bluuebunny/crossref_metadata_2025_split huggingface dataset:
Compliance with a time-out procedure intended to prevent wrong surgery in hospitals: results of a national patient safety programme in the Netherlands
Authors: van Schoten Steffie M , Kop Veerle , de Blok Carolien , Spreeuwenberg Peter , Groenewegen Peter P , Wagner Cordula 
Published: July 2014

ObjectiveTo prevent wrong surgery, the WHO ‘Safe Surgery Checklist’ was introduced in 2008. The checklist comprises a time-out procedure (TOP): the final step before the start of the surgical procedure where the patient, surgical procedure and side/site are reviewed by the surgical team. The aim of this study is to evaluate the extent to which hospitals carry out the TOP before anaesthesia in the operating room, whether compliance has changed over time, and to determine factors that are associated with compliance.DesignEvaluation study involving observations.SettingOperating rooms of 2 academic, 4 teaching and 12 general Dutch hospitals.ParticipantsA random selection was made from all adult patients scheduled for elective surgery on the day of the observation, preferably involving different surgeons and different procedures.ResultsMean compliance with the TOP was 71.3%. Large differences between hospitals were observed. No linear trend was found in compliance during the study period. Compliance at general and teaching hospitals was higher than at academic hospitals. Compliance decreased with the age of the patient, general surgery showed lower compliance in comparison with other specialties and compliance was higher when the team was focused on the TOP.ConclusionsLarge differences in compliance with the TOP were observed between participating hospitals which can be attributed at least in part to the type of hospital, surgical specialty and patient characteristics. Hospitals do not comply consistently with national guidelines to prevent wrong surgery and further implementation as well as further research into non-compliance is needed.
Similarity indices and the Miyazawa polynomials of virtual links
Authors: Jeong Myeong-Ju , Park Chan-Young 
Published: July 2014

Y. Miyazawa introduced a two-variable polynomial invariant of virtual knots in 2006 [Magnetic graphs and an invariant for virtual links, J. Knot Theory Ramifications 15 (2006) 1319–1334] and then generalized it to give a multi-variable one via decorated virtual magnetic graph diagrams in 2008. A. Ishii gave a simple state model for the two-variable Miyazawa polynomial by using pole diagrams in 2008 [A multi-variable polynomial invariant for virtual knots and links, J. Knot Theory Ramifications 17 (2008) 1311–1326]. H. A. Dye and L. H. Kauffman constructed an arrow polynomial of a virtual link in 2009 which is equivalent to the multi-variable Miyazawa polynomial [Virtual crossing number and the arrow polynomial, preprint (2008), arXiv:0810.3858v3, http://front.math.ucdavis.edu .]. We give a bracket model for the multi-variable Miyazawa polynomial via pole diagrams and polar tangles similarly to the Ishii's state model for the two-variable polynomial. By normalizing the bracket polynomial we get the multi-variable Miyazawa polynomial fK ∈ ℤ[A, A-1, K1, K2, …] of a virtual link K. n-similar knots take the same value for any Vassiliev invariant of degree < n. We show that fK1 ≡ fK2 mod (A4 - 1)n if two virtual links K1 and K2 are n-similar. Also we give a necessary condition for a virtual link to be periodic by using n-similarity of virtual tangles and the Miyazawa polynomial.
Predicting and Identifying Missing Node Information in Social Networks
Authors: Eyal Ron , Rosenfeld Avi , Sina Sigal , Kraus Sarit 
Published: July 2014

In recent years, social networks have surged in popularity. One key aspect of social network research is identifying important missing information that is not explicitly represented in the network, or is not visible to all. To date, this line of research typically focused on finding the connections that are missing between nodes, a challenge typically termed as the
link prediction problem
.

This article introduces the missing node identification problem, where missing members in the social network structure must be identified. In this problem, indications of missing nodes are assumed to exist. Given these indications and a partial network, we must assess which indications originate from the same missing node and determine the full network structure.
Toward solving this problem, we present the missing node identification by spectral clustering algorithm (MISC), an approach based on a spectral clustering algorithm, combined with nodes’ pairwise affinity measures that were adopted from link prediction research. We evaluate the performance of our approach in different problem settings and scenarios, using real-life data from Facebook. The results show that our approach has beneficial results and can be effective in solving the missing node identification problem. In addition, this article also presents R-MISC, which uses a sparse matrix representation, efficient algorithms for calculating the nodes’ pairwise affinity, and a proprietary dimension reduction technique to enable scaling the MISC algorithm to large networks of more than 100,000 nodes. Last, we consider problem settings where some of the indications are unknown. Two algorithms are suggested for this problem: speculative MISC, based on MISC, and missing link completion, based on classical link prediction literature. We show that speculative MISC outperforms missing link completion.
Ten Years of Rich Internet Applications
Authors: Casteleyn Sven , Garrig'os Irene , Maz'on Jose-Norberto 
Published: July 2014

BACKGROUND. The term Rich Internet Applications (RIAs) is generally associated with Web applications that provide the features and functionality of traditional desktop applications. Ten years after the introduction of the term, an ample amount of research has been carried out to study various aspects of RIAs. It has thus become essential to summarize this research and provide an adequate overview.
OBJECTIVE. The objective of our study is to assemble, classify, and analyze all RIA research performed in the scientific community, thus providing a consolidated overview thereof, and to identify well-established topics, trends, and open research issues. Additionally, we provide a qualitative discussion of the most interesting findings. This work therefore serves as a reference work for beginning and established RIA researchers alike, as well as for industrial actors that need an introduction in the field, or seek pointers to (a specific subset of) the state-of-the-art.
METHOD. A systematic mapping study is performed in order to identify all RIA-related publications, define a classification scheme, and categorize, analyze, and discuss the identified research according to it.
RESULTS. Our source identification phase resulted in 133 relevant, peer-reviewed publications, published between 2002 and 2011 in a wide variety of venues. They were subsequently classified according to four facets: development activity, research topic, contribution type, and research type. Pie, stacked bar, and bubble charts were used to depict and analyze the results. A deeper analysis is provided for the most interesting and/or remarkable results.
CONCLUSION. Analysis of the results shows that, although the RIA term was coined in 2002, the first RIA-related research appeared in 2004. From 2007 there was a significant increase in research activity, peaking in 2009 and decreasing to pre-2009 levels afterwards. All development phases are covered in the identified research, with emphasis on “design” (33%) and “implementation” (29%). The majority of research proposes a “method” (44%), followed by “model” (22%), “methodology” (18%), and “tools” (16%); no publications in the category “metrics” were found. The preponderant research topic is “models, methods and methodologies” (23%) and, to a lesser extent, “usability and accessibility” and “user interface” (11% each). On the other hand, the topic “localization, internationalization and multilinguality” received no attention at all, and topics such as “deep Web” (under 1%), “business processing”, “usage analysis”, “data management”, “quality and metrics” (all under 2%), “semantics”, and “performance” (slightly above 2%) received very little attention. Finally, there is a large majority of “solution proposals” (66%), few “evaluation research” (14%), and even fewer “validation” (6%), although the latter have been increasing in recent years.
Blueshell
Authors: Plumbridge Gary , Whitham Jack , Audsley Neil 
Published: July 2014

The rapid increase in FPGA logic capacity has enabled the prototyping of multiprocessor Network-on-Chip (NoC) architectures. However, the design space exploration of these complex architectures is highly time consuming with traditional methodologies for FPGA design.
Our paper addresses the challenges of multiprocessor network design with the Blueshell framework for generating multiprocessor networks on chip (NoC) and a coupled Java software stack, Network-Chi. With Blueshell hardware is mconstructed from high-level components including processors and routers using concise Bluespec System Verilog. The Network-Chi software framework is also presented to enable programming the on-chip processors in a familiar Java style and without exposing the low-level systems programming to the application designer.
We demonstrate that Blueshell systems with as many as 20 processors can be implemented on a modestly sized FPGA. Performance figures for a selection of distributed applications are also provided.
Beyond linear chain
Authors: Marcheggiani Diego 
Published: July 2014

Information Extraction (IE) is a field at the crossroads of IR and NLP that studies methods for extracting information from text in such a way that this information can be used to populate a structured information repository. The main methods by means of which IE has been tackled rely on supervised learning;the best-performing such methods belong to the class of probabilistic graphical models, and, in particular, to the class of Conditional Random Fields (CRFs). In this thesis we investigate two major aspects related to textual IE via CRFs: (a) the creation of CRFs models that can outperform the commonly adopted linear- chain CRFs, and the creation of methods for ensuring the quality of training data and for assessing the impact of training data quality on the accuracy of CRFs systems for IE.
We start by facing the task of IE from medical documents written in the Italian language. We propose two novel approaches: (i) a cascaded, two-stage method composed by two layers of CRFs, and (ii) a confidence-weighted ensemble method that combines standard linear-chain CRFs and the proposed two-stage method. Both the proposed models are shown to outperform a standard linear-chain CRFs system.
We then investigate aspect-oriented sentence-level opinion mining from product reviews, that consists in predicting, for all sentences in the review, whether the sentence expresses a positive, neutral, or negative opinion (or no opinion at all) about a specific aspect of the product. We propose a set of increasingly powerful models based on CRFs, including a hierarchical multi-label CRFs scheme that jointly models the overall opinion expressed in a product review and the set of aspect-specific opinions expressed in each of its sentences. The proposed CRFs models are shown to obtain better results than linear-chain CRFs.
We then study the impact that the quality of training data has on the accuracy of an IE system via experiments performed on a dataset in which inter-coder agreement data are available. Finally, we investigate active learning techniques for a type of semi-supervised CRFs specifically devised for partially labeled sequences. We show that margin-based strategies always obtain the best results on the four tasks we have tested them on.
AMPK Reverses the Mesenchymal Phenotype of Cancer Cells by Targeting the Akt–MDM2–Foxo3a Signaling Axis
Authors: Chou Chih-Chien , Lee Kuen-Haur , Lai I-Lu , Wang Dasheng , Mo Xiaokui , Kulp Samuel K. , Shapiro Charles L. , Chen Ching-Shih 
Published: July 2014

Abstract
In cancer cells, the epithelial–mesenchymal transition (EMT) confers the ability to invade basement membranes and metastasize to distant sites, establishing it as an appealing target for therapeutic intervention. Here, we report a novel function of the master metabolic kinase AMPK in suppressing EMT by modulating the Akt–MDM2–Foxo3 signaling axis. This mechanistic link was supported by the effects of siRNA-mediated knockdown and pharmacologic activation of AMPK on epithelial and mesenchymal markers in established breast and prostate cancer cells. Exposure of cells to OSU-53, a novel allosteric AMPK activator, as well as metformin and AICAR, was sufficient to reverse their mesenchymal phenotype. These effects were abrogated by AMPK silencing. Phenotypic changes were mediated by Foxo3a activation, insofar as silencing or overexpressing Foxo3a mimicked the effects of AMPK silencing or OSU-53 treatment on EMT, respectively. Mechanistically, Foxo3a activation led to the transactivation of the E-cadherin gene and repression of genes encoding EMT-inducing transcription factors. OSU-53 activated Foxo3a through two Akt-dependent pathways, one at the level of nuclear localization by blocking Akt- and IKKβ-mediated phosphorylation, and a second at the level of protein stabilization via cytoplasmic sequestration of MDM2, an E3 ligase responsible for Foxo3a degradation. The suppressive effects of OSU-53 on EMT had therapeutic implications illustrated by its ability to block invasive phenotypes in vitro and metastatic properties in vivo. Overall, our work illuminates a mechanism of EMT regulation in cancer cells mediated by AMPK, along with preclinical evidence supporting a tractable therapeutic strategy to reverse mesenchymal phenotypes associated with invasion and metastasis. Cancer Res; 74(17); 4783–95. ©2014 AACR.
BluepRINT for Moderate-to-Low Penetrance Cancer Susceptibility Genes Needed: Breast Cancer and Beyond
Authors: Ngeow Joanne , Eng Charis 
Published: July 2014

Abstract
Summary:RINT1 is a novel moderately penetrant cancer susceptibility gene seen in breast cancer as well as possibly in Lynch syndrome–related cancers. Cancer Discov; 4(7); 762–3. ©2014 AACR.
See related article by Park et al., p. 804
CCR5 as a Treatment Target in Pulmonary Arterial Hypertension
Authors: Amsellem Valérie , Lipskaia Larissa , Abid Shariq , Poupel Lucie , Houssaini Amal , Quarck Rozenn , Marcos Elisabeth , Mouraret Nathalie , Parpaleix Aurélien , Bobe Régis , Gary-Bobo Guillaume , Saker Mirna , Dubois-Randé Jean-Luc , Gladwin Mark T. , Norris Karen A. , Delcroix Marion , Combadière Christophe , Adnot Serge 
Published: July 2014

Background—
Pulmonary arterial hypertension (PH), whether idiopathic or related to underlying diseases such as HIV infection, results from complex vessel remodeling involving both pulmonary artery smooth muscle cell (PA-SMC) proliferation and inflammation. CCR5, a coreceptor for cellular HIV-1 entry expressed on macrophages and vascular cells, may be involved in the pathogenesis of PH. Maraviroc is a new CCR5 antagonist designed to block HIV entry.

Methods and Results—

Marked CCR5 expression was found in lungs from patients with idiopathic PH, in mice with hypoxia-induced PH, and in Simian immunodeficiency virus–infected macaques, in which it was localized chiefly in the PA-SMCs. To assess the role for CCR5 in experimental PH, we used both gene disruption and pharmacological CCR5 inactivation in mice. Because maraviroc does not bind to murine CCR5, we used human-CCR5ki mice for pharmacological and immunohistochemical studies. Compared with wild-type mice, CCR5
−/−
mice or human-CCR5ki mice treated with maraviroc exhibited decreased PA-SMC proliferation and recruitment of perivascular and alveolar macrophages during hypoxia exposure. CCR5
−/−
mice reconstituted with wild-type bone marrow cells and wild-type mice reconstituted with CCR5
−/−
bone marrow cells were protected against PH, suggesting CCR5-mediated effects on PA-SMCs and macrophage involvement. The CCR5 ligands CCL5 and the HIV-1 gp120 protein increased intracellular calcium and induced growth of human and human-CCR5ki mouse PA-SMCs; maraviroc inhibited both effects. Maraviroc also reduced the growth-promoting effects of conditioned media from CCL5-activated macrophages derived from human-CCR5ki mice on PA-SMCs from wild-type mice.

Conclusion—
The CCL5-CCR5 pathway represents a new therapeutic target in PH associated with HIV or with other conditions.
Stochastic Model Output Statistics for Bias Correcting and Downscaling Precipitation Including Extremes
Authors: Wong Geraldine , Maraun Douglas , Vrac Mathieu , Widmann Martin , Eden Jonathan M. , Kent Thomas 
Published: July 2014

AbstractPrecipitation is highly variable in space and time; hence, rain gauge time series generally exhibit additional random small-scale variability compared to area averages. Therefore, differences between daily precipitation statistics simulated by climate models and gauge observations are generally not only caused by model biases, but also by the corresponding scale gap. Classical bias correction methods, in general, cannot bridge this gap; they do not account for small-scale random variability and may produce artifacts. Here, stochastic model output statistics is proposed as a bias correction framework to explicitly account for random small-scale variability. Daily precipitation simulated by a regional climate model (RCM) is employed to predict the probability distribution of local precipitation. The pairwise correspondence between predictor and predictand required for calibration is ensured by driving the RCM with perfect boundary conditions. Wet day probabilities are described by a logistic regression, and precipitation intensities are described by a mixture model consisting of a gamma distribution for moderate precipitation and a generalized Pareto distribution for extremes. The dependence of the model parameters on simulated precipitation is modeled by a vector generalized linear model. The proposed model effectively corrects systematic biases and correctly represents local-scale random variability for most gauges. Additionally, a simplified model is considered that disregards the separate tail model. This computationally efficient model proves to be a feasible alternative for precipitation up to moderately extreme intensities. The approach sets a new framework for bias correction that combines the advantages of weather generators and RCMs.
Assessment of Bias Assumptions for Climate Models
Authors: Kerkhoff Christian , Künsch Hans R. , Schär Christoph 
Published: July 2014

Abstract
Climate scenarios make implicit or explicit assumptions about the extrapolation of climate model biases from current to future time periods. Such assumptions are inevitable because of the lack of future observations. This manuscript reviews different bias assumptions found in the literature and provides measures to assess their validity. The authors explicitly separate climate change from multidecadal variability to systematically analyze climate model biases in seasonal and regional surface temperature averages, using global and regional climate models (GCMs and RCMs) from the Ensemble-Based Predictions of Climate Changes and Their Impacts (ENSEMBLES) project over Europe. For centennial time scales, it is found that a linear bias extrapolation for GCMs is best supported by the analysis: that is, it is generally not correct to assume that model biases are independent of the climate state. Results also show that RCMs behave markedly differently when forced with different drivers. RCM and GCM biases are not additive, and there is a significant interaction component in the bias of the RCM–GCM model chain that depends on both the RCM and GCM considered. This result questions previous studies that deduce biases (and ultimately projections) in RCM–GCM combinations from reanalysis-driven simulations. The authors suggest that the aforementioned interaction component derives from the refined RCM representation of dynamical and physical processes in the lower troposphere, which may nonlinearly depend upon the larger-scale circulation stemming from the driving GCM. The authors’ analyses also show that RCMs provide added value and that the combined RCM–GCM approach yields, in general, smaller biases in seasonal surface temperature and interannual variability, particularly in summer and even for spatial scales that are, in principle, well resolved by the GCMs.
Projections of the Tropical Atlantic Vertical Wind Shear and Its Relationship with ENSO in SP-CCSM4
Authors: Zhu Xiaojie , Xu Li , Stan Cristiana 
Published: July 2014

Abstract
The vertical wind shear over the tropical Atlantic Ocean and its relationship with ENSO are analyzed in the superparameterized Community Climate System Model, version 4 (SP-CCSM4) and in the conventional CCSM4. The climatology of vertical wind shear over the tropical Atlantic and the ENSO–shear relationship are well simulated in the control runs of SP-CCSM4 and CCSM4. However, because of different representations of cloud processes, in a warmer climate such as the representative concentration pathway 8.5 (RCP8.5) scenario, SP-CCSM4 projects increased mean westerlies at 200 hPa during July through October (JASO), whereas CCSM4 projects decreased mean westerlies at 200 hPa over the equatorial Atlantic. The different changes in the upper-level wind further contribute to different projection of JASO mean vertical wind shear over the equatorial Atlantic. In the RCP8.5 scenario, when excluding the linear trend, projection of the ENSO–shear relationships by SP-CCSM4 retains similar features as in the observed current climate, whereas the ENSO–shear relationship projected by CCSM4 indicates an increase in the vertical wind shear dominating the tropical Atlantic during El Niño events. The difference in projection of ENSO–shear relationship is, to a certain extent, related to the different response of the tropical Atlantic SST to ENSO. Analysis of the climate change projection of Walker circulation, cloud cover, and convective activity illustrates that superparameterization simulates a stronger suppression of African convection than the conventional parameterization of moist processes. The weak convective activity diminishes the divergent wind associated with the vertical motion, which contributes to increased westerlies projected in SP-CCSM4.