dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgements C. M. ( FT200100870 ), K. L. N. ( DE210100606 ) and R. D. S. -S. (FT190100599) were by  Australian Research Council  funding. M. A. M. was supported by the  Natural Sciences and Engineering Research Council Canada Research Chairs Program. J. P. W. R. received funding from a  Leverhulme Trust Early Career Fellowship. N. A. J. G. received funding from the  Royal Society  ( URF\R\201029 ) and from the  European Union 's  Horizon 2020 research and innovation programme  under grant agreement number  820989  (project  COMFORT ). C. C. H. receives funding from a  European Research Council   Starting Grant  ( 759457 ) and a  Philip Leverhulme Prize. C. D. G. and J. Z. -M. receive funding from the  National Science Foundation   CNH-L 1826668  and the  John and Katie Hansen Family Foundation.
6  the randomized, phase 3 SINUS-24 (NCT02912468) and SINUS-52 (NCT02898454) studies, dupilumab produced rapid and sustained improvements in loss of smell and the University of Pennsylvania Smell Identification Test (UPSIT) compared with placebo. 7 In addition, dupilumab significantly reduced nasal polyp score, nasal congestion and HRQoL compared with placebo, and was generally well tolerated. 8 Given that loss of taste is widely reported in CRSwNP,  9  we determined the effect of dupilumab on patient-reported sense of "taste" and assessed associated changes in sense of "taste" and sense of smell from the pooled SINUS-24 and SINUS-52 trial populations. Biologic treatment has not previously been reported to impact patient-reported taste in patients with CRSwNP. Full details of the patient population, methodology and primary and secondary outcomes from the SINUS-24 and SINUS-52 dupilumab phase 3 studies have been published previously.
In SINUS-24, patients were randomized (1:1) to receive dupilumab 300 mg subcutaneously (SC) or placebo every 2 weeks (q2w) for 24 weeks. In SINUS-52, patients were randomized (1:1:1) to receive dupilumab 300 mg SC q2w for 52 weeks, dupilumab 300 mg SC q2w for 24 weeks and then every 4 weeks for the remaining 28 weeks or placebo q2w for 52 weeks. This post hoc analysis included data for patients who received dupilumab or placebo to Week 24 in SINUS-24 or to Week 52 in SINUS-52. Week 52 data from SINUS-52 are presented for the combined dupilumab q2w groups up to Week 24. Patient-reported sense of "taste" was assessed weekly using a loss-of-taste severity categorical scale (0-3), with a higher score representing greater severity (0 = no symptoms, 1 = mild symptoms, 2 = moderate symptoms and 3 = severe symptoms).
placebo: SINUS-24: -0. 99 [95% CI -1. 21, -0. 78]; p <. 0001; SINUS-52, -0. 80, 95% CI -0. 98, -0. 62; p <. 0001; Table  2 ). The improvement in loss-of-taste severity induced by dupilumab in this enriched population was rapid and sustained over 24 and 52 weeks (additional data regarding change in taste severity over time can be found here: https://osf. io/gxycn/ ?view_only=fb9fb 14804 264d9 c862d 2ec0f 39d79e1). A significantly higher proportion of patients receiving dupilumab compared with placebo achieved an improvement in loss-of-taste severity of ≥1 point at Week 24 in the ITT population (pooled SINUS-24/52: 61. 2% vs. 26. 2%; p <. 0001), with this effect maintained at Week 52 (SINUS-52; Table  2 ). The proportion of patients with an improvement in loss-of-taste severity of ≥1 point was also significantly greater with dupilumab versus placebo in the enriched population at Week 24 (pooled SINUS-24/52: 69.
Research sponsored by  Sanofi  and  Regeneron Pharmaceuticals, Inc. Clini calTr ialsNCT02898454 ( SINUS-52 ) and  NCT02912468  (SINUSboard member; AstraZeneca-research support and advisory board member; Optinose-consultant and research support. Z. M. Soler: Lyra ,  Novartis ,  Olympus , Optinose-advisory board and/or consultspeaker fees, and advisory boards; Boehringer Ingelheim-speaker fees and advisory boards; GlaxoSmithKline-research grants and advisory boards; Menarini, Uriach-speaker fees; MSD-advisory boards. L. Crampette: Medtronic, Novartis, Zambon-speaker fees; ALK,  AstraZeneca ,.
DATA AVA I L A B I L I T Y S TAT E M E N T Qualified researchers may request access to patient-level data and related study documents including clinical study report, study protocol with any amendments, blank case report form, statistical analysis plan and dataset specifications. Patient-level data will be anonymized and study documents will be redacted to protect the privacy of trial participants. Further details on Sanofi's data sharing criteria, eligible studies and process for requesting access can be found at: https://www. clini calst udyda tareq uest. com.
ACKNOWLEDGMENTS We would like to thank reviewers for their efforts in evaluating manuscripts for this Research Topic collection. We acknowledge support from  R01AG061382  (JMC), RF1AG072300 (JMC) an Alzheimer's  Association Research Grant  (JMC),  R01AG067552 (IAP) ,  Centre National de la Recherche Scientifique (CNRS)  (SB), the  Institut National de la Santé et de le Recherche Médicale National (INSERM) (SB) ,  Sorbonne Université, Faculté des Sciences et Ingénierie (SB) , the  Agence Nationale pour la Recherche  ( ANR 2020-CE16 ) (SB), and  Association Française contre les Myopathies-Téléthon (AFM-Téléthon ) (SB).
At the same time, long presence in the field allowed me to situate the collected verbal accounts in relation to observed interactions  (Jerolmack & Khan, 2014) , making it possible to relativize the social significance of certain assertions. All the interviews with defense attorneys and activists were recorded with the permission of interviewees and fully transcribed. Court hearings can be audio-recorded without any specific permission from the judge. The courthouse and courtroom observations were manually written down on a smartphone and sometimes complemented with the use of audio recordings. The identification and organization of emergent themes in the analysis was done manually by working with printed interviews and field notes. I began data analysis after my first trip and benefited from constant iterative movement between fieldwork and data analysis.
ACKNOWLEDGMENTS My sincere thanks go to  Gilles Favarel-Garrigues ,  Sida Liu ,  Mathilde Darley ,  Douglas Rogers ,  Elena Adasheva-Klein ,  Andrei Semenov ,  Dominic Martin ,  Thomas Keck ,  Ata Hindi ,  Sanele Sibanda ,  Andrei Yakovlev , participants of the 2017 Alexanteri conference,  2018 ICSID seminar at Higher School of Economics, 2019 seminar "Autoritarisme en question" at EHESS, 2020 LSA Early Career workshop and 2021 Political Violence and its Legacies workshop at Yale  for their helpful feedback on earlier drafts. I am also deeply grateful to  Peter Solomon ,  Lauren McCarthy , and  Kathryn Hendley  for the conversations about law and politics in Russian courts, the editors, and the three anonymous reviewers for their insightful comments. Finally, my heartfelt thanks to my interlocutors in Moscow.
Overview Our patient portal use data were retrieved from a large AMC that offers a wide range of services and subspecialty care. The AMC is located in an urban area in the United States. Similar to the rest of the world, the city was severely disrupted by the COVID-19 pandemic. On  March 11, 2020 , the governor declared a state of emergency in response to the pandemic. The AMC took measures to limit the spread of SARS-CoV-2, including increasing personal protective equipment stockpiles, limiting visitors to both inpatient and outpatient settings, and halting nonemergency surgeries. In line with a broader trend, the AMC noticed a sharp decline in patients seeking in-person health care during the pandemic  [50]. The AMC offers a patient portal as a central digital health gateway for its patients, which has been in place since 2012.
In addition, we focused on the second-order effect use rather than the first-order effect access by limiting our sample to patients who had used the portal before the pandemic. We obtained all patients' portal use data and their EHR data before August 30, 2020 (the end date of the data set). We limited the sample period of our study to 2 periods in 2019 and 2020 (Figure  1 ). The COVID-19 period was between  March 11 , 2020 (when the state of emergency was declared), and August 30, 2020. The corresponding pre-COVID-19 period was from  March 11, 2019 , to August 30, 2019. Among the 34,240 patients who used the patient portal during either of the sample periods (Figure  1 ), we excluded 5540 (16. 18%) patients who did not use the patient portal at least once before  March 11, 2020. We focused on the use behavior of 28,700 (83.
82%) out of 34,240 existing patient portal users when COVID-19 started without including new patient portal users; all patients in our sample had logged in to the system at least once before the COVID-19 pandemic. Because the patient portal was integrated with the AMC's EHR system, we merged the use data with the EHRs. The EHR data set included patient demographics, office visits, health vitals, diagnosis, insurance type, and medical problems. The merged sample included 26,742 patients with no missing data. Finally, we excluded patients who were identified as Asian, Native American, multiracial, and unknown ethnicities because they either represent only a small percentage of the patients or are not traditionally considered as underprivileged racial minority groups in the digital divide context  [11, 30, 41, [52] [53] [54].
Because patient portal use may be associated with office visits  [3, 56] , we also controlled for the number of outpatient office visits made by the patient in the previous month. We also controlled for patients' demographics, including their age, gender, marital status, and insurance. Patient marital status is a set of binary variables that includes married, significant other, divorced or separated, single, and others. Patient insurance status is a set of binary variables that indicates commercial, Medicaid, Medicare, self-pay, and others (eg, workers' compensation). Finally, we found the average adjusted gross income of each patient's zip code using the data from the Internal Revenue Service. We used the zip code-adjusted gross income, education attainment, and insurance status as proxies for the patient's economic status.
intervention (PCI) outcomes. Describing predictors of their utilization may identify opportunities to improve quality of care. Methods: The Nationwide Readmission Database was queried to identify ischemic heart disease (IHD) hospitalizations with PCI and IVUS/ OCT guidance from 2012 to 2018. Trends and predictive factors for IVUS/OCT utilization were analyzed via linear and multivariate logistical regressions. Three age groups (18-50, 51-70, 71 years) were considered. Results: Of 1,383,100 PCI hospitalizations with IHD (67. 83% AMI, 32. 17% non-AMI) as primary diagnosis, IVUS/OCT were utilized in 5. 74% of AMI and 8. 64% of non-AMI hospitalizations (p<. 001). IVUS/ OCT utilization over the years shows an increase (on average 0. 21% per year) within AMI hospitalization that is trending for significance (p¼.
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If data are publicly available, provide accession Case report-Access Microbiology-Yes (indicate where provided: page no/section/legend) n/a No organisms detected not required. Not detected. not required. Blinding not required. inclusion/exclusion criteria not required. number in repository or DOI or URL. If publicly available data are reused, provide accession number in repository or DOI or URL, where possible. Not detected. corrected. docx By Bijay Mirdha Sample definition and in-laboratory replication Yes (indicate where provided: page no/section/legend) n/a State number of times the experiment was replicated For all newly generated code and software essential Not detected. in laboratory for replicating the main findings of the study: Define whether data describe technical or biological State whether the code or software is available.
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Recruitment of the panel of experts Thirteen gastroenterologists from six Countries (Italy, the USA, the UK, Finland, France and New Zealand) were invited to participate by two of the authors (FB and AS) during and immediately after the 2019 Paris Symposium. The members of the task force have recognised international expertise on the diagnosis, clinical management and delivery of care for adult patients affected by various forms of CD and NCEs. Some of them have already participated to collaborative working groups on the definitions and diagnostic criteria of CD. 4 18-20  An external statistician was also enrolled to ensure unbiased management of experts' opinions and data analysis.
The LFIA-CTX Test The analytic performances of the LFIA-CTX test were similar to those of the β-LACTA TM test and the ESBL NDP test (Table  2 ). Indeed, 100% specificity was observed for all species while sensitivity was 100%, 75%, and 100% for Enterobacterales, P. aeruginosa, and A. baumannii, respectively (Table  2 ). The sensitivity for P. aeruginosa was comparable to those of the β-LACTA™ test and the ESBL NDP test, as the same three ESBLs producers (GES-5, SHV-2a, TEM-4) plus PME-1 producing P. aeruginosa were not detected. The presence of the genes in these isolates was confirmed by PCR (data not shown). Finally, the LFIA-CTX test detected cefotaxime hydrolysing enzymes efficiently in the 12 Acinetobacter spp. isolates tested.
Energy strategy analysis methodology To understand why and how these EPCIs hope to embrace the energy transition and produce renewable energy we studied their public discourse and action over the course of the year 2020. Using a qualitative approach, we gathered data via existing documents collection (climate plan, reports, communication materials, etc. ) and semidirective interviews with actors in these territories. In all, 55 interviews were conducted to reconstitute the history of the local energy strategy and to collect the interviewees' personal opinion on it and to cross-check their different point of views. They include: territorial public employees in charge of energy issues and political representatives (24 people), national administrations (10 people), energy companies (14 people), and not-for-profit organizations (7 people).
The interviewees were all involved in preparing, planning and adopting local energy policy or assessing, counselling and directly implementing renewable energy projects. This allowed us to interview most of the people implicated in the decision-making processes related to renewable energy in the four territories studied. The interviews covered several topics: the respondents' job description and functions, the strategies of their entities, the types of projects developed and the collaboration between actors to implement them. Therefore, we coded manually the interviews and gathered data through this analytical framework to characterize and compare the energy strategy deployed in each case study. The content of the discourse was analysed to identify key elements in the way the EPCIs consider the energy transition and the main arguments put forth to justify their choices (type of energy, business model, political endorsement …).
The strategies underlying the Territorial Air, Climate and Energy Plans and their implementation in the projects studied are identifiable through four main elements: 1) the stated and pursued energy objectives and the concerns driving the involvement of the EPCIs; 2) the means of action leveraged; 3) the role the EPCIs grant themselves; 4) and the relationships they maintain with other energy players and stakeholders in their territory. Therefore, we coded manually the interviews and gathered data through this analytical framework to characterize and compare the energy strategy deployed in each case study: --objectives and desired outcomes: quantitative targets expressed in % of production in relation to national and European objectives, and in relation to local uses and consumption; greater energy independence, incremental policy, territorial autonomy, benchmarking according to standards and targets of national policy, etc.
Acknowledgments We thank  Ambarish Kamalkar  and another anonymous reviewer for their helphul comments on the original manuscript. We are also grateful to all IPCC AR6 lead authors (LAs) and contributing authors (CAs) for their valuable contributions to WGI Chapter 8 and WGII Chapter 4. Yet, we would like to stress that this position paper does not commit all of them but only the authors of this synthesis. We particularly thank Stephane Senesi for Fig 2 and  Ben Cook  for Fig 3, previously published as Fig TS. 12e in WG1 Technical Summary and Fig 4. 18 in WGII Chapter 4, respectively. RAB was supported by the  Met Office Hadley Centre Climate Programme  funded by  BEIS  and  Defra. H. D. conceptualized the overarching objectives of the study, wrote the preliminary draft of all sections except Section 4, and prepared Fig 1 and Fig 4.
This proceedings article presents actionable research targets on the basis of the presentations and discussions at the 2nd Curing Coma National Institutes of Health (NIH) symposium held from May 3 to May 5, 2021. Here, we summarize the background, research priorities, panel discussions, and deliverables discussed during the symposium across six major domains related to disorders of consciousness. The six domains include (1) Biology of Coma, (2) Coma Database, (3) Neuroprognostication, (4) Care of Comatose Patients, (5) Early Clinical Trials, and (6) Long-term Recovery. Following the 1st Curing Coma NIH virtual symposium held on September 9 to September 10, 2020, six workgroups, each consisting of field experts in respective domains, were formed and tasked with identifying gaps and developing key priorities and deliverables to advance the mission of the Curing Coma Campaign.
With this goal, the CCC was formally launched in 2019 at the NCS Annual Meeting in Vancouver, BC, Canada. The National Institute of Neurological Disorders and Stroke (NINDS) initially collaborated with the CCC to organize a part I, 2-day virtual symposium in September 2020 to facilitate a broad discussion between various stakeholders, including CCC leadership, National Institutes of Health (NIH) representative, experts in coma science, industry partners, and patient advocates. The summary of the proceedings was published in the special CCC issue  [21]. Following the discussions of the first NIH symposium, six major workgroups (WGs) were created to investigate gaps and develop research priorities across six domains: (1) Biology of Coma, (2) Coma Database,  (3)  Neuroprognostication, (4) Care of Comatose Patients,  (5)  Early Clinical Trials, and (6) Long-term Recovery.
Coma Science Database Background A large international data set that captures data from patients with DoC is crucial to gain insights into mechanisms, predictors, and trajectory of recovery and to lay the foundation for future interventional trials. The coma science database WG conducted a needs assessment in 2020 to understand the acute data needs of the coma science community. The majority of survey participants were primarily involved with clinical research affecting patients with DoC. According to the survey, the missioncritical data needed to accomplish goals toward curing coma included patient-specific data, encounter-specific data, and psychometric data. Additionally, survey participants recognized that long-term follow-up data and high-fidelity and time-synchronous data are needed but not currently accessible.
The survey results, main research gaps, and challenges have been outlined in the proceedings article from the 1st symposium  [21]. A panel discussion at the time concluded that a way forward would include (1) creation of data dictionaries based on common data elements (CDEs), formulation of common language, and terminology as well as data structure framework, and (2) a large simple international database on patients with DoC that is built on CDEs. CDE development aims to streamline neuroscience clinical research using content standards that enable clinical investigators to systematically collect, analyze, and share data across the research community. The CDE project has been developed in collaboration with the NINDS to create CDEs specific to coma and DoC. A total of ten different WGs have been created to approach a variety of topics, including (1) clinical/ behavioral phenotype, (2) hospital course/confounders/medications, (3) imaging (4), electrophysiology,  (5)  biospecimens, (6) pediatric and other patient groups, (7) therapeutic interventions, (8) physiologic data,  (9)  outcomes and end points, and (10) goals of care/family data.