dataesr/scientific-paragraphs-categorization huggingface dataset:
The correlations between climate parameters and GDGT / pollen Table  1. Statistical results of the MAT and WAPLS methods applied to four surface pollen datasets and ten climate parameters (a). a) Only the five better fitting regression models for each climate parameter are shown. Model Database Climate k best k best k R 2 RMSE parameter R 2 (b) RMSE (b) selected (c) selected (c) selected (c) -27. 3 × [IIIc] -3. 3 × [IIa ] -26. 3 × [IIb] + 8. 5 × [IIb ] -5. 6 × [Ia] MAATmr6 9 0. 67 1. 1 155. 7 MAATmr6 = 12. 3 × 1 -52. 1 × [IIIa] -16. 9 × [IIIb] -25. 9 × [IIIb ] -41. 1 × [IIIc] -6 × [IIa] -10. 4 × [IIa ] -38. 5 × [IIb] -13. 3 × [Ia] -32. 8 × [Ic] MAATmr7 10 0. 68 1. 1 157. 2 MAATmr7 = 12. 3 × 1 -52. 6 × [IIIa] -16. 8 × [IIIb] -25. 3 × [IIIb ] -35. 7 × [IIIc] -6 × [IIa] -10. 5 × [IIa ] -37. 8 × [IIb] -15.
These local calibrations fit the best with the MAAT Ding from Ding et al. (2015) which is also a local calibration made on the Tibet-Qinghai plateau database. The global databases made on worldwide sites (De Jonge et al. , 2014b, a; Naafs et al. , 2017) provide MAAT model > MAAT real and large standard deviation (SD). The extreme MAAT values are attenuated with reconstructed temperatures higher by up to +5 to +10 • C in the Siberian basin and the Mongolian plateau, and lower by up to to -3 to -5 • C in the Gobi desert. Finally, the local calibrations performed on subtropical to tropical Chinese transects (Yang et al. , 2014; Thomas et al. , 2017)  have smaller SD but largely overestimate MAAT values due to the warmer conditions of the initial database sites.
Tian et al. , 2014;Cao et al. , 2014;Ghosh et al. , 2017 on local or global datasets (among others,Tian et al. , 2014;Cao et al. , 2014;Ghosh et al. , 2017, , Tierney et al. , 2019 in press). We tested both approaches on our datasets. The global br-GDGT -climate calibration artificially reaches higher R-squared than local ones due to the larger range of values of the climate.
Acknowledgements. We want to thank all the direct and indirect contributors to the global surface pollen dataset as well as the  Laboratory of Ecological  and  Evolutionary Synthesis  of the  National University of Mongolia  for its support during the field trip. We also express gratitude to  Laure Paradis  for her GIS advice,  Marc Dugerdil  for the help with Python fixing,  Jérôme Magail  and the  Monaco-Mongolia joint mission  for their technical and financial support in providing top cores and sediment samples from  Arkhangai , and  Salomé Ansanay-Alex  for her spectrometer expertise. We are grateful to the  ISEM team DECG  for financial support. For the analytical work completed at  LGLTPE-ENS de Lyon , this research was funded by  Institut Universitaire de France  funds to GM. improve this manuscript.
( Fig. 7B1 and 7B2) were tested. The MAAT reconstructions provide different responses to the three main bio-climate areas (parcel A1): if they properly estimate temperatures in the Siberian Baikal basin, they overestimate and underestimate them for the center of the northern Mongolian mountains and the Gobi desert, respectively. For precipitation (parcel B1), all the MAP mr , including the ones based on the local to regional databases, also misrepresent the extreme values: precipitation values are too high and too low for the Gobi desert and the Baikal basin, respectively. To conclude, the wider the dataset extension, the more alleviated the extreme values. Both on MAAT mr and MAP mr models, the 95 % interval shrinks with parameter addition, but the mean values do not necessarily get closer to the climate parameter measured value (the dashed line in Fig.
Tian et al. , 2014;Cao et al. , 2014;Ghosh et al. , 2017 on local or global datasets (among others,Tian et al. , 2014;Cao et al. , 2014;Ghosh et al. , 2017, , Tierney et al. , 2019 in press). We tested both approaches on our datasets. The global br-GDGT -climate calibration artificially reaches higher R-squared than local ones due to the larger range of values of the climate parameters involved (M AAT ∈ [-5; 30] in Naafs et al. (2017) soil world dataset against M AAT ∈ [0; 5] in this case study, inducing a lower signal/noise ratio). Despite the relatively lower R-squared value of 0. 62 scored by the MAAT mr5 inferred model compared with.
Having geographical proximity and a high volume of trade with China, the first country to record an outbreak of the new Coronavirus disease (COVID-19), Vietnam was expected to have a high risk of transmission. However, as of 4 April 2020, in comparison to attempts to containing the disease around the world, responses from Vietnam are seen as prompt and effective in protecting the interests of its citizens, with 239 confirmed cases and no fatalities. This study analyzes the situation in terms of Vietnam's policy response, social media and science journalism. A self-made web crawl engine was used to scan and collect official media news related to COVID-19 between the beginning of January and April 4, yielding a comprehensive dataset of 14,952 news items. The findings shed light on how Vietnam-despite being under-resourced-has demonstrated political readiness to combat the emerging pandemic since the earliest days.
Materials and Methods This paper reviews Vietnamese policy response, news and science journalisms related to COVID-19 recently. Findings were derived from the analysis of a database of recent policies, articles and the credibility of data sources in Vietnam. Extensive coverage was given to the pandemic in both the official press and academic journals as well as through reports, briefs and presentations by members of concerned organizations (e. g. , WHO). A Python-powered web crawler engine was used to scan the data from online newspapers in Vietnam, such as Tuổi Trẻ, Thanh Niên, VnExpress or Kênh 14, to name a few. Then, the scanned data were saved into a news analysis system, which is developed by. NET Core, for storage and future analysis. The data structure contains three main components:.
Materials and Methods This paper reviews Vietnamese policy response, news and science journalisms related to COVID-19 recently. Findings were derived from the analysis of a database of recent policies, articles and the credibility of data sources in Vietnam. Extensive coverage was given to the pandemic in both the official press and academic journals as well as through reports, briefs and presentations by members of concerned organizations (e. g. , WHO). A Python-powered web crawler engine was used to scan the data from online newspapers in Vietnam, such as Tuổi Trẻ, Thanh Niên, VnExpress or Kênh 14, to name a few. Then, the scanned data were saved into a news analysis system, which is developed by. NET Core, for storage and future analysis. The data structure contains three main components: • Projects & Data Sources: Settings for projects and news sources.
Using this system, we can set up sources and keywords. Furthermore, all tools and datasets will be maintained for future mining. We expect the dataset to keep growing over time, presenting us with new opportunities to extract deeper and more valuable insights. Using this system, we can set up sources and keywords. Furthermore, all tools and datasets will be maintained for future mining. We expect the dataset to keep growing over time, presenting us with new opportunities to extract deeper and more valuable insights. In this article, using five keywords related to COVID-19, namely: covid, ncov, corona, viem phoi (Vietnamese for pneumonia, which has some symptoms in common with COVID-19), sars-cov, between January 9 and April 4, the tool has collected 14,952 news reports on the topic of concern, as presented in Table  1.
Raw data were manually cleaned then categorized based on its characteristics, such as the timeline of COVID-19 cases, the timeline of international events regarding COVID-19, media reports and policy response from the Vietnamese government. Regarding the social media aspect, due to technical limitations, we could not scan information from Facebook. Thus, we used the remediation of social media on news outlets as a proxy to explore the social media aspect. Keywords that uniquely fit with the aspect, including 'mạng xã hội' (social media), 'cư dân mạng' (netizens), Facebook and Zalo, were used to search within the collected dataset. Furthermore, the data of the VN INDEX, which represents the changes in the Vietnamese stock market's prices during the COVID-19 pandemic, was also added to complete the dataset.
Finally, we store the cleaned data as a comprehensive dataset in excel files. The dataset (updated as of April 4, 2020) is available at Open Science Framework (OSF) (URL: https: //osf. io/4w9ef/; DOI: 10. 17605/OSF. IO/4W9EF)  [22]. Having organized the dataset, we then calculated descriptive statistics to illustrate how the Vietnamese government, news and science journalism respond to COVID-19.
Official Press Prior to the first case of COVID-19 in Vietnam, news on a "strange pneumonia" in China had circulated on Vietnamese media as early as the beginning of January 2020. Our dataset suggests news regarding this "strange pneumonia" first appeared on Báo Chính phủ (chinhphu. vn), Vietnam Government Portal and Sức Khỏe và Đời Sống [Health and Life] (suckhoedoisong. vn), the official news channel of the Ministry of Health, on January 9  [72, 73]. According to the article written by the Public Health Emergency Operation Center on Sức Khỏe và Đời Sống  [73] , public health experts expected high risk of having an outbreak in Vietnam because it was near the Tet holidays (or Chinese New Year). The following preventive measures had been proposed:.
This shows the positive signal of the Vietnamese scientific community to move forward with these global trends. The findings from Vietnamese hospitals and authors can, therefore, contribute to the database of global knowledge and expertise and may help to curtail this outbreak and prepare for future outbreaks. On April 3, one of the leading universities in Vietnam, the National Economic University, also released a report titled "Assessment of COVID-19 impacts on the economy and policy recommendations," which has been heavily covered on the media  [85]. Therefore, it appeared that researchers from hospitals and universities, rather than other types of institutions, have published more on COVID-19. This is consistent with the findings from  [86]  that university-affiliated authors in Vietnam tend to have higher research productivity than institution-affiliated peers.
Government officials further explained that data and information from four Public Health Emergency Operation Centers of Vietnam were directly connected to the Centers for Disease Control and Prevention USA and, therefore, shared openly to the global database  [107]. In the later periods, the emergence of strong political leaders such as Deputy Prime Minister Vu Duc Dam had a significant and positive influence on public perception of the Vietnamese government as well as the consensus and trust in Vietnam's efforts to fight against the pandemic. On social media, images and quotes of Deputy PM Dam appeared extensively on citizen's posts, which created a sense of solidarity and the belief in governments' efforts. Recently, the call from Prime Minister Nguyen Xuan Phuc on the whole nation's joint efforts in COVID-19 combat attracted public attention and support from individual citizens  [108].
Although Conditions α and α * cover voting environments, it is not always straightforward to check whether a given voting rule satisfies these conditions. In fact, the literature is not very rich in analyzing subgame perfect implementability of voting rules by checking the satisfaction of Conditions α and α *. Abreu and  Sen [1990]  shows that the plurality rule is not subgame perfect implementable whereas no scoring rule is subgame perfect * We thank Arunava Sen and Hannu Vartiainen for very fruitful exchanges and two anonymous reviewers for very useful comments. This project has been supported by the ANR-14-CE24-0007-01 (CoCoRIC-oCoDEC) and the project IDEX ANR-10-IDEX-0001-02 PSL MIFID. 1 A social choice rule f is subgame perfect implementable if there exists an extensive form mechanism Γ such that the set of subgame perfect equilibrium outcomes of Γ coincides with the outcome of f for any possible preference profile.
The science of cities seeks to understand and explain regularities observed in the world's major urban systems. Modelling the population evolution of cities is at the core of this science and of all urban studies. Quantitatively, the most fundamental problem is to understand the hierarchical organization of cities and the statistical occurrence of megacities, first thought to be described by a universal law due to Zipf [1, 2], but whose validity has been challenged by recent empirical studies [3, 4]. A theoretical model must also be able to explain the relatively frequent rises and falls of cities and civilizations  [5] , and despite many attempts [6, 7, 8, 9, 10] these fundamental questions have not been satisfactorily answered yet. Here we fill this gap by introducing a new kind of stochastic equation for modelling population growth in cities, which we construct from an empirical analysis of recent datasets (for Canada, France, UK and USA) that reveals how rare but large interurban migratory shocks dominate city growth.
Deriving the equation of city growth To understand city growth, we need a robust bottom-up approach, starting from elementary mechanisms governing the evolution of cities. Without loss of generality, the growth dynamics of a system (such as a country) of cities  of size  ! can be decomposed into the sum of an inter-urban migration term between metropolitan areas and an 'out-of-system' term that combines the other sources of growth: natural growth (birth and deaths) and migrations that do not occur within the system of cities (international migrations and exchanges with smaller towns). We denote by () the set of neighbours of city , ie. cities that exchange a non-zero number of inhabitants. On the four recent datasets of migrations that we use here (USA for 2012-2017, France for 2003-2008, UK for 2012-2016 and Canada for 2012-2016) we find for France and USA that () ∨  ! " where  ≈ 0.
5 (Extended data Figure  2 ). The British and Canadian datasets are fully-connected leading to  = 0. The time evolution of the population size  ! can then be written as: 𝜕 # 𝑆 ! = 𝜂 ! 𝑆 ! + ∑ 𝐽 $→! -𝐽 !→$ $∈'(!) (1) where the quantity  ! is an uncorrelated random variable accounting for the 'out-of-system' growth of city  and that we found in the data to be gaussian distributed (Extended Data Figure  3 ). The flow  !→$ is the number of individuals moving from  to  during the time. If there is an exact balance of migration flows ( !→$ =  $→! ), the equation becomes equivalent to Gibrat's model  [9]  which predicts a lognormal distribution of populations. Starting from this general equation (  1 ) is very natural as it amounts to write the balance of births, deaths and migrations but -as it is often the case of general basic equations -it is very difficult to use for making predictions.
)2. 1 O 1 5 ⁄ (1. 6) decreases exponentially at large times. This expansion shows that the probability distribution of city sizes is dominated at large  by the order  = 1 and converges towards a Pareto distribution with exponent  ≠ 1. The speed of convergence towards this power-law can be estimated with the ratio (, ) of the first and second terms of the expansion Eq. (  4 ) and leads to: 𝜆(𝑆, 𝑡) = < ' ; T𝑆(𝑡) ´𝑆 ⁄ V 5(1. 6) (5) where () ´ is the average city size. If () ≥ 1, the -exponent regime is not valid in the right-tail with threshold  at time. Estimates of  and for the four datasets show that finite-time effects are very important in general and that a power-law regime is only reached for unrealistically large city sizes (see discussion in the SI for details). Hence, the range of city sizes for which we can observe a power-law distribution may not exist in practice and there is no reason in general to observe Zipf's law or any other stationary distribution.
US migrations Data of migrations in the United States are taken from the 2013-2017 American Community Survey (ACS)  [43]. Aggregated Metro Area to Metro Area Migration Flows and Counterflows are directly given between 389 metropolitan statistical areas (MSA) in the US. More precisely, the American Community Survey (ACS) asked respondents whether they lived in the same residence one year ago and for people who lived in a different residence, the location of their previous residence is collected.
Data availability statement: The datasets used in this study are freely available from public repositories: the American community survey for the US data  [43]  available at the address https://www. census. gov/data/tables/2017/demo/geographic-mobility/metro-to-metromigration. html, accessed Feb. 21, 2020, the INSEE for the French data  [44]  available at the following link: https://www. insee. fr/fr/statistiques/2022291, accessed Feb. 21, 2020, the ONS data for the UK at https://www. ons. gov. uk/peoplepopulationandcommunity/populationandmigration/migrationwithint heuk/datasets/matricesofinternalmigrationmovesbetweenlocalauthoritiesandregionsincludingthecou ntriesofwalesscotlandandnorthernireland, accessed Jun 2, 2020 and the Canadian data at https://www150. statcan. gc. ca/t1/tbl1/en/tv.
Description of our sample Participants were 357 females and 292 males (mean age 33. 62 years, SD = 15. 44 years) (due to a technical error in the data collection, redistribution choices could only be analyzed for 626 participants). Regarding the socio-professional category, it turned out that managers and white-collar professions (34. 36%) and students (41. 60%) were overrepresented in our sample (both categories representing 75% of the sample). Regarding reported votes for the first round, our sample was clearly left-wing oriented, and voters for the two main right-wing candidates (Fillon and Le Pen) were underrepresented, whereas voters for Melenchon, Hamon, and Macron were overrepresented (Fig  1 ). Therefore, in subsequent analyses we focus on participants who reported having voted for Melenchon, Hamon, or Macron in the first round of the election (N = 506, 78% of the initial sample), given the lack of data for the other cases.
That result is even more surprising since they reported the most egalitarian views on income (M = 2. 07) compared to Hamon voters (M = 2. 60) and Macron voters (M = 3. 86), F(2, 503) = 69, p < 0. 001. Explanations of this finding in terms of age, sex, or socio-economic status are unlikely in our dataset as Melenchon voters and Hamon voters did not differ significantly on these variables (Table  1 ). In addition, we verified that our Status manipulation was truly random with respect to age, sex, or socio-economic status, which did not differ between overachievers and underachievers (Table  2 ). Here, we suggest one explanation for our finding that Melenchon voters were the most affected by Status manipulation. It is worth noting that these voters were also the most versatile at the end of the electoral campaign.
It has been several years since ride-sharing platforms such as Ola and Uber have entered the Indian market. As a type of matching service, mainstream economic theory predicts that they will bring economic efficiencies to hired transportation. In this study, we investigate the impact of ride-sharing on drivers of taxi cabs and auto-rickshaws in New Delhi through a mixed-methods study involving 60 drivers. We find mixed outcomes for drivers with little clear evidence of overall benefit. We saw no statistically significant impact of ride-sharing on drivers' average revenue per day, though the data is suggestive of income gains of 7-18% which seem likely to be due to longer hours driven. In contrast to the corporate marketing where driver autonomy and flexibility are oft-cited perks, our participants tended to report less autonomy and control with ride-sharing.
Data Collection We conducted 60 interviews in New Delhi, India, between January and June 2019, each consisting of a questionnaire with questions related to demographics and business as well as a semi-structured portion with open-ended questions. Interviews were conducted with three types of drivers: • Auto-rickshaw drivers who used Ola or Uber (Abbreviation: RU; 20 interviews) • Auto-rickshaw drivers who did not use Ola or Uber (Abbreviation: RN; 20 interviews) • Taxi cab drivers who used Ola or Uber (Abbreviation: TU; 20 interviews) All interviews were conducted verbally by the first author during hailed (and paid) rides. Interviews were conducted in Hindi through paid interpreters on all rides. The questionnaire portion asked about their demographic profile as well as the details of the costs and revenues of their driving-related work.
Simulation Conditions The coevolved communities that arose during the initialization were then used as initial communities for the evolving metacommunity simulations. For each of the three different levels of niche width (σ α ), we ran simulations for each three-patch metacommunity at different dispersal levels (d = 0, 0. 01, 0. 1) and different rates of environmental change (∆ = 0, 10 -5 , 4 × 10 -4. All of the 27 simulations ran for 50,000 generations, and all simulation parameters were set at t 0. Simulations were conducted in MATLAB R2017a version 9. 2. 0. 556344.
Rows are increasing levels of environmental change (∆ = 0, 10 -5 , and 4 × 10 -4 from top to bottom) and columns are increasing levels of dispersal (d = 0, 0. 01, and 0. 1 from left to right). Supplementary Code: Code for simulation and results of 27 simulation conditions available on the GitHub page of J. H. Pantel (https://github. com/jhpantel/EcoEvoMC). Author Contributions: Conceptualization, J. H. P. ; methodology, J. H. P. and A. P. F. ; software, J. H. P. and A. P. F. ; validation, J. H. P. and A. P. F. ; formal analysis, J. H. P. and A. P. F. ; investigation, J. H. P. and A. P. F. ; resources, J. H. P. and A. P. F. ; data curation, J. H. P. and A. P. F. ; writing-original draft preparation, J. H. P. ; writing-review and editing, J. H. P. and A. P. F. ; visualization, J. H. P. and A.
Acknowledgments: We would like to thank  N. Loeuille  for his guidance in formulating research questions. The authors acknowledge  William & Mary Research Computing  for providing computational resources and/or technical support that have contributed to the results reported within this paper. URL: https://www. wm. edu/it/rc. A. P. F was supported by the  William &   Mary 1693 Scholars Program. J. H. P. acknowledges support from the  The Richard Lounsbery Foundation , for the project  Urbanization  and  Land Use Change Effects on Aquatic Biodiversity.
Online population-based survey A population-based survey using anonymous questionnaire was conducted online to evaluate if people living in the Haut-Rhin department had symptoms commonly experienced in case of COVID-19 infection, when and which ones. In order to achieve a quick deployment to reduce memorization bias, we followed a fast track procedure to build protocol and get legal and ethical agreements. After testing the questionnaire on four voluntary families in France and Switzerland, the study was approved by the legal and ethical agreements of Clermont Auvergne University Ethic Committee on April 10 th 2020, and Clermont Auvergne University Personal Data Protection Management authorities and National Center for Scientific Research Personal Data Protection Management authorities both on April 21 st 2020.