Hochschule Bonn-Rhein-Sieg

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    7939 research outputs found

    Open-Source Machine Learning in Computational Chemistry

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    The field of computational chemistry has seen a significant increase in the integration of machine learning concepts and algorithms. In this Perspective, we surveyed 179 open-source software projects, with corresponding peer-reviewed papers published within the last 5 years, to better understand the topics within the field being investigated by machine learning approaches. For each project, we provide a short description, the link to the code, the accompanying license type, and whether the training data and resulting models are made publicly available. Based on those deposited in GitHub repositories, the most popular employed Python libraries are identified. We hope that this survey will serve as a resource to learn about machine learning or specific architectures thereof by identifying accessible codes with accompanying papers on a topic basis. To this end, we also include computational chemistry open-source software for generating training data and fundamental Python libraries for machine learning. Based on our observations and considering the three pillars of collaborative machine learning work, open data, open source (code), and open models, we provide some suggestions to the community

    Case report: Novel variants in RELA associated with familial Behcet's-like disease

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    RELA haploinsufficiency is a recently described autoinflammatory condition presenting with intermittent fevers and mucocutaneous ulcerations. The RELA gene encodes the p65 protein, one of five NF-κB family transcription factors. As RELA is an essential regulator of mucosal homeostasis, haploinsufficiency leads to decreased NF-κB signaling which promotes TNF-driven mucosal apoptosis with impaired epithelial recovery. Thus far, only eight cases have been reported in the literature. Here, we report four families with three novel and one previously described pathogenic variant in RELA. These four families included 23 affected individuals for which genetic testing was available in 16. Almost half of these patients had been previously diagnosed with more common rheumatologic entities (such as Behcet's Disease; BD) prior to the discovery of their pathogenic RELA variants. The most common clinical features were orogenital ulcers, rash, joint inflammation, and fever. The least common were conjunctivitis and recurrent infections. Clinical variability was remarkable even among familial cases, and incomplete penetrance was observed. Patients in our series were treated with a variety of medications, and benefit was observed with glucocorticoids, colchicine, and TNF inhibitors. Altogether, our work adds to the current literature and doubles the number of reported cases with RELA-Associated Inflammatory Disease (RAID). It reaffirms the central importance of the NF-κB pathway in immunity and inflammation, as well as the important regulatory role of RELA in mucosal homeostasis. RELA associated inflammatory disease should be considered in all patients with BD, particularly those with early onset and/or with a strong family history

    Improving Natural Language Inference in Arabic using Transformer Models and Linguistically Informed Pre-Training

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    This paper addresses the classification of Arabic text data in the field of Natural Language Processing (NLP), with a particular focus on Natural Language Inference (NLI) and Contradiction Detection (CD). Arabic is considered a resource-poor language, meaning that there are few data sets available, which leads to limited availability of NLP methods. To overcome this limitation, we create a dedicated data set from publicly available resources. Subsequently, transformer-based machine learning models are being trained and evaluated. We find that a language-specific model (AraBERT) performs competitively with state-of-the-art multilingual approaches, when we apply linguistically informed pre-training methods such as Named Entity Recognition (NER). To our knowledge, this is the first large-scale evaluation for this task in Arabic, as well as the first application of multi-task pre-training in this context

    Achieving Usable Security and Privacy Through Human-Centered Design

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    Users should always play a central role in the development of (software) solutions. The human-centered design (HCD) process in the ISO 9241-210 standard proposes a procedure for systematically involving users. However, due to its abstraction level, the HCD process provides little guidance for how it should be implemented in practice. In this chapter, we propose three concrete practical methods that enable the reader to develop usable security and privacy (USP) solutions using the HCD process. This chapter equips the reader with the procedural knowledge and recommendations to: (1) derive mental models with regard to security and privacy, (2) analyze USP needs and privacy-related requirements, and (3) collect user characteristics on privacy and structure them by user group profiles and into privacy personas. Together, these approaches help to design measures for a user-friendly implementation of security and privacy measures based on a firm understanding of the key stakeholders

    Verbraucherpolitik

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    Technikvideos für Mädchen?

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    Die Autorinnen untersuchten Faktoren für die Attraktivität von Technikvideos und formulierten aus den Ergebnissen Leitlinien für die Produktion von Videos zu Technikthemen für Mädchen und junge Frauen

    BWL kompakt für Dummies

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    "BWL kompakt für Dummies" bietet Ihnen eine verständliche Einführung in die Betriebswirtschaftslehre, egal ob Sie sie für die Aus- oder Weiterbildung brauchen oder sich einfach schlau machen wollen. Tobias Amely stellt Ihnen die wesentlichen Elemente und Grundbegriffe der Betriebswirtschaftslehre vor und zeigt die Bezüge zur Unternehmenspraxis auf: Materialwirtschaft, Leistungsbereitstellung und Produktion, Marketing, Investition und Finanzierung, Unternehmensorganisation und -führung, Rechnungswesen und Controlling. (Verlagsangaben

    Exploring clonality and virulence gene associations in bloodstream infections using whole-genome sequencing and clinical data

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    Background: Bloodstream infections (BSIs) remain a significant cause of mortality worldwide. Causative pathogens are routinely identified and susceptibility tested but only very rarely investigated for their resistance genes, virulence factors, and clonality. Our aim was to gain insight into the clonality patterns of different species causing BSI and the clinical relevance of distinct virulence genes. Methods: For this study, we whole-genome-sequenced over 400 randomly selected important pathogens isolated from blood cultures in our diagnostic department between 2016 and 2021. Genomic data on virulence factors, resistance genes, and clonality were cross-linked with in-vitro data and demographic and clinical information. Results: The investigation yielded extensive and informative data on the distribution of genes implicated in BSI as well as on the clonality of isolates across various species. Conclusion: Associations between survival outcomes and the presence of specific genes must be interpreted with caution, and conducting replication studies with larger sample sizes for each species appears mandatory. Likewise, a deeper knowledge of virulence and host factors will aid in the interpretation of results and might lead to more targeted therapeutic and preventive measures. Monitoring transmission dynamics more efficiently holds promise to serve as a valuable tool in preventing in particular BSI caused by nosocomial pathogens

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