Enabling Multi-Stakeholder Cooperative Modelling in Automotive Software Development and Implications for Model Driven Software Development

One of the motivations for a model driven approach to software development is to increase the involvement for a range of stakeholders in the requirements phases. This inevitably leads to a greater diversity of roles being involved in the production of models, and one of the issues with such diversity is that of providing models which are both accessible and appropriate for the phenomena being modelled. Indeed, such accessibility issues are a clear focus of this workshop. However, a related issue when producing models across multiple parties,often at dierent sites, or even dierent organisations is the management of such model artefacts. In particular, different parties may wish to experiment with model choices. For example, this idea of prototypingprocesses by experimenting with variants of models is one which has been used for many years by business process modellers, in order to highlight the impact of change, and thus improve alignment of process and supporting software specications. The problem often occurs when such variants needed to be merged, for example, to be used within a shared repository. This papers reports upon experiences and ndings of this merging problem as evaluated at Bosch Automotive. At Bosch we have dierent sites where modellers will make changes to shared models, and these models will subsequently require merging into a common repository. Currently, this work has concentrated on one type of diagram, the class diagram. However, it seems clear that the issue of how best to merge models where collaborative multi-party working takes places is one which has a significant potential impact upon the entire model driven process, and, given the diversity of stakeholders, could be particularly problematic for the requirements phase. In fact, class diagrams can also be used for information or data models created in the system analysis step. Hence, we believe that the lessons learned from this work will be valuable in tackling the realities of a commercially viable model driven process

Robust model-based analysis of single-particle tracking experiments with Spot-On.

Single-particle tracking (SPT) has become an important method to bridge biochemistry and cell biology since it allows direct observation of protein binding and diffusion dynamics in live cells. However, accurately inferring information from SPT studies is challenging due to biases in both data analysis and experimental design. To address analysis bias, we introduce 'Spot-On', an intuitive web-interface. Spot-On implements a kinetic modeling framework that accounts for known biases, including molecules moving out-of-focus, and robustly infers diffusion constants and subpopulations from pooled single-molecule trajectories. To minimize inherent experimental biases, we implement and validate stroboscopic photo-activation SPT (spaSPT), which minimizes motion-blur bias and tracking errors. We validate Spot-On using experimentally realistic simulations and show that Spot-On outperforms other methods. We then apply Spot-On to spaSPT data from live mammalian cells spanning a wide range of nuclear dynamics and demonstrate that Spot-On consistently and robustly infers subpopulation fractions and diffusion constants

Korrelation zwischen Immunmarkern und nicht-invasiver Fibrosemessung in Patienten mit chronischer Hepatitis C unter der Therapie mit „direct-acting antiviral agents“

Hintergrund: Bei Patienten mit chronischer Hepatitis C (HCV)-Infektion wurde ein schneller Rückgang der Lebersteifigkeit bei der nicht-invasiven Fibrosemessung beschrieben, sogar innerhalb des Behandlungszeitraums der Therapie mit direkt wirkenden antiviralen Medikamenten (DAA). Methoden: Wir untersuchten prospektiv die Veränderung der Lebersteifigkeit mittels „acoustic radiation force impulse“ (ARFI) bei 217 Patienten unter DAA-Therapie zu Beginn der Behandlung („baseline" BL) und 12 Wochen nach Ende der Therapie („sustained virological response“ SVR12). Zusätzlich wurden demografische Daten, Labor- und mikrobiologische Parameter, Zytokine und Chemokine erhoben. Ergebnisse: Die ARFI-Werte sanken von 1,86 m/s auf 1,68 m/s (p=0,01), was am deutlichsten bei Patienten, die eine F4-Fibrose auf BL-Niveau hatten (3,27 m/s auf 2,37 m/s; p0,1) mit den ARFI-Werten auf. Albumin (p<0,001) und Thrombozytenzahl (p=0,007) zeigten einen Anstieg unter der Therapie ohne Korrelation zu den ARFI-Werten. Die Zytokine IL1α (p=0,026), INFy (nur bei F4-Fibrose p=0,043) zeigten einen Anstieg; TNFα (p=0,031), IFNα2 (p=0,036), IL10 (p=0,005) und IP10 (p<0,001) nahmen unter DAA-Therapie ab. Veränderungen von TNFα (r=0,54; p=0,037) und IL10 (F1-F3-Fibrose, r=0,32; p=0,03) korrelierten mit den Veränderungen der ARFI-Werte. Schlussfolgerung: Wir bestätigen, dass sich ARFI-Werte, Fibrose-Scores, systemische Entzündungsparameter und Parameter der Leberfunktion unter DAA-Therapie signifikant verbessert haben. Darüber hinaus haben wir gezeigt, dass nicht die Fibrose-Scores oder die Thrombozytenzahl am stärksten mit dem schnellen Rückgang der ARFI-Werte korrelieren, sondern die Entzündungsmarker

О возможности использования индуктивного параметрона для защиты от замыканий на землю в сетях с изолированной нейтралью

Показана возможность использования индуктивного параметрона как реагирующего органа в защитах от замыканий на землю в сетях с изолированной нейтралью. Защита с параметроном является селективной и равночувствительной, обладает достаточной чувствительностью

Deep reinforcement learning uncovers processes for separating azeotropic mixtures without prior knowledge

Process synthesis in chemical engineering is a complex planning problem due to vast search spaces, continuous parameters and the need for generalization. Deep reinforcement learning agents, trained without prior knowledge, have shown to outperform humans in various complex planning problems in recent years. Existing work on reinforcement learning for flowsheet synthesis shows promising concepts, but focuses on narrow problems in a single chemical system, limiting its practicality. We present a general deep reinforcement learning approach for flowsheet synthesis. We demonstrate the adaptability of a single agent to the general task of separating binary azeotropic mixtures. Without prior knowledge, it learns to craft near-optimal flowsheets for multiple chemical systems, considering different feed compositions and conceptual approaches. On average, the agent can separate more than 99% of the involved materials into pure components, while autonomously learning fundamental process engineering paradigms. This highlights the agent's planning flexibility, an encouraging step toward true generality.Comment: 36 pages, 7 figures, 4 tables. G\"ottl and Pirnay contributed equally as joint first authors. Burger and Grimm contributed equally as joint last author

Sonoporation-mediated loading of trehalose in cells for cryopreservation.

Trehalose, a non-reducing disaccharide, is present in many microorganisms and metazoans. In these organisms, trehalose acts as a stress protectant and helps preserve lipid membranes of cells during states of desiccation and freezing. Trehalose is required on both sides of the cell membrane to achieve a significant cryoprotective effect. Specific loading methods for trehalose are required since this sugar is impermeant to mammalian cells. Trehalose loading in mammalian cells has been achieved by fluid-phase endocytosis and genetic modification for the expression of trehalose transporters, however cryoprotective outcomes are unable to compete with established methods of cryopreservation for mammalian cells. Sonoporation was achieved using a microfluidics device modified with an ultrasound emitter in the presence of microbubbles. Ultrasound frequencies emitted by the transducer result in a process called cavitation, which is the rapid expansion and collapse of lipid-coated gas-filled bubbles present in the solution. Cavitation of microbubbles creates small jets of liquid that can create membrane pores that are 150-300 nm in size and quickly reseal through budding and exocytosis allowing for uptake of impermeant compounds, such as trehalose

Spatial heterogeneity of flesh-cell osmotic potential in sweet cherry affects partitioning of absorbed water

A fleshy fruit is commonly assumed to resemble a thin-walled pressure vessel containing a homogenous carbohydrate solution. Using sweet cherry (Prunus avium L.) as a model system, we investigate how local differences in cell water potential affect H2O and D2O (heavy water) partitioning. The partitioning of H2O and D2O was mapped non-destructively using magnetic resonance imaging (MRI). The change in size of mesocarp cells due to water movement was monitored by optical coherence tomography (OCT, non-destructive). Osmotic potential was mapped using micro-osmometry (destructive). Virtual sections through the fruit revealed that the H2O distribution followed a net pattern in the outer mesocarp and a radial pattern in the inner mesocarp. These patterns align with the disposition of the vascular bundles. D2O uptake through the skin paralleled the acropetal gradient in cell osmotic potential gradient (from less negative to more negative). Cells in the vicinity of a vascular bundle were of more negative osmotic potential than cells more distant from a vascular bundle. OCT revealed net H2O uptake was the result of some cells loosing volume and other cells increasing volume. H2O and D2O partitioning following uptake is non-uniform and related to the spatial heterogeneity in the osmotic potential of mesocarp cells

Trapped-Ion Quantum Logic Utilizing Position-Dependent ac Stark Shifts

We present a scheme utilizing position-dependent ac Stark shifts for doing quantum logic with trapped ions. By a proper choice of direction, position and size, as well as power and frequency of a far-off-resonant Gaussian laser beam, specific ac Stark shifts can be assigned to the individual ions, making them distinguishable in frequency-space. In contrast to previous all-optical based quantum gates with trapped ions, the present scheme enables individual addressing of single ions and selective addressing of any pair of ions for two-ion quantum gates, without using tightly focused laser beams. Furthermore, the decoherence rate due to off-resonant excitations can be made negligible as compared with other sources of decoherence.Comment: 5 pages, 4 figures. Submitted to Physical Review Letter