Generalised median of a set of correspondences based on the hamming distance.

A correspondence is a set of mappings that establishes a relation between the elements of two data structures (i.e. sets of points, strings, trees or graphs). If we consider several correspondences between the same two structures, one option to define a representative of them is through the generalised median correspondence. In general, the computation of the generalised median is an NP-complete task. In this paper, we present two methods to calculate the generalised median correspondence of multiple correspondences. The first one obtains the optimal solution in cubic time, but it is restricted to the Hamming distance. The second one obtains a sub-optimal solution through an iterative approach, but does not have any restrictions with respect to the used distance. We compare both proposals in terms of the distance to the true generalised median and runtime

Modelling the generalised median correspondence through an edit distance.

On the one hand, classification applications modelled by structural pattern recognition, in which elements are represented as strings, trees or graphs, have been used for the last thirty years. In these models, structural distances are modelled as the correspondence (also called matching or labelling) between all the local elements (for instance nodes or edges) that generates the minimum sum of local distances. On the other hand, the generalised median is a well-known concept used to obtain a reliable prototype of data such as strings, graphs and data clusters. Recently, the structural distance and the generalised median has been put together to define a generalise median of matchings to solve some classification and learning applications. In this paper, we present an improvement in which the Correspondence edit distance is used instead of the classical Hamming distance. Experimental validation shows that the new approach obtains better results in reasonable runtime compared to other median calculation strategies

Heuristics-based detection to improve text/graphics segmentation in complex engineering drawings.

The demand for digitisation of complex engineering drawings becomes increasingly important for the industry given the pressure to improve the efficiency and time effectiveness of operational processes. There have been numerous attempts to solve this problem, either by proposing a general form of document interpretation or by establishing an application dependant framework. Moreover, text/graphics segmentation has been presented as a particular form of addressing document digitisation problem, with the main aim of splitting text and graphics into different layers. Given the challenging characteristics of complex engineering drawings, this paper presents a novel sequential heuristics-based methodology which is aimed at localising and detecting the most representative symbols of the drawing. This implementation enables the subsequent application of a text/graphics segmentation method in a more effective form. The experimental framework is composed of two parts: first we show the performance of the symbol detection system and then we present an evaluation of three different state of the art text/graphic segmentation techniques to find text on the remaining image

Symbols in engineering drawings (SiED): an imbalanced dataset benchmarked by convolutional neural networks.

Engineering drawings are common across different domains such as Oil & Gas, construction, mechanical and other domains. Automatic processing and analysis of these drawings is a challenging task. This is partly due to the complexity of these documents and also due to the lack of dataset availability in the public domain that can help push the research in this area. In this paper, we present a multiclass imbalanced dataset for the research community made of 2432 instances of engineering symbols. These symbols were extracted from a collection of complex engineering drawings known as Piping and Instrumentation Diagram (P&ID). By providing such dataset to the research community, we anticipate that this will help attract more attention to an important, yet overlooked industrial problem, and will also advance the research in such important and timely topics. We discuss the datasets characteristics in details, and we also show how Convolutional Neural Networks (CNNs) perform on such extremely imbalanced datasets. Finally, conclusions and future directions are discussed

Novel insights into host-fungal pathogen interactions derived from live-cell imaging

Acknowledgments The authors acknowledge funding from the Wellcome Trust (080088, 086827, 075470 and 099215) including a Wellcome Trust Strategic Award for Medical Mycology and Fungal Immunology 097377 and FP7-2007–2013 grant agreement HEALTH-F2-2010-260338–ALLFUN to NARG.Peer reviewedPublisher PD

Therapeutic Benefit of Radial Optic Neurotomy in a Rat Model of Glaucoma

Radial optic neurotomy (RON) has been proposed as a surgical treatment to alleviate the neurovascular compression and to improve the venous outflow in patients with central retinal vein occlusion. Glaucoma is characterized by specific visual field defects due to the loss of retinal ganglion cells and damage to the optic nerve head (ONH). One of the clinical hallmarks of glaucomatous neuropathy is the excavation of the ONH. The aim of this work was to analyze the effect of RON in an experimental model of glaucoma in rats induced by intracameral injections of chondroitin sulfate (CS). For this purpose, Wistar rats were bilaterally injected with vehicle or CS in the eye anterior chamber, once a week, for 10 weeks. At 3 or 6 weeks of a treatment with vehicle or CS, RON was performed by a single incision in the edge of the neuro-retinal ring at the nasal hemisphere of the optic disk in one eye, while the contralateral eye was submitted to a sham procedure. Electroretinograms (ERGs) were registered under scotopic conditions and visual evoked potentials (VEPs) were registered with skull-implanted electrodes. Retinal and optic nerve morphology was examined by optical microscopy. RON did not affect the ocular hypertension induced by CS. In eyes injected with CS, a significant decrease of retinal (ERG a- and b-wave amplitude) and visual pathway (VEP N2-P2 component amplitude) function was observed, whereas RON reduced these functional alterations in hypertensive eyes. Moreover, a significant loss of cells in the ganglion cell layer, and Thy-1-, NeuN- and Brn3a- positive cells was observed in eyes injected with CS, whereas RON significantly preserved these parameters. In addition, RON preserved the optic nerve structure in eyes with chronic ocular hypertension. These results indicate that RON reduces functional and histological alterations induced by experimental chronic ocular hypertension

The Role of the Proteinase Inhibitor Ovorubin in Apple Snail Eggs Resembles Plant Embryo Defense against Predation

BACKGROUND: Fieldwork has thoroughly established that most eggs are intensely predated. Among the few exceptions are the aerial egg clutches from the aquatic snail Pomacea canaliculata which have virtually no predators. Its defenses are advertised by the pigmented ovorubin perivitellin providing a conspicuous reddish coloration. The nature of the defense however, was not clear, except for a screening for defenses that identified a neurotoxic perivitellin with lethal effect on rodents. Ovorubin is a proteinase inhibitor (PI) whose role to protect against pathogens was taken for granted, according to the prevailing assumption. Through biochemical, biophysical and feeding experiments we studied the proteinase inhibitor function of ovorubin in egg defenses. METHODOLOGY/PRINCIPAL FINDINGS: Mass spectrometry sequencing indicated ovorubin belongs to the Kunitz-type serine proteinase inhibitor family. It specifically binds trypsin as determined by small angle X-ray scattering (SAXS) and cross-linking studies but, in contrast to the classical assumption, it does not prevent bacterial growth. Ovorubin was found extremely resistant to in vitro gastrointestinal proteolysis. Moreover feeding studies showed that ovorubin ingestion diminishes growth rate in rats indicating that this highly stable PI is capable of surviving passage through the gastrointestinal tract in a biologically active form. CONCLUSIONS: To our knowledge, this is the first direct evidence of the interaction of an egg PI with a digestive protease of potential predators, limiting predator's ability to digest egg nutrients. This role has not been reported in the animal kingdom but it is similar to plant defenses against herbivory. Further, this would be the only defense model with no trade-offs between conspicuousness and noxiousness by encoding into the same molecule both the aposematic warning signal and an antinutritive/antidigestive defense. These defenses, combined with a neurotoxin and probably unpalatable factors would explain the near absence of predators, opening new perspectives in the study of the evolution and ecology of egg defensive strategies

Observation of associated near-side and away-side long-range correlations in √sNN=5.02 TeV proton-lead collisions with the ATLAS detector

Two-particle correlations in relative azimuthal angle (Δϕ) and pseudorapidity (Δη) are measured in √sNN=5.02  TeV p+Pb collisions using the ATLAS detector at the LHC. The measurements are performed using approximately 1  μb-1 of data as a function of transverse momentum (pT) and the transverse energy (ΣETPb) summed over 3.1<η<4.9 in the direction of the Pb beam. The correlation function, constructed from charged particles, exhibits a long-range (2<|Δη|<5) “near-side” (Δϕ∼0) correlation that grows rapidly with increasing ΣETPb. A long-range “away-side” (Δϕ∼π) correlation, obtained by subtracting the expected contributions from recoiling dijets and other sources estimated using events with small ΣETPb, is found to match the near-side correlation in magnitude, shape (in Δη and Δϕ) and ΣETPb dependence. The resultant Δϕ correlation is approximately symmetric about π/2, and is consistent with a dominant cos⁡2Δϕ modulation for all ΣETPb ranges and particle pT

Efficacy of a brief multifactorial adherence-based intervention on reducing the blood pressure of patients with poor adherence: protocol for a randomized clinical trial

<p>Abstract</p> <p>Background</p> <p>Lowering of blood pressure by antihypertensive drugs reduces the risks of cardiovascular events, stroke, and total mortality. However, poor adherence to antihypertensive medications reduces their effectiveness and increases the risk of adverse events. In terms of relative risk reduction, an improvement in medication adherence could be as effective as the development of a new drug.</p> <p>Methods/Design</p> <p>The proposed randomized controlled trial will include patients with a low adherence to medication and uncontrolled blood pressure. The intervention group will receive a multifactorial intervention during the first, third, and ninth months, to improve adherence. This intervention will include motivational interviews, pill reminders, family support, blood pressure self-recording, and simplification of the dosing regimen.</p> <p>Measurement</p> <p>The primary outcome is systolic blood pressure. The secondary outcomes are diastolic blood pressure, proportion of patients with adequately controlled blood pressure, and total cost.</p> <p>Discussion</p> <p>The trial will evaluate the impact of a multifactorial adherence intervention in routine clinical practice. Ethical approval was given by the Ethical Committee on Human Research of Balearic islands, Spain (approval number IB 969/08 PI).</p> <p>Trial registration</p> <p>Current controlled trials ISRCTN21229328</p

Predicting the onset and persistence of episodes of depression in primary health care. The predictD-Spain study: Methodology

Background: The effects of putative risk factors on the onset and/or persistence of depression remain unclear. We aim to develop comprehensive models to predict the onset and persistence of episodes of depression in primary care. Here we explain the general methodology of the predictD-Spain study and evaluate the reliability of the questionnaires used. Methods: This is a prospective cohort study. A systematic random sample of general practice attendees aged 18 to 75 has been recruited in seven Spanish provinces. Depression is being measured with the CIDI at baseline, and at 6, 12, 24 and 36 months. A set of individual, environmental, genetic, professional and organizational risk factors are to be assessed at each follow-up point. In a separate reliability study, a proportional random sample of 401 participants completed the test-retest (251 researcher-administered and 150 self-administered) between October 2005 and February 2006. We have also checked 118,398 items for data entry from a random sample of 480 patients stratified by province. Results: All items and questionnaires had good test-retest reliability for both methods of administration, except for the use of recreational drugs over the previous six months. Cronbach's alphas were good and their factorial analyses coherent for the three scales evaluated (social support from family and friends, dissatisfaction with paid work, and dissatisfaction with unpaid work). There were 191 (0.16%) data entry errors. Conclusion: The items and questionnaires were reliable and data quality control was excellent. When we eventually obtain our risk index for the onset and persistence of depression, we will be able to determine the individual risk of each patient evaluated in primary health care.The research in Spain was funded by grants from the Spanish Ministry of Health (grant FIS references: PI04/1980, PI0/41771, PI04/2450, and PI06/1442), Andalusian Council of Health (grant references: 05/403, 06/278 and 08/0194), and the Spanish Ministry of Education and Science (grant reference SAF 2006/07192). The Malaga sample, as part of the predictD-International study, was also funded by a grant from The European Commission (reference QL4-CT2002-00683)