dataesr/scientific-paragraphs-categorization huggingface dataset:
Pour le pilotage de l'appareil, acquisition et pré-traitement des données, nous avons utilisé le logiciel SpectraMagic XN (Konika Minolta Optics Inc. ). Le traitement statistique des données a été fait avec le tableur Excel (Microsoft Corp. ). Pour caractériser chacune des six tapisseries, une gamme de couleurs et de nuances la plus large possible a été mesurée, incluant à chaque fois des parties originelles et des parties restaurées (fig. 3 ), tout en privilégiant les surfaces les plus homogènes. Chaque point de mesure est la valeur moyennée de trois prises successives faites automatiquement par l'appareil sans déplacement de sa tête de mesure. Pour diminuer l'erreur due au positionnement de la tête de mesure, plus ou moins reproductible, 2 à 4 points de mesure rapprochés par fragment de surface ont été sélectionnés.
Remerciements À toute l'équipe de restauration :  Cécilia Aguirre  (metzlicecilia@ gmail. com), Thalia Bajon-Bouzid  (thbajonbouzid@gmail. com),  Anne Breugnot  (annebreugnot@yahoo. fr),  Sylvie Forestier  (sylforestier@orange. fr).
Laboratory testing of hospitalized patients can sometimes be unnecessary, particularly repetitive testing  [11]. The CPOE itself can favor such repetitive testing, particularly when its workflow does not correspond to the usual behavior of the physician (eg, when a physician orders a test for a patient and does not know that the same test has already been recently ordered, even if the result is stored in the CPOE database)  [12]. However, CPOE with embedded decision-support tools could reduce such repetitive testing  [11, 13, 14]. In this study, we hypothesized that a reminder of previous existing results (collected from all available patient stays) could prevent unnecessary viral serology testing. We evaluated the impact of a Serology-CDSS providing point of care reminders of previous existing serology results, embedded in a CPOE used in a university teaching hospital.
Outcome measures Primary outcome The primary outcome was the proportion of unnecessary repetitions of viral serology tests. A test was considered unnecessary when it was ordered within 90 days after the presence in the EHR of a result of the same test for the same patient. The test could have been ordered in the Cardiovascular Surgery department or in another department. Conversely, HBs antigen tests were not considered as unnecessarily repeated when previous results were unavailable (poor sample, broken tube. ). Laboratory results of interest were extracted from the DxCare® database for the study period.
Secondary outcome Each time a physician intended to order a test within the 90 day limit, a record was stored in the Serology-CDSS database. The records stored by the Serology-CDSS make it possible to estimate the proportion of all intentions to repeat a test order within 90 days of the last test. Compliance with the alert was evaluated by comparing the number of HBV tests unnecessarily repeated, ie, the number of 90-day repeated results compared to the number of potentially unnecessary HBV test orders, ie, the number of « alerts displayed ».
Acknowledgement I dedicate this thesis to my mom and dad, for their endless love, support and encouragement. Thank you for always supporting my choices, even when it meant I would be living in another continent. I have had the luck of being surrounded by outstanding individuals throughout my PhD journey, people without whom this thesis would not have been completed. First, I would like to acknowledge my supervisor Patricia Dargent-Molina. She is an exceptional mentor; offering the perfect 'balance' between academic freedom, and wise guidance. She was always a knock on the door away, ready to listen to my point of view, and perceptively guiding my autonomous reasoning. I learned a lot from her on many levels, her dedication and perfectionism is inspiring. I also like to thank Prof Bernard Cassou.
Méthodes Revue systématique et méta-analyse Des recherches bibliographiques ont été effectuées dans plusieurs bases de données (PubMed, Cochrane Library, Embase, CINAHL) pour repérer les essais randomisés contrôlés de prévention des chutes par l'exercice physique réalisés chez des personnes de plus de 65 ans vivant à leur domicile, et publiés jusqu'en juillet 2013. Les essais qui ciblent des participants ayant des problèmes neuro-dégénératives, les études qui comparent des interventions multifactorielles, ou qui ne présentent pas des données quantitatives sur les conséquences des chutes, étaient exclus. Les recommandations de la 'Cochrane Collaboration' ont été appliquées pour évaluer le risque de biais de chacun des essais les domaines suivants : méthode de randomisation, dissimulation de l'allocation des groupes, évaluation à l'aveugle ou pas, méthode de confirmation de la blessure, et le traitement des données manquantes.
Search strategy Once the study question had been well defined and the criteria for the studies to be included had been specified, the next step was to conduct a thorough, exhaustive and reproducible literature search to identify relevant studies. Since there is no single database that covers all publications from all healthcare journals, several electronic databases were searched, supplemented by examining other pertinent resources. This comprehensive search of a range of sources minimises selection bias and is one of the major differences between systematic reviews and other reviews. Thus The Cochrane Library, Pubmed, Embase, and CINAHIL databases were searched in order to identify relevant studies published in peer-reviewed journals through June 2013. The Cochrane library is a collection of databases in medicine and other healthcare subjects, Embase is an international biomedical database that contains over 25 million indexed records from thousands of peer-reviewed journals.
A subscription is needed to access this database. Hand searching: we also screened references in relevant reviews for additional studies. All the references in the latest Cochrane review on 'Interventions for preventing falls in older people living in the community' were manually searched  (Gillespie et al. 2012). The references in two other relevant reviews were also hand-searched  (Sherrington et al. 2011; Schwenk et al. 2012 ).
Literature search results Figure  3  presents the flow chart of the studies' selection process. We identified 524 potentially eligible titles from searching the Cochrane library, 593 titles from Pubmed, 412 from Embase and 70 from the CINAHIL engine. In total, we had collected 1599 titles and abstracts from searching electronic databases. We also identified 59 titles and abstracts through handsearching references in pertinent reviews. After removing duplicates, the total number of titles and abstracts we examined was 1011 papers, from which 812 papers were excluded after examination. Thus 199 full-text articles were retrieved and examined for inclusion, from which 172 were excluded:   Most of the trials were carried out in industrialised countries (USA (3), Australasia  (5) , Europe (7)), with only one trial located in China  (Li, 2005).
Effect of exercise on all falls We had also extracted data on all falls, and computed a pooled estimate for the effect of exercise intervention on the rate of falls for trials included in each analysis described above. These effects were: 0. 64 (0. 55-0. 73) for trials included in category A analysis, 0. 74 (0. 61-0. 89) for trials included in category B analysis, 0. 69 (0. 56-0. 85) and 0. 64 (0. 55-0. 75) for trials included in category C and D analyses.
Data management Completed fall surveys were digitised by an independent data entry company. Separately, the investigator who called the woman registered the event on the study's data management software. This password-protected software was specially developed by the URC (Unité de Recherche Clinique Paris-Ouest, developers: O. Thierry and A. Cindy) for the Ossebo study and could only be accessed through the servers of the CESP in Villejuif. At the end of the follow-up, records from the digitised fall surveys were compared and verified with exported registers from the study software using the SAS software to ensure that all falls were included in the analysis and validate the records used for analysis.
There was information available from 609 (Intervention group: n=299) women for the first follow-up examination, and from 573 (I=284) participants for the examination at the end of the study (figure  13 ). For the first examination at 1 year after inclusion, 602 (I=297) women undertook the physical examination and completed the auto-questionnaire. Five women (I=1) completed the physical examination but did not return the questionnaire, while 2 women (I=1) only returned the auto-questionnaire. For the second examination at the end of the trial, data from the physical examination and auto-questionnaire was available for 570 (I=283) participants, while the other 3 women (I=2) only returned the auto-questionnaire. Table  6  presents reasons for drop out in the two groups.
2007 ). The difference between the 2 MCFs corresponds to the mean number of preventable events by participant. A log-rank type test of equality of the rate functions was used to test the equality of the 2 MCFs, assuming the weight functions are constant through time (events that occur at different times has the same weight) (Joseph C. Gardiner 2014). This analysis was done for every fall outcomes: injurious falls, all falls, and severe injurious falls using the 'reliability' procedure in SAS  (Gutierrez, n. d. ).
3. 2. 1. c. Sensitivity analysis To assess the potential impact of attrition (incomplete outcome data due to attrition) on the intervention effect estimates, we performed a sensitivity analysis using a worst case scenario based on the method proposed in the Cochrane review of interventions to prevent falls  (Gillespie et al. 2012). At first the ratio of two rate ratios of falls were computed: the first one (RaR1) is calculated by dividing the rate of injurious falls in the intervention group by the rate of injurious falls in the control group, using all available data. These rates were not computed with a statistical model but by dividing the total number of injurious falls by the number of person-years in each group (to use the same computation method as for the second rate ratio). The second ratio (RaR2) is calculated for all participants by using the conservative assumption that participants with missing data in the intervention group had the same rate of falls as observed in the control group (during their "lost" follow-up time), and vice versa.
Then a population-averaged model (marginal model) was used to analyse the effect of the intervention on these repeated measures. The marginal model adjusts for within-subject co-variability by modelling the within-patient covariance structure  (Verbeke and Molenberghs 2009). In other words, observations from the same individual are not assumed to be independent. This is done by assuming that the residuals from a single subject are related: their covariances are non-zero. The term 'marginal' is used to Methods 120 emphasise that the mean response modelled is conditional only on covariates and not on other responses or random effects. To choose the best covariance structure, the different available structures in SAS (variance component, autoregressive, Toeplitz, compound symmetry, and unstructured) were compared using the Akaike Information Criterion (AIC).
Therefore for each variable, the covariance structure of the model with the lowest AIC was chosen. A random effect for study centre was also added to the model. All analyses were conducted with SAS 9. 4 (SAS Institute, Inc). The analysed data set had one examination per observation (maximum 3 rows per women). The 'poc Genmod' procedure was used for GEE modelling, along with the 'repeated' statement for subject identification. The statement 'estimate' was used to compute a relative risk and confidence intervals by using robust error variances. The marginal model was run with the 'proc mixed' procedures, using the 'repeated' statement for subject identification, and the 'random' statement for adjusting for centre. At each follow-up the fixed effect of the intervention was extracted using the 'lsmeans' statement that presented the estimated mean difference along with its 95% confidence interval between the two groups.
3. 4. 1. b. Programme-implementation factors Implementation-related variables concern the design and execution of the intervention. These variables include the distance from a participant house to the exercise location, the setting of the exercise location, and the period of the year (season) when the baseline examination took place. Due to the hierarchical structure of the data (participants nested within centres), multivariate analysis was carried out with a multilevel mixed effects logistic regression in order to identify factors independently associated with participation  (Dai, Li, and Rocke 2006). Two 'levels' of characteristics were considered for this analysis; individual characteristics (first level) and characteristics relevant to the centre (2 nd level) or 'implementation' factors (Figure  25 ).
The underlying hypothesis is that women from the same centre are more similar than those between centres, and this would result in clustering of the data. Multi-Level Modelling is a statistical technique that controls for the effects of clustering, as well as allowing the examination of explanatory variables at the two levels. As a result, individual and centre level variables can be considered in tandem when developing a model, adding considerably to the statistical robustness of the model  (Dai, Li, and Rocke 2006). Odds ratios with 95% confidence intervals are presented. A value of p<0. 05 was accepted as being statistically significant. Analyses were performed with SAS V9. 4. , with the 'Proc Glimmix' procedure, with the link function 'logit'. All independent variables were entered as fixed factors, additionally; the random intercept was added at the centre (2 nd ) level.
provided by the Cochrane Collaboration and other organisations. It contains among other databases 'The Cochrane Central Register of Controlled Trials (CENTRAL)'; a database listing the details of articles of Controlled trials and other studies of healthcare interventions from bibliographic databases and other published and unpublished sources. A subscription is needed to access this library. The search terms used in the Cochrane Library were: (fall) and (exercise or tai chi or training or physical activity) excluding (Alzheimer or Parkinson's or dementia or nursing home or protocol or athletes) in the title or abstract of trials, with the word 'prevention' in the text and the word variations option enabled. Pubmed is a subscription-free search engine maintained by the United States National Library of Medicine (NLM) at the National Institutes of Health (NIH).
Using this engine that searches 'Medline', a bibliographic database of life sciences and biomedical information, we searched for: (((fall*[Title/Abstract]) AND (Title/Abstract]) NOT ((parkinson's) OR (asthma) OR (alzheimer) OR (dementia*)OR "nursing home"[Title/Abstract]), while specifying that search results should have be a 'clinical trial' or a 'controlled clinical trial' or a 'randomised controlled trial', in 'humans' and   for 'middle aged: 45-64 years' or 'aged:65+years' or '80 and over: 80+ years'.
The search terms for this database were: fall*:ab and (exercise:ab or train*:ab or 'tai chi':ab or 'physical activity':ab) not ('nursing homes':ti or parkinson*:ti or alzheimer:ti or dementia:ti or stroke:ti) and ([controlled clinical trial]/lim or [randomized controlled trial]/lim) and ([article]/lim or [article in press]/lim) and [aged]/lim and [humans]/lim. CINAHL (Cumulative Index to Nursing and Allied Health Literature) is an index of journal articles about nursing, allied health, biomedicine and healthcare. The search terms for CINAHIL were: AB fall AND AB (exercise OR train OR "tai chi" OR "physical activity») NOT TI ("nursing homes" OR Parkinson OR Alzheimer OR dementia OR stroke ). While applying the 'related words' option and restricting the search to randomised controlled trials and for the age groups: 'aged: 65+ years, aged, 80 and over'.
randomised controlled trial (Patricia Dargent-Molina, Khoury, and Cassou 2013; Patricia Dargent-Molina and Cassou 2008). Randomisation was stratified for study centre and body weight. The study protocol was approved by the Ile-de-France IV 'Committee for the Protection of Persons' (CPP) (ref 2007/29). It is registered with the CNIL ('Commission nationale de l'informatique et des libertés': French data protection authority) under the number 907198. It is also registered on ClinicalTrials. gov under the number: NCT00545350.
Persuading faculty members to take the time to sort through their works and self--archive those that are not bound by rights restrictions is a challenge. Standard installations of popular IR software, including DSpace, Digital Commons, and ePrints, do little to help facilitate easy and efficient IR deposits by faculty. As Dorothea Salo writes in a widely cited critique of IRs managed by academic libraries, the "'build it and they will come' proposition has been decisively wrong. "  2  A major issue she points out is that repositories were predicated on the "assumption that faculty would deposit, describe, and manage their own material. " 3 Seven years after the publication of her article, a vast majority of the more than 2,600 repositories currently operating around the world still function in this way and struggle to attract widespread faculty support.
4 To deposit works into these systems, faculty are often required to fill out an online form to describe and upload each work individually. This can be a laborious process that includes deciphering lengthy copyright agreements, filling out an array of metadata fields, and ensuring file formats or file sizes that are compatible with the constraints of the software. In August of 2014, MacEwan University Library in Edmonton, Alberta, launched an IR, Research Online at MacEwan (RO@M; http://roam. macewan. ca). Our hope was that RO@M's simple user interface and straightforward submission process would help to bolster faculty contributions. The site was built using Islandora, an open--source software framework that offered the project developers substantial flexibility in appearance and functionality.
Defining what we mean by a "microinteraction" is important when translating Saffer's theory to a library environment. He describes a microinteraction as "a tiny piece of functionality that only does one thing. every time you change a setting, sync your data or devices, set an alarm, pick a password, turn on an appliance, log in, set a status message, or favorite or Like something, you are engaging with a microinteraction. "  15 In libraries, many microinteractions are built around common user tasks such as booking a group--use room, placing a hold on an item, registering for an event, rating a book, or conducting a search in a discovery tool. A single piece of interactive library technology may have any number of discrete microinteractions, and often are part of a larger ecosystem of connected processes.
Methods and results : Leaf blades and petioles from 36 vineyards of 'red Grenache' (Vitis vinifera L. ) grafted on Richter 110 were collected and analyzed at flowering and veraison between 1992 and 2008. Using the compiled data bank, nutritional references for ten elements (N, P, K, Ca, Mg, Fe, Mn, Zn, Cu and B were calculated. Optimal values were those around the central data (µ ± 0. 25σ), while excessive and deficient values were those beyond the tails of the distribution (µ ± 0. 84σ). Percentile calculation was performed when transformations to normal distributions became unlikely.
, 1993; Lucena, 1997). This method quantifies the difference between a single nutrient concentration and its reference value, offering the advantage of ranking the order of requirements or order of limitation from the most negative to the highest positive nutrient index  (Montañés et al. , 1993). DOP indexes help us to determine which nutrients need to be included in a fertilization program  (Montañés et al. , 1993; Monge et al. , 1995). Furthermore, the sum of the absolute value of the different DOP indexes (∑│DOP i │) is a general index which represents the complete nutritional balance of the plant and indicates the importance or severity of an anomalous situation. However, the DOP method is not widely used mainly due to the lack of useful references for many crops  (Lucena, 1997). A large data bank of leaf analysis gathered over a long period of time is necessary to establish adequate and representative references with the objective of monitoring the nutritional status of a vineyard within the environmental and cultural factors of a particular area  (Sumner, 1978 ; Failla et al.
, 1993b ; Lucena, 1997 ; García-Escudero et al. , 2013). Large data banks are often used to define desirable ranges for leaf analysis interpretation  (Sumner, 1978 ; Lucena, 1997 ; García-Escudero et al. , 2013)  through statistical operations that explain the variability of nutrient concentrations inside the population  (Sumner, 1978). As a result, different sufficiency ranges have been published for different regions and variety-rootstock combinations. Failla et al. (1993a)  proposed one common sufficiency range using a dataset which contains data from thirteen varieties grafted on ten different rootstocks, grown at four locations in northern Italy on different soil types. Failla et al. (1993b)  proposed reference values for several cultivars and regions in north-central Italy. Ciesielska et al.
(2013)  proposed reference values for 'Tempranillo' in the Rioja AOC of Spain. In spite of the regional character of all these references, they are widely used for nutritional diagnosis around the world, even for different varieties. The accuracy of the ranges obtained improves when the number of foliar analysis in the dataset increases and when variation sources such as variety and rootstock combinations, seasonal weather conditions, soil types and cultural practices  (Robinson, 2005)  decrease. These sources of variation in nutritional status often generate wide reference ranges  (Sumner, 1978). Therefore, the most accurate reference ranges are achieved at a local scale  (Failla et al. , 1995 ; Robinson, 2005). Furthermore, many authors even proposed a yearly adjustment of the references to consider the impact of seasonal weather conditions over the years  (Failla et al.
Sampling area and establishment of the data bank A data bank of blade and petiole analysis was compiled over seventeen years  (1992) (1993) (1994) (1995) (1996) (1997) (1998) (1999) (2000) (2001) (2002) (2003) (2004) (2005) (2006) (2007) (2008)  in the north-eastern area of Spain within the Rioja AOC  (1º 40' 55'' to 2º 54' 46'' W -42º 4' 24'' to 42º 38' 15'' N). A total of thirty-six representative fully productive vineyards (more than 5 years old) of Vitis vinifera L. cv. red Grenache (Garnacha tinta, Grenache noir) grafted on Richter 110 were selected to create a representative data bank in order to obtain reference levels for the whole region. The data bank included different descriptive parameters of each vineyard : (i) plot characteristics (year of planting, geographic coordinates, altitude, percent slope, chemical soil analysis), (ii) vineyard design (spacing, planting density, row orientation, training system), (iii) mineral nutrient concentration in leaf tissues (blade or petiole) and sampling time (flowering or veraison), (iv) plant material (variety, rootstock), (v) cultural practices (vineyard training, fertilization, hydric regime, soil management), (vi) yield, and (vii) environmental factors (pests, diseases, climatic incidents and physiological alterations).