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Off-lattice Boltzmann methods increase the flexibility and applicability of lattice Boltzmann methods by decoupling the discretizations of time, space, and particle velocities. However, the velocity sets that are mostly used in off-lattice Boltzmann simulations were originally tailored to on-lattice Boltzmann methods. In this contribution, we show how the accuracy and efficiency of weakly and fully compressible semi-Lagrangian off-lattice Boltzmann simulations is increased by velocity sets derived from cubature rules, i.e. multivariate quadratures, which have not been produced by the Gauss-product rule. In particular, simulations of 2D shock-vortex interactions indicate that the cubature-derived degree-nine D2Q19 velocity set is capable to replace the Gauss-product rule-derived D2Q25. Likewise, the degree-five velocity sets D3Q13 and D3Q21, as well as a degree-seven D3V27 velocity set were successfully tested for 3D Taylor-Green vortex flows to challenge and surpass the quality of the customary D3Q27 velocity set. In compressible 3D Taylor-Green vortex flows with Mach numbers Ma={0.5;1.0;1.5;2.0} on-lattice simulations with velocity sets D3Q103 and D3V107 showed only limited stability, while the off-lattice degree-nine D3Q45 velocity set accurately reproduced the kinetic energy provided by literature.
Hintergrund: Empirische Studien zeigen, dass mehr als zwei Drittel der Beschäftigten trotz Krankheit zur Arbeit gehen. Dieser sog. Präsentismus bringt sowohl gesundheitliche und motivationale Risiken für die Mitarbeiter als auch wirtschaftliche Risiken für die Organisation mit sich.
Ziel der Arbeit: Die durchgeführten Studien fokussieren Möglichkeiten zur Verringerung der negativen gesundheitlichen Effekte und entwickeln Maßnahmen zur generellen Vermeidung von Präsentismus am spezifischen Setting Hochschule.
Methode: An einer deutschen Hochschule erfolgte eine quantitative Befragung (n = 308) zur Prävalenz von Präsentismus, dessen Zusammenhang mit körperlichen Beschwerden untersucht wurde. Weiterhin wurden potenziell moderierende Effekte der Ressourcen Erholung, Achtsamkeit und Work-Life-Balance (WLB) betrachtet. Eine qualitative Studie explorierte auf Grundlage von Interviews (n = 11, qualitative Inhaltsanalyse) Gründe für Präsentismus und potenzielle Maßnahmen, um diesem entgegenzuwirken.
Ergebnisse: Die quantitativen Ergebnisse zeigen, dass Präsentismus im Hochschulkontext vertreten ist und körperliche Beschwerden begünstigt. Die Ressourcen Erholung, Achtsamkeit und WLB können bei hoher Ausprägung die negativen gesundheitlichen Effekte von Präsentismus abschwächen. Bei niedriger Ausprägung verstärken sie die Effekte. Die qualitative Analyse machte deutlich, dass quantitative Arbeitsbelastung, Pflichtgefühl sowie das Gefühl, noch leistungsfähig zu sein, zentrale Gründe für Präsentismus sind und zum Beispiel die Unterstützung eines gesundheitsförderlichen Organisationsklimas oder Vertretungsregelungen geeignete Gegenmaßnahmen darstellen.
Diskussion: Die Ergebnisse werden vor dem Hintergrund verhaltens- und verhältnispräventiver Maßnahmen diskutiert und praktische Implikationen abgeleitet.
Ghana suffers from frequent power outages, which can be compensated by off-grid energy solutions. Photovoltaic-hybrid systems become more and more important for rural electrification due to their potential to offer a clean and cost-effective energy supply. However, uncertainties related to the prediction of electrical loads and solar irradiance result in inefficient system control and can lead to an unstable electricity supply, which is vital for the high reliability required for applications within the health sector. Model predictive control (MPC) algorithms present a viable option to tackle those uncertainties compared to rule-based methods, but strongly rely on the quality of the forecasts. This study tests and evaluates (a) a seasonal autoregressive integrated moving average (SARIMA) algorithm, (b) an incremental linear regression (ILR) algorithm, (c) a long short-term memory (LSTM) model, and (d) a customized statistical approach for electrical load forecasting on real load data of a Ghanaian health facility, considering initially limited knowledge of load and pattern changes through the implementation of incremental learning. The correlation of the electrical load with exogenous variables was determined to map out possible enhancements within the algorithms. Results show that all algorithms show high accuracies with a median normalized root mean square error (nRMSE) <0.1 and differing robustness towards load-shifting events, gradients, and noise. While the SARIMA algorithm and the linear regression model show extreme error outliers of nRMSE >1, methods via the LSTM model and the customized statistical approaches perform better with a median nRMSE of 0.061 and stable error distribution with a maximum nRMSE of <0.255. The conclusion of this study is a favoring towards the LSTM model and the statistical approach, with regard to MPC applications within photovoltaic-hybrid system solutions in the Ghanaian health sector.
Data emerged as a central success factor for companies to benefit from digitization. However, the skills in successfully creating value from data – especially at the management level – are not always profound. To address this problem, several canvas models have already been designed. Canvas models are usually created to write down an idea in a structured way to promote transparency and traceability. However, some existing data science canvas models mainly address developers and are thus unsuitable for decision-makers and communication within interdisciplinary teams. Based on a literature review, we identified influencing factors that are essential for the success of data science projects. With the information gained, the Data Science Canvas was developed in an expert workshop and finally evaluated by practitioners to find out whether such an instrument could support data-driven value creation.
The actomyosin system generates mechanical work with the execution of the power stroke, an ATP-driven, two-step rotational swing of the myosin-neck that occurs post ATP hydrolysis during the transition from weakly to strongly actin-bound myosin states concomitant with Pi release and prior to ADP dissociation. The activating role of actin on product release and force generation is well documented; however, the communication paths associated with weak-to-strong transitions are poorly characterized. With the aid of mutant analyses based on kinetic investigations and simulations, we identified the W-helix as an important hub coupling the structural changes of switch elements during ATP hydrolysis to temporally controlled interactions with actin that are passed to the central transducer and converter. Disturbing the W-helix/transducer pathway increased actin-activated ATP turnover and reduced motor performance as a consequence of prolonged duration of the strongly actin-attached states. Actin-triggered Pi release was accelerated, while ADP release considerably decelerated, both limiting maximum ATPase, thus transforming myosin-2 into a high-duty-ratio motor. This kinetic signature of the mutant allowed us to define the fractional occupancies of intermediate states during the ATPase cycle providing evidence that myosin populates a cleft-closure state of strong actin interaction during the weak-to-strong transition with bound hydrolysis products before accomplishing the power stroke.
This book shows in a comprehensive presentation how Bond Graph methodology can support model-based control, model-based fault diagnosis, fault accommodation, and failure prognosis by reviewing the state-of-the-art, presenting a hybrid integrated approach to Bond Graph model-based fault diagnosis and failure prognosis, and by providing a review of software that can be used for these tasks.
Current knowledge about cell-biomaterial interactions is often based on 2D cell culture systems like protein-coated glass slides. However, such smooth surfaces cannot mimic the nanofibrous environment of the native extracellular matrix (ECM). It is therefore a major challenge to transfer the results from 2D surfaces to 3D protein scaffolds with biomimetic nanofiber architecture. To understand the influence of different protein topographies on the cell response we introduce a new process to fabricate binary collagen scaffolds of variable thickness with spatially controlled regions of nanofibrous and smooth topography. We used pH-induced self-assembly to prepare collagen nanofibers with diameters between 130 and 150 nm on glass surfaces, which were partly covered with a polymer mask. After cross-linking with glutaraldehyde, smooth collagen films were prepared on the remaining glass regions. Atomic force microscopy revealed a much lower surface roughness of smooth collagen compared to nanofibers.
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.
