dataesr/scientific-paragraphs-categorization huggingface dataset:
30 These relationships include DNS-specific associations, that is, other DNS record types, as well as more general Internet routing 29. Piscitello and Strutt; Aaron. 30. Akiwate, Jonker, Sommese, et al. dependencies, such as IP address blocks announced by BGP, ROAs, autonomous systems, and registrar information. Another source of data relies on the same files to seed active measurements of DNS infrastructure. Three Dutch research institutions (SURFnet, SIDN Labs, and U. Twente), operate the OpenINTEL project, a system for comprehensive measurements of the global DNS. 31  OpenINTEL uses ICANN's Centralized Zone Data Service files, and agreements with other registries, to drive DNS queries for all covered domain names once every 24 hours, covering over 232 million domains per day. OpenINTEL measurements using.
com and. nl zones revealed that the vast majority of second-level domains in. com have name servers located in a single AS, while almost half of domains in the. nl zone have name servers in at least two AS. Topological diversity is important to protect against DoS attacks. Sustaining such data infrastructure is necessary to enable transparent and accountable evaluation and socialization of proposed operational practices such as the Internet Society has stewarded for the routing system. ICANN's Security and Stability Advisory Committee has for many years published documents on how to mitigate the many risks to security of a domain name in its lifecycle, and advised stakeholders, accordingly. 32 The recommendations in these reports could serve as the basis for discussing a proposed code of conduct.
In this case, not only does the traffic need to cross only one service provider, but the traffic enters the access network at a point close to where it will exit to the consumer. Many application designers similarly use cloud platforms and associated services to host applications and content close to the users, thereby shortening the path data takes across the Internet, optimizing performance for users, infrastructure support cost for themselves, and improved resilience. In the United States, the largest cloud providers are Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure. As an example, AWS organizes its cloud platform into regions, within which are availability zones for resilience. As of October 2020, AWS has 24 regions (three more announced) and 77 availability zones across the globe.
Measuring Regionalization Measuring the degree to which the Internet experience has become more localized is challenging, because the degree to which a user's experience is localized will depend on where that user is within the Internet. A user attached to a large, US broadband access provider will probably have a much more localized experience than a user from the developing world. In addition, measuring the destination to which actual users go raises issues of data collection and privacy. As an initial exploration to assess how localized the Internet experience is becoming, we took two different datasets of popular destinations on the Internet, and measured how far away they were (in terms of the number of AS crossed to reach them) starting from the home location of one of us. This sort of exploration yields only anecdotal insight, and (as mentioned earlier) is highly colored by the fact that the origin used for the exploration was served by a well-connected US broadband access provider.
The emergence of a coherent region of directly connected MANRS AS creates a stronger industry incentive for additional AS to join MANRS. Customers are better protected from being misled by false BGP announcements if they connect to a MANRS-compliant transit provider, and a customer that is concerned that others will not forward its route announcements needs to connect to a MANRS-compliant transit provider. There is an alternative approach to preventing the propagation of invalid path announcements, called Autonomous System Provider Authorization, or ASPA. 40 ASPA proposes a new, global, cryptographically signed database, perhaps stored in the same location as the ROA data, in which each AS records its transit providers. If all AS within a zone of trust have recorded an ASPA, then any AS within the zone that receives an invalid (hijack) route announcement can detect it.
AS within the zone are then protected from hijacks based on invalid path announcements. In recursive MANRS, the knowledge of which providers an AS is using is implicit-the knowledge is not publicly recorded in a global database but results from business agreements between provider and customer AS. Since the data is not globally known, only a router at the point where a MANRS-compliant AS receives a route announcement from a noncompliant customer can perform the check. In ASPA, any router can perform the 40. Aximov, Bogomazov, Bush, et al. check. Recursive MANRS is thus an enhanced practice that all MANRScompliant AS must implement. The advantage of recursive MANRS is that there is no global, public database. A database of that sort may be a substantial barrier to deployment, as it requires every AS to publicly disclose its potential transit providers, and it may be a target of malicious attack to corrupt the information.
Corrupting the database could effectively drop an AS from the Internet. On the other hand, the global database may allow the detection (and blocking) of certain forms of route leaks. This discussion of preventing hijacks based on invalid path announcements illustrates that a given mechanism, for example, the use of ROAs, can play a role in a range of operational practices with different security outcomes. Simple dropping of route announcements where the ROA makes the route invalid will prevent invalid origin hijacks. Dropping route announcements according to the recursive MANRS rule additionally prevents invalid path hijacks. Of course, different operational practices may trigger different incentives by the various actors to deploy the practices.
Functional prediction changes associated with changing inoculum and diets To discern any changes in predicted functional capabilities of bacterial communities as a whole, we employed PICRUSt2 on the 16S rRNA sequences  (47)  and subsequently identified predicted microbial metabolic pathways using the MetaCyc database  (48). Overall, there were 406 predicted pathways in the cockroach gut microbiomes. Although microbial function was more conserved than microbiome composition (Figs. 5; S7; Table  S9 ), consistent with previous studies (e. g. , 49), there were clear differences in response to our treatments (Table  S10 ). Diet had a strong and significant impact on the metabolic profiles, explaining 22. 2% of the observed variation (PERMANOVA 10,000 permutations ; F 1 = 37. 08, p adj = 1e-5) (Fig.
1 ). We assessed the effectiveness of the antimicrobial treatment using one cockroach per ootheca (Fig. 1 ; Table  S1 ). A hatchling was crushed in 300 μL 0. 2% saline solution (Sigma-Aldrich, Germany, Cas number: 7732-18-5, Sigma-Aldrich, Germany 7647-14-5), vortexed and 50 μL of the mixture was plated onto two different Potato Dextrose Agar plates (PDA; 39g/L PDA, 10 g/L agar). The remaining 200 μL was snap frozen in liquid nitrogen and stored at -20℃ for MiSeq amplicon sequencing (see below). One plate was kept anoxic in a GasPak 100™ Anaerobic System (Becton-Dickinson, USA), while the other was left at ambient oxygen levels. Plates were left at room temperature for a minimum of one month and the number of Colony Forming Units (CFUs) was counted for each morphologically distinct microbe (up to 100 per unique morphology) and results were visualized in R (81) using the package ggplot  (82).
Bioinformatics and statistical analyses Batches were handled identically using the dada2 pipeline v. 1. 12. 1 (85) using RStudio v. 3. 6. 1  (81). Default parameters were used aside from truncation length (275, 260), maxEE  (2, 3)  and minOverlap set to 20. Taxonomic assignment was first performed with the manually curated Dict_db 3. 0 database (30), followed by reclassification using SILVA v. 1. 3. 2 (86) of ASVs that were not classified to the genus level. This procedure allowed 96. 4% of ASVs and 99. 7% of reads to be classified to genus level in batch 1 and 92. 1% of ASVs and 98. 4% of reads in batch 2. Blattabacterium, an intracellular symbiont  (37) , was found in all controls and these were therefore ignored. A cellular mock community standard (Zymobiomics, Nordic BioSite ApS, Copenhagen) was used to control for extraction, PCR and sequencing biases.
All eight expected taxa were detected and classified appropriately and no contaminants were detected in the mock community, despite lower DNA concentrations than biological samples, strongly suggesting sample cleanliness. Blattabacterium and Eukaryote ASVs were filtered, as were ASVs with less than 10 observations in the full dataset. Rarefaction plots (plotted prior to rare ASV removal; Fig. S2 ) indicate we captured a satisfactory portion of the full bacterial community. Alpha diversity was calculated using the R package phyloseq estimate_richness function v. 1. 28. 0  (87). ANOVAs  (88)  were performed to calculate significant differences between experimental setups using the stats package v. 3. 6. 1  (81) , after testing deviation from assumptions with shapiro. test (89)  and bptest  (90)  from the lmtest package v.
Acknowledgements We thank  Aram Mikaelyan ,  Callum Richards , and  Saria Otani  for fruitful discussions in the early stages of this work,  Sylvia Mathiasen  for help with laboratory work,  Rasmus Stenbak Larsen  and  Pol Lannes  for help with maintenance of the cockroaches, and  Veronica M. Sinotte ,  Nick Bos ,  Ana Cuesta , and  Blanca Ballesteros  for comments on a previous draft of the manuscript. This work was supported by the  European Research Council   Consolidator Grant   771349  to MP. KHB was supported by a  Carlsberg Foundation Distinguished.
Differentially-abundant bacterial taxa between different treatment groups were identified following CoDa good practices (44, 45,     https://github. com/ggloor/CoDa_microbiome_tutorial). A center-log-ratio transformed multivariate model was conducted using the Aldex2 package (100) including variables inoculum, diet and antimicrobial treatment. After inspecting MA and volcano plots, significant values (p adj < 1e-5) were extracted and plotted against their centered log ratio. As binning by genus is dependent on the order of classification database used, we repeated the analysis using SILVA first and Dict_db second, as described above (Supplementary Figure  S6 ). Functional prediction changes associated with changing inoculum and diets were evaluated across treatment groups and on differentially abundant genera specifically using PICRUSt2 on 16S rRNA sequences  (47).
Abstract. Statistics of anticyclonic eddy activity and eddy trajectories in the Levantine Basin over the 2000-2018 period are analyzed using the DYNED-Atlas database, which links automated mesoscale eddy detection by the Angular Momentum Eddy Detection and Tracking Algorithm (AMEDA) algorithm to in situ oceanographic observations. This easternmost region of the Mediterranean Sea, delimited by the Levantine coast and Cyprus, has a complex eddying activity, which has not yet been fully characterized. In this paper, we use Lagrangian tracking to investigate the eddy fluxes and interactions between different subregions in this area. The anticyclonic structure above the Eratosthenes Seamount is identified as hosting an anticyclone attractor, constituted by a succession of long-lived anticyclones.
, 2010). However, due to their limited time coverage, these studies had a static perspective. Zodiatis et al. (2010)  probably presents the most advanced vision from this approach, displaying a hint of interannual variability. In the more recent hydrographic regionalization review of  Ayata et al. (2018) , the anticyclonic structure south of Cyprus is called the "Eratosthenes anticyclone", which is the name used hereafter. In the 1990s, the development of satellite observation, initially undertaken using SST, already enabled the identification of some of these long-lived anticyclonic structures as accumulation areas for mesoscale eddies detached from the coast  (Millot and Taupier-Letage, 2005; Hamad et al. , 2006). Later altimetry products of sea surface height (SSH) such as Archiving, Validation, and Interpretation of Satellite Oceanographic Data (AVISO)/Copernicus Marine Environment Monitoring Service (CMEMS) with a grid resolution on the order of the deformation radius helped to investigate the unsteady dynamics of mesoscale structures in the region.
The large-scale deployment of autonomous drifters in the global ocean (such as the Argo or MEOP programs), as well as the centralization of collected data (such as CMEMS products), enables one to bridge the gap in the temporal scale between satellite and in situ data. Argo is a global array of more than 3000 floats measuring temperature and salinity down to 2000 m (ARGO, 2020). Using Argo data,  Laxenaire et al. (2019)  captured the subsurface evolution of one single Agulhas ring over 1. 5 years in the South Atlantic with the conjunction of Argo profiles and SSH data. This demonstrates that long-lived anticyclones can transport warm water masses over very long distances isolated in their thick core. Recently, in the Algerian Basin,  Pessini et al. (2018)  attempted to link eddy observations to in situ measurements and to compute eddy regional statistics, although they utilized an algorithm that did account for merging and splitting events.
Mason et al. (2019)  also attempted to study the vertical eddy structure with regional variation in the Alboran Sea, although they used data from assimilated models. Thus far, no such regional characterization of eddy systematic detection has been attempted in the eastern Mediterranean. This approach of both eddy tracking, detected by altimetry that takes merging and splitting events into account, and colocalization with in situ observations can be generalized into an eddy atlas. The DYNED-Atlas database combines over 19 years of subsurface observations from Argo floats of identified eddies, tracked in time and space by the AMEDA algorithm (DYNED-Atlas-Med, 2019). The DYNED-Atlas is the perfect tool for the study of eddy dynamics and the associated transport of water masses in their cores, as it combines eddy detection and physical properties.
It has not been exploited in the LB yet, although  Stegner et al. (2019)  already demonstrated very deep subsurface eddy signatures in this area. Using eddy contours, tracks and co-localized profiles from the DYNED-Atlas database, extended with avail-able expendable bathythermograph (XBT) and conductivitytemperature-density (CTD) profiles to compensate for the sparsity of observations, this study will investigate additional information from Lagrangian anticyclone tracking and statistically significant drift patterns and structures in the southeastern LB -east of 28 • E and south of Cyprus. After introducing the datasets in Sect. 2, we present our methodology of a Lagrangian convergence framework and the regions studied in Sect. 3. Analysis of this method with DYNED-Atlas data is detailed in Sect.
Eddy contours, centers and tracks The dynamical evolution of eddies and their individual tracks are retrieved from the DYNED-Atlas database (DYNED-Atlas-Med, 2019) for the 2000-2018 period. The DYNED-Atlas project, with eddy tracks and physical property signatures, is accessible online: https://www1. lmd. polytechnique. fr/dyned/ (last access: 18 August 2021). The dynamical characteristics of the eddies contained in the DYNED-Atlas database were computed by the AMEDA eddy detection algorithm  (Le Vu et al. , 2018)  applied on daily surface velocity fields. The latter were derived from the absolute dynamic topography (ADT) maps produced by Salto/Duacs and distributed by the Copernicus Marine Environment Monitoring Service (CMEMS) with a spatial resolution of 1/8 • , which is on the order of the internal deformation radius in the Mediterranean Sea (10-12 km;  Mkhinini et al.
In situ oceanographic observations About 34 406 Argo profiles are available from the DYNED-Atlas database in the whole Mediterranean Sea over this 19-year period. However, due to sparser campaigns, only 9384 were available in the LB, mostly after 2014. To complete these in situ measurements, we added 2311 CTD and 3860 XBT casts downloaded from the Sea-DataNet portal (https://www. seadatanet. org/Data-Access, last access: 15 June 2020, data in unrestricted access) as well as 7020 additional profiles from the CORA (Coriolis Ocean database ReAnalysis) database, which is also available on the CMEMS catalogue: IN-SITU_GLO_TS_REP_OBSERVATIONS_013_001_b (https://resources. marine. copernicus. eu/?option=com_ csw&view=details&product_id=INSITU_GLO_TS_REP_ OBSERVATIONS_013_001_b, last access: 15 June 2020).
Finally, glider measurements carried out in October 2018 by the Israel Oceanographic and Limnological Research (IOLR) in one transect offshore of Israel provided 370 profiles that were added to the database. The data sources listed above add up to 22 945 profiles from 2000 to 2018 in the LB. All of the hydrological profiles are then co-localized with detected eddies following the standard procedure used in the DYNED-Atlas database. Profiles are considered to be inside an eddy if they are inside its maximal speed contour.
Eddy-induced physical property anomalies The DYNED-Atlas database establishes a method to estimate the physical property anomalies induced by an eddy (DYNED-Atlas-Med, 2019). This method is followed in this study, only extending the database with profiles from sources other than Argo and using in situ temperature instead of potential temperature to match up with XBT profiles. Each oceanographic measurement is compared to the AMEDA observations. If it falls within the contour of an eddy on the same day that it is cast, the profile is co-localized with the eddy and then considered as sampling its physical properties. If it falls outside any eddy observation, it is considered an "outside-eddy" profile. Estimation of the eddy-induced physical property anomalies (temperature, salinity, density) is next done by comparison with a reference background.
11b-c , although slightly higher. The vertical structure of Eratosthenes anticyclones described above should be compared with physical properties of neighboring eddies in the LB. Figure  12  presents the comparison between a section representative of the Eratosthenes anticyclone, using data from the BOUM campaign in June 2008  (Moutin and Prieur, 2012) , and an anticyclone section in the Tel Aviv region performed in October 2018 by a glider from IOLR. Next to each section is an ADT map representative of the SSH activity at that time (Fig  12b, d ). The glider section lasts for 10 d, with 20 October 2018 being the median date; a magenta line indicates the glider track, and the position on the 20 October is shown with a magenta circle. The daily altimetric eddy contours are plotted on the ADT maps, with cyclones in red and anticyclones in blue, and a dot with a size proportional to the vortex Rossby number indicates the center.
(2006)  and  Gertman et al. (2010) , suggest that the second option is likely happening. On the other hand, the high occurrence of eddy merging and splitting highlights the importance of eddy-eddy interactions in this basin. Further studies in this direction are needed to outline eddy dynamics, although the small internal deformation radius in the Mediterranean Sea of 10-12 km  (Mkhinini et al. , 2014)  only allows one to accurately detect large mesoscale structures. Nevertheless, great improvements are possible via the application of eddy automatic detection at smaller scales than the mesoscale with the help of SST data  (Moschos et al. , 2020). The presence of the EAA over a seamount obviously raises the question of topographic interactions. Two attractor structures are observed in the LB, over very different bathymetry: the Marsa Matruh attractor over the Herodotus Trench deeper than 2000 m and the EAA over the Eratosthenes Seamount whose summit is approximately 700 m deep.
Conclusions Using the DYNED-Atlas database of eddies in the Mediterranean Sea, a Lagrangian convergence method is defined, and its application to anticyclone tracking from 2000 to 2018 enables one to quantify anticyclone transfers between subregions of the southeastern LB. At the position of a known area of anticyclone accumulation, it reveals the existence of anticyclone convergence toward the Eratosthenes Seamount in a structure that we named the Eratosthenes anticyclone attractor. This attractor proves not to be a single fixed anticyclone but is rather constituted by a succession of long-lived anticyclones sharing dynamical characteristics, distinct from neighboring eddies: longer lifetime -more than 1 year and up to 4 years -and a maximal speed radius above 40 km -more than 3 times the internal deformation radius.
Acknowledgements. The authors wish to thank the  IOLR  staff for help with glider operations. We are also grateful to the  Agence National de la Recherche  for financial support of the  DYNED-Atlas  project. Finally, the authors wish to acknowledge  Briac Le Vu  for fruitful discussions on AMEDA detections. Financial support. This research has been supported by the  Israel Science Foundation  (grant no. 1666/18 ). Review statement. This paper was edited by  Anna Rubio  and reviewed by two anonymous referees.
Data availability. The DYNED-Atlas database for 2000-2018 is freely available at https://doi. org/10. 14768/2019130201. 2  (Stegner and Briac, 2019). XBT and CTD casts used are freely available on the SeaDataNet portal (https://cdi. seadatanet. org/search, last access: 10 September 2021), by selecting data with unrestricted access in the LB (using the coordinates utilized in the present study which are available in the Supplement). The CORA database is available on the CMEMS catalogue: INSITU_GLO_TS_REP_OBSERVATIONS_013_001_b (https://doi. org/10. 5194/os-9-1-2013, Cabanes et al. , 2013). The IOLR glider data can be made available upon reasonable request from Ayah Lazar. Supplement. The supplement related to this article is available online at: https://doi. org/10. 5194/os-17-1231-2021-supplement.
Background Multiple voluntary surveillance platforms were developed across the world in response to the COVID-19 pandemic, providing a real-time understanding of population-based COVID-19 epidemiology. During this time, testing criteria broadened and health-care policies matured. We aimed to test whether there were consistent associations of symptoms with SARS-CoV-2 test status across three surveillance platforms in three countries (two platforms per country), during periods of testing and policy changes. Methods For this observational study, we used data of observations from three volunteer COVID-19 digital surveillance platforms (Carnegie Mellon University and University of Maryland Facebook COVID-19 Symptom Survey, ZOE COVID Symptom Study app, and the Corona Israel study) targeting communities in three countries (Israel, the UK, and the USA; two platforms per country).
Findings Between April 1 and July 31, 2020, 514 459 tests from over 10 million respondents were recorded in the six surveillance platform datasets. Anosmia-ageusia was the strongest, most consistent symptom associated with a positive COVID-19 test (robust aggregated rank one, meta-analysed random effects OR 16•96, 95% CI 13•13-21•92). Fever (rank two, 6•45, 4•25-9•81), shortness of breath (rank three, 4•69, 3•14-7•01), and cough (rank four, 4•29, 3•13-5•88) were also highly associated with test positivity. The association of symptoms with test status varied by duration of illness, timing of the test, and broader test criteria, as well as over time, by country, and by platform. Interpretation The strong association of anosmia-ageusia with self-reported positive SARS-CoV-2 test was consistently observed, supporting its validity as a reliable COVID-19 signal, regardless of the participatory surveillance platform, country, phase of illness, or testing policy.