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https://www.readbyqxmd.com/read/27922128/space-geodetic-monitoring-of-engineered-structures-the-ongoing-destabilization-of-the-mosul-dam-iraq
#1
Pietro Milillo, Roland Bürgmann, Paul Lundgren, Jacqueline Salzer, Daniele Perissin, Eric Fielding, Filippo Biondi, Giovanni Milillo
We present a detailed survey of the ongoing destabilization process of the Mosul dam. The dam is located on the Tigris river and is the biggest hydraulic structure in Iraq. From a geological point of view the dam foundation is poor due to a site geology formed by alternating strata of highly soluble materials including gypsum, anhydrite, marl and limestone. Here we present the first multi-sensor cumulative deformation map for the dam generated from space-based interferometric synthetic aperture radar measurements from the Italian constellation COSMO-SkyMed and the European sensor Sentinel-1a over the period 2014-2016 that we compare to an older dataset spanning 2004-2010 acquired with the European Envisat satellite...
December 6, 2016: Scientific Reports
https://www.readbyqxmd.com/read/27922118/mining-visualizing-and-comparing-multidimensional-biomolecular-data-using-the-genomics-data-miner-gmine-web-server
#2
Carla Proietti, Martha Zakrzewski, Thomas S Watkins, Bernard Berger, Shihab Hasan, Champa N Ratnatunga, Marie-Jo Brion, Peter D Crompton, John J Miles, Denise L Doolan, Lutz Krause
Genomics Data Miner (GMine) is a user-friendly online software that allows non-experts to mine, cluster and compare multidimensional biomolecular datasets. Various powerful visualization techniques are provided, generating high quality figures that can be directly incorporated into scientific publications. Robust and comprehensive analyses are provided via a broad range of data-mining techniques, including univariate and multivariate statistical analysis, supervised learning, correlation networks, clustering and multivariable regression...
December 6, 2016: Scientific Reports
https://www.readbyqxmd.com/read/27922113/non-small-cell-lung-cancer-quantitative-phenotypic-analysis-of-ct-images-as-a-potential-marker-of-prognosis
#3
Jiangdian Song, Zaiyi Liu, Wenzhao Zhong, Yanqi Huang, Zelan Ma, Di Dong, Changhong Liang, Jie Tian
This was a retrospective study to investigate the predictive and prognostic ability of quantitative computed tomography phenotypic features in patients with non-small cell lung cancer (NSCLC). 661 patients with pathological confirmed as NSCLC were enrolled between 2007 and 2014. 592 phenotypic descriptors was automatically extracted on the pre-therapy CT images. Firstly, support vector machine (SVM) was used to evaluate the predictive value of each feature for pathology and TNM clinical stage. Secondly, Cox proportional hazards model was used to evaluate the prognostic value of these imaging signatures selected by SVM which subjected to a primary cohort of 138 patients, and an external independent validation of 61 patients...
December 6, 2016: Scientific Reports
https://www.readbyqxmd.com/read/27922081/source-apportionment-of-chlorinated-polycyclic-aromatic-hydrocarbons-associated-with-ambient-particles-in-a-japanese-megacity
#4
Yuta Kamiya, Akihiro Iijima, Fumikazu Ikemori, Tomoaki Okuda, Takeshi Ohura
Chlorinated polycyclic aromatic hydrocarbons (ClPAHs) are novel species of environmental contaminants whose possible sources remain unclear. The occurrence of ClPAHs within total suspended particles (TSP) is compared with weekly air samples at two sites of differing characteristics (industrial and residential) in the megacity of Nagoya, Japan. Samples were collected over 12 months during 2011-2012. All 24 species of targeted ClPAHs were detected at both industrial and residential sites, where mean concentrations of total ClPAHs in TSP were 20...
December 6, 2016: Scientific Reports
https://www.readbyqxmd.com/read/27921338/melancholic-and-atypical-depression-as-predictor-and-moderator-of-outcome-in-cognitive-behavior-therapy-and-pharmacotherapy-for-adult-depression
#5
Pim Cuijpers, Erica Weitz, Femke Lamers, Brenda W Penninx, Jos Twisk, Robert J DeRubeis, Sona Dimidjian, Boadie W Dunlop, Robin B Jarrett, Zindel V Segal, Steven D Hollon
BACKGROUND: Melancholic and atypical depression are widely thought to moderate or predict outcome of pharmacological and psychological treatments of adult depression, but that has not yet been established. This study uses the data from four earlier trials comparing cognitive behavior therapy (CBT) versus antidepressant medications (ADMs; and pill placebo when available) to examine the extent to which melancholic and atypical depression moderate or predict outcome in an "individual patient data" meta-analysis...
December 6, 2016: Depression and Anxiety
https://www.readbyqxmd.com/read/27921121/a%C3%A2-4d-ultrasound-real-time-tracking-system-for-external-beam-radiotherapy-of-upper-abdominal-lesions-under-breath-hold
#6
Dwi Seno Kuncoro Sihono, Lena Vogel, Christel Weiß, Johannes Thölking, Frederik Wenz, Frank Lohr, Judit Boda-Heggemann, Hansjörg Wertz
BACKGROUND AND PURPOSE: To evaluate a novel four-dimensional (4D) ultrasound (US) tracking system for external beam radiotherapy of upper abdominal lesions under computer-controlled deep-inspiration breath-hold (DIBH). MATERIALS AND METHODS: The tracking accuracy of the research 4D US system was evaluated using two motion phantoms programmed with sinusoidal and breathing patterns to simulate free breathing and DIBH. Clinical performance was evaluated with five healthy volunteers...
December 5, 2016: Strahlentherapie und Onkologie: Organ der Deutschen Röntgengesellschaft ... [et Al]
https://www.readbyqxmd.com/read/27920952/a-methodology-for-the-design-of-experiments-in-computational-intelligence-with-multiple-regression-models
#7
Carlos Fernandez-Lozano, Marcos Gestal, Cristian R Munteanu, Julian Dorado, Alejandro Pazos
The design of experiments and the validation of the results achieved with them are vital in any research study. This paper focuses on the use of different Machine Learning approaches for regression tasks in the field of Computational Intelligence and especially on a correct comparison between the different results provided for different methods, as those techniques are complex systems that require further study to be fully understood. A methodology commonly accepted in Computational intelligence is implemented in an R package called RRegrs...
2016: PeerJ
https://www.readbyqxmd.com/read/27919732/learning-from-heterogeneous-temporal-data-in-electronic-health-records
#8
Jing Zhao, Panagiotis Papapetrou, Lars Asker, Henrik Boström
Electronic health records contain large amounts of longitudinal data that are valuable for biomedical informatics research. The application of machine learning is a promising alternative to manual analysis of such data. However, the complex structure of the data, which includes clinical events that are unevenly distributed over time, poses a challenge for standard learning algorithms. Some approaches to modeling temporal data rely on extracting single values from time series; however, this leads to the loss of potentially valuable sequential information...
December 2, 2016: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/27919705/the-complete-mitochondrial-genome-of-thitarodes-sejilaensis-lepidoptera-hepialidae-a-host-insect-of-ophiocordyceps-sinensis-and-its-implication-in-taxonomic-revision-of-hepialusadopted-in-china
#9
Zhiwen Zou, Qiang Min, Shiyu Cheng, Tianrong Xin, Bin Xia
The mitochondrial genome is widely used for phylogenetic analyses and evolutionary biology. The complete mitochondrial genome of Thitarodes sejilaensis (Lepidoptera: Hepialidae) was sequenced and analyzed in this study. This mitogenome is a typical circular molecule of 15,290bp, with the gene content, orientation and order identical to other insects in the family Hepialidae. The genome nucleotide composition is heavily biased towards As and Ts, accounting for 80.87% of total nucleotide content. The major strand shows a positive AT-skew and negative GC-skew...
December 2, 2016: Gene
https://www.readbyqxmd.com/read/27919675/individual-differences-in-internal-noise-are-consistent-across-two-measurement-techniques
#10
Greta Vilidaite, Daniel H Baker
Internal noise is a fundamental limiting property on visual processing. Internal noise has previously been estimated with the equivalent noise paradigm using broadband white noise masks and assuming a linear model. However, in addition to introducing noise into the detecting channel, white noise masks can suppress neural signals, and the linear model does not satisfactorily explain data from other paradigms. Here we propose estimating internal noise from a nonlinear gain control model fitted to contrast discrimination data...
December 2, 2016: Vision Research
https://www.readbyqxmd.com/read/27919554/quantitative-structure-property-relationships-for-predicting-sorption-of-pharmaceuticals-to-sewage-sludge-during-waste-water-treatment-processes
#11
L Berthod, D C Whitley, G Roberts, A Sharpe, R Greenwood, G A Mills
Understanding the sorption of pharmaceuticals to sewage sludge during waste water treatment processes is important for understanding their environmental fate and in risk assessments. The degree of sorption is defined by the sludge/water partition coefficient (Kd). Experimental Kd values (n=297) for active pharmaceutical ingredients (n=148) in primary and activated sludge were collected from literature. The compounds were classified by their charge at pH7.4 (44 uncharged, 60 positively and 28 negatively charged, and 16 zwitterions)...
December 2, 2016: Science of the Total Environment
https://www.readbyqxmd.com/read/27919391/privacy-preserving-data-cube-for-electronic-medical-records-an-experimental-evaluation
#12
Soohyung Kim, Hyukki Lee, Yon Dohn Chung
INTRODUCTION: The aim of this study is to evaluate the effectiveness and efficiency of privacy-preserving data cubes of electronic medical records (EMRs). An EMR data cube is a complex of EMR statistics that are summarized or aggregated by all possible combinations of attributes. Data cubes are widely utilized for efficient big data analysis and also have great potential for EMR analysis. For safe data analysis without privacy breaches, we must consider the privacy preservation characteristics of the EMR data cube...
January 2017: International Journal of Medical Informatics
https://www.readbyqxmd.com/read/27919250/the-impact-of-health-information-technologies-on-quality-improvement-methodologies-efficiency-throughput-and-financial-outcomes-a-retrospective-observational-study
#13
Raed H AlHazme, Syed S Haque, Hal Wiggin, Arif M Rana
BACKGROUND: To evaluate whether or not the utilization of Health Information Technologies (HITs) in Quality Improvement Methodologies (QIMs) has impacts on QIMs' efficiency, throughput and financial outcomes at healthcare organizations and physician practices in the United States. METHODS: This is a retrospective observational study that was conducted between the years of 2014 and 2015 and relied on two data sources: the Dorenfest Institute dataset and the Healthcare Information and Management Systems Society (HIMSS) Analytics data source...
December 5, 2016: BMC Medical Informatics and Decision Making
https://www.readbyqxmd.com/read/27919220/deepqa-improving-the-estimation-of-single-protein-model-quality-with-deep-belief-networks
#14
Renzhi Cao, Debswapna Bhattacharya, Jie Hou, Jianlin Cheng
BACKGROUND: Protein quality assessment (QA) useful for ranking and selecting protein models has long been viewed as one of the major challenges for protein tertiary structure prediction. Especially, estimating the quality of a single protein model, which is important for selecting a few good models out of a large model pool consisting of mostly low-quality models, is still a largely unsolved problem. RESULTS: We introduce a novel single-model quality assessment method DeepQA based on deep belief network that utilizes a number of selected features describing the quality of a model from different perspectives, such as energy, physio-chemical characteristics, and structural information...
December 5, 2016: BMC Bioinformatics
https://www.readbyqxmd.com/read/27919211/development-of-mlr-and-svm-aided-qsar-models-to-identify-common-sar-of-gaba-uptake-herbal-inhibitors-used-in-the-treatment-of-schizophrenia
#15
Sahila Mohammed Marunnan, Babitha Pallikkara Pulikka, V K Gopalakrishnan, Srinivas Bandaru, Mukesh Yadav, Anuraj Nayarisseri, Victor Arokia Doss
Deficits in GABAnergic system is implicated in the pathophysiology of schizophrenia. Available antipsychotics that target GABA receptor form a desirable therapeutic strategy in the treatment regimen of schizophrenia but, unfortunately, suffers serious setback due to their prolonged side effects. The present investigation focuses on developing QSAR models from the biological activity of herbal compounds and their derivatives that promise to be alternative candidates to GABA uptake inhibitors. Three sets of compounds were undertaken in the study to develop the QSAR models...
December 5, 2016: Current Neuropharmacology
https://www.readbyqxmd.com/read/27919075/land-use-intensification-causes-multitrophic-homogenization-of-grassland-communities
#16
Martin M Gossner, Thomas M Lewinsohn, Tiemo Kahl, Fabrice Grassein, Steffen Boch, Daniel Prati, Klaus Birkhofer, Swen C Renner, Johannes Sikorski, Tesfaye Wubet, Hartmut Arndt, Vanessa Baumgartner, Stefan Blaser, Nico Blüthgen, Carmen Börschig, Francois Buscot, Tim Diekötter, Leonardo Ré Jorge, Kirsten Jung, Alexander C Keyel, Alexandra-Maria Klein, Sandra Klemmer, Jochen Krauss, Markus Lange, Jörg Müller, Jörg Overmann, Esther Pašalić, Caterina Penone, David J Perović, Oliver Purschke, Peter Schall, Stephanie A Socher, Ilja Sonnemann, Marco Tschapka, Teja Tscharntke, Manfred Türke, Paul Christiaan Venter, Christiane N Weiner, Michael Werner, Volkmar Wolters, Susanne Wurst, Catrin Westphal, Markus Fischer, Wolfgang W Weisser, Eric Allan
Land-use intensification is a major driver of biodiversity loss. Alongside reductions in local species diversity, biotic homogenization at larger spatial scales is of great concern for conservation. Biotic homogenization means a decrease in β-diversity (the compositional dissimilarity between sites). Most studies have investigated losses in local (α)-diversity and neglected biodiversity loss at larger spatial scales. Studies addressing β-diversity have focused on single or a few organism groups (for example, ref...
November 30, 2016: Nature
https://www.readbyqxmd.com/read/27918908/likelihood-ratio-sequential-sampling-models-of-recognition-memory
#17
Adam F Osth, Simon Dennis, Andrew Heathcote
The mirror effect - a phenomenon whereby a manipulation produces opposite effects on hit and false alarm rates - is benchmark regularity of recognition memory. A likelihood ratio decision process, basing recognition on the relative likelihood that a stimulus is a target or a lure, naturally predicts the mirror effect, and so has been widely adopted in quantitative models of recognition memory. Glanzer, Hilford, and Maloney (2009) demonstrated that likelihood ratio models, assuming Gaussian memory strength, are also capable of explaining regularities observed in receiver-operating characteristics (ROCs), such as greater target than lure variance...
December 2, 2016: Cognitive Psychology
https://www.readbyqxmd.com/read/27918905/dental-age-estimation-of-children-and-adolescents-validation-of-the-maltese-reference-data-set
#18
Hani Alsaffar, Waleed Elshehawi, Graham Roberts, Victoria Lucas, Fraser McDonald, Simon Camilleri
The purpose of this study was to validate a Reference Data Set, developed from the radiographic archives of the Dental Department, Mater Dei Hospital, Malta, for Dental Age Estimation of the Maltese population and to assess the accuracy of the method. Dental Panoramic Tomograms of 100 male and 100 females were selected. Tooth Development Stages were recorded for all 16 permanent teeth on the left and both third molars on the right. Summary and percentile data were calculated for each Tooth Development Stage and the Dental Age of each subject estimated using the unweighted average method...
November 28, 2016: Journal of Forensic and Legal Medicine
https://www.readbyqxmd.com/read/27918893/spectrum-image-analysis-tool-a-flexible-matlab-solution-to-analyze-eel-and-cl-spectrum-images
#19
Franz-Philipp Schmidt, Ferdinand Hofer, Joachim R Krenn
Spectrum imaging techniques, gaining simultaneously structural (image) and spectroscopic data, require appropriate and careful processing to extract information of the dataset. In this article we introduce a MATLAB based software that uses three dimensional data (EEL/CL spectrum image in dm3 format (Gatan Inc.'s DigitalMicrograph(®))) as input. A graphical user interface enables a fast and easy mapping of spectral dependent images and position dependent spectra. First, data processing such as background subtraction, deconvolution and denoising, second, multiple display options including an EEL/CL moviemaker and, third, the applicability on a large amount of data sets with a small work load makes this program an interesting tool to visualize otherwise hidden details...
November 21, 2016: Micron: the International Research and Review Journal for Microscopy
https://www.readbyqxmd.com/read/27918599/hierarchical-bayesian-inference-for-ion-channel-screening-dose-response-data
#20
Ross H Johnstone, Rémi Bardenet, David J Gavaghan, Gary R Mirams
Dose-response (or 'concentration-effect') relationships commonly occur in biological and pharmacological systems and are well characterised by Hill curves. These curves are described by an equation with two parameters: the inhibitory concentration 50% (IC50); and the Hill coefficient. Typically just the 'best fit' parameter values are reported in the literature. Here we introduce a Python-based software tool, PyHillFit , and describe the underlying Bayesian inference methods that it uses, to infer probability distributions for these parameters as well as the level of experimental observation noise...
2016: Wellcome Open Res
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