dataesr/scientific-paragraphs-categorization huggingface dataset:
Selection of the U. S. and French plans We selected 36 multi-issue local climate change adaptation plans of small and mid-size cities (population between 50 0 0 and 30 0,0 0 0 people), representative of diverse climate types and geographic regions of the US and France. The selection of adaptation plans is fully explained in  [1, p4]. Online databases and bibliographic review were used as a departure point to identify communities with existing climate adaptation plans and their umbrella organizations. We used Google searches to locate websites of the cities, the published plans, and other additional documents (annexes, prior plans and related reports). The last access date of the plans has been specified in the record cards  [2]. Population numbers were obtained from the national censuses' websites  [ 3 , 4 ]  and climatic types of each location were identified based on Köppen classification  [5].
French climate adaptation plans were located through the national ADEME (Agence de l'environnement et de la maîtrise de l'énergie -French Environment and Energy Management Agency) database  [6]. The sample includes case studies from all climate zones and diverse geographic regions of France (Atlantic and Mediterranean coasts, the Alps and Massif Central, and overseas territories as Martinique). Examination of completion of adaptation plans by the communities meeting our criteria has led us to the sample of 16 Territorial Climate, Air, and Energy Plans 1  (PCAET/PCETs) of 18 urban communities. The selection includes plans of 7 "communautés urbaines " (CU), 5 "communautés d'agglomération " (CA), and 3 "communauté de communes " (CC) (see Fig. 1A  in  [1]  and Table  2  ). Definitions of these local administrative divisions in France are available in Table  1.
Some exceptions should be noted for French communities: the PCAET "Ouest 06 is a joint climate adaptation plan by three adjacent small cities (Sophia Antipolis, Pays de Grasse and Cannes Pays de Lérins) and the adaptation plan of Saint-Etienne Metropole covers an ensemble of suburban and rural communities, higher than 30 0,0 0 0 people, adjacent to the main mid-size city of Saint Etienne. To locate the U. S. climate adaptation plans we used online datasets of the Georgetown Climate Center Adaptation Clearinghouse  [7]  , ICLEI USA  [8]  , Local Model Forest Policy Program Climate Solutions University [9] , and the U. S. EPA Climate Change Adaptation Resource Center  [10]  ; independent reports, and scholarly reviews to identify cities meeting our selection criteria. The complete list of bibliographic sources can be found in Lioubimtseva and da Cunha  [1].
99, Excellent 4. Complete analysis of the scores can be found in Lioubimtseva and da Cunha  [1]. To protect information about quality scores of individual adaptation plans, we have excluded raw quantitative scores generated through the study from the publication. For the purpose of this open access publication the ranking scores for criteria and qualitative total scores of plans have been masked and replaced by the Boolean data (Yes or No), where No means < 1 and Yes means > 1. The criteria ranked as 4 are highlighted in the dataset as exemplary strong points of each plan. Such format is chosen to guide users to examples of strengths in each climate adaptation plan without publicly disclosing all assessment scores.
A more in-depth description of the social context of adolescents in each of the GEAS sites is provided by Mmari et al  [25]  who shed light on the family and peer relationships, adversities, school opportunities, and resources of young adolescents living in these impoverished communities and discussed the differences across sites and by gender. The three Indonesian sites were combined into one sample for the purpose of this analysis. All GEAS sites shared the same study protocol and survey instruments, although sampling strategies and data collection modes varied as explained elsewhere  [25]. In each site, the study took place in a poor urban setting and included a convenience sample of adolescents between the ages of 10e14 years, who provided assent and received parent consent to participate.
Each GEAS setting received local ethical approval and was also approved by the Johns Hopkins Bloomberg School of Public Health Institutional Review Board. From the original sample of 9,990 adolescents surveyed across the four settings, 8,977 were retained in the current analysis after excluding 1,013 cases (10%) with missing data on any of the 17 gender norm questions that contribute to our primary outcomes. The final analytic sample comprised 2,767 adolescents in Kinshasa, 1,657 in Shanghai, 618 in Cuenca, and 3,935 in Indonesia, each corresponding to 97. 4% of the original sample size in Kinshasa, 94. 1% in Shanghai, 87. 8% in Cuenca, and 84. 0% in Indonesia. Sensitivity analysis comparing results among respondents of Cuenca and Indonesia included in the analysis and those excluded indicated that excluded individuals had slightly less stereotypical views than participants who provided complete answers.
Acknowledgments This study was conducted with support from the  UNDP-UNFPA-UNICEF-WHO-World Bank Special Programme of Research, Development and Research Training in Human Reproduction (HRP) , a co-sponsored programme executed by the  World Health Organization (WHO). Support was also provided by the  Oak Foundation  [ OCAY-17-649 ],  Bill & Melinda Gates Foundation  [ OPP1125119 ,  OPP1197258 ], the  Packard Foundation  [ 2017-66517 ], and the  United States Agency for International Development  [ AID-OAA-A-15-00042 ]. ".
The new high-resolution CO2 record during the early Holocene We obtained 99 data points that cover 622. 14-539. 06 m at SNU, corresponding to 11. 7-9. 0 ka (Figure  1 ). To extend the record to 7. 4 ka, we made a composite dataset using a previous CO2 record from the Siple Dome ice core covering 9. 0-7. 4 ka measured by the needle cracker system at OSU  (Ahn et al. , 2014b)  (Figure  1 ). Between 2 and 6 replicates (2. 6 and 2. 4 on average for SNU and OSU data, respectively) from individual depth intervals were analysed. The standard error of the mean of replicates from the same depth interval was 0. 8 and 0. 5 ppm on average for SNU and OSU data, respectively. The sampling resolution is ~30 years for 11. 7-9. 0 ka and ~15 years for 9. 0-7. 3 ka. To make a composite record of atmospheric CO2, we tested for bias between the two data sets.
Siple Dome samples from 7 depth intervals between 538. 55-490. 16 samples were analysed at both laboratories  (Ahn et al. , 2014b). The SNU measurements were higher than the OSU measurements by 0. 3±0. 7 ppm (1σ) on average, indicating that the SNU and OSU results agree well (Table  S2  in SI). The small offset of 0. 3 ppm was added to OSU data before combining them with the SNU results.
Comparison with existing CO2 records for the early Holocene The new atmospheric CO2 record from Siple Dome was compared to the existing CO2 data from Dome C measured using the needle cracker at University of Bern (UB)  (Monnin et al. , 2001; Monnin et al. , 2004)  and the existing CO2 data from the WAIS Divide ice core measured by the needle cracker at OSU  (Marcott et al. , 2014) (Figure S2 in SI). On multi-millennial time scales, the baseline levels of the Siple Dome and WAIS Divide CO2 records  (Marcott et al. , 2014)  are higher than those from Dome C  (Flückiger et al. , 2002; Monnin et al. , 2004)  and Taylor Dome  (Indermühle et al. , 1999) records (Figure S2 in SI). The CO2 offset between the Dome C and Siple Dome ice cores is 3-6 ppm. The offset between Siple Dome CO2 data in this study and other CO2 data sets might be related to differences in the analytical methods used to make the measurements.
, 2004). Nehrbass-Ahles (2017), discussed CO2 offsets during the Holocene (11. 7-0 ka). For the early Holocene, five datasets were compared: CO2 from the WAIS Divide ice core measured by the needle cracker at OSU  (Marcott et al. , 2014) , CO2 from the Siple Dome ice core measured by the needle cracker at OSU  (Ahn et al. , 2014b) , CO2 from Law Dome measured by sublimation at UB  (Eggleston, 2015) , CO2 from Talos Dome measured by the Centrifugal Ice Microtome (CIM) at UB, and CO2 from Dome C measured by the needle cracker at UB  (Monnin et al. , 2001; Monnin et al. , 2004). The individual datasets show similar patterns of CO2 variability over the early Holocene. Offsets among ice cores are lower during the late Holocene but become larger during the early Holocene. During the early Holocene, the largest offset was between Dome C and Law Dome, up to 12 ppm.
Two main cooling events in Greenland are recorded at ~11. 4 and ~8. 2 ka  (Rasmussen et al. , 2007). The well-known 8. 2 ka cooling event is mainly influenced by the collapse of the Laurentide ice sheet  (Merz et al. , 2015)  rather than by solar forcing; when temperature was colder in Greenland at ~11. 4 ka, solar forcing was higher, not reaching a minimum at until ~11. 2 ka. It is also elusive whether solar forcing has an influence on climate in Greenland at ~11. 4 ka  (Mekhaldi et al. , 2020). Darby et al. (2012)  presented proxy data from the coast of Alaska reflecting the Arctic Oscillation (AO) over the past 9. 0 ka. This study found 1,500-year cycles of AO estimated using a proxy of sea-ice drift in the Arctic Ocean, which is similar to the cycles of IRD in the North Atlantic. But there is no significant linear relationship between AO and solar activity on millennial time scales during the 9.
Acknowledgements. Financial support was provided by  Basic Science Research Program  through the  National Research Foundation of Korea (NRF)  ( NRF-2015R1A2A2A01003888 ;  NRF-2020M1A5A1110607 ). This research was also partly conducted under US  NSF grants  ( OPP 0944764  and  ATM 0602395 ) to EB. Our special thanks go to  Eunji Byun ,  Jisu Choi , https://doi. org/10. 5194/cp-2021-113Preprint. Discussion started: 25 August 2021 c Author(s)  2021. CC BY 4. 0 License.
Acknowledgements Earlier drafts of this paper have been presented at  Università di Genova , and at the  ECPR Joint Sessions Workshop on Political Normativity. We are particularly grateful to  Zoltán Gábor Szűcs  and  Ben Cross  for detailed written notes, as well as to two anonymous referees for their insightful comments and challenges. Funding Burelli: Funded by  PRIN 2017 'Deceit and Self-Deception. How We Should Address Fake News and Other Cognitive Failures of the Democratic Public '. Destri: Funded by VoiCED -H2020-MSCA-IF-2018 European grant, project number  836571.
Methods The program Dstretch (plugin to ImageJ) was used for highlighting red paintings in digital pictures. Painted and nonpainted areas were analyzed by x-ray fluorescence spectrometry with a device developed by the Laboratoire d'Archéologie Moléculaire et Structurale and based on a bullet x-ray source from Moxtek (USA) and a 25-mm 2 silicon drift detector from Amptek (USA). CT was carried out with a micro-CT scanner General Electric v|tome|xs at CNES, Toulouse. Visualization and analysis of CT data were realized with VGStudio MAX (Volume Graphics).
We conducted spectral analyses with the free computer software package Praat (version 6. 0. 29). In Fig. 4 , graphs 1 to 3 show the average spectra of three notes produced by the musician. The spectrum displays the fundamental frequency F0 of each note (256, 265, and 285 Hz, respectively, representing each time an interval of approximately ½ tone in a tempered musical system), as well as several harmonics whose frequencies are whole multiples of the F0. In addition to the F0 and harmonics, the analyses showed the presence of parasite energy corresponding to the noise described in the qualitative analysis of the sound. Note 3 (graph 3) contains the most noise. The spectrum also displays a decrease in energy according to the frequency. The lowest note is close to C and the two others are respectively close to a C-sharp and a D, equaling a halftone each time.
Acknowledgments: We thank  F. Bourcier ,  Centre National d'Etude Spatiales, Service Laboratoire et expertises, Toulouse , and  J. Uzanu  ( ELEMCA, Labège ) for help in carrying out the CT scan of the object;  M. Quesnel  of the  Clinique du Parc  for medical scanning and Benjamin Moreno-IMA solutions for 3D processing;  P. Dalous , curator at the Natural on February 11, 2021 http://advances. sciencemag. org/Downloaded from.
To identify relevant literature, we conducted an extensive keyword search in online databases such as EBSCO, JSTOR, and Google Scholar. The keywords included "marketing standardization," "standardization," "marketing adaptation," "adaptation," "global marketing strategy," "international marketing strategy," "performance," "sales," "profit," and "growth. " Five criteria guided our article selection. First, similar to recent practices in systematic literature reviews  (Paul & Rosado-Serrano, 2019; Randhawa et al. , 2016) , we limited the search to journals listed in the Social Science Citation Index (SSCI) with an annual (2018) impact factor of at least 1. 0. Second, we restricted the time frame of our search to 1989-2019. We chose 1989 as a starting point, because most work on the link between marketing standardization/adaptation and performance was sparked by pioneering contributions in the late 1980s  (Jain, 1989)  and early 1990s  (Samiee & Roth, 1992 ).
Several reasons justify our choice. First, Mexico exhibits a very high level of income inequality with the fourth highest Gini index of 0. 46 among OECD members in 2016  (OECD, 2019). Second, overweight and obesity have rapidly increased and are now predominant: one-third of Mexican adults are obese and two-thirds are overweight  (NCD-Risk Factor Collaboration, 2016). Our empirical investigation is based on the construction of an original database that merges municipality-level data from various sources and individual-level data from the 2016 Mexican Health and Nutrition Survey (Encuesta Nacional de Salud y Nutricion, ENSANUT). To measure income inequality, we rely on small area estimation (SAE) and combine data from the 2015 inter-census survey (Encuesta Intercensal, EIC) and the 2016 National Survey of Household Income and Expenditure (Encuesta Nacional de Ingresos y Gastos de Hogares, ENIGH) to construct measures of income inequality that are representative at the municipallevel.
Using this original dataset, we implement multilevel estimations to identify the link between municipal income inequality and individual nutritional outcomes. To limit potential reverse causality bias and the presence of unobserved heterogeneity, we also run a two-stage estimation model based on instrumental variables (IV), besides controlling for a comprehensive set of municipal and individual characteristics. The IV design uses meteorological data as instruments for municipal income inequality (i. e. yearly average amount of precipitation, temperature and altitude). We also investigate potential gender heterogeneity. Finally, we explore pathways through which municipal income inequality can affect individual nutritional outcomes, using three-stage least square estimations (3SLS).
Moreover, we also detect a notable importance of the psychological pathway since income inequality tends to favor weight loss (or impede weight gain) through a poorer quality of sleep. These results point out the necessity for public policies aiming at reducing inequalities to be accompanied by nutritional policies and awareness campaigns. The rest of the article structures as follows. In section 2, we illustrate the conceptual framework. In sections 3 and 4, we respectively describe the database and the empirical strategy. In section 5, we present the results. Finally, section 6 concludes and provides policy recommendations.
The model includes income predictors that are common to both data sources and comparable across them. The methodology and its implementation are extensively described in the online Supplementary Material S1. From these SAE simulations, we generate our main measures of income inequality, calculated at the municipal level. We mainly use the Gini index but have also calculated the generalized entropy indices to test the robustness of our results. We enrich the analysis using alternative measures describing the income distribution at the municipal scale. Interestingly, the National Council for the Evaluation of Social Development Policy (Consejo Nacional de Evaluación de la Política de Desarrollo Social, CONEVAL) has also proposed estimates of the municipal Gini index based on the 2015 EIC survey and on a different SAE methodology (i.
, 2018). Quintiles of socioeconomic status are used as controls in the regression analysis. Second, to account for the influence of the living environment on nutrition, we include municipal-level predictors collected from different sources. From INEGI datasets, we account for demography with municipal population density and control for the exposure to violence with the 2015 homicide rate per 100,000 inhabitants. From CONEVAL, we use a composite index of deprivation which measures the percentage of population who are deprived in at least three dimensions among six dimensions (educational lag, lack of access to health services, lack of access to social security, housing with inadequate quality or insufficient space, lack of basic housing services and lack of access to food)  (CONEVAL, 2014).
Discussion and conclusion Using an original database combining different sources of information and an IV multilevel strategy, this article aimed to detect the effect of municipal income inequality on excess weight. Our results highlight a negative impact of municipal income inequality on individual BMI, waist circumference, overweight and obesity in Mexico, especially for women. This gendered result is consistent with previous empirical studies focusing on the US  (Bjornstrom, 2011; Fan et al. , 2016)  and is robust to alternative inequality measures. Another contribution of this article relies on the identification of explanatory mechanisms behind our main findings. 3SLS estimations identify three potential pathways to explain why municipal income inequality leads to weight loss among Mexican women.
Likewise, despite constraints on data availability (especially J o u r n a l P r e -p r o o f in the context of developing countries), future research should also improve the specification of econometric models by not only controlling for omitted environmental determinants of obesity (e. g. occupational characteristics, time allocation), but also for genetic determinants. Indeed, it is now widely acknowledged that BMI and obesity have a strong genetic basis  (Albuquerque et al. , 2017). For this reason, the use of individual genetic information based on the collection and analysis of genetic samples is becoming more common in the social science literature addressing the determinants of obesity, at least in rich countries  (Willage, 2018). Finally, relying on longitudinal datasets may also facilitate the identification of a causal relationship between inequality and bodyweight.
4 per cent. Further descriptions of the ESS, including more detailed information on data collection and response rates for all countries are available on the ESS web site (europeansocialsurvey. org). We restrict the sample to respondents aged 25-55 years whose main activity is employment, living in Western Europe, 1  as we are interested in prime-age workers who have finished full-time education and are not yet approaching retirement. Sample sizes by country and survey round are reported in Table  A1. Anti-immigration attitudes are our outcome variable and are measured based on three questions. The general question wording is 'Now, using this card, to what extent do you think [country] should allow people from [a certain group] to come and live here?' [Country] refers to the country where the interview takes place.
As with share of immigrants, data is matched based on 1-digit NACE sector by country and year. Sectoral unemployment is not available for Norway after 2004. The gap in employment protection of permanent vs. fixed-term contracts is measured using the Employment Protection Legislation (EPL) indicators assembled by the OECD (OECD, 2020a). EPL scores for permanent contracts are based on policies for dismissal (such as notification procedures and severance pay). The score for temporary contracts are based on the criteria for hiring (e. g. types of work, maximum contract duration). As Passaretta and Wolbers (2019) argue, both indicators capture turnover costs. The scores are normalized to a 0-6 range, in which higher scores reflect higher levels of protection. Following Passaretta and Wolbers (2019), we use the absolute difference in EPL scores for temporary and permanent contracts.
In our analyses we included the sectoral share of immigrants as a proxy for the likelihood an immigrant could take over a job. However immigrant share is likely to also be related to contact with immigrants in the workplace. Our analyses show no (cross-sectional) or a positive effect (longitudinal) effect of sectoral share of immigrants on anti-immigration attitudes. This makes it unlikely that there is an underlying competition effect that is countered by contact experiences. Strikingly, while our analyses of the German panel data showed no relation between increased job security and concern about immigration, a study using an earlier version of the same data found a relation between job loss and concern about immigration  (Lancee and Pardos-Prado, 2013). Similarly, additional analyses of the ESS data show that the unemployed are more opposed to immigration that those employed on either permanent contracts or fixed-term contracts (Figure  A2 ).
anonymous reviewers. Evelyn Ersanilli 's work is supported by the  European Research Council  ( ERC-2017-StG-760043 , ' RIGHTS '). Patrick Präg's work is supported by the  French National Research Agency ANR , ' Investissements d'Avenir' (LabEx Ecodec/ ANR-11-LABX-0047 ). The data used for our analysis are publicly available (ESS, 2002(ESS, , 2004(ESS, , 2006(ESS, , 2008(ESS, , 2010.
The contribution of neuroimaging will allow us to better define the relationship between brain and endocast. Models of intra-and inter-species variability in brain morphology inferred from large neuroimaging databases will help make the most of the rare endocasts of extinct species. We also conclude that exchanges between these two disciplines will also be beneficial to our knowledge of the Homo sapiens brain. Documenting the anatomy among other human species and including the variation over time within our own species are approaches that offer us a new perspective through which to appreciate what really characterizes the brain of humanity today.
Despite their importance for modeling the organization of the human cortex, these mappings are currently still inaccessible in vivo. They have only been achieved in 3D for about ten postmortem brains, each with its own idiosyncrasies  [9]. In this sense, this particular field of neuroimaging shares with paleoanthropology the scarcity of samples from which a representative model of the brain of a species and its variability must be inferred. During the last forty years, functional imaging has revolutionized brain research, allowing major advances in the understanding of brain regionalization and its anatomical characterization. Moreover, it is now possible to access huge databases of Homo sapiens brains combining morphological and functional imaging, but also maps of large axonal bundles whose evolution is probably key to the acquisition of certain abilities  [10].