Otto-von-Guericke-Universität Magdeburg
  • Magdeburg, Saxony-Anhalt, Germany
Recent publications
This paper presents the graphical results of the Lagrangian-model and the weathering processes associated with oil spills in the tropical South Atlantic, taking into account the meteorological and oceanographic conditions of the study region. The scenarios were created in the Brazilian-NE waters adjacent, with simulation times of 670 h, and densities of 35, 25, and 15API with volume of 1590 m 3 were considered. The main results showed that the meteo-oceanographic characteristics of the study region influence the trajectories and weathering processes in the oil spill. The trajectories varied for each launch point and reached the continent severely in January and October. The associated weathering processes showed higher rates in September and lower rates in April, indicative of the influence of phenomena such as Intertropical Tropical Convergence Zone and warm pool in the South Atlantic region. Sea surface temperature and wind speed are key factors that correlate positively with these months.
In numerical simulations of dispersed multiphase flows by computational fluid dynamics (CFD) methods the most usual assumption is that the particles are spherical. This is however a very crude assumption when considering flows laden with non-spherical particles, such as fibres or plates. This applies to the relevant fluid dynamic forces and to the interactions between particles as well as particle-wall collisions. Consequently, such numerical results are not reflecting the full truth yielding to an unrealistic modelling of the problem. Numerical simulations of fibre-laden flows using a point-particle Euler/Lagrange approach are based on tracking these elongated particles with respect to translation and rotation, where the centre of gravity position and the orientation of the fibres for each Lagrangian calculation are known. Here, an LES-Euler/Lagrange approach for elongated, inertial fibres was developed based on first principles and implemented in the open-source platform OpenFOAM®. The validation of the numerical approach was done considering a particle-laden turbulent channel flow which was thoroughly studied using DNS. Special attention was directed to the fibre-wall interaction model. For that purpose, a wall-impact model considering the particle orientation and the point of wall contact was implemented. The obtained numerical results were compared to those using a crude centre of mass specular reflection for the fibres. Both simulations yielded completely different results regarding the fibre orientation and concentration near the wall. The latter was considerably lower for the realistic wall collision model.
Unsteady, technically relevant particle-laden flows are nowadays efficiently simulated with an LES-Euler/Lagrange approach. The present contribution is related to fine particle separation in a gas cyclone which involves an unsteady central vortex being responsible for particle separation. Particle motion is largely controlled by near-wall transport processes including wall collisions as well as near-wall turbulence. Naturally, in a LES this region is not very well resolved so that a remarkable contribution to the local turbulence is included in the modelled sub-grid-scale (SGS) turbulence. In this paper the importance of SGS turbulence on particle transport is analysed. It is shown that neglecting the SGS contribution to the particle transport yields a wrong prediction of the particle size-dependent separation of a cyclone.
In order to detect outliers and potential anomalies in datasets, anomaly detection plays a pivotal role in identifying infrequent and irregular occurrences. The purpose of this paper is to examine and compare the effectiveness of prominent anomaly detection algorithms, including Isolation Forest, Local Outlier Factor (LOF), and One-Class Support Vector Machines (SVM). A variety of datasets are used in our assessment to evaluate key metrics such as precision, recall, F1-score, and overall accuracy. We also introduce innovative techniques that enhance the interpretability of these algorithms, shedding light on the underlying factors that contribute to anomaly detection. By providing insights into the attributes and behaviors associated with anomalies, our research empowers decision-makers to cultivate a profound comprehension of the identified anomalies, subsequently facilitating well-informed decisions grounded in the outcomes of anomaly detection. Through our meticulous comparative analysis and our dedication to unraveling the elements of explainability, we provide invaluable perspectives and pragmatic suggestions to facilitate effective anomaly detection in real-world scenarios.
The intricate relation between action and somatosensory perception has been studied extensively in the past decades. Generally, a forward model is thought to predict the somatosensory consequences of an action. These models propose that when an action is reliably coupled to a tactile stimulus, unexpected absence of the stimulus should elicit prediction error. Although such omission responses have been demonstrated in the auditory modality, it remains unknown whether this mechanism generalizes across modalities. This study therefore aimed to record action‐induced somatosensory omission responses using EEG in humans. Self‐paced button presses were coupled to somatosensory stimuli in 88% of trials, allowing a prediction, or in 50% of trials, not allowing a prediction. In the 88% condition, stimulus omission resulted in a neural response consisting of multiple components, as revealed by temporal principal component analysis. The oN1 response suggests similar sensory sources as stimulus‐evoked activity, but an origin outside primary cortex. Subsequent oN2 and oP3 responses, as previously observed in the auditory domain, likely reflect modality‐unspecific higher order processes. Together, findings straightforwardly demonstrate somatosensory predictions during action and provide evidence for a partially amodal mechanism of prediction error generation.
Campylobacter infections and campylobacteriosis-associated post-infectious sequelae are a significant global health burden that needs to be addressed from a specific African perspective. We conducted a comprehensive literature search on NCBI PubMed to compile a comprehensive narrative review article on Campylobacter infections in Africa, focusing on key aspects in human and veterinary medicine as well as food hygiene. We specifically focused on the epidemiology of enteropathogenic Campylobacter spp. in sub-Saharan and North Africa considering antimicrobial susceptibility. The most significant sequela resulting from molecular mimicry to Campylobacter surface structures is the Guillain-Barré syndrome, which was mainly examined in the context of limited studies conducted in African populations. A dedicated subsection is allocated to the limited research on the veterinary medically important species Campylobacter fetus. There are significant differences in the composition of the gut microbiome, especially in rural areas, which affect the colonization with Campylobacter spp. and the manifestation of campylobacteriosis. There may be a problem of overdiagnosis due to asymptomatic colonization, particularly in the detection of Campylobacter using molecular biological techniques. To reduce the colonization and infection rate of Campylobacter, we propose implementing several control measures and urge further research to improve the current understanding of the peculiarities of campylobacteriosis in Africa.
Many human teratogens are associated with a spectrum of congenital anomalies rather than a single defect, and therefore the identification of congenital anomalies occurring together more frequently than expected may improve the detection of teratogens. Thirty-two EUROCAT congenital anomaly registries covering 6,599,765 births provided 123,566 cases with one or more major congenital anomalies (excluding chromosomal and genetic syndromes) for the birth years 2008–2016. The EUROCAT multiple congenital anomaly algorithm identified 8804 cases with two or more major congenital anomalies in different organ systems, that were not recognized as part of a syndrome or sequence. For each pair of anomalies, the odds of a case having both anomalies relative to having only one anomaly was calculated and the p value was estimated using a two-sided Fisher’s exact test. The Benjamini–Hochberg procedure adjusted p values to control the false discovery rate and pairs of anomalies with adjusted p values < 0.05 were identified. A total of 1386 combinations of two anomalies were analyzed. Out of the 31 statistically significant positive associations identified, 20 were found to be known associations or sequences already described in the literature and 11 were considered “potential new associations” by the EUROCAT Coding and Classification Committee. After a review of the literature and a detailed examination of the individual cases with the anomaly pairs, six pairs remained classified as new associations. In summary, systematically searching for congenital anomalies occurring together more frequently than expected using the EUROCAT database is worthwhile and has identified six new associations that merit further investigation.
It is well known that plain concrete suffers from creep under sustained loads. Although various constitutive models have been proposed in the last years, these approaches are often restricted to linear creep of concrete at low load levels, face difficulties regarding multiaxial stress and deformation states, or involve a large number of parameters. The current contribution aims at closing this gap and presents a new robust modelling approach for the non-linear basic creep of plain concrete. Coupled non-linear evolution equations are formulated with respect to the creep strain and a backstress variable, which allows for the consideration of hardening effects. Both uniaxial and multiaxial stress conditions are taken into account, and the Drucker-Prager equivalent stress is utilized. Material parameters are determined based on compressive and tensile creep tests. Furthermore, the model is verified against an additional set of creep tests, which demonstrates that the proposed concept provides an accurate prediction for basic creep of concrete. Thereby, the concept is applicable for loads up to 70% of the short-term strength, while requiring a relatively low number of material parameters.
Background The aetiology and consequences of ‘baby blues’ (lower mood following childbirth) are yet to be sufficiently investigated with respect to an individual's clinical history. Aims The primary aim of the study was to assess the symptoms of baby blues and the relevant risk factors, their associations with clinical history and premenstrual syndrome (PMS), and their possible contribution to the early recognition of postpartum depression (PPD). Method Beginning shortly after childbirth, 369 mothers were followed up for 12 weeks. Information related to their clinical history, PMS, depression, stress and mother–child attachment was collected. At 12 weeks, mothers were classified as non-depressed, or with either PPD or adjustment disorder. Results A correlation was found between the severity of baby blues and PMS ( r = 0.397, P < 0.001), with both conditions increasing the possibility of adjustment disorder and PPD (baby blues: OR = 6.72, 95% CI 3.69–12.25; PMS: OR = 3.29, 95% CI 2.01–5.39). Baby blues and PMS independently predicted whether a mother would develop adjustment disorder or PPD after childbirth ( χ ² (64) = 198.16, P < 0.001). Among the non-depressed participants, baby blues were found to be associated with primiparity ( P = 0.012), family psychiatric history ( P = 0.001), PMS ( P < 0.001) and childhood trauma ( P = 0.017). Conclusions Baby blues are linked to a number of risk factors and a history of PMS, with both conditions adding to the risk of PPD. The neuroendocrine effects on mood need be understood in the context of individual risk factors. The assessment of both baby blues and PMS symptoms within the first postpartum days may contribute to an early identification of PPD.
Spreading processes on networks (graphs) have become ubiquitous in modern society with prominent examples such as infections, rumors, excitations, contaminations, or disturbances. Finding the source of such processes based on observations is important and difficult. We abstract the problem mathematically as an optimization problem on graphs. For the deterministic setting we make connections to the metric dimension of a graph and introduce the concept of spread resolving sets. For the stochastic setting we propose a new algorithm combining parameter estimation and experimental design. We discuss well-posedness of the algorithm and show encouraging numerical results on a benchmark library.
In this paper, we challenge the standard interpretation of pain asymbolia (PA), a neuropsychiatric condition that causes unusual reactions to pain stimuli. The standard interpretation asserts that PA subjects experience pain but lack important features of the experience. However, the paper argues that the clinical evidence for PA does not support this interpretation and that the arguments put forward by the defenders of the standard interpretation end up making self-contradicting claims. Finally, we suggest that the best interpretation of the available evidence is to take a deflationist stance toward PA, at least until further evidence becomes available.
Aims Inflammation and angiogenesis play an important role in the development of early diabetic kidney disease. We investigated the association of soluble Tumour Necrosis Factor Receptor 1 (sTNF‐R1), sTNF‐R2 and endostatin with new onset microalbuminuria in normoalbuminuric patients with diabetes mellitus type 2. Methods We conducted a case control study to assess serum levels of sTNF‐R1, sTNF‐R2 and endostatin in 169 patients with new onset microalbuminuria and in 188 matched normoalbuminuric, diabetic controls. Baseline serum samples from participants of the ROADMAP (Randomized Olmesartan and Diabetes Microalbuminuria Prevention) and observational follow‐up (ROADMAP‐OFU) studies were used. Results Endostatin and sTNF‐R1 but not sTNF‐R2 were increased at baseline in patients with future microalbuminuria. In the multivariate analysis, each log 2 increment in endostatin levels was associated with an increase of only 6% in the risk of development of microalbuminuria (adjusted HR (95% CI) 1.006 (1.001–1011). sTNF‐R1 and sTNF‐R2 levels were conversely associated with microalbuminuria, but the results did not reach statistical significance. The respective adjusted HRs (95% CI) were 1.305 (0.928–1.774) and 0.874 (0.711–1.074). Conclusions sTNF‐R1 and sTNF‐R2 failed to predict the occurrence of microalbuminuria in normoalbuminuric patients with type 2 diabetes. Likewise, the utility of endostatin in predicting new onset proteinuria is limited.
Event cameras are biologically inspired devices. They are fundamentally different from conventional frame-based sensors in that they directly transmit an (x, y, t) output stream of asynchronously and independently detected changes in brightness. For the development of monitoring systems, scenario-based long-term experiments are much more representative than day-to-day experiments. However, unconstrained “real-world” factors pose processing challenges. To perform a semantic scene filtering on the output stream of an event camera in such an outdoor monitoring scenario, this paper describes a multi-stage processing chain. The goal is to identify and store only those segments that contain events that were triggered by a specific set of objects of interest. The main idea of the proposed processing pipeline is to pre-process the data stream using different filters to identify Patches-Of-Interest (PoIs). These PoIs, natively represented as space-time event clouds, are further processed by PointNet++, a 3D-based semantic segmentation network. An evaluation was performed on about 89 h of real-world outdoor sensor data, achieving a semantic filtering with a false negative rate of \({\approx }3.8\%\) and a true positive rate of \({\approx }96.2\%\).
Background Arcobacter species are considered emerging foodborne pathogens that can potentially cause serious infections in animals and humans. This cross-sectional study determined the frequency of potentially pathogenic Arcobacter spp. in both commercial and smallholder farm animals in Ghana and Tanzania. A total of 1585 and 1047 (poultry and livestock) samples were collected in Ghana and Tanzania, respectively. Selective enrichment media, along with oxidase and Gram testing, were employed for isolation of suspected Arcobacter spp. and confirmation was done using MALDI-TOF MS. Antibiotic susceptibility was assessed through disk diffusion method and ECOFFs were generated, for interpretation, based on resulting inhibition zone diameters. Results The overall Arcobacter frequency was higher in Ghana (7.0%, n = 111) than in Tanzania (2.0%, n = 21). The frequency of Arcobacter in commercial farms in Ghana was 10.3% (n/N = 83/805), while in Tanzania, it was 2.8% (n/N = 12/430). Arcobacter was detected in only 3.6% (n/N = 28/780) of the samples from smallholder farms in Ghana and 1.5% (n/N = 9/617) of the samples from Tanzania. For commercial farms, in Ghana, the presence of Arcobacter was more abundant in pigs (45.1%, n/N = 37/82), followed by ducks (38.5%, n/N = 10/26) and quails (35.7%, n/N = 10/28). According to MALDI-TOF-based species identification, Arcobacter butzleri (91.6%, n/N = 121/132), Arcobacter lanthieri (6.1%, n/N = 8/132), and Arcobacter cryaerophilus (2.3%, n/N = 3/132) were the only three Arcobacter species detected at both study sites. Almost all of the Arcobacter from Ghana (98.2%, n/N = 109/111) were isolated during the rainy season. The inhibition zone diameters recorded for penicillin, ampicillin, and chloramphenicol allowed no determination of an epidemiological cut-off value. However, the results indicated a general resistance to these three antimicrobials. Multidrug resistance was noted in 57.1% (n/N = 12/21) of the Arcobacter isolates from Tanzania and 45.0% (n/N = 50/111) of those from Ghana. The type of farm (commercial or smallholder) and source of the sample (poultry or livestock) were found to be associated with multi-drug resistance. Conclusions The high levels of MDR Arcobacter detected from farms in both countries call for urgent attention and comprehensive strategies to mitigate the spread of antimicrobial resistance in these pathogens.
Distributed state estimation and localisation methods have become increasingly popular with the rise of ubiquitous computing, and have led naturally to an increased concern regarding data and estimation privacy. Traditional distributed sensor navigation methods typically involve the leakage of sensor or navigator information by communicating measurements or estimates and thus do not preserve participants' privacy. The existing approaches that do provide such guarantees fail to address sensor and navigator privacy in the common application of model-based range-only localisation, consequently forfeiting broad applicability. In this work, we define a notion of privacy-preserving linear combination aggregation and use it to derive a modified Extended Kalman Filter using range measurements such that navigator location, sensors' locations, and sensors' measurements are kept private during navigation. Additionally, a formal cryptographic backing is presented to guarantee our method's privacy as well as an implementation to evaluate its performance. The novel, provably secure, range-based localisation method has applications in a variety of environments where sensors may not be trusted or estimates are considered sensitive, such as autonomous vehicle localisation or air traffic navigation.
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Konrad Mühler
  • Department of Simulation and Graphics (ISG)
Marcel Lichters
  • Chair of Marketing
Frank Ortmeier
  • Faculty of Computer Science
Christian Apfelbacher
  • Institute of Social Medicine and Health Systems Research
Alexander Hohn
  • Clinic for Radiology and Nuclear Medicine
Universitätsplatz 2, 39106, Magdeburg, Saxony-Anhalt, Germany
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