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In der heutigen Zeit nimmt die Bedeutung schlanker und effektiver Prozesse in Unternehmen vor dem Hintergrund des Wettbewerbs sowie Kostendrucks stetig zu. Um dieser Herausforderung entgegenzuwirken, fokussieren sich Unternehmen auf die Identifikation neuer innovativer Potenziale. Aufgrund der Tatsache, dass monotone und regelbasierte Prozesse durch Softwareroboter automatisiert werden können, ist das Interesse an Robotic Process Automation (RPA) in den letzten Jahren stetig gestiegen. Bevor sich Unternehmen allerdings für oder gegen den Einsatz von RPA entscheiden, ist es zunächst notwendig, dass die Entscheidungsträger ein Verständnis von RPA erlangen sowie die entsprechenden Einsatzpotenziale und Risiken einschätzen können. Dieser Artikel trägt diesem Bedürfnis Rechnung, indem es diese auf Basis einer Literaturrecherche ermittelt und bewertet. Im Ausblick wird das zukünftige Potenzial von RPA eingeschätzt.
Next tram stop
(2020)
İnsanlar yeryüzünün doğal kaynaklarını onun bunları yenileyebileceğinden daha hızlı tüketmektedirler. İnsanların bu tutumlarının bedelini gelecek kuşaklar ödeyeceklerdir. Gelecek kuşaklara bu bedeli ödetmemek için artık parasal kârları ençoklamak, niceliksel olarak büyümek ve bolluk yaratmak doğrultusunda işleyen şimdiki ekonomik faaliyetleri bir başka biçime dönüştürmek kaçınılmazdır. Peren Teoremi göstermektedir ki Dünya örneğinde de olduğu gibi kapalı bir sistem doğal kaynak tüketimi eş düzeyde bir doğal kaynak üretimi ile yaşayabilir. Üretim ile tüketim arasındaki denge çok uzun bir süre bozulursa gezegen doğal bir ölüm ile karşılaşır. Bunu sağlamak üzere Dünya üzerinde yaşayan ve/veya dünya sayesinde yaşayan tüm insanların kişi başına doğal kaynak tüketimlerini artan küresel nüfusla orantılı bir biçimde azaltmak gerekir.
Coumarin as a structural component of substrates and probes for serine and cysteine proteases
(2020)
Further development on globally convergent algorithms for solution of stationary network problems is presented. The algorithms make use of global non-degeneracy of Jacobi matrix of the system, composed of Kirchhoff's flow conservation conditions and transport element equations. This property is achieved under certain monotonicity conditions on element equations and guarantees an existence of a unique solution of the problem as well as convergence to this solution from an arbitrary starting point. In application to gas transport networks, these algorithms are supported by a proper modeling of gas compressors, based on individually calibrated physical characteristics. This paper extends the modeling of compressors by hierarchical methods of topological reduction, combining the working diagrams for parallel and sequential connections of compressors. Estimations are also made for application of topological reduction methods beyond the compressor stations in generic network problems. Efficiency of the methods is tested by numerical experiments on realistic networks.
Maßgefertigte Abläufe
(2017)
Cytokine-induced killer (CIK) cells are heterogeneous, major histocompatibility complex (MHC)-unrestricted T lymphocytes that have acquired the expression of several natural killer (NK) cell surface markers following the addition of interferon gamma (IFN-γ), OKT3 and interleukin-2 (IL-2). Treatment with CIK cells demonstrates a practical approach in cancer immunotherapy with limited, if any, graft versus host disease (GvHD) toxicity. CIK cells have been proposed and tested in many clinical trials in cancer patients by autologous, allogeneic or haploidentical administration. The possibility of combining them with specific monoclonal antibodies nivolumab and ipilimumab will further expand the possibility of their clinical utilization. Initially, phenotypic analysis was performed to explore CD3, CD4, CD56, PD-1 and CTLA-4 expression on CIK cells and PD-L1/PD-L2 expression on tumor cells. We further treated CIK cells with nivolumab and ipilimumab and measured the cytotoxicity of CIK cells cocultured to renal carcinoma cell lines, A-498 and Caki-2. We observed a significant decrease in viability of renal cell lines after treating with CIK cells (p < 0.0001) in comparison to untreated renal cell lines and anti-PD-1 or anti-CTLA-4 treatment had no remarkable effect on the viability of tumor cells. Using CCK-8, Precision Count Beads™ and Cell Trace™ violet proliferation assays, we proved significant increased proliferation of CIK cells in the presence of a combination of anti-PD-1 and anti-CTLA-4 antibodies compared to untreated CIK cells. The IFN-γ secretion increased significantly in the presence of A-498 and combinatorial blockade of PD-1 and CTLA-4 compared to nivolumab or ipilimumab monotreatment (p < 0.001). In conclusion, a combination of immune checkpoint inhibition with CIK cells augments cytotoxicity of CIK cells against renal cancer cells.
2-methylacetoacetyl-coenzyme A thiolase (beta-ketothiolase) deficiency: one disease - two pathways
(2020)
Background: 2-methylacetoacetyl-coenzyme A thiolase deficiency (MATD; deficiency of mitochondrial acetoacetyl-coenzyme A thiolase T2/ “beta-ketothiolase”) is an autosomal recessive disorder of ketone body utilization and isoleucine degradation due to mutations in ACAT1.
Methods: We performed a systematic literature search for all available clinical descriptions of patients with MATD. Two hundred forty-four patients were identified and included in this analysis. Clinical course and biochemical data are presented and discussed.
Results: For 89.6% of patients at least one acute metabolic decompensation was reported. Age at first symptoms ranged from 2 days to 8 years (median 12 months). More than 82% of patients presented in the first 2 years of life, while manifestation in the neonatal period was the exception (3.4%). 77.0% (157 of 204 patients) of patients showed normal psychomotor development without neurologic abnormalities.
Conclusion: This comprehensive data analysis provides a systematic overview on all cases with MATD identified in the literature. It demonstrates that MATD is a rather benign disorder with often favourable outcome, when compared with many other organic acidurias.
Optical gas sensors based on chiral-nematic liquid crystals (N* LCs) forming one-dimensional photonic crystals do not require electrical energy and have a considerable potential to supplement established types of sensors. A chiral-nematic phase with tunable selective reflection is induced in a nematic host LC by adding reactive chiral dopants. The selective chemical reaction between dopant and analyte is capable to vary the pitch length (the lattice constant) of the soft, self-assembled, one-dimensional photonic crystal. The progress of the ongoing chemical reaction can be observed even by naked eye because the color of the samples varies. In this work, we encapsulate the responsive N* LC in microscale polyvinylpyrrolidone (PVP) fibers via coaxial electrospinning. The sensor is, thus, given a solid form and has an improved stability against nonavoidable environmental influences. The reaction behavior of encapsulated and nonencapsulated N* LC toward a gaseous analyte is compared, systematically. Making use of the encapsulation is an important step to improve the applicability.
Der bestandskräftige Bescheid eines Unfallversicherungsträgers, mit dem gegenüber einem Versicherten die Anerkennung eines Arbeitsunfalls abgelehnt worden ist, entfaltet keine Bindungswirkung gegenüber dem Krankenversicherungsträger, der die Kosten der Krankenbehandlung aus dem Unfallereignis von dem Unfallversicherungsträger erstattet bekommen möchte.
This work thoroughly investigates a semi-Lagrangian lattice Boltzmann (SLLBM) solver for compressible flows. In contrast to other LBM for compressible flows, the vertices are organized in cells, and interpolation polynomials up to fourth order are used to attain the off-vertex distribution function values. Differing from the recently introduced Particles on Demand (PoD) method , the method operates in a static, non-moving reference frame. Yet the SLLBM in the present formulation grants supersonic flows and exhibits a high degree of Galilean invariance. The SLLBM solver allows for an independent time step size due to the integration along characteristics and for the use of unusual velocity sets, like the D2Q25, which is constructed by the roots of the fifth-order Hermite polynomial. The properties of the present model are shown in diverse example simulations of a two-dimensional Taylor-Green vortex, a Sod shock tube, a two-dimensional Riemann problem and a shock-vortex interaction. It is shown that the cell-based interpolation and the use of Gauss-Lobatto-Chebyshev support points allow for spatially high-order solutions and minimize the mass loss caused by the interpolation. Transformed grids in the shock-vortex interaction show the general applicability to non-uniform grids.
Failure prognostic builds up on constant data acquisition and processing and fault diagnosis and is an essential part of predictive maintenance of smart manufacturing systems enabling condition based maintenance, optimised use of plant equipment, improved uptime and yield and to prevent safety problems. Given known control inputs into a plant and real sensor outputs or simulated measurements, the model-based part of the proposed hybrid method provides numerical values of unknown parameter degradation functions at sampling time points by the evaluation of equations that have been derived offline from a bicausal diagnostic bond graph. These numerical values are computed concurrently to the constant monitoring of a system and are stored in a buffer of fixed length. The data-driven part of the method provides a sequence of remaining useful life estimates by repeated projection of the parameter degradation into the future based on the use of values in a sliding time window. Existing software can be used to determine the best fitting function and can account for its random parameters. The continuous parameter estimation and their projection into the future can be performed in parallel for multiple isolated simultaneous parametric faults on a multicore, multiprocessor computer.
The proposed hybrid bond graph model-based, data-driven method is verified by an offline simulation case study of a typical power electronic circuit. It can be used to implement embedded systems that enable cooperating machines in smart manufacturing to perform prognostic themselves.
