Miracle-dz/UniFAR-FTUs huggingface dataset:
Extent of ST-segment depression and cardiac events in non-ST-segment elevation acute coronary syndromes.

AIMS We sought to determine whether the extent of myocardial ischaemia on the admission electrocardiogram (ECG) has independent predictive value for short-term risk stratification of patients with non-ST-segment elevation acute coronary syndromes (NSTE ACS). Although the presence of ischaemic ECG changes on admission has been shown to predict outcome, the relationship between the extent of ECG changes and the risk of cardiac events is still ill defined. METHODS AND RESULTS We analysed the admission ECGs of 5192 ACS patients enrolled in the GUSTO-IIb trial, without an ECG indication for thrombolysis. ECG tracings showing one or more of the following were eligible: ST-segment depression >0.5 mm, T-wave inversion >1 mm, and ST-segment elevation >0.5 mm but <1 mm. ECG variables associated with unfavourable 30 day outcomes in a univariable analysis were further assessed in a multivariable logistic regression model including independent clinical predictors. In the multivariable clinical, enzymatic, and ECG model, the sum of ST-segment depression (in millimetres) in all leads was a powerful independent predictor of 30 day death (P<0.0001), with a continuous increase in risk with the extent of ST-segment depression. The sum of ST-segment depression (P<0.0001) and the presence of minimal inferior ST-segment elevation (P<0.0001) or anterior ST-segment elevation (P=0.0182) were also independent predictors of the composite of death and myocardial infarction or reinfarction. The extent of ST-segment depression showed a highly significant correlation with the prevalence of three-vessel (P<0.0001) or left main coronary disease (P<0.0001), and also with the peak levels of creatine kinase (P<0.0001) during the index episode of ACS. CONCLUSION In patients with NSTE ACS, the sum of ST-segment depression in all ECG leads is a powerful predictor of all-cause mortality at 30 days, independent of clinical variables and correlates with the extent and severity of coronary artery disease. The presence of even minimal (<1 mm) ST-segment elevation in anterior or inferior leads is independently associated with adverse outcomes.
Issues in Ontology-based Information Integration

Solving queries to support e-commerce transactions can involve retrieving and integrating information from multiple information resources. Often, users don’ t care which resources are used to answer their query. In such situations, the ideal solution would be to hide from the user the details of the resources involved in solving a particular query. An example would be providing seamless access to a set of heterogeneous electronic product catalogues. There are many problems that must be addressed before such a solution can be provided. In this paper, we discuss a number of these problems, indicate how we have addressed these and go on to describe the proof-of-concept demonstration system we have developed.
Multi criteria decision making (MCDM): A modified partial order theory (POT) approach

A partial order based method is presented for multi criteria decision making (MCDM), using a modified and novel partial order theory (POT) approach. The aim of this paper is to resolve some drawbacks of several conventional methods of determining the best alternative. The proposed approach incorporates data matrices, which results in different scenarios (alternatives), with their specific probabilities, called linear extensions (LE). Thereafter, the ranking probability matrix (RPM) is obtained, which will lead us to a total order ranking of the MCDM alternatives. In order to evaluate the performance of the proposed MCDM method, a shopping case study is conducted and capabilities of the proposed methodology are demonstrated.
Social anxiety and self-presentation: a conceptualization and model.

This article presents a self-presentation approach to the study of social anxiety that proposes that social anxiety arises when people are motivated to make a preferred impression on real or imagined audiences but doubt they will do so, and thus perceive or imagine unsatisfactory evaluative reactions from subjectively important audiences. We presume that specific situational and dispositional an- tecedents of social anxiety operate by influencing people's motivation to impress others and their expectations of satisfactorily doing so. In contrast to drive models of anxiety but consistent with social learning theory, it is argued that the cognitive state of the individual mediates both affective arousal and behavior. The tradi- tional inverted-U relation between anxiety and performance is reexamined in this light. Implications of the approach for counseling situations are considered, especially the recommendation that treatments be tailored to the specific type of self-presentational problem encountered by clients,
Mapping the Design Space for Socio-Cognitive Task Design

This chapter describes a framework for cognitive task design that focuses on social and communication issues. It is intended to complement the more traditional task oriented views. The chapter starts by describing a process model for cognitive task design then introduces cognitive and social pathologies: heuristics for analysing potential causes of failure in sociotechnical systems. This is followed by an introduction to generic tasks as reusable models for specifying human action, to which requirements for computer system task support can be attached, as well as the pathologies to warn the designer about potential failure points. A general model of discourse is described which is also associated with pathologies and generic requirements to guide the designer towards reusable knowledge at appropriate stages in the communication process. The discourse model is supplemented with patterns for specific types of communication such as Command and Control, proposals and liaison, etc. The next section proposes models for analysing power and trust in human-human and interorganisational relationships. Once again models are associated with pathologies and countermeasures. Use of the models is illustrated by analysis of Command and Control tasks in the combat sub-system of a Navy frigate. A scenario-based approach is taken to walk through the models using operation scenarios of a missile attack. The design implications for cognitive task support and communication are assessed, then two alternative designs for intelligent computerised radar and standard radar are compared using the generic models for analysing communication, perceptions of power and trust. The chapter concludes by reviewing the lessons learned for functional allocation, and future work in providing more effective decision support for operators in socio-technical systems.
Impact forces during running: Loaded questions, sensible outcomes

Load carriage was used as an experimental tool to evaluate the ability of an anatomically-based, two-mass model of the human body to predict vertical impact and peak forces during running from only four inputs: body weight (W<sub>b</sub>), contact time (t<sub>c</sub>), aerial time, (t<sub>a</sub>), and lower-limb acceleration (a<sub>1</sub>). Simultaneous motion and force data were acquired from seven subjects during steady-speed trials (3.0-6.0 m·s<sup>-1</sup>) on a custom, force-instrumented treadmill under three loading conditions: unloaded (1.0 W<sub>b</sub>), 15% added weight (1.15 W<sub>b</sub>) and 30% added weight (1.30 W<sub>b</sub>). Model-predicted impact and peak forces corresponded with measured values, on average, to within 14.9±1.3% and 13.8±0.6%, respectively (R<sup>2</sup> best-fits=0.82 and 0.88, n=71). Ankle jerk and velocity data derived from optical position-time data suggest wearable sensor acquisition of the model-needed inputs is fully feasible. We conclude that the two-mass model offers a promising approach to quantifying running ground reaction forces using wearable technologies.
Fast method for extracting representative graph from decorative character images

In this paper, we propose a fast method for extracting a representative graph from decorative character images. The representative graph is an effective method to describe structure information of a graph class. However, the computation time of existing methods for extracting a representative graph is extremely expensive. They search all combinations of nodes of a class. The proposed method calculates the common nodes in a class which have same features before the representative graph is extracted. The computation time can be reduced using the common nodes. To show the validly of the proposed method, experiments are carried out using decorative character images.
Routing Policy Engine Actions Persistent Events Events Liveness Messages Liveness PolicySafety Policy Module Apply Update Predicate Read + Predicate Write + Predicate PADRE Runtime Application Read Application Write Body Subscriptions Fetch Invalidation Subscriptions Body Subscriptions Fetch Invalid

This paper presents PADRE, a policy architecture that qualitatively simplifies the development of data replication systems. PADRE achieves this by embodying the right abstractions for replication in largescale systems. In particular, PADRE cleanly separates the problem of building a replication system into the subproblems of specifying safety policy and specifying liveness policy and identifies a surprisingly small set of primitives that are easy to use and sufficient to specify sophisticated safety constraints and liveness protocols. As a result, building a replication system is reduced to picking a consistency library and then writing a few rules in a declarative language to set up a communication topology. We demonstrate the flexibility and simplicity of PADRE by constructing 6 substantial and diverse systems using just a few dozen lines of system-specific policy code each. We demonstrate the agility of systems built on PADRE by adding new features to four systems yield significant performance improvements; each addition required fewer than 10 additional lines of code and took less than a day.
Resource Allocation for Downlink Multi-Cell OFDMA Cognitive Radio Network Using Hungarian Method

This paper considers the problem of resource allocation for downlink part of an OFDM-based multi-cell cognitive radio network which consists of multiple secondary transmitters and receivers communicating simultaneously in the presence of multiple primary users. We present a new framework to maximize the total data throughput of secondary users by means of subchannel assignment, while ensuring interference leakage to PUs is below a threshold. In this framework, we first formulate the resource allocation problem as a nonlinear and nonconvex optimization problem. Then we represent the problem as a maximum weighted matching in a bipartite graph and propose an iterative algorithm based on Hungarian method to solve it. The present contribution develops an efficient subchannel allocation algorithm that assigns subchannels to the secondary users without the perfect knowledge of fading channel gain between cognitive radio transmitter and primary receivers. The performance of the proposed subcarrier allocation algorithm is compared with a blind subchannel allocation as well as another scheme with the perfect knowledge of channel-state information. Simulation results reveal that a significant performance advantage can still be realized, even if the optimization at the secondary network is based on imperfect network information.
NONLINEAR TIDES IN CLOSE BINARY SYSTEMS

We study the excitation and damping of tides in close binary systems, accounting for the leading-order nonlinear corrections to linear tidal theory. These nonlinear corrections include two distinct physical effects: three-mode nonlinear interactions, i.e., the redistribution of energy among stellar modes of oscillation, and nonlinear excitation of stellar normal modes by the time-varying gravitational potential of the companion. This paper, the first in a series, presents the formalism for studying nonlinear tides and studies the nonlinear stability of the linear tidal flow. Although the formalism we present is applicable to binaries containing stars, planets, and/or compact objects, we focus on non-rotating solar-type stars with stellar or planetary companions. Our primary results include the following: (1) The linear tidal solution almost universally used in studies of binary evolution is unstable over much of the parameter space in which it is employed. More specifically, resonantly excited internal gravity waves in solar-type stars are nonlinearly unstable to parametric resonance for companion masses M′ ≳ 10–100 M⊕ at orbital periods P ≈ 1–10 days. The nearly static “equilibrium” tidal distortion is, however, stable to parametric resonance except for solar binaries with P ≲ 2–5 days. (2) For companion masses larger than a few Jupiter masses, the dynamical tide causes short length scale waves to grow so rapidly that they must be treated as traveling waves, rather than standing waves. (3) We show that the global three-wave treatment of parametric instability typically used in the astrophysics literature does not yield the fastest-growing daughter modes or instability threshold in many cases. We find a form of parametric instability in which a single parent wave excites a very large number of daughter waves (N ≈ 103[P/10 days] for a solar-type star) and drives them as a single coherent unit with growth rates that are a factor of ≈N faster than the standard three-wave parametric instability. These are local instabilities viewed through the lens of global analysis; the coherent global growth rate follows local rates in the regions where the shear is strongest. In solar-type stars, the dynamical tide is unstable to this collective version of the parametric instability for even sub-Jupiter companion masses with P ≲ a month. (4) Independent of the parametric instability, the dynamical and equilibrium tides excite a wide range of stellar p-modes and g-modes by nonlinear inhomogeneous forcing; this coupling appears particularly efficient at draining energy out of the dynamical tide and may be more important than either wave breaking or parametric resonance at determining the nonlinear dissipation of the dynamical tide.
Collaborative filtering via epidemic aggregation in distributed virtual environments

The ever-increasing amount of available information in today's digital society necessitates inline techniques for determining the most relevant content. Collaborative filtering (CF) systems have proven to be an adequate means for reducing informational overload and generating useful recommendations. Current systems are predominantly built on centralized or, more recently, structured Peer-to-Peer (P2P) approaches. However, in order to apply collaborative filtering to large-scale distributed virtual environments (DVEs) in unstructured networks with substatially higher user numbers, different approaches are necessary. Within this paper we present a collaborative filtering algorithm for DVEs utilizing epidemic data aggregation based exclusively on local information. Designed to be extremely scalable, it creates recommendations in a transparent way by distributing an accumulated view of favorite ratings to interacting users. The algorithm is intended for deployment in the HyperVerse - a self-organizing middleware service for large-scale DVEs - for generating and managing rating predictions of object favorites. Evaluation results show that, in terms of quality, locally aggregated predictions converge well on those obtained from an idealized global view.
Optimal Technology Selection and Operation of Commercial-Building Microgrids

The deployment of small ( < 1-2 MW ) clusters of generators, heat and electrical storage, efficiency investments, and combined heat and power (CHP) applications (particularly involving heat-activated cooling) in commercial buildings promises significant benefits but poses many technical and financial challenges, both in system choice and its operation; if successful, such systems may be precursors to widespread microgrid deployment. The presented optimization approach to choosing such systems and their operating schedules uses Berkeley Lab's Distributed Energy Resources Customer Adoption Model (DER-CAM), extended to incorporate electrical and thermal storage options. DER-CAM chooses annual energy bill minimizing systems in a fully technology-neutral manner. An illustrative example for a hypothetical San Francisco hotel is reported. The chosen system includes one large reciprocating engine and an absorption chiller providing an estimated 11% cost savings and 8% carbon emission reductions under idealized circumstances.
Towards Multi-Faceted Test Cases Optimization

The target of software engineering is to produce high quality software product at low cost. Software testing is labour-intensive, ambiguous and error prone activity of software development. How to provide cost-effective strategies for software test cases optimization problem such as classification, minimization, selection, and prioritization has been one of the research focuses in software testing for a long time. Many researchers and academicians have addressed the effectiveness/fitness and optimization of test cases, and obtained many interesting results. However, one issue of paramount importance in software testing i.e. the intrinsic imprecise and uncertainty of test cases fitness, fitness parameters, multi-objective optimization, is left unaddressed. Test cases fitness depends on several parameters. Vagueness of fitness of test cases and their fitness parameters have created the uncertainty in test cases optimization. Cost and adequacy values are incorporated into multi-faceted optimization of test cases. This paper argues test cases optimization requires multi-faceted optimization in order to adequately cater realistic software testing. In this paper, authors have identified several parameters for test cases fitness and multiple objectives for test cases optimization. In addition above, authors have formulated the test cases optimization problem in three different ways using multi-faceted concept. These formulations can be used in future by authors and researchers.
A Calibration Method for MEMS Inertial Sensors Based on Optical Tracking

A MAG-muIMU which is based on MEMS accelerometers, gyroscopes and magnetometers has been developed for real-time estimation of human hand motions. Appropriate filtering, transformation and sensor fusion techniques are combined in the ubiquitous digital writing instrument (UDWI) to record the handwriting on any surface. However, because of the sensors' intrinsic biases and random noise such as circuit thermal noise, a calibration system that provides good reference measurement parameters must be used to compare the output of the MAG-muIMU sensors. We propose here a novel idea to calibrate three-dimensional linear accelerations, angular velocities and space attitude through optical tracking techniques. The optical tracking system (OTS) developed by our group consists of two parts: 1) 2D trajectory calibration that is used to obtain linear accelerations of the UDWI in a particular frame defined by us; 2) multiple camera calibration that is used for attitude calibration of the UDWI. An essential relationship to transform reference frames and angular velocities can be guaranteed after real-time attitude calibration. Hence, the entire nine-dimensional output of the MAG-muIMU can be rectified according to these more accurate data obtained from optical tracking.
Compact linear lead/lag metamaterial phase shifters for broadband applications

A compact one-dimensional phase shifter is proposed using alternating sections of negative refractive index (NRI) metamaterials and printed transmission lines (TL). The NRI metamaterial sections consist of lumped element capacitors and inductors, arranged in a dual TL (high-pass) configuration. By adjusting the NRI-medium lumped element values, the phase shift can be tailored to a given specification. Periodic analysis is applied to the structure and design equations are presented for the determination of the lumped element parameters for any arbitrary phase shift. To validate the design, various phase shifters are simulated and tested in coplanar waveguide (CPW) technology. It is demonstrated that small variations in the NRI-medium lumped element values can produce positive, negative or 0/spl deg/ phase shifts while maintaining the same short overall length. Thus, the new phase shifter offers some significant advantages over conventional delay lines: it is more compact in size, it exhibits a linear phase response around the design frequency, it can incur a phase lead or lag which is independent of the length of the structure and it exhibits shorter group delays.
University ’ s repository of research publications and other research outputs Organizational learning and knowledge in public service organizations : a systematic review of the literature

Copyright and Moral Rights for the articles on this site are retained by the individual authors and/or other copyright owners. For more information on Open Research Online's data policy on reuse of materials please consult the policies page. This paper is a systematic review of the literature on organizational learning and knowledge with relevance to public service organizations. Organizational learning and knowledge are important to public sector organizations, which share complex external challenges with private organizations, but have different drivers and goals for knowledge. The evidence shows that the concepts of organizational learning and knowledge are under-researched in relation to the public sector and, importantly, this raises wider questions about the extent to which context is taken into consideration in terms of learning and knowledge more generally across all sectors. A dynamic model of organizational learning within and across organizational boundaries is developed that depends on four sets of factors: features of the source organization; features of the recipient organization; the characteristics of the relationship between organizations; and the environmental context. The review concludes, first, that defining 'organization' is an important element of understanding organizational learning and knowledge. Second, public organizations constitute an important, distinctive context for the study of organizational learning and knowledge. Third, there continues to be an over-reliance on the private sector as the principal source of theoretical understanding and empirical research and this is conceptually limiting for the understanding of organizational learning and knowledge. Fourth, differences as well as similarities between organizational sectors require conceptualization and research that acknowledge sector-specific aims, values and structures. Finally, it is concluded that frameworks for explaining processes of organizational learning at different levels need to be sufficiently dynamic and complex to accommodate public organizations.