Assessing Cognitive Processing and Human Factors Challenges in NextGen Air Traffic Control Tower Team Operations

Previous research of Terminal Radar Control Facilities and Standard Terminal Automation Replacement Systems interactions by the authors examined how combined NextGen digitized technology affects air traffic controller functions. Applying their updated SHELL model, human factors implications on the Tower Team before and after implementing NextGen technology were examined, focusing on cognitive loading and automated functions affecting each team member. A survey examined where cognitive difficulties occur when controllers are responsible for multiple screen views, remote airfields or helipads, and digitized cameras and blind spots. Scanning challenges were identified where local traffic, ground operations, and data converge onto one screen, and when attention is diverted to distant screens. Also studied were automatic aircraft handoffs and potential for missed handoffs, and, assessing changes from voice communication to text messaging for human error. Findings indicated a necessity for controllers to manage balanced tasking, vigilance pacing, and resource management

The colonization history of British water vole (Arvicola amphibius (Linnaeus, 1758)): origins and development of the Celtic fringe.

The terminal Pleistocene and Early Holocene, a period from 15 000 to 18 000 Before Present (BP), was critical in establishing the current Holarctic fauna, with temperate-climate species largely replacing cold-adapted ones at mid-latitudes. However, the timing and nature of this process remain unclear for many taxa, a point that impacts on current and future management strategies. Here, we use an ancient DNA dataset to test more directly postglacial histories of the water vole (Arvicola amphibius, formerly A terrestris), a species that is both a conservation priority and a pest in different parts of its range. We specifically examine colonization of Britain, where a complex genetic structure can be observed today. Although we focus on population history at the limits of the species' range, the inclusion of additional European samples allows insights into European postglacial colonization events and provides a molecular perspective on water vole taxonomy

Thermodynamics of an ideal generalized gas:II Means of order α\alpha

The property that power means are monotonically increasing functions of their order is shown to be the basis of the second laws not only for processes involving heat conduction but also for processes involving deformations. In an $L$-potentail equilibration the final state will be one of maximum entropy, while in an entropy equilibrium the final state will be one of minimum $L$. A metric space is connected with the power means, and the distance between means of different order is related to the Carnot efficiency. In the ideal classical gas limit, the average change in the entropy is shown to be proportional to the difference between the Shannon and R\'enyi entropies for nonextensive systems that are multifractal in nature. The $L$-potential, like the internal energy, is a Schur convex function of the empirical temperature, which satisfies Jensen's inequality, and serves as a measure of the tendency to uniformity in processes involving pure thermal conduction.Comment: 8 page

Sri Lankan tsunami refugees: a cross sectional study of the relationships between housing conditions and self-reported health

BACKGROUND: On the 26th December 2004 the Asian tsunami devastated the Sri Lankan coastline. More than two years later, over 14,500 families were still living in transitional shelters. This study compares the health of the internally displaced people (IDP), living in transitional camps with those in permanent housing projects provided by government and non-government organisations in Sri Lanka. METHODS: This study was conducted in seven transitional camps and five permanent housing projects in the south west of Sri Lanka. Using an interviewer-led questionnaire, data on the IDPs' self-reported health and housing conditions were collected from 154 participants from transitional camps and 147 participants from permanent housing projects. Simple tabulation with non-parametric tests and logistic regression were used to identify and analyse relationships between housing conditions and the reported prevalence of specific symptoms. RESULTS: Analysis showed that living conditions were significantly worse in transitional camps than in permanent housing projects for all factors investigated, except 'having a leaking roof'. Transitional camp participants scored significantly lower on self-perceived overall health scores than those living in housing projects. After controlling for gender, age and marital status, living in a transitional camp compared to a housing project was found to be a significant risk factor for the following symptoms; coughs OR: 3.53 (CI: 2.11-5.89), stomach ache 4.82 (2.19-10.82), headache 5.20 (3.09-8.76), general aches and pains 6.44 (3.67-11.33) and feeling generally unwell 2.28 (2.51-7.29). Within transitional camp data, the only condition shown to be a significant risk factor for any symptom was household population density, which increased the risk of stomach aches 1.40 (1.09-1.79) and headaches 1.33 (1.01-1.77). CONCLUSION: Internally displaced people living in transitional camps are a vulnerable population and specific interventions need to be targeted at this population to address the health inequalities that they report to be experiencing. Further studies need to be conducted to establish which aspects of their housing environment predispose them to poorer health

Phase Transitions and Their Interaction with Dislocations in Silicon

In this paper, phase transformations (PTs) in silicon were investigated through molecular dynamics (MD) using Tersoff potential. In the first step, simulations of PTs in single crystal silicon under various stress-controlled loading were carried out. Results shows that all instability points under various stress states are described by criteria, which are linear in the space of normal stresses. There is a region in the stress space in which conditions for direct and reverse PTs coincide and a unique homogeneous phase transition (without nucleation) can be realized. Finally, phase transition in bi-crystalline silicon with a dislocation pileup along the grain boundary (GB) was carried out. Results showed that the phase transition pressure first decreases linearly with the number of dislocation pileups and then reaches a plateau with the accumulation of dislocations in the pileup. The maximum reduction of phase transition pressure is 30% compared to that for perfect single crystalline silicon

Recognizing recurrent neural networks (rRNN): Bayesian inference for recurrent neural networks

Recurrent neural networks (RNNs) are widely used in computational neuroscience and machine learning applications. In an RNN, each neuron computes its output as a nonlinear function of its integrated input. While the importance of RNNs, especially as models of brain processing, is undisputed, it is also widely acknowledged that the computations in standard RNN models may be an over-simplification of what real neuronal networks compute. Here, we suggest that the RNN approach may be made both neurobiologically more plausible and computationally more powerful by its fusion with Bayesian inference techniques for nonlinear dynamical systems. In this scheme, we use an RNN as a generative model of dynamic input caused by the environment, e.g. of speech or kinematics. Given this generative RNN model, we derive Bayesian update equations that can decode its output. Critically, these updates define a 'recognizing RNN' (rRNN), in which neurons compute and exchange prediction and prediction error messages. The rRNN has several desirable features that a conventional RNN does not have, for example, fast decoding of dynamic stimuli and robustness to initial conditions and noise. Furthermore, it implements a predictive coding scheme for dynamic inputs. We suggest that the Bayesian inversion of recurrent neural networks may be useful both as a model of brain function and as a machine learning tool. We illustrate the use of the rRNN by an application to the online decoding (i.e. recognition) of human kinematics

Theory of Star Formation

We review current understanding of star formation, outlining an overall theoretical framework and the observations that motivate it. A conception of star formation has emerged in which turbulence plays a dual role, both creating overdensities to initiate gravitational contraction or collapse, and countering the effects of gravity in these overdense regions. The key dynamical processes involved in star formation -- turbulence, magnetic fields, and self-gravity -- are highly nonlinear and multidimensional. Physical arguments are used to identify and explain the features and scalings involved in star formation, and results from numerical simulations are used to quantify these effects. We divide star formation into large-scale and small-scale regimes and review each in turn. Large scales range from galaxies to giant molecular clouds (GMCs) and their substructures. Important problems include how GMCs form and evolve, what determines the star formation rate (SFR), and what determines the initial mass function (IMF). Small scales range from dense cores to the protostellar systems they beget. We discuss formation of both low- and high-mass stars, including ongoing accretion. The development of winds and outflows is increasingly well understood, as are the mechanisms governing angular momentum transport in disks. Although outstanding questions remain, the framework is now in place to build a comprehensive theory of star formation that will be tested by the next generation of telescopes.Comment: 120 pages, to appear in ARAA. No changes from v1 text; permission statement adde

Internet-based Self-Assessment after the Tsunami: lessons learned

BACKGROUND: In the aftermath of the Tsunami disaster in 2004, an online psychological self-assessment (ONSET) was developed and made available by the University of Zurich in order to provide an online screening instrument for Tsunami victims to test if they were traumatized and in need of mental health care. The objective of the study was to report the lessons learnt that were made using an Internet-based, self-screening instrument after a large-scale disaster and to discuss its outreach and usefulness. METHODS: Users of the online self-assessment decided after finishing the procedure whether their dataset could be used for quality control and scientific evaluation Their answers were stored anonymously only if they consented (which was the case in 88% of the sample), stratified analyses according to level of exposure were conducted. RESULTS: A total of 2,914 adult users gave their consent for analysis of the screenings. Almost three quarter of the sample filled out the ONSET questionnaire within the first four weeks. Forty-one percent of the users reported direct exposure to the Tsunami disaster. Users who were injured by the Tsunami and users who reported dead or injured family members showed the highest degree of PTSD symptoms. CONCLUSION: ONSET was used by a large number of subjects who thought to be affected by the catastrophe in order to help them decide if they needed to see a mental health professional. Furthermore, men more frequently accessed the instrument than women, indicating that Internet-based testing facilitates reaching out to a different group of people than "ordinary" public mental health strategies