Quantum Optical Experiments Modeled by Long Short-Term Memory

We demonstrate how machine learning is able to model experiments in quantum physics. Quantum entanglement is a cornerstone for upcoming quantum technologies such as quantum computation and quantum cryptography. Of particular interest are complex quantum states with more than two particles and a large number of entangled quantum levels. Given such a multiparticle high-dimensional quantum state, it is usually impossible to reconstruct an experimental setup that produces it. To search for interesting experiments, one thus has to randomly create millions of setups on a computer and calculate the respective output states. In this work, we show that machine learning models can provide significant improvement over random search. We demonstrate that a long short-term memory (LSTM) neural network can successfully learn to model quantum experiments by correctly predicting output state characteristics for given setups without the necessity of computing the states themselves. This approach not only allows for faster search but is also an essential step towards automated design of multiparticle high-dimensional quantum experiments using generative machine learning models.Comment: 9 page

Brain temperature regulation in poor-grade subarachnoid hemorrhage patients – A multimodal neuromonitoring study

Elevated body temperature (Tcore) is associated with poor outcome after subarachnoid hemorrhage (SAH). Brain temperature (Tbrain) is usually higher than Tcore. However, the implication of this difference (Tdelta) remains unclear. We aimed to study factors associated with higher Tdelta and its association with outcome. We included 46 SAH patients undergoing multimodal neuromonitoring, for a total of 7879 h of averaged data of Tcore, Tbrain, cerebral blood flow, cerebral perfusion pressure, intracranial pressure and cerebral metabolism (CMD). Three-months good functional outcome was defined as modified Rankin Scale ≤2. Tbrain was tightly correlated with Tcore (r = 0.948, p < 0.01), and was higher in 73.7% of neuromonitoring time (Tdelta +0.18°C, IQR −0.01 – 0.37°C). A higher Tdelta was associated with better metabolic state, indicated by lower CMD-glutamate ( p = 0.003) and CMD-lactate ( p < 0.001), and lower risk of mitochondrial dysfunction (MD) (OR = 0.2, p < 0.001). During MD, Tdelta was significantly lower (0°C, IQR −0.2 – 0.1; p < 0.001). A higher Tdelta was associated with improved outcome (OR = 7.7, p = 0.002). Our study suggests that Tbrain is associated with brain metabolic activity and exceeds Tcore when mitochondrial function is preserved. Further studies are needed to understand how Tdelta may serve as a surrogate marker for brain function and predict clinical course and outcome after SAH

Brain Exposure to Piperacillin in Acute Hemorrhagic Stroke Patients Assessed by Cerebral Microdialysis and Population Pharmacokinetics

Background The broad antibacterial spectrum of piperacillin/tazobactam makes the combination suitable for the treatment of nosocomial bacterial central nervous system (CNS) infections. As limited data are available regarding piperacillin CNS exposure in patients without or with low-grade inflammation, a clinical study was conducted (1) to quantify CNS exposure of piperacillin by cerebral microdialysis and (2) to evaluate different dosing regimens in order to improve probability of target attainment (PTA) in brain. Methods Ten acute hemorrhagic stroke patients (subarachnoid hemorrhage, n = 6; intracerebral hemorrhage, n = 4) undergoing multimodality neuromonitoring received 4 g piperacillin/0.5 g tazobactam every 8 h by 30-min infusions for the management of healthcare-associated pneumonia. Cerebral microdialysis was performed as part of the clinical neuromonitoring routine, and brain interstitial fluid samples were retrospectively analyzed for piperacillin concentrations after the first and after multiple doses for at least 5 days and quantified by high-performance liquid chromatography. Population pharmacokinetic modeling and Monte Carlo simulations with various doses and types of infusions were performed to predict exposure. A T->MIC of 50% was selected as pharmacokinetic/pharmacodynamic target parameter. Results Median peak concentrations of unbound piperacillin in brain interstitial space fluid were 1.16 (range 0.08-3.59) and 2.78 (range 0.47-7.53) mg/L after the first dose and multiple doses, respectively. A one-compartment model with a transit compartment and a lag time (for the first dose) between systemic and brain exposure was appropriate to describe the brain concentrations. Bootstrap median estimates of the parameters were: transfer rate from plasma to brain (0.32 h(-1)), transfer rate from brain to plasma (7.31 h(-1)), and lag time [2.70 h (coefficient of variation 19.7%)]. The simulations suggested that PTA would exceed 90% for minimum inhibitory concentrations (MICs) up to 0.5 mg/L and 1 mg/L at a dose of 12-16 and 24 g/day, respectively, regardless of type of infusion. For higher MICs, PTA dropped significantly. Conclusion Limited CNS exposure of piperacillin might be an obstacle in treating patients without general meningeal inflammation except for infections with highly susceptible pathogens. Brain exposure of piperacillin did not improve significantly with a prolongation of infusions

CD6 modulates thymocyte selection and peripheral T cell homeostasis

The CD6 glycoprotein is a lymphocyte surface receptor putatively involved in T cell development and activation. CD6 facilitates adhesion between T cells and antigen-presenting cells through its interaction with CD166/ALCAM (activated leukocyte cell adhesion molecule), and physically associates with the T cell receptor (TCR) at the center of the immunological synapse. However, its precise role during thymocyte development and peripheral T cell immune responses remains to be defined. Here, we analyze the in vivo consequences of CD6 deficiency. CD6(-/-) thymi showed a reduction in both CD4(+) and CD8(+) single-positive subsets, and double-positive thymocytes exhibited increased Ca(2+) mobilization to TCR cross-linking in vitro. Bone marrow chimera experiments revealed a T cell-autonomous selective disadvantage of CD6(-/-) T cells during development. The analysis of TCR-transgenic mice (OT-I and Marilyn) confirmed that abnormal T cell selection events occur in the absence of CD6. CD6(-/-) mice displayed increased frequencies of antigen-experienced peripheral T cells generated under certain levels of TCR signal strength or co-stimulation, such as effector/memory (CD4(+)TEM and CD8(+)TCM) and regulatory (T reg) T cells. The suppressive activity of CD6(-/-) T reg cells was diminished, and CD6(-/-) mice presented an exacerbated autoimmune response to collagen. Collectively, these data indicate that CD6 modulates the threshold for thymocyte selection and the generation and/or function of several peripheral T cell subpopulations, including T reg cells

The James Webb Space Telescope Mission

Twenty-six years ago a small committee report, building on earlier studies, expounded a compelling and poetic vision for the future of astronomy, calling for an infrared-optimized space telescope with an aperture of at least $4m$. With the support of their governments in the US, Europe, and Canada, 20,000 people realized that vision as the $6.5m$ James Webb Space Telescope. A generation of astronomers will celebrate their accomplishments for the life of the mission, potentially as long as 20 years, and beyond. This report and the scientific discoveries that follow are extended thank-you notes to the 20,000 team members. The telescope is working perfectly, with much better image quality than expected. In this and accompanying papers, we give a brief history, describe the observatory, outline its objectives and current observing program, and discuss the inventions and people who made it possible. We cite detailed reports on the design and the measured performance on orbit.Comment: Accepted by PASP for the special issue on The James Webb Space Telescope Overview, 29 pages, 4 figure

An ontology as shared vocabulary for distributed intelligence in smart homes

Zsfassung in dt. SpracheGebäudeautomation im Zweck- sowie Wohnbau gewinnt zunehmend an Popularität, nicht zuletzt aufgrund einer Vielzahl von Möglichkeiten, die sich durch die Integration unterschiedlichster Komponenten ergeben. Heimautomation stellt in diesem Zusammenhang mit dem Schlagwort "Smart Home" generell einen höheren persönlichen Komfort bei gleichzeitiger Optimierung des Energiebedarfs in Aussicht. Meist bleibt jedoch trotz einer hoch technologisierten Umgebung, die Verantwortlichkeit für Konfiguration, Überwachung und optimierten Betrieb des Gebäudes beim Bewohner. Eine mögliche Lösung dieser Problematik ist, die Kontrolle des Wohngebäudes (teilweise) an ein autonomes System abzugeben, das Routineaufgaben im Auf trag des Benutzers durchführt. Eine Herausforderung hierbei ist unter Anderem die Berücksichtigung neuer, bisher außer Acht gelassener Einflussfaktoren. Eine Integration dieser zusätzlichen Parameter in Kontrollstrategien eines intelligenten Gebäudesystems ermöglicht die Umsetzung von zukunftsorientierten Anwendungsfällen, wie beispielsweise proaktiver Kontrolle. Um eine möglichst akkurate Abbildung des Gebäudes zu erreichen, müssen höchst unterschiedliche Bereiche berücksichtigt und entsprechend in einem grundlegenden Modell verknüpft werden. In diesem Zusammenhang wird im Rahmen dieser Arbeit ein umfassendes Wissensmodell präsentiert, welches die Umgebung eines Smart Homes möglichst vollständig abbildet, um eine wesentliche Grundlage für die autonome Schaffung von Benutzerkomfort sowie optimierter Energieeffizienz zu liefern. Als Formalismus der Wissensrepräsentation wurde die Web Ontology Language (OWL) gewählt, die eine semantische Beschreibung von Begriffen ermöglicht. Eines der Hauptprobleme in diesem Zusammenhang ist die Abstraktion von der Wirklichkeit, um eine effiziente Steuerung des Gebäudes zu gewährleisten, ohne dabei wichtige Einflussfaktoren zu verlieren. Zur Demonstration der Eignung des erstellten Modells für die genannte Domäne werden aus einer Reihe von Anwendungsfällen Kompetenzfragen generiert, die notwendige Eigenschaften einer derartigen Wissensbasis widerspiegeln und zur Evaluierung herangezogen werden. Die Ontologie stellt eine formale Beschreibung einer großen Anzahl unterschiedlicher Parameter dar, die unabhängig von der Umsetzung des Kontrollmechanismus entwickelt wird. Wenngleich die Wissensbasis im Zuge dieser Arbeit für ein Wohngebäude definiert wird, ist ein Großteil der Konzepte auch für den Einsatz im Zweckbau geeignet. Die Ontologie wird anhand eines einzelnen Gebäudes demonstriert, ist jedoch als verteiltes Vokabular insbesondere für die Anwendung in mehreren intelligenten Gebäudesystemen im Rahmen einer Smart City sinnvoll.Automation of buildings in the commercial but also the residential sector is on the rise, not least because of advanced opportunities developing from the integration of a multitude of devices into a single control system. While home automation thereby promises improved personal comfort and the optimized operation of the so-called smart home, these goals are currently only partly reached with regard to energy consumption. Mostly, configuration and monitoring of the building are in the responsibility of the home owners often leaving them overwhelmed with the amount and variety of influencing parameters and control options. One solution is to hand over control of a residential building to an autonomous system. For such a system, an unambiguous view of the environment is indispensable. In this regard, one major challenge is to address yet unconsidered factors that can be taken into account for the optimized control of a dwelling. The integration of these additional parameters into building control strategies allows the realization of advanced use cases such as proactive control that consider the current and future state of the building. In this context, highly heterogeneous domains need to be combined to reach an accurate representation of the building and its surroundings which is mandatory when an intelligent and optimized operation is desired. This dissertation presents an ontology that comprehensively models the smart home environment in order to provide the foundation for autonomous control of user comfort and energy efficiency. Using the Web Ontology Language (OWL) as knowledge representation formalism thereby facilitates the semantic description of terms and their interconnections. In this respect, one of the main problems addressed in this work is the abstraction from reality while still providing all major influencing factors to a building control system. It is shown how capabilities of OWL like subtle reasoning can be optimally utilized when creating a knowledge base for a smart home. The designed model is furthermore evaluated against competency questions retrieved from a set of advanced smart home use cases to demonstrate its suitability for this domain. One of the major benefits of the resulting ontology is the formal description of a large variety of parameters which is accessible through a well defined interface yet at the same time independent from the actual implementation of the control mechanism. Although the focus is the residential sector, the created conceptualization is to a great extent also useful for commercial buildings. While the application of the ontology is demonstrated for an individual building, as a shared vocabulary it may also be the basis for the integration of multiple building control systems in the context of a smart city by providing a unified view of the world.24