dataesr/scientific-paragraphs-categorization huggingface dataset:
Methods Ethics statement: This was a literature-based study; therefore, neither approval by the institutional review board nor informed consent was required. Study design: This study was a descriptive analysis of the literature focusing on journals' policies. Data source/measurement: Target journals were selected from the SJR (2018 edition). The selection and searches of the journal homepages were done from June 1 to June 30, 2020. Three countries (Brazil, France, and South Korea) were selected. Out of the SJR journal list, only Web of Science Core Collection journals were selected. The target journals were from all research fields, including the natural sciences, social sciences, and arts and humanities. Data were downloaded. No print versions were considered, and the homepage of each target journal was searched to answer the above goals.
If there were terms such as "should, " "mandatory, " or "must, " it was classified as mandatory. Wiley's classification of data sharing policies includes four levels: "encourage, " "expect, " "mandates, " and "mandates with peer re-view of data"  [7]. In this study, "encourage" and "expect" were treated as optional policies, while "mandates" and "mandates with peer review of data" were treated as mandatory policies. Data repository sites were searched from the instructions to the authors or policies section. Description of the statements of data availability was searched in journal articles with the data sharing policies. Bias: There was no bias in selecting journals and finding the policies, statements, level of data sharing, or repository site. Study size: All target journals were included from the three countries; therefore, sample size is not an issue.
Results Target journals for analysis: There were 163 journals from Brazil. From France, 243 search results were returned, from which four books, five discontinued journals, and two trade journals were excluded, resulting in a total of 232 journals that were analyzed. From Korea, 170 journals were included after excluding one trade journal and one discontinued journal. The total number of target journals was 565 (Datasets 1-3). Data sharing policies and their levels: Data sharing policies were classified as mandatory, optional, or none. The number of journals with optional data sharing policies was 11 (6. 7%) in Brazil, 64 (27. 6%) in France, and 44 (25. 9%) in Korea. There was one journal with mandatory data sharing in Korea (Journal of Educational Evaluation for Health Professions) and none in Brazil and France (Fig.
Discussion Key results: Of 565 journals from Brazil, France, and Korea, 118 (20. 9%) had optional data sharing policies, and one had a mandatory data sharing policy. Of the journals with data sharing policies, actual statements of data availability in articles were only found in two journals from Korea. The repository site of one journal was Harvard Dataverse, while the other did not indicate a specific site. Twenty-one journals had adopted a clinical trial data sharing policy. Interpretation and suggestion: Data sharing policies still have not been adopted by a sufficient proportion of journals from these three countries. Whether to adopt a data sharing policy is the choice of the editor or publisher. Some editors are not interested in adopting a data sharing policy because they are worried about a possible decrease in the number of submissions and increased workload  [1].
is an example [9]. When authors deposit data to a repository, the data receive a DOI and the metadata are transferred to Crossref. The DOI maintains a continuous connection between the data and the  Example 3. All of the individual participant data collected are available from a data repository immediately after publication without an end date. The study protocol, statistical analysis plan, informed consent form, clinical study report, and analytic code are also available. Anyone can access the data, and the data can be used for any purpose. published article  [10]. If it is difficult to use a data repository site, it is also acceptable to describe data availability using phrasing such as "Data are available from the corresponding author with a reasonable request" or "Please contact the corresponding author for data availability.
The number of entries since 2019 with associated data and clinical trials and RCTs from the 21 journals with ICMJE clinical trial data sharing policies from PubMed (N=21) In the Journal of Educational Evaluation for Health Professions, the editorial office deposited data to the Harvard Dataverse, officially available at https://dataverse. harvard. edu/dataverse/jeehp. In the other journal, Integrative Medicine Research, the data may be deposited to any repository sites, or to the article site itself by authors themselves. This journal supported Mendeley Data.
In the first exercise, we focus on a sub-sample of roughly 200 chemical products that we argue offer very little ground for product differentiation, because they correspond to raw molecular substances. By comparing the level of price dispersion in this sample and in the rest of the dataset, we can provide some indicative elements regarding the role of product differentiation as a source of price discrepancies. In the sample of homogenous products, the mean coefficient of variation is about 10 percentage points lower than in the control group. The difference is significant, including when identified within firms selling homogenous and heterogeneous chemical products, controlling for unobserved heterogeneity across firms. Extrapolating these results beyond the chemical industry suggests about a quarter of the observed price dispersion is due to product differentiation within a firm.
Interestingly, firms at the top of the distribution of sales in their sector are especially good at charging new consumers high prices while suffering from relatively less pronounced downward price renegotiation. We thus offer some insights on the way superstar firms exert their market power. Literature review. In addition to the works cited above, this paper pertains to different strands of the literature. Deviations from the LOP are often associated with market segmentation and border effects. Engel and Rogers (1996)  document systematic deviations from the LOP using disaggregated consumer price indices across Canadian and US cities. Using similar data across European cities, the authors do not find evidence of price convergence after the introduction of the euro  (Engel and Rogers, 2004).
We exploit the cross-sectional richness in the analysis. On top of the identity of both firms involved in the export flow, transactions recorded in the dataset are characterized by a date, at the monthly frequency, a product category at the 8-digit level of the combined nomenclature, the value of the transaction, and the physical quantity being traded. 9 Although the data are exhaustive, small exporters are allowed to complete a simplified form that does not request information on the product category or the physical quantity exported. Because these variables are key in the analysis, we neglect this population of firms. Between 2001 and 2006, the simplified regime concerned exporters whose annual export turnover in the EU was below 100,000 euros. The declaration threshold was increased to 150,000 euros in 2007 and to 460,000 euros in 2011.
The value of the transaction, V alue sb(c)pt , is measured in euros and is fob. The analysis excludes transactions below 100 euros, because of rounding issues. The quantity, Quantity sb(c)pt is either measured in kilograms or in physical units for some specific product categories. Therefore, unit values are not necessarily comparable across products but they are within a product category, the focus of the analysis. 10 he high disaggregation of data, which enables us to compute unit values for each trade transaction, helps mitigate composition effects that have been argued to reduce the quality of unit values as a proxy for prices. Because unit values can still suffer from measurement issues when either the value or the quantity is misreported, we trim the data and remove price quotes that deviate from the median price set by the firm for this product over the considered year by more than 200%.
Section 5 discusses the extent to which product differentiation is likely to explain results in sections 3 and 4. Over 2002-2006, our dataset is composed of more than 37. 7 million observations involving 70,649 exporters, 1. 1 million importers located in 24 European countries, and 9,400 (harmonized) product categories. Table  1  provides detailed statistics over the structure of the dataset, by destination country. Note that the period encompasses the entry of 10 Eastern European countries into the EU and thus into the dataset. For this reason, we compute a number of statistics on a sample restricted to the 15 "old" members of the EU. 12 Likewise, EMU members are those that were already part of the euro-area in 2002. For each observation, we observe a transaction-specific price quote. We use the high dimensionality to condition the statistics regarding the variance of prices on a particular position in the network.
16  We further consider the possibility that firms choose to price uniformly within a market but not across destinations, which would be consistent with zone pricing  (Adams and Williams, 2019). 17 The prevalence of NUP within EMU countries is 15 We have also computed the same statistics based on the EMU less Belgium and Netherlands. Trade with these countries is somewhat biased by the presence of major trade ports in Anvers and Rotterdam. A substantial share of trade between the EU and the rest of the world indeed transits through these ports. In principle, these trade flows have been excluded from the dataset as we dropped trade flows that are reported to be exported to destinations outside of the EU but exit France through another EU country. However, a significant number of trade flows could still be intermediated by firms in these countries, in which case the flow is recorded as an intra-EU transaction.
To control for this heterogeneity, we again rely on randomization. Namely, we retrict the dataset to the 10% of firms that export to at least three partners in three different destinations. In this subsample, we randomize to recover three price quotes per destination and three price quotes in three different destinations. Based on this subsample, we can compute measures of price dispersion within and across destinations that are fully comparable within a firm, because they are based on the same number of price quotes, with the location of the partners being the only source of variation. The distributions recovered from the two samples are reported in Figure  5. Within a firm (×product×period), the dispersion of prices charged on three random partners located in a given destination is 22% lower that the corresponding statistics based on three random partners located in three different countries, on average.
Examples of homogenous products include Fluorine (CN8 28013010), Calcium (CN8 28051200), Sulphuric acid (CN8 28070010), Solid potassium hydroxide (CN8 28152010), Trichloroethylene (CN8 29032200), or Octan-2-ol (CN8 29051620). The complete list of these products is available in Table  11. 25 nce the products were identified, we merged the list with the customs data to select the subsample of export transactions for these particular homogenous products. This selection leaves us with 7,441 observations covering 276 product categories exported by 395 sellers.
Column (  1 ) is the analog of Figure  8. The coefficient of variation is explained by a dummy that is equal to 1 if the exported product is a homogenous chemical product, the control group being composed of the rest of the dataset. Price discrimination is 5. 6 percentage points lower in the selected sample. Because all homogenous products belong to the chemical industry, the difference in means may be entirely explained by composition effects across industries. Column (2) is thus restricted to products in the chemical and allied industries. This sample includes all homogenous products but also other chemical products such as pharmaceuticals, specialty chemicals, or any chemical substance that was not sufficiently homogenous to pass the selection process. In this sample as well, we find prices of homogenous products significantly less dispersed than more differentiated products, with a difference of 16 percentage points.
Methodology. The decomposition takes inspiration from the labor literature. Following  Abowd et al. (1999) , this literature has extensively used matched employeremployee data and high-dimensional fixed-effect estimators to identify the sources of the dispersion in wages observed in the data. Our dataset has the same bipartite graph structure, and we can thus rely on this methodology to decompose the observed variance of export prices. The estimated model takes the following form: ln p sb(c)pt = βX sb(c)pt + F E s + F E b(c) + e sb(c)pt (6) where X sb(c)pt is a set of control variables, F E s is a (time-invariant) fixed effect for seller s, F E b(c) is a (time-invariant) fixed effect for buyer b(c), and e sb(c)pt is a residual that captures the unexplained dispersion of prices within a seller-buyer match.
A Data Appendix This section provides additional information regarding the various variables used as controls in the analysis. A. 1 Variables constructed using the Customs data Count partners. Tables  4, 5 , and 6 use as control the number of partners in the firm's portfolio, which is also equal to the number of observations used to recover the corresponding coefficient of variation. This variable is also used in Table  10  to understand the dynamics of average prices, within a seller. Size. We use two measures of the "size" of trade relationships as controls in the analysis. Throughout the paper, the size of a trade relationship is measured as the value of exports recorded in the Customs database. In the raw data, the variable is available for each transaction involving a seller s, a buyer b(c) over a particular product p, and for a specific period t.
comments, as well as  Thibault Cezanne  for excellent research assistance. Mejean gratefully acknowledges support from a public grant overseen by the  French National Research Agency (ANR)  as part of the  "Investissements d'Avenir" program  ( Idex Grant  Agreement No. ANR-11-IDEX-0003-02 / Labex ECODEC  No. ANR-11-LABEX-0047  and  Equipex  reference:  ANR-10-EQPX-17 -Centre  d'accès sécurisé aux données -CASD) as well as the  European Research Council (ERC)  under the European Union's  Horizon 2020 research and innovation programme  (grant agreement No. 714597 ). The views expressed herein are those of the authors and do not necessarily reflect the views of the  National Bureau of Economic Research. NBER working papers are circulated for discussion and comment purposes. They have not been peer-for insightful comments, as well as  Thibault Cezanne  for excellent research assistance.
Mejean gratefully acknowledges support from a public grant overseen by the  French National Research Agency (ANR)  as part of the  "Investissements d'Avenir" program  ( Idex Grant  Agreement No. ANR-11-IDEX-0003-02 / Labex ECODEC  No. ANR-11-LABEX-0047  and  Equipex  reference:  ANR-10-EQPX-17 -Centre  d'accès sécurisé aux données -CASD) as well as the  European Research Council (ERC)  under the European Union's  Horizon 2020 research and innovation programme  (grant agreement No. 714597 ).
Oral and intravenous DMTs. Dimethyl fumarate (DMF) was assessed in a subgroup analysis of patients with high clinical or radiological activity in the DEFINE and CONFIRM trials. 26, 27 However, results were not compared to other DMTs in this analysis. Fingolimod has been compared to other DMTs and showed a greater effect on the annualized relapse rate (ARR) compared with interferon (IFN)-β1a in patients with high clinical or radiological activity. 30 owever, fingolimod might not be as effective as Mabs and its superiority over DMF is not clear. A propensity score-matching analysis assessed no evidence of disease activity (NEDA-3) at 2 years in two patient datasets after starting natalizumab, fingolimod or self-injectables: one study included patients with high clinical activity despite first-line DMTs and one included highly active, treatment-naïve patients.
36 hen comparing natalizumab and fingolimod, the proportion of patients with NEDA-3 was greater for natalizumab than fingolimod in the first dataset, whereas in the second, the difference did not reach statistical significance, probably due in part to the smaller size of that cohort. 36 systematic review and meta-analysis of highly active rMS and rapidly evolving severe MS explored the efficacy of fingolimod relative to DMF and natalizumab. 37 In the highly active relapsing-remitting multiple sclerosis (RRMS) population, a trend favoured fingolimod over DMF in reducing the ARR and confirmed disability progression. In the rapidly evolving severe MS population, patients on fingolimod had a non-statistically significant increase in the ARR and in confirmed disability progression compared to patients on natalizumab.
Introduction The discovery of a heavy scalar particle by ATLAS and CMS  [1, 2]  provided experimental confirmation of the Englert-Brout-Higgs mechanism  [3] [4] [5] [6] [7] [8] , which spontaneously breaks electroweak (EW) gauge symmetry and generates mass terms for the W and Z gauge bosons. In the Standard Model (SM) the fermion masses are generated via Yukawa interactions. The Yukawa couplings to third-generation fermions were determined by measurements of Higgs boson production and decays  [9] [10] [11] [12] [13] [14] [15] , and found to be in agreement with the expectations of the SM. However, there is currently no evidence of Higgs boson decays into first-or second-generation quarks or leptons. This Letter presents the first ATLAS searches for H → ee and for the lepton-flavour-violating decay H → eµ using the full Run 2 dataset of proton-proton (pp) collisions at a centre-of-mass energy of √ s = 13 TeV, with an integrated luminosity of 139 fb - 1.
The best-fit value of the branching fraction is (0. 0 ± 1. 7 (stat. ) ± 0. 6(syst. )) × 10 -4. The uncertainty is dominated by the statistical uncertainty in the data, while the largest systematic contribution is from the background modelling uncertainty. The observed (expected) upper limit on the branching fraction, computed using a modified frequentist CL s method  [95, 96] , at the 95% confidence level, is found to be 3. 6 × 10 -4 (3. 5 × 10 -4 ). This result is a significant improvement on the previous limit by CMS of 1. 9 × 10 -3 based on the Run 1 dataset  [16]. In the eµ channel, a similar fit is performed to the observed electron-muon mass spectra divided into 50 m eµ bins in each of the eight categories. The data and expectation for all categories summed together are shown in Figure  1.
No evidence of the decay H → eµ is observed, with a best-fit value of the branching fraction of (0. 4 ± 2. 9 (stat. ) ± 0. 3(syst. )) × 10 -5. The uncertainty is dominated by the statistical uncertainty in the data, while the largest systematic contribution is from the Higgs boson production cross-section uncertainty. The observed (expected) upper limit at the 95% confidence level is found to be 6. 2 × 10 -5 (5. 9 × 10 -5 ). This result is a significant improvement on the previous limit by CMS of 3. 5 × 10 -4 based on the Run 1 dataset  [17].
Conclusion Searches are performed for the Higgs boson decays H → ee and H → eµ using 139 fb -1 of data collected with the ATLAS detector in pp collisions at √ s =13 TeV at the LHC. No evidence of either decay is found and observed (expected) upper limits at the 95% confidence level on the branching fractions of 3. 6 × 10 -4 (3. 5 × 10 -4 ) for B(H → ee) and 6. 2 × 10 -5 (5. 9 × 10 -5 ) for B(H → eµ) are obtained for a Higgs boson with mass 125 GeV. These are the first such searches made by the ATLAS Collaboration and are considerable improvements on previous measurements. (Taiwan), RAL (UK) and BNL (USA), the Tier-2 facilities worldwide and large non-WLCG resource providers. Major contributors of computing resources are listed in Ref. [97].
They minimized the effect of the insertion on maximum lateness. Artigues et al. (2003)  present a polynomial insertion algorithm based on which they propose scheduling algorithms for the static resource-constrained project scheduling problem (RCPSP) and for rescheduling in a dynamic RCPSP setting with the objective of minimizing the resulting makespan. Özdamar and Alanya (2001)  examined software development projects and considered uncertainty in both task durations and in network topology, specifically start-to-start precedence relationships among activities. These network changes are mainly caused by the common use of database and program modules, and design problems might result from changes in precedence relations. Recently,  Vaagen et al. (2017)  investigated the complexity in planning engineer-to-order projects due to design uncertainty, which covered changes in specifications.
Results Compositional Characteristics. Our sampling strategy included all identifiable objects to capture the early Islamic glass assemblage in its entirety. Compositionally, the assemblage from Šaqunda encompasses a mix of natron-type and some soda-rich plant ash glasses, as well as high-lead samples (Fig. 1A ). The bulk of the assemblage (n = 48) adheres to the ancient natron glass recipe, and virtually all of these samples show elevated levels of transition metals, clearly indicating a significant contribution of recycled material (Dataset S1). The glasses nonetheless can be attributed to distinct natron-type glass groups, depending on the proportion of primary glasses in the recycled material (Fig. 1B ). One subset of natron glass has high titanium, zirconium, and manganese concentrations that are consistent with a glass type known as Foy 2.
2, a recycled variant of the Egyptian Foy 2 family  (22). Another subpopulation is closely related to Levantine glass that contains lower heavy element levels  (22, 23). Three samples stand out due to their high titanium and zirconium levels, indicative of an Egyptian provenance  (23). One of these samples is a silver-stained (luster) fragment with characteristics similar to Egypt 2 but with a lower lime concentration (10, 25) (Dataset S1; MIR 051). The overall group structure of the natron glasses demonstrates on the one hand extensive recycling of older glass groups and on the other hand the importation of early Islamic natron-type glasses from Egypt. However, this import appears to relate only to isolated, finished objects and not to the trade of raw glass en masse. In contrast, raw glass chunks indicative of bulk imports and regional secondary working have been recovered from numerous late antique and Visigothic Iberian sites  (11, 26).
Three of the six soda-rich plant ash glasses of the Šaqunda assemblage date to the eighth or early ninth century CE, making them the oldest plant ash glasses so far identified in al-Andalus. The plant ash glasses are highly variable in terms of both the plant ash component and the silica source (Fig. 1C ), severely limiting the historical and archaeological interpretation. However, what we can say is that the three early samples match contemporaneous Mesopotamian glasses, specifically glass from Samarra and/or al-Raqqa. This illustrates the medieval longdistance exchange of glass objects from Mesopotamia. The three 10th-century plant ash samples have very different compositional signatures, characterized by elevated silica-related elements such as alumina, titanium, and zirconium (Dataset S1), that are consistent with early Islamic plant ash glasses produced in the Iberian Peninsula  (27).