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Individualisierbare, webbasierte Benutzerschnittstelle zur Überwachung von Industrieprozessen
No full textIm Rahmen eines Projektes zur Applikation der Präskriptiven Analytik für die dynamische Prozessführung von intelligenten Kälteanlagen wurde eine webbasierte Software mit einer anwenderfreundlichen und individualisierbaren Benutzerschnittstelle zur Überwachung und Regelung umgesetzt. Als Teilprojekt wurde ein Softwarepaket entwickelt, welches eine konfigurierbare Anlagenvisualisierung für diese Benutzerschnittstelle umsetzt. Beim Entwurf und der Implementierung der Software wurde auf einen modularen Aufbau geachtet, sodass die Software leicht erweiterbar und aus auswechselbaren, unabhängigen Komponenten zusammengesetzt ist
Advancing microbiome research with machine learning: key findings from the ML4Microbiome COST action
No full textThe rapid development of machine learning (ML) techniques has opened up the data-dense field of microbiome research for novel therapeutic, diagnostic, and prognostic applications targeting a wide range of disorders, which could substantially improve healthcare practices in the era of precision medicine. However, several challenges must be addressed to exploit the benefits of ML in this field fully. In particular, there is a need to establish “gold standard” protocols for conducting ML analysis experiments and improve interactions between microbiome researchers and ML experts. The Machine Learning Techniques in Human Microbiome Studies (ML4Microbiome) COST Action CA18131 is a European network established in 2019 to promote collaboration between discovery-oriented microbiome researchers and data-driven ML experts to optimize and standardize ML approaches for microbiome analysis. This perspective paper presents the key achievements of ML4Microbiome, which include identifying predictive and discriminatory ‘omics’ features, improving repeatability and comparability, developing automation procedures, and defining priority areas for the novel development of ML methods targeting the microbiome. The insights gained from ML4Microbiome will help to maximize the potential of ML in microbiome research and pave the way for new and improved healthcare practices
Little Big Data: Karelian Twitter Corpus
No full textThis paper investigates Karelian language visibility on Twitter and describes the first corresponding data collection using language-related keywords and hashtags. In total, 2626 entries written fully or partially in Livvi, South and Viena Karelian were scraped with Postman API. The visibility of Karelian on Twitter has been considerably increasing in the past few years, Livvi-Karelian being the most prominent dialect. The data were analysed linguistically (manually and with language detection software) and thematically. Although language-related topics are the most popular, there is a substantial number of entries in eight further topics. Applicability of the collected data for linguistic and sociological research, and further data collection considerations are discussed
Investigation of the Impact of Insulin Resistance on the Bone Density of the Upper Wall of the Maxillary Sinus
No full textThe aim of our study was to investigate the impact of insulin resistance on the bone density of the upper wall of the maxillary sinus. Materials and Methods: The study included 100 female participants aged 18 to 44 years, divided into two groups. The first group consisted of individuals with insulin resistance, while the control group comprised individuals without signs of insulin resistance. In each group, we conducted an investigation of the radiological density of the upper wall of the maxillary sinus using uncertainty calculations. Results of the study suggest a potential influence of insulin resistance on the density of bone tissue around the nasal sinuses, specifically the upper wall of the maxillary sinus in our case. This parameter was found to be minimal in the group of individuals with insulin resistance. It is particularly noteworthy that both minimum and maximum bone density decreased in this group. Conclusions. The research focused on how insulin resistance affects the density of the upper wall of the maxillary sinus. By employing uncertainty calculations, the study revealed that insulin resistance is associated with a decrease in the minimum density of the upper wall of the maxillary sinus. This tendency may act as a catalyst for the emergence of significant inflammatory alterations in the nasal sinuses, serving as a foundation for the initiation of complications
Electrolytical Coating of Inhomogeneous Structures Distributed on Metallic Surfaces
No full textIn modern electrochemical coating technology, it is common practice to create uniform layers. However, this study focuses on the deposition of non-uniform layers achieved through a deliberate arrangement of micro structured electrodes on the anode side. The "dog bone effect” was employed as the primary approach [1]. When electroplating on an otherwise uniform surface, this effect selectively processes an area influenced by the geometric edge effect (figure 1 left). The coating within this area is intended to be (i) unevenly distributed and (ii) non-reproducible. Process data was obtained through electrochemical simulations and subsequently applied to a specially designed micro-galvanic setup. This enabled the production of suitable micro structured anodes, validation of coating parameters, and the deposition of visually imperceptible structured areas with inhomogeneous properties using "adhesive gold" on appropriate substrates such as silver and nickel. The layers and their local topography were characterized and analyzed using confocal laser microscopy, X-Ray fluorescence analysis (XRF), as well as a self-designed and constructed laser interference device. As a result, this specific galvanic process technology successfully produced metallic layers that (i) cannot be visually confirmed by the naked eye, (ii) exhibit varied microstructural anode geometries, (iii) display unique differences in layer thickness, (iv) possess non-reproducible and chaotic topographies, and (v) can be detected and identified using conventional analysis techniques or a simple interference setup
The combination of omics strategies to evaluate starter and probiotic strains in the Catharina sour Brazilian-style beer
No full textCatharina sour, the first internationally recognized Brazilian beer, is characterized by fermentation with lactic acid bacteria (LAB), which may have probiotic potential, and the addition of fruit juice. This study aimed to evaluate the use of the starter Streptococcus thermophilus TH‐4 (TH‐4) and the probiotics Lacticaseibacillus paracasei F19 and 431, associated with Saccharomyces cerevisiae US-05, in the absence (control)/presence of passion fruit or peach juices. Evaluation proceeded during fermentation and storage by enumeration using pour-plate and qPCR; gene expressions of hop resistance; proteome by Liquid Chromatography Tandem Mass Spectrometry (LC-MS/MS); and odor, flavor, and metabolome by Headspace Solid-Phase Microextraction (HS-SPME), coupled with the gas chromatography–mass spectrometry (GC–MS) analysis. We concluded that the strains studied are recommended for applications in sour beers, due to the presence of defense mechanisms like membrane adhesion and H+ pump. Furthermore, HS-SPME/GC-MS indicated that the strains may contribute to the beer flavor and odor
Planning for wolf-livestock coexistence: landscape context predicts livestock depredation risk in agricultural landscapes
No full textExtensive pastoral livestock systems in Central Europe provide multiple ecosystem services and support biodiversity in agricultural landscapes but their viability is challenged by livestock depredation (LD) associated with the recovery of wolf populations. Variation in the spatial distribution of LD depends on a suite of factors, most of which are unavailable at the appropriate scales. To assess if LD patterns can be predicted sufficiently with land use data alone at the scale of one federal state in Germany, we employed a machine-learning-supported resource selection approach. The model used LD monitoring data, and publicly available land use data to describe the landscape configuration at LD and control sites (resolution 4 km * 4 km). We used SHapley Additive exPlanations to assess the importance and effects of landscape configuration and cross-validation to evaluate the model performance. Our model predicted the spatial distribution of LD events with a mean accuracy of 74%. The most influential land use features included grassland, farmland and forest. The risk of livestock depredation was high if these three landscape features co-occurred with a specific proportion. A high share of grassland, combined with a moderate proportion of forest and farmland, increased LD risk. We then used the model to predict the LD risk in five regions; the resulting risk maps showed high congruence with observed LD events. While of correlative nature and lacking specific information on wolf and livestock distribution and husbandry practices, our pragmatic modelling approach can guide spatial prioritisation of damage prevention or mitigation practices to improve livestock-wolf coexistence in agricultural landscapes
Automatisierte Erkennung von Messarealen bei robotergestützten In Vivo Messungen
No full textDieser Beitrag schlägt ein Bildverarbeitungsmodell zur automatisierten Bestimmung von Messarealen bei robotergestützten In Vivo Messungen vor. Es wird angenommen, dass moderne Verfahren der Deep-Learning-Objekterkennung in der Lage sind die einzelnen Areale wiederholbar genau genug zu erkennen, um die benötigten Messareale im dreidimensionalen Raum einzupassen. Für das Einpassen werden Tiefeninformationen aus einer stereoskopischen Kamera verwendet. Weiter wird untersucht inwiefern diese Tiefeninformationen als zusätzlicher Eingang für die Deep-Learning-Modelle verwendet werden können. Hierfür wird ein Konzept ausgearbeitet, ein Datensatz erstellt und Modelle zur Objekterkennung in verschiedenen Implementierungen trainiert. Das Verwenden von Tiefeninformationen führt zu einer besseren Generalisierbarkeit der Modelle, insbesondere auf tätowierten Hautarealen. Das Bildverarbeitungsmodell erreicht beim Einpassen der Messareale eine gemittelte Wiederholgenauigkeit bzw. Abweichung von 6, 1 mm bei einer Bildwiederholrate von 2, 3 bis 3, 3 Bildern die Sekunde
Gender Team Diversity in Entrepreneurship Education
No full textThis study explores the impact of the student team’s gender diversity on different performance outcomes in a business plan course with active teaching elements. Although the team’s gender diversity is oftentimes neglected in entrepreneurship education research, the empirical analysis shows that significant performance differences depending on a gender-specific composition exist. In general, mixed-gender teams perform better than men’s teams, which receive, on average, worse grades for their business plan. Additionally, mixed teams perform comparatively better in attracting interest for their business idea as measured by views on an online idea platform. To enhance group performance, practitioners shall pay more attention to team composition in an educational setting and actively promote mixed-gender teams
Integrating Line Planning for Construction Sites into Periodic Timetabling via Track Choice
No full textWe consider maintenance sites for urban rail systems, where unavailable tracks typically require changes to the regular timetable, and often even to the line plan. In this paper, we present an integrated mixed-integer linear optimization model to compute an optimal line plan that makes best use of the available tracks, together with a periodic timetable, including its detailed routing on the tracks within the stations. The key component is a flexible, turn-sensitive event-activity network that allows to integrate line planning and train routing using a track choice extension of the Periodic Event Scheduling Problem (PESP). Major goals are to maintain as much of the regular service as possible, and to keep the necessary changes rather local. Moreover, we present computational results on real construction site scenarios on the S-Bahn Berlin network. We demonstrate that this integrated problem is indeed solvable on practically relevant instances