dataesr/scientific-paragraphs-categorization huggingface dataset:
Data acquisition The classification of satellite images was performed according to the object-oriented classification methodology (GEOBIA), with an interval of 5 years for each year worked and a temporal space of one decade. The steps followed to reach the final result are schematized in Fig. 2. The images used were acquired on the free platform of the INPE image catalog that provides images from the CBERS satellite. The images are organized thus: CBERS 2B images are from 2010, CBERS 4 from 2015, and CBERS 4A from 2020. After processing, the images have a resolution of 20, 5, and 2 m, respectively, with properties and characteristics described in Table  1. Other data used in the work were: (1) an orthomosaic with a resolution of 25 cm/pixel in RGB (true color) articulated in blocks of 10 × 10 km, elaborated through the differential rectification of aerial photographs based on a digital elevation model (DEM); and (2) a digital elevation model (DEM), i.
e. , a three-dimensional representation of the Earth's physical surface with a 2 m pixel size, automatically generated by digital photogrammetry  (IEMA, 2015). Both were prepared between 2012 and 2015 under the Mapping ES 2012-2015 project, by the company Hiparc Geotecnologia contracted by the Institute of Environment and Water Resources (IEMA, ES, Brazil), acquired on the platform of the Integrated System of Geospatial Bases of the State of Espírito Santo (GEOBASE). Vector data were also used, such as shapes of town, state and federal boundaries, as well as roads, hydrography and cities obtained from the IBGE and IEMA databases.
Pre-processing The acquired images went through pre-processing processes to be used later in the classification, going through the following treatments. • Mosaic: The DEM images were mosaicized with a total of six scenes that covered the entire study area, where they were later cut out on the perimeter of the polygon of interest; this was carried out in the Arcmap 10. 7 software using the Mosaic to New Raster tool; • Reprojection: All data acquired except the orthomosaic and the DEM present original projection DATUM WGS1984 and UTM Zone 24S coordinate system. It was necessary to reproject the data for the current Brazilian system with DATUM SIRGAS2000 and UTM Zone 24S coordinate system. This reprojection was performed on the QGIS 3. 10. 14 software platform; • Atmospheric correction: In the CBERS 2B, CBERS 4 and CBERS 4A images, atmospheric correction was performed using the Dark Object Subtraction method from the Envi5.
The fusion method was used in the images developed to improve the spatial resolution, using the pansharpening tool available on the Arcmap 10. 7 software platform. It was possible to achieve an improvement in resolution from 20 m to 5 m in the CBERS 4 image and from 8 m to 2 m in the CBERS 4A image. The technique makes it possible to integrate the best spatial resolution of the panchromatic band with the best spectral resolution of the other bands, producing color images that combine both characteristics  (Leonardi and Oliveira, 2009).
It also provides an analogy to the human mind, using the color, shape, texture, and size of objects, in addition to the context and relationships of the landscape. The software used was Definions e-Cognition, which extracts the meaning of connotations and mutual relationships of objects, not only from neighbors but from various input data. The software has algorithms for analyzing the following different aspects: multiresolution segmentation, where weight is assigned to the bands according to the spectral response ranging from 0 to 1; segmentation scale and shape; and compactness. Other aspects analyzed by the algorithm were the classification, stage of defining, and hierarchical ordering of classes, which were modeled by fuzzy relevance rules, in addition to merging regions, the final process of grouping objects belonging to the same classes.
Detection of changes The change detection process was carried out through an adaptation of the methodology employed by  Weckmüller and Vicens (2013) , using the "from-to" technique. Using the GIS environment of the ArcMap 10. 7 software, the maps produced in eCognition in vector format were inserted; and analyses and data crossing were processed using the intersect tool, locating exactly the regions that underwent changes. To highlight the mangrove class, the main object of this study, all other classes such as area of use, restinga, beach, fluvial water and sea were grouped and reclassified as "other class," so only the mangrove class was analyzed, putting in evidence the regions that have suffered losses and increases in mangrove forests, as well as areas that have managed to remain unchanged over the years.
Data acquisition for accuracy calculation To perform the accuracy analysis through the error matrices, it was necessary to analyze the classification regarding the error and hit statistics through the confusion matrix proposed by  Story and Congalton (1986). For this, in ArcMap 10. 7 software, random points were generated and sufficiently representative across the entire work area. Thus, a total of 300 points were randomly obtained for each classification for the years 2010, 2015 and 2020, divided between the mangrove and others classes (the latter class formed by grouping together the area of use, restinga, beach, ocean water, and fluvial water classes), in which 150 reference points correspond to the mangrove class and 150 points to the others class.
, 2015; Kundal et al. , 2023) , and also new technologies such as drones  (Cohen et al. , 2023). The results are justified by the good images of the CBERS sensors used in the classification, achieving a resolution of 20, 5 and even 2 m, when applied to the pre-processing techniques in the images. Furthermore, the 2 m mesh digital elevation allowed us to differentiate the small elevations in the coastal plain that occur in the area, distinguishing the regions of low vegetation from those areas with the presence of exuberant vegetation, represented by the well-developed mangroves. When comparing the mapping data from the present study for the years 2010-2015 (16. 77 km 2 ), considering an average, we identified similarities with the mapping published by  (IEMA, 2015)  and carried out between the intervals of the years 2012-2015 (16.
Conclusion The work developed shows that we can combine data from Brazilian remote sensors, such as CBERS, with the use of GEOBIA techniques in the study of a specific area of interest and not just in areas of large territorial dimensions; and by this method we can reach satisfactory and reliable results. Thus, in a decade, a coastal region underwent changes in its mangrove area, showing a tendency to growth, but punctuating variations in the 5-year time intervals. Currently, society increasingly needs to obtain information about its environments, seeking to understand their changes as well as the consequences of these changes for biodiversity. Therefore, studies of this nature are of great scientific, social, educational and economic relevance, as they aim to contribute to decision-making for better management of coastal environments.
Acknowledgments We would like to thank the members of the  Laboratory of Coastal Dynamics (LADIC-UFPA) ,  Graduate Program in Geology and Geochemistry -PPGG, Federal University of Pará , and  Laboratory of Oceanography and Climate, Federal Institute of Espírito Santo -Campus Piúma  for their support. This study was financed by the  Fundação de Amparo à Pesquisa e Inovação do Espírito Santo -FAPES  ( 093/2020 ,  03/2021 ,  282/2021 ,  441/2021 ,  417/2022 ,  850/2022 , and  1034/2022 ), and in part by the  Coordenação de Aperfeiçoamento de Pessoal de Nível Superior -Brasil (CAPES) -Finance   Code 001. The second author would like to thank  CNPq  for research scholarship ( 309618/2020-7 ).
0 years, SD = 8. 0 years, range = 18-66 years, mean number of years of formal education = 16. 1 years) were recruited using the Prolific database (www. prolific. co, 2023) and reimbursed for their time. Ethical approval was obtained from the University College London Review Board conforming to Helsinki's Declaration. All participants provided informed written consent. We removed 19 participants who selected 'other' for gender as we believed it would be hard to make any informative interpretation of any findings with this limited sample size. We then further identified outliers in this remaining sample of participants using Mahalanobis' Distance, a method shown to have high sensitivity and specificity and a minimal change in bias in simulated and real datasets when removing outliers based on questionnaire data compared to other methods  (Curran, 2016; Zijlstra et al.
Conclusion Overall, our findings suggest that engaging in certain activities, such as playing video games, may indeed be beneficial to one's navigation ability. Accordingly, this research will serve as a platform for future research looking into how actively practicing cognitive abilities during daily activities, such as playing video games, may mitigate the effect of gender and reliance on GPS on navigation performance and provide a greater understanding as to why individual differences in navigation ability may exist. A dataset containing the preprocessed trajectory lengths and demographic information is available at https://osf. io/7nqw6/?view_only=6af022f2a7064d4d8a7e586913a1f157. Due to its considerable size (around 1 terabyte), a dataset with the full trajectories is available on a dedicated server: https://shqdata.
z6. web. core. windows. net/. We also set up a portal where researchers can invite a targeted group of participants to play SHQ and generate data about their spatial navigation capabilities. Those invited to play the game will be sent a unique participant key, generated by the SHQ system according to the criteria and requirements of a specific project decided by the experimenter. https://seaheroquest. alzheimersresearchuk. org/. Access to the portal will be granted for non-commercial purposes. Future publications based on this dataset should add 'Sea Hero Quest Project' as a co-author.
Survey data and complementary data sources Data on vaccination was obtained from The University of Maryland Social Data Science Center Global. This survey collects questionnaires filled by Facebook users. We included in the study 21 out of 27 member countries of the European Union, excluding Cyprus, Estonia, Latvia, Lithuania, Luxembourg, Malta, for insufficient data (Supplemental File Table  S1  reports the sample size in the excluded countries). We also included Norway, a member of the European Economic Area that participates to the network of the European Centre for Disease Prevention and Control (ECDC). Tables  1  and 2  list the number of questionnaires by country, demographics and vaccination status. Questionnaires were offered in different languages, to Facebook users aged 18 years or older.
Acknowledgements We acknowledge  Shweta Bansal ,  Vittoria Colizza  and  Chiara Poletto  for useful discussions. This research is based on survey results from  University of Maryland. Partial support from  EU  grant  MOOD  ( H2020-874850 ),  ANR  and  Fondation de France -NoCOV  ( 00105995 ),  ANRS EMERGEN  ( ANRS0151 ) and  Sorbonne Universit e ISCD.
Acknowledgements The authors are grateful to  Iliass Sedrati  and  Abdelkarim Tadibaght  for their untiring help and support during the eld surveys, and  Reda Hawat  for operating the drone. We also thank the  Provincial Directorate in Larache of the Ministry of Equipment, Transport, Logistics , and Water, as well as the  Moroccan Royal Armed Forces , for authorizations and support in the eld. This work is part of the project  Gof-Boulders.
While the European General Data Protection Regulation (GDPR) has received significant attention in the information systems literature, concerns that it would adversely affect websites' ability to provide quality content to their visitors have not been thoroughly investigated. We construct a longitudinal data-set of news and media websites to study how online content providers adapted their responses to the GDPR over time, and whether restrictions on online tracking enforced by the regulation affected downstream outcomes such as the quantity of content those websites offer to their visitors and visitors' engagement with such content. We find robust evidence of websites' reactions to the GDPR in both the US and the EU, including an initial reduction in the number of third-party cookies and intensity of visitor tracking.
Introduction Because of growing consumer concerns over data privacy and governments' expanding policy efforts to address them, information systems, marketing, and economics scholars have become interested in estimating the impact and potential costs of privacy regulation  (Goldfarb and Tucker, 2012). In May 2018, the European Union (EU) implemented the General Data Protection Regulation (GDPR)-a major new component of EU privacy law. With stiff fines for non-compliance, the GDPR could significantly impact the collection and use of personal data both within and outside EU markets. Since its implementation, much empirical attention has been devoted to capturing the GDPR's direct impacts -such as degrees of firms' compliance, changes in online consent mechanisms, and variations in flows of personal data across the advertising ecosystem  (Degeling et al.
, 2019; Johnson and Shriver, 2019; Aridor et al. , 2020; Peukert et al. , 2020; Jia et al. , 2021; Goldberg et al. , 2021; Godinho de Matos and Adjerid, 2022; Lukic et al. , 2022). Relatively less attention has been devoted to understanding downstream consequences the regulation might have on economically relevant metrics, such as the ability of online publishers to produce new, quality content. Content providers such as news and media websites frequently rely on online advertising for revenue. Hence, fears were raised that they could be uniquely and adversely affected by regulation of the flows of data used in programmatic ads and restrictions on online tracking  (IHS Technology, 2015). We construct a longitudinal data-set of nearly one thousand EU and US content providers (news and media websites), mining information from their websites at regular intervals before and after the implementation of the regulation.
We study how those content providers adapted their response to the GDPR, and whether the regulation affected the quantity and quality of their content, as well as their survival, and thus the ability of those websites to continue to engage audiences. In contrast to prior work, we capture website-level data that allows us to tie websites' responses to downstream outcomes, accounting for ecosystem effects that impact websites' outcomes because of their location (EU vs US), and website-level effects that are function of website-specific responses to the GDPR. Our longitudinal panel also allows us to account for how content providers reacted to the regulation in both the short-and the long-term. Given the widespread collection of (and reliance upon) personal data across different sectors of the economy, the GDPR was predicted in early industry reports to produce substantial negative economic effects.
Downstream outcomes are collected from multiple publicly available sources and measure the quantity and the quality of the content those websites produce. Following related work, quantity of content is measured as the number of new URLs of content generated over time; as proxies for quality, we use various metrics of user engagement previously adopted in the literature, including traffic metrics (Page Views Per User, Page Views Per Million, Reach, and Rank) and visitors' engagement (social media reactions on Facebook). Finally, we capture data on websites' market exit and changes in their revenueand data-generating strategies that may signal regulatory-induced distress. Our longitudinal, website-level response data allows us to paint a rich picture of the evolution of the impact of the GDPR over time and to link website responses to it to downstream outcomes.
The analysis first focuses on websites' responses (Section 5). We find robust evidence of websites' reactions to the GDPR in both the US and the EU, and of significant heterogeneity in response strategies both between EU and US websites, as well as within EU websites. We also find evidence of changes-especially among EU websites-in responses over time. In particular, we find evidence of an initial reduction in the number of third-party cookies and visitor tracking among both EU and US websites following the enactment of the GDPR. Those initial reductions are followed, several months after the enactment of the regulation, by a trend reversal and an uptick in tracking among EU websites. In fact, we also find evidence that an initial increase in concentration in the EU market of third-party data trackers immediately after the enactment of the GDPR (an increase consistent with post-GDPR concentration dynamics documented by prior studies of the GDPR:  Johnson and Shriver (2019) ;  Peukert et al.
(2020) ) was followed by re-entry of numerous market players several months thereafter. Next, we estimate the impact of the GDPR on downstream outcomes (Section 6). A known complication in GDPR analysis is its extraterritorial scope: organizations located outside the EU are subject to the requirements of the GDPR when interacting with EU data subjects, clouding the distinction between control and treatment groups. While the complication is real, and spillover effects can reach US-based websites, we argue in Section 3 that it is legitimate to expect content providers located inside vs. outside the EU to differ both in the mode of response to the GDPR and in the likelihood of their downstream outcomes being affected by the regulation. The first step in our empirical strategy consists of several difference-in-differences specifications that estimate an ecosystem effect-how the regulation impacts EU websites compared to US websites, accounting both for websites location and for the share of traffic they receive from the EU or the US.
Next, we complement the difference-indifferences analysis by leveraging our data-set of individual websites' responses. In contrast to other GDPR studies, by virtue of capturing websites' data from both EU and US IP addresses, we are able to determine whether content providers respond differently to the regulation depending on the country of origin of the visitor, and therefore how they differ in mode and degree of response to the regulation. Thus we are able to account for website-level effects -the effect that the GDPR has on downstream outcomes as function of the specific responses by the websites to EU visitors (for example, a website may see a decrease in the value of the ads they display after they implement a consent mechanism that induces users not to consent to tracking). To account for endogeneity in response behavior, we use two specifications: an instrumental variable approach (local average treatment effect or LATE) to estimate the effect of the regulation on websites that do decide to respond; and a look-ahead matching analysis, which compares the outcomes experienced by websites that adopt the same response to GDPR, but at different points in time, allowing us to exploit the temporal variation in adoption to identify the effect of the response.
For instance,  Zhuo et al. (2021)  measure the impact of the GDPR on interconnection agreements between EU network providers with those outside the EU. Although the authors note a decrease in demand for data within EU networks, they estimate zero effects of the regulation on the number of types of interconnection agreements. Recent work has focused on the impact of the GDPR on online tracking and the online advertising market. Peukert et al. (2020)  observed increased concentration among web technology providers following the introduction of the GDPR (the market share for small firms decreased while that of large firms such as Google increased). Shortly after the enforcement of the GDPR,  Libert et al. (2018)  reported a 22% drop in third-party cookies on news websites. Later,  Dabrowski et al.
Aridor et al. (2020)  found that the total number of consumers observed by a data intermediary in the online travel industry decreased by 12. 5% after the GDPR, suggesting that a significant number of consumers decided to opt-out. Congiu et al. (2022)  investigate the impact of the GDPR on traffic measures for 5, 000 websites in the US and EU. The authors find a 15% reduction in overall traffic for US and EU websites along with a reduction in traffic metrics for EU websites relative to US websites. They attribute this effect to a reduction in the effectiveness of display advertising and e-mail marketing for acquiring traffic. Our study differs from that work in several dimensions. Rather than investigating how GDPR has affected the different channels that websites use to acquire visitors, our aim is to determine whether the GDPR has affected the ability of news and media websites to continue to provide content and engage audiences.
Downstream Impact Article 6 of the GDPR includes requirements that may affect downstream outcomes for entities (including websites) generating some or most of their revenues through online advertising. First, the enactment of the GDPR may reduce the extent to which customers and visitors are tracked and their personal data collected. The reduction in tracking may be due to a number of factors and manifest itself in different ways: through a website's decision to block traffic from EU visitors altogether (in order to avoid potential fines associated with GDPR violations); through the decision by data controllers (such as websites) to reduce or altogether stop the tracking of EU customers or visitors (again, to avoid potential fines associated with GDPR violations); or through the adoption of consent mechanisms, which present users with options concerning the usage of their data (rather than assuming visitor consent and tracking their behavior by default) and which may therefore increase the portion of users who opt-out from tracking and targeting relative to the pre-GDPR status quo.
Ecosystem Effects By ecosystem effects we refer to the differential impact the GDPR may have on US vs. EU websites, as a function of website location and, therefore, the share of traffic a website receives from EU vs non-EU data subjects. Ecosystem effects materialize through two mechanisms. First, while the GDPR applies to both EU and non-EU websites, 8  EU-based data controllers (such as websites and advertising networks) are in principle required to comply with GDPR rules for all users and visitors, whereas data controllers based outside the EU can choose to apply GDPR-compliant practices only to the share of visitors originating from the EU. As non-EU websites are likely to receive a smaller portion of their traffic from the EU, relative to EU websites, they may opt to comply with the regulation for smaller shares of visitors.
Hence, at parity of GDPR response relative to an EU counterpart, a US website may experience the chain of decline in tracking, targeting, and revenues described in Section 3. 1 for smaller portions of its traffic than that counterpart, and may end up being relatively less affected by it. 9  Second, the responses to the GDPR by all other stakeholders within the EU (vs. US) online advertising/publishing ecosystems (such as individual websites, ad networks, and so forth) collectively affect the aggregate availability of consumer data within that ecosystem. Such changes in data availability can in turn affect the ability of individual websites within that ecosystem to target their respective visitors with behavioral ads. 10 Hence we expect EU websites, on average, to be more negatively affected by this mechanism than US websites, as the GDPR should more significantly reduce tracking and data availability across the EU-based data ecosystem, thus affecting all websites in it, regardless of their response.