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Streptococcus agalactiae is the leading cause of bacterial sepsis and meningitis in neonates and is also the causative agent of several serious infections in immunocompromised adults. S. agalactiae encounters multiple niches during an infection, suggesting that regulatory mechanisms control the expression of specific virulence factors in this bacterium. The present study describes the functional characterization of a gene from S. agalactiae, designated rga, which encodes a protein with significant similarity to members of the RofA-like protein (RALP) family of transcriptional regulators. After deletion of the rga gene in the genome of S. agalactiae, the mutant strain exhibited significantly reduced expression of the genes srr-1 and pilA, which encode a serine-rich repeat surface glycoprotein and a pilus protein, respectively, and moderately increased expression of the fbsA gene, which encodes a fibrinogen-binding protein. Electrophoretic mobility shift assays demonstrated specific DNA binding of purified Rga to the promoter regions of pilA and fbsA, suggesting that Rga directly controls pilA and fbsA. Adherence assays revealed significantly reduced binding of the Δrga mutant to epithelial HEp-2 cells and to immobilized human keratin 4, respectively. In contrast, the adherence of the Δrga mutant to A549 cells and its binding to human fibrinogen was significantly increased. Immunoblot and immunoelectron microscopy revealed that the quantity of pilus structures was significantly reduced in the Δrga mutant compared with the parental strain. The wild-type phenotype could be restored by plasmid-mediated expression of rga, demonstrating that the mutant phenotypes resulted from a loss of Rga function.
This paper presents implementation results of several side channel countermeasures for protecting the scalar multiplication of ECC (Elliptic Curve Cryptography) implemented on an ARM Cortex M3 processor that is used in security sensitive wireless sensor nodes. Our implementation was done for the ECC curves P-256, brainpool256r1, and Ed25519. Investigated countermeasures include Double-And-Add Always, Montgomery Ladder, Scalar Randomization, Randomized Scalar Splitting, Coordinate Randomization, and Randomized Sliding Window. Practical side channel tests for SEMA (Simple Electromagnetic Analysis) and MESD (Multiple Exponent, Single Data) are included. Though more advanced side channel attacks are not evaluated, yet, our results show that an appropriate level of resistance against the most relevant attacks can be reached.
In memoriam Willy Lehnert
(2023)
Der Globale Migrationspakt der Vereinten Nationen beschreibt globale Kompetenzpartnerschaften bzw. Global Skills Partnerships (GSP) als eine innovative Möglichkeit, die Fachkräftebasis global zu stärken, bleibt hinsichtlich ihrer Ausgestaltung aber recht vage. Auch die hierzulande unter der Bezeichnung „transnationale Ausbildungspartnerschaften“ laufenden Aktivitäten sind in Zahl und Reichweite sehr begrenzt und es liegen bisweilen kaum empirische Analysen zu ihnen vor. Hier schafft die vorliegende Expertise von Michael Sauer und Jurica Volarevic Abhilfe, indem sie existierende Ausbildungspartnerschaften insbesondere aus dem Erfahrungsraum der Republik Kosovo vorstellt und analytisch beleuchtet. Mithilfe einer Bestandsaufnahme der konzeptionellen Diskurse und Praxiserfahrungen wird ein Kategorisierungsvorschlag unternommen, mit dessen Hilfe die empirische Vielfalt besser geordnet und konzeptionell greifbar gemacht werden kann: Transnationale Qualifizierungs- und Mobilitätspartnerschaften (tQMP).
The Global Compact for Safe, Orderly and Regular Migration defines Global Skill Partnerships (GSP) as an innovative means of strengthen skills development among origin countries and countries of destination in mutually beneficial manner. However, GSPs are very limited in number and scope, and empirical analyses of them are, to date, relatively rare. This study helps fill this gap in data by presenting and examining existing GSPs or GSP-like approaches (e.g., transnational training partnerships). The aim of the study is to take stock of the various conceptual discourses on and practical experience with transnational skill partnerships. Using Kosovo as a case study, the study details the structure of such partnerships and the processes they entail. It documents the experience of those involved and catalogues the factors contributing to success. On this basis, the authors propose a means of categorizing the various practices that will help structure the empirical diversity of such approaches and render them conceptually feasible: Transnational Skills and Mobility Partnerships (TSMP).
The representation, or encoding, utilized in evolutionary algorithms has a substantial effect on their performance. Examination of the suitability of widely used representations for quality diversity optimization (QD) in robotic domains has yielded inconsistent results regarding the most appropriate encoding method. Given the domain-dependent nature of QD, additional evidence from other domains is necessary. This study compares the impact of several representations, including direct encoding, a dictionary-based representation, parametric encoding, compositional pattern producing networks, and cellular automata, on the generation of voxelized meshes in an architecture setting. The results reveal that some indirect encodings outperform direct encodings and can generate more diverse solution sets, especially when considering full phenotypic diversity. The paper introduces a multi-encoding QD approach that incorporates all evaluated representations in the same archive. Species of encodings compete on the basis of phenotypic features, leading to an approach that demonstrates similar performance to the best single-encoding QD approach. This is noteworthy, as it does not always require the contribution of the best-performing single encoding.
The representation, or encoding, utilized in evolutionary algorithms has a substantial effect on their performance. Examination of the suitability of widely used representations for quality diversity optimization (QD) in robotic domains has yielded inconsistent results regarding the most appropriate encoding method. Given the domain-dependent nature of QD, additional evidence from other domains is necessary. This study compares the impact of several representations, including direct encoding, a dictionary-based representation, parametric encoding, compositional pattern producing networks, and cellular automata, on the generation of voxelized meshes in an architecture setting. The results reveal that some indirect encodings outperform direct encodings and can generate more diverse solution sets, especially when considering full phenotypic diversity. The paper introduces a multi-encoding QD approach that incorporates all evaluated representations in the same archive. Species of encodings compete on the basis of phenotypic features, leading to an approach that demonstrates similar performance to the best single-encoding QD approach. This is noteworthy, as it does not always require the contribution of the best-performing single encoding.