An Overview and Categorization of Approaches for Train Timetable Generation

A train timetable is a crucial component of railway transportation systems as it directly impacts the system’s performance and the customer satisfaction. Various approaches can be found in the literature that deal with timetable generation. However, the approaches proposed in the literature differ significantly in terms of the use case for which they are in tended. Differences in objective function, timetable periodicity, and solution methods have led to a confusing number of works on this topic. Therefore, this paper presents a com pact literature review of approaches to train timetable generation. The reviewed papers are briefly summarized and categorized by objective function and periodicity. Special emphasis is given to approaches that have been applied to real-world railway data

A multi-method field experiment to determine local groundwater flow in a glacier forefield

We implemented multiple independent field techniques to determine the direction and velocity of groundwater flow at a specific stream reach in a glacier forefield. Time-lapse experiments were conducted using two electrical resistivity tomography (ERT) lines installed in a cross pattern. A circular array of groundwater tubes was also installed to monitor groundwater flow via discrete salt injections. Both inter-borehole and ERT results confirmed this stream section as a losing reach and enabled quantification of the flow direction. Both techniques yielded advection velocities varying between 5.7 and 21.8 m/day. Estimates of groundwater flow direction and velocity indicated that groundwater infiltrates from the stream nearby and not from the adjacent lateral moraine. Groundwater age estimated from radon concentration measurements supported this hypothesis. Despite uncertainties inherent to each of the methods deployed, the combination of multiple field techniques allowed drawing consistent conclusions about local groundwater flow. We thus regard our multi-method approach as a reliable way to characterize the two-dimensional groundwater flow at sites where more invasive groundwater investigation techniques are difficult to carry out and local heterogeneities can make single measurements unreliable

Identifying predictive features of autism spectrum disorders in a clinical sample of adolescents and adults using machine learning

Diagnosing autism spectrum disorders (ASD) is a complicated, time-consuming process which is particularly challenging in older individuals. One of the most widely used behavioral diagnostic tools is the Autism Diagnostic Observation Schedule (ADOS). Previous work using machine learning techniques suggested that ASD detection in children can be achieved with substantially fewer items than the original ADOS. Here, we expand on this work with a specific focus on adolescents and adults as assessed with the ADOS Module 4. We used a machine learning algorithm (support vector machine) to examine whether ASD detection can be improved by identifying a subset of behavioral features from the ADOS Module 4 in a routine clinical sample of N = 673 high-functioning adolescents and adults with ASD (n = 385) and individuals with suspected ASD but other best-estimate or no psychiatric diagnoses (n = 288). We identified reduced subsets of 5 behavioral features for the whole sample as well as age subgroups (adolescents vs. adults) that showed good specificity and sensitivity and reached performance close to that of the existing ADOS algorithm and the full ADOS, with no significant differences in overall performance. These results may help to improve the complicated diagnostic process of ASD by encouraging future efforts to develop novel diagnostic instruments for ASD detection based on the identified constructs as well as aiding clinicians in the difficult question of differential diagnosis

The low acute effectiveness of a high-power short duration radiofrequency current application technique in pulmonary vein isolation for atrial fibrillation

Background: Application of high power radiofrequency (RF) energy for a short duration (HPSD) to isolate pulmonary vein (PV) is an emerging technique. But power and duration settings are very different across different centers. Moreover, despite encouraging preclinical and clinical data, studies measuring acute effectiveness of various HPSD settings are limited.Methods: Twenty-five consecutive patients with symptomatic atrial fibrillation (AF) were treated with pulmonary vein isolation (PVI) using HPSD. PVI was performed with a contact force catheter (Thermocool SF Smart-Touch) and Carto 3 System. The following parameters were used: energy output 50 W, target temperature 43°C, irrigation 15 mL/min, targeted contact force of > 10 g. RF energy was applied for 6–10 s. Required minimal interlesion distance was 4 mm. Twenty minutes after each successful PVI adenosine provocation test (APT) was performed by administrating 18 mg adenosine to unmask dormant PV conduction.Results: All PVs (100 PVs) were successfully isolated. RF lesions needed per patient were 131 ± 41, the average duration for each RF application was 8.1 ± 1.7 s. Procedure time was 138 ± 21 min and average of total RF energy duration was 16.3 ± 5.2 min and average amount of RF energy was 48209 ± 12808 W. APT application time after PVI was 31.1 ± 8.3 min for the left sided PVs and 22.2 ± 4.6 min (p = 0.005) for the right sided PVs. APT was transiently positive in 18 PVs (18%) in 8 (32%) patients.Conclusions: Pulmonary vein isolation with high power for 6–10 s is feasible and shortens the procedure and ablation duration. However, acute effectiveness of the HPSD seems to be lower than expected. Further studies combining other ablation parameters are needed to improve this promising technique

Osteopontin and Fibronectin Levels Are Decreased in Vitreous of Autoimmune Uveitis and Retinal Expression of Both Proteins Indicates ECM Re-Modeling

Autoimmune uveitis is an intraocular inflammation that arises through autoreactive T-cells attacking the inner eye, eventually leading to blindness. However, the contributing molecular pathomechanisms within the affected tissues remain as yet elusive. The extracellular matrix (ECM) is a highly dynamic structure that varies tremendously and influences the encompassing tissue. In order to assess ECM re-modeling in autoimmune uveitis, we investigated the expression of ECM molecules fibronectin and osteopontin in vitreous and retina samples. This was carried out in the only spontaneous animal model for human autoimmue uveitis, namely equine recurrent uveitis (ERU) that resembles the human disease in clinical as well as in immunopathological aspects. ERU is a naturally occurring autoimmune disease in horses that develops frequently and has already proved its value to study disease-related pathomechanisms. Western blot analysis of fibronectin and osteopontin in healthy and uveitic vitreous revealed significant reduction of both proteins in uveitis. Immunohistochemical expression of fibronectin in healthy retinas was restricted to the inner limiting membrane abutting vimentin positive Müller cell endfeet, while in uveitic sections, a disintegration of the ILM was observed changing the fibronectin expression to a dispersed pattern extending toward the vitreous. Retinal expression of osteopontin in control tissue was found in a characteristic Müller cell pattern illustrated by co-localization with vimentin. In uveitic retinas, the immunoreactivity of osteopontin in gliotic Müller cells was almost absent. The ability of Müller cells to express fibronectin and osteopontin was additionally shown by immunocytochemistry of primary cultured equine Müller cells and the equine Müller cell line eqMC-7. In conclusion, severe ECM re-modeling in autoimmune uveitis reported here, might affect the adhesive function of fibronectin and thus the anchoring of Müller cell endfeet to the ILM. Furthermore, the absence of osteopontin in gliotic Müller cells might represent reduced neuroprotection, an osteopontin attribute that is intensively discussed

Semiconductor laser mode locking stabilization with optical feedback from a silicon PIC

Semiconductor mode-locked lasers can be used in a variety of applications ranging from multi-carrier sources for WDM communication systems to time base references for metrology. Their packaging in compact chip- or module-level systems remains however burdened by their strong sensitivity to back-reflections, quickly destroying the coherence of the mode-locking. Here, we investigate the stabilization of mode-locked lasers directly edge coupled to a silicon photonic integrated circuit, with the objective of moving isolators downstream to the output of the photonic circuit. A 2.77 kHz 3 dB RF linewidth, substantially improved compared to the 15.01 kHz of the free running laser, is obtained in the best case. Even in presence of detrimental reflections from the photonic circuit, substantial linewidth reductions from 20 kHz to 8.82 kHz, from 572 kHz to 14.8 kHz, and from 1.5 MHz to 40 kHz are realized

Quantitative imaging of water, ice and air in permafrost systems through petrophysical joint inversion of seismic refraction and electrical resistivity data

Quantitative estimation of pore fractions filled with liquid water, ice and air is crucial for a process-based understanding of permafrost and its hazard potential upon climate- induced degradation. Geophysical methods offer opportunities to image distributions of permafrost constituents in a non-invasive manner. We present a method to jointly estimate the volumetric fractions of liquid water, ice, air and the rock matrix from seismic refraction and electrical resistivity data. Existing approaches rely on conventional inversions of both data sets and a suitable a priori estimate of the porosity distribution to transform velocity and resistivity models into estimates for the four-phase system, often leading to non-physical results. Based on two synthetic experiments and a field data set from an Alpine permafrost site (Schilthorn, Bernese Alps and Switzerland), it is demonstrated that the developed petrophysical joint inversion provides physically plausible solutions, even in the absence of prior porosity estimates. An assessment of the model covariance matrix for the coupled inverse problem reveals remaining petrophysical ambiguities, in particular between ice and rock matrix. Incorporation of petrophysical a priori information is demonstrated by penalizing ice occurrence within the first two meters of the subsurface where the measured borehole temperatures are positive. Joint inversion of the field data set reveals a shallow air-rich layer with high porosity on top of a lower-porosity subsurface with laterally varying ice and liquid water contents. Non-physical values (e.g. negative saturations) do not occur and estimated ice saturations of 0–50 per cent as well as liquid water saturations of 15–75 per cent are in agreement with the relatively warm borehole temperatures between −0.5  and 3 ° C. The presented method helps to improve quantification of water, ice and air from geophysical observations