Interferometer for cold neutrons

Design and setup of an interferometer for cold and ultracold neutrons are described. As neutron optical components three holographically produced gratings are arranged in triple Laue geometry. The gratings are adjusted during their recording process in photosensitized polymer slabs once for ever. Employing this device we measured the coherence function of a cold neutron beam by means of interferometry.     

Quantenprogrammiersprachen

Algorithmen für Quantenrechner wie der Faktorisierungsalgorithmus von Shor lassen sich mittels neuer Programmiersprachen formulieren, die neben konventionellen auch über für Quantenrechner spezifische Sprachkonstrukte verfügen. In Verbindung mit Simulatoren kann man so auch bereits heute Programme für Quantenrechner entwickeln und testen.     

Computing the update of the repeated median regression line in linear time

The repeated median line estimator is a highly robust method for fitting a regression line to a set of n data points in the plane. In this paper, we consider the problem of updating the estimate after a point is removed from or added to the data set. This problem occurs, e.g., in statistical online monitoring, where the computational effort is often critical. We present a deterministic algorithm for the update working in O(n) time and O(n²) space.     

A Tractable Class of Maximal Hedging Policies in Multi-Part Manufacturing Systems

The flow control problem in multi-part failure prone manufacturing systems is considered. While computationnaly attractive, the near optimal controllers of Caramanis and Sharifnia, suffer from the drawback that the production capacity set must be approximated via a very restricted set of inscribed hypercubes, namely those for which a componentwise feasibility requirement is satisfied. Also, due to the completely decoupled nature of production along each component, utilization of the restricted capacity set is suboptimal. A class of capacity set incribed hypercube policies called simple maximal hedging (SMH) policies is introduced. In SMH policies production levels along the various components of the capacity set are coupled, the componentwise feasibility requirement is lifted, and there is no underutilization of production capacity if needed. In a p part types manufacturing system, for partwise additive cost functionals, it is shown that performance evaluation of a given SMH policy reduces to the analysis of p decoupled (fictitious) semi-Markovian machines. The machines are Markovianized via first passage-time analysis and a Padé approximants technique. Numerical optimization over the class of SMH policies in a sample manufacturing system indicates that their performance can come close to that of the optimal control.     

Microscopy under pressure--an optical chamber system for fluorescence microscopic analysis of living cells under high hydrostatic pressure

High hydrostatic pressure (HHP) becomes more and more interesting for life science research, since it can be employed to inactivate various cells. To directly monitor "cells under pressure," the development of an optical high-pressure chamber is required. Therefore, an optical pressure chamber that can be used for up to 300 MPa was constructed. This chamber has already been described as a tool for in situ observation of dynamic changes of microscopic structures in bright field as well as phase contrast. In combination with an inverted microscope, we obtained brilliant microscopic color pictures with an optical resolution more than 0.56 microm. Here, we demonstrate the capabilities of the HHP cell, in combination with epifluorescence microscopy. Using a nonadherent human B-cell line (Raji, ATCC CCL 86), stained with the fluorescent dyes propidium iodide, Hoechst 33342, or dihexyloxacarbocyanine iodide, we were able to show that the system is suitable to perform fluorescence microscopic analyses, with pressures up to 300 MPa, with viable mammalian cells.     

The PINK1 p.Asn521Thr Variant Is Associated with Earlier Disease Onset in GRN/C9orf72 Frontotemporal Lobar Degeneration

Genetic frontotemporal lobar degeneration (FTLD) is characterized by heterogeneous phenotypic expression, with a disease onset highly variable even in patients carrying the same mutation. Herein we investigated if variants in lysosomal genes modulate the age of onset both in FTLD due to GRN null mutations and C9orf72 expansion. In a total of 127 subjects (n = 74 GRN mutations and n = 53 C9orf72 expansion carriers), we performed targeted sequencing of the top 98 genes belonging to the lysosomal pathway, selected based on their high expression in multiple brain regions. We described an earlier disease onset in GRN/C9orf72 pedigrees in subjects carrying the p.Asn521Thr variant (rs1043424) in PTEN-induced kinase 1 (PINK1), a gene that is already known to be involved in neurodegenerative diseases. We found that: (i) the PINK1 rs1043424 C allele is significantly associated with the age of onset; (ii) every risk C allele increases hazard by 2.11%; (iii) the estimated median age of onset in homozygous risk allele carriers is 10–12 years earlier than heterozygous/wild type homozygous subjects. A replication study in GRN/C9orf72 negative FTLD patients confirmed that the rs1043424 C allele was associated with earlier disease onset (−5.5 years in CC versus A carriers). Understanding the potential mechanisms behind the observed modulating effect of the PINK1 gene in FTLD might prove critical for identifying biomarkers and/or designing drugs to modify the age of onset, especially in GRN/C9orf72-driven disease.     

Sustained Increase in Serum Glial Fibrillary Acidic Protein after First ST-Elevation Myocardial Infarction

Acute ischemic cardiac injury predisposes one to cognitive impairment, dementia, and depression. Pathophysiologically, recent positron emission tomography data suggest astroglial activation after experimental myocardial infarction (MI). We analyzed peripheral surrogate markers of glial (and neuronal) damage serially within 12 months after the first ST-elevation MI (STEMI). Serum levels of glial fibrillary acidic protein (GFAP) and neurofilament light chain (NfL) were quantified using ultra-sensitive molecular immunoassays. Sufficient biomaterial was available from 45 STEMI patients (aged 28 to 78 years, median 56 years, 11% female). The median (quartiles) of GFAP was 63.8 (47.0, 89.9) pg/mL and of NfL 10.6 (7.2, 14.8) pg/mL at study entry 0–4 days after STEMI. GFAP after STEMI increased in the first 3 months, with a median change of +7.8 (0.4, 19.4) pg/mL (p = 0.007). It remained elevated without further relevant increases after 6 months (+11.7 (0.6, 23.5) pg/mL; p = 0.015), and 12 months (+10.3 (1.5, 22.7) pg/mL; p = 0.010) compared to the baseline. Larger relative infarction size was associated with a higher increase in GFAP (ρ = 0.41; p = 0.009). In contrast, NfL remained unaltered in the course of one year. Our findings support the idea of central nervous system involvement after MI, with GFAP as a potential peripheral biomarker of chronic glial damage as one pathophysiologic pathway.     

Information Theory and Neural Networks for Managing Uncertainty in Flood Routing

This paper presents an approach for handling uncertainties arising mainly from ignored or misrepresented processes in physically based models. The approach is based on the application of a parallel artificial neural network (ANN) model that uses state variables, input and output data, and previous model errors at specific time steps to predict the errors of a physically based model. Concepts from information theory are used to discover the relationships between the variables and the model errors, which also serves as a mechanism to detect the predictability of the errors. The resulting information is used to select the best related input data for the error prediction model. The error prediction model is then trained and applied to improve the forecasts made by the physically based model. This approach was applied to a routing model of a 70 km reach of the River Wye, United Kingdom. The results demonstrate that errors from the physically based model show a consistent trend governed by some dynamics of their own, which can be modeled with learning algorithms. Errors were forecasted at different lead times. In all cases the forecasts made by the combined application of both models were more accurate than those made by the physically based model alone. From this it was concluded that, along with proper information analysis techniques, the use of ANN models to predict the forecast errors of physically based models can help to improve significantly the prediction and therefore to reduce the associated uncertainty.     

Automatic image annotation using visual content and folksonomies

Automatic image annotation is an important and challenging task, and becomes increasingly necessary when managing large image collections. This paper describes techniques for automatic image annotation that take advantage of collaboratively annotated image databases, so called visual folksonomies. Our approach applies two techniques based on image analysis: First, classification annotates images with a controlled vocabulary and second tag propagation along visually similar images. The latter propagates user generated, folksonomic annotations and is therefore capable of dealing with an unlimited vocabulary. Experiments with a pool of Flickr images demonstrate the high accuracy and efficiency of the proposed methods in the task of automatic image annotation. Both techniques were applied in the prototypical tag recommender “tagr”.