dataesr/scientific-paragraphs-categorization huggingface dataset:
The presented methodology on this paper proposed the use of a national level multi-regional environmentally extended input output table (MRIO) and an extract of the labor force survey, describing local employment, for the construction of a city-level circularity measure. This measure is computed by combining both datasets and quantifies as the number of local circular jobs on the city. This is achieved by classifying all economic sector by its circular activity and using material import dependencies to identify the resource dependency of individual economic sectors. The main advantage of this approach is that both required datasets are available in most cities around the globe, this is important for us to include cities with a low data infrastructure. The obtained results from this approach represent the circularity of a city by quantifying the total number of existing local circular jobs.
Data and methodologies The stock index data of the seven ASEAN countries considered in this study were obtained from Thomson Reuters's financial data vendor at daily, weekly and monthly frequencies. All variables are log-transformed. The sample period runs from January 1, 2009 to May 4, 2022, excluding holidays, and contains 3,480 observations for each market. The choice of countries and sample period were subject to the availability of stock market data suitable for empirical analyses in the aftermath of the global financial crisis. Table  A1  in Appendix describes the stock market indexes used in the sample and their data sources, while Table  A2  provides statistical descriptions of the variables by level, log level and first difference of log. In terms of stock market returns, we note that all markets posted positive average performances and that markets in less developed countries (Cambodia, Indonesia, Philippines, Thailand, and Vietnam) appeared to outperform even the most developed countries (Singapore and Malaysia) during the sample period.
5 (see Supplementary Information); (iii) HMEs bound at i may spread a mark to a distal nucleosome j only if they are placed in very closed proximity by a loop extruding factor (like cohesin or condensin) (67-70) translocating along the chromatin, leading to P c (i, j) = exp ( -|j -i|/s 0 ) (see Supplementary information and Supplementary Figure  S2 ). Stochastic simulations. For a given set of parameters, the stochastic dynamics of the system is simulated using the standard Gillespie algorithm (71) implemented on Python (can be downloaded at https://github. com/physicalbiology-of-chromatin/Painter-Model). In all our work, we simulated the dynamics of n = 201 nucleosomes corresponding to ∼40 kb-long genomic region. Starting from a random initial macro-state (i. e random choice between U or M states for each nucleosome), the system relaxes to a steady state.
ACKNOWLEDGEMENTS We are grateful to  Geneviève Fourel ,  Kapil Newar ,  Gaëlle Legube  and  Raphaël Mourad  for fruitful discussions. We thank  PSMN (Pôle Scientifique de Modélisation Downloaded  from https://academic. oup. com/nar/advance-article/doi/10. 1093/nar/gkac702/6677333 by  National Pingtung University of Science  and  Technology user on 29 August 2022 Nucleic Acids Research, 2022 19 Numérique)  and  CBP (Centre Blaise Pascal)  of the  ENS de Lyon  for computing resources.
FUNDING Agence Nationale de la Recherche  [ ANR-18-CE12-0006-03  to  D. J. ,  ANR-18-CE45-0022-01  to A. Z. B. , D. J. ,  ANR-21-CE45-0011-01  to D. J. , C. V. ]. Funding for open access charge:  Agence Nationale de la Recherche.
Acknowledgements This work was supported by the  ANR JC/JC  grant " Supertrack "  ANR-16-CE09-0007 , by an  FRC   Emerging Investigators grant , by the  ERC   Consolidator grant  BrightSens  648528 , and by the  "Prix Espoirs de l'Université de Strasbourg ". The authors acknowledge the support and the use of resources of the  French Infrastructure for Integrated Structural Biology FRISBI   ANR-10-INBS-05  and of  Instruct-ERIC  and especially  C. Crucifix  for help with electron microscopy.
(1) , GHI = DHI + DNI. cos θ ( 1 ) where GHI is the global horizontal irradiation, DHI is the diffuse irradiation on the horizontal plane, DNI is the direct, or beam, normal irradiance, and θ is the solar zenith angle. The determination of the GHI may also be achieved indirectly by combining DNI and DHI measurements and Eq. (  1 ), which minimizes the GHI directional measurements error; however, the most accurate measurement procedure for DNI and DHI usually requires a sun-tracker system which presents higher costs, making a single sensor set in horizontal the preferred solution for GHI measurements in most cases. In high-end solar monitoring stations, it is common practice to measure the 3 components of irradiance and compare them to verify data quality  [4] [5] [6]. In practical measurements, there can be deviations from the ideal behaviour (Eq.
Background: Scientific researchers who wish to reuse health data pertaining to individuals can obtain consent through an opt-in procedure or opt-out procedure. The choice of procedure may have consequences for the consent rate and representativeness of the study sample and the quality of the research, but these consequences are not well known. Objective: This review aimed to provide insight into the consequences for the consent rate and consent bias of the study sample of opt-in procedures versus opt-out procedures for the reuse of routinely recorded health data for scientific research purposes. Methods: A systematic review was performed based on searches in PubMed, Embase, CINAHL, PsycINFO, Web of Science Core Collection, and the Cochrane Library. Two reviewers independently included studies based on predefined eligibility criteria and assessed whether the statistical methods used in the reviewed literature were appropriate for describing the differences between consenters and nonconsenters.
Search Strategy and Study Selection The search was performed in August 2021. The databases searched were PubMed, Embase, CINAHL, PsycINFO, Web of Science Core Collection, and the Cochrane Library. Databases were searched using a predetermined strategy, as detailed in Multimedia Appendix 1. Two reviewers independently selected the studies that satisfied the eligibility criteria (see Inclusion Criteria). In the first step, selection was based on the title and abstract (YdM and ALF), and in the second step, the full texts were checked (YdM and YWJ or MGOV). Discrepancies in reviewer selection were resolved by discussion and consulting with another reviewer or coauthor. The selection process is described using a PRISMA flow diagram  [25]  (Figure  1 ).
Research Topics Studies must focus on the scientific research reuse of routinely recorded health data pertaining to individuals and on health data routinely recorded in relation to good clinical practice involving individuals. Studies were only included if individuals or legal representatives (any substitute decision-makers appointed under the relevant law) to whom the data pertain were involved in the consent procedure, as opposed to studies in which only the health care provider provided consent. Studies must have implemented an opt-in procedure, opt-out procedure, or a combination of opt-in and opt-out consent procedures to be included.
Exclusion Criteria Studies were excluded if the opt-in or opt-out procedures for the secondary use of health data followed earlier consent for study participation, for instance, for participation in a survey or intervention study. Studies were excluded if the opt-in or opt-out procedure for secondary use of health data was an integral part of broader consent for study participation, for instance, for participation in a survey or intervention study. Studies were also excluded if consent was obtained in a hypothetical setting (eg, the participants were asked in which situations they would be willing to provide consent for the reuse of health data containing information on their treatment). Editorials, essays, literature reviews, and other nonempirical studies were also excluded. However, the reference lists of the relevant literature reviews were checked to identify potentially relevant empirical research.
Data Extraction and Synthesis For each included study, information relevant to our review questions was extracted using a prestructured format. This information included authors and country, research questions for which routinely recorded health data were used, the setting, type of consent procedure (opt-in, opt-out, or a combination of both), whether the consent was study specific or broad, the method of obtaining consent, the person who provided consent, and the characteristics of consenters and nonconsenters. To answer the review questions regarding consent rates, we also extracted the number of individuals approached and the number of individuals who gave consent. We pooled the extracted data regarding consent rates stratified by consent procedure (opt-in or opt-out) and the outcome of interest (broad vs specific consent, representative vs individual consent, and different methods of informing individuals).
In the case of missing data regarding the numbers of individuals approached, individuals who responded, consenters, or nonconsenters, where possible, we deduced the numbers and percentages based on the numbers that were provided by the study concerned. For instance, for opt-in procedures, if the numbers of individuals who were approached and who gave consent were known, we could calculate the nonconsenters by subtracting the consenters from the individuals approached. To answer the review questions regarding the representativeness of the study sample, we extracted and described all data describing statistical differences in characteristics between consenters and nonconsenters or differences in characteristics between consenters and the total study population. In other words, we extracted information on consent bias arising from the type of consent procedure used.
Strengths, Limitations, and Recommendations for Further Research To the best of our knowledge, this is the first systematic review assessing the consequences of opt-in procedures versus opt-out procedures for consent rates and consent bias in research where health data routinely recorded by health care professionals are reused. Another strength of our review is that we used a broad search strategy in 6 literature databases and performed a statistical quality assessment of the included studies. However, regarding our results, the following limitations should be considered. First, only 2 studies implemented an opt-out procedure to obtain authorization for the reuse of routinely recorded health data. Therefore, our results must be interpreted with caution, and further research is required to validate the results.
Further research on these issues is necessary to strengthen the indications. Fourth, 73% (11/15) of reviewed studies reused data recorded in a hospital setting. We suggest further empirical research to explore whether the results of our review will be similar in other settings. In addition, almost all studies involved patients diagnosed with 1 specific condition. Only 4 studies examined the general population. Patients with a specific diagnosis will probably be more engaged with a study topic related to their illness. This is likely to increase their tendency to consent to reusing health data. Whether this is the case cannot be determined from our results; therefore, we recommend further studies focusing on consent procedures in more general health settings to assess the effect of this on consent rates and consent bias.
In all cases, the Amerindian parental populations were inferred by sampling local indigenous communities, selected to be as "pure" as possible (although this terminology was not used, the idea was always to select an isolated population that had been as free as possible from the effects of mestizaje). In most cases, the African component was based on internationally used reference populations, such as the HapMap's sample of Yoruba from Ibadan, Nigeria  (International HapMap Consortium 2005). Unusually, in one Colombian study, a local black population from the Pacific coast region was used  (Rojas et al. 2010). The European component was assessed using international datasets, such as the HapMap's sample of Utah residents of northern and western European descent. The use of parental populations implies a temporal distancing, taking us back to the "original" encounter between three continental populations.
Acknowledgements This article was prepared during a  British Academy Wolfson Research Professorship. Some of the material in the article draws on Wade (2017). The material on genomics derives from a project " Race, Genomics and Mestizaje (Mixture) in Latin America: A Comparative Approach " funded by the  UK Economic and Social Research Council  (grant  RES-062-23-1914 ) and the  Leverhulme Trust  ( RPG-044 ). The project was based at the  University of Manchester  and ran from January 2010 to March 2013. It was directed by myself, with co-directors  Carlos López Beltrán ,  Eduardo Restrepo , and  Ricardo Ventura Santos ; researchers  Vivette García Deister ,  Michael Kent ,  María Fernanda Olarte-Sierra , and  Ernesto Schwartz-Marín ; and research assistants  Adriana Díaz del Castillo ,  Verlan Valle Gaspar Neto ,  Mariana Rios Sandoval ,  Roosbelinda Cárdenas , and  Abigail Nieves.
Standard protocol approvals, registrations, and patient consents Approval was obtained from the local ethics committee or institutional review board at each trial center, and all patients provided written informed consent. The trials were conducted in accordance with the International Conference on Harmonisation guidelines for Good Clinical Practice and the principles of the Declaration of Helsinki. The trials are registered with ClinicalTrials. gov, NCT02028884 (SAkuraSky) and NCT02073279 (SAkuraStar).
Conclusion In conclusion, this analysis of safety data from the SAkura studies provides evidence that the favorable safety profile and tolerability of satralizumab are sustained with long-term treatment both as monotherapy and in combination with baseline IST in patients with AQP4-IgG-seropositive and AQP4-IgG-seronegative NMOSD. These results are promising, given the need for minimizing safety risks associated with long-term therapy use in patients with NMOSD. This study adds to the current experience of IL-6R inhibition in patients with NMOSD and other inflammatory diseases; knowledge obtained from this analysis will aid in optimizing the clinical benefit for patients. The long-term safety and efficacy of satralizumab continues to be monitored in the ongoing OLE study, SAkuraMoon (NCT04660539), which will evaluate patients with NMOSD who have completed the SAkuraSky and SAkuraStar OLE periods.
In France, a study using the 2010 French national health care database showed that following a hip fracture, dialysis patients have a significantly greater mortality rate than those without dialysis, 12% for men and 8% for women. They also have a longer hospital stay in the intensive care unit  [13]. In the Dialysis Outcomes and Practice Patterns Study (DOPPS), the annual rate of hip fracture in dialysis patients varied from 1. 2 to 4. 5% according to country  [28] , with a fracture risk, compared to the general population, that was 1. 5 to 8 times higher and a risk of death that was also 3. 7 times higher than in the general population. The highest risk of death was seen during the first month following the hip fracture, and the principal causes of death were cardiovascular complications and infection  [28].
Modern science delivers other outputs, mostly digital, like datasets, software, algorithms or protocols, and it delivers highly skilled people through specialised education and mentoring. Multidisciplinary collaborations are required to address new scientific questions arising from increased complexity and that is another aspect of this evolution. More and more researchers from different domains, from biology and physics to economics, anthropology or humanities, work together in the boundaries of areas of knowledge. One of the actions included in the first Policy Agenda for the European Research Area, for the next three years 2022-2024, is to advance towards the reform of the assessment system for research, researchers and institutions to improve their quality, performance and impact. We consulted a variety of stakeholders in 2021, including organisations representing researchers, public funders, private funders, universities, research centres, academies, national evaluation agencies and policymakers, and we received strong support for the objective of ensuring a combination of qualitative and quantitative indicators to evaluate research and researchers without compromising on objectivity and peer review.
All the trials selected were governed by the FDA Amendments Act and were supposed to post their results. However, three years after the study was completed 69% of the trials had no results posted at the ClinicalTrials. gov register and half of them had no results publicly available, meaning no results that were either posted or published. We also now have access to data for France thanks to the French Open Science Monitor 6 whose last edition was made public last week. It shows that only 57% of the clinical trials with at least one site in France have their results available, with some difference according to the sponsor: 76% for industry-led trials and 31% for academic-led trials. A very important initiative and tools have been developed by Ben Goldacre and his team at Oxford University  7.
They developed the TrialsTracker 8 , which identifies all the studies that have to post their results on ClinicalTrials. gov and on the EU Clinical Trial Register and data mines whether they actually fulfil the law. The number of trials overdue, meaning that they should have posted their results but have not, increases over time. Compliance, meaning posting results one year after the study was completed, has increased slightly, but remains low and currently stable at 40%. When you assess the compliance with the requirement to report on the EU Clinical Trial Register the team evaluated 7,274 completed trials and they found that only 49% actually reported results, 68% for industry-funded trials and only 11% for academic trials. What are the consequences? Of course, first, we do not have access to the results and cannot make evidence-based decisions.
When the results were negative, showing that there was no evidence the treatment had any effect, 68% were not published. Further, the author tried to do a meta-analysis, summarising all the data, using first only the data that were published and compared it to the data including all trials that were published and not published. This showed that meta-analysis of journal dataset, using only data that were published, showed an increase in effect size of 32%, from 11% to 69%, according to the individual drug evaluated. What could be done? We are meta-researchers and so we always try to find easy low-cost interventions that could improve research. Here we propose to send an email reminding trialists of the legal requirement to post results on ClinicalTrials. gov. We identified 379 trials that met the FDA requirements but did not post their results on the registry one year after the completion of the trials  10.
The results were very disappointing because out of 160 articles, 80 in each group, only two datasets were shared in each group, so very, very little and no difference  14. To this point, and this is my last point, the importance of always evaluating the initiatives and proposals -we must make science more reproducible -and there is a final example. This has not yet been studied in a randomised trial. It is a tool called Discrepancy review  15. This is a peer review intervention that would try to reduce undisclosed discrepancies between registrations and publications. They have a set of guidelines and they would have a separate reviewer who would basically check all these aspects. They would do nothing else. They would not review the rest of the paper. They would just be checking whether the paper disclosed deviations from the final publication in the registry.
To go a step further "A lot of work has gone into making ClinicalTrials. gov work, but what seems to be the crucial issue is that even when authors are mandated to register their trial or their study and so forth you also need to have oversight as to whether or not they give all the necessary information. For instance, do they say exactly when they measure what they will measure? Do they say how? Do they say out of 10 tools, which is the primary one? ClinicalTrials. gov is improving in that in the sense that recent registrations are better, but there are still problems there. " "With data sharing, again clinical trial platforms would be a great tool, at least for aggregate data sharing, where, although it is not individual patient data, it is still crucial for meta-analysis and reviews. However, even there again you have to always have in mind that it is not enough to have a registry.
You need oversight. There are many examples from ClinicalTrials. gov of researchers or whoever completes the study record putting inadequate information, incomplete information, unusable information and so on. I think the tool could be used, but again what we need to fix is the problem of how we offer support for implementation and from whom. This is the same for journals. Who checks that you did what is required?" "In experimental clinical psychology, the first step of a PhD is you try to get results that are similar, in the same ballpark, as the seminal studies that inspired you. During my own PhD, I was not. I was getting the opposite results. This was one of the first things that drew my attention. I was starting to look for explanations. I noticed that so many things were not really reported in the original papers I was using, so it was impossible for me to know what I was doing wrong or differently because there was not enough information.
The frequently quoted reasons are they are not interested in the results and they do not have time to submit results for publication. The reasons for selective outcome reporting mirror those of publication bias. Investigators' misconception that the editors favour positive results was the main reason for not publishing the results. Also, there is an unawareness of the seriousness of underreporting. On the other hand, there is no evidence that peer reviewer suggestions or the editors' decisions are influenced by the nature and direction of the findings. In summary, it was mainly the researchers' problem. We should always submit our results for publication regardless of the direction and the nature of the finding. To end on a high note, how do we address reporting biases? Both speakers have touched upon trial registration and a result database.
I will discuss data sharing and access to study documents. There are also reporting guidelines and core outcome sets that people can follow. Beginning with the early studies, it became quite clear that to address reporting and publication bias we need to have a full account of all the studies from its beginning. The study of publication reporting biases and their consequences has led to legislation and policy mandating trial registration. In 1997, the Food and Drug Administration Modernisation Act required that all the drug trials of severe and life-threatening conditions must be registered. As a result, in response to that legislation, the National Library of Medicine of the National Institutes of Health in the US launched ClinicalTrials. gov, the trial registration database in 2000. However, the registration had not taken off until the International Committee of Medical Journal Editors (ICMJE) made a requirement of prospective registration of trials before the trial results can be published by the ICMJE journals.