A paper-based, cell-free biosensor system for the detection of heavy metals and date rape drugs.

Gräwe A, Dreyer A, Vornholt T, et al. A paper-based, cell-free biosensor system for the detection of heavy metals and date rape drugs. PloS one. 2019;14(3): e0210940.Biosensors have emerged as a valuable tool with high specificity and sensitivity for fast and reliable detection of hazardous substances in drinking water. Numerous substances have been addressed using synthetic biology approaches. However, many proposed biosensors are based on living, genetically modified organisms and are therefore limited in shelf life, usability and biosafety. We addressed these issues by the construction of an extensible, cell-free biosensor. Storage is possible through freeze drying on paper. Following the addition of an aqueous sample, a highly efficient cell-free protein synthesis (CFPS) reaction is initiated. Specific allosteric transcription factors modulate the expression of 'superfolder' green fluorescent protein (sfGFP) depending on the presence of the substance of interest. The resulting fluorescence intensities are analyzed with a conventional smartphone accompanied by simple and cheap light filters. An ordinary differential equitation (ODE) model of the biosensors was developed, which enabled prediction and optimization of performance. With an optimized cell-free biosensor based on the Shigella flexneri MerR transcriptional activator, detection of 6 mug/L Hg(II) ions in water was achieved. Furthermore, a completely new biosensor for the detection of gamma-hydroxybutyrate (GHB), a substance used as date-rape drug, was established by employing the naturally occurring transcriptional repressor BlcR from Agrobacterium tumefaciens

CS3 2021- Cloud Storage Synchronization and Sharing

To make clients pick up changes to a shared file the etag of all recipients root folders needs to be updated. The current implementation in OCIS jails shares into a `/Shares` folder to calculate a dynamic etag, based on all accepted shares. This multiplies the stat requests made to the underlying storage system by the number of shares on every propfind. By letting the storage registry cache the root etag of every storage id we can reduce this number to one stat request per storage. This cache would not only allow the gateway to calculate the etag for any path based on the mount point of storages: it would allow sharing the stat cache for all clients, the ocis instance could dynamically adjust the cache timeout to react to system load, and storages providers can push etag changes to the storage registry to prepare for push notifications to clients

CS3 2021- Cloud Storage Synchronization and Sharing

Looking up files by a stable id is an inefficient operation in most filesystems. While an efficient lookup by file id can be cached inside an OCIS storage provider this cache needs to be kept up to date. By deconstructing a filesystem and storing every node by its uuid we can evade the cache invalidation problem at the cost of more stat requests. The ocis storage driver allows an efficient lookup of file metadata by path and by file id while relying solely on the filesystem as a persistence layer. Furthermore, the layout on disk can be used to implement trash, versions and in the future deduplication. It serves as a blueprint for seperating metadata and content in an S3 or librados storage driver

CS3 2022 - Cloud Storage Synchronization and Sharing

When working on the spaces feature we reorganized reva's internal path semantics. While the current global path based namespace looks efficient, it ties namespace organization to a single instance. This prevents true federation. By replacing absolute paths with relative paths and a corresponding root we can delegate building a user individual namespace to the clients. This allows them to present a more meaningful layout to the end user, even aggregating spaces from multiple instances. Furthermore, operations like quota, trash and change propagation now also operate on individual spaces. We are moving this approach forward on the "edge" branch and will propose changes to the cs3api to optimize the implementation. We consider spaces the logical next step in enterprise file sync&share

European Society of Biomechanics S.M. Perren Award 2022: Standardized tibio-femoral implant loads and kinematics

Knowledge of both tibio-femoral kinematics and kinetics is necessary for fully understanding knee joint biomechanics, guiding implant design and testing, and driving and validating computational models. In 2017, the CAMS-Knee datasets were presented, containing synchronized in vivo implant kinematics measured using a moving fluoroscope and tibio-femoral contact loads measured using instrumented implants from six subjects. However, to date, no representative summary of kinematics and kinetics obtained from measurements at the joint level of the same cohort of subjects exists. In this study, we present the CAMS-Knee standardized subject “Stan”, whose reference data include tibio-femoral kinematics and loading scenarios from all six subjects for level and downhill walking, stair descent, squat and sit-to-stand-to-sit. Using the peak-preserving averaging method by Bergmann and co-workers, we derived scenarios for generally high (CAMS-HIGH100), peak, and extreme loading. The CAMS-HIGH100 axial forces reached peaks between 3022 and 3856 N (3.08–3.93 body weight) for the five investigated activities. Anterior-posterior forces were about a factor of ten lower. The axial moment around the tibia was highest for level walking and squatting with peaks of 9.4 Nm and 10.5 Nm acting externally. Internal tibial rotations of up to 8.4° were observed during squat and sitting, while the walking activities showed approximately half the internal rotation. The CAMS-HIGH100 loads were comparable to Bergmann and co-workers’, but have the additional benefit of synchronized kinematics. Stan’s loads are +11 to +56% higher than the ISO 14243 wear testing standard loads, while the kinematics exhibit markedly different curve shapes. Along with the original CAMS-Knee datasets, Stan’s data can be requested at cams-knee.orthoload.com.ISSN:0021-9290ISSN:1873-238

Fujaba Days 2011

Beitrag 3: Supported by the International Graduate School “Dynamic Intelligent Systems” and by the ‘Excellence Initiative’ of the German Federal and State Governments and the Graduate School of Computational Engineering at TU Darmstadt Beitrag 4: This work was developed in the course of the Collaborative Research Center 614 – Self-optimizing Concepts and Structures in Mechanical Engineering – University of Paderborn, and was published on its behalf and funded by the Deutsche Forschungsgemeinschaft. This work was developed in the project "ENTIME: Entwurfstechnik Intelligente Mechatronik" (Design Methods for Intelligent Systems). The project ENTIME is funded by the state of North Rhine Westphalia (NRW), Germany and the EUROPEAN UNION, European Regional Development Fund, "Investing in your future"