dataesr/scientific-paragraphs-categorization huggingface dataset:
, 2017; Gimpel et al. , 2018). However, these data are developed at a large scale and their spatial resolution could be poorly adapted to local needs (regional/aquaculture farm scale). Data analysis or the use of local numerical models may also be required in addition in some areas. The AquaSpace tool includes maps produced by WATER (Where can Aquaculture Thrive in Europe, http://www. longline. co. uk/water/), a web-based application developed to produce maps of regions (at the spatial resolution of the Exclusive Economic Zone) suitable for cultivation of aquatic organisms  (Boogert et al. , 2017). The tolerance and optimal ranges (for 13 parameters) of 45 species are included within WATER. The species thresholds database is linked to an environmental conditions database to produce suitability maps.
Human activities (e. g. aquaculture, maritime traffic in terms of route locations or intensity, dredge disposal sites and locations of anchorages or submarine cables) as well as governance and regulation systems (e. g. aquaculture licensed areas, sanitary quality of shellfish culture areas, marine protected areas) are often described through the space they occupy. For these aspects, the European portal EMODnet (http://www. emodnet. eu/) is a valuable resource which has already been utilised within some applications  (Gimpel et al. , 2018 ). Yet again, access to local data can be more appropriate. For instance, EMODnet shellfish culture areas are simply identified by a presence symbol whereas in SISAQUA, aerial images with a resolution of a few meters enable us to show and delimit precisely the space occupied by aquaculture.
Analysis tools and functions The review of decision support tools undertaken by Coleman et al. (  2011 ) highlights the variety of functions and technological backgrounds that make the tools operational and applicable. Accessibility and visualisation by users are the basic features required for management tools. In MarineMap, geospatial data are centralized and accessible via a web browser. Visualisation tools include classical panning, zooming, querying and identifying data layers and features in a 2 and 3 dimensional space. In AkvaVis and SISAQUA, data are accessible via a webserver through a client/server infrastructure. They are documented with a catalogue of metadata and several of them are automatically updated by the WMS and WFS facilities. Tools should also be thought of in terms of usability.
In MarineMap, a great deal of attention was paid to the usability and responsiveness of the application through the development of a user interface that borrowed many conventions, lessons learned, and technologies from applications such as Google Earth. Additionally, developers were involved in the entire planning process, allowing them to customize and refine the application as the planning process evolved and feedback was gathered from stakeholders. The user can draw the proposed locations of Marine Protected Areas (MPAs) and analytical tools process the MPA attributes, e. g. distance matrices between habitats based on connectivity calculation. MarineMap has been used by stakeholders who had little to no experience with traditional GIS software. Running the AquaSpace tool however requires an existing knowledge of GIS  (Gimpel et al.
, 2018). The user defines the study area, the port from which aquaculture business should be transacted, the culture species and corresponding culture system, the constraints (e. g. exclusion zones or other management regulations), and the conflict matrix indicating conflicts or synergies with other human uses. The Assessment Report summarizes general planning, site information, and all inter-sectorial, environmental impact, economic   (Taranger et al. , 2015)  and a production zone management system of the industry  (Myksvoll et al. , 2018). In Normandy, SISAQUA integrates an indicator of salmon parasitism risk. The AquaSpace tool developed a distance-based function for estimating the risk of disease  (Gimpel et al. , 2018). Our tools integrate mainly geobiophysical data essential for potential aquaculture investors, while social and economic aspects are currently only available thorough indirect information.
However, a profitability module is under development within the APDSS tool. Economic and social valuation is considered as current gaps and key innovations to the future of marine spatial planning  (Brigolin et al. , 2017 , Pınarbaşı et al. , 2017). An economic analysis is proposed in the AquaSpace tool including a function providing i) a direct assessment of an aquaculture activity (e. g. revenue, added value, profit) and ii) an indirect assessment on other sectors related to aquaculture  (Gimpel et al. , 2018). Based on the functionalities shown for our tools and their analytical capacities for specific aquaculture spatial planning we conclude there are potentials for integrating more social and economic aspects to the tools.
In our project, the first goal of stakeholder consultation was to provide an accurate and local view of stakeholder expectations in each of our CS. Consultation was part of a broader survey over 16 study sites aimed at investigating the constraints to the expansion of the marine aquaculture industry, as well as the main needs and recommendations for better management of this activity from a stakeholder perspective  (Galparsoro et al. , 2020). This survey covered a wide range of aquaculture management strategies, coastal activities, environmental conditions, production capacity, technological development, and economic, social and policy contexts. It yielded a dataset of criteria which helped identifying aquaculture issues, geographical dimensions and relevant spatial data for each CS. The second goal of stakeholder involvement dealt with the demonstration and testing of our tools through a series of workshops.
Similar benefits were experienced when developing MarineMap, where tests in the first study region supported development of the remaining regions  (Merrifield et al. , 2013). As our tools are only partially implemented in management, this can be regarded as a gap. In the Normandy CS, SISAQUA has been transferred to an institutional spatial data infrastructure for marine environments which is maintained by Ifremer. This infrastructure guarantees the compatibility with all geographic information portals. Thus, the tool is further operationalized and applied within an institutional structure that can be regarded as prepared for implementation in aquaculture spatial management. In Norway, continued development of the AkvaVis tool was halted after the end of project but the conceptual ideas can be recognised in the existing operational web based portals, the Salmon Lice Map (https://www.
2016; Myksvoll et al. 2018) , which resulted in the postponement of the further development of the AkvaVis tool. Merrifield et al. (2013)  emphasise the critical role of funding in any software development for spatial decision support tools, an issue of high relevance for the tools developed within our study. In this respect, Salmon Lice Map and BarentsWatch operating at national level in Norway have ministerial financial support. The AkvaVis tool developed for the Carlingford Lough CS was designed with the intention to support decision making within in the aquaculture licensing processes within the CS area which are currently met with complex regulatory and management issues. The issues within this CS were further compounded by the multiple user and trans-boundary nature of the water body, and the limited financial timeframe of the AQUASPACE project which restricted further implementation.
The key strengths of AkvaVis and its companion tools SISAQUA and APDSS relate to their capacity to manage and display spatial data from different sources in a transparent way, the facility to use and display built-in indicators, and the long-term development perspective made possible by the maintenance strategy of tools, services and data depositories. Lessons learned during the AQUASPACE project highlighted that stakeholder involvement is necessary to ensure that the tools developed are beneficial for aquaculture spatial planning. Figure  1 : Synthesis of the process followed during this study giving for each CS i) an overview of aquaculture (arrows indicate the trend of development for each species; see Table  A1  and Section 2),  ii) main aquaculture issues (see Table  A2  for an exhaustive list), iii) stakeholder consultation (see  Sections 3 & 4) , iv) tool purpose and functions (see Tables  A3  and A4 ) and vi) lessons learned (see Section 4).
The rationale to utilise open source data was addressed by Merrifield et al. (2013)  who stated that the use of free and open source software facilitates additional developments and applications to other case studies, permitting other developers to alter the code and deploy at a minimum additional cost. The AquaSpace tool is one of the first open-source tools using datasets at a European scale that allows for a spatially explicit and integrated assessment of indicators reflecting the economic, environmental, inter-sectorial and socio-cultural risks and.
Acknowledgements This work was supported by  AQUASPACE  ( Ecosystem Approach  to making  Space for Sustainable Aquaculture ) project, funded by the  European Union  under the  H2020 Programme  (grant agreement no. 633476 ). The first developments of the Norwegian AkvaVis tool were funded by  Institute of Marine Research, Aquaculture Program, Norway. We are grateful to  A. Ervik ,  I. Døskeland  ( Vestland County Council ) and  A. A. Hageberg  ( Norwegian Research Center AS ) for their fundamental contributions to the development, and to participants in the project steering group and stakeholder workshops for contributions. Work undertaken in support of the development of the AkvaVis tool for Carlingford was funded by the  Department of Agriculture, Environment and Rural Affairs, Northern Ireland.
For example, on the one hand, using multiple injectors may increase the reservoir injectivity, although this is highly dependent on factors such as reservoir pressure, injection rates, and spacing between wells. On the other hand, the construction and operation of wells is a significant contributor to investment and operating costs, and may not always be justified by the increased volume of CO 2 that may be stored. In this paper we build on the analysis in De Simone et al. (  2019 ) to develop a methodology to estimate CO 2 injection rates that maximise storage whilst not exceeding a limiting pore pressure increase specific of the reservoir. A range of scenarios of injection well number and inter-well distance is explored. The methodology has been implemented within an open source software tool named CO2BLOCK.
Dynamic Storage Resources of the UK We apply the methodology described in Section 2 (Fig. 1 ) to assess the maximum potential for CO 2 storage in the UK offshore system. All data have been collected from the CO 2 stored database  (Bentham et al. , 2014; Energy Technologies Institute LLP, 2018) , which contains information including geological data for nearly 600 potential CO 2 storage units located offshore UK. These include oil and gas reservoirs and saline aquifers. We perform an initial screening to identify a subset of the sites with the most beneficial attributes for storage. Our analysis is limited to saline aquifers, representing about the 85% of the total storage capacity in the UK  (Gammer et al. , 2011; Pale Blue Dot Energy, 2016). The analysis is further restricted to formations where the caprock is deeper than 1 km in the subsurface, to ensure CO 2 remains in a supercritical state  (IPCC, 2005).
Only sites with permeability greater than 1 mD and porosity greater than 0. 1 are considered. Finally, the aquifers with theoretical CO 2 storage less than 200 Mt are excluded. The screening reduces the consideration from 292 potential saline aquifer sites to 25, mostly located in the Northern, Southern or Central North Sea (see inset of Fig. 9  and Section S4 in supporting information for further details). They represent approximately 1/3 of the total theoretical capacity of 60 Gt provided by the 292 saline aquifers. The database does not provide information about the in situ stress conditions and the mechanical parameters, which are essential for the evaluation of the maximum sustainable pressure. We assume that the maximum stress is the vertical stress, σ v , which implies that the minimum stress is horizontal, σ h.
Countering this, however, Heinemann  A detailed site characterization is not usually available and there are significant uncertainties in the storage resource estimates. The greatest uncertainty is related to the geomechanical parameters, which are often difficult to estimate. Given the lack of information about these parameters in the CO 2 stored database, we explore here the sensitivity of the storage capacity to the values of the geomechanical parameters by assuming a range of possible values. The ratio of the average horizontal stress to the vertical stress, σ h /σ v , varies over a range between 0. 5 and 2  (Brown and Hoek, 1978). Values smaller than 1 correspond to the case of a normal faulting regime (extensional), whereas values greater than 1 correspond to a reverse faulting regime (compressional).
This approach is also adopted in a similar software, EasiTool  (Ganjdanesh and Hosseini, 2017, 2018) , but CO2BLOCK includes a correction factor for the superposition error. From the output, optimisation may be performed, for example, to consider tradeoffs between costs and maximising injection volumes in a storage resource. We demonstrate the use of CO2BLOCK to perform an estimate of the maximum storage resource in the UK offshore system, including an uncertainty analysis. Neglecting consideration of any regulatory and economic constraints, we estimate that around 140 Gt of CO 2 can be safely stored in 30 years through injection into 25 sites in UK identified through a screening for advantageous reservoir properties. Uncertainty from leading order geological parameters alone result in an order of magnitude range in the estimate, from 25 -250 Gt of resource potential.
Acknowledgements The authors acknowledge financial support from the  MESMERISE-CCS  ( Multi-scale Energy Systems Modelling Encompassing Renewable, Intermittent, Stored Energy and Carbon Capture  and  Storage -EP/M001369/1 ) and the  UKCCSRC 2017 (UK Carbon Capture and Storage Research Centre   2017 -EP/P026214/1 ) projects funded by the  Engineering and Physical Sciences Research Council (EPSRC). All data are detailed in the manuscript or in the Supporting Information. CO2BLOCK is available at the repository https://github. com/co2block/CO2BLOCKor at http://doi. org/10. 5281/zenodo. 4313311).
Methods This study, approved by the French national ethics committee and registered in the Clinical Trials database (NCT 03503110)  [36] , did not modify the usual surgical nor brain mapping protocols. Our data set consisted of newly acquired anonymized presurgical dMRI and intrasurgical ECoG signal recordings, both of which we describe in detail later in this section. They are not publicly available due to restrictions imposed by the administering institution. The authors will share them by request from any qualified investigator after completion of a data sharing agreement. The source code for the data post-processing, correlation study, and prediction of CCEPs is available for download at: https://doi. org/10. 5281/zenodo. 3989987 [37].
Data acquisition Diffusion MRI. We acquired presurgical diffusion MR images with 2x2x2 mm voxel size resolution. Our protocol comprised 4 shells having b ∈ {400, 800, 1550, 3100} [s/mm 2 ] with {6, 13, 29, 51} directions, respectively, interleaved with 6 images without diffusion weighting (b = 0). The pulse width was δ = 0. 0322 s and the diffusion time ∆ = 0. 0450 s. We used the above acquisition parameters since they maximized image reconstruction accuracy of the MAPL signal representation  [34]  under the constraint of 25 minutes of imaging time on the clinical GE 3T-scanner. The MAPL helped us obtain numerous brain microstructure indices  [39]  that we present in Subsection 2. 6.
During the acquisition, the neurosurgeon stimulated consecutive cortical sites located in the proximity of all accessible electrodes. Note that parts of strips could be inserted beyond the bone flap, slipped between the dura matter and the cortex, allowing to record the signal in areas inaccessible to stimulation (Figure  2b ). We used a 32-channel signal amplifier manufactured by TMSi ® with our recording electrodes set to the common reference mode, the ground electrode placed on the patient's back, and all the remaining inputs being short-circuited. Finally, the recordings were made using ASALAB software by ANT Neuro ® with a 2 kHz sampling rate.
Structural connectivity For each patient, we ran probabilistic tractography algorithm iFOD2  [40]  twice, using the same dMRI data acquired prior to the surgery. The first run was destined for surgical planning and neuronavigation. To this end, we computed a whole-brain tractogram containing one million streamlines. From that, we dissected AF and SLF3, as mentioned earlier, using MI-Brain software by Imeka ®. Next, we overlaid the streamlines of interest on a T1-weighted image that we transferred into the neuronavigation system produced by Brainlab ®. In the operating room, the neurosurgeon placed the ECoG electrodes on the cortex in the precise locations of the WM bundle terminations indicated with tractography and localized spatially with the neuronavigation system (Figure  2 ). Our second tractography was performed retrospectively, after a surgery.
Acknowledgements This work has received funding from the  ANR/NSF  award NeuroRef. The authors would like to thank  Lavinia Slabu  for her valuable help in performing the ECoG signal acquisition,  Gabriel Girard  for a piece of advice, and  Amandine Audino  for the engineering support. We also thank the  CHU Nice  for promoting this study and  INRIA  for funding it.
An analysis of recent literature This section synthesizes the existing literature focusing on digital and social media marketing and discusses each theme listed in Table  1  from a review of the extant literature. Studies included in this section were identified using the Scopus database by using the following combination of keywords "Social media", "digital marketing" and "social media marketing". This approach is similar to the one used by existing review papers on a number of key topics (e. g. Dwivedi et al. , 2017 , Dwivedi et al. , 2019a , Dwivedi et al. , 2019b , Dwivedi et al. , 2019c; Marriott et al. , 2017; Shareef et al. , 2015). Based on the classification provided by  Kannan and Li (2017)  the overall topics were divided into four themes: environment, company, outcomes, and marketing strategies.
3. 7. 1. 2 The interdisciplinary nature of the field. The fragmented nature of the social media marketing knowledge base plays a significant role in the inter-disciplinary nature of the SMM field. For example, systematic literature reviews on social media marketing, important in distilling the essence of a field and offering future research agendas, are to be found in journals in a range of disciplines including information management, marketing, industrial marketing, data systems, psychology, and decision support. Whilst there are some commonalities between these reviews, there is also significant variation in their scope, and in their proposals for future research, although there is some consensus on the need for the inclusion of further research on both (1) social media practice and strategy, and (2) social media consumer behavior  (Rowley and Keegan, 2019).
Social media marketing management. Social media marketing management is a very broad field, and becomes even more complex when differing contexts are considered, as discussed further below. However, surprisingly, it is one of the fields that has received relatively little attention from researchers, possibly because exploring this area involves access to managers in organisations, which is often more difficult than access to consumers or social media posts and content. Despite having received some limited attention, the research questions below require further investigation: • How can social media be used in such a way as to justify investment in SMM? What is the Return-on-Investment (ROI)? • Which data analytics offer the most meaningful insights to support the development of social media campaigns? What is the relationship between the different data analytics that are available from different social media platforms? • How do organisations articulate and realize their social media marketing objectives? What are their objectives, e.
We need interdisciplinary and intersectional perspectives to develop best practices that afford every person the ability to develop the skills to successfully navigate the digital world. Rather than delegate this important task to grade school education, data literacy needs to be a life-long commitment that is not only taught, but reinforced, by various stakeholders, such as higher education, workplaces, and government. Considering that this area is in need of further research and investigation, this paper makes the following research proposition: Proposition: The public's comfort with social media marketing may be affected by data literacy. As the public-and governments-gain data literacy, there may be increasing pressure on organisations to engage in more transparent and ethical data practices.
Briefly, for each species, we selected k-mers that were found in all female DNA and RNA samples but in none of the male samples. RNA-seq reads containing these female-specific k-mers were extracted and assembled into putative W-transcripts. Male and female DNA reads were further mapped to putative W-transcripts longer than 200 base pairs (bp), and only transcripts with a high number of reads mapping perfectly in females but not in males were kept in our set of candidates (Sup. Figures  2  and 3 ; specific steps to improve the assembly in S. japonicum are described in the methods). We used BLAT  (Kent 2002)  to map our candidates to the gene models (CDS) of the S. mansoni genome (v7, Sup. Table  2 ) in order to assess the efficacy of our pipeline (as the S. japonicum genome is not assembled at the chromosome level): of the 86 S.
mansoni candidate W transcripts (Sup. Dataset 1), 37 mapped to known protein coding genes (Table  1. A). The majority of these (24) mapped primarily to annotated W-linked genes in the current assembly (v7, obtained from female and male DNA), confirming the validity of our approach for detecting female-specific protein-coding sequences. Another 9 mapped to Z-linked genes, and likely represent true W-genes which are missing from the current assembly. Finally, 4 mapped to genes in other chromosomal locations; these may represent W-linked genes that do not have a Z-homolog, or false positives. For the rest of our analyses, we combined our S. mansoni W-candidates with the annotated W-genes in this species (when a gene was found in both sets, only the longest transcript was kept) (Table  1. B, Sup.
Dataset 2), yielding a "combined" set of candidates of 90 transcripts, 42 of them protein-coding. A similar number of S. japonicum W-candidates mapped to S. mansoni coding sequences (48 out of 94), all of which did so to known Z-linked genes, again confirming the efficacy of our pipeline for detecting W-linked protein coding genes (Table  1. D, Sup. Dataset 3). In order to investigate the evolutionary history of these W-derived coding sequences, we further extracted their closest homologs in the genome. For S. mansoni, we remapped the candidate W-transcripts to the CDS set, after excluding annotated W-genes. We retrieved a close homolog for 40 out of the 42 protein-coding transcripts; 34 of them mapped to a homolog on the Z-chromosome, as expected if W and Z-linked genes share a close ancestry (Table  1.