Investigation of the influence of active dopant and co-dopant on the luminescent properties of the phosphor based on calcium aluminate

In the present study the luminescent properties of calcium aluminate activated by Eu3+ and Dy3+ions are investigated. The phosphor on the basis of calcium aluminate was obtained via citric-nitrate sol gel method using a microwave radiation. It was determined by X-ray diffraction method and by electron microprobe analysis that rare earth elements (REE) ions incorporate into lattice of calcium aluminate and don't form own phases. Luminescent properties of calcium aluminate activated by REE ions were studied by spectrofluorimeter. Luminescent spectrum of Ca0,95Eu0,05Al2O4 contains five bands groups of emission between 580-710 nm which correspond to 5D0 - 7Fj transitions of Eu3+(λ=254 nm). Present maxima lie in the red area of the spectrum and determine the obtainment of red glow phosphor. Excitation spectrum of Ca0,95Dy0,05Al2O4 contains two bands with maxima at 240 and 380 nm. Exciting the sample by the far ultraviolet (240 nm), two bands with maxima at 420 and 490 nm conditioning a blue glow of phosphor under overlapping of violet (4G11/2 - 6H15/2 transition of Dy3+) and blue-green (4F9/2 - 6H15/2 transition of Dy3+) radiations, respectively, were observed. Exciting the sample by the near ultraviolet (380 nm), one intense band at 420 nm and bright violet glowing were observed. Emission spectrum of the phosphor obtaining by co-activation of calcium aluminate by two test REE ions is identical to the emission spectrum of calcium aluminate activated by Dy3+ ions. Transitions of Eu3+ in this case are not observed. Nevertheless, the increase of band intensity conditioning more bright violet glowing was observed

Modeling approach to multi-agent system of human and machine agents: Application in design of early experiments for novel aeronautics systems

Design of future systems for flight-deck automation will reflect a trend of changing the paradigm of human-computer interaction from the master (human)- slave (machine) mode to more equilibrated cooperation. In many cases such cooperation considers several humans and computer systems, for which multi-agent dynamic cooperative systems are appropriate models. Development of such systems requires very profound analysis of mutual interactions and conflicts that may arise in such systems. Additional testing is exhaustive and expensive for such systems. In the scope of the D3CoS project these problems are addressed from the modelling point of view with ambition to create tools that will simplify the development phase and replace parts of the testing phase. In this paper we investigate common flight procedures, for which computer assistance could be developed. We show how formal modelling of procedures allows us to inspect procedural inconsistencies and workload peaks before the development starts. We show how a computer cognitive architecture (a virtual pilot) can simulate human pilot behaviour in the cockpit to address questions typical for the early phase of the development. Analysis of these questions allows us to reduce the number of candidates for the final implementation without the need of expensive experiments with human pilots. This modelling approach is demonstrated on experiments undertaken both with human pilots and a virtual pilot. The quality of the outcome from both experimental settings remains conserved as shown by physiological assessment of pilot workload, which in turn justifies the use of the modelling approach for this type of problems

Evaluation of an Approach Stabilization Advisory system in a B737 full flight simulator

Unstabilized approach has been identified to be a major causal factor of approach and landing accidents (e.g. off runway touchdowns, tail strikes etc.). In the D3CoS project, we conducted experiments in order to analyze pilots workload during approaches. Therefore 15 type rated, commercial pilots flew 4 different approaches each in a B737 full flight simulator. Geometry characteristics, winds and weather conditions were manipulated in order to induce unstabilized approaches. The pilot flying‘s eye gaze, heart rate and subjective data (NASA TLX) were collected. Flight data were also recorded and aggregated with an algorithm to provide a stabilization performance indicator. Flight data analysis suggests that the scenarios were able to induce unstabilized approaches. Moreover, our results showed that only half of the unstabilized approaches were subjectively perceived as critical by the participants. Interestingly enough, a scenario at Dalaman airport was very efficient to induce unstabilized approach and elicited higher physiological responses, as well as higher Nasa TLX scores. The next step is to implement an Approach Stabilization Advisory System (AStA) that monitors aircraft performance/configuration and pilot’s behavior/cognitive state. When AStA detects a potential occurrence of an unstabilized approach, it suggests corrective actions to restabilize the approach or to go around. AStA will be tested in the next experimental campaign of D3CoS

Analysing cerebrospinal fluid with explainable deep learning: From diagnostics to insights

Aim Analysis of cerebrospinal fluid (CSF) is essential for diagnostic workup of patients with neurological diseases and includes differential cell typing. The current gold standard is based on microscopic examination by specialised technicians and neuropathologists, which is time-consuming, labour-intensive and subjective. Methods We, therefore, developed an image analysis approach based on expert annotations of 123,181 digitised CSF objects from 78 patients corresponding to 15 clinically relevant categories and trained a multiclass convolutional neural network (CNN). Results The CNN classified the 15 categories with high accuracy (mean AUC 97.3%). By using explainable artificial intelligence (XAI), we demonstrate that the CNN identified meaningful cellular substructures in CSF cells recapitulating human pattern recognition. Based on the evaluation of 511 cells selected from 12 different CSF samples, we validated the CNN by comparing it with seven board-certified neuropathologists blinded for clinical information. Inter-rater agreement between the CNN and the ground truth was non-inferior (Krippendorff's alpha 0.79) compared with the agreement of seven human raters and the ground truth (mean Krippendorff's alpha 0.72, range 0.56–0.81). The CNN assigned the correct diagnostic label (inflammatory, haemorrhagic or neoplastic) in 10 out of 11 clinical samples, compared with 7–11 out of 11 by human raters. Conclusions Our approach provides the basis to overcome current limitations in automated cell classification for routine diagnostics and demonstrates how a visual explanation framework can connect machine decision-making with cell properties and thus provide a novel versatile and quantitative method for investigating CSF manifestations of various neurological diseases.Peer Reviewe

S100A1: A Multifaceted Therapeutic Target in Cardiovascular Disease

Cardiovascular disease is the leading cause of death worldwide, showing a dramatically growing prevalence. It is still associated with a poor clinical prognosis, indicating insufficient long-term treatment success of currently available therapeutic strategies. Investigations of the pathomechanisms underlying cardiovascular disorders uncovered the Ca2+ binding protein S100A1 as a critical regulator of both cardiac performance and vascular biology. In cardiomyocytes, S100A1 was found to interact with both the sarcoplasmic reticulum ATPase (SERCA2a) and the ryanodine receptor 2 (RyR2), resulting in substantially improved Ca2+ handling and contractile performance. Additionally, S100A1 has been described to target the cardiac sarcomere and mitochondria, leading to reduced pre-contractile passive tension as well as enhanced oxidative energy generation. In endothelial cells, molecular analyses revealed a stimulatory effect of S100A1 on endothelial NO production by increasing endothelial nitric oxide synthase activity. Emphasizing the pathophysiological relevance of S100A1, myocardial infarction in S100A1 knockout mice resulted in accelerated transition towards heart failure and excessive mortality in comparison with wild-type controls. Mice lacking S100A1 furthermore displayed significantly elevated blood pressure values with abrogated responsiveness to bradykinin. On the other hand, numerous studies in small and large animal heart failure models showed that S100A1 overexpression results in reversed maladaptive myocardial remodeling, long-term rescue of contractile performance, and superior survival in response to myocardial infarction, indicating the potential of S100A1-based therapeutic interventions. In summary, elaborate basic and translational research established S100A1 as a multifaceted therapeutic target in cardiovascular disease, providing a promising novel therapeutic strategy to future cardiologists

The theory of the firm and its critics: a stocktaking and assessment

Includes bibliographical references."Prepared for Jean-Michel Glachant and Eric Brousseau, eds. New Institutional Economics: A Textbook, Cambridge, Cambridge University Press.""This version: August 22, 2005."Since its emergence in the 1970s the modern economic or Coasian theory of the firm has been discussed and challenged by sociologists, heterodox economists, management scholars, and other critics. This chapter reviews and assesses these critiques, focusing on behavioral issues (bounded rationality and motivation), process (including path dependence and the selection argument), entrepreneurship, and the challenge from knowledge-based theories of the firm

A rise in NAD precursor nicotinamide mononucleotide (NMN) after injury promotes axon degeneration.

NAD metabolism regulates diverse biological processes, including ageing, circadian rhythm and axon survival. Axons depend on the activity of the central enzyme in NAD biosynthesis, nicotinamide mononucleotide adenylyltransferase 2 (NMNAT2), for their maintenance and degenerate rapidly when this activity is lost. However, whether axon survival is regulated by the supply of NAD or by another action of this enzyme remains unclear. Here we show that the nucleotide precursor of NAD, nicotinamide mononucleotide (NMN), accumulates after nerve injury and promotes axon degeneration. Inhibitors of NMN-synthesising enzyme NAMPT confer robust morphological and functional protection of injured axons and synapses despite lowering NAD. Exogenous NMN abolishes this protection, suggesting that NMN accumulation within axons after NMNAT2 degradation could promote degeneration. Ectopic expression of NMN deamidase, a bacterial NMN-scavenging enzyme, prolongs survival of injured axons, providing genetic evidence to support such a mechanism. NMN rises prior to degeneration and both the NAMPT inhibitor FK866 and the axon protective protein Wld(S) prevent this rise. These data indicate that the mechanism by which NMNAT and the related Wld(S) protein promote axon survival is by limiting NMN accumulation. They indicate a novel physiological function for NMN in mammals and reveal an unexpected link between new strategies for cancer chemotherapy and the treatment of axonopathies

Assessing Drivers Situation Awareness in Semi-Autonomous Vehicles: ASP based Characterisations of Driving Dynamics for Modeling Scene Interpretation and Projection

Semi-autonomous driving, as it is already available today and will eventually become even more accessible, implies the need for driver and automation system to reliably work together in order to ensure safe driving. A particular challenge in this endeavour are situations in which the vehicle's automation is no longer able to drive and is thus requesting the human to take over. In these situations the driver has to quickly build awareness for the traffic situation to be able to take over control and safely drive the car. Within this context we present a software and hardware framework to asses how aware the driver is about the situation and to provide human-centred assistance to help in building situation awareness. The framework is developed as a modular system within the Robot Operating System (ROS) with modules for sensing the environment and the driver state, modelling the driver's situation awareness, and for guiding the driver's attention using specialized Human Machine Interfaces (HMIs). A particular focus of this paper is on an Answer Set Programming (ASP) based approach for modelling and reasoning about the driver's interpretation and projection of the scene. This is based on scene data, as well as eye-tracking data reflecting the scene elements observed by the driver. We present the overall application and discuss the role of semantic reasoning and modelling cognitive functions based on logic programming in such applications. Furthermore we present the ASP approach for interpretation and projection of the driver's situation awareness and its integration within the overall system in the context of a real-world use-case in simulated as well as in real driving

Multi-Criteria Evaluation of Aircraft Cockpit Systems by Model-based Simulation of Pilot Performance

International audienceThe paper describes a new methodology for simulation and evaluating human-machine interaction in aircraft cockpits with the objective to assess the impact of a new system design on overall flight crew performance. The methodology shall allow to assess multiple performance criteria and to derive needed design improvements more accurately and earlier (in the development process) and with reduced effort compared to existing approaches. The main technical enabler is a cognitive model of pilot behaviour. The focus of the paper is on the application of the new methodology for simulating and evaluating the interaction with a 4D Advanced Flight Management System

KONECT: Implementation and Extension of a Method for the Development of Safety-Critical Human-Machine Interaction Interfaces

In safety-critical systems, monitoring can be risky, because overlooking or misinterpreting important information can lead to serious consequences. For this purpose, the KONECT method was developed. The method is capable of systematically deriving information visualizations for monitoring tasks in safety-critical systems. We have studied this method and describe planned extensions and implementations of the steps of the KONECT method. In this way, the method offers more possibilities and can be applied more easily by the user