dataesr/scientific-paragraphs-categorization huggingface dataset:
326 • Integrating artificial intelligence into health care through data access regulations pertaining to health information, considered to be substantially similar. 51 IPEDA and its provincial equivalents apply to private organizations which collect, use or disclose personal data for commercial purposes. In that sense, their scope of application is more inclusive than HIPAA's, as they encompass any processing of personal data performed by a company (art. 2, PIPEDA). Under the previous Directive on data protection, PIPEDA was considered adequate to protect personal data covered by EU law. 52 Adequacy is especially important to guarantee data flows from the EU to Canadian companies. Article 46. 5 of the GDPR allows PIPEDA to benefit from this beneficial status until the next evaluation. The lack of specific protection mechanisms, including regarding sensitive data, could yet impede PIPEDA from maintaining adequacy.
Without such status, each international personal data transfer is only allowed by exception. Such exceptions include when the data subject has explicitly consented, after being informed of the absence of an adequacy decision and the risks associated (art. 49. 1. a, GDPR). Other possibilities include when a transfer is necessary for the performance of a contract with the data subject, or for 'important reasons of public interest' (art. 49. 1. b and d). Such requirements can be impractical, especially in scenarios where large amounts of data are needed to develop a DL system, for example. PIPEDA has yet to be updated to take into consideration the implications of AI on privacy and data protection, especially in case of sensitive and health-related information. In an op-ed following the revelations of illicit uses by Facebook of personal data for political purposes, the Privacy Commissioner of Canada warned against the limitations in Canada's legislation on privacy and urged for the revision of PIPEDA.
53 In line with the recommendations formulated by the Privacy Commissioner, the Committee on Access to Information, Privacy and Ethics of the House of Commons published a report with comparable reform propositions for PIPEDA. The Committee emphasizes on the necessity to adapt Canada's legislation in order to maintain adequacy status with European regulations and prevent a potential chilling effect on commercial exchanges with the EU. 54 Meanwhile, the Council of Canadian Academies concluded that Canada's current legal framework on data regulation is not only unsuccessful in protecting privacy but also gravely hinders timely access to data for health research. The reporters recalled the dilemma policymakers are faced with and the growing need for amendments to solve it:  55  research that is in the public interest, on the one hand, and to respect Canadians' privacy and maintain confidentiality of their information when it is used for research, on the other.
As previously mentioned, although seemingly large, this category leaves out substantial areas. It excludes public health agencies, law enforcement agencies or personal health record vendors, for example, meaning that any PHI held by a non-covered entity is no longer under HIPAA's protection. A health record transferred to a non-covered entity may then, at best, fall into the scope of application of another privacy regulation, but could also be completely passed over by US data regulation. 65 While data portability can be beneficial for research by facilitating data transfers, in the US context, it also reduces HIPAA's already limited scope of application. In Canada, PIPEDA contains no obligation regarding data portability. Given its potential to favor data transfers in research (by facilitating data transfer from any file to a research project in which a data subject wishes to participate, for example), the Committee on Access to Information, Privacy and Ethics recommended that PIPEDA be amended 'to provide for a right to data portability'.
organizations. It is a GDPR novelty which is absent from both HIPAA and PIPEDA. This right is meant to assure data subjects that any personal information they disclose can be completely erased at their request. Article17 also provides some implicit restrictions to the application of the right to erasure, as it only applies when based on one of the legal grounds enumerated. These grounds include personal data collected which is no longer necessary in relation to the purposes for which they were collected in the first place. Should this data still be necessary for the processing and no other legal ground apply, the request for erasure could be validly denied. Other exceptions include when the processing is necessary for reasons of public interest in the area of public health (art. 17. 1. c, GDPR) or when it involves the exercise of official authority (art.
An exception to the requirement to perform a DPIA can be found at recital 91, which specifically provides that: 'the processing of personal data should not be considered to be on a large scale if the processing concerns personal data from patients or clients by an individual physician, other health care professional or lawyer. In such cases, a data protection impact assessment should not be mandatory'. Although absent from PIPEDA, the DPIA mechanism is mandatory under Canadian law for public federal government institutions only. Under US law, HIPAA also recommends performing a risk assessment annually to ensure that entities are compliant to HIPAA's requirements. This assessment is, however, different from the GDPR's DPIA, which is conceived as a continuous and preventive process, undertaken before the processing.
The DPIA is, in that sense, quite unique to the EU regulation. Moreover, under the GDPR, data actors are required to 'integrate the necessary safeguards into the processing in order to meet the requirements of this regulation and protect the rights of data subjects' (art. 25, GDPR). This principle, known as 'privacy by design', was actually developed in the 1990s in Canada by Ontario's former Privacy Commissioner Ann Cavoukian. 71 Curiously, it has not been formally integrated in the Canadian PIPEDA. Accordingly, the Privacy Committee of the House of Commons commended in 2018 that 'PIPEDA be amended to make privacy by design a central principle and to include the seven foundational principles of this concept'. 72 The GDPR has also enforced a new 'privacy by default' principle (art. 25, GDPR).
Higher penalties and security breach notification requirements Perhaps the most significant difference rising from the comparison of PIPEDA, HIPAA and the GDPR are linked to stances on penalties and security breach notifications. As to security breach notifications, HIPAA's Privacy Rule requires covered entities to notify individuals of any breach in protected health information security within 60 days (45 CFR § § 164. 400-414, HIPAA Breach Notification Rule). In Canada, provincial health privacy laws in Alberta, Ontario, New Brunswick, and Newfoundland and Labrador have also enforced data breach notification systems. 74 Amendments to PIPEDA that entered into force in November 2018 include a new data breach notification obligation to the Privacy Commissioner. However, some have criticized the imprecise language of the new text, requiring notifications only in case of 'real risk' of 'significant harm'.
83, GDPR). This dissuasive system aims at increasing the accountability of actors dealing with personal data and encouraging self-regulation to prevent privacy breaches. These higher sanctions come with significant administrative simplifications. Under the former Directive, heavy declaration formalities to authorities in charge of privacy at the national were mandatory prior to any collection or processing. In an attempt to alleviate administrative tasks for data processors, the GDPR no longer contains declaration requirement but now requests organizations to keep a record of their activities (art. 30, GDPR). This simplification comes at the cost of granting national privacy authorities with higher investigatory and sanction powers. In Canada, PIPEDA is much more conservative with its fines.
77 Since the enforcement of the Digital Privacy Act, failure to notify a data breach is sanctioned by fines of up to C$100,000-about US$75,300 (art 28, PIPEDA). However, the enforcement powers of the Privacy Commissioner are limited. As currently framed, the Privacy Commissioner has no authority to order changes or emit sanctions in case of non-compliance. At the provincial level, some privacy commissioners (ie Alberta and Quebec) have such authority. 78 The lack of harmonization results in somewhat uneven practices on the Canadian territory. Following the Facebook data breaches, the opportunity to provide Commissioner with more extended investigation and sanction power may warrant further consideration. 79 If sanctions under PIPEDA may be insufficient to ensure compliance from industrial giants, the US legislation does not provide a satisfying harmonized framework on the territory, making high sanctions difficult to apply at times.
Bioinformatics analysis Bioinformatics analysis followed the analytical methods of  Li et al. (2016b). Briefly, the raw sequences were analyzed using QIIME Pipeline-Version 1. 9. 0 (http://qiime. org/tutor ials/tutor ial. html)  (Caporaso et al. 2010). All sequences were trimmed and assigned to each sample based on their unique barcodes only if they completely matched their unique barcodes. The FLASH-1. 2. 8 software  (Caporaso et al. 2012 ) was used to merge the overlapping paired-end reads. The merged sequences with high quality (reads length more than 300 bp, without ambiguous base "N", and average base quality score more than 30) were kept for further analysis. Then the aligned 16S rRNA gene sequences underwent a chimera check using the Uchime algorithm  (Edgar et al. 2011). Due to possible contamination of chloroplast sequences in PCR amplification, the Metaxa2 software tool was used to remove chloroplast sequences from our large sequencing datasets  (Bengtsson-Palme et al.
2015). After filtering chimeras and chloroplasts, the remaining sequences were clustered into operational taxonomic units (OTUs) at a 97% identity threshold with an open-reference OTU picking method using the Uclust algorithm  (Edgar 2010). Those sequences not classifying to bacteria (Eukaryota and Archaea lineages) were filtered out. Singleton OTUs were also removed. The most abundant sequences within each OTU were defined as "representative sequences". Taxonomic classification of representative sequences was implemented using the Ribosomal Database Project classifier in the QIIME platform  (Wang et al. 2007). To minimize the impact of uneven sequencing depth, each sample was rarefied to 32,805 sequences. To evaluate alpha diversity indices, Goods coverage, Chao1, observed OTUs, Shannon diversity and evenness were calculated.
Statistical analysis Permutational multivariate analysis of variance (PER-MANOVA) was used to reveal whether the structures of gut microbiota were significantly different among groups based on the Jaccard and Bray-Curtis distance matrices using "adonis" in the R 'vegan' package  (Li et al. 2017a). The model also comprised other variables, including animal body weight. Taxonomic profiles were evaluated at the phylum and genus levels. Differences in relative abundances of the genera were performed through the group significance. py script in the QIIME platform with one-way analysis of variance (one-way ANOVA) with Tukey's post hoc test. P-values were corrected using false discovery rate (FDR). Comparison of the alpha diversity indices among groups was tested using Mann-Whitney U tests. Statistical significance was accepted at a P < 0.
05. Linear discriminant analysis effect size (LEfSe)  (Nicola et al. 2011 ) was used to identify bacterial OTU biomarkers at OTU level among groups based on a P < 0. 05 and LDA score > 2. 0. This analysis was performed online in the Galaxy workflow framework (http://hutte nhowe r. sph. harva rd. edu/galax y/). The Spearman correlation analysis among SCFA levels, bioamines, bacterial biomarkers (based on LefSe results) was achieved using function "cor. test" of the package "Stats" in R. One heatmap plot of the correlation values were produced using package "gplots". One-way ANOVA with Tukey's post hoc test was used to evaluate the difference of SCFA levels and bioamines among groups. Absolute SCFA or bioamine concentrations (μmol/g) were converted to molar percentages within each individuals  (Li et al.
However, both observations and modeling partially captured GW characteristics depending respectively on the observational instruments  [11] [12] [13] [14] [15]  and the model setup  [16] [17] [18] [19]. Reference  [20]  derived dominant low-frequency GWs with short vertical wavelengths of 1-3 km, horizontal wavelengths of 80-400 km and periods of 4. 6-13 h in the upper troposphere (UT) and LS from radiosonde and FormoSat-3/COSMIC (Formosa Satellite Mission-3/Constellation Observing System for Meteorology, Ionosphere, and Climate) radio occultation (RO) datasets, while mesoscale modelling with a vertical resolution of about 500 m highlighted a wide spectrum of resolved GWs with horizontal wavelengths of 20-2000 km, short vertical wavelengths of 1. 5-4 km and periods of 20 min-2 days and up to 25 km height in the LS.
The PBL and cumulus convection processes are highly sensitive to vertical resolution. Therefore, increasing vertical resolution in the lower layer could effectively strengthen the TC  [42, 43]. Reference  [44]  reported no significant changes in maximum intensity when the horizontal grid spacing was decreased from 5 to 1 km and suggested a horizontal grid spacing of 3 km to resolve the rainbands. In the present study, wavelike structures with vertical wavelengths ranging between 500 m and 7 km were characterized with numerical and observational datasets. Vertical profiles of the dynamic parameters, such as the wind and temperature, were resampled at a resolution of 100 m, using a cubic spline interpolation, and then analyzed with different methods to derive the spectral characteristics of the GWs.
In our study, they were applied on simulated vertical profiles of horizontal wind and temperature perturbations. The temperature was derived from the WRF prognostic variable of the potential temperature using the script built into NCAR Command Language (NCL) software. 2a ). Soudelor underwent an eyewall replacement cycle (ERC) with steady weakening from 4 August until its re-intensification above warmer waters with SST and OHC values > 30 • C and 75 kJ/cm 2 , respectively (refer to the Regional and Mesoscale Meteorology Branch products), at longitudes between 124 • E and 126 • E when it was approaching Taiwan late on 6 August. At 03:00 UTC on Friday, 7 August, the intense TC reached 1 min maximum sustained winds of about 50 m/s with wind gusts around 67 m/s when moving west-north-west at a speed of 5.
In this framework, FormoSat-3/COSMIC RO data may be an alternative means to cross-check the characteristics of GWs in the future studies as demonstrated in the current investigation. The follow-up mission of FormoSat-3/COSMIC, or FormoSat-7/COSMIC-2, is expected to be launched in 2019. Thus more COSMIC RO observations will be available to improve our knowledge of the TC inner core. In perspective, GW sources and momentum fluxes will be investigated. Supplementary Materials: A 3D animation of the simulation from 6 August 18:00 UTC to 7 August 18:00 UTC 2015, produced by the Weather 3D software developed by Meteo-France, is available at https://www. youtube. com/ watch?v=1aEDfNNqqWc.
Acknowledgments: This work was financially supported by grants from the  ANRT  ( CIFRE 2015/0876 ),  French ANR  ( BOOST3R ANR-17-CE01-0016-01 ) and  Taiwanese MOST  ( 105-2221-E-008-056-MY3 ,  107-2111-M-008-036 ). It was performed using HPC resources from  GENCI-[TGCC/CINES/IDRIS] (Grant 2017 [A0010107689 ]) and the  University of La Réunion. The WRF-ARW model and NCL software (http://dx. doi. org/10. 5065/D6WD3XH5)were provided by the  National Center for Atmospheric Research (NCAR). FormoSat-3/COSMIC RO data were obtained from CDAAC (COSMIC Data Analysis and Archive Center): http://cdaac-www. cosmic. ucar. edu. In-situ Taiwanese meteorological data were provided by the  Central Weather Bureau.
Abstract. In October 2017, the Sentinel-5 Precursor (S5P) mission was launched, carrying the TROPOspheric Monitoring Instrument (TROPOMI), which provides a daily global coverage at a spatial resolution as high as 7 km × 3. 5 km and is expected to extend the European atmospheric composition record initiated with GOME/ERS-2 in 1995, enhancing our scientific knowledge of atmospheric processes with its unprecedented spatial resolution. Due to the ongoing need to understand and monitor the recovery of the ozone layer, as well as the evolution of tropospheric pollution, total ozone remains one of the leading species of interest during this mission. In this work, the TROPOMI near real time (NRTI) and offline (OFFL) total ozone column (TOC) products are presented and compared to daily ground-based qualityassured Brewer and Dobson TOC measurements deposited in the World Ozone and Ultraviolet Radiation Data Centre (WOUDC).
Additional comparisons to individual Brewer measurements from the Canadian Brewer Network and the European Brewer Network (Eubrewnet) are performed. Furthermore, twilight zenith-sky measurements obtained with ZSL-DOAS (Zenith Scattered Light Differential Optical Absorption Spectroscopy) instruments, which form part of the SAOZ network (Système d'Analyse par Observation Zénitale), are used for the validation. The quality of the TROPOMI TOC data is evaluated in terms of the influence of location, solar zenith angle, viewing angle, season, effective temperature, surface albedo and clouds. For this purpose, globally distributed ground-based measurements have been utilized as the background truth. The overall statistical analysis of the global comparison shows that the mean bias and the mean standard deviation of the percentage difference between TROPOMI and ground-based TOC is within 0 -1.
TROPOMI/S5P TOC products The TOC products validated in this work and the respective algorithms are described in the following sections. The TROPOMI dataset used here spans the time period from its launch in October 2017, until 30 November 2018, hence a full year of operation is covered, including the commissioning phase "E1" that concluded at the end of April 2018. This phase started immediately after the initial switch-on and acquisition of nominal orbit characteristics, in order to perform functional checking of the end-to-end system on board the Sentinel-5P, as well as engineering calibration and geophysical validation of the first observations.
The OFFL TOC product For the offline (OFFL) TOC product other requirements were defined: the required accuracy is higher, but the time requirement is more relaxed (14 d after the measurements). To be consistent with the ECMWF C3S-ozone dataset, it was decided to use the GODFIT (GOME-type Direct FITting) algorithm for the total ozone column offline retrieval. The TROPOMI OFFL TOC product relies on the operational implementation of the GODFIT v4 algorithm, which is a direct-fitting algorithm developed to retrieve, in one step, total ozone columns from satellite nadir-viewing instruments. Simulated radiances in the Huggins bands (fitting window: 325-335 nm) are directly adjusted to the observations by varying a number of key parameters describing the atmosphere. In particular, the state vector includes, among others, the total ozone, the effective scene albedo and the effective temperature.
This approach, more physically sound than the usual DOAS technique, provides more accurate retrievals in extreme geophysical conditions (large ozone optical depths). GODFIT v4 is also the baseline to produce the Copernicus C3S and ESA CCI climate data records from the different sensors GOME, SCIAMACHY, GOME-2A and GOME-2B, OMI, and OMPS. More details on the algorithm and on the quality of the datasets can be found in  Lerot et al. (2014)  and  Garane et al. (2018). OFFL TOC data are available through the Sentinel-5P Expert Users Data Hub (https://s5pexp. copernicus. eu/, last access: 6 September 2019) and the Sentinel-5P Pre-Operations Data Hub (https://s5phub. copernicus. eu/, last access: 6 September 2019), and the datasets used here are listed in Table  1. The data filtering was applied following the recommendations of the S5P Mission Performance Centre readme document for the OFFL total ozone product  (Lerot et al.
The Eubrewnet network consists of 46 stations, mainly in Europe and South America but also in North America, Greenland, North Africa, Singapore and Australia. After quality control (QC) of their measurements, some Brewers were excluded from the validation datasets, while others did not have available measurements for the time period of interest, leaving the network with 25 Brewers. The Canadian Brewer Network is comprised of eight sites, plus Mauna Loa, Hawaii (MLO), and South Pole (SPO) observatories where Brewers are operated jointly with NOAA. Every site (except SPO) has at least two Brewers, including one double spectrometer, while each Arctic site has three Brewers. Due to very low stray light, double Brewers produce reliable ozone measurements when the sun is low above the horizon (air mass values up to of 7 at SPO and 5 at all other sites).
This data are called LATMOS_RT and are used here. In the context of satellite validation, the SAOZ measurements are complementary to the Brewer and Dobson measurements for several reasons: (a) they use spectral features of the visible Chappuis band, where the ozone differential absorption cross sections are temperature insensitive, (b) the long horizontal stratospheric optical path allows measurements of the column above cloudy scenes, and (c) measurements are always performed in the same small SZA range (86-91 • ). For further details on the measurement procedures we refer to  Balis et al. (2007a) ,  Verhoelst et al. (2015) ,  Garane et al. (2018)  and references therein. Additional information on the specific collocation approach, taking into account the actual area of measurement sensitivity, is given in Sect.
, 2011). Another, possibly important, source of bias between the different datasets discussed in this paper is the use of different ozone absorption cross section coefficients; while the Dobson and Brewer TOC algorithms are based on the traditional  Bass and Paur (1985; BP)  ozone absorption cross sections, the TROPOMI NRTI TOCs are extracted using the so-called "Brion-Daumont-Malicet" (BDM) cross sections  (Daumont et al. , 1992; Malicet et al. , 1995; Brion et al. , 1998) , whereas the TROPOMI OFFL TOCs using the more recent  Serdyuchenko et al. (2014) , henceforth Serdyuchenko, coefficients. It has already been shown that, for the Brewer wavelengths, the replacement of the BP with the Serdyuchenko cross sections would cause a minimal reduction of the extracted Brewer TOCs of less than 1 %, whereas a replacement with the BDM would result in a reduction of the nominal TOC by about 3 % (see  Fragkos et al.
, 2013; Redondas et al. , 2014). For the Dobson wavelengths, the calculated TOC changes by +1 %, with little variation depending on which of the aforementioned cross sections is used (see  Redondas et al. , 2014; Orphal et al. , 2016). These findings illustrate the current uncertainty associated with the use of different ozone cross section measurements between platforms and should be considered when examining biases between the different TROPOMI TOC algorithms validated against the Brewer and Dobson observations. The lists of the stations used in this validation work for each instrument and database category are displayed in Tables S1-S5 in the Supplement. In Fig. S1  the respective maps show the very good geographical coverage of the Earth by the ground-based measurement sites used herein.