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In this contribution, a vector-autoregressive (VAR) process with multivariate t-distributed random deviations is incorporated into the Gauss-Helmert model (GHM), resulting in an innovative adjustment model. This model is versatile since it allows for a wide range of functional models, unknown forms of auto- and cross-correlations, and outlier patterns. Subsequently, a computationally convenient iteratively reweighted least squares method based on an expectation maximization algorithm is derived in order to estimate the parameters of the functional model, the unknown coefficients of the VAR process, the cofactor matrix, and the degree of freedom of the t-distribution. The proposed method is validated in terms of its estimation bias and convergence behavior by means of a Monte Carlo simulation based on a GHM of a circle in two dimensions. The methodology is applied in two different fields of application within engineering geodesy: In the first scenario, the offset and linear drift of a noisy accelerometer are estimated based on a Gauss-Markov model with VAR and multivariate t-distributed errors, as a special case of the proposed GHM. In the second scenario real laser tracker measurements with outliers are adjusted to estimate the parameters of a sphere employing the proposed GHM with VAR and multivariate t-distributed errors. For both scenarios the estimated parameters of the fitted VAR model and multivariate t-distribution are analyzed for evidence of auto- or cross-correlations and deviation from a normal distribution regarding the measurement noise.

Electric arc furnaces (EAFs) represent ∼32% of the world’s steel production and are designed as flexible metallurgical production units. Roughly 80% of these EAFs constitute the main metallurgical ...

This paper describes a specific local search approach to solve a problem arising in logistics which we prove to be NP-hard. The problem is a complex scheduling or vehicle routing problem where we have to schedule the tours of concrete mixer vehicles over a working day from concrete-producing depots to concrete-demanding customers and vice versa. We give a general mixed integer programming model which is too hard to solve for state of the art mixed integer programming optimizers in the case of the usually huge problem instances coming from practice. Therefore we present a certain local search approach to be able to handle huge practical problem instances.

This paper considers the problem of assigning flights to airport gates. We examine the general case in which an aircraft serving a flight may be assigned to different gates for arrival and departure processing and for optional intermediate parking. Restrictions to this assignment include gate closures and shadow restrictions, i.e., the situation in which certain gate assignments may cause the blocking of neighboring gates. The objectives include maximization of the total assignment preference score, minimization of the number of unassigned flights during overload periods, minimization of the number of tows, as well as maximization of the robustness of the resulting schedule with respect to flight delays. We are presenting a simple transformation of the flight-gate scheduling (FGS) problem to a graph problem, i.e., the clique partitioning problem (CPP). The algorithm used to solve the CPP is a heuristic based on the ejection chain algorithm by Dorndorf and Pesch [Dorndorf, U., E. Pesch. 1994. Fast clustering algorithms. ORSA J. Comput. 6 141–153]. This leads to a very effective approach for solving the original problem.

This paper introduces models of robustness in flight gate assignments at airports. We briefly repeat the general flight gate assignment problem and disruptions occurring in airline scheduling. Recovery strategies and robust scheduling are surveyed as the main methods in disruption management. We present a non-robust flight gate assignment model and incorporate two approaches of robustness.

A general rule of thumb for biological conservation obtained from simple models of hypothetical species is that for populations with strong environmental noise moderate increases in habitat size or quality do not substantially reduce extinction risk. However, whether this rule also holds for real species with complex behavior, such as social species with breeding units and reproductive suppression, is uncertain. Here we present a population viability analysis of the alpine marmot Marmota marmota, which displays marked social behavior, i.e. it lives in social groups of up to twenty individuals. Our analysis is based on a long-term field study carried out in the Bavarian Alps since 1982. During the first fifteen years of this study, 687 marmots were individually marked and the movements and fate of 98 dispersing marmots were recorded with radio-telemetry. Thus, in contrast to most other viability analyses of spatially structured populations, good data about dispersal exist. A model was constructed which is individual-based, spatially explicit at the scale of clusters of neighbouring territories, and spatially implicit at larger scales. The decisive aspect of marmot life history, winter mortality, is described by logistic regression where mortality is increased by age and the severity of winter, and decreased by the number of subdominant individuals present in a group. Model predictions of group size distribution are in good agreement with the results of the field study. The model shows that the effect of sociality on winter mortality is very effective in buffering environmental harshness and fluctuations. This underpins theoretical results stating that the appropriate measure of the strength of environmental noise is the ratio between the variance of population growth rate and the intrinsic rate of increase. The lessons from our study for biological conservation are that simple, unstructured models may not be sufficient to assess the viability of species with complex behavioral traits, and that even moderate increases in habitat capacity may substantially reduce extinction risk even if environmental fluctuations seem high.

Objective - The expression of intercellular adhesion molecule-3 (ICAM-3), a member of the Ig supergene family, is restricted to immune competent cells. Expression of soluble and cell surface ICAM-3 (s- and c-ICAM-3) is preferentially seen in the state of low activation of the immune system. We studied the relevance of the expression levels of sand c-ICAM-3 in cerebrospinal fluid (CSF) and blood as markers for disease activity as well as the influence of high-dose methylprednisolone (MP) treatment upon the expression of s- and c-ICAM-3 in blood of patients with multiple sclerosis (MS). Materials and methods - A total of 33 patients (relapses n = 25, remission n = 8) with relapsing-remitting MS were included into the study. CSF and blood were acquired from all of them. Of the patients 24 were treated with high-dose MP. In those, blood was additionally collected at the 10th day of the therapy and after 3 months. Expression of c-ICAM-3 was determined by two colour FACS analysis, whereas the concentration levels of s-ICAM-3 were measured by ELISA, Results - In CSF we detected a significant decrease of the expression levels of c-ICAM-3 on CD3 + T cells in 25 patients suffering from an acute relapse in contrast to 8 patients with remission (P=0.04). In comparison to the levels before treatment and after 3 months, at the 10th day of MP treatment we obtained highly significant changes of the expression values of c-ICAM-3 both on CD3 + T cells (P=0.0004; P=0.005) and CD14 + monocytes/macrophages (P=0.0006; P=0.008) on the 10th day of high-dose MP treatment from 24 MS patients. Conclusion - The increase of ICAM-3 levels might indicate the antiinflammatory effect of the MP treatment. It could be interesting to search for similar effects investigating the new immune modulatoring therapy forms of MS.

Eight carriers of the A3243G mutation of mitochondrial DNA without stroke-like episodes were monitored for up to 7 years in clinical and metabolic studies, by magnetic resonance imaging (MRI) and positron emission tomography (PET). None developed mitochondrial encephalopathy (MELAS), but 2 developed diabetes mellitus, 1 terminal kidney failure and 2 cardiomyopathy. One patient improved markedly under ubiquinone. Electroencephalography showed progressive slowing in 2 cases, but electrophysiological tests and MRI were otherwise noncontributary. PET showed widespread cortical and basal ganglion metabolic deficits in 6 cases. We conclude that internal medical complications are more common than MELAS in adult carriers of the mutation. PET findings, firstly reported in such patients, suggest that chronic subclinical encephalopathy is very frequent, and PET may play a role in monitoring in the future. Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG-geförderten) Allianz- bzw. Nationallizenz frei zugänglich.