dataesr/scientific-paragraphs-categorization huggingface dataset:
DISCUSSION We have proposed FBID, a new definition of impact degree, which can not only efficiently deal with the reversible reactions in metabolic networks but also have the state conditions being taken into account. To compute the FBID against perturbations, we proposed two algorithms, an LP-based method and an EMbased algorithm. The advantage of the LP-based method is that it can solve all LP instances individually, can strongly benefit Fig. 4. ROC curve (left) and precision-recall curve (right) for phenotype prediction with FBID and FBA on the Keio dataset using the iJO1366 network Although computational cost of the LPbased method grows with the network size and the number of perturbations to be tested, the overall time complexity is still bounded polynomially. If we are interested in only a few candidate perturbations, then only the corresponding LP need to be solved.
ACKNOWLEDGEMENT We thank the reviewers for many helpful suggestions, in particular, the possibility to compute FBID efficiently with fastFVA. Funding:  Japan Society for the Promotion of Science, Japan  ( Grants-in-Aid 22240009  and  22650045  to T. A, in part;  Grantin-Aid for Scientific Research  (A)  25250028  to T. T in part);  European Research Council  ( SMAC-ERC-280032  to J. P. V. ).
This apprehension is often focused on the fear of involuntary eye movements during the procedure, which may complicate the surgeon's task, on patients' fear of seeing their eye surgery or on the fear of painful sensations. In reply, quite abundant data are now available stemming from several studies focused on the impressions of patients during the procedures. 2 3  Various methods to assess the perception of pain have been used and have validated that cataract surgery under topical anaesthesia is by and large usually a painless procedure. 4 Visual sensations experienced by patients under the operating microscope have also been recorded and have mostly been found to be of no concern. 5 6 In addition to these topics, patients prior to their surgery have frequent qualms regarding the duration of the procedure and hence regarding their ability to withstand their eye surgery under topical anaesthesia.
METHODS The study was set in the Department of Ophthalmology of Hôpital Cochin, a teaching university hospital located in Paris, France. Data were collected prospectively from consecutive patients operated between 17 May 2011 and 22 July 2011, and was approved by the Institutional Review Board. All patients who had uneventful phacoemulsification under topical anaesthesia with the placement of an intraocular lens in the capsular bag were included. Cases with any 'significant adverse event' defined either by a major intraoperative complication such as vitreous loss or by a technical problem such as phacoemulsifier malfunction that prolonged the procedure by 10 min or more were excluded. Similarly, patients who required any anaesthesia in addition to topical lidocaine 2% gel or those who required sedation in addition to the preoperatively given hydroxyzine were excluded from the analyses.
We also computed the intraclass correlation coefficient to quantitatively evaluate the agreement. Correlation tests were conducted using the Spearman's correlation coefficient (r). Factors with p<0. 10 in the univariate analysis were included in a multivariate linear regression and analysis of covariance model to determine the independent factors associated with either objective or patient-assessed surgery durations. p Values <0. 05 were considered significant. All analyses were performed with XLSTAT V. 2012. 2. 02 software (Addinsoft, Paris, France).
Endpoints Endpoints considered were time from surgery to distant metastasis and breast cancer specific survival (BCSS), defined as time from surgery to breast cancer-related death. For the analysis of distant metastasis-free survival (DMFS) we considered distant metastases as failure; patients were censored on date of death from any cause or date of last follow-up visit. For the BCSS analysis patients were censored on date of last follow-up or date of death from other cause. Clinico-pathological data was collected, and databases were pooled for our current study.
Discussion We report here the last series of the complete range of Mam-maPrint assessment as prognostic assay in primary breast cancers. Table  3  summarizes the various validation studies published so far. All studies confirmed the prognostic significance of the signature, and were combined in a large database of 1696 patients which included 72 patients with more than 4 positive nodes representing only 4% of the total study population. The group of patients with 4 or more involved nodes represents 10% of the population in the Oncopool database of 16,944 cases of breast cancers,  11  but remains poorly studied in terms of clinicopathological and biological features. In the current report we selected a cohort of 173 patients who were diagnosed with 4e9 lymph nodes at initial diagnosis. Interestingly, the signature classified 40% of the patients at Low Risk and 60% at High Risk, and these proportions remain similar throughout all the series, whatever the clinical group of patients studied, including the report of the pilot phase (800 patients) of the ongoing prospective clinical trial MINDACT.
The light-weight separation device was laboratory tested down to a temperature of -20 • C. It is composed of both a Microchip microcontroller PIC 16F88 and a Freescale MPX4515A analogue pressure sensor that performs measurements in the range 1150-150 hPa with an accuracy of 15 hPa. Raw pressure data are collected by rounds of nine measurements performed every 100 ms. The separation order is based upon the median value of those nine samples to mitigate the impact of noisy measurements. The set release is coded on 6 bits, which provides a resolution of 10 hPa between 1050 and 420 hPa. The separation is achieved by fusion of a nylon wire wrapped around a resistance of 15 , 1/4 W powered at 8. 2 V. The mean delay between the pressure measured by the sensor and the target separation is 3 hPa (STD of 2 hPa).
Uncertainties on the landing point As discussed earlier, a proper estimation of the landing point is needed to maximize the odds of recovering the probes or to achieve particular applications (Fig. 4 ). The two major sources of uncertainties arise from the estimation of the ascent/descent speed of the system and from the accuracy of the vertical wind profile used to estimate the flight trajectory. A couple of experiments were conducted from the BLLAST dataset in order to evaluate the impact of these errors on the determination of the landing point. Figure  7a  shows the differences between the actual landing point of each recovered radiosonde and the ones simulated using horizontal wind profiles forecasted by Arome at the time of soundings and (i) mean theoretical ascent and descent speeds of 5 and 3.
Primary antibodies were followed by secondary horseradish peroxidase conjugated mouse or rabbit antibodies (Jackson ImmunoResearch, West Grove, PA, USA). Membranes were visualized using Pico Stable peroxide solution and luminol enhancer solution (Pierce Biotechnology, Inc. , Rockford, IL, USA). Protein bands were detected by Kodak Image Station 4000R (Eastman Kodak Company, Rochester, NY, USA), and quantified using the Carestream MI (Carestream Molecular Imaging, Woodbridge, CT, USA) analysis software. Data were exported to Excel spreadsheet and corrected for background and loading control signal, prior to statistical analysis in the Graphpad PRISM software, using the paired Student's t-test to compare two and two groups. 3 H-thymidine DNA incorporation H1299 cells (2610 3 or 5610 3 ) were seeded in 96 well plates and left to settle for 20 hours prior to treatment.
The cells were treated for 8 or 12 hrs, and 3 H -thymidine (1 mCi per well; TRA310, Amersham International, Amersham, UK) was added the last 6 or 10 hours of the treatment period, respectively. For basal proliferation experiments the cells were incubated with 3 H-thymidine for 10 hours. Cells were harvested and DNA synthesis was determined by 3 H-thymidine incorporation assays as described  [31]. Statistical analysis was performed using GraphPad PRISM (version 5. 0b, GraphPad Software, Inc. , La Jolla, CA, USA) software. Groups were compared using paired Student's t-test.
554293 BD Pharmingen) diluted in 16PBS with 0. 5% BSA and incubated at 4uC over night before incubation with secondary antibody (1:5,000 of Alexa 488 goat anti-mouse (Invitrogen Molecular Probes)) diluted in 16PBS with 0. 5% BSA, and incubated in the dark for 1 hour at room temperature. Last, the coverslip was washed 16PBS and mounted in 5 ml Fluoro-gel II with DAPI (Electron Microscopy Sciences, PA, USA). Images of cell fluorescence were acquired with a Zeiss Axio Observer Z1 inverted microscope (Carl Zeiss Microimaging GmbH, Germany) and analyzed by the AxioVision 4. 8. 2 software.
First, red signals were detected automatically in each confocal section. Visual control confirmed that more than 90% of all red signals for each slice of each image were detected correctly, with respect to human judgment (Figure  4A, B, E, F ). The detection of chromosome territories was more complicated because in most cases it was not evident to an observer (expert) where exactly the borders of the chromosome territory should lie (Figure  4C, D, G, H, I ). Clearly, computer programs would detect chromosome territories with a bit of uncertainty and the statistical data would be more relevant. On each image automatically detected chromosome territories were confirmed by visually comparing them to the initial images and detection parameters adjusted to make the results more adequate. The parameters for chromosome territory detection were the same for all images (due to good normalisation).
Analysis of a relative position of the MLL gene with respect to chromosome 11 territory The 3' fragment of the MLL gene was labelled with SpectrumOrange marker (detected as a red signal). The chromosome 11 territory was labelled with a fluorescent marker possessing the same characteristics as FITC (detected as a green signal). Nine series of experiments were carried out. Each series included confocal microscope images of control and etoposide-treated cells, several fields of view in each case. Further steps were applied separately to each image consisting of numerous slices, which were documented as separate graphical files (Table  1 ). Images from both control and etoposide-treated cells underwent the same protocol. The protocol is based on scripts written by authors in the bash and Python programming languages with the use of the Python Imaging Library and Numpy packages.
From these values the differences (ΔL*, Δa* and Δb*) can be calculated as well as the total colour difference (ΔE*) between treated and untreated wood. (1) The measurements of hardness and modulus of elasticity in compression were performed on Zwick 050 machine by the Janka method. Janka hardness test measures the resistance of a type of wood to denting and wear. It measures the force required to embed an 11. 28 mm steel ball into wood. The values of modulus of elasticity were calculated by software testXpert, hardness was calculated by the following equation. (2) Density was measured by common equation  (Siau 1984). Equilibrium moisture content was observed on all specimens which were subjected to the same conditions as the untreated ones.
ACKNOWLEDGEMENT This work was funded by the  European Social Fund  and the state budget of the  Czech Republic, project  " The Establishment of an International Research Team for the Development of New Wood-based Materials " reg. no. CZ. 1. 07/2. 3. 00/20. 0269 ( EE2. 3. 20. 0269 ). This study was also supported by the  Internal Grant Agency (IGA) of Faculty of Forestry and Wood Technology, Mendel University in Brno  -project no. 26/2012  and  IGA-V 50/2011.
Phenotypic analysis Cell suspensions were suspended in PBS 2% FCS and stained with anti-human antibodies (BD, Beckman). pDCs were iden- tified as CD45 þ HLA-DR þ BDCA2 þ or Lin À HLA-DR þ CD123 þ and myeloid dendritic cells as Lin À HLA-DR þ CD11c þ. The phenotype of pDCs was determined using anti-CD62L, -OX40L, -GITRL, ICOSL, -PDL1, -PDL2, -CD40, -CD80, -CD86 antibodies and their isotype-matched controls. Suspensions were subjected to flow cytometry analysis using a FACSCalibur and CellQuest software (BD).
Modeling Modeling of the water chemistry, including calculation of percent error in charge balance, the effect of temperature on chemical speciation, the saturation state of the water with respect to mineral and gas phases, and predictions of the aqueous chemistry during CO 2 injection was performed using PHREEQC  (Parkhurst and Appelo, 1999). The standard PHREEQC database with additional data from  Gysi and Stefánsson (2011)  was used for these model calculations.
Acknowledgements We would like to thank our friends and co-workers at the  University of Iceland , in particularly  Júlía K. Björke ,  Eydís S. Eiríksdóttir ,  Snorri Guðbrandsson ,  Iwona M. Galeczka ,  Kiflom G. Mesfin ,  Gabrielle Stockmann ,  Alexander Gysi ,  Nicole Hurtig ,  Mahnaz Rezvani Khalilabad ,  Domenik Wolff-Boenisch ,  Andri Stefánsson ,  Níels  Óskarsson and Þorsteinn  Jónsson  for field-and lab assistance and fruitful discussions. We would also like to thank  Einar Örn  Þrastarson,  Hólmfríður Sigurðardóttir ,  Edda Sif Aradóttir ,  Ingvi Gunnarsson  and  Bergur Sigfússon  at  Reykjavík Energy ;  Clare Desplats  at  CNRS, Toulouse ; and  Godfrey Fitton  and  Nic Odling  at the  Universty of Edinburgh. The  Environmental Fund of Reykjavík Energy  through the CarbFix project and the European Community through the  MIN-GRO Research and Training Network  ( MRTN-CT-2006-035488 ) and the  European R&D  Project  CARBFIX  ( FP7-ENERGY-2011-1-283148 CarbFix ) are thanked for their financial support.
Search methods We searched the Cochrane Infectious Diseases Group Specialized Register; Cochrane Central Register of Controlled Trials (CENTRAL); MEDLINE; EMBASE; CABS Abstracts; and LILACS up to 24 October 2012. We handsearched the Tropical Diseases Bulletin from 1900 to 2010, the archives of the World Health Organization (up to 11 February 2011), and the literature database of the Armed Forces Pest Management Board (up to 2 March 2011). We also contacted colleagues in the field for relevant articles.
Electronic searches We searched the following databases using the search terms and strategy described in Appendix 1: Cochrane Infectious Diseases Group Specialized Register; Cochrane Central Register of Controlled Trials (CENTRAL), published in The Cochrane Library; MEDLINE; EMBASE; CABS Abstracts and LILACS  (May 10, 2013). We handsearched the US Armed Forces Pest Management Board Defense Pest Management Literature Retrieval System (search completed March 2, 2011) and the Tropical Diseases Bulletin from 1900 to 2010 (search completed March 2, 2011) using the terms: malaria AND mosquito control.
Data collection and analysis Selection of studies SL and JT independently screened the electronic search results for potentially relevant studies. We attempted to retrieve the full articles for all studies identified by either SL or JT. Both LT and JT independently screened the handsearch results for potentially relevant studies. JT, LT, and KB assessed eligibility using an eligibility form. Two authors (JT, LT, or KB) assessed each article independently, and we resolved any disagreements through discussions with the third author. If any disagreement remained, SL or JG made a final judgment. Native speakers evaluated the foreign language studies in consultation with one of the authors. We checked study reports to ensure that multiple publications from the same study were included only once.
Data extraction for cluster-RCTs For trials randomized using clusters, we extracted the number of clusters in the trial, the average size of clusters, and the unit of randomization (for example, household or community). Where possible, we documented the statistical methods used to analyze the trial. We examined the methods for adjustments for clustering or other covariates. We recorded estimates of the intra-cluster correlation (ICC) coefficient for each outcome when they were reported. We contacted authors to request missing information. Where results were not adjusted for clustering, for count data (incidence of clinical malaria) we extracted the number of events in the treatment and control group and the total person time at risk in each group. For dichotomous outcomes (parasite or splenomegaly prevalence), we extracted the number of participants that experienced the event and the number of participants in each treatment group.
Data synthesis We calculated the outcome measure (for example, parasite prevalence) separately for each year, month, or survey and we took an unweighted average to aggregate data from multiple years, months, surveys, or sites. We compared data from the follow-up period (for both control and intervention areas) for the same portion of the year to take into account seasonality where baseline data were available only for portion of a year. For data collected from multiple cross-sectional surveys, we used data during or immediately after a transmission season, rather than during a dry season or at the beginning of a transmission season. Where longitudinal data were presented separately for the transmission and non-transmission season, we used the data for the transmission season. For studies where no events were observed in one or both arms, we added a fixed value (0.
Clinical data For cluster-RCTs and controlled before-and-after trials, we stratified the data by intervention: (1) habitat modification alone; (2) habitat modification with larviciding; (3) habitat manipulation alone; (4) habitat manipulation with larviciding; (5) larviciding alone; or (6) any LSM. We then stratified by outcome: (1) incidence of malaria; (2) parasite prevalence; or (3) splenomegaly prevalence. Finally, we stratified the data by study design: (1) cluster-RCTs; or (2) controlled before-and-after trials. Although the interventions used in these trials were highly variable, we justified pooling of data across interventions in the final analysis as all trials shared the common aim to reduce mosquito numbers. In this respect, we judged the interventions as appropriately different as they were designed to suit the local vector biology and larval habitats.
Blinding Due to the nature of the intervention, blinding of the implementers and the recipients was not possible, and we therefore classified all trials at high risk of performance bias. Two cluster-RCTs only reported entomological data. As it would have been impossible to blind the data collectors, we classified these trials at high risk of bias (Coulibaly 2011 MLI; Shililu 2007 ERI). We judged two cluster-RCTs reporting clinical outcomes at unclear risk of detection bias (Yapabandara 2001 LKA; Yapabandara 2004 LKA). Two of the controlled before-and-after studies blinded the microscopists to allocation and we considered these trials at low risk of detection bias  (Fillinger 2009 KEN; Geissbühler 2009 TZA). Three trials did not blind the microscopists to allocation and we considered these trials at high risk of detection bias  (Balfour 1936 GRC; Fillinger 2008 TZA; Sharma 2008 IND).
Selective reporting We judged two cluster-RCTs at high risk of reporting bias as they had evidence of selective reporting for entomological outcomes. The authors described several methods of data collection but they did not report all (Yapabandara 2001 LKA; Yapabandara 2004 LKA). We deemed two controlled before-and-after trials at high risk of selective reporting as they collected data on the whole population but only reported data on children  (Castro 2009 TZA; Geissbühler 2009 TZA).
Comparison 5. Larviciding alone versus control Three cluster-RCTs, one randomized cross-over study, and three controlled before-and-after studies evaluated larviciding alone. Two cluster-RCTs were conducted in rural Sri Lanka, where larvicide (pyriproxyfen) was applied to larval habitats two to three times over a one year period. The main larval habitats of the primary vectors An. culicifacies and An. subpictus were abandoned gem mine pits (Yapabandara 2001 LKA) and river bed pools, streams, irrigation ditches, and rice paddies (Yapabandara 2004 LKA). The third RCT was conducted in Mali and reported entomological data only (Coulibaly 2011 MLI). Larvicide (Bti and Bs) was applied to larval habitats every one to two weeks for 18 months. The main larval habitats of the primary vector An. gambiae were brick pits, ponds, and tyre prints.
The editorial base for the Cochrane Infectious Diseases Group is funded by UKaid from the UK government for the benefit of developing countries. Steve Lindsay received partial funding for this work from the Research and Policy for Infectious Disease Dynamics (RAPIDD) Program of the Science and Technology Directory, Department of Homeland Security, and Fogarty International Center, National Institutes of Health. Ulrike Fillinger is supported through a National Institute of Health (NIH) Grant (grant number R01 AI082537). Lucy Tusting received a Fellowship from the Cochrane Infectious Diseases Group. The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention.
Cluster size: Unclear Number of clusters in each arm: Intervention The editorial base for the Cochrane Infectious Diseases Group is funded by UKaid from the UK government for the benefit of developing countries. Steve Lindsay received partial funding for this work from the Research and Policy for Infectious Disease Dynamics (RAPIDD) Program of the Science and Technology Directory, Department of Homeland Security, and Fogarty International Center, National Institutes of Health. Ulrike Fillinger is supported through a National Institute of Health (NIH) Grant (grant number R01 AI082537). Lucy Tusting received a Fellowship from the Cochrane Infectious Diseases Group. The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention.
63(7):623-77. Francesca Solmi, Gabriel Ponce de Leon, Junko Kiriya, Liam Crosby, Lucy Haurisa, Mariana De Niz Hidalgo, Marta Buysana, Pluess 2010 Pluess B, Tanser FC, Lengeler C, Sharp BL. Indoor Support for judgement High risk of confounding. Marta Maia, Maryna Braga, Sara Carrillo de Albornoz, Yulia Iossi-fova, and Tapan Bhattacharyya assisted with the translation of for-eign language papers. The London School of Hygiene and Trop-residual spraying for preventing malaria. Cochrane Database Environmental management sites purpose-of Systematic Reviews 2010, Issue 4. DOI: 10. 1002/ 14651858. CD006657. pub2 fully chosen according to stated criteria ical Medicine Library and Archives and the Centers for Disease Control and Prevention Library Services helped with article re-Ranson 2011 Sites purposefully selected.
In this work we use the ultra-deep (m AB <26. 5, 3σ) optical medium-band spectro-photometry provided by the Survey for High-z Absorption Red and Dead Sources (SHARDS;  Pérez-González et al. 2013)  in combination with accurate photometric and spectroscopic redshifts and stellar masses from the Rainbow 1  database  (Pérez-González et al. 2008; hereafter PG08)  to analyse the stellar populations and star formation histories of a mass-selected sample of galaxies at 0. 65<z<1. 1. SHARDS is imaging an area of 141 arcmin 2 in the GOODS-North field with GTC/OSIRIS in 24 contiguous medium-band (R∼50) filters covering the spectral range 500-950 nm. At the time of this writing, the entire survey area has been observed in the 15 filters covering the spectral range 636-883 nm, and one half of the area has also been observed in the F619W17 filter (central wavelength: 619 nm, FWHM: 17 nm).