dataesr/scientific-paragraphs-categorization huggingface dataset:
Robustness was evaluated by a variation of ±10% of the optimized reaction volume and the DNA template. The optimized hybridization temperature was also modified by ±2˚C. To evaluate the transferability of the test, the assay was performed on another real-time platform, i. e. a LightCycler 480 Real-Time PCR system (ROCHE), and using the EUROGENTEC MasterMix NO ROX with the optimized conditions. Normality distribution of the data was verified by the Shapiro-Wilk test and by Q-Q plots. Data were analyzed either by Student's t-test or a Mann-Whitney-Wilcoxon test to check for differences in the parameters.
Design and preliminary evaluation of real time PCR primers and probe Thirty-four new sequences of the putative virulence gene were obtained during this study. All the sequences were deposited in GenBank with accessions numbers KX463694-KX463727 (S1 Table ). Alignment of sequences allowed the design of the primers/probe in the FWB-TR4 test (Table  1 ) to amplify a 180-bp region when used in PCR with target DNA. The in silico analytical specificity of FWB-TR4 could only be confirmed for VCG 01213/16 because sequences from VCG 0121 for this gene were absent from GenBank. The DNA regions targeted by the FWB-TR4 primers/probe were all 100% conserved within all the VCG 01213/16 isolates included in this work. However, the TR4-R primer shared 100% identity with the orthologous region in F. oxysporum f.
Under our conditions, the SYBR-GREEN PCR test developed by Lin et al. [26] , cross-reacted with DNA from two isolates of Foc race 1 and one strain of F. oxysporum f. sp. canariensis. A plausible explanation for this is that some isolates may be classified as Foc STR4 under subtropical conditions (where they can affect Cavendish banana), but as Foc race 1 in tropical areas, where they are unable to affect Cavendish banana  [10]. The cross-reaction with F. oxysporum f. sp. canariensis is more difficult to explain, as no sequences for this gene and for this species are available in any public database. The Foc4 0422F2/R2/P2 probebased test, described as a Foc race 4 detection tool by Yang et al. [29] , was found to be similar to FWB-TR4 in terms of specificity (both tests target VCGs 01213/16 and 0121) and sensitivity, when compared to the conventional PCR tests.
Evaluation approach The safety of caffeine from all sources was previously evaluated by the SCF in 1999 and 2003 (see Appendix H). More recently, an extensive evaluation of caffeine from all major sources was undertaken by the NDA Panel  (EFSA NDA Panel, 2015). Therefore, the CEF Panel considered it inappropriate to evaluate caffeine through the Procedure for the evaluation of chemically defined flavouring substances (see Appendix A) and instead chose to build on the NDA opinion for the revised evaluation of caffeine. Like for caffeine, the Panel decided not to evaluate theobromine through the Procedure, but to base its assessment on the fact that theobromine is a major metabolite of caffeine. Thus, the information available on the safety of caffeine in the NDA opinion could also be used for the safety assessment of this substance, for which only limited toxicity data in humans are available.
Methodology Dietary exposure to caffeine and theobromine from their use as chemically defined flavouring substances was estimated by combining food consumption data available within the EFSA Comprehensive European Food Consumption Database (hereafter Comprehensive Database)  4  (EFSA, 2011a) with the maximum permitted levels and/or reported use levels submitted to EFSA by the flavour industry, as appropriate. In this assessment, a brand loyalty model was chosen. In this model, it is assumed that a consumer is exposed on a long-term basis to a specific category of food, containing the flavouring substance of interest at the maximum use/permitted level. For both caffeine and theobromine, it was decided that this category of food will be the one resulting in the highest potential dietary exposure.
For the remaining categories, normal use levels were applied. This is in line with the added portions exposure technique (APET) calculations as developed in the guidelines for flavourings (EFSA CEF  Panel, 2010). Dietary exposure to caffeine from all non-flavouring sources (i. e. natural sources, stimulant use) was estimated by combining food consumption data available within the Comprehensive Database (see  Section 2. 4. 3)  with occurrence data from the literature, as used by the NDA Panel in their assessment  (EFSA NDA Panel, 2015). For theobromine, data reported in the literature was used (Appendix C, Table  C. 4). For the systemic exposure to theobromine resulting from caffeine intake, a factor of 0. 11 (see  Section 2. 4. 4. 2. c ) was applied, based on the metabolic conversion of caffeine into theobromine.
Caffeine and theobromine exposure estimates were calculated for each individual in the Comprehensive Database. Only surveys with collected data for at least 2 days were used. For each individual, exposure from all identified food groups was summed up over the entire survey period and subsequently divided by the number of survey days to derive average daily intakes. Finally, the so derived estimates were normalised for individual body weight (bw), resulting in an individual average daily exposure per kg bw for the survey period (absolute intake values in mg of flavouring substance per day are also provided in Appendix D, Tables D. 1 and D. 2). High-level exposure was calculated for only those population groups where the sample size was sufficiently large to allow calculation of the 95th percentile  (EFSA, 2011b).
EFSA Comprehensive European food consumption database 4 Since 2010, the Comprehensive Database has been populated with national data on food consumption at a detailed level. Competent authorities in the European countries provide EFSA with data on the level of food consumption by the individual consumer from the most recent national dietary survey in their country (cf. Guidance of EFSA on the 'Use of the EFSA Comprehensive European Food Consumption Database in Exposure Assessment')  (EFSA, 2011a). New consumption surveys 5  recently added in the Comprehensive database were also taken into account in this assessment (see  Appendix B, Table B. 1). The food consumption data gathered by EFSA were collected by different methodologies and thus direct country-to-country comparisons should be interpreted with caution.
Depending on the food category and the level of detail used for exposure calculations, uncertainties could be introduced owing to possible subjects' underreporting and/or misreporting of the consumption amounts. Nevertheless, the EFSA Comprehensive Database represents the best available source of food consumption data across Europe at present. Food consumption data from the following population groups: toddlers, children, adolescents, adults and the elderly were used for the exposure assessment. For the present assessment, food consumption data were available from 41 different dietary surveys carried out in 23 European countries (Table  4 ). Consumption records were coded according to the FoodEx classification system (EFSA, 2011b). For the purposes of the present assessment, nomenclature from the FoodEx classification system was linked to the Food Categorisation System (FCS) as presented in Annex III of Reg.
(EC) 1565/2000 (see Appendix C, Table  C. 3). Use and use levels were provided to EFSA by the flavour industry (Flavour Industry, 2010) and are detailed below (see Table  5  and Appendix C, Table  C. 2). Use and use levels were provided for five categories; however, only four food categories were included in the exposure assessment. The use of caffeine in the food category alcoholic beverages is not authorised and was therefore not taken into account in the present assessment. This may result in an underestimation of the exposure. The matching food categories were selected from the EFSA Comprehensive Database, at the most detailed level possible (up to FoodEx Level 4) (EFSA, 2011b) (see Appendix C, Table  C. 3). In order to take brand loyalty into account, it was assumed that a consumer is exposed, on a longterm basis, to caffeine present at the maximum reported use level in the food category resulting in the highest potential dietary exposure (i.
b) Natural and non-flavouring caffeine concentrations in food and beverages For the purposes of assessing intake from all sources, additional data on non-flavour use (e. g. stimulant use) and natural occurrence of caffeine was used. For caffeine, this datataken from the literatureis the same as used by the NDA Panel in their assessment of caffeine (EFSA NDA Panel, 2015) (see Table  6 ). The concentration data reported by the NDA Panel for the above four food groups was used to derive exposure estimates from natural and non-flavouring sources. The use of caffeine in energy drinks, in excess of MPLs for flavouring use 6 , is permitted for purposes other than imparting flavour. For these high use levels, specific labelling requirements are included in the legislation. 7 Therefore, caffeine from energy drinks was included in the exposure assessment from all sources, which was reported in excess of the applicable MPL for flavouring use, in this assessment scenario, but it was not included in the exposure assessment for use as a flavouring substance.
Caffeine For the safety assessment of caffeine a very broad human database is available, which eliminates the need for animal data. The (clinical) pharmacology of caffeine has been extensively studied. Its favourable central nervous system (CNS) effects (see e. g. (Fredholm et al. , 1999; Fredholm, 2011; Winston et al. , 2005)  for reviews) are the reason for its wide consumption in e. g. coffee and 'energy drinks'. Major effects are CNS stimulation, diuresis, stimulation of cardiac muscle and relaxation of smooth muscle. Caffeine is registered as a medicine for various indications, including treatment of apnoea in prematurely born babies  (EMEA, 2009; EMA 2015). The main mechanism of action of caffeine is antagonism of the adenosine A 1 and A 2 receptors; at increased dose levels it inhibits phosphodiesterases.
Carcinogenicity studies IARC evaluated the carcinogenic properties of caffeine and theobromine in 1991. For caffeine, five studies in rats were available of which two were negative and the other three were found to be inadequate for evaluation; the mouse studies were also inadequate. The available epidemiological data did not show correlation with any tumour. IARC therefore classified caffeine in Group 3: 'not classifiable as to its carcinogenicity to humans'  (IARC, 1991). Many epidemiological investigations on associations between coffee and various cancer sites since then have been published; a meta-analysis from 2011 of these data concludes that there is no association; if anything, the analysis suggests that coffee may reduce the total cancer incidence  (Yu et al. , 2011). The latter is also mechanistically discussed by  Beaudoin and Graham (2011).
Earlier, IARC had classified 'coffee' as 2B  (IARC, 1991) , based on a signal for bladder cancer, while caffeine as pure compound was in group 3. The majority of high-quality studies that have subsequently been published, however, do not show consistent evidence that coffee consumption is associated with bladder cancer. Very recently, IARC re-evaluated 'drinking coffee' as to its carcinogenicity. They concluded that 'overall coffee drinking was evaluated as inclassifiable (group 3) as to its carcinogenicity to humans' based on the extensive epidemiological database available as well as on animal studies  (IARC, 2016). IARC classified theobromine in Group 3: 'not classifiable as to its carcinogenicity to humans' because of lack of data  (IARC, 1991). The structurally related theophylline was evaluated in an NTP toxicology and carcinogenesis study  (NTP, 1998).
Cola beverages were found to be by far the main contributor to the exposure to caffeine used as a chemically defined flavouring substance (Flavour Industry, 2010). Like for caffeine, the Panel decided to not evaluate theobromine through the Procedure but to base its assessment on the fact that theobromine is a major metabolite of caffeine. Thus, the information available on the safety of caffeine in the NDA opinion could also be used for the safety assessment of theobromine. Unlike caffeine, having a broad human database of toxicity studies, no specific toxicological information on the safety of long-term theobromine exposure in humans is available. For the evaluation of theobromine, the Panel decided not to focus on the outcome of the animal studies available for this substance, but to base its assessment on the human data on caffeine.
Use and exposure The two candidate flavouring substances have been reported to occur naturally in foods such as coffee, chocolate, tea and cocoa beans as well as in some other plants such as guarana seeds, mate leaves and yoco bark. Dietary exposure to caffeine and theobromine from their use as chemically defined flavouring substances was estimated by combining food consumption data available within the EFSA Comprehensive European Food Consumption Database 4 with the MPLs and/or reported use levels submitted to EFSA by the flavour industry. In this assessment, a brand loyalty model was chosen. In this model, it was assumed that a consumer is exposed on a long-term basis to a specific category of food, containing the flavouring substance of interest at the maximum use/permitted level. For both caffeine and theobromine, it was decided that this category of food will be the one resulting in the highest potential dietary exposure.
In line with the outcome of the NDA Panel, the CEF Panel decided to apply these levels of no safety concern, for the evaluation of caffeine when used as a chemically defined flavouring substance. Unlike caffeine, having a broad database of human toxicity studies, no specific toxicological information on the safety of long-term exposure to theobromine in humans is available. For the evaluation of theobromine, the Panel decided not to focus on the outcome of the animal studies available for this substance, but to base its assessment on the human data on caffeine. To derive a reference dose for theobromine from the caffeine data, the Panel used the results of pharmacokinetic studies on caffeine and its metabolites indicating that approximately 11% of the oral intake of caffeine is converted to theobromine.
For each of these compounds and each volunteer, the pharmacokinetics based on their plasma levels were determined  (Lelo et al. , 1986a). Subsequently, during steady state oral administration of caffeine the partial clearances of each metabolic route in each volunteer were determined based again on plasma pharmacokinetic data. The fractional conversion data are therefore based on the initial demethylation step of caffeine metabolism, and are not influenced by the fact that some further metabolites may be derived from the same precursor (e. g. 7-MX may be derived from both theobromine and paraxanthine). Moreover, eventual deficits in urinary excretion of the metabolites do not play a role. Another study found that paraxanthine accounted for 63 AE 13% of the dimethylxanthines in plasma, theobromine 27 AE 15% and theophylline 10 AE 2.
FL-no Name Status in the FLAVIS database, May 2008 16. 027 Thiamine hydrochloride FGE. 76 -Adopted EFSA consideration of JECFA evaluated substances 16. 032 Theobromine FGE. 49 -FL-no: FLAVIS number; FLAVIS: Flavour Information System; FGE: Flavouring Group Evaluation; JECFA: The Joint FAO/WHO Expert Committee on Food Additives; ADI: acceptable daily intake; bw: body weight; SCF: Scientific Committee on Food.
1 ) 1 EFFA (European Flavour and Fragrance Association), 2002. Letter from EFFA to Dr. Joern Gry, Danish Veterinary and Food Administration. Dated 31 October 2002. Re. : Second group of questions. FLAVIS/8. 26. 2) EFFA (European Flavour and Fragrance Association), 2004. Intake -Collection and collation of usage data for flavouring substances. Letter from Dan Dils, EFFA to Torben Hallas-Møller, CAS Chemical Abstract Service CEF EFSA Panel on Food Contact Materials, Enzymes, Flavourings and Processing Aids CNS central nervous system CoE Council of Europe CONTAM EFSA Panel on Contaminants in the Food Chain CYP cytochrome EFFA European Flavour and Fragrance Association FAO Food and Agriculture Organization of the United Nations FCS Food Categorisation System FEMA Flavor and Extract Manufacturers Association FGE Flavouring Group Evaluation FLAVIS (FL) Flavour Information System (database) GLP Good Laboratory Practice HDL high-density lipoprotein IARC International Agency for Research on Cancer ID identity IOFI International Organization of the Flavour Industry IR infrared spectroscopy JECFA The Joint FAO/WHO Expert Committee on Food Additives LDL low-density lipoprotein MPL maximum permitted level MSDI Maximised Survey-derived Daily Intake NDA EFSA Panel on Dietetic Products, Nutrition and Allergies NOAEL no observed adverse effect level OECD Organization for Economic Co-operation and Development SCE sister chromatid exchange SCF Scientific Committee on Food WHO World Health Organization EFSA.
Model Model  period 1966-1975 1981-1990 1991-2000 2001-2010  MPI-ESM 10 10 10 10 REMO-ERA 1 1 1 1 R E M O -W 3 3 3 3 R E M O -H 3 3 3 3 REMO-O1 3 3 3 3 REMO-O2 3 3 3 3 WRF 2 2 2 2 CCLM-ERA 1 1 1 1 CCLM 3 3 3 3 are driven by initialized coupled global climate model simulations from the German decadal prediction system. First, RCM experiments have been realized which are nested in reanalysis data in order to assess the models' ability to reproduce interannual to decadal climate variability under more or less realistic lateral and oceanic boundary conditions. One set of experiments is carried out with REMO version 2009  (Jacob, 2001 , REMO-ERA in Table  1 ) and one with the nonhydrostatic RCM COSMO-CLM  (Rockel et al. , 2008 ; CCLM-ERA in Table  1 ) which has been applied and evaluated in CORDEX-Africa configuration  (Panitz et al.
Gaetani and Mohino, 2013). On this basis a weighted mean skill score for each MPI-ESM ensemble member is determined in order to achieve a rating into better and worse hindcasts of observed SST variability. (3) The three-member ensemble for the dynamical downscaling comprises the best, the worst and an intermediate MPI-ESM decadal hindcast experiment for each decade. For WRF, only the best and worst simulations are selected. For the validation of simulated WAM rainfall and the assessment of its decadal forecast potential three commonly used gridded observational data sets are considered, CRU  (Mitchell and Jones, 2005, updated) , GPCC  (Rudolf, 1995, updated)  and WMMA  (Willmott and Matsuura, 2001, updated). All three data sets are available at 0. 5°resolution and cover the full range of considered simulation periods.
When comparing regional mean time series of precipitation, all observational data sets and the MPI-ESM have been interpolated to the common resolution of the RCMs. The skill of the decadal predictions with MPI-ESM and various RCMs is evaluated by means of two standard skill scores: the Pearson correlation coefficient  (Wilks, 2006)  and the mean squared skill score (MSSS,  Goddard et al. , 2013). While the former only measures the phase relationship between time series, the MSSS also depends on the ability of the prediction system to reproduce the observed variance. While  Hawkins et al. (2014)  argue that biases in decadal predictions should experience more scientific attention in order to improve the prediction systems, we put more stress upon the correlation coefficient because it has been demonstrated that the bias of decadal predictions can reasonably be reduced via statistical post-processing  (Kharin et al.
Acknowledgements We thank the  Max-Planck Institute for Meteorology , the  ECMWF , the  IIASA , the  Joint Research Centre , the  FAO, OpenStreetMaps , the  University of Delaware , the  NASA-GSFC , the  Climatic Research Unit  and the  ESA  for providing the MPI-ESM decadal predictions, the  ERA40 ,  ERA-Interim  and  ORAS4  reanalyses, the WATCH-WFDEI data set, the GLC2000 land use data set, the  FAO statistical data sets , the street data set, the Willmott-Matsuura data set, the GPCP data sets, the  CRU data set  and the  ESA CCI  soil moisture data set, respectively. This work was carried out in the framework of the  German MiKlip  project and supported by the  German Minister of Education and Research (BMBF)  under grants No. 01LP1129A -F. We thank three anonymous reviewers for their valuable comments which helped to improve the quality and readability of the paper.
Cellular Uptake and Interaction with Luciferase-Luciferin Assay The uptake and luciferase-luciferin assays were performed using the IVIS Spectrum system, which allows simultaneous measurement of both luminescence and fluorescence. The excitation and emission filters were selected experimentally to measure the fluorescence of PTMTC and exclude autofluorescence background of the cells itself. The experiment showed that PTMTC was not absorbed by cells and its presence had no impact on the fluorescence intensity produced by oxidation of luciferin in luciferase expressing LNCaP cells (data not shown).
CALIOP Dataset. The CALIOP aboard CALIPSO provides the vertical profiles of elastic backscatter from a near nadir-viewing geometry. Due to the initial laser beam diameter and its divergence, the footprint diameter is about 70 m and can provide the vertical observations of aerosol and cloud at an interval of 333 m resolution in the direction along the CALIOP track  [28]  during both day and night phases of the orbit. CALIPSO belongs to the afternoon (A-train) constellation of satellites with a 705 km sun-synchronous orbit. The A-train crosses the equator each afternoon at around 1:30 p. m. local time with a 16-day repeat cycle. CALIOP performs measurements at the two wavelengths of 532 nm and 1064 nm with an energy of 110 mJ. The 532 nm band has two polarized channels, including horizontal and perpendicular directions  [29].
Ground-Based Lidar Dataset. Because the space-borne Lidar provides the observations of aerosol from space by means of laser footprint, thus it has a limited spatial coverage on the earth's surface. Therefore, it is a little difficult to validate the space-borne Lidar measurements from the spatial and temporal (especially spatial) synchronous observations by ground-based Lidar. The data used in this study is acquired by the ground-based Lidar in a site in Lille, north of France. This ground-based Lidar belongs to the Laboratoire d'Optique Atmospherique (LOA). Figure  1  shows an example of the position relation between the CALIOP footprints and Lidar site (50. 6 ∘ N, 3. 1 ∘ E). The average distance between CALIOP footprints and Lille Lidar site is around 15 km. The proximity of CALIOP footprint from the ground-based station makes of Lille a location of particular interest for comparison exercises.
Indeed, in most of the similar studies, this distance ranges between 30 and 50 km (e. g. ,  [27] ). The Lidar at Lille site is a monoaxial Cimel Micropulsed Lidar (CAML CE370) that provides attenuated backscatter profiles at 532 nm up to a height of 30 km. The profiles are available with a time resolution of 1 s and a vertical resolution of 15 m. The Lidar was set up in 2007 and has been running continuously since then. The use of the 2007-2015 dataset allows maximizing the number of comparisons with CALIOP. The estimation method of PBLH was described in Section 3. 2.