Simultaneous structuring and scheduling of multiple projects with flexible project structures

We study the problem to simultaneously decide on the structures and the schedules for an entire portfolio of flexible projects. The projects are flexible as alternative technologies and procedures can be used to achieve the respective project task. The choice between different technologies and procedures affects the activities to be implemented and thus the precedence relations, i.e., the structure of the project. The different projects have given due dates with specific delay payments and compete for scarce resources. In this situation, project structure decisions and scheduling decisions are highly intertwined and have to be made simultaneously in order to achieve the assumed objective of minimizing the delay payments for the entire project portfolio. The problem is formally stated and solved via novel and problem-specific genetic algorithms. The performance of the new algorithms is evaluated with respect to speed and accuracy in a systematic and comprehensive numerical study. © 2020, The Author(s)

Food consumption of adults in Germany: results of the German National Nutrition Survey II based on diet history interviews

The second German National Nutrition Survey (NVS II) aimed to evaluate food consumption and other aspects of nutritional behaviour of a representative sample of the German population, using a modular design with three different dietary assessment methods. To assess usual food consumption, 15 371 German speaking subjects 14–80 years of age completed a diet history interview between November 2005 and November 2006. With reference to the guidelines of the German Nutrition Society (DGE), NVS II observed that the German population did not eat enough foods of plant origin, especially vegetables and consumed too much of meat and meat products. While generally similar food consumption is observed in other European countries, consumption of bread, fruit juices/nectars and beer is higher in Germany. On average, men consumed two times more meat and soft drinks as well as six times more beer than women did, whereas the consumption of vegetables, fruit as well as herbal/fruit tea was higher in women. Older participants showed a lower consumption of meat, fruit juice/nectars, soft drinks and spirits as well as a higher consumption of fish, vegetables, fruit, and herbal/fruit tea than adolescents and younger adults did. There are also differences in food consumption with regard to socio-economic status (SES). Persons with higher SES consumed more vegetables, fruit, fish, water, coffee/tea and wine, while persons with lower SES consumed more meat and meat products, soft drinks and beer. In general, the food consumption of women, the elderly and the higher SES group tends to be closer to the official dietary guidelines in Germany

Acute transverse myelitis and psoriasiform dermatitis associated with Sjoegren’s syndrome: a case report

BACKGROUND: Clinical complications of Sjoegren’s syndrome include myelitis and skin manifestations. There is scarce observational data and a lack of randomised controlled studies regarding the treatment of Sjoegren’s syndrome in the presence of such complications. CASE PRESENTATION: Here we report the case of a 41-year-old Caucasian female patient with biopsy-proven Sjoegren’s syndrome who initially presented with generalized exanthema and subsequently developed acute extensive transverse myelitis. In view of the rapid deterioration we opted for an intensive treatment using a combination of corticosteroid pulse therapy, plasmapheresis and cyclophosphamide, which we later changed to rituximab. Under that treatment the skin manifestations resolved entirely whereas transverse myelitis showed incomplete remission. CONCLUSION: Severe neurological and dermatological complications may occur in Sjoegren’s syndrome. This suggests a close yet currently unclear pathogenetic relationship. Intensive immunosuppressant treatment resulted in significant improvement of both symptom clusters. Skin manifestations may precede other severe complications in Sjoegren’s syndrome and therefore require particular attention

Combining NLP, speech recognition, and indexing. An AI-based learning assistant for higher education

This paper presents the ongoing development of HAnS (Hochschul-Assistenz-System), an Intelligent Tutoring System (ITS) designed to support self-directed digital learning in higher education. Initiated by twelve collaborating German universities and research institutes, HAnS is developed 2021–2025 with the goal of utilizing artificial intelligence (AI) and Big Data in academic settings to enhance technology-based learning. The system employs AI for speech recognition and the indexing of existing learning resources, enabling users to search and compile these materials based on various parameters. Here, we provide an overview of the project, showcasing how iterative design and development processes contribute to innovative educational research in the evolving field of AI-based ITS in higher education. Notwithstanding the potential of HAnS, we also deliberate upon the challenges associated with ensuring a suitable dataset for training the AI, refining complex algorithms for personalization, and maintaining data privacy. (DIPF/Orig.)In diesem Beitrag wird die laufende Entwicklung von HAnS (Hochschul-Assistenz-System) vorgestellt, einem Intelligenten Tutoring-System (ITS), das selbstgesteuertes digitales Lernen in der Hochschulbildung unterstützen soll. HAnS wurde von zwölf deutschen Hochschulen und Forschungsinstituten initiiert und wird 2021-2025 mit dem Ziel entwickelt, künstliche Intelligenz (KI) und Big Data im akademischen Umfeld zu nutzen, um technologiebasiertes Lernen zu verbessern. Das System nutzt KI für die Spracherkennung und die Indizierung vorhandener Lernressourcen und ermöglicht es den Nutzern, diese Materialien auf der Grundlage verschiedener Parameter zu suchen und zusammenzustellen. Hier geben wir einen Überblick über das Projekt und zeigen, wie iterative Design- und Entwicklungsprozesse zu innovativer Bildungsforschung auf dem sich entwickelnden Gebiet der KI-basierten ITS in der Hochschulbildung beitragen. Ungeachtet des Potenzials von HAnS gehen wir auch auf die Herausforderungen ein, die mit der Sicherstellung eines geeigneten Datensatzes für das Training der KI, der Verfeinerung komplexer Algorithmen für die Personalisierung und der Wahrung des Datenschutzes verbunden sind. (Autor

N2 fixation in eddies of the eastern tropical South Pacific Ocean

Mesoscale eddies play a major role in controlling ocean biogeochemistry. By impacting nutrient availability and water column ventilation, they are of critical importance for oceanic primary production. In the eastern tropical South Pacific Ocean off Peru, where a large and persistent oxygen deficient zone is present, mesoscale processes have been reported to occur frequently. However, investigations on their biological activity are mostly based on model simulations, and direct measurements of carbon and dinitrogen (N2) fixation are scarce. We examined an open ocean cyclonic eddy and two anticyclonic mode water eddies: a coastal one and an open ocean one in the waters off Peru along a section at 16° S in austral summer 2012. Molecular data and bioassay incubations point towards a difference between the active diazotrophic communities present in the cyclonic eddy and the anticyclonic mode water eddies. In the cyclonic eddy, highest rates of N2 fixation were measured in surface waters but no N2 fixation signal was detected at intermediate water depths. In contrast, both anticyclonic mode water eddies showed pronounced maxima in N2 fixation below the euphotic zone as evidenced by rate measurements and geochemical data. N2 fixation and carbon (C) fixation were higher in the young coastal mode water eddy compared to the older offshore mode water eddy. A co-occurrence between N2 fixation and biogenic N2, an indicator for N loss, indicated a link between N loss and N2 fixation in the mode water eddies, which was not observed for the cyclonic eddy. The comparison of two consecutive surveys of the coastal mode water eddy in November and December 2012 revealed also a reduction of N2 and C fixation at intermediate depths along with a reduction in chlorophyll by half, mirroring an aging effect in this eddy. Our data indicate an important role for anticyclonic mode water eddies in stimulating N2 fixation and thus supplying N offshore

A Semiquantitative Non-invasive Measurement of PcomA Patency in C57BL/6 Mice Explains Variance in Ischemic Brain Damage in Filament MCAo

Numerous studies on experimental ischemic stroke use the filament middle cerebral artery occlusion (fMCAo) model in C57BL/6 mice, but lesion sizes in this strain are highly variable. A known contributor is variation in the posterior communicating artery (PcomA) patency. We therefore aimed to provide a semiquantitative non-invasivein vivomethod to routinely assess PcomA patency. We included 43 male C57BL/6 mice from four independent studies using a transient 45 min fMCAo model. Edema-corrected lesion sizes were measured by magnetic resonance (MR) imaging 24 h after reperfusion. Time-of-flight MR angiography was performed 7 days before and 24 h after fMCAo. Scores of PcomA size measured 24 h after, but not scores measured 7 days before fMCAo were negatively correlated with lesion size. Variability in PcomA patency explained 30% of the variance in our cohort (p< 0.0001, coefficient of determinationr(2)= 0.3). In a simulation using parameters typical for experimental stroke research, the power to detect a true effect ofd= 1 between two groups increased by 15% when an according covariate was included in the statistical model. We have demonstrated thatin vivomeasurement of PcomA size is feasible and can lead to increased accuracy in assessing the effect of treatments

Robust Tumor Segmentation with Hyperspectral Imaging and Graph Neural Networks

Segmenting the boundary between tumor and healthy tissue during surgical cancer resection poses a significant challenge. In recent years, Hyperspectral Imaging (HSI) combined with Machine Learning (ML) has emerged as a promising solution. However, due to the extensive information contained within the spectral domain, most ML approaches primarily classify individual HSI (super-)pixels, or tiles, without taking into account their spatial context. In this paper, we propose an improved methodology that leverages the spatial context of tiles for more robust and smoother segmentation. To address the irregular shapes of tiles, we utilize Graph Neural Networks (GNNs) to propagate context information across neighboring regions. The features for each tile within the graph are extracted using a Convolutional Neural Network (CNN), which is trained simultaneously with the subsequent GNN. Moreover, we incorporate local image quality metrics into the loss function to enhance the training procedure's robustness against low-quality regions in the training images. We demonstrate the superiority of our proposed method using a clinical ex vivo dataset consisting of 51 HSI images from 30 patients. Despite the limited dataset, the GNN-based model significantly outperforms context-agnostic approaches, accurately distinguishing between healthy and tumor tissues, even in images from previously unseen patients. Furthermore, we show that our carefully designed loss function, accounting for local image quality, results in additional improvements. Our findings demonstrate that context-aware GNN algorithms can robustly find tumor demarcations on HSI images, ultimately contributing to better surgery success and patient outcome.Comment: 11 pages, 6 figure