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Acute contact with profibrotic macrophages mechanically activates fibroblasts via αvβ3 integrin–mediated engagement of Piezo1
Get PDFFibrosis—excessive scarring after injury—causes 40% of disease-related deaths worldwide. In this misguided repair process, activated fibroblasts drive the destruction of organ architecture by accumulating and contracting extracellular matrix. The resulting stiff scar tissue, in turn, enhances fibroblast contraction—bearing the question of how this positive feedback loop begins. We show that direct contact with profibrotic but not proinflammatory macrophages triggers acute fibroblast contractions. The contractile response depends on αvβ3 integrin expression on macrophages and Piezo1 expression on fibroblasts. The touch of macrophages elevates fibroblast cytosolic calcium within seconds, followed by translocation of the transcription cofactors nuclear factor of activated T cells 1 and Yes-associated protein, which drive fibroblast activation within hours. Intriguingly, macrophages induce mechanical stress in fibroblasts on soft matrix that alone suppresses their spontaneous activation. We propose that acute contact with suitable macrophages mechanically kick-starts fibroblast activation in an otherwise nonpermissive soft environment. The molecular components mediating macrophage-fibroblast mechanotransduction are potential targets for antifibrosis strategies
Investigation of AI algorithms for the clustering and combination of pick and stow operations in warehouses and development of a learning module for undergraduates
No full textSmall and medium-sized enterprises face challenges in the performance-oriented improvement and integration of digital solutions in pick and stow operations, due to a high degree of manual processes. Traditional methods for improving these processes based on historical data are becoming increasingly ineffective due to short product life cycles and small order quantities. The use of AI offers great potential for data-driven analysis and optimization of pick and stow operations.
Currently used AI algorithms focus on optimizing either pick or stow operations but not both in combination, missing the opportunity for holistic improvement of warehouse operations by reducing walking distances and process times. This paper targets these limitations by investigating AI algorithms for near-real-time AI-based clustering and combination of pick and stow operations conjointly.
The research addressed in this paper aims to review AI algorithms for the clustering and combination of pick and stow operations to set the basis for the enhancement of these algorithms by incorporating close-to-real-time data analytics to improve logistics performance.
The findings of these investigations will be transferred directly into an undergraduate learning module for first-year students to give them a basic understanding of the possibilities of using AI for clustering and combination of pick and stow operations, hence preparing these students for their first industry internship. In addition to a theoretical introduction, the concept includes practical holistic scenarios in the Werk150, the learning factory of the ESB Business School on the campus of Reutlingen University
Alternating generation of single and multi-beam modes using the sequential rotation technique in antenna arrays
No full textA simple technique for generating single and multiple beams from antenna arrays is presented. The approach is based on the sequential rotation technique. It is shown that by applying a controlled second sequential rotation, circularly polarized antenna arrays operating alternately in a single-beam mode M1 and multi-beam mode M2 in the same frequency band can be designed. Proof of the concept is provided in light of case studies. The approach can be applied to large antenna arrays following a modular principle adapted to the array size and needed applications without loss of generality
Exploring morphological and molecular properties of different adipose cell models: monolayer, spheroids, gellan gum-based hydrogels, and explants
Get PDFWhite adipose tissue (WAT) plays a crucial role in energy homeostasis and secretes numerous adipokines with far-reaching effects. WAT is linked to diseases such as diabetes, cardiovascular disease, and cancer. There is a high demand for suitable in vitro models to study diseases and tissue metabolism. Most of these models are covered by 2D-monolayer cultures. This study aims to evaluate the performance of different WAT models to better derive potential applications. The stability of adipocyte characteristics in spheroids and two 3D gellan gum hydrogels with ex situ lobules and 2D-monolayer culture is analyzed. First, the differentiation to achieve adipocyte-like characteristics is determined. Second, to evaluate the maintenance of differentiated ASC-based models, an adipocyte-based model, and explants over 3 weeks, viability, intracellular lipid content, perilipin A expression, adipokine, and gene expression are analyzed. Several advantages are supported using each of the models. Including, but not limited to, the strong differentiation in 2D-monolayers, the self-assembling within spheroids, the long-term stability of the stem cell-containing hydrogels, and the mature phenotype within adipocyte-containing hydrogels and the lobules. This study highlights the advantages of 3D models due to their more in vivo-like behavior and provides an overview of the different adipose cell models
Surface biofunctionalization of additive manufactured materials for implants with nano-thin polyelectrolyte multilayer coatings
Get PDFTitanium-based additive manufacturing of medical implants has attracted considerable attention over the past decade due to numerous advantages over standard manufacturing. Regarding the surface modification and biofunctionalization of additive manufactured titanium materials carried out by the application of coatings, however, very limited research has been reported so far. The interaction between the adherent tissues and the implant takes place at the interface between them, therefore the tissues response is strongly mediated and controlled by the surface properties of the implanted material. To the best of the authors' knowledge, this is the first study on the surface modification of additively manufactured titanium materials with ultrathin polyelectrolyte multilayer coatings. The application of these coating with a thickness of only a few nanometers proved to be able to impart chemical homogeneity to the surface and allowed targeted modification of the hydrophilicity of the additively manufactured titanium materials without changing their macro-topography and bulk properties. An important and first-of-its-kind finding of the present study, which is being reported for the first time, is the adhesion strength of polyelectrolyte coatings to the surface of additively manufactured titanium materials that were found to meet the requirements of the ISO regulations for coatings, applied to metal implants. The non-cytotoxicity and high adhesion strength classify the polyelectrolyte multilayer coatings as very promising for application as coatings of additively manufactured medical devices
A systematic technology review of general-purpose open-source TOSCA orchestrators
No full textThe manual deployment of applications distributed across the cloud, fog, and edge is error-prone and complex. TOSCA is a standard for modeling the deployment of cloud applications in a vendor-neutral and technology-independent manner that is also suitable for the fog and edge continuum. However, there exist various TOSCA orchestrators with different functionalities. Thus, selecting an appropriate TOSCA orchestrator requires technical expertise since all the available orchestrators must be analyzed regarding technical, functional, legal, and organizational requirements. In this paper, we tackle this issue and present a systematic technology review of TOSCA orchestrators. Our goal is to support project managers, developers, and researchers in selecting a suitable TOSCA orchestrator. For this, we select actively maintained general-purpose open-source TOSCA orchestrators. Moreover, we introduce the TOSCA Orchestrator Classification Framework and present a selection support system
Is artificial intelligence a hazardous technology? Economic trade-off model
Get PDFArtificial intelligence (AI) demonstrates various opportunities and risks. Our study explores the trade-off of AI technology, including existential risks. We develop a theory and a Bayesian simulation model in order to explore what is at stake. The study reveals four tangible outcomes: (i) regulating existential risks has a boundary solution of either prohibiting the technology or allowing a laissez-faire regulation. (ii) the degree of ‘normal’ risks follows a trade-off and is dependent on AI-intensity. (iii) we estimate the probability of ‘normal’ risks to be between 0.002% to 0.006% over a century. (iv) regulating AI requires a balanced and international approach due to the dynamic risks and its global nature
Dynamic human–object interaction detection for feature exclusion in visual simultaneous localization and mapping (SLAM)
Get PDFVisual simultaneous localization and mapping (SLAM) remains a focal point in robotics research, particularly in the realm of mobile robots. Despite the existence of robust methods such as ORBSLAM3, their effectiveness is limited in dynamic scenarios. The influence of moving entities in these scenarios poses challenges to data association, leading to compromised pose estimation accuracy. This paper proposes a novel approach that utilizes spatial reasoning to reduce the influence of dynamic entities present in an environment. Our approach, known as human–object interaction detection, identifies the dynamic nature of an object by evaluating the intersecting area between the bounding boxes of a person and the object. We tested our approach by extending the ORBSLAM3 RGB-D SLAM algorithm. Consequently, all ORB features associated with dynamic objects are filtered out from the ORBSLAM3 tracking thread. To validate our approach, we conducted evaluations on highly dynamic sequences extracted from the TUM RGB-D dataset. Our results exhibited a significant performance enhancement over ORBSLAM3. Furthermore, in comparison to other state-of-the-art research, our results remained competitive, given the simplicity of our approach
A reference model for predictive maintenance model development
Get PDFDeterioration modeling plays a pivotal role in various industries, enabling predictive maintenance strategies and cost-effective resource allocation. Furthermore, with an escalating influx of data across multiple domains, opportunities for predictive analysis continue to expand. The development of wear models becomes a more and more complex process especially when acquiring and handling large amounts of customer data of different products and stakeholders since additional topics such as data privacy have to be included. Therefore, the development process causes high efforts in time, capacity and coordination between the different disciplines such as domain experts, data scientists and IT-administration. This paper presents a reference model for predictive maintenance model development. Based on adopted best practice approaches from the industrial production context, the reference model is structured around the four phases of the CRISP-DM model. Altogether it encompasses 48 defined steps. Covering the whole life cycle, beginning with component identification, use case description and culminating in model deployment and maintenance, each step is meticulously crafted to ensure quality and speed up the predictive maintenance model development. By adhering to this systematic approach, wear models for components can be developed with confidence, with lower effort and costs and mitigating uncertainties. The reference model is validated in the automotive industry since there already exist large amounts of fleet data of different products and customer. By providing a reliable and systematic approach to predictive maintenance model development, this reference model empowers stakeholders to optimize maintenance schedules, reduce downtime, and enhance overall operational efficiency
A technique for alternating generation of single and multi-beams from circularly polarized antenna arrays
Get PDFA simple technique for generating single and multiple beams from antenna arrays is presented. The approach is based on the multistage sequential rotation technique. A new feature in using multistage sequential rotation is provided. It is demonstrated that by applying a controlled second sequential rotation, circularly polarized antenna arrays operating alternately in a single-beam mode M1 and multi-beam mode M2 in the same frequency band can be designed. Proof-of-concept is provided mathematically and through numerical simulations in light of case studies. The approach can not only be applied to large antenna arrays following a modular principle adapted to the array size and needed applications without loss of generality, but it also paves the way for the manufacture of circularly polarized antennas operating alternately or simultaneously in both modes in the same frequency band. In addition, antennas designed using the proposed approach may have a wide range of applications ranging from monopulse radar to antennas for compensation of interference and blockage in dynamic communication environments