We propose a codec specifically designed for meshlet compression, optimized for rapid data-parallel GPU decompression within a mesh shader. Our compression strategy orders triangles in optimal generalized triangle strips (GTSs), which we generate by formulating the creation as a mixed integer linear program (MILP). Our method achieves index buffer compression rates of 16:1 compared to the vertex pipeline and crack-free vertex attribute quantization based on user preference. The 15.5 million triangles of our teaser image decompress and render in 0.59 ms on an AMD Radeon RX 7900 XTX.

A number of machine learning process models (SEMMA, KDD, CRISP-DM, CRISP-ML, Data-to-Value1 etc.) have been recently proposed to facilitate the development of machine learning models in their organizational context. While the existing proposals vary with respect to complexity and suitability for particular tasks, it would be desirable to have software tools that embody or support these process models, and make it easier for project teams to capture, share among team members and stakeholders and preserve the relevant project information pertaining to the various process stages. In particular, recorded past statistics may be applied to predict the duration of stages or the overall project effort.

Presently, to the best of our knowledge, no requirement analysis exists that stipulates the detailed needs. To this end, we present a first collection and analysis of a requirements document for the software tooling for machine learning process models. We describe the functional and non-functional requirements of a Computer-Aided Machine Learning Modeling (CAMLM) tool, the soft-computing world’s counter-part to a CASE (Computer Aided Software Engineering) tool.

Various software cover sub-areas such as team management and communication management (Confluence, Jira, Slack, Zoom...) or project management (CRISP-DM, Scrum, Kanban-Board...) or data and information management (model management [Weber, Christian; Hirmer, Pascal; Reimann, Peter; Schwarz, Holger (2019): A New Process Model for the Comprehensive Management of Machine Learning Models. In: Proceedings of the 21st International Conference on Enterprise Information Systems: SCITEPRESS - Science and Technology Publications.] ). What is not available to our knowledge, however, is software that covers the entire sub-areas and the entire life cycle of machine learning projects in detail.

In Zeiten zurückhaltender wirtschaftlicher Stimmungslage ist die Gründung einer Unternehmung/ der Schritt in die Selbstständigkeit durchaus risikobehaftet. Handelt es sich dabei zudem um eine Gründung/Selbstständigkeit mit Nachhaltigkeits-Fokus, so deuten Befragungen darauf hin, dass hierbei nochmals weitere spezifische Herausforderungen auftreten können. Gleichzeitig leisten nachhaltigkeitsorientierte Gründerinnen und Gründer jedoch einen wertvollen Beitrag zur Bewältigung wirtschaftlicher und gesamtgesellschaftlicher Herausforderungen unserer Zeit - auch und gerade in einer ländlich und industriell geprägten Region wie der Region Oberfranken/Südthüringen. Im Austausch mit unseren externen hochschulischen Praxispartnern (allen voran der IHK zu Coburg und der HWK Bayreuth), die traditionell in der Phase der Unternehmensgründung/des Sich-Selbstständigmachens unterstützen, entstand die Idee, eine Befragung regionaler nachhaltigkeitsorientierter Gründerinnen und Gründer durchzuführen, um deren spezifischen Unterstützungsbedarfe und -wünsche zu erfragen. Dies haben wir gemeinsam mit Studierenden eines interdisziplinären Seminars der Hochschule Coburg im Wintersemester 2023/2024 umgesetzt. Die Befragung wurde dabei mit den Studierenden in allen Phasen der Untersuchung partizipativ geplant, durchgeführt und ausgewertet. Die Ergebnisse der Befragung sollen vorrangig der Gründungsberatung dienen (einer Aufgabe, mit denen sich auch Hochschulen jüngst immer mehr auseinandersetzen müssen), gleichzeitig aber auch Implikationen für die Hochschullehre i.S. einer “Sustainable/Social Entrepreneurship Education” bieten. Im angehängten Ergebnisposter werden Ausgangslage und Zielstellung der Untersuchung, die Methodische Anlage sowie die Ergebnisse der Befragung von N=14 nachhaltigen Gründerinnen und Gründern der Region Coburg/Südthüringen vorgestellt und sich erste daraus ergebende Implikationen aufgezeigt.

This study investigates the social acceptance of integrated photovoltaic (IPV) systems in heritage and landscape contexts, focusing on Italian stakeholders in the construction sector. As part of the “BIPV meets History” research project, this study aims to identify barriers, potentials, drivers, and challenges for widespread PV technology adoption, considering heritage conservation, land preservation, energy production, and climate mitigation. A survey exploring opinions on PV technology integration was conducted. The survey was improved and extended to a total of 271 respondents, using the online method of Computer-Aided Web Interviewing (CAWI), to understand how perceptions of integrated photovoltaics have changed after COVID-19 and the European energy crisis, emphasizing aesthetic, environmental, economic, and personal aspects. The results indicate a general awareness of the technologies, with increasing acceptance in protected contexts, for historic buildings (from 51 to 68%) and especially landscapes (from 44 to 71%), driven by energy and environmental benefits. Cultural concerns, particularly the risk of impacting historical and natural identities, emerge as major barriers. Additionally, it is evident that awareness of PV panel recycling methods is still limited.

Renal cell carcinoma (RCC) is the most common form of kidney cancer, known for its immune evasion and resistance to chemotherapy. Evidence indicates that the SARS-CoV-2 virus may worsen outcomes for RCC patients, as well as patients with diminished renal function. Evidence suggests that the SARS-CoV-2 virus may exacerbate outcomes in RCC patients and those with impaired renal function. This study explored the unidirectional effects of RCC cells and the SARS-CoV-2 spike protein (S protein) on human renal proximal tubule epithelial cells (RPTECs) using a microphysiological approach. We co-cultured RCC cells (Caki-1) with RPTEC and exposed them to the SARS-CoV-2 S protein under dynamic 3D conditions. The impact on metabolic activity, gene expression, immune secretions, and S protein internalization was evaluated. The SARS-CoV-2 S protein was internalized by RPTEC but poorly interacted with RCC cells. RPTECs exposed to RCC cells and the S protein exhibited upregulated expression of genes involved in immunogenic pathways, particularly those related to antigen processing and presentation via the major histocompatibility complex I (MHCI). Additionally, increased TNF-α secretion suggested a pro-inflammatory response. Metabolic shifts toward glycolysis were observed in RCC co-culture, while the presence of the S protein led to minor changes. The presence of RCC cells amplified the immune-modulatory effects of the SARS-CoV-2 S protein on the renal epithelium, potentially exacerbating renal inflammation and fostering tumor-supportive conditions. These findings suggest that COVID-19 infections can impact renal function in the presence of kidney cancer.

The tricellular tight junctions are crucial for the regulation of paracellular flux at tricellular junctions, where tricellulin (MARVELD2) and angulins (ILDR1, ILDR2, or LSR) are localized. The role of ILDR2 in podocytes, specialized epithelial cells in the kidney, is still unknown. We investigated the role of ILDR2 in glomeruli and its influence on blood filtration. Western blots, single-cell RNA sequencing (scRNA-seq), and superresolution microscopy showed a strong expression of ILDR2 in podocytes that colocalized with the podocyte-specific claudin CLDN5. Co-immunoprecipitation revealed that ILDR2 interacts with CLDN5. In glomerulopathies, induced by nephrotoxic serum and by desoxycorticosterone acetate (DOCA)-salt heminephrectomy, ILDR2 was strongly up-regulated. Furthermore, Ildr2 knockout mice exhibited glomerular hypertrophy and decreased podocyte density. However, they did not develop effacement of podocyte foot processes or proteinuria. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) proteomic analysis of isolated glomeruli showed an increase in matrix proteins, such as fibronectin and collagens. This suggests a protective role of ILDR2 in glomerulopathies.