Optimal motility strategies for self-propelled agents to explore porous media

Micro-robots for, e.g., biomedical applications, need to be equipped with motility strategies that enable them to navigate through complex environments. Inspired by biological microorganisms we investigate motility patterns such as run-and-reverse, run-and-tumble or run-reverse-flick applied to active rod-like particles in silico. We investigate their capability to efficiently explore disordered porous environments with various porosities and mean pore sizes ranging down to the scale of the active particle. By calculating the effective diffusivity for the different patterns, we can predict the optimal one for each porous sample geometry. We find that providing the agent with the ability to sense position for a certain time and to make a decision based on its observation yields a motility pattern outperforming the biologically inspired patterns for all investigated porous samples

Autonomous engines driven by active matter: Energetics and design principles

Because of its nonequilibrium character, active matter in a steady state can drive engines that autonomously deliver work against a constant mechanical force or torque. As a generic model for such an engine, we consider systems that contain one or several active components and a single passive one that is asymmetric in its geometrical shape or its interactions. Generally, one expects that such an asymmetry leads to a persistent, directed current in the passive component, which can be used for the extraction of work. We validate this expectation for a minimal model consisting of an active and a passive particle on a one-dimensional lattice. It leads us to identify thermodynamically consistent measures for the efficiency of the conversion of isotropic activity to directed work. For systems with continuous degrees of freedom, work cannot be extracted using a one-dimensional geometry under quite general conditions. In contrast, we put forward two-dimensional shapes of a movable passive obstacle that are best suited for the extraction of work, which we compare with analytical results for an idealised work-extraction mechanism. For a setting with many noninteracting active particles, we use a mean-field approach to calculate the power and the efficiency, which we validate by simulations. Surprisingly, this approach reveals that the interaction with the passive obstacle can mediate cooperativity between otherwise noninteracting active particles, which enhances the extracted power per active particle significantly.Comment: 21 pages, 8 figure

Phylogeny of "Sphecidae" (Hymenoptera: Apoidea) based on molecular data

Die Grabwespen (Sphecidae sensu Bohart & Menke 1976; Sphecidae sensu lato in neueren, phylogenetischen Arbeiten), zu denen nach Day (1984) und späteren Autoren auch die Heterogynaidae zählen, umfassen derzeit 266 Gattungen mit 9559 beschriebene Arten (Pulawski 2006). Zusammen mit den Bienen (= Apiformes nach Michener 2000, bzw. Anthophila nach Engel 2005) bilden die Grabwespen ein gut begründetes Monophylum, das nach Michener (1986) den Namen Apoidea trägt und eine der drei Hauptlinien innerhalb der aculeaten Hymenoptera ist. Die Monophylie der aculeaten Hymenoptera, der Apoidea sowie die der Bienen ist jeweils gut begründet (z.B. Brothers 1975, Königsmann 1978, Lomholdt 1982, Alexander 1992, Brothers & Carpenter 1993). Anders verhält es sich mit den Grabwespen. Neben der phylogenetischen Untersuchung von Brothers & (1993), die die Monophylie der Grabwespen unterstützt, haben andere morphologische als auch molekularsystematische Analysen starken Zweifel an dieser Hypothese aufkommen lassen (z.B. Königsmann 1978, Lomholdt 1982, Alexander 1992, Prentice 1998, Melo 1999, Ohl & Bleidorn 2006).Sequences from the nuclear long-wavelength-rhodopsin and the mitochondrial cytochrom-c-oxidase (subunit I) from different representatives of the Apoidea, with special emphasis on digger wasps (Sphecidae sensu lat), were analysed using maximum parsimony, maximum likelihood and Baysian inference methods. Compared with previous phylogenetic studies based on morphology, the results of the molecular analyses are controversial but correspond in the absence of support for the Sphecidae s. l (sensu Bohart & Menke). The relationships within the Sphecidae sensu stricto correspond largely with recent morphological studies. There is circumstantial evidence that the Ampulicidae and Sphecidae s. str. together form a monophyletic group, whereas the relationships within this taxon are still uncertain. Although there is no evidence for a definitive phylogenetic position of the Heterogynaidae; it can be excluded that they are the sistertaxon to all other Apoidea. Instead, they are probably a derived group within the Crabronidae. In conflict to the majority of current morphological studies, the molecular analyses provide no support for the Crabronidae and Bembicinae. Some molecular analyses imply a close relationship between Philanthinae and bees

Environmental effects on emergent strategy in micro-scale multi-agent reinforcement learning

Multi-Agent Reinforcement Learning (MARL) is a promising candidate for realizing efficient control of microscopic particles, of which micro-robots are a subset. However, the microscopic particles' environment presents unique challenges, such as Brownian motion at sufficiently small length-scales. In this work, we explore the role of temperature in the emergence and efficacy of strategies in MARL systems using particle-based Langevin molecular dynamics simulations as a realistic representation of micro-scale environments. To this end, we perform experiments on two different multi-agent tasks in microscopic environments at different temperatures, detecting the source of a concentration gradient and rotation of a rod. We find that at higher temperatures, the RL agents identify new strategies for achieving these tasks, highlighting the importance of understanding this regime and providing insight into optimal training strategies for bridging the generalization gap between simulation and reality. We also introduce a novel Python package for studying microscopic agents using reinforcement learning (RL) to accompany our results.Comment: 12 pages, 5 figure

Entanglement demonstration on board a nano-satellite

Global quantum networks for secure communication can be realized using large fleets of satellites distributing entangled photon pairs between ground-based nodes. Because the cost of a satellite depends on its size, the smallest satellites will be most cost-effective. This Letter describes a miniaturized, polarization entangled, photon-pair source operating on board a nano-satellite. The source violates Bell’s inequality with a Clauser–Horne–Shimony–Holt parameter of 2.60±0.06. This source can be combined with optical link technologies to enable future quantum communication nano-satellite missions

SpooQy-1: The First Nano-Satellite to Demonstrate Quantum Entanglement in Space

SpooQy-1 is a 3-unit nanosatellite that was launched into a Low Earth Orbit from the International Space Station on the 17th of June 2019. The spacecraft hosts a scientific payload capable of producing entangled photon-pairs and measuring their polarization in orthogonal bases to perform a Bell test. Since launch, SpooQy-1 has routinely demonstrated the generation and detection of polarization entangled photon-pairs in Space, something that has previously only been demonstrated by the 630kg Micius mission by the Chinese Academy of Sciences. The measured entanglement correlations can violate Bell\u27s inequality with a CHSH parameter value of 2.60±0.06, over operating temperatures of 16 °C to 21.5 °C. These results demonstrate that quantum entanglement can be generated in space on highly resource-constrained platforms. A follow-on 12U mission, developed in partnership with RAL space,will build on this to demonstrate space-to-ground entanglement distribution, which is required for space-based nodes to support global quantum communication networks

Accuracy and Predictive Power of Sell-Side Target Prices for Global Clean Energy Companies

Target prices are often provided as a support for stock recommendations by sell-side analysts which represent an explicit estimate of the expected future value of a company’s stock. This research focuses on mean target prices for stocks contained in the Standard and Poor’s Global Clean Energy Index during the time period from 2009 to 2020. The accuracy of mean target prices for these global clean energy stocks at any point during a 12-month period (Year-Highest) is 68.1% and only 46.6% after exactly 12 months (Year-End). A random forest and an SVM classification model were trained for both a Year-End and a Year-Highest target and compared to a random model. The random forest demonstrates the best results with an average accuracy of 73.24% for the Year-End target and 81.15% for the Year-Highest target. The analysis of the variables shows that for all models the mean target price is the most relevant variable, whereas the number of target prices appears to be highly relevant as well. Moreover, the results indicate that following the rare positive predictions of the random forest for the highest target return groups (“30% to 70%” and “Above 70%”) may potentially represent attractive investment opportunities

Adaptation of Clinical Practice Guideline Recommendations in Hospitals for People Living With Dementia and Their Caregivers

Background Dementia is common in older people in general hospitals. To improve the quality of their care, the use of nonpharmacological interventions based on the best evidence from clinical guidelines is recommended. Many international clinical guidelines exist, but their recommendations are often not used because they do not fit the local setting or the country. Aim The aim of this study was to adapt the international clinical guidelines and their recommendations to the Austrian context regarding nonpharmacological interventions for people with dementia living in the general hospital setting. Methods The ADAPTE process was chosen as a method for the adaptation. A search for international clinical guidelines was conducted in seven databases within this process. The guidelines which met the inclusion and quality criteria were assessed with the AGREE II instrument by two independent reviewers. The recommendations of the guidelines were extracted. Those that did not fit the Austrian context were excluded, and recommendations with similar statements were summarized. The selected and modified recommendations were translated into German. Results Out of 206 guidelines, three met the inclusion criteria and two, the quality criteria. One hundred and fifty‐two recommendations were extracted from these two guidelines, 42 of which were suitable for the Austrian setting and 20 of which had similar statements and could be summarized. Finally, 32 recommendations were identified that were applicable to the general hospital setting in Austria. Linking Evidence to Action The adaptation of clinical guidelines with the ADAPTE process generated seven topics with 32 recommendations. Many international guidelines exist, but they cannot be applied verbatim in every country due to the fact that some recommendations are not applicable with respect to the national and local context. Creating an adaption of international guidelines is an effective way to provide and link evidence from research to national nursing practice

Autonomous Engines Driven by Active Matter: Energetics and Design Principles

Because of its nonequilibrium character, active matter in a steady state can drive engines that autonomously deliver work against a constant mechanical force or torque. As a generic model for such an engine, we consider systems that contain one or several active components and a single passive one that is asymmetric in its geometrical shape or its interactions. Generally, one expects that such an asymmetry leads to a persistent, directed current in the passive component, which can be used for the extraction of work. We validate this expectation for a minimal model consisting of an active and a passive particle on a one-dimensional lattice. It leads us to identify thermodynamically consistent measures for the efficiency of the conversion of isotropic activity to directed work. For systems with continuous degrees of freedom, work cannot be extracted using a one-dimensional geometry under quite general conditions. In contrast, we put forward two-dimensional shapes of a movable passive obstacle that are best suited for the extraction of work, which we compare with analytical results for an idealized work-extraction mechanism. For a setting with many noninteracting active particles, we use a mean-field approach to calculate the power and the efficiency, which we validate by simulations. Surprisingly, this approach reveals that the interaction with the passive obstacle can mediate cooperativity between otherwise noninteracting active particles, which enhances the extracted power per active particle significantly