2,571 research outputs found
Electron Dynamics in the Diffusion Region of an Asymmetric Magnetic Reconnection
During a magnetopause crossing near the subsolar point Cluster observes the ion diffusion region of antiparallel magnetic reconnection. The reconnecting plasmas are asymmetric, differing in magnetic field strength, density, and temperature. Spatial changes in the electron distributions in the diffusion region are resolved and investigated in detail. Heating of magnetosheath electrons parallel to the magnetic field is observed. This heating is shown to be consistent with trapping of magnetosheath electrons by parallel electric fields
Scheduling MapReduce Jobs under Multi-Round Precedences
We consider non-preemptive scheduling of MapReduce jobs with multiple tasks
in the practical scenario where each job requires several map-reduce rounds. We
seek to minimize the average weighted completion time and consider scheduling
on identical and unrelated parallel processors. For identical processors, we
present LP-based O(1)-approximation algorithms. For unrelated processors, the
approximation ratio naturally depends on the maximum number of rounds of any
job. Since the number of rounds per job in typical MapReduce algorithms is a
small constant, our scheduling algorithms achieve a small approximation ratio
in practice. For the single-round case, we substantially improve on previously
best known approximation guarantees for both identical and unrelated
processors. Moreover, we conduct an experimental analysis and compare the
performance of our algorithms against a fast heuristic and a lower bound on the
optimal solution, thus demonstrating their promising practical performance
Agility in humanitarian supply chain: an organizational information processing perspective and relational view
Humanitarian organizations are increasingly facing challenges in terms of improving the efficiency and the effectiveness of their disaster relief efforts. These challenges often arise due to a lack of trust, poor collaboration and an inability to respond to disaster affected areas in a timely manner. Our study attempts to understand how these challenges are overcome by seeking answers to questions related to the topics of swift-trust, collaboration and agility in humanitarian supply chains. For instance, in our study we have attempted to examine how information sharing and supply chain visibility in humanitarian supply chains improve the swift-trust among the humanitarian actors engaged in disaster relief operations. Further, we attempt to understand how-swift trust, commitment and collaboration among the humanitarian actors improve the agility in humanitarian supply chains. In our study we provide both theoretical and data-driven answers to our stated research gaps. Our theoretical model is firmly grounded in organizational information process theory and relational view. We tested our research hypotheses using variance based structural equation modelling with survey data collected using a web based pre-tested instrument from 147 NGOs respondents drawn from the National Disaster Management Authority database. Our results help to advance the theoretical debates surrounding “swift-trust”, “collaboration” and “agility” in humanitarian settings. We further provide direction to managers engaged in disaster relief operations. The humanitarian actors engaged in disaster relief often fail to understand how to build swift-trust. Moreover, how swift-trust further affects commitment and collaboration which in turn further affect agility in humanitarian supply chains. Thus humanitarian organizations must understand how information sharing and supply chain visibility is key to swift-trust among humanitarian actors and agility in humanitarian supply chains. Finally, we outline the limitations of our study and offer some future research directions for investigation
Combining estimates of interest in prognostic modelling studies after multiple imputation: current practice and guidelines
Background: Multiple imputation (MI) provides an effective approach to handle missing covariate
data within prognostic modelling studies, as it can properly account for the missing data
uncertainty. The multiply imputed datasets are each analysed using standard prognostic modelling
techniques to obtain the estimates of interest. The estimates from each imputed dataset are then
combined into one overall estimate and variance, incorporating both the within and between
imputation variability. Rubin's rules for combining these multiply imputed estimates are based on
asymptotic theory. The resulting combined estimates may be more accurate if the posterior
distribution of the population parameter of interest is better approximated by the normal
distribution. However, the normality assumption may not be appropriate for all the parameters of
interest when analysing prognostic modelling studies, such as predicted survival probabilities and
model performance measures.
Methods: Guidelines for combining the estimates of interest when analysing prognostic modelling
studies are provided. A literature review is performed to identify current practice for combining
such estimates in prognostic modelling studies.
Results: Methods for combining all reported estimates after MI were not well reported in the
current literature. Rubin's rules without applying any transformations were the standard approach
used, when any method was stated.
Conclusion: The proposed simple guidelines for combining estimates after MI may lead to a wider
and more appropriate use of MI in future prognostic modelling studies
Supervision and feedback for junior medical staff in Australian emergency departments: findings from the emergency medicine capacity assessment study
<p>Abstract</p> <p>Background</p> <p>Clinical supervision and feedback are important for the development of competency in junior doctors. This study aimed to determine the adequacy of supervision of junior medical staff in Australian emergency departments (EDs) and perceived feedback provided.</p> <p>Methods</p> <p>Semi-structured telephone surveys sought quantitative and qualitative data from ED Directors, Directors of Emergency Medicine Training, registrars and interns in 37 representative Australian hospitals; quantitative data were analysed with SPSS 15.0 and qualitative data subjected to content analysis identifying themes.</p> <p>Results</p> <p>Thirty six of 37 hospitals took part. Of 233 potential interviewees, 95 (40.1%) granted interviews including 100% (36/36) of ED Directors, and 96.2% (25/26) of eligible DEMTs, 24% (19/81) of advanced trainee/registrars, and 17% (15/90) of interns. Most participants (61%) felt the ED was adequately supervised in general and (64.2%) that medical staff were adequately supervised. Consultants and registrars were felt to provide most intern supervision, but this varied depending on shift times, with registrars more likely to provide supervision on night shift and at weekends. Senior ED medical staff (64%) and junior staff (79%) agreed that interns received adequate clinical supervision. Qualitative analysis revealed that good processes were in place to ensure adequate supervision, but that service demands, particularly related to access block and overcrowding, had detrimental effects on both supervision and feedback.</p> <p>Conclusions</p> <p>Consultants appear to provide the majority of supervision of junior medical staff in Australian EDs. Supervision and feedback are generally felt to be adequate, but are threatened by service demands, particularly related to access block and ED overcrowding.</p
Bio-psychosocial determinants of cardiovascular disease in a rural population on Crete, Greece: formulating a hypothesis and designing the SPILI-III study
Background: In 1988, the SPILI project was established in order to evaluate the cardiovascular disease (CVD) risk
profile of the inhabitants of Spili, in rural Crete, Greece. The first reports from this project revealed that against the unfavourable risk factors’ profile observed, only a few men with a previous myocardial infarction were encountered. A follow-up study (SPILI II) was performed twelve years after the initial examination, and the unfavourable cardiovascular risk profile was re-confirmed.
Presentation of the Hypothesis: This paper presents a hypothesis formulated on the basis of previous research to
investigate if dynamic psycho-social determinants, including social coherence of the local community, religiosity and spirituality, are protective against the development of coronary heart disease in a well-defined population. Testing the Hypothesis: A follow-up examination of this Cretan cohort is currently being performed to assess the link between psychosocial factors and CVD. Psychosocial factors including sense of control, religiosity and spirituality are assessed in together with conventional CVD risk factors. Smoking and alcohol consumption, as well as dietary habits and activity levels are recorded. Oxidative stress and inflammatory markers, as well as ultrasound measurement of carotid intima media thickness, a preclinical marker of atherosclerosis, will also be measured. Implications of the hypothesis tested: The issue of the cardio-protective effect of psycho-social factors would be revisited based on the results of this Cretan cohort; nevertheless, further research is needed across different subpopulations in order to establish a definite relationship. A comprehensive approach based on the aspects of biosocial life may result in more accurate CVD risk management
Vigorous star formation hidden by dust in a galaxy at
Near-infrared surveys have revealed a substantial population of enigmatic
faint galaxies with extremely red optical-to-near-infrared colours and with a
sky surface density comparable to that of faint quasars. There are two
scenarios for these extreme colours: (i) these distant galaxies have formed
virtually all their stars at very high redshifts and, due to the absence of
recently formed stars, the colours are extremely red and (ii) these distant
galaxies contain large amounts of dust, severely reddening the rest-frame
UV--optical spectrum. HR10 () is considered the archetype of the
extremely red galaxies. Here we report the detection of the continuum emission
from HR10 at 850m and at 1250m, demonstrating that HR10 is a very
dusty galaxy undergoing a major episode of star formation. Our result provides
a clear example of a high-redshift galaxy where the star formation rate
inferred from the ultraviolet luminosity would be underestimated by a factor up
to 1000, and shows that great caution should be used to infer the global star
formation history of the Universe from optical observations only.Comment: 12 pages, 1 figure, Nature, in press (30 April 1998
The Galaxy Structure-Redshift Relationship
There exists a gradual, but persistent, evolutionary effect in the galaxy
population such that galaxy structure and morphology change with redshift. This
galaxy structure-redshift relationship is such that an increasingly large
fraction of all bright and massive galaxies at redshifts 2 < z < 3 are
morphologically peculiar at wavelengths from rest-frame ultraviolet to
rest-frame optical. There are however examples of morphologically selected
spirals and ellipticals at all redshifts up to z ~ 3. At lower redshift, the
bright galaxy population smoothly transforms into normal ellipticals and
spirals. The rate of this transformation strongly depends on redshift, with the
swiftest evolution occurring between 1 < z < 2. This review characterizes the
galaxy structure-redshift relationship, discusses its various physical causes,
and how these are revealing the mechanisms responsible for galaxy formation.Comment: 20 pages, 8 figures. Invited Review to appear in "Penetrating Bars
Through Masks of Cosmic Dust: The Hubble Tuning Fork Strikes A New Note", ed.
D. Block et a
Manifold Elastic Net: A Unified Framework for Sparse Dimension Reduction
It is difficult to find the optimal sparse solution of a manifold learning
based dimensionality reduction algorithm. The lasso or the elastic net
penalized manifold learning based dimensionality reduction is not directly a
lasso penalized least square problem and thus the least angle regression (LARS)
(Efron et al. \cite{LARS}), one of the most popular algorithms in sparse
learning, cannot be applied. Therefore, most current approaches take indirect
ways or have strict settings, which can be inconvenient for applications. In
this paper, we proposed the manifold elastic net or MEN for short. MEN
incorporates the merits of both the manifold learning based dimensionality
reduction and the sparse learning based dimensionality reduction. By using a
series of equivalent transformations, we show MEN is equivalent to the lasso
penalized least square problem and thus LARS is adopted to obtain the optimal
sparse solution of MEN. In particular, MEN has the following advantages for
subsequent classification: 1) the local geometry of samples is well preserved
for low dimensional data representation, 2) both the margin maximization and
the classification error minimization are considered for sparse projection
calculation, 3) the projection matrix of MEN improves the parsimony in
computation, 4) the elastic net penalty reduces the over-fitting problem, and
5) the projection matrix of MEN can be interpreted psychologically and
physiologically. Experimental evidence on face recognition over various popular
datasets suggests that MEN is superior to top level dimensionality reduction
algorithms.Comment: 33 pages, 12 figure
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