dataesr/scientific-paragraphs-categorization huggingface dataset:
Conclusions In the paper we present a modeling analysis of the 24-hour marine drift by the windsurfer whose mast broke on 29 Oct 2018 16 UTC, during a 29 Oct 2018 Scirocco storm in the Northern Adriatic. We conduct an interview with the survivor in order to reconstruct his trajectory and its uncertainty. We present numerical circulation (NEMO), wave (ECWAM), atmosphere (AL-ADIN SI) and Lagrangian tracking models, used in an attempt to hindcast this trajectory. We present available measurements from the regional coastal buoy Vida and HF surface current radar to qualitatively assess marine conditions in the Gulf of Trieste during the period of the drift. Two Lagrangian tracking models were employed to compute the survivor's trajectory. wave data and Stokes drift computation prior to particle advection, but this option was not used for the simulations performed in this paper.
Acknowledgements. The authors would first and foremost like to thank the survivor of the incident,  Mr. Goran Jablanov , for his willingness to respond to the interview request and to reconstruct the trajectory of his drift as accurately as possible. M. L. would like to thank  Jean Bidlot  ( ECMWF ) for his kind suggestions regarding the regional Adriatic setup of the ECWAM cycle 46R1 code. The authors would like to thank  Sašo Petan  ( ARSO ) for providing Soča/Isonzo river runoff at Solkan station. The authors would like to thank all technicians and engineers at our institutions for enabling and supporting the research work. M. L. wishes to acknowledge support of the  Slovenian Research Agency  grant  J1-9157 : "Drivers that structure coastal marine microbiome with emphasis on pathogens -an integrated approach".
5 km horizontal resolution 22×20 regular grid (see Figure 5 for coverage during the event and both station locations). Combined data are stored in databases and can be visualized in near real time at http://www. nib. si/mbp/en/oceanographic-data-and-measurements/other-oceanographic-data/hf-radar-2. The two WERA HF systems are operated and maintained in collaboration between researchers, engineers and technicians from OGS and NIB. 3 Models 3. 1 Ocean, Wave and Atmospheric Models 3. 1. 1 NEMO Circulation Model (Madec, 2008)a high horizontal resolution (1 • /111 or roughly 1000 m) setup of NEMO v3. 6(Madec, 2008)over the Adriatic basin on a regular 999×777 longitude-latitude grid and 33 vertical z * -levels with partial step. Model domain spans 12 • -21 • E and 39 • -46 • N, see Figure3. Maximum vertical discretization stretch is located at 15th level to allow for appropriate vertical resolution near the surface.
SSLs acoustics sensing and environmental data We performed a hydroacoustic survey along the "Petite Côte", south of Cap-Vert peninsula off Senegal (14. 6-13. 5 • N, 16. 9-17. 6 • W). The survey was conducted with the research vessel Antea of the French National Research Institute of Sustainable Development (IRD France) during the upwelling season from 6 to 18 March 2013. The Petite Côte is a nursery area for fish and is the main area in which juveniles of numerous species (particularly small pelagic species) concentrate  (Diankha et al. , 2018; Thiaw et al. , 2017). Strong upwelling occurs during spring, which contributes to high primary productivity, thus providing an ideal nursery area for commercially important fish species  (Tiedemann and Brehmer, 2017). We collected hydroacoustic data along three transects (T1 (North), T2 (intermediary), and T3 (south)) in 18 nautical miles (nmi) perpendicular to the coast (Fig.
1 ). Hydroacoustic data were continuously recorded (day and night) using a Simrad EK60 echo sounder  (38, 70, 120, and 200 kHz) , set at 20 log R time-varied gain function (where R is the range in meters) and using a pulse length of 1. 0 ms. In this study, we used the acoustic monofrequency approach (using 38 kHz, one of the most current frequencies used in fisheries surveys) to study the spatiotemporal SSL structure. The 38 kHz frequency offers the advantages of depth penetration, covering the whole vertical range of SSLs. The multifrequency echogram was used to identify the main scatterers of SSLs and to justify the SSLs extraction threshold (see below). Transducers were calibrated following the procedures recommended in  Foote et al. (1987). Considering the aft draught of the vessel, the acoustic near field, and the presence of acoustic parasites (including air bubbles) in the upper part of the water column, we have applied an offset of 10 m (acoustic data above 10 m have been deleted).
Echoes along the three transects were integrated at a spatial resolution of 0. 1 nmi × 1 m depth. We estimated the SSL acoustic density by calculating the nautical area scattering coefficient (NASC or s A ), which represents the relative biomass of acoustic targets. We assumed that the composition of the scattering layers and the resulting scattering properties of organisms in the SSLs are homogeneous within each layer we identified (sensu  MacLennan et al. , 2002). We analyzed integrated echoes using the in-house tool "Matecho"  (Perrot et al. , 2018). Matecho is an integrative processing software that allows us to manually correct echograms (e. g. , by correcting bottom depths, removing empty pings, removing echogram interferences, and reducing background noise). For echo-integration accuracy, Matecho computes a quality factor (QC) (Fig.
S1  in the Supplement) for each echo-integration cell, which is the number of integrated samples divided by the total number of samples in one echo-integration cell. After each echogram cor- rection, we extracted the SSLs that were below the mean acoustic volume backscattering strength (S v in dB) threshold of -75 dB (i. e. , values below -75 dB were excluded from the analysis). Cascão et al. (2017)  and  Saunders et al. (2013)  excluded marine pelagic organisms that backscattered at -70 dB, a threshold based on the aggregative behavior of marine pelagic organisms. The SSL extraction method is based on a threshold of -75 dB and a MAT-LAB algorithm used in Matecho named "contourf. m" (https: //ch. mathworks. com/help/matlab/ref/contourf. html, last access: 12 January 2019), which appear relevant to extract the main SSL at 38 kHz (Fig.
S2 ). This process performs a segmentation of the echo integration from the given threshold on echo levels to extract (by calculation of isolines according to the selected S v threshold) the attached echo groups that formed the SSLs and their associated contours. Based on this contour, a set of descriptors are estimated, e. g. , up and down depths of SSL and thickness. In our study, the backscattering was due to zooplankton and micronekton, as well as small pelagic fish. The inshore area is known to be rich in copepod and fish larva  (Ndour et al. , 2018; Tiedemann and Brehmer, 2017) ; however, a low sample number was collected in the coastal inshore water due to safety reasons, i. e. , the research vessel investigated areas of > 20 m bottom depth. We collected hydrographic data using a calibrated Sea-Bird SBE 19plus conductivity, temperature, and depth (CTD) probe.
From 6 to 8 March 2013, we conducted CTD casts along three transects at 36 stations. At each station, sensors measured water temperature ( • C), depth (m), fluorescence (µg L -1 ), water density (here sigma-theta, kg m -3 ), and DO. Global High Resolution Sea Surface Temperature (GHRSST) data were extracted from daily outputs by the Regional Ocean Modeling System group at NASA's Jet Propulsion Laboratory (JPL OurOcean Project, 2010). Daily SST data (GHRSST Level 4 G1SST Global Foundation Sea Surface Temperature Analysis) were averaged for the 3 d of surveying using SeaDAS software version 7. 2 (https://seadas. gsfc. nasa. gov/, last access: 10 November 2018) and interpolated on maps using R software (R Core Team, 2016). Cubic spline interpolations of gridded data were used within the R package Akima  (Akima et al.
Data analysis After extracting SSLs with Matecho, we developed an ad hoc MATLAB extension of Matecho named "Layer" (S1 in the Supplement). We obtained SSL thickness, minimum and maximum SSL depths (D min and D max , respectively), and an echo-integrated echogram from Matecho output files to provide it to another MATLAB program "ComparEchoProfil" (S2). ComparEchoProfil allows the user to fit in time and depth echo-integrated echograms to the associated CTD vertical profiles. We used the equation below to calculate thickness: Thickness = D max -D min (1) Mean nautical area backscattering coefficient (s A , NASC) and mean acoustic volume backscattering strength (S v in dB) profiles were based on the average of three ESUs (small-scale elementary sampling units): the ESU nearest to the CTD position (ESU ctd ) as well as previous and following in correspondence with CTD depths (d n ) s A (d n ) = i=ESU ctd +1 i=ESU ctd -1 s A (i, d n ) /3, (2) S v (d n ) = 10 × log 10 i=ESU ctd +1 i=ESU ctd -1 10 (S v (i,d n )/10) /3.
(3) The ComparEchoProfil displayed the profile for S v in dB over an ESU of 0. 1 nmi around each CTD station. The program also allowed us to display acoustic profiles for physicochemical parameters (temperature, CHL (chlorophyll), density, and DO) associated with S V profiles (Fig. 2 ). The output included meta-information (station ID, station date, station time, latitude and longitude, diel phase (day, night), and bottom depth), all of which we associated with SSL descriptors (SSL thickness, maximum SSL depth, S v , and s A ) based on classic fish school descriptors  (Brehmer et al. , 2007 (Brehmer et al. , , 2019) )  and physicochemical parameters associated with each SSL. We applied hierarchical cluster analyses (HCAs) to discriminate between water masses of inshore and offshore stations over the continental shelf based on CTD data collected at 10 m depth.
HCA was based on Euclidean distance and Ward's aggregation method  (Ward, 1963). We used principal component analysis (PCA)  (Chessel et al. , 2013)  on the same dataset to determine similarities between CTD stations relative to environmental parameters. Physicochemical parameters were standardized a priori because they were measured with different metrics. Inshore-offshore variability of morphometric (thickness, depth) and acoustic characteristics (s A ) of the SSLs are investigated in the discriminated groups considering bottom depth and diel period. Diel transition periods are removed from analyses to avoid SSL density change biases due to diel vertical migrations. Transition periods are defined using sun altitude, i. e. , around sunset and sunrise corresponding to a sun altitude between ±18 •  (Lehodey et al.
The selection of the best models was performed using stepwise procedures. Stepwise selection was based on minimizing the Akaike information criterion (AIC)  (Akaike, 1974). The relative importance of each variable in total deviance explained was determined from the "relaimpo" R package  (Tonidandel and LeBreton, 2011). Validity assumptions of the models were then assessed by checking for normality of distributed errors and homogeneity of residuals (Figs. S3 to S5). For the ANCOVA, SSL density (s A ) was log 10 transformed for normality assumption. For all statistical tests, the significance threshold used was 0. 05. Ocean Sci. , 16, 65-81, 2020 www. ocean-sci. net/16/65/2020/ We used R software (R Core Team, 2016) for statistical analyses and to map data. We used the R package "Cluster"  (Maechler et al.
Acknowledgements. Results of this paper were discussed during international conferences (ICAWA) in Dakar (2016) and in Mindelo (2017). We thank the participants for helpful comments made during these conferences. We are thankful to the  AWA  project ( Ecosystem Approach  to  Management of Fisheries and Marine Environment in West African Waters ), funded by  IRD  and the  BMBF  (grant  01DG12073E ), and the  PREFACE  project  (Enhancing Prediction of Tropical Atlantic Climate and its Impacts ), and the  TriAtlas  project, as well as all  IRD -ISRA/CRODT -Genavir  staff for helping us at sea during the survey (https://doi. org/10. 17600/13110030 ,Brehmer, 2017). We thank  Gildas Roudaut ,  Fabrice Roubaud ,  François Baurand , and the  US Imago (IRD)  for data collection aboard FRV Antea (IRD), the  Gnavir crew of Antea ,  Dominique Dagorne  (IRD) curating satellite products, as well as the personal of  ISRA/CRODT (Senegal) ,  IRD DR-Ouest (France)  and  INRH (Morocco)  for their administrative help during  Ndague Diogoul PhD  stays in Morocco financed by  OWSD (Organization for Women in Sciences  for the Developing World).
Code availability. "Matecho" is an open-source tool available at https://svn. mpl. ird. fr/echopen/MATECHO/ (last access: 15 February 2019) (login: userecho, password: echopen). Other MATLAB codes used in this work are "Layer" and "ComparEchoProfil" and are shared in the Supplement sections S1 and S2 of this paper. "Matecho" (Perrot et al. , 2018)  is an Open-Source Tool available at: https://svn. mpl. ird. fr/echopen/MATECHO/ (login: userecho, password: echopen).
Documentation Each APA is delivered with a traveler document in which specific assembly information is gathered, initially by hand on a paper copy, then entered into an electronic version for longer term storage. The traveler database contains a detailed log of the production of each APA, including where and when the APA was built and the origin of all parts used in its construction. Assembly issues that arise during the construction of an APA are gathered in an issue log for each APA, and separate short reports provide details of what caused the occurrence, how the issue was immediately resolved, and what measures should be taken in the future to ensure the specific issue has a reduced risk of occurring.
APA quality control during integration and installation All active detector components are shipped to the SDWF before final transport to SURF. After unpacking an APA (underground at SURF), a visual inspection will be performed and wire continuity and tension measurements will be made. Tension values will be recorded in the database and compared with the original tension measurements performed at the production sites, as was done for ProtoDUNE-SP and shown in figure  2. 20. Definite guidance for the acceptable tension values will be available to inform decisions on the quality of the APA. Clear pass/fail criteria will be provided as well as clear procedures to deal with individual wires lying outside the acceptable values. This guidance will be informed also by the ProtoDUNE-SP experience. In addition, a continuity test and a leakage current test is performed on all channels and the data recorded in the database.
To avoid problems during most of the production phase, we plan to emphasize training as well as documentation of the QA plan. Reference parts will be tested at several sites to ensure consistent results. At a single site, some parts will be tested repeatedly to ensure that the response of the apparatus does not change and that new personnel involved in testing detector components are as proficient as more experienced personnel. All data from the QC process will be stored in a common database, and the yields of the production will be centrally monitored and compared among different sites. The procedures adopted for detector construction will evolve from the experience gained with ProtoDUNE-SP. A first version of the testing procedures will be put in place in 2020, while the final designs of the detector components are completed and new prototypes are tested.
ASIC testing is performed with dedicated test boards that allow tests of the functionality of the chips and are also used to determine the initial calibration constants that are stored in a database for later use. The dedicated test boards reproduce the entire readout chain where the input to the FE amplifier or to the ADC is replaced by an appropriate signal generator, and some parts of the backend may be replaced by a simple FPGA that is directly connected to a computer. Tests of the FEMBs can be performed by connecting them directly to a standalone WIB, as discussed in section 4. 2. 6. Given the large number of ASICs and FEMBs required for one DUNE FD SP detector, we plan to distribute the corresponding QC activities among multiple institutions belonging to the TPC electronics consortium.
Test results will be stored in a database, and criteria will be developed for the acceptance of ASICs and FEMBs. The acceptance rate will be monitored, and in case of problems, the failures will be analyzed and root cause analyses will be performed. If necessary, the test program will be stopped at all sites while issues are being investigated. In the case of CRYO, since each FEMB will only have two chips, it may be possible to bypass chip-level testing altogether. If the chip-level failure rate is low enough, it may be sufficient to simply test assembled FEMBs and reject or rework those that fail the tests. For the large numbers of ASICs required for one DUNE FD SP detector (6,000 or 54,000 chips depending on the ASIC solution chosen), manual testing of the chips requires excessive amounts of resources and, based on the lessons learned from constructing ProtoDUNE-SP, would lead to unacceptable rejection factors.
These injected pulses will also be used to determine the calibration constants of the ADC. The test setup requires one WIB and a printed-circuit board similar to those used on the cryostat penetration, allowing simultaneous testing of four FEMBs. A standalone 12 V power supply is required, and the readout of the WIB uses a direct Gb Ethernet connection to a PC. The setup used for ASIC testing is similar. In both cases, the data can be processed locally on the PC, and the results from the tests and calibrations are then stored in a database. The plan is to have the capability to retrieve these test and calibration results throughout the entire life of the experiment. As in the case of ASIC testing, we will monitor the test results to ensure that all sites have similar test capabilities and yields and to identify possible problems during production.
Many of these software tools already exist and have been used for the simulation and the reconstruction of -207 --207 --207 -ProtoDUNE-SP. In the coming years they will be updated to reflect the changes to the detector design relative to ProtoDUNE-SP. Similarly, the TPC electronics consortium has an interface with the Software and Computing consortium that covers mostly the need for data storage and data access. This includes both database needs (for storing detector calibration constraints and detector configurations) and disk space needs (for storing the data from special calibration runs that are used to obtain the calibration data). The calibration data on the response shape of the electronics and on its gain are also relevant to the Calibration consortium, which is tasked with obtaining high-level calibrations of the detector response.
Incoming materials control Each PD sub-component assembly site will have a quality control supervisor, who will be responsible for overseeing all quality-related activities at that site, maintaining all production records and assembly travelers, and uploading them to the production database as appropriate. This local supervisor will report directly to the PD consortium lead. All materials for PD module assembly will be delivered to the UNICAMP module assembly facility with a QC traveler (in the case of materials custom fabricated for DUNE) generated prior to arrival at the assembly site or will have an incoming materials traveler generated immediately -274 --274 --274 -upon receipt of the component (for commercial components). These travelers will be scanned (or uploaded if in electronic format) upon receipt at the assembly facility, and the data stored in the DUNE QC database.
Materials will either arrive with a pre-existing DUNE inventory control batch/lot number, or will have one assigned prior to entering the assembly area. Bar code labels attached to storage containers for all components in the assembly area will facilitate traceability throughout the assembly process. Immediately upon receipt, all materials will undergo an incoming-materials inspection, including confirmation of key dimensional tolerances as specified on their incoming materials documentation. The results of these inspections will be included on the traveler for that batch/lot and entered into the database. In the case of deviations from specification noted in these inspections, the deviation from nominal will be recorded in an exception section of the traveler, as will the resolution of the discrepancy.
Assembly procedures As was done for ProtoDUNE-SP, detailed step-by-step written procedure documents will guide the assembly for each PD module, with a QC traveler completed and recorded in the database. Travelers will be based on those used for ProtoDUNE-SP, modified as need to capture additional data needed for X-ARAPUCA module fabrication. ProtoDUNE-SP experience suggests that a two-person assembly team is necessary. Our current assembly plan envisions a pair of two-person assembly teams working simultaneously, with a fifth person acting as shift leader. This labor force will allow for production of 20 PD modules per week, meeting our production requirements. 31For example, GAMTUBE T1510™ from GAM Products, Inc. , http://www. gamonline. com/catalog/gamtube/index. php. 32F007-010™ Amber with Adhesivehttp://www.
It is critical that the performance specifications for the PD system meet the needs of the physics and reconstruction teams, both in terms of detector performance and background (including false triggers from radiologicals and light contamination from cryostat light leaks, HV system corona discharges, and calibration system effects such as purity monitors, laser flashers and cameras. These interfaces will be captured here. Light contamination of any nature must be studied quantitatively so that the impact on error budget due to misclassification of events can be calculated. Quantitative indicators should be established using ProtoDUNE-SP data, which should also provide the basis for identification algorithms of spurious signals caused by light leakage. The SP PD system shares interfaces with the DUNE core computing systems, primarily with databases.
The two databases that will have direct interfaces with the SP PD system are the hardware/QC and calibration databases. All the off-line calibration values will be stored in the DUNE calibration database. Additionally, the system will interface with the DUNE hardware database. During all stages of production/procurement and QC evaluations of PD system components, as well as integration and installation of the system, tracking of the hardware, and test results will be stored in the DUNE hardware/QC database. The SP PD system consortium will work with the database -291 --291 --291 -group to ensure that all schema, applications, and procedures for the database interfaces are developed. As components of the system will originate at multiple institutions, well defined procedures and management will be required to ensure that all data is archived in the DUNE hardware/QC database.
Bagged modules will be packaged in groups of ten modules (matching the need for a single APA transported in a single shipping box), approximately 20 cm × 20 cm × 250 cm long. These shipping boxes will be gathered into larger crates to facilitate shipping. The optimal number per shipment is being considered. Documentation and tracking of all components and PD modules will be required during the full logistics process. Well defined procedures are in place to ensure that all components/modules are tested and examined prior to, and after, shipping. Information coming from such testing and examinations will be stored in the DUNE hardware database. Each PD module shipping bag will be labeled with a text and barcode label, referencing the unique ID number for the module contained, and allowing linkage to the hardware database upon unpacking prior to integration into the APAs underground.