dataesr/scientific-paragraphs-categorization huggingface dataset:
Calculating connectivity pathways from remote-sensing datasets, it has also been shown that the southern province of the Red Sea is affected by remote upstream regions in the Gulf of Aden and Indian Ocean  [27]. The southern Red Sea is subjected to a considerable biannual water influx from the Indian Ocean via the Gulf of Aden, which facilitates gene flow between the two regions  [65, 66]. By contrast, the Republic of Senegal on the West coast of Africa is one of the least ABNJ-connected coastal zones. Ocean currents in this region are dominated by the relatively weak, southward-flowing Canary Current, which feeds into the westward-flowing North Equatorial Current, and the southward-flowing Guinea Current. As seen from Fig. 3 , on a timescale of six months, most of the coastal zone remains unconnected to the ABNJ.
Gaps in evidence for connectivity and impact of climate change Ecological connectivity across the global ocean is an emerging area of science and some gaps in evidence are inevitable. Establishing the underlying connectivity of ocean circulation relies on the quality of either the ocean model (as done in this study) or the global observational dataset synthesized from ocean float and satellite-derived observations used for obtaining ocean current velocities. Both areas of research have made substantial progress in the last decade, and further progress is expected to be rapid due to advances in computing power, an increasing fleet of advanced ocean floats, coordinated and standardised international efforts for sustained observations (e. g. Global Ocean Observing System, GOOS, http://www. goosocean.
The establishment of a global network and centralized database would allow for the collection and dissemination of telemetry data on a global scale  [85]. Importantly, patterns of present day ecological connectivity will not remain static in time due to the emerging impact of climate change on both ocean circulation  [13]  and the global climate-driven redistribution of species  [86]. Areas deemed important for conservation may not remain so in the longer term requiring climate-proofing of ABNJ conservation regimes. Consequently, continuous effort will be required to monitor evolving patterns of marine ecological connectivity, as well as the various anthropogenic impacts that can affect it. Thus the impact of climate change may undermine the conservation efforts and will require approaches which go beyond currently proposed adaptive management  [87, 88].
Acknowledgements The initial workshop to generate the ideas took place in Seychelles in April 2018 with financial support from  Sida. Data analysis was jointly supported by  Sida  and the  UK GCRF  project  SOLSTICE  ( NERC grant   NE/P021050/1 ). The modelling tools and approaches were supported by the  UK GCRF  project  SOLSTICE  and the  UK National Capability  project  ACCORD. V. Allain was supported by the  Global Environment Facility 's Oceanic Fisheries Management Project # 2. G. Pecl  was supported by an  Australian Research Council Future Fellowship. D. Raitsos  was supported by the  King Abdullah University of Science and Technology Office of Sponsored Research (OSR)  under the Project No. 3268. This work used the NEMO ocean general circulation model (https://www. nemo-ocean. eu/)and the  ARCHER UK National Supercomputing Service  (http://www.
The test is freely available, offers clinical cut-off scores for dementia (vs. healthy age-matched controls) and has been initially validated in patients with early AD, bvFTD and healthy elderly participants. The test has since also proven valuable for the differential diagnosis of language variants of FTD, showing evidence of diseasespecific "apraxia profiles"  (301). Data on praxis impairments in other early neurodegenerative patient groups (e. g. , Parkinson's disease) as well as more extensive normative data for the DATE involving healthy controls from diverse cultural backgrounds is currently collected.
Because of the importance of emotion and theory of mind deficits in bvFTD as well as the increasing evidence pointing to interoception deficits and the associations of these deficits with insular damage, bvFTD may represent a prototype to investigate the relationship between these functions and could bring clinical data to understand the generative and predictive nature of the embodied mind. With regard to links between apraxia, social and affective cognition, and interoception, preliminary data suggest that deficits in the imitation of facial postures may be correlated with facial emotion recognition performance and to a lesser degree also with caregiver reports of social-behavioral abnormalities in bvFTD  (301). One reason for these associations and a potential common mechanism for both, facial affect recognition and face imitation may be that an accurate interpretation of internal somatosensory signals (and interoceptive changes) is required to (a) correctly decode and label a facial expression (or a body posture) and (b) to correctly imitate it  (328).
In the specific case of bvFTD, we believe that a major limitation to include some already well-described novel cognitive markers in the diagnostic criteria is the lack of availability of many current cognitive performance tests and behavioral scales. One of the potential reasons for this is an overall lack of research regarding cross-validation of the existing instruments as well as establishing adequate normative data and evidence of psychometric quality. These approaches require a lot of time and energy while being commonly disregarded in academia and research, as the former often leads to replications or negativefindings and the later will only be published in neuropsychologyspecific, often national journals. This might be especially true for neuropsychological tools that are developed within a medical context (such as in neurodegeneration) as the difficulty to convince about the importance of psychometric studies and to conduct such studies in medicine may be higher than in the field of psychology.
Although cultural and socio-economical variability may appear as more important for the domain of social cognition, its influence may also be observed in a wide range of neuropsychological measures and "classic" cognitive domains [e. g. ,  (340, 341) ]. Finally, the vast majority of the presented standardized performance-tests and scales to differentiate between bvFTD and competing diagnoses (e. g. , AD, affective disorders, other neurodegenerative diseases) have so far mainly been shown to function in usually small samples (with specific demographic and cultural characteristics), highlighting the importance of collaborative research and crosscultural validation studies. Replications and cross-validation studies of tests and scales in larger and more diverse samples including extensive collection of data from healthy controls are needed in order to extrapolate from individual test results onto specific diagnostic decisions (e.
g. , Which cognitive performance profile or which set of behaviors are both pathological/abnormal and specific for an early diagnosis of bvFTD in a certain agegroup, for a specific level of education, and in a certain culture?). In our view, this is currently one of the major challenges in the field of clinical neuropsychology but also a crucial prerequisite for the future establishment of valid and meaningful biomarkers for FTLD. In this perspective, the Social cognition and FTLD network (https://sites. google. com/view/soccogftld) has been created in order to share data on healthy controls and patients allowing large-scale clinical validity and crosscultural studies-so far using the mini-SEA. If multiplicated, such initiatives may bring important data on both cognitive functions and the tests used to assess them and could later fasten the inclusion of specific cognitive dysfunction into the diagnostic criteria for neurodegenerative diseases.
The depth of abrasion was estimated to be no more than 100 μm. Both DVH and LGB powders were then rinsed in methanol and dried at room temperature. Bivalve samples. Three specimens of Antarctic scallop species Adamussium colbecki were collected at a water depth of 15 m near the Dumont d'Urville Antarctic station in January 2007 (66. 658°S, 140. 008°E). Seawater temperature, constrained by the ROSAME network (Reśeau d'Observation Sub-Antarctique et Antarctique du niveau de la MEr), remains stable annually (mean T = -1. 8 °C) except for a summer warming peak around -0. 5 °C between January and March  59. Seawater δ 18 O VSMOW value, estimated from the Global Seawater Oxygen-18 Database of Schmidt et al. 60  , is -0. 26 ± 0. 06‰. Five live specimens of the deep-sea oyster species Neopycnodonte cochlear were collected in March 2010 from the Lacaze-Duthiers canyon (42.
Acknowledgements We thank  C. Spoẗl  and three anonymous reviewers for useful feedback on the manuscript. M. D. is grateful to  T. Kluge  for his early encouragement to write up this study. The clumped-isotope facility at LSCE is part of  PANOPLY (Plateforme Analytique Geósciences Paris-Saclay ) and was supported by the following institutions:  Reǵion Ile-de-France ;  Direction des Sciences de la Matiere du Commissariat àl'Energie Atomique ;  Institut National des Sciences de l'Univers ,  Centre National de la Recherche Scientifique ; Universtitéde Versailles/Saint-Quentin-en-Yvelines. M. D. thanks  N. Smialkowski ,  F. Dewilde , and  C. Waelbroeck  ( LSCE ) for "bulk" δ 13 C VPDB and δ 18 O VPDB analyses on LGB and DVH. This work was partially supported by  Australian Research Council Discovery Project  Grants  DP110102185  (to R.
Background: Diabetes is one of the underlying risk factors for developing community-acquired pneumonia (CAP). The high prevalence of diabetes among population and the rising incidence of this illness, converts it as an important disease to better control and manage, to prevent its secondary consequences as CAP. The objective of this research is to describe the characteristics of the patients with diabetes and the differences with the no diabetes who have had an episode of CAP in the context of the primary care field. Methods: A retrospective, observational study in adult patients (> 18 years-old) who suffer from CAP and attended at primary care in Spain between 2009 and 2013 was developed using the Computerized Database for Pharmacoepidemiological Studies in Primary Care (BIFAP). We carried out a descriptive analysis of the first episodes of CAP, in patients with or without diabetes as comorbidity.
Methods This is a retrospective observational study aimed at describing the epidemiological characteristics of patients over 18 years of age who suffered their first episode of CAP between January 2009 and December 2013 and were diabetic patients. As inclusion criteria, patients had to have been treated for at least one year by their PC doctor. The diagnosis of CAP in Primary Care in Spain is based in the history and physical examination (the presence of cough, fever, tachycardia and cramps  [15] ) and must be supported by chest radiography and an elevation of reactive protein C  [16]. The database used was the Database for Pharmacoepidemiological Research in Primary Care (Base de datos para la Investigación Farmacoepidemiológica en Atención Primaria, BIFAP) from the Spanish Agency for Medicine and Health Products (Agencia Española del Medicamento y Productos Sanitarios) [17], previously described in the literature  [9].
The present study has potential We diabetes type I and II and we did not consider patient treatment variables in order to indirectly stratify the degree of diabetic control that could have an influence in CAP  [42, 43]. However, the BIFAP is one of the largest PC databases available  [18] , and the large sample of patients and variables available through it provides a good representation of the current population of diabetics who have had their first episodes of pneumonia in the context of a PC setting. This greatly strengthens the study.
Acknowledgements NEUMOEXPERTOS group is national working group on pneumonia prevention endorsed by the  Healthcare Research Insitute of Santiago de Compostela (Spain)  and consisting of:  F. Martinón-Torres ,  D. Vargas ,  E. Mascarós ,  E. Redondo ,  J. L. Díaz-Maroto ,  M. Linares-Rufo ,  A. Gil ,  J. Molina ,  D. Ocaña ,  I. Rivero-Calle. The data analysed for this publication is part of the BIFAP database, managed by the  Spanish Agency of Medicines and Sanitary Products (AEMPS). The results, discussion and conclusions of this study are those perceived by the authors only and do not represent in any way the position of the AEMPS on this subject. The authors are grateful for the excellent collaboration of family physicians and primary care pediatricians who participated in BIFAP. They would also like to acknowledge the assistance from the BIFAP team at the  AEMPS , and especially recognise the work of  Mónica Ríos Martínez ,  María Consuelo Huerta Álvarez  and  Cristina Amil Bastardo.
is labelled corresponding to ten geophysical phenomena, including both oceanic and meteorologic features. These images cover the entire open ocean and are manually selected from Sentinel-1A WV acquisitions in 2016. For each image, only one prevalent geophysical phenomenon with its prescribed signature and texture is selected for labelling. The SAR images are processed into a quick-look image provided in the formats of PNG and GeoTIFF as well as the associated labels. They are convenient for both visual inspection and machine learning-based methods exploitation. The proposed dataset is the first one involving different oceanic or atmospheric phenomena over the open ocean. It seeks to foster the development of strategies or approaches for massive ocean SAR image analysis. A key objective was to allow exploiting the full potential of Sentinel-1 WV SAR acquisitions, which are about 60,000 images per satellite per month and freely available.
, 2005; Alpers et al. , 2016)  and oceanic processes  (Espedal et al. , 1996; Jia et al. , 2018). Therefore, SAR is a unique tool for extensive observation of ocean-atmosphere interactions at sub-km scales  (Brown, 2000; Jackson and Apel, 2004). SAR sensors have a variety of acquisition modes. A common one is wide-swath which provides data over several hundred kilometres. More specifically for Sentinel-1, wide-swath acquisitions in TOPS mode  (De Zan and Monti Guarnieri, 2006 ) (Extended wide swath EW and Interferometric wide swath IW) are mainly used for monitoring of sea ice areas and coastal regions over the ocean. Due to power and data constraints of contemporary systems, the wide-swath mode with high-resolution capability is not able to collect data continuously and globally. The 'WaVe mode' (WV or WM), by contrast, is dedicated to measuring ocean waves from the global open ocean.
The primary intent of the small-sized vignettes is to provide ocean swell directional spectra as an ESA Level-2 ocean product  (Torres et al. , 2012). However, they also capture a much wider range of geophysical processes that are of significant interest in ocean-atmosphere interactions. Global coverage is combined with high resolution and routine acquisitions in all weather conditions during day and night; and at such high resolution (5 m) make S-1 WV a presence and unique data source for new geophysical applications. In this study, we define ten categories of different oceanic or atmospheric phenomena. These are the most common phenomena that can be observed in S-1 WV vignettes. The categories are pure ocean waves (POW), wind streaks (WS), micro convective cells (MCC), rain cells (RC), biological slicks (BS), sea ice (SI), icebergs (IB), low wind areas (LWA), atmospheric fronts (AF) and oceanic fronts (OF).
Details on these definitions are introduced in Section 2. A labelled SAR WV dataset containing 37,553 images is then established. Within each image, only the prevalent geophysical phenomenon with clear signature and/ or pattern is presented. The images are derived from the Single Look Complex (SLC) product of S-1 WV  (Torres et al. , 2012) , and provided in formats of Portable Network Graphics (PNG) and Georeferenced Tagged Image File Format (GeoTIFF). The proposed dataset, called TenGeoP-SARwv for 'Ten Geophysical Phenomena from SAR wave mode', is provided by IFREMER and publicly available at sea scientific open data publication (SEANOE): http:// www. seanoe. org/data/00456/ 56796/. The methodology used to create the dataset is described in section 3. Such a labelled dataset could benefit the strategic development of massive ocean SAR data analysis.
| Ten geophysical phenomena In this subsection, the ten defined oceanic or atmospheric phenomena are presented. Due to the 20-km WV image size, scales of observed geophysical phenomena are limited to about between 0. 1 and 5 km. We focus on the prescribed ten geophysical phenomena because they are commonly observed by the S-1 WV SAR vignettes. It is worth noting that the WV can also capture signatures of other geophysical phenomena like internal waves  (Jia et al. , 2018)  and atmospheric gravity waves  (Li et al. , 2013) , and signatures of ships or platforms. While such phenomenaS are seldom seen in the open ocean, we may include those categories in this dataset in the near future.
| DATASET CREATION 3. 1 | SAR image processing The 20 × 20 km image with 5 m resolution provides an image with more than 4,000 pixels in range and azimuth directions. This full-scale WV intensity image is not necessary for visual interpretation of oceanic or atmospheric phenomena. For instance, an example of a full resolution σ 0 image with features of wind streaks is shown in Figure  2a. It is clear that the wind streaks are concealed due to the low intensity contrast. In addition, the subplot of σ 0 mean values along range is displayed in Figure  2a *. It indicates that values of σ 0 slightly vary with different incidence angles within images. Therefore, three processing steps are applied to σ 0 images to enhance broadscale features of oceanic and atmospheric phenomena.
2. For machine learning-based exploitation For the sake of machine learning approaches, another normalization process is also implemented. As opposed to the dataset used for human visualization where the retained minimum and maximum values are specific for each image, fixed values of 0 and 3 common to the entire database are applied to all downsampled ssr images. In between these two values, the quantization process is instead performed on 16 bits  ([0, 65,535] ) ensuring all texture and radiometric information are numerically maintained. The TenGeoP-SARwv dataset is established based on the acquisitions of S-1A WV in VV polarization. This dataset consists of 37,553 SAR vignettes divided into our ten geophysical categories. For each category, the selection of SAR images covers the full year of 2016, and is manually labelled through visual inspection following the criteria documented in Section 2.
| Data format The image patches are provided in formats of Portable Network Graphics (PNG) and Georeferenced Tagged Image File Format (GeoTIFF). PNG files are processed with floating normalization for better visualization of human eyes. While in GeoTIFF files, high precision values (16 bits) as well as the geographical information are kept for exploitation of machine learning-based approaches and geophysical application. In addition, text files containing description of categories and information for the file name, labelling, swath, capture time, and centre latitude and longitude of each image are also provided. These SLC products of S-1 WV are freely available at 'Sentinel open access hub' of ESA https ://senti nel. esa. int/ web/senti nel/senti nel-data-access. Notice that the GeoTIFF of TenGeoP-SARwv dataset is completely different from that of ESA SLC product.
The latter contains original data and much more image processing information than this labelled dataset. 4 | DISCUSSION AND PERSPECTIVES SAR images capture signatures of various geophysical phenomena that are associated with air-sea interactions. Most of them have been previously discussed to provide a comprehensive understanding of their imprints on SAR imagery  (Alpers and Brümmer, 1994; Young et al. , 2005; Li et al. , 2013; Alpers et al. , 2016). Several of these phenomena factor significantly in the vertical transport of heat, moisture and momentum, and play key roles in the climate system  (Khalsa and Greenhut, 1985; Ufermann and Romeiser, 1999; Vandemark et al. , 2001; Schneider et al. , 2017). Although understood, these manifestations of key geophysical phenomena are not systematically analysed or ingested in numerical models.
In particular, automated detection and classification of these phenomena from the numerous SAR images is still challenging. The proposed SAR imagery dataset with individual annotations of oceanic or atmospheric phenomena should allow new efforts to test, validate and benchmark different methods for the identification of key geophysical processes. The annotations will allow massive classification of the data and open new perspectives for global or seasonal analysis of these phenomena. This work is a step towards broadening the scientific value of 25 years WV data acquired by ERS-1/2, Envisat ASAR and Sentinel-1  (Kerbaol et al. , 1998; Torres et al. , 2012; Stopa et al. , 2016). In addition, this labelled dataset can be directly used to statistically investigate the geophysical properties of the ten defined phenomena and characteristics of the imaged features.
Therefore, such a dataset of labelled ocean SAR imagery is put forward for both scientific and engineering applications for different communities such as deep learning, remote sensing, oceanography and meteorology. et al. , 2015). This new approach has been widely introduced to remote sensing  (Zhang et al. , 2016; Chen et al. , 2016; Cheng et al. , 2017). However, a lack of high-quality labelled datasets limits further application and development of CNN models for ocean SAR images. et al. , 2015)  and can also benefit from this dataset. However, there is still room in the proposed dataset for improvement. In the near future, more geophysical categories corresponding to other oceanic or atmospheric phenomena should be included. In addition, some of the vignettes contain multiple geophysical phenomena within the same scene even they are small-sized SAR images.
With the TenGeoP-SARwv dataset, one can potentially investigate the environmental conditions under which these phenomena occur. This would help to better understand their impact on sea surface roughness and therefore how they are imaged by SAR. In addition to that, ocean swell is of first interest as they are a fundamental phenomenon over the open ocean. The swell spectra inversion from SAR measurements are still distorted by the presence of various oceanic or atmospheric phenomena. The dataset of TenGeoP-SARwv can help us quantify the impact of these phenomena on SAR forward mapping from ocean wave spectrum to SAR image spectra. Therefore, it may be possible to recover more ocean swell estimation by taking their impact into account. This will benefit the study of global and local wave climate.
| Geophysical investigation SAR imagery yields high-resolution imprints of ocean surface and provides significant geophysical parameters for global weather and climate analysis, demonstrating its indispensable contributions to the Earth monitoring system  (Brown, 2000). Investigation of key geophysical phenomena by utilizing SAR data, for example wind streaks and micro convective cells, has been performed for many years, mostly in the stage of case and field studies  (Alpers and Brümmer, 1994; Vandemark et al. , 2001; Levy, 2001; Babin et al. , 2003; Li et al. , 2013). Statistical analysis of key geophysical phenomenon based on SAR data are barely attempted due to lack of reliable dataset. This proposed TenGeoP-SARwv dataset opens perspective to use S-1 WV acquisitions for global geophysical phenomena analysis.