dataesr/scientific-paragraphs-categorization huggingface dataset:
6b ). Additional evidence of shortcomings of the reference dataset arises from the comparison between the reference salinity calculated by the OWC OM algorithm on the basis of the ADMT-Argo dataset, and the RG  (Roemmich and Gilson 2009)  climatology (Fig. 6c ). A large discrepancy was observed in June 2017 when the reference Argo dataset yielded lower salinity. Comparison between the ADMT-Argo reference data and other climatologies and gridded monthly products [World Ocean Atlas 2005-17 of 18 resolution (WOA1)  (Garcia et al. 2018; Locarnini et al. 2019; Zweng et al. 2019) ; Monthly Isopycnal and Mixed-Layer Ocean Climatology (MIMOC)  (Schmidtko et al. 2013) ; CSIRO Atlas of Regional Seas (CARS2009)  (Ridgway et al. 2002) ; In Situ Analysis System (ISAS13)  (Gaillard 2015; Gaillard et al.
9a, b ). The importance of reference data for salinity drift assessment was evident from the beginning of the Argo program  (Gaillard et al. 2009; Kobayashi and Minato 2005). Previous studies demonstrated an increase in the number of Argo profiles erroneously attributed as suspicious in dynamic and weakly stratified regions like the North Atlantic  (Böhme and Send 2005; Cabanes et al. 2016) , high eddy kinetic energy regions such as western boundary currents  (Jia et al. 2016; Wang et al. 2013) , or during anomalous events such as El Niño-Southern Oscillation (ENSO)  (Cabanes et al. 2013). This study also demonstrates the importance of long-term trends in salinity  (Li et al. 2019; Liu et al. 2019; Wang et al. 2017)  which must be taken into account in OWC analysis. We see that increasing the OWC time separation factor causes the Argo DMQC reference databases to approach climatology, while current conditions are different from climatological values.
Summary and conclusions This study demonstrates that salinity measurements collected by Argo floats equipped with inductive conductivity cells are stable for both older and newer design of the RBRargo. While the older design, where conductivity cell and thermistor are separated in space, presents an offset slightly exceeding Argo accuracy specifications, the newer design that combines the conductivity and temperature sensors is proven to be within the Argo accuracy requirements. The Core Argo program currently depends mostly on the SBE41 and SBE41CP CTDs produced by a single manufacturer (Sea-Bird Scientific). While this allows relative consistency in the collected data, it exposes the entire Argo program to a ''risk of single points of failure''  (Roemmich et al. 2019). To mitigate this risk, the Argo program welcomes initiatives to establish alternative sensor payloads  (Roemmich et al.
Acknowledgments. The data from the  Argo Australia ,  China Argo , and  Japan Argo  floats used here were collected and are made freely available by the  International Argo program  and the national programs that contribute to it (Argo 2000). The Argo Program is part of the Global Ocean Observing System. Author Dr. G. Maze was supported by the  EARISE  project, a  European Union 's  Horizon 2020 research and innovation program  under Grant Agreement 824131, Call INFRADEV-03-2018-2019: Individual support to ESFRI and other world-class research infrastructures. We acknowledge  Susan Wijffels , who provided advice on reference climatologies, coordinated access to the data from  Argo Australia  float  5904925 , and provided ship CTD data to evaluate the initial accuracy of the float. Toshio Suga  and  Shigeki Hosoda  provided ship CTD data for assessing the initial accuracy of  Japan Argo  floats  2903005  and  2903327.
We thank  Zenghong Liu  for coordinating access to ship CTD data and continued discussion regarding RBRargo CTD accuracy and stability. We thank  IFREMER  for providing us access to ADMT-CTD and ADMT-Argo reference datasets. We thank  Annie P. S. Wong  for critical comments and recommendations in data analysis. We thank two anonymous reviewers whose suggestions were very constructive and greatly improved this paper. Last, we thank the  Argo Steering Team  for encouraging Argo member nations to take part in the  RBR CTD Argo Global Pilot Project.
In this paper, we consider a job-shop scheduling problem with mixed blocking constraints. Contrary to most previous studies, where no blocking or only one type of blocking constraint was used among successive operations, we assume that, generally, we may address several different blocking constraints in the same scheduling problem depending on the intermediate storage among machines, the characteristics of the machines, the technical constraints, and even the jobs. Our objective was to schedule a set of jobs to minimize the makespan. Thus, we propose, for the first time, a mathematical model of the job-shop problem taking into account the general case of mixed blocking constraints, and the results were obtained using Mosel Xpress software. Then, after explaining why and how groups of jobs have to be processed, a blocking constraint conflict-free warranted evaluation function is proposed and tested with the particle swarm optimization and genetic algorithm methods.
Results Obtained on Mixed Blocking Constrained Jobshop Problems To facilitate new heuristic developments, we decided to adapt some instances of Lawrence  [39]. For each sized problem, we arbitrarily generated four blocking matrices, which constitute different situations of mixed blocking constraints. The four matrices used for the 5x5 problem are given in Figure  3. The blocking constraints were duplicated for higher range problems. The results, which are presented in Table  1 , were obtained using the above presented mathematical model, which was computed with Mosel-Xpress software on a 3 GHz/1Go PC. The mathematical model's computation time strongly increases with respect to the number of jobs that are treated and the number of machines. As a consequence, to be able to treat it within a reasonable computational time, for each sized problem, in the next section, we propose an evaluation function that is able to adapt any classic meta-heuristic to a JS problem with mixed blocking constraints.
The results, which are presented in Table  1 , were obtained using the above presented mathematical model, which was computed with Mosel-Xpress software on a 3 GHz/1Go PC.                 = 0 1 2 3 2 2 1 1 3 0 2 0 3 2 1 0 0 3 2 1 1 A                 = 2 1 3 0 0 0 0 1 0 1 2 3 0 1 0 2 3 2 1 0 2 A                 = 1 2 0 3 0 1 3 0 2 0 0 1 0 0 0 0 0 2 1 3 3 A                 = 0 0 0 0 0 2 3 1 0 3 1 2 0 1 2 0 0 1 0 1 4 A The mathematical model's computation time strongly increases with respect to the number of jobs that are treated and the number of machines. As a consequence, to be able to treat it within a reasonable computational time, for each sized problem, in the next section, we propose an evaluation function that is able to adapt any classic meta-heuristic to a JS problem with mixed blocking constraints.
Pigment and bacteria concentration in seawater To characterize the biological conditions at CVAO, a variety of pigments including chlorophyll a (chl a) were measured in the samples of Cape Verde bulk water (data in Table  S4  and illustrated in Sect. 5. 4. 1). Chl a is the most prominently used tracer for biomass in seawater; however, information on phytoplankton composition can only be determined by also determining marker pigments. Therefore, each time when a water sample was taken, several liters of bulk water were also collected for pigment analysis (more details in the Supplement). Chl a concentrations varied between 0. 11 and 0. 6 µg L -1 and are more thoroughly discussed together with the pigment composition in Sect. 5. 4. 1. Moreover, as organisms other than phytoplankton can contribute to the OM pool, bacterial abundance was analyzed in the SML and bulk water samples, and these data are reported in Sect.
In the vicinity of the MarParCloud sampling site the glider observed a slight enhancement in fluorescence when compared to open-ocean waters. This is in agreement with the measured pigment concentration. The overall pattern of slightly enhanced biological activity was also confirmed by the MODIS Terra satellite fluorescence measurements (Fig. 7b ). However, both in situ glider and sample data as well as remote sensing data did not show any particularly strong coastal bloom events and thus indicate that the MarParCloud sampling site represented the open-ocean regime well during the sampling period. 5 Measurements and selected results.
g. ,  Read et al. , 2008). Finally, a series of continuous measurements of nitrous acid (HONO) was conducted, aiming to evaluate the possible contribution of marine surfaces to the production of HONO. The measurements indicated that HONO concentrations exhibited diurnal variations peaking at noontime. The concentrations during daytime (08:00 to 17:00 local time) and nighttime (17:30 to 07:00 local time) periods were around 20 and 5 ppt on average, respectively. The fact that the observed data showed higher values during the day compared to the nighttime was quite surprising since HONO is expected to be photolyzed during the daytime. If confirmed, the measurements conducted here may indicate that there is an important HONO source in the area of interest. Altogether, for the trace gases, a variety of conditions were observed in this 3-week period with an influence from ocean-atmosphere exchange and also potential impacts of long-range transport.
To this end, the meteorological model data by the Consortium for Small-scale Modelling-Multiscale Chemistry Aerosol Transport Model (COSMO)  (Baldauf et al. , 2011)     rent weather forecast model of the German Weather Service. The numerical calculation of the weather forecast is achieved by using information on the underlying orography and land use, as well as boundary data for all meteorological fields. The needed boundary and initial fields will be derived from reanalysis data and/or input parameters from coarse-resolved weather model data. The first simulations show that clouds frequently occurred at heights of 700 to 800 m (Fig. 23 ), in strong agreement with the observations. This demonstrates that clouds at Mt. Verde can form solely due to the local meteorological conditions and not necessarily due to orographic effects.
Acknowledgements. We acknowledge the CVAO site manager,  Luis Neves , and the  Atmospheric Measurement Facility  at the  National Centre for Atmospheric Science (AMF, NCAS ). The authors acknowledge Thomas Conrath,  Tobias Spranger  and  Pit Strehl  for their support during fieldwork. Kerstin Lerche  from the  Helmholtz-Zentrum für Umweltforschung GmbH -UFZ (Magdeburg)  is acknowledged for the pigment measurements. The authors thank  Susanne Fuchs ,  Anett Dietze ,  Sontje Krupka ,  René Rabe  and  Anke Rödger  for providing additional data and filter samples, as well as  Elisa Berdalet  for the discussion about the pigment concentrations. Kay Weinhold ,  Thomas Müller  and  Alfred Wiedensohler  are acknowledged for their data support. We thank  Johannes Lampel  for providing the photograph in Fig.
1. In addition, the use of SEVIRI data and NWCSAF processing software, distributed by  EUMETSAT  and obtained from the  TROPOS  satellite archive, is acknowledged. María Eugenia Monge is a research staff member from  CONICET  ( Consejo Nacional de Investigaciones Científicas y Técnicas, Argentina ). Ryan Pereira  thanks  Juliane Bischoff  and  Sara Trojahn  for technical support. We also thank the  Monaco Explorations program  as well as captain and crew of  MV YERSIN  for supporting the wave glider deployment. Finally, the authors thank the anonymous reviewers for their valuable comments and suggestions. Financial support. This work was funded by the  Leibniz Association SAW  under the project " Marine biological production , organic aerosol particles and marine clouds: a  Process Chain (MarPar-Cloud) " ( SAW-2016-TROPOS-2 ) and within the  Research and Innovation Staff Exchange EU  project  MARSU  (grant no.
Data availability. The data are available through the World Data Centre PANGAEA under the following links: https://doi. pangaea. de/10. 1594/PANGAEA. 910693 (van Pinxteren, 2020a; Table  2 ) and https://doi. pangaea. de/10. 1594/PANGAEA. 910692 (van Pinxteren, 2020b; Table  1 ). Supplement. The supplement related to this article is available online at: https://doi. org/10. 5194/acp-20-6921-2020-supplement.
poynter. org/ifcn-fact-checkers-code-of-principles/). 8 https://github. com/hypothesis/client/ to the W3C Web Annotation Recommendation, and JaCaMo, a platform for the development of MAS 9. The rest of this paper is structured as follows. Sec. 2 discusses background and related work on tackling online disinformation, social machines, and MAS. Sec. 3 presents our approach, including detailed reasoning for its encompassing features. We present the current state of our prototypical implementation in Sec. 4 and discuss its limitations.
In distributed artificial intelligence, MAS are systems conceptualized in terms of agents situated and interacting in a shared environment, where an autonomous agent is commonly defined as "a computer system, situated in some environment, that is capable of flexible autonomous action in order to meet its design objectives"  [11, 23]. 17 Drawing upon MAS research, in  [13]  the authors propose to design social machines for crowd-sourcing software development by complementing the social compute unit -a model for ad-hoc human worker teams -with interaction protocols expressed in lightweight social calculus. Interaction protocols are also central to  [5] : the authors define social protocols as behavioral standards based on the expectations of (human and non-human) participants towards interactions, which are then reflected in a computational model and can be enacted in a decentralized manner.
To this end, we use the cloud-based service provided by Hypothesis. For the display and aggregation of annotations, the browser plugin retrieves those annotations from the back end, sorts and aggregates them on the front end. The intermediary component sits between the front and back end, managing and keeping track of the organization (see Sec. 3. 2) to help coordinate the fact-checking of articles. We designed the intermediary component using JaCaMo  [4]  a MAS platform that provides also the reference implementation for MOISE -to define and deploy multi-agent organizations. In our MOISE organization, people are proxied by simple software agents: agents enact roles in the organization on behalf of humans in order to signal the achievement of goals, and they forward to humans all their permissions and obligations within the organization (e.
Also, a weak relationship was present between genotyped rams in training and validation groups. Since 2014, the Latxa breeding program has collected more phenotypic and pedigree data and has genotyped all the new males used in the last years in AI. Also, new developments in evaluation, such as single-step GBLUP (ssGBLUP), which enables the use of phenotypes of both animals with and without genotypes, yield better predictions  (Legarra et al. , 2009; Christensen and Lund, 2010). New methods in validation of results (LR method;  Legarra and Reverter, 2018)  may yield more objective measures of predictive ability. Furthermore, the metafounders (MF) theory  (Legarra et al. , 2015)  provides a more coherent framework for genomic evaluation theory  (Garcia-Baccino et al. , 2017; Meyer et al. , 2018; Bradford et al.
Phenotypic and Pedigree Data All data came from the Latxa Breeders' Associations' Confederation (CONFELAC). The full data set included in this study comprised 639,517 lactations and 263,308 animals in the LCNEUS pedigree and 392,109 lactations and 150,185 animals in the LCR pedigree. The evaluated trait was 120-d standardized milk yield whose heritability is 0. 18 and 0. 22 for LCNEUS and LCR, respectively. More details about phenotypic and pedigree data are shown in Table  1. Because of the frequent use of natural mating with several rams, the breeding program only accepts filiations for AI rams. Also, several dams are unknown, mainly in flocks entering the breeding scheme. As a result, based on the average of the full data set, 31% of the ewes with milk records have unknown sire and dam, even though since 2000 this percentage has decreased to 21%.
Genotypic Data Using stored (for old) and recent DNA samples, AI rams were genotyped with the OvineSNP50 BeadChip (Illumina Inc. , San Diego, CA). As quality control, animals with call rate <0. 90 and parent-progeny Mendelian conflicts (<5%) were eliminated. For SNP, markers Regarding the previous study  (Legarra et al. , 2014) , this work includes 178 new genotyped individuals (80 LCNEUS and 98 LCR) corresponding to the rams entering the AI center from 2010 to 2014. Genotyping was irregular during the first years, but from 2011 all the rams entering the AI center have been genotyped, which enables a more balanced and stronger data structure. The distribution of genotyped rams by year of birth is shown in Figure  1.
Goodness of Prediction The goodness of prediction of pedigree and genomic evaluations was analyzed by cross-validation using the LR method  (Legarra and Reverter, 2018). This method measures biases and accuracies from global changes in (G)EBV of candidates to selection from a "partial" (1984-2014) to a "whole" (1984-2017) data set. We chose a set of validation individuals, considering genotyped AI rams born into the last 3 cohorts of the partial data set (between 2012 and 2014). The details of rams' distribution across validation and training group are described in Table  2. These animals were not progeny tested in the partial data set and have at least 10 daughters with lactations in the whole data set. First, GEBV were estimated in whole and partial data sets using ssGBLUP. Second, EBV were estimated in whole and partial data sets using BLUP.
ACKNOWLEDGMENTS The authors thank the  Confederación de Asociaciones de Criadores de Ovino de Razas Latxa y Carranzana (CONFELAC, Vitoria-Gasteiz, Spain)  for providing the milk recording and pedigree data and the  Department of Economic Development and Infrastructure of the Basque Government  for the grant for young researchers and technologists. This research has also be financed by project  ARDI (Ardi Research Development and Investigation ;  EFA208/16 ) funded by  INTERREG POCTEFA (Programa INTERREG V-A España-Francia-Andorra ; https: / / www. poctefa. eu/ ) with  European Union Fonds européen de développement régional (FEDER)  funds and by  SMARTER (Small Ruminants Breeding for Efficiency And Resilience)  project (grant agreement no. 772787 ) funded by  European Union   Horizon 2020 Research and Innovation program.
The defective pixel detection method is based on the evaluation and analysis of local dispersion parameters of the pixel blocks, while the concealment method is based on local median filters. This control loop process takes an image and a target quality score as inputs and generates the corrected image when its quality score is above the target quality or when the quality decreases after a correction. This control loop has been implemented on FPGA demonstrating the feasibility of integrating the proposed solution in an image sensor. FPGA results are very encouraging, with more than 93% correlation for image quality assessment and a significant enhancement of the performance of image sensors in the control loop. Work in progress is oriented towards extracting information from the control loop to feed a dataset that will be used to evaluate wear features and device reliability.
However, our experiments do not prove that TREX1 is the main driver of DNA damage in this context nor that DNA damage associated with nuclear deformation plays a role in the human disease progression. TREX1 has been described to promote pro-or anti-tumoral effects depending on different cellular and tumoral contexts (  [64] [65] [66]  ). To get further insight into this question, we analyzed the association of TREX1 expression level in breast cancer with overall survival using public datasets. This analysis revealed that high level of TREX1 expression is significantly associated with reduced probability of survival (Fig  S7 ). Notably, TREX1 is also implicated in modulating cGAS-dependent pro-tumorigenic inflammatory response (  [40] [41] [42] 44  ). For exemple, TREX1 expression is reduced in fibroblasts undergoing replicative or oncogene-induced senescence, resulting in accumulation of DNA in cytosol and cGAS activation ( 67 ).
Staining was revealed using Novolink Polymer Detection Systems (Novocastra) and SuperSensitive Link-Label IHC Detection System Alkaline Phosphatase (Biogenex). DAB (3,3'diaminobenzidine) and Vulcan Fast Red were used as substrate chromogens. The slides were counterstained with Harris hematoxylin (Novocastra) to reveal nuclei. All the sections were analyzed under a Zeiss AXIO Scope. A1 microscope (Zeiss, Germany) and microphotographs were collected using a Zeiss Axiocam 503 Color digital camera using the Zen2 imaging software. Double immunohistochemistry was performed on 7 breast cancer tissues, but taking into account also the double IF RAB5A/gH2aX, the number of cases increases to 15.
Data represents 3 independent experiments where cells invading from 10 random gates (at 20x magnification) were analyzed per condition per experiment. Bar, 60 µm. P values were calculated by unpaired Student's t-test, ***P < 0. 0001. experiments where 25 cells per condition per experiment were analyzed. (E) DCIS cells were transiently depleted for TREX1 or cGAS using siRNA and 48 h later cells were treated for 12 h with doxorubicin (Doxo, 80 nM) or DMSO (vehicle). Following the treatment period, cells were harvested and embedded in 3D type I collagen for 12 h to assess their collagen degradation activity by immunostaining with an antibody that specifically recognizes the collagenase-cleaved ¾ fragment of collagen I. Graph: and whisker plot showing the median value and 10-90 percentiles of the collagen degradation area.
Graph: box and whisker plot showing the median value and 10-90 percentiles of nuclear projected area. Data represents 3 independent experiments where 70 cells per condition per experiment were analyzed. (C) DCIS cells stably expressing life actin-EGFP were confined for 2 h at the indicated heights. Following the confinement period, cells were harvested and embedded in 3D type I collagen and imaged for 15 h. Bar, 20 µm. (D) Scatter dot plots of different measured parameters while cells where embedded into 3D type I collagen (lines are median). Data represents 2 independent experiments where 25 cells per condition per experiment were analyzed. (E) DCIS cells were transiently depleted for TREX1 or cGAS using siRNA and 48 h later cells were treated for 12 h with doxorubicin (Doxo, 80 nM) or DMSO (vehicle).
Acknowledgements: We thank  Titia de Lange  ( Rockefeller University, New York, USA ) and  John Maciejowski  ( Memorial Sloan Kettering Cancer Center, New York, USA ) for providing the guideRNA to generate the TREX1 KO CRISPR cell lines. We also thank  John Maciejowski  and  Alexis Lomakin  for suggestions during the writing of this manuscript. We thank the flow cytometry and cell sorting facility and the animal facility at the  Institut Curie (Paris, France)  for provision of equipment and technical assistance. We thank  Nicolas Carpi  ( Institut Curie, Paris, France ) for lab management, plasmid amplifications and computer technical support. We thank  Juan-Manuel Garcia Arcos  ( Institut Curie, Paris, France ) for kindly drawing the model of this study (Figure  S6 ). This work has also received the support of  Institut Pierre-Gilles de Gennes-IPGG  ( Equipement d'Excellence, "Investissements d'avenir", program   ANR-10-EQPX-34 ).