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The efficient execution of process planning activities requires the knowledge from several distinct domains. However, in this context, a common issue is the existence of collective knowledge in the one domain with a lack of networked expertise with other domains. Motivated by this, the paper proposes an approach to support process planning by comparing the generated part design with older, validated products. The utilization of this earlier CAD part models has the potential to reduce development costs, shorten the production start-up time and improve the product quality. The new concept provides the manufacturing personnel with a method for comparing the newly designed part with a pool of validated models to identify the most similar one. Each previous CAD part model is linked with the necessary manufacturing information, so that the initial values for the manufacturing process are available without a time consuming testing phase. The method is divided in three main steps: the global similarity comparison, the segmentation of the part and the local similarity comparison. In the first step, the geometry is projected onto a sphere and then transformed to a matrix. Afterwards these matrices are compared and clustered into corresponding groups. In the following step, a Machine Learning algorithm segments the objects into specific, manufacturing relevant groups. In every cluster, the segmented geometries are again compared for similarity. The combination of the first and the second ranking results in a global similarity hierarchy for the newly designed part. In this paper, the entire procedure is shown with the example of sheet-bulk metal formed parts. This new manufacturing process particularly benefits from this method, as the amount of data is still limited and therefore little expert knowledge exists. [ABSTRACT FROM AUTHOR]

To describe an experience using a protocol using de novo belatacept (DNB) based maintenance immunosuppression in the setting of lymphocyte depletion. A retrospective, observational study was performed on 37 kidney transplant recipients treated with the DNB protocol, which was defined as belatacept initiated within 7 days after a kidney transplant with steroids and mycophenolate with anti-thymocyte globulin (ATG) induction without concomitant calcineurin inhibitors (CNIs). Patients who received a deceased donor kidney meeting one or more of the following criteria: anticipated cold ischemia time (CIT) greater than 24 h, donation after cardiac death, donor acute kidney injury, and a Kidney Donor Profile Index (KDPI) >85% during the study period were included. Patient survival at 1 year was 97.3% and graft survival was 94.6%. Delayed graft function (DGF) occurred in 40.54% of the patients. Two patients experienced a Banff 1B acute cellular rejection. BK viremia was detected in 32.4% of patients. The mean estimated glomerular filtration rate (eGFR) calculated with the use of modification of diet in renal disease (MDRD) equation at 1 year in the study group was 54.7 ml/min/1.73 m 2 . We believe that utilization of the DNB protocol, which allows early CNI avoidance, may decrease organ discard rates., (© 2022 Asian Pacific Society of Nephrology.)

Fringe projection profilometry in combination with other optical measuring technologies has established itself over the last decades as an essential complement to conventional, tactile measuring devices. The non-contact, holistic reconstruction of complex geometries within fractions of a second in conjunction with the lightweight and transportable sensor design open up many fields of application in production metrology. Furthermore, triangulation-based measuring principles feature good scalability, which has led to 3D scanners for various scale ranges. Innovative and modern production processes, such as sheet-bulk metal forming, thus, utilize fringe projection profilometry in many respects to monitor the process, quantify possible wear and improve production technology. Therefore, it is essential to identify the appropriate 3D scanner for each application and to properly evaluate the acquired data. Through precise knowledge of the measurement volume and the relative uncertainty with respect to the specimen and scanner position, adapted measurement strategies and integrated production concepts can be realized. Although there are extensive industrial standards and guidelines for the quantification of sensor performance, evaluation and tolerancing is mainly global and can, therefore, neither provide assistance in the correct, application-specific positioning and alignment of the sensor nor reflect the local characteristics within the measuring volume. Therefore, this article compares fringe projection systems across various scale ranges by positioning and scanning a calibrated sphere in a high resolution grid.