related skin diseases. Copyright (C) 2012 S. Karger AG, Base

Stability of Intercelular Exchange of Biochemical Substances Affected by Variability of Environmental Parameters

Communication between cells is realized by exchange of biochemical substances. Due to internal organization of living systems and variability of external parameters, the exchange is heavily influenced by perturbations of various parameters at almost all stages of the process. Since communication is one of essential processes for functioning of living systems it is of interest to investigate conditions for its stability. Using previously developed simplified model of bacterial communication in a form of coupled difference logistic equations we investigate stability of exchange of signaling molecules under variability of internal and external parameters.Comment: 11 pages, 3 figure

A New Multi-objective Solution Approach Using ModeFRONTIER and OpenTrack for Energy-Efficient Train Timetabling Problem

Trains move along the railway infrastructure according to specific timetables. The timetables are based on the running time calculation and they are usually calculated without considering explicitly energy consumption. Since green transportation is becoming more and more important from environmental perspectives, energy consumption minimization could be considered also in timetable calculation. In particular, the Energy-Efficient Train Timetabling Problem (EETTP) consists in the energy-efficient timetable calculation considering the trade-off between energy efficiency and running times. In this work, a solution approach to solve a multi-objective EETTP is described in which the two objectives are the minimization of both energy consumption and the total travel time. The approach finds the schedules to guarantee that the train speed profiles minimize the objectives. It is based on modeFRONTIER and OpenTrack that are integrated by using the OpenTrack Application Programming Interface in a modeFRONTIER workflow. In particular, the optimization is made by modeFRONTIER, while the calculation of the train speed profiles, energy consumption and total travel time is made by OpenTrack. The approach is used with Multi-objective Genetic Algorithm-II and the Non-dominating Sorting Genetic-II, which are two genetic algorithms available in modeFRONTIER. The solution approach is tested on a case study that represents a real situation of metro line in Turkey. For both algorithms, a Pareto Front of solution which are a good trade-off between the objectives are reported. The results show significant reduction of both energy consumption and total travel time with respect to the existing timetable

The Metal-Insulator Transition of NbO2: an Embedded Peierls Instability

Results of first principles augmented spherical wave electronic structure calculations for niobium dioxide are presented. Both metallic rutile and insulating low-temperature NbO2, which crystallizes in a distorted rutile structure, are correctly described within density functional theory and the local density approximation. Metallic conductivity is carried to equal amounts by metal t_{2g} orbitals, which fall into the one-dimensional d_parallel band and the isotropically dispersing e_{g}^{pi} bands. Hybridization of both types of bands is almost negligible outside narrow rods along the line X--R. In the low-temperature phase splitting of the d_parallel band due to metal-metal dimerization as well as upshift of the e_{g}^{pi} bands due to increased p-d overlap remove the Fermi surface and open an optical band gap of about 0.1 eV. The metal-insulator transition arises as a Peierls instability of the d_parallel band in an embedding background of e_{g}^{pi} electrons. This basic mechanism should also apply to VO2, where, however, electronic correlations are expected to play a greater role due to stronger localization of the 3d electrons.Comment: 4 pages, revtex, 6 eps figures, additional material avalable at http://www.physik.uni-augsburg.de/~eyert

On intermediate subfactors of Goodman-de la Harpe-Jones subfactors

In this paper we present a conjecture on intermediate subfactors which is a generalization of Wall's conjecture from the theory of finite groups. Motivated by this conjecture, we determine all intermediate subfactors of Goodman-Harpe-Jones subfactors, and as a result we verify that Goodman-Harpe-Jones subfactors verify our conjecture. Our result also gives a negative answer to a question motivated by a conjecture of Aschbacher-Guralnick.Comment: To appear in Comm. Math. Phy

Explaining Deep Learning Time Series Classification Models using a Decision Tree

This preliminary study proposes a new post hoc method to explain deep learning-based time series classification models using a decision tree. Our approach generates a decision tree graph or rulesets as an explanation, improving interpretability compared to saliency map-based methods. The method involves two phases: training and evaluating the deep learning-based time series classification model and extracting prototypical events from the evaluation set to train the decision tree classifier. We conducted experiments on artificial and real datasets, evaluating the explanations based on accuracy, fidelity, number of nodes, and depth. Our preliminary findings suggest that our post-hoc method improves the interpretability and trust of complex time series classification models.https://arrow.tudublin.ie/cddpos/1018/thumbnail.jp

Acting Locally in a Flat World: Global Citizenship and the Democratic Practice of Service-Learning

This paper series seems especially significant this year, as Campus Compact celebrates an important milestone. The context has certainly changed over the decades since the founding of Campus Compact twenty years ago. For while Campus Compact has grown impressively to more than 950 member campuses with 31 state offices under the leadership of Elizabeth Hollander, there is also a sense that service-learning is at a crossroads. At least one dimension for educators to consider is the connection between the local and the global, and the importance of global citizenship and democratic practices which promote global citizenship. To be engaged and relevant requires that service-learning includes a large vision, along with democratic practices for acting locally with global intentions. The flattened world which Thomas Friedman has popularly termed for the rapid rise of globalization since the start of the 21st century has important implications for service-learning educators trying to implement John Dewey\u27s vision of building democratic, neighborly communities. It requires us to ask: if democracy begins at home, what does this mean in the context of an increasingly global society