dataesr/scientific-paragraphs-categorization huggingface dataset:
Gel phantoms for temperature gradients Combined test samples designed to provide genuine temperature gradients, herein called phantoms, were generated as follows. An alkaline (pH 8. 2) gel sample containing 1 % agarose and 80 mM PCho was heated to about 90 °C and filled into a 5-mm NMR tube which was then put on ice. In addition, an alkaline gel sample containing 1 % agarose and 80 mM NAA was heated to about 90 °C and filled into a 10-mm NMR tube, which was then maintained at 60 °C in a water bath. Subsequently, the heated 10-mm tube was removed from the water bath, and the cooled 5-mm NMR tube was immediately inserted into the 10-mm tube, upon which the combined phantom was quickly lowered into a 10-mm NMR probe. Simultaneously, a series of 1 H NMR experiments was started by way of home-made AU programs (Bruker macros based on the C programming language; see Appendix in S1 Supplemental Materials 1).
The interconnections of amygdala and PRC, which are especially heavy as well as reciprocal, amygdala implementation of consolidation processes, and early intracranial recording findings consistent with meaningful amygdala representations, together suggest that amygdala likewise contributes meaningful and fine-grained representations for integration by PRC. These representations are hypothesized to concern intangible knowledge. Intangible knowledge is an important component of cognition (see later section: significance for social processing), but it has been little researched as evidenced by few entries in the Medline database. There is no accepted definition, so it is provisionally defined as non-physical or non-concrete features of stimuli, that ubiquitously and substantively modulate behavior, cognition, and emotion.
Qualitative study From June to November 2009, a qualitative study was carried out. The studied population was composed of patients who came to the day-hospital of Lucien Neuwirth Cancer Institut for their first chemotherapy treatment (June 2009). The aim of the study was to collect the needs of the patients in the course of treatment, these needs arising from their experience with the chemotherapy administered at the center. The secondary objectives were to identify the skills that the patients could put into practice and/or those they wished to acquire, for better management of their chemotherapy. Data collection was carried out by a sociologist. The usual sample size recommended for qualitative research aiming at identifying individuals' needs is around 30. 21  This sample size reduces the probability under 5% of missing one major need.
Analysis In order to carry out the qualitative analysis, anonymized interviews were recorded and transcribed into a synthetic transcript by the sociologist who led the interviews. The results were analyzed and compared, according to the groundwork suggested by Miles and Huberman. 23 A thematic analysis of the directed interviews was then made, using the themes from the interview grid. The totality of the data was coded. An analysis of the contents for each theme as well as a comparative analysis of the data were then carried out. Data saturation was searched for and validated through this process. For the quantitative analysis, we planned to include 100 patients in accordance with the recommendations of European Organisation for Research and Treatment of Cancer (EORTC). 24 EORTC developed guidelines for quality questionnaire development.
In those guidelines, for the psychometric validation of a questionnaire, EORTC recommended that "a few hundred patients" should be recruited. Considering that a part of our questionnaire had already been validated and that our primary objective was not the validation of the questionnaire but the search for representativeness, we calculated a conservative sample size based on expected precision: to obtain a CI of 95%, a precision at 10% for the most conservative proportion of an expected answer (50%), 96 patients are needed. 25 In order to take invalid questionnaires into account, we decided to recruit 100 patients. The statistical analysis was descriptive, the quantitative variables were expressed as a percentage, and missing data were reported. The study was approved by the ethics committee of Saint Etienne University Hospital on January 20, 2014 (No IRBN052014/CHUSTE).
Perhaps, non-existing needs were brought to the attention of the patients. Yet, for four of the six needs expressed in 2009, the proportions gathered remained the same as those in 2013. Correspondingly, the new needs resulting from the study carried out in 2014 had been mentioned by the patients during exploratory interviews, even if they had not been retained in the results of the qualitative study since they were marginal comments. Thus, they do not appear from nowhere. Moreover, for the quantitative study, we used a questionnaire which had been validated and which has therefore previously demonstrated reliable psychometric capacities. Another limitation of this study is the fact that the data were collected in a monocentric manner. Due to this fact, it is more difficult to validate the generalization of the results to the total population of patients under IV chemotherapy, especially since this cancer center has a long history of patient counseling and education.
igacproject. org/activities/TOAR). Initiated in 2014, TOAR's mission is to provide the research community with an up-to-date scientific assessment of the global distribution and trends in ozone from the surface to the tropopause. TOAR's primary goals are to: 1) Produce the first tropospheric ozone assessment report using all available surface ozone observations, the peerreviewed literature and new analyses and 2) Generate easily accessible, documented data on ozone exposure metrics at thousands of measurement sites around the world (urban and non-urban). Through the TOAR-Surface Ozone database (https://join. fz-juelich. de/), these ozone metrics are freely accessible for research on the global and regional-scale impact of ozone on human health, crop and ecosystem productivity and climate  (Schultz et al.
, 2017;  hereinafter referred to as TOAR-Surface Ozone Database). The assessment report is organized as series of peer-reviewed publications in Elementa: Science of the Anthropocene (this Special Feature), with this paper (hereinafter referred to as TOAR-Health) focusing on the global distribution and trends of ozone metrics relevant for human health. Ozone affects human health through its natural presence in the stratosphere where it absorbs harmful UV radiation that could otherwise reach the Earth's surface. However, at the Earth's surface ozone is an air pollutant, and inhalation of this powerful oxidant can impair the functioning of the human respiratory and cardiovascular systems through its reaction with the lining of the lung and other surfaces in the respiratory tract  (WHO 2005; US EPA 2013).
The goal of TOAR-Health is to present, for the first time, the global distribution and trends of ozone using all available surface ozone observations. The analysis relies on a variety of ozone metrics that are either used by air quality managers to inform and evaluate strategies to protect human health from the adverse effects of ozone, or are useful for epidemiologists who use the daily maximum 8-hour running mean ozone metric or the daily 1 hour maximum ozone metric to quantify the impact of ozone on human health (section 2). The selection of five health relevant ozone metrics are discussed in section 3. The TOAR measurement stations and their data availability used to calculate the ozone health metrics, their classification as urban and non-urban stations, their regional aggregation and associated population demographics are outlined in section 4.
Surface ozone and human health effects A summary of the different types of studies used to determine ozone-related health effects as well as recent risk estimates are provided in this section. These include observational-based toxicological and clinical or controlled human exposure studies and statistically-based epidemiological studies. Further discussion on exposure and dose definitions and health effect studies pertinent for a wide range of exposure metrics are provided in  Lefohn et al. (2017a;  hereinafter referred to as TOAR-Metrics). To facilitate comparison of published studies with the new analyses in TOAR-Health, based on the ozone metrics in the TOAR-Surface Ozone Database, we briefly describe the choice of ozone units reported in this paper. When referencing an observation in ambient air, TOAR follows World Meteorological Organization guidelines  (Galbally et al.
For simplicity the conversion between these units is often based on a fixed a temperature and pressure (See Table  S1  for this conversion). Above and in section 2, when units of ozone concentrations are quoted in units of µg m -3 , the corresponding mixing ratio is also quoted in units of ppb for simplicity using a 1:2 ratio on the basis that 1 ppb = 2 µg m -3 at a reference temperature of 20°C and standard pressure of 1013. 25 hPa. The air quality metrics in the TOAR-surface ozone database in relation to human health can be categorized as a) short-term exposure metrics based on high values of daily concentrations, e. g. the 4 th highest MDA8 ozone value in a year (4MDA8) b) short-term exposure metrics of the numbers of days in a year with MDA8 ozone greater than 70 ppb or other value e. g.
60 ppb (see examples in Figure  1 ), and c) short or long-term exposure metrics with a seasonal or annual averaging or summation period. All reported metric values meet a data capture criterion of >75% (TOAR-Surface Ozone Database). Often the warm season (April-September in the Northern Hemisphere and October-March in the Southern Hemisphere) is used mainly because some individual states within the US only report data during their "ozone season", and hence site coverage is lower outside of this period. The ozone season is selected because it is the part of the year with highest temperatures and strongest solar radiation and thus the time when photochemical reactions of ozone precursor gases are most likely to produce high ozone levels  (Rice, 2014). The full set of health metrics have been detailed in TOAR-Metrics, and are organised according to the range of the ozone distribution to which they correspond, specifically: high ozone concentrations, high and mid-level ozone concentrations and ozone concentrations from across the distribution.
Since these various health metrics are determined from different parts of the distribution of ozone concentrations, their spatial variation may be substantial. Similarly, conclusions about the extent to which various health-relevant ozone metrics have increased, decreased or not changed over time will also depend on the changes in the relative frequency of concentrations in different parts of the ozone concentration distribution that have occurred over the time period of interest (TOAR-Metrics). The features associated with different metrics are also evaluated in  Lefohn et al. (2017b). To reflect the breadth of different health-related indicators used globally, five metrics (four of which use MDA8 for representing daily ozone levels) have been selected from the TOAR database and are shown in Table  1  and outlined below:  1.
4MDA8: The 4 th highest MDA8 ozone value represents peak short-term exposure and is used in the US for determining compliance with the National Ambient Air Quality Standards for Ozone. The annual 4 th highest value falls in the range of the 98 th to 99 th percentile of the 365 values of the MDA8 per year. This metric is applied to data from the 6-month warm season only to augment the number of sites in the US for which this metric can be constructed. This is a reasonable approach since, in most cases, the 4MDA8 ozone value occurs within the warm season (TOAR-Metrics and TOAR-Surface Ozone Database). A unique exception is the occurrence of high wintertime ozone in rural snow-covered regions of the western US, associated with emissions from oil and natural gas extraction  (Oltmans et al. , 2014).
2. NDGT70: The number of days with MDA8 ozone greater than 70 ppb also represents peak shortterm exposure. The benchmark level of MDA8  While the first two metrics, 4MDA8 and NDGT70 reflect peak ozone levels, SOMO35 represents mid-high ozone levels summed annually, and 3MMDA1 and AVGMDA8 represent high ozone levels over a 3-6 month season. As noted above, the first three metrics are associated with regulatory standards in different world regions for the protection of human health to acute or short-term exposure to ozone. These five ozone metrics are calculated for all urban and non-urban ozone monitoring stations (section 4. 2) available in the TOAR database, as presentday averages for 2010-2014 (section 5), as well as trends between 2000-2014 (section 6).
Stations and time periods The TOAR database contains the world's largest collection of ozone metrics, calculated consistently from hourly ozone observations at all available surface monitoring sites around the globe. The data were contributed by national and regional ozone monitoring networks as well as by independent research programs. The data contributors and the methods for calculating the ozone metrics are described in TOAR-Surface Ozone Database. All data have undergone quality control and validation by the air quality agencies that collected the data (TOAR-Surface Ozone Database). For this analysis we utilize ozone metrics derived from over 4,800 monitoring sites worldwide (1,470 from North America, 1,935 from Europe, 1,239 from South, Southeast and East Asia, and 176 from other regions of the world).
1) cover the 5-year period of 2010-2014, with each station required to have hourly data from at least 3 years within this period. For the trend analysis in section 6, data from 2000 to 2014 were required, with no more than 2 years missing from either end of this period; longer trend periods were also considered. These constraints limit the number of stations available for trend analysis, but provide the necessary data for robust trend assessment. See the Supplemental Materials to TOAR-Surface Ozone Database for a full description of stations and the details of the data requirements.
TOAR station classification using global gridded metadata Historically, station locations have been classified by type, such as: urban, suburban, rural, remote, background, or baseline depending on the network. However, there are limitations associated with using these classifications on the global-scale, since different interpretations of these classifications are likely used by different agencies around the world. This will introduce inconsistencies in site type classifications across continental regions. Therefore, some harmonization is required to link health-related ozone metrics to a more consistent site type classification that can be applied to all stations in the global TOAR database. One key consideration for health-related ozone metrics is characterizing population exposure in urban or nonurban environments.
For the purposes of the overall TOAR assessment, all the TOAR stations were categorized as urban, rural or unclassified. This classification is based on the combined use of several high-resolution global gridded data sets to provide objective criteria for determining whether a station is considered urban (see TOAR-Surface Ozone Database) and is based on the year 2010. For the purposes of this study sites are classified as either urban or non-urban. Therefore, non-urban stations include all stations except those classified as urban i. e. all rural and unclassified stations. The high-resolution datasets used for the urban and non-urban classifications are:.
Human population (Socioeconomic Data and Applications Center; SEDAC/CIESIN 2015) Gridded Population of the World (GPW), v3 hereafter (GPWv3). This is a dataset of world population gridded data at ~5 km resolution. 2. NOAA night-time lights of the world at 0. 925 km resolution  (Elvidge et al. , 2014). The urban site classification was set with thresholds so that sites included would be robustly "urban" across the globe. For example, sites in North America, where the population density of urban areas is much lower than in Asia, needed to be included in the urban classification. Following a number of iterations, a global "urban" classification was achieved by means of the following criteria: These urban stations are representative of relatively dense urban environments and this classification excludes some sites that may be considered as urban by local or regional air quality managers.
For example, Perth, Australia is a city with 2 million inhabitants, but its large area results in population densities near the city's five ozone monitors that do not meet the threshold criteria for urban classification. For more details see TOAR-Surface Ozone Database. The number and percentage of urban stations aggregated for different continental regions is described in section 4. 3. Further independent classification of the sites based on these proxy data, in addition to tropospheric NO 2 column data at 0. 1° resolution from the OMI satellite instrument  (Krotkov et al. 2016) , was carried out using Ward's hierarchical cluster analysis  (Ward, 1963; Kaufman and Rousseeuw, 1990). This method produces six clusters that resemble the TOAR classifications (Supplemental Materials: Figures  S2  and S3 ).
Regional aggregation of stations and station population characteristics The global distribution of stations assigned to the continental region divisions used in the TOAR assessment is derived from the Task Force on Hemispheric Transport of Air pollution (TF-HTAP) phase II experiment regions (www. htap. org) and is depicted in Figure  3. These HTAP II regions were used for regional aggregations in sections 5 and 6. Gridded population data at ~5 km resolution were also assigned to each ozone station in the TOAR database and used to calculate an average regional human population density for the 15 TOAR regions shown in (East, South and Southeast Asia were combined into Asia; Central and South America were likewise combined into Latin America). The number of monitoring stations for 2010-2014 in each region as well as the number of monitors per 100 million people per region is given in Table  2.
g. Meng et al. 2012 ; US EPA 2013 for a discussion of the validity of this assumption). The number of stations in each country or state used in the analysis, as well as the percentage of the country/state population within 5 km of an urban or non-urban TOAR station (usually under 5% but up to 8% for urban stations) is shown in the Supplemental Materials (Figures  S4  and S5 ). However, because the monitored population of a state or country is estimated over a small geographical area these results may not be representative of the total population of that European country or US state. Present day (2010-2014 average) and 2000-2014 trend data were used to estimate ozone levels in 2000. The percentage of the non-urban monitored population exposed to ozone levels >60 ppb for 25 or more days is generally either similar to, or greater than the corresponding percentage of the urban monitored population in both 2000 and 2010-2014.
To be able to include more sites with shorter data sets, a decadal change from 2005 to 2014 (inclusive, and with at least 7 years of data) was also calculated. The terminology "change" is used to reflect the difficulty of annual trend detection with less than a decade of data (i. e. 7-10 data points) e. g. Fischer et al. (2011). In this section, only trends for the period 2000 to 2014 are shown. However, a full set of figures including the longer and shorter periods is included in the Supplemental Materials (Figures  S7-S9 ). Trend analysis is based on the non-parametric methods described in detail by TOAR-Metrics, in which a Mann-Kendall test is used to determine the statistical significance (p-values) associated with each trend calculation. The Theil-Sen estimator is applied to calculate a quantitative trend estimate for the five ozone metrics for all sites.
These statistical methods were applied uniformly across all ozone time series in the TOAR-Surface Ozone Database, as described in TOAR-Surface Ozone Database. For the TOAR assessment the following terminology is used when describing trend results: a trend associated with a p-value ≤ 0. 05 is a statistically significant trend; a trend with a p-value of 0. 05-0. 1 is referred to as indicative of a trend; a trend value with p-value = 0. 1-0. 34 is described as having a weak indication of change; and a trend with a p-value > 0. 34 is referred to as weak or no change. These bounds on p-values are based on analysis of the regional average daytime ozone trend across eastern North America by  Chang et al. (2017)  using a generalized additive mixed model (GAMM). They found that trends at individual sites with p-values up to 0.
Furthermore, it is the lower end of the ozone distribution that is most strongly affected by this process, hence other drivers, especially regional to local meteorology may influence these trend results. In particular, interannual variability in meteorology may well be the cause of the large number of insignificant trend results found in all regions and globally (section 6. 1), and noted in a European context by  Colette et al. (2016). In addition, despite the extensive a Columns represent: No change, from not significant (NS) to increase, NS to decrease and vice versa) at the p = 0. 05 level. Also shown is the number of qualifying sites per region (N)). Each category is displayed as a % of total sites in the region. data quality assurance that went into the TOAR database, issues with changed calibration or operating procedures over time remain (TOAR-Surface Ozone Database).
Conclusions The goal of this paper, TOAR-Health, is to present the global distribution and trends of ozone using all available surface ozone observations and relying on ozone metrics that are relevant to human health. Using the TOAR-surface ozone database, global and regional present-day distributions and trends for the period 2000-2014 are analyzed for five health relevant ozone metrics. For analyses of present-day distributions (averaged for 2010-2014) data from 4,801 global monitoring sites were utilized; whilst for trend analysis for 2000-2014 data from 2,600 sites were used. These ozone health metrics are derived based on of clinical and epidemiological studies that examine health outcomes associated with short-and long-term exposure of surface ozone that are typically based on daily maximum 8-hour running mean ozone (MDA8) mixing ratios.
The five metrics are: the 4 th highest MDA8 (4MDA8); the number of days per year with MDA8 > 70 ppb (NDGT70); annual Sum of Ozone Means Over 35 ppb (SOMO35); annual maximum of the 3 month running mean of daily 1-hour ozone (3MMDA1); and the warm season average MDA8 (AVGMDA8). The first three of the five metrics are also associated with regulatory standards to protect human health from short-term exposure to ozone. The 4MDA8 and NDGT70 metrics reflect peak ozone levels. SOMO35 represents mid-high ozone values summed over the whole year. The last two metrics (3MMDA1/AVGMDA8) are averaged annually/seasonally to provide a perspective on long-term exposure. These health metrics are examined for two globally applicable objective site categories: urban and non-urban, that are determined based on the use of gridded metadata associated with urban characteristics: population and night-time lights.