Flexicurity, workfare or inclusion? The politics of welfare and activation in the UK and Denmark

In this paper through a comparative analysis of welfare to work in the UK and Denmark we wish to redefine the debate and challenge dominant notions of inclusion and exclusion and illustrate how the European Employment Strategy is influenced by different national contexts. The paper sets out to provide a broad comparative framework which places greater emphasis on politics and agency and the role of localisation in the configuration of welfare changes. In the conclusion we outline some suggestions for new guidelines and evaluation criteria of the EU-employment and inclusion strategies and their national implementation. We are aware that the politics of inclusion involves other social policy instruments such as, for example neighbourhood renewal, however, it is employability and insertion into the labour market that are dominant in liberal and social democratic welfare discourses

Cosmology With A Dark Refraction Index

We review Gordon's optical metric and the transport equations for the amplitude and polarization of a geometrical optics wave traveling in a gravity field. We apply the theory to the FLRW cosmologies by associating a refraction index with the cosmic fluid. We then derive an expression for the accumulated effect of a refraction index on the distance redshift relations and fit the Hubble curve of current supernova observations with a non-accelerating cosmological model. We also show that some observational effects caused by inhomogeneities, e.g. the Sachs-Wolfe effect, can be interpreted as being caused by an effective index of refraction, and hence this theory could extend to other speed of light communications such as gravitational radiation and neutrino fluxes.Comment: 21 pages, 3 figure

Evaluation of Technology Concepts for Traffic Data Management and Relevant Audio for Datalink in Commercial Airline Flight Decks

Datalink is currently operational for departure clearances and in oceanic environments and is currently being tested in high altitude domestic enroute airspace. Interaction with even simple datalink clearances may create more workload for flight crews than the voice system they replace if not carefully designed. Datalink may also introduce additional complexity for flight crews with hundreds of uplink messages now defined for use. Finally, flight crews may lose airspace awareness and operationally relevant information that they normally pickup from Air Traffic Control (ATC) voice communications with other aircraft (i.e., party-line transmissions). Once again, automation may be poised to increase workload on the flight deck for incremental benefit. Datalink implementation to support future air traffic management concepts needs to be carefully considered, understanding human communication norms and especially, the change from voice- to text-based communications modality and its effect on pilot workload and situation awareness. Increasingly autonomous systems, where autonomy is designed to support human-autonomy teaming, may be suited to solve these issues. NASA is conducting research and development of increasingly autonomous systems, utilizing machine-learning algorithms seamlessly integrated with humans whereby task performance of the combined system is significantly greater than the individual components. Increasingly autonomous systems offer the potential for significantly improved levels of performance and safety that are superior to either human or automation alone. Two increasingly autonomous systems concepts - a traffic data manager and a conversational co-pilot - were developed to intelligently address the datalink issues in a complex, future state environment with significant levels of traffic. The system was tested for suitability of datalink usage for terminal airspace. The traffic data manager allowed for automated declutter of the Automatic Dependent Surveillance-Broadcast (ADS-B) display. The system determined relevant traffic for display based on machine learning algorithms trained by experienced human pilot behaviors. The conversational co-pilot provided relevant audio air traffic control messages based on context and proximity to ownship. Both systems made use of the connected aircraft concepts to provide intelligent context to determine relevancy above and beyond proximity to ownship. A human-in-the-loop test was conducted in NASA Langley Research Centers Integration Flight Deck B-737-800 simulator to evaluate the traffic data manager and the conversational co-pilot. Twelve airline crews flew various normal and non-normal procedures and their actions and performance were recorded in response to the procedural events. This paper details the flight crew performance and evaluation during the events

Increasing Pilots Understanding of Future Automation State an Evaluation of an Automation State and Trajectory Prediction System

A pilot in the loop flight simulation study was conducted at NASA Langley Research Center to evaluate a trajectory prediction system. The trajectory prediction system computes a five-minute prediction of the lateral and vertical path of the aircraft given the current and intent state of the automation. The prediction is shown as a graphical representation so the pilots can form an accurate mental model of the future state. Otherwise, many automation changes and triggers are hidden from the flight crew or need to be consolidated to understand if a change will occur and the exact timing of the change. Varying dynamic conditions like deceleration can obscure the future trajectory and the ability to meet constraints, especially in the vertical dimension. Current flight deck indications of flight path assume constant conditions and do not adequately support the flight crew to make correct judgments regarding constraints. The study was conducted using ten commercial airline crews from multiple airlines, paired by airline to minimize procedural effects. Scenarios spanned a range of conditions that provided evaluation in a realistic environment with complex traffic and weather conditions. In particular, scenarios probed automation state and loss of state awareness. The technology was evaluated and contrasted with current state-of-the-art flight deck capabilities modeled from the Boeing 787. Objective and subjective data were collected from aircraft parameters, questionnaires, audio/video recordings, head/eye tracking data, and observations. This paper details findings about the trajectory prediction system including recommendations about further study

Frequency-specific effects of low-intensity rTMS can persist for up to 2 weeks post-stimulation: A longitudinal rs-fMRI/MRS study in rats

Background Evidence suggests that repetitive transcranial magnetic stimulation (rTMS), a non-invasive neuromodulation technique, alters resting brain activity. Despite anecdotal evidence that rTMS effects wear off, there are no reports of longitudinal studies, even in humans, mapping the therapeutic duration of rTMS effects. Objective Here, we investigated the longitudinal effects of repeated low-intensity rTMS (LI-rTMS) on healthy rodent resting-state networks (RSNs) using resting-state functional MRI (rs-fMRI) and on sensorimotor cortical neurometabolite levels using proton magnetic resonance spectroscopy (MRS). Methods Sprague-Dawley rats received 10 min LI-rTMS daily for 15 days (10 Hz or 1 Hz stimulation, n=9 per group). MRI data were acquired at baseline, after seven days and after 14 days of daily stimulation and at two more timepoints up to three weeks post-cessation of daily stimulation. Results 10 Hz stimulation increased RSN connectivity and GABA, glutamine, and glutamate levels. 1 Hz stimulation had opposite but subtler effects, resulting in decreased RSN connectivity and glutamine levels. The induced changes decreased to baseline levels within seven days following stimulation cessation in the 10 Hz group but were sustained for at least 14 days in the 1 Hz group. Conclusion Overall, our study provides evidence of long-term frequency-specific effects of LI-rTMS. Additionally, the transient connectivity changes following 10 Hz stimulation suggest that current treatment protocols involving this frequency may require ongoing “top-up” stimulation sessions to maintain therapeutic effects

Combined rTMS/fMRI studies: An overlooked resource in animal models

Repetitive transcranial magnetic stimulation (rTMS) is a non-invasive neuromodulation technique, which has brain network-level effects in healthy individuals and is also used to treat many neurological and psychiatric conditions in which brain connectivity is believed to be abnormal. Despite the fact that rTMS is being used in a clinical setting and animal studies are increasingly identifying potential cellular and molecular mechanisms, little is known about how these mechanisms relate to clinical changes. This knowledge gap is amplified by non-overlapping approaches used in preclinical and clinical rTMS studies: preclinical studies are mostly invasive, using cellular and molecular approaches, while clinical studies are non-invasive, including functional magnetic resonance imaging (fMRI), TMS electroencephalography (EEG), positron emission tomography (PET), and behavioral measures. A non-invasive method is therefore needed in rodents to link our understanding of cellular and molecular changes to functional connectivity changes that are clinically relevant. fMRI is the technique of choice for examining both short and long term functional connectivity changes in large-scale networks and is becoming increasingly popular in animal research because of its high translatability, but, to date, there have been no reports of animal rTMS studies using this technique. This review summarizes the main studies combining different rTMS protocols with fMRI in humans, in both healthy and patient populations, providing a foundation for the design of equivalent studies in animals. We discuss the challenges of combining these two methods in animals and highlight considerations important for acquiring clinically-relevant information from combined rTMS/fMRI studies in animals. We believe that combining rTMS and fMRI in animal models will generate new knowledge in the following ways: functional connectivity changes can be explored in greater detail through complementary invasive procedures, clarifying mechanism and improving the therapeutic application of rTMS, as well as improving interpretation of fMRI data. And, in a more general context, a robust comparative approach will refine the use of animal models of specific neuropsychiatric conditions

Experimental simulation: using generative modeling and palaeoecological data to understand human-environment interactions

The amount of palaeoecological information available continues to grow rapidly, supporting improved descriptions of the dynamics of past ecosystems and enabling them to be seen from new perspectives. At the same time, there has been concern over whether palaeoecological enquiry needs to move beyond descriptive inference to a more hypothesis-focussed, or experimental approach. However, the extent to which conventional hypothesis-driven scientific frameworks can be applied to historical contexts (i.e., the past) is the subject of ongoing debate. In other disciplines concerned with human-environment interactions, including physical geography and archaeology, there has been growing use of generative simulation models, typified by agent-based approaches. Generative modeling encourages counter-factual questioning (“what if…?,”) a mode of argument that is particularly important in systems and time-periods, such as the Holocene, and now the Anthropocene, where the effects of humans and other biophysical processes are deeply intertwined. However, palaeoecologically focused simulation of the dynamics of the ecosystems of the past either seems to be conducted to assess the applicability of some model to the future or treats humans simplistically as external forcing factors. In this review we consider how generative simulation-modeling approaches could contribute to our understanding of past human-environment interactions. We consider two key issues: the need for null models for understanding past dynamics and the need to be able learn more from pattern-based analysis. In this light, we argue that there is considerable scope for palaeoecology to benefit from developments in generative models and their evaluation. We discuss the view that simulation is a form of experiment and by using case studies, consider how the many patterns available to palaeoecologists can support model evaluation in a way that moves beyond simplistic pattern-matching and how such models might also inform us about the data themselves and the processes generating them. Our emphasis is on how generative simulation might complement traditional palaeoecological methods and proxies rather than on a detailed overview of the modeling methods themselves

Information Management to Mitigate Loss of Control Airline Accidents

Loss of control inflight continues to be the leading contributor to airline accidents worldwide and unreliable airspeed has been a contributing factor in many of these accidents. Airlines and the FAA developed training programs for pilot recognition of these airspeed events and many checklists have been designed to help pilots troubleshoot. In addition, new aircraft designs incorporate features to detect and respond in such situations. NASA has been using unreliable airspeed events while conducting research recommended by the Commercial Aviation Safety Team. Even after significant industry focus on unreliable airspeed, research and other evidence shows that highly skilled and trained pilots can still be confused by the condition and there is a lack of understanding of what the associated checklist(s) attempts to uncover. Common mode failures of analog sensors designed for measuring airspeed continue to confound both humans and automation when determining which indicators are correct. This paper describes failures that have occurred in the past and where/how pilots may still struggle in determining reliable airspeed when confronted with conflicting information. Two latest generation aircraft architectures will be discussed and contrasted. This information will be used to describe why more sensors used in classic control theory will not solve the problem. Technology concepts are suggested for utilizing existing synoptic pages and a new synoptic page called System Interactive Synoptic (SIS). SIS details the flow of flight critical data through the avionics system and how it is used by the automation. This new synoptic page as well as existing synoptics can be designed to be used in concert with a simplified electronic checklist (sECL) to significantly reduce the time to configure the flight deck avionics in the event of a system or sensor failure

Supernova Brightening from Chameleon-Photon Mixing

Measurements of standard candles and measurements of standard rulers give an inconsistent picture of the history of the universe. This discrepancy can be explained if photon number is not conserved as computations of the luminosity distance must be modified. I show that photon number is not conserved when photons mix with chameleons in the presence of a magnetic field. The strong magnetic fields in a supernova mean that the probability of a photon converting into a chameleon in the interior of the supernova is high, this results in a large flux of chameleons at the surface of the supernova. Chameleons and photons also mix as a result of the intergalactic magnetic field. These two effects combined cause the image of the supernova to be brightened resulting in a model which fits both observations of standard candles and observations of standard rulers.Comment: 17 pages, 3 figure