Mechanical design and analysis of a novel three-legged, compact, lightweight, omnidirectional, serial–parallel robot with compliant agile legs

In this work, the concept and mechanical design of a novel compact, lightweight, omnidirectional three-legged robot, featuring a hybrid serial–parallel topology including leg compliance is proposed. The proposal focusses deeply on the design aspects of the mechanical realisation of the robot based on its 3D-CAD assembly, while also discussing the results of multi-body simulations, exploring the characteristic properties of the mechanical system, regarding the locomotion feasibility of the robot model. Finally, a real-world prototype depicting a single robot leg is presented, which was built by highly leaning into a composite design, combining complex 3D-printed parts with stiff aluminium and polycarbonate parts, allowing for a mechanically dense and slim construction. Eventually, experiments on the prototype leg are demonstrated, showing the mechanical model operating in the real world

Topological analysis of a novel compact omnidirectional three-legged robot with parallel hip structures regarding locomotion capability and load distribution

In this study, a novel design for a compact, lightweight, agile, omnidirectional three-legged robot involving legs with four degrees of freedom, utilizing an spherical parallel mechanism with an additional non-redundant central support joint for the robot hip structure is proposed. The general design and conceptual ideas for the robot are presented, targeting a close match of the well-known SLIP-model. CAD models, 3d-printed prototypes, and proof-of-concept multi-body simulations are shown, investigating the feasibility to employ a geometrically dense spherical parallel manipulator with completely spherically shaped shell-type parts for the highly force-loaded application in the legged robot hip mechanism. Furthermore, in this study, an analytic expression is derived, yielding the calculation of stress forces acting inside the linkage structures, by directly constructing the manipulator hip Jacobian inside the force domain

Artificial neural network for fast and versatile model parameter adjustment utilizing PAT signals of chromatography processes for process control under production conditions

Preparative chromatography is a well-established operation in chemical and biotechnology manufacturing. Chromatography achieves high separation performances, but often has to deal with the yield versus purity trade-off as the optimization criterium regarding through-put. The initial trade-off is often disturbed by the well-known phenomenon of chromatogram shifts over process lifetime, and has to be corrected by operators via adjustment of peak fraction cutting. Nevertheless, with regard to autonomous operation and batch to continuous processing modes, an advanced process control strategy is needed to identify and correct shifts from the optimal operation point automatically. Previous studies have already presented solutions for batch-to-batch variance and process control options with the aid of rigorous physico-chemical process modeling. These models can be implemented as distinct digital twins as well as statistical process operation data analyzers. In order to utilize such models for advanced process control (APC), the model parameters have to be updated with the aid of inline Process Analytical Technology (PAT) data to describe the actual operational status. This updating process also includes any operational change phenomena that occur, and its relation to their physico-chemical root cause. Typical phenomena are fluid dynamic changes due to packing breakage, channelling or compression as well as mass transfer and phase equilibrium-related separation performance decrease due to adsorbent aging or feed and buffer composition changes. In order to track these changes, an Artificial Neural Network (ANN) is trained in this work. The ANN training is in this first step, based on the simulation results of a distinct and previously experimentally validated process model. The model is implemented in the open source tool CasADi for Python. This allows the implementation of interfaces to process control systems, among others, with relatively low effort. Therefore, PAT signals can easily be incorporated for sufficient adjustment of the process model for appropriate process control. Further steps would be the implementation of optimization routines based on PAT and ANN predictions to derive optimal operation points with the model

Objektorientierte Graphendarstellung von Simulink-Modellen zur einfachen Analyse und Transformation

In software and hardware development MATLAB and Simulink are used to model cyber physical systems for many years, , especially in automation technology and the automotive industry. Compliance with the required product quality and project efficiency is facilitated by analyzing and transforming Simulink models. The existing API, provided by MATLAB is only suitable for programmatic changing of Simulink models. We show using our own tool which is used in industry, how such as a Simulink model can be edited more easily. For this purpose the model, is converted to an object-oriented class structure that provides convenient access and editing APIs and allows applying well-known algorithms and analyses from graph theory directly. It is also designed as a bi-directional tool, so it transforms a Simulink model into a graph representation and vice versa. ----- In der Software- und Hardwareentwicklung wird seit Jahren verst\"arkt MATLAB und Simulink f\"ur die Modellierung von cyberphysikalischen Systemen, insbesondere in der Automatisierungstechnik und der Automobilindustrie eingesetzt. Die Einhaltung der notwendigen Produktqualit\"at und Projekteffizienz wird durch Analysen und Transformationen auf Simulink-Modellen erleichtert. Die bestehende, von MATLAB bereitgestellte, API ist f\"ur die programmatische Ver\"anderung von Simulink-Modellen nur bedingt geeignet. Wir zeigen deshalb anhand eines eigenen, im industriellen Einsatz befindlichen Werkzeugs, wie ein Simulink-Modell leichter bearbeitet werden kann. Dazu wird es in eine objektorientierte Klassenstruktur \"uberf\"uhrt, die einen komfortablen Zugang und Bearbeitungs-APIs bietet und es erlaubt bekannte Algorithmen und Analysen aus der Graphentheorie direkt anzuwenden. Das Werkzeug ist bidirektional entworfen, es transformiert also ein Simulink-Modell in eine Graphenrepresentation und umgekehrt.Comment: 10 pages in German, 7 figures. AALE 2013 in Stralsund Germany, 10. Fachkonferenz, Das Forum f\"ur Fachleute der Automatisierungstechnik aus Hochschulen und Wirtschaft, 201

Artificial Neural Network for Fast and Versatile Model Parameter Adjustment utilizin PAT signals of Chromatography Processes for Process Control under Production Conditions

Preparative chromatography is a well-established operation in the chemical and biotechnology manufacturing. Chromatography achieves high separation performances but often has to deal with the yield versus purity trade-off as the optimization criterium regarding through-put. The initial trade-off is often disturbed by the well-known phenomenon of chromatogram shifts over process lifetime and has to be corrected by operators via adjustment of peak fraction cutting. Nevertheless, with regards to autonomous operation and batch to continuous processing modes, any advanced process control strategy is needed to identify and correct shifts from the optimal operation point automatically. Previous studies already presented solutions for batch-to-batch variance and process control options with the aid of rigorous physico-chemical process model-ling. These models can be implemented as distinct digital twins as well as statistical process op-eration data analysers. In order to utilize such models for advanced process control, the model parameters have to be up dated with aid of inline PAT data to describe the actual operational status. Also including any occurring operational change phenomenon and its relation to their physico-chemical root cause. Typical phenomena are fluid dynamic changes due to packing breakage, channelling or compression as well as mass transfer and phase equilibrium related separation performance decrease due to adsorbent ageing or feed and buffer composition changes. In order to track these changes an Artificial Neural Network (ANN) is trained in this work. The ANN training is in this first step based on the simulation results of a distinct and pre-viously experimentally validated process model. The model is implemented in the open source tool CasADi for python. This allows the implementation of interfaces to e.g. process control systems with relatively low effort. Therefore, PAT signals can easily incorporated for the suffi-cient adjustment of the process model for appropriate process control. Further steps would be the implementation of optimization routines based on the PAT and ANN predictions to derive optimal operation points with the model

Detection and Prevalence Patterns of Group I Coronaviruses in Bats, Northern Germany

The virus is probably maintained on the population level by amplification and transmission in maternity colonies

Exome Sequencing Reveals Comprehensive Genomic Alterations across Eight Cancer Cell Lines

It is well established that genomic alterations play an essential role in oncogenesis, disease progression, and response of tumors to therapeutic intervention. The advances of next-generation sequencing technologies (NGS) provide unprecedented capabilities to scan genomes for changes such as mutations, deletions, and alterations of chromosomal copy number. However, the cost of full-genome sequencing still prevents the routine application of NGS in many areas. Capturing and sequencing the coding exons of genes (the “exome”) can be a cost-effective approach for identifying changes that result in alteration of protein sequences. We applied an exome-sequencing technology (Roche Nimblegen capture paired with 454 sequencing) to identify sequence variation and mutations in eight commonly used cancer cell lines from a variety of tissue origins (A2780, A549, Colo205, GTL16, NCI-H661, MDA-MB468, PC3, and RD). We showed that this technology can accurately identify sequence variation, providing ∼95% concordance with Affymetrix SNP Array 6.0 performed on the same cell lines. Furthermore, we detected 19 of the 21 mutations reported in Sanger COSMIC database for these cell lines. We identified an average of 2,779 potential novel sequence variations/mutations per cell line, of which 1,904 were non-synonymous. Many non-synonymous changes were identified in kinases and known cancer-related genes. In addition we confirmed that the read-depth of exome sequence data can be used to estimate high-level gene amplifications and identify homologous deletions. In summary, we demonstrate that exome sequencing can be a reliable and cost-effective way for identifying alterations in cancer genomes, and we have generated a comprehensive catalogue of genomic alterations in coding regions of eight cancer cell lines. These findings could provide important insights into cancer pathways and mechanisms of resistance to anti-cancer therapies

Wnt Pathway in Bone Repair and Regeneration – What Do We Know So Far

Wnt signaling plays a central regulatory role across a remarkably diverse range of functions during embryonic development, including those involved in the formation of bone and cartilage. Wnt signaling continues to play a critical role in adult osteogenic differentiation of mesenchymal stem cells. Disruptions in this highly-conserved and complex system leads to various pathological conditions, including impaired bone healing, autoimmune diseases and malignant degeneration. For reconstructive surgeons, critically sized skeletal defects represent a major challenge. These are frequently associated with significant morbidity in both the recipient and donor sites. The Wnt pathway is an attractive therapeutic target with the potential to directly modulate stem cells responsible for skeletal tissue regeneration and promote bone growth, suggesting that Wnt factors could be used to promote bone healing after trauma. This review summarizes our current understanding of the essential role of the Wnt pathway in bone regeneration and repair