Current Capabilities and Development Potential in Surgical Robotics

Commercial surgical robots have been in clinical use since the mid-1990s, supporting surgeons in various tasks. In the past decades, many systems emerged as research platforms, and a few entered the global market

Continuous ErrP detections during multimodal human-robot interaction

Human-in-the-loop approaches are of great importance for robot applications. In the presented study, we implemented a multimodal human-robot interaction (HRI) scenario, in which a simulated robot communicates with its human partner through speech and gestures. The robot announces its intention verbally and selects the appropriate action using pointing gestures. The human partner, in turn, evaluates whether the robot's verbal announcement (intention) matches the action (pointing gesture) chosen by the robot. For cases where the verbal announcement of the robot does not match the corresponding action choice of the robot, we expect error-related potentials (ErrPs) in the human electroencephalogram (EEG). These intrinsic evaluations of robot actions by humans, evident in the EEG, were recorded in real time, continuously segmented online and classified asynchronously. For feature selection, we propose an approach that allows the combinations of forward and backward sliding windows to train a classifier. We achieved an average classification performance of 91% across 9 subjects. As expected, we also observed a relatively high variability between the subjects. In the future, the proposed feature selection approach will be extended to allow for customization of feature selection. To this end, the best combinations of forward and backward sliding windows will be automatically selected to account for inter-subject variability in classification performance. In addition, we plan to use the intrinsic human error evaluation evident in the error case by the ErrP in interactive reinforcement learning to improve multimodal human-robot interaction

Identification of the honey bee swarming process by analysing the time course of hive vibrations

Honey bees live in groups of approximately 40,000 individuals and go through their reproductive cycle by the swarming process, during which the old queen leaves the nest with numerous workers and drones to form a new colony. In the spring time, many clues can be seen in the hive, which sometimes demonstrate the proximity to swarming, such as the presence of more or less mature queen cells. In spite of this the actual date and time of swarming cannot be predicted accurately, as we still need to better understand this important physiological event. Here we show that, by means of a simple transducer secured to the outside wall of a hive, a set of statistically independent instantaneous vibration signals of honey bees can be identified and monitored in time using a fully automated and non-invasive method. The amplitudes of the independent signals form a multi-dimensional time-varying vector which was logged continuously for eight months. We found that combined with specifically tailored weighting factors, this vector provides a signature highly specific to the swarming process and its build up in time, thereby shedding new light on it and allowing its prediction several days in advance. The output of our monitoring method could be used to provide other signatures highly specific to other physiological processes in honey bees, and applied to better understand health issues recently encountered by pollinators

On the relation between filament density, force generation, and protrusion rate in mesenchymal cell motility

Lamellipodia are flat membrane protrusions formed during mesenchymal motion. Polymerization at the leading edge assembles the actin filament network and generates protrusion force. How this force is supported by the network and how the assembly rate is shared between protrusion and network retrograde flow determines the protrusion rate. We use mathematical modeling to understand experiments changing the F-actin density in lamellipodia of B16-F1 melanoma cells by modulation of Arp2/3 complex activity or knockout of the formins FMNL2 and FMNL3. Cells respond to a reduction of density with a decrease of protrusion velocity, an increase in the ratio of force to filament number, but constant network assembly rate. The relation between protrusion force and tension gradient in the F-actin network and the density dependency of friction, elasticity, and viscosity of the network explain the experimental observations. The formins act as filament nucleators and elongators with differential rates. Modulation of their activity suggests an effect on network assembly rate. Contrary to these expectations, the effect of changes in elongator composition is much weaker than the consequences of the density change. We conclude that the force acting on the leading edge membrane is the force required to drive F-actin network retrograde flow

Partizipation und Stakeholder-Beteiligung in der Pilotregion Mostviertel: WP3 Synthesebericht

Aufgabe eines Partizipativen Regional Integrierten Vulnerabilitätsassessments (PRIVAS) ist es, in Zusammenarbeit mit Stakeholdern die integrative Wissensproduktion bei einem komplexen Mensch-Umwelt-Problem wie dem Klimawandel zu optimieren. Dieses Ziel stellt jedes Projekt vor konzeptive, methodische, prozessuale und forschungspraktische Herausforderungen, denen sich RIVAS in der Testregion gestellt hat. Auf Basis der Analyse und Erfahrungen aus 14 nationalen und internationalen Vulnerabilitätsassessments und der einschlägigen wissenschaftlichen Literatur wurde ein experimentelles Ablaufdesign für ein PRIVAS erstellt, welches im Mostviertel in einer Laufzeit von über einem Jahr umgesetzt wurde. Den Kern der Stakeholderinteraktionen bildete eine Referenzgruppe, die sich aus Akteuren der Demosektoren Land-, Wasser- und Forstwirtschaft, dem Regionalmanagement und des Projektteams zusammensetzte. Die Referenzgruppe war zentraler Kommunikationsort, wo eine Dialog- und Konsensorientierung vorherrschte. Die partizipativen Anknüpfungspunkte der Personen aus der Referenzgruppe im Vulnerabilitätsassessment waren unterschiedlich ausgeformt und gewichtet, da in RIVAS einige innovative und konzeptive Überlegungen getestet werden sollten. Der Schwerpunkt dabei wurde auf die partizipative Problemformulierung und Eingrenzung der Untersuchungsfragen (Phase „zu Beginn“ eines Assessments) sowie auf die Methodenanwendung und Analyse (Phase „während“ eines Assessments) gelegt. Eines der zentralen Ergebnisse von RIVAS ist, dass nicht nur das Produkt und die Ergebnisse einer Vulnerabilitätsbewertung Wissen und Verständnis schaffen, sondern dass zumindest gleichberechtigt auch der strukturierte Prozess für die Verbreitung, Aufnahme und den Transfer von Informationen und Wissen verantwortlich ist. Der Prozesscharakter solcher Interaktionen optimiert nicht nur die Qualität und Nutzbarkeit der Projektergebnisse, sondern unterstützt auch ein soziales Lernen und begünstigt langfristige Wirkungen, die weit über die Projektlaufzeit hinausreichen. Neben den bereits in der Literatur vielfach beschrieben organisatorischen Rahmenbedingungen (Transparenz, Regelmäßigkeit, Langfristigkeit, Vertrauenswürdigkeit, Interaktionsregeln und -techniken, Zeitpläne, etc.) ist vor allem der Grad der Partizipation ein entscheidendes Kriterium, welches für den Erfolg oder Misserfolg eines PRIVAS verantwortlich ist. In welchen Bereichen des Vulnerabilitätsassessments eine Mitbestimmung von Stakeholdern auf der Ebene der Information, Konsultation oder Mitbestimmung stattfinden soll, muss nicht nur frühzeitig und entlang der Bedürfnisse der Stakeholder und WissenschafterInnen abgestimmt werden, sondern sollte insbesondere immer einer zielgerichteten Entscheidung unterliegen, die auf den Zweck der Partizipation fokussiert. Ein weiteres Attribut für das Gelingen eines PRIVAS ist eine regel- und gleichmäßige Partizipation der Stakeholder. Das Projekt zeigt auf, dass die Institutionalisierung der Beteiligung vor allem durch die Bildung der Referenzgruppe gewährleistet werden konnte. Darüber hinaus hat die Einbindung eines regionalen Prozessträgers – des Regionalmanagements Mostviertel – entscheidend zur Beteiligungsmotivation beigetragen. Die Partizipation an einem Prozess und nicht nur die punktuellen Beteiligung an einem Projekt stand damit im Vordergrund. Schlussendlich müssen sich alle Partizipationsverfahren in einem PRIVAS dahingehend rechtfertigen, ob der notwendige Aufwand an Kosten und Zeit in einem angemessenen Verhältnis zu den Ergebnissen steht, und ob die im Projekt angestrebten Ziele auch erreicht wurden. Beides kann mit Hilfe der nach Abschluss des regionalen Projektteils durchgeführten Evaluation der Stakeholderbeteiligung für RIVAS positiv bestätigt werden

Bovine oocytes in secondary follicles grow and acquire meiotic competence in severe combined immunodeficient mice

A rigorous methodology is developed that addresses numerical and statistical issues when developing group contribution (GC) based property models such as regression methods, optimization algorithms, performance statistics, outlier treatment, parameter identifiability, and uncertainty of the prediction. The methodology is evaluated through development of a GC method for the prediction of the heat of combustion (Δ<i>H</i>_c^o) for pure components. The results showed that robust regression lead to best performance statistics for parameter estimation. The bootstrap method is found to be a valid alternative to calculate parameter estimation errors when underlying distribution of residuals is unknown. Many parameters (first, second, third order group contributions) are found unidentifiable from the typically available data, with large estimation error bounds and significant correlation. Due to this poor parameter identifiability issues, reporting of the 95% confidence intervals of the predicted property values should be mandatory as opposed to reporting only single value prediction, currently the norm in literature. Moreover, inclusion of higher order groups (additional parameters) does not always lead to improved prediction accuracy for the GC-models; in some cases, it may even increase the prediction error (hence worse prediction accuracy). However, additional parameters do not affect calculated 95% confidence interval. Last but not least, the newly developed GC model of the heat of combustion (Δ<i>H</i>_c^o) shows predictions of great accuracy and quality (the most data falling within the 95% confidence intervals) and provides additional information on the uncertainty of each prediction compared to other Δ<i>H</i>_c^o models reported in literature

Exoskeleton Technology in Rehabilitation: Towards an EMG-Based Orthosis System for Upper Limb Neuromotor Rehabilitation

The rehabilitation of patients should not only be limited to the first phases during intense hospital care but also support and therapy should be guaranteed in later stages, especially during daily life activities if the patient’s state requires this. However, aid should only be given to the patient if needed and as much as it is required. To allow this, automatic self-initiated movement support and patient-cooperative control strategies have to be developed and integrated into assistive systems. In this work, we first give an overview of different kinds of neuromuscular diseases, review different forms of therapy, and explain possible fields of rehabilitation and benefits of robotic aided rehabilitation. Next, the mechanical design and control scheme of an upper limb orthosis for rehabilitation are presented. Two control models for the orthosis are explained which compute the triggering function and the level of assistance provided by the device. As input to the model fused sensor data from the orthosis and physiology data in terms of electromyography (EMG) signals are used

On the impact of urban surface exchange parameterisations on air quality simulations: the Athens case

Most of the standard mesoscale models represent the dynamic and thermodynamic surface exchanges in urban areas with the same technique used for ruralareas (based on Monin–Obukhov similarity theory and a surface energy budget). However it has been shown that this technique is not able to fully capture the structure of the turbulent layer above a city. Aim of this study is to evaluate the importance for meteorological and air quality simulations, of properly capture the dynamic and thermodynamic surface exchanges in urban areas. Two sets of simulations were performed over the city of Athens (Greece): a first using a mesoscale model with a detailed urban surface exchange parameterisation (able to reproduce the surface exchanges better than the traditionalmethod), and a second with the traditionalapproach. Meteorological outputs are passed to a Eulerian photochemical model (the photochemical model is run offline). Comparison with measurements shows better agreement for the simulation with the detailed parameterisation. The differences between the simulations concern, mainly, wind speed (maximum difference of 0.5–1ms-1), night-time temperatures (2–3°C), turbulence intensity (2m2 s-2) and heat fluxes (0.15Kms-1) over the urban area, urban nocturnal land breeze intensity, timing and extension of sea breeze. These differences modify the pollutant distribution (e.g. for ozone maximum differences are of the order of 30 ppb). Differences between the simulations are also found in AOT60 values (inside and outside the city) and in O3 chemicalregimes

Protective immune trajectories in early viral containment of non-pneumonic SARS-CoV-2 infection

The antiviral immune response to SARS-CoV-2 infection can limit viral spread and prevent development of pneumonic COVID-19. However, the protective immunological response associated with successful viral containment in the upper airways remains unclear. Here, we combine a multi-omics approach with longitudinal sampling to reveal temporally resolved protective immune signatures in non-pneumonic and ambulatory SARS-CoV-2 infected patients and associate specific immune trajectories with upper airway viral containment. We see a distinct systemic rather than local immune state associated with viral containment, characterized by interferon stimulated gene (ISG) upregulation across circulating immune cell subsets in non-pneumonic SARS-CoV2 infection. We report reduced cytotoxic potential of Natural Killer (NK) and T cells, and an immune-modulatory monocyte phenotype associated with protective immunity in COVID-19. Together, we show protective immune trajectories in SARS-CoV2 infection, which have important implications for patient prognosis and the development of immunomodulatory therapies