dataesr/scientific-paragraphs-categorization huggingface dataset:
Opaque Messages in Widevine Workflow As studied in  [48] , the Widevine protocol defines four main operations: License/Renewal Requests and License/Renewal Responses. Here, we investigate the correspondence of these operations with the EME protocol. To acquire a media license, the EME user-agent creates a session within the Widevine CDM to ask for a license request through the generateRequest EME API. The CDM requires some Initialization Data to issue licenses, also stated as Content Keys. These data include Content Key IDs associated with some encrypted media. The corresponding request contains a Request ID for associating subsequent responses, one or several Content Key IDs for the desired media, and a Client ID used for license protection (further details are given in subsection 3. 5). Using the EME JavaScript API, the browser sends this request alongside its signature to a license server, which will respond with the according license response.
Persistent Session As explained in section 2. 3. 2, EME can define a persistent session type. Once closed, a persistent session can be re-opened to retrieve content keys without the need for a license acquisition phase. In Widevine, the workflow does not differ for a temporary or persistent session; the type is only mentioned when opening the session. However, a persistent session becomes persistent only when a response is processed through the update call and the associated license policies permit it. Upon session closing, Widevine entirely relies on the user-agent implementation to store a session blob from the CDM. Here the user-agent is responsible for implementing a per-origin policy as mentioned in EME using, for instance, service storage for licenses inside dedicated databases. Sessions can then be re-opened using their session ID through the load function.
The EME specification (refer to section 11. 4. 2 of  [11] ) presents their recommendations for a privacy-friendly EME implementation. Of particular interest, we mention two recommendations: (1) encrypt distinctive identifiers, and (2) treat key systems stored data like cookies or web storage. However, we argue that these considerations lack binding requirements and are insufficiently concrete. In that regard, users do not have any guarantee that their privacy is safeguarded when using EME with proprietary DRM modules. In our paper, we empirically challenge these privacy claims by scrutinizing one of the most popular real-world functioning of EME, namely Widevine. In our paper, we provide, to the best of our knowledge, the first conformance test verifying EME privacy recommendations for Widevine EME.
Experimental Setup To explore our question, we deployed our tests on multiple devices both for desktop and Android. Note that for both experiment setups, no real users were involved avoiding user privacy risks. On Desktop. For our population, we used 159,923 devices with Windows 10/11, macOS Big Sur and Linux. The majority comes from Windows and Mac VMs of BrowserStack 1  , added to our own device pool of Windows and Linux devices for comparison purpose between real and emulated devices. To inspect Widevine Client IDs and persistent sessions, we automated navigation to our custom site in which we open persistent sessions when available, and perform license renewal to obtain clear Client IDs using custom license policies as described in subsection 4. 3. On Android. We used 317 physical devices from BrowserStack and our own device pool, as well as 18,101 emulated ones, to collect Client IDs.
Client ID Certificate Fingerprint In subsection 3. 5, findings from our reverse engineering strongly indicate that the Client ID contains multiple distinctive permanent identifiers. Indeed, its inner Client Info contains device-specific attributes related to hardware instances and software versions for desktop and Android. In addition, it contains an RSA certificate chain used to protect the transmitted licenses. On the one hand, attributes can help classify devices into subgroups. On the other hand, the Widevine certificate chain might be enough to point out an exact device. The nature of this chain depends on the platform as explained above. On desktop (i. e. , Linux, macOS, and Windows), the certificate chain is hard-coded within the CDM. Due to this design, all desktop Widevine CDMs share the same DRM certificate chain for a given CDM version.
Uniqueness. As explained in subsection 5. 2, our dataset of mostly emulated devices cannot be relied upon to calculate the entropy of Client Info for a real-world population. Nevertheless, we can still provide some insights from our collected data. On Android, the data from Client Info can point to an exact device model and build version using the Build Info string (refer to the example of Pixel 7 in Table  2 ). On desktop, although with fewer fields than on Android, Client Info can still narrow down devices to architecture and OS subgroups, making entropy close to a standard browser UA regarding system information, which was studied in  [18]. In the Chromium project, the related Widevine implementation indicates eight possible values 2  : Windows (x86, x64, and arm64), Linux (x64, arm, and arm64) and MacOS (x64, and arm64).
Persistent Session Re-invocation With our EME Track script, an origin can gather Client IDs in clear when available from any user-agent and create persistent sessions when supported within the browser file system. Here we describe the workflow of a curious website tracking users based on their stored Widevine persistent sessions. At first, a user-agent visits a curious website and receives a tracking script starting to be executed. A Widevine access is demanded using requestMediaKeySystemAccess with persistent license support configuration. At this point, either by hard-coded values within the script or by receiving it through the origin, previously gathered session IDs are provided by the curious website to the CDM in an attempt to load an already existing session. On return, the script provides the result of this operation to the curious website.
Rinaldy's article about shipping industry safety was very relevant  [1]. The subject is delicate and critical because of the number of accidents and severe accidents among seafarers  [2, 3]. The author has thus made a review of the literature. This will help for future research and to improve safety policies in the Indonesia shipping industry. However, as the author points out, the review has limitations inherent in its method: the quality of the data thus collected depends on the database, keywords, etc. But there is also another bias: using Scopus, the humanities may be underrepresented. It's why, we would like to complete Rinaldi's research by providing some notions from the human sciences. For example, the author highlights the importance of the literature about human error, which would be responsible for 80% to 85% of accidents.
Bundespresseamt (Bundesarchiv Koblenz) 1949-1985, the Vereinigte Presseabteilung der Reichsregierung (Bundesarchiv Berlin) 1918-1933, the Bundespressekonferenz (Berlin) 1949-1985, the Verein der ausländischen Presse 1970-1975, and the administrative documents filed in the documentation department of the Bundespresseamt. The 1985 cut-off date was the maximum access limit for open archives according to the thirty-year limit at the time of the investigation and according to the classification of these data by the institutions (BPA and BPK). Some more recent documents could be consulted, when they had not been sent to the archives, and the interviews largely made up for this period. In order to investigate the work done by the journalists of the BPK and the Government Communication Service (BPA), I established a first theoretical principle.
Research in context Evidence before this study Core outcome sets (COS) have been developed for many health and pain-related conditions, but COS capturing shared experiences across pain conditions do not yet exist for the field of pain. We conducted a literature review to identify all articles that developed, updated, or implemented a COS for pain conditions or health conditions where pain is a major symptom in adults. Published articles were identified from PubMed (including Medline) and from the COMET database, and results of the literature review were used to inform the present Delphi study, which aimed to develop COS for: acute pain, acute to chronic pain, recurrent/episodic pain, and chronic pain.
0,  25  and the PROMIS Pain Interference scale. 23  However, the "how" to measure the outcomes/ subdomains needs further systematic research followed by a final consensus process on the COS of PROMs for each pain category. The result of our Delphi provides COS with lists of domains achieved by respondent consensus. Pain intensity was included in three out of the four COS. However, pain intensity did not reach consensus for the recurrent/episodic pain COS; instead, pain temporality was included by Delphi participants, indicating the importance of frequency and duration of pain. There are two intended principal uses for the present COS. First, they can be used in research to supplement measures that researchers already collect for certain conditions. In this way, the COS can advance the pain field through data harmonization across studies without limiting innovation within specific projects.
Laura Wandner  has nothing to disclose. Esther Pogatzki-Zahn  reports grants from the  German Research Foundation (DFG) , the  Federal Ministry of Education and Research (BMBF) , the  Federal Joint Committee  ( G-BA ) and the  Innovative Medicines Initiative   2 Joint Undertaking  under grant agreement No  777500. This Joint Undertaking receives support from the  European Union 's  Horizon 2020 research and innovation programme  and  EFPIA. All money goes to the institutions ( WWU/UKM)  EPZ is working for. EPZ received personal fees (money went to her institution) from.
Acknowledgements The authors would like to thank all stakeholders who participated in the August 2020 Opportunities to Advance the Field of Pain and June 2022 virtual consensus meetings. We also would like to thank all pain researchers, clinicians, people with lived experience of pain, and organization representatives who played a role in the Delphi, including those who reached out to their social networks to help advertise the initiative and those who voted in the surveys. Meeting participants and Delphi voters who wish to be named as contributors to this initiative, and have provided consent to have their names listed as part of this initiative, can be found at the following website link: https://www. painconsortium. nih. gov/integrate-pain-initiative. Additionally, we would like to thank the  NIH  and EU leadership who helped initiate this effort.
The  NIH  and  NIH  staff did not receive any funding for the  INTEGRATEPain Consortium. This work was conducted as part of  IMI PainCare PROMPT  (an  Innovative Medicines Initiative 2 Joint  undertaking under grant agreement No  777500 ). This Joint Undertaking receives support from the  European Union 's  Horizon 2020 research and innovation programme  and  EFPIA. www. imi. europa. eu; www. imi-paincare. eu. The statements and opinions presented here reflect the authors' view and neither IMI nor the  European Union ,  EFPIA , or any Associated Partners are responsible for any use that may be made of the information contained therein. RDT acknowledges grants from  Esteve  and  TEVA. None of the funders of the  IMI-PainCare initiative  (the  NIH  did not receive any funding) were involved in the study design, data collection, data analyses, interpretation, or writing of report.
Purpose The United Kingdom Childhood Cancer Study's (UKCCS's) matched cohort was established to examine the longer term morbidity and mortality of individuals previously diagnosed with cancer before 15 years of age, comparing future healthcare patterns in 5-year cancer survivors to baseline activity seen in age-and sexmatched individuals from the general population. Participants Predicated on a national childhood cancer case-control study conducted in the early 1990s (4430 cases, 9753 controls) in England, Scotland and Wales, the case population comprises 3125 cancer survivors (>5 years), and the control population 7156 age-and sex-matched individuals from the general population who did not have cancer as a child. Participants are now being followed up via linkage to national administrative healthcare databases (deaths, cancers and secondary care hospital activity).
⇒ With respect to weaknesses, lack of primary care data and information from psychosocial services are obvious deficiencies that currently affect all UK record-linkage studies of the type described here. Open access occur later in life (eg, second cancers, cardiac and bone problems and fertility issues). [4] [5] [6] [7]  With a view to investigating childhood cancer survivors' health, the national matched cohort described in this report was established with the aim of examining the relationship between cancers diagnosed before 15 years of age and other morbidities and health states in the years after cancer diagnosis; specific aims include the examination of secondary care hospital activity patterns and the impact of deprivation on longer term outcomes. The cohorts are predicated on the structures established in the United Kingdom Childhood Cancer Study (UKCCS), which was set up as a national population-based casecontrol study in the early 1990s in England, Scotland and Wales to investigate a wide range of possible causes of childhood cancer.
Collecting data from multiple sources (including interviews with parents, primary care records, obstetric/neonatal notes, birth certificates, household radiation measurements and pretreatment and remission blood samples), the case-control study investigated the potentially carcinogenic effects of a wide range of physical (eg, non-ionising radiation), chemical (eg, drugs) and biological (eg, infectious agents) agents. [8] [9] [10] [11] [12] [13] [14]  Examining associations in the prenatal, in utero and postnatal periods, as well as associations with birth characteristics (eg, birth weight) and other illnesses (eg, allergies), over 90 reports have thus far been published (www. UKCCS. org). Underpinned by updated ethics and legal permissions, the UKCCS has now been transformed into a matched population-based cohort, with follow-up linkages to electronic national administrative healthcare databases (inpatient and outpatient hospital episode statistics-HES, cancers and deaths).
COHORT DESCRIPTION Full details of the UKCCS case-control study ( www. UKCCS. org), which provides the foundation of the matched cohort described here, have been published. 8 10 18  Briefly, the sampling frame for cases and controls comprised all children registered with the National Health Service (NHS) in England, Scotland or Wales at the time the study was conducted (>98% of the childhood population in these countries); unfortunately, for logistical reasons Northern Ireland (~3. 5% of the total UK population aged 0-14) was not included. Overseen by a management committee that included epidemiologists, statisticians, paediatric oncologists/ haematologists and expert scientists that was chaired by Professor Sir Richard Doll, 10 UKCCS administrative areas covering the whole of Britain were created for the purposes of data collection, with each being the responsibility of a well-established epidemiological research centre  8  (online supplemental figure  1 ).
The study began on 1 January 1991 in Scotland and on either 1 April 1992 or 1 September 1992 in the nine UKCCS administrative areas of England and Wales. In Scotland, case accrual ended on 31 December 1994, and in England and Wales, it was restricted to children diagnosed with leukaemia or non-Hodgkin's lymphoma throughout 1995 and leukaemia alone throughout 1996. In order to ensure ascertainment completeness, proactive cancer notification systems were established in all diagnostic/treatment centres across the UK, the majority of cases being notified at the point of diagnosis directly to the relevant UKCCS administrative centre by paediatric oncologists or haematologists practising in the study area. Subsequent crosschecks were made against regional childhood cancer registries (where they existed); the population-based National Registry of Childhood Tumours (NRCT), which covered England, Scotland and Wales  8 19  ; and clinical trial datasets (acute lymphoblastic leukaemia).
With the permission of the child's clinical team, the parents of children with cancer were subsequently contacted. Each child whose parents agreed to be interviewed (3835/4430; 87%) was individually matched on sex, date of birth (month and year) and UKCCS region of residence to 10 controls who were randomly selected from the same population-based health service authority list as the case. With their general practitioner's (GP's) permission, the parents of the first two controls on the list ('first-choice' controls) were contacted and asked to participate in the study; but if the GP declined, or the parents did not wish to be interviewed, the next child was selected, and this procedure was repeated until two control families agreed to take part. By the end of the data collection phase, 96. 7% (3786/3835) cases had two participating controls and 1.
Importantly, in line with current ethical and governance requirements, the matched cohorts are now pseudonymised; NHS identifiers are no longer held by the study but by the national administrative bodies supplying linked data (NHS England, Public Health Scotland, NHS Central Register Scotland, and the Secured Anonymised Information Linkage Databank). Beginning with the numbers registered in the original case-control study, the flow diagram presented in figure  1  gives the number of cases and controls who survived 5 years or more, followed by the number of cases who were successfully linked to national administrative data Open access sources. Cases the survivors' cohort exactly 5 years after their cancer was first diagnosed and controls 5 years after their corresponding case's cancer was first diagnosed (pseudo-diagnosis date).
Controls who emigrated, died or were lost to follow-up before 5 years had elapsed are not included in the survivor cohort, nor are controls who were matched to cases who died within 5 years of their diagnosis, since, where applicable, their follow-up was truncated when their matched case died (figure  1 ; bottom row). All those who were targeted for interview in the original case-control study are shown on the left side of figure 1 and all those whose parents were interviewed on the right side; the total number of individuals that are being followed is shown in the yellow boxes in the centre of the figure. With respect to the available data, the time periods currently covered by the various linked healthcare datasets, which are updated on an annual basis, are shown in online supplemental figure 2; and the key data domains and fields are listed in table 3.
Characteristics of individuals in the study Detailed diagnostic and treatment information was obtained from multiple sources, including diagnostic/ treatment centres, national treatment trials (where they existed), hospital records and reference laboratories. The diagnostic distribution, coded to the International Classification of Childhood Cancer Third Edition (ICCC-3), as well as information on age, sex and interview status, is shown in table 4. As expected, given the increasing emphasis on leukaemia in the later years of the casecontrol study's data collection phase, the final diagnostic distribution was weighted towards leukaemia. Variations with parental interview status are also evident, with the non-interviewed group containing proportionally more CNS tumours (ICCC III) and other cancers (ICCC XI and XII).
FINDINGS TO DATE The UKCCS provides a valuable resource within which to examine both the potential causes and long-term health consequences of childhood cancer. Thus far, over 90 peer-reviewed articles containing UKCCS data have been published, and a full list is available on the study website (www. UKCCS. org). Assembling data from multiple sources, key reports include ALL genome-wide association studies (GWAS),  14 20  and those examining the potential aetiological roles of a wide range of biological (eg, infections/markers of infectious exposure),  [21] [22] [23]  physical (eg, ionising/non-ionising radiation)  12   13 24 25  and chemical (eg, prescription drugs/smoking) agents acting on parents before the child's conception and the child during pregnancy/early life,  10 26 27  as well as relationships with other illnesses (eg, allergy) and birth characteristics (eg, birth weight).
40 41  Thus far, with follow-up extending over 25 years from diagnosis, we have examined health through the teenage and early adult years, and individuals in the matched cohorts will continue to be tracked as they age. With respect to limitations, lack of reliable details about ethnicity as well as information from primary care and psychosocial services are obvious deficiencies that currently affect all UK record-linkage Open access studies the type described here. [42] [43] [44]  Analyses are also constrained the fact that national administrative healthcare data are primarily collected for administrative and clinical purposes and not for research.
Study population In May 2020, 371,000 individuals aged 15 years and over were randomly selected from the French national tax database and invited to participate to the EpiCov cohort. As shown in Fig. 1 , a total of 134,391 individuals (aged 15 years or older) participated in the self-administered computer-assisted-web or computer-assisted-telephone questionnaire at baseline (participation rate: 36. 6%) and were invited for follow-up in Autumn 2020 ( rst follow-up, 107,759 participants) and in Summer 2021 (second follow-up, 85,074 participants). A sub-sample of 10% of the participants was offered an extended version of the questionnaire at baseline (14,371 respondents) and rst follow-up  (11,255 respondents) , including questions about children.
Sample selection and characteristics As shown in the ow-chart (Fig. 2 ), at the second follow-up, 21,512 participants had at least one child aged 3-17 years. Among them, 1,432 were part of the subsample completing the extended questionnaire at baseline and rst follow-up, and therefore had screen time assessments since baseline. Then, 320 children were excluded from analyses because they were aged 15-17 years and 23 children had missing data on outcomes or exposure. The analyses were therefore performed on 1,089 children aged 3-14 years who provided parental assessments of screen time since May 2020 and parental answers to the SDQ in Summer 2021. The sample characteristics are described in Table  1.
Objectives: Quantify the effects of characteristics of nursing homes and their surroundings on the spread of COVID-19 outbreaks and assess the changes in resident protection between the first 2 waves (March 1 to July 31 and August 1 to December 31, 2020). Design: An observational study was carried out on data on COVID-19 outbreaks extracted from a database that monitored the spread of the virus in nursing homes. Setting and Participants: The study concerned all 937 nursing homes with >10 beds in Auvergne-Rhône-Alpes region, France. Methods: The rate of nursing homes with at least 1 outbreak and the cumulative number of deaths were modeled for each wave. Results: During the second (vs the first wave), the proportion of nursing homes that reported at least 1 outbreak was higher (70% vs 56%) and the cumulative number of deaths more than twofold (3348 vs 1590).