Levels of abstraction in human supervisory control teams

This paper aims to report a study into the levels of abstraction hierarchy (LOAH) in two energy distribution teams. The original proposition for the LOAH was that it depicted five levels of system representation, working from functional purpose through to physical form to determine causes of a malfunction, or from physical form to functional purpose to determine the purpose of system function. The LOAH has been widely used throughout human supervisory control research to explain individual behaviour. The research seeks to focus on the application the LOAH to human supervisory control teams in semi-automated “intelligent” systems

Testing Hollnagel's contextual control mod

Please contact publisher for further reprinting or re-useThis article sets out to test the hypothetical COtext and COntrol Model (COCOM) developed by Hollnagel (1993). Essentially, Hollnagel develops the argument that team behavior should be analyzed at a macro, rather than micro, level. He proposes 4 principal models of team activity: strategic, tactical, opportunistic, and scrambled. These modes of team behavior vary in terms of the degree of forward planning (highest in the strategic mode) and reactivity to the environment (highest in the scrambled mode). He further hypothesizes a linear progression through the modes from strategic to tactical to opportunistic to scrambled, depending on context, and vice versa. To test the COCOM model, we placed teams of people in a simulated energy distribution system. Our results confirm Hollnagel's hypothesized model in 2 main ways. First, we show that the team behavior could be categorized reliably into the 4 control modes and this provided a useful way of distinguishing between experimental conditions. Second, the progression between control modes conformed to the linear progression as predicted. This research provided the first independent test of the COCOM model and lends empirical support to the hypotheses

Microcanonical studies on isoscaling

The exponential scaling of isotopic yields is investigated for sources of different sizes over a broad range of excitation energies and freeze-out volumes, in both primary and asymptotic stages of the decay in the framework of a microcanonical multifragmentation model. It was found that the scaling parameters have a strong dependence on the considered pair of equilibrated sources and excitation energy and are affected by the secondary particle emission of the break-up fragments. No significant influence of the freeze-out volume on the considered isotopic ratios has been observed. Deviations of microcanonical results from grandcanonical expectations are discussed.Comment: 19 pages, 6 figure

Stripe Fluctuations, Carriers, Spectroscopies, Transport, and BCS-BEC Crossover in the High-T_c Cuprates

The quasiparticles of the high-T_c cuprates are found to consist of: polaron-like "stripons" carrying charge, and associated primarily with large-U orbitals in stripe-like inhomogeneities; "quasielectrons" carrying charge and spin, and associated with hybridized small-U and large-U orbitals; and "svivons" carrying spin and lattice distortion. It is shown that this electronic structure leads to the systematic behavior of spectroscopic and transport properties of the cuprates. High-T_c pairing results from transitions between pair states of stripons and quasielectrons through the exchange of svivons. The cuprates fall in the regime of crossover between BCS and preformed-pairs Bose-Einstein condensation behaviors.Comment: Latex file, 8 pages (new version including a figure

Multiphysics Modelling and Simulation of Thrombolysis via Activated Platelet-Targeted Nanomedicine

PURPOSE: This study establishes a multiphysics simulation platform for both conventional and targeted thrombolysis using tissue plasminogen activator (tPA). Based on our computational results, the effects of therapeutic parameters on the dynamics of thrombolysis and the risk of side effects are investigated. METHODS: The model extends our previously developed one-dimensional(1D) mathematical models for fibrinolysis by incorporating targeted thrombolysis. It consists of two parts: (i) a coupled mathematical model of systemic pharmacokinetics (PK) and pharmacodynamics (PD) and local PD in a 1D occluded artery, and (ii) a mechanistic model for a targeted thrombolytic system via activated platelet-targeted tPA-loaded nanovesicles (tPA-NV), with model parameters derived from our in vitro experiments. A total of 16 therapeutic scenarios are simulated by varying the clot location and composition as well as the dosing regimen with free tPA or tPA-NV. RESULTS: Our simulation results indicate that tPA-NV offers several advantages over free tPA for thrombolysis. It reduces systemic exposure of tPA, thereby minimising the risk of bleeding complications. Simulations with different tPA-NV doses reveal that tPA-NV at 10% of the recommended dose can be as effective as the standard regimen with the full recommended dose of free tPA, demonstrating the potential of our tPA-NV as a new thrombolytic strategy with a reduced tPA dose. Moreover, faster recanalisation can be achieved with tPA-NV, especially for platelet-rich(or fibrin-poor) clots. CONCLUSIONS: Our simulation platform for thrombolysis with well-tuned model parameters can be used to evaluate and optimise treatment regimens of existing and new thrombolytic therapies via benefit/risk assessment under various therapeutic scenarios

Ab initio prediction of Boron compounds arising from Borozene: Structural and electronic properties

Structure and electronic properties of two unusual boron clusters obtained by fusion of borozene rings has been studied by means of first principles calculations, based on the generalized-gradient approximation of the density functional theory, and the semiempirical tight-binding method was used for the transport calculations. The role of disorder has also been considered with single vacancies and substitutional atoms. Results show that the pure boron clusters are topologically planar and characterized by (3c-2e) bonds, which can explain, together with the aromaticity (estimated by means of NICS), the remarkable cohesive energy values obtained. Such feature makes these systems competitive with the most stable boron clusters to date. On the contrary, the introduction of impurities compromises stability and planarity in both cases. The energy gap values indicate that these clusters possess a semiconducting character, while when the larger system is considered, zero-values of the density of states are found exclusively within the HOMO-LUMO gap. Electron transport calculations within the Landauer formalism confirm these indications, showing semiconductor-like low bias differential conductance for these stuctures. Differences and similarities with Carbon clusters are highlighted in the discussion.Comment: 10 pages, 2 tables, 5 figure

Pertactin-negative and filamentous hemagglutinin-negative Bordetella pertussis, Australia, 2013-2017

During the 2008-2012 pertussis epidemic in Australia, pertactin (Prn)-negative Bordetella pertussis emerged. We analyzed 78 isolates from the 2013-2017 epidemic and documented continued expansion of Prn-negative ptxP3 B. pertussis strains. We also detected a filamentous hemagglutinin- negative and Prn-negative B. pertussis isolate

SMART: Unique splitting-while-merging framework for gene clustering

Copyright @ 2014 Fa et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Successful clustering algorithms are highly dependent on parameter settings. The clustering performance degrades significantly unless parameters are properly set, and yet, it is difficult to set these parameters a priori. To address this issue, in this paper, we propose a unique splitting-while-merging clustering framework, named “splitting merging awareness tactics” (SMART), which does not require any a priori knowledge of either the number of clusters or even the possible range of this number. Unlike existing self-splitting algorithms, which over-cluster the dataset to a large number of clusters and then merge some similar clusters, our framework has the ability to split and merge clusters automatically during the process and produces the the most reliable clustering results, by intrinsically integrating many clustering techniques and tasks. The SMART framework is implemented with two distinct clustering paradigms in two algorithms: competitive learning and finite mixture model. Nevertheless, within the proposed SMART framework, many other algorithms can be derived for different clustering paradigms. The minimum message length algorithm is integrated into the framework as the clustering selection criterion. The usefulness of the SMART framework and its algorithms is tested in demonstration datasets and simulated gene expression datasets. Moreover, two real microarray gene expression datasets are studied using this approach. Based on the performance of many metrics, all numerical results show that SMART is superior to compared existing self-splitting algorithms and traditional algorithms. Three main properties of the proposed SMART framework are summarized as: (1) needing no parameters dependent on the respective dataset or a priori knowledge about the datasets, (2) extendible to many different applications, (3) offering superior performance compared with counterpart algorithms.National Institute for Health Researc