dataesr/scientific-paragraphs-categorization huggingface dataset:
Conclusion and Future Work In this paper, we have presented a service prototype to define data subscriptions to Euro-Argo data, connected to invoking a processing pipeline optimised with Dynamic Real Time Infrastructure Planner (DRIP) solution. We demonstrated how DRIP could be used to automatically select and provision infrastructure resources, deploy services, and optimise the runtime quality for the EUDAT data subscription service based on a study case involving the Euro-Argo research infrastructure. The DRIP microservice suite optimises the runtime quality of service provided by a data service deployed dynamically on a virtualised e-infrastructure, with a particular focus on time-critical constraints such as deadlines for delivering data to a distributed set of targets. We demonstrated how to select an optimal strategy for partitioning the input tasks into workers using a modicum of expert knowledge concerning the specifics of an application.
The results clearly show the value of integrated systems such as DRIP for dynamic optimisation of data services in research support environments, and how with further investigation and development they might be used for a number of similar applications cases involving distributed services and large, dynamic datasets. Furthermore, we showed subscription matching in the presence of existing data life cycle stages through which investigators can free up time and be notified of significant events in subscribed data. The demonstrated Data subscription service prototype is part of the EUDAT innovation portfolio. The starting point for developing the subscription service has been to provide a generic component that can be connected to different community frontends, and that can utilise different e-infrastructure platforms for automated processing.
This paper presents the successful Euro-Argo pilot case within ENVRIplus project that demonstrates the interaction of several service components from several providers: the Euro-Argo data portal, EUDAT B2SAFE data storage, the EUDAT data subscription service, the DRIP solution, and EGI FedCloud. The EUDAT Collaborative Data Infrastructure has identified the potential in the subscription model and considers it as a possible new addition to the data management services, depending on the interest of user communities and availability of development resources. Regarding the DRIP solution, it is necessary to acknowledge the difficulty still inherent in building generic solutions for fully automated optimisation of infrastructure for arbitrary data services. Some degree of application-specific customisation is still necessary when applying infrastructure-level optimisation.
We remove the first transit of Sector 10 from our dataset -which was contaminated by excess scattered light -leaving 15 transits for our analysis. We show the detrended MASCARA-4 b TESS light curve here. The orbital inclination (i) is the planet's orbital tilt toward/away the viewer, and is defined by cos(i) = bR /r, where b is the impact parameter and r is the planet's distance from the star. The star's color gradient represents its gravity-darkened surface. The gravity-darkening technique constrains the true alignment of a planet, but cannot distinguish between a prograde or retrograde orbit. Dorval et al. (2019)  previously determined MASCARA-4 b to be in a retrograde configuration; we therefore assume a retrograde orbit in our model, resulting in a single value for the planet's true alignment angle.
2009 ). To reduce motion artifacts, participants were instructed to keep their head motion to a minimum, additionally an independent component analysis with a coefficient of spatial uniformity of 0. 5 was applied to remove motion artifacts. The steps of noise and motion artifacts removal are critical to avoid false discovery in brain network and connectivity analysis  (Santosa et al. 2017). The parameters in data processing are based on prior research  (Sato, Hokari & Wade 2011; Naseer & Hong 2015). The filtering process was conducted using Shimadzu fNIRS software, and the following analysis was conducted using Python (NetworkX package was used for the network analysis). Only oxygenated hemoglobin (oxy-Hb) in the filtered data is reported in the results because oxy-Hb generally has a higher amplitude and is more sensitive to cognitive activities than deoxygenated hemoglobin (deoxy-Hb)  (Chu et al.
In the case of morphological analysis, students decomposed the problem based on functions, so the association processing could seem more manageable and require less activation in the mPFC than brainstorming. The fewest cognitive resources were required when using TRIZ. Similar to morphological analysis, this logical process relies on decomposition and analysis. In addition to the changes in cognitive load and patterns of activation in subregions, the brain network analysis in our dataset revealed potential connections between the structuredness of each concept generation technique and the central regions for cognitive coordination. The right DLPFC is the most central region needed for communication across brain regions during brainstorming. The right and left DLPFC are the two most central regions for communication across the brain during morphological analysis, and the right and left DLPFC and the medial PFC are the most central for communication across brain regions during TRIZ.
When class I models are unstable it is due to excessive positive feedback at the highest level of the system (i. e. , for longest-length feedback cycles), which typically causes runaway growth or decay in a particular variable or subsystem of variables, preventing the system's return to a former state of equilibrium. Class II models become unstable when there is excessive feedback at higher levels in the system (or insufficient lower-level feedback), which causes the system to oscillate uncontrollably. Further theoretical background and details about these stability metrics can be found in Dambacher et al. [69]. In order to calculate the scope for stability for our four alternative model structures (S1-S4, Fig. 1 ), we used a program developed by Dambacher et al. [37]  (esapubs. org/archive/ecol/E083/022) for qualitative analyses of the community matrix and calculations of the stability matrices (wFn, wDn).
We used this approach and the program developed by Dambacher et al. [37] (esapubs. org/archive/ecol/E083/022) in Maple to analyze the sign response and the associated level of probability of sign determinacy for 10 different press perturbation scenarios. The individual perturbations are from Raoux et al. [5]. The different scenarios had five main perturbations (Fig. 2 ): Fishing restrictions (Perturbation 1, P1): The consequences of safety measures around the OWF on the social system, in terms of reduced fishing opportunities for the "trawl" and "dredge fishery". Reef effect (P2): Representing the consequence of the OWF on the ecosystem through the "reef effect", i. e. the hard substrate of the wind farm is expected to increase habitats and shelters for benthic ("benthos") organisms thus supporting their growth in terms of both abundance and biomass.
Acknowledgments We would like to thank  Rhoda Fofack ,  Jean-Claude Dauvin , and Camille Maz� e for important input and discussions when constructing the model, and  Boris Leroy  for giving useful comments on the manuscript. The work was funded by the  TROPHIK  project ( ANR/FEM EMR-ITE 2015 ) and supported by  France Energies Marines  and the  French State , managed by the  National Research Agency  under the " Investissements d'avenir" program  ( ANR-10-IEED-0006-12 ). We also thank two anonymous reviewers for their comments improving this paper.
Results and Discussion Confocal laser-scanning SMLM measurements were carried out on a custom-built timeresolved confocal microscope equipped with a fast laser scanner, see Fig. 1a  (for more details see SI). For dSTORM measurements, a region of interest of 10 µm × 10 µm was scanned with an image scan rate of ~27 Hz. Excitation was done with a pulsed laser at 640 nm wavelength, a repetition rate of 40 MHz, and a pulse width of ~50 ps. Single fluorescence photons were detected with a single-photon avalanche diode (SPAD), and photon detection events were correlated in time to excitation pulses (Time-Correlated Single-Photon Counting or TCSPC) with high-speed electronics. For data analysis, recorded photons were converted into a stack of intensity images, always combining 10 subsequent scans into one image to minimise distortions by those labels that are switching while being scanned.
The stack of intensity images is then used to localise single molecules and to identify switching events. These localisations were subsequently used to reconstruct a super-resolved image (similar to conventional wide-field dSTORM). Taking full advantage of our TCSPC detection, fluorescence lifetimes of each localised molecule were determined by pooling all photons associated with it and fitting the resulting lifetime histogram with a mono-exponential decay function. To increase the number of photons per localisation, identical localisations in subsequent frames were merged. Using this lifetime information, super-resolved fluorescence lifetime images were reconstructed. To make the data analysis for confocal laser-scanning FL-SMLM widely available, the complete data processing pipeline was integrated into a Matlab-based GUI app, see Fig.
On our wide-field microscope, we could not detect single switching events when focusing at the centre of the beads. In contrast, it was possible to localise switching molecules (Fig. 3a ) with the CLSM, to determine their fluorescence lifetimes, and to reconstruct a fluorescence-lifetime dSTORM image (Fig. 3b ). The image shows two beads that are labelled with two different dyes, namely Alexa 647 having an average fluorescent lifetime of 1. 4 ns and ATTO 655 with 2. 4 ns. Details on data processing and the resulting lifetime histogram can be found in the methods section (see Fig. S5 ). To enable fluorescence-lifetime multiplexing dSTORM, it is crucial to use buffer conditions which are compatible with all fluorophores. This includes control of sufficient on-and offswitching rates while guaranteeing high dye brightness.
The output signal of the photon detector was recorded by a TCSPC system (HydraHarp 400, PicoQuant) which was synchronised with the triggering signal from the excitation laser. Measurements were acquired with the software (SymPho-Time 64, PicoQuant), which controlled both the TCSPC system and the scanner system. Typically, sample scan with a virtual pixel size of 100 nm, and a dwell time of 2. 5 µs/pixel and a TCSPC time resolution of 16 ps were chosen. To evaluate the performance of the laser scanner, TetraSpeck microspheres were measured with the same parameters as used in the dSTORM measurements (10×10 µm region of interest, 100 nm pixel size and 2. 5 µs dwell time). For the evaluation, 10 scans were binned to one frame as it was done for the dSTORM measurement. For the analysis TrackNTrace was used to independently localise the spheres in each frame.
The following acquisition settings were used: area 20×20 µm, virtual pixel size 100 nm, dwell time 2. 5 µs/pixel and a TCSPC time resolution 16 ps. 10 scans were combined together as for the dSTORM measurements and analysed by TrackNTraceLT software. The Fourier ring correlation (FRC) maps were obtained for reconstructed superresolved images (see Figure  S3 ) and the average resolutions were calculated 45 nm and 41 nm for confocal DNA-PAINT and conventional DNA-PAINT, respectively. The following average localization precision values were calculated 18 nm and 26 nm, correspondingly. The measured lifetimes values were as following: non-conjugated ATTO 655 dye in solution 1. 83±0. 01 ns, DNA-dye construct in solution 2. 69 ± 0. 01 ns and DNA-dye construct attached to its complementary docking strand inside the nucleus 3.
TrackNTrace Lifetime Edition In order to facilitate the data analysis of scanning confocal super-resolution imaging, we developed an extended version of the Matlab based framework TrackNTrace. (22)  To allow the processing of FLIM data the image import was generalised to use file type specific plugins. The existing support for TIFF files was moved to a dedicated import plugin and a plugin in for PicoQuant Time Tagged File Format (PTU) was implemented. Since the PTU format stores a stream of photons with relative time information and position markers it is not possible to read specific photons. To allow random access to photon data based on the frame and position they were detected at, an index of all photons including their position, frame, micro time (TCSPC bin) and channel was created and stored as MAT-file, which is hdf5-based and allows random access.
Acknowledgments The authors thank  Dr. Shama Sograte-Idrissi  for COS-7 cells preparation for DNA-PAINT experiments. We are grateful to  Dr. Anna Chizhik  for fruitful discussions. J. E. and O. N. acknowledge financial support by the  Deutsche Forschungsgemeinschaft (DFG)  via project " Super-resolution microscopy through single molecule localization at cryogenic temperature " ( EN297/15-1 ). J. C. T. is grateful to the  DFG  for financial support via project  A05  of the SFB 937, and to the  International Max Planck Research School for Physics of Biological and Complex Systems (IMPRS PBCS)  for financial support. N. O. is grateful to the  Deutsche Forschungsgemeinschaft (DFG)  for financial support via project  A10  of the SFB 803.
Social trust is linked to a host of positive societal outcomes, including improved economic performance, lower crime rates and more inclusive institutions. Yet, the origins of trust remain elusive, partly because social trust is difficult to document in time. Building on recent advances in social cognition, we design an algorithm to automatically generate trustworthiness evaluations for the facial action units (smile, eye brows, etc. ) of European portraits in large historical databases. Our results show that trustworthiness in portraits increased over the period 1500-2000 paralleling the decline of interpersonal violence and the rise of democratic values observed in Western Europe. Further analyses suggest that this rise of trustworthiness displays is associated with increased living standards.
The algorithm generates automatic human-like trustworthiness ratings on portraits based on the muscle contractions (facial action units) detected in facial displays using the open software OpenFace  23. This algorithm was trained on avatars controlled for trustworthiness and optimized using a random forest procedure (see Supplementary Methods for more details). To assess the generalizability of our model, we then tested its validity on four databases of natural faces rated by real participants. We first demonstrated that the algorithm produced trustworthiness ratings that were aligned with those produced by human participants in all four controlled databases. Another validation method would have been to also measure the correlation between the estimated trustworthiness of the historical portraits calculated by our algorithm and the evaluations of the actual participants on these paintings.
Third, we checked that the output of the algorithm was robust to variations in head orientation  21, 24  (see Supplementary Methods for the results). We then replicated all these findings outside well-controlled databases by analyzing all the images (photographs and paintings) obtained from a Google image search for 'women portraits' vs 'male portraits' (N = 633; trustworthiness: t(632) = 7. 89, p < 0. 001; dominance: t(632) = -11. 79, p < 0. 001). This validation method provides evidence of the ability of our algorithm to produce human-like face evaluations on a large range of images (i. e. , controlled photographs, natural photographs and paintings).
Results Trustworthiness displays in portraits increased throughout history. To assess the evolution of trustworthiness displays in history, we first analyzed the paintings of the National Portrait Gallery (Fig. 1a ), the largest online database of historical portraits (analyzed N = 1962 English portraits from 1505 to 2016). Because perceived trustworthiness is correlated with perceived dominance  24  , all the analyses were controlled for dominance. In line with historical work, we found a significant increase of trustworthiness displays with time (b = 0. 14 ± 0. 02, z = 7. 49, p < 0. 001; Table  1 ; time coded such as one unit corresponds to 100 years, ±corresponds to standard errors to the mean; Figs. 1b  and 2a ), suggesting that the value of interpersonal trust increased from the 16 th to the 20 th century.
We then replicated our findings on the Web Gallery of Art, an important fine art repository (N = 4106 portraits) spanning 19 Western European countries seven centuries (1360-1918) and found a significant increase in trustworthiness displays with time (b = 0. 07 ± 0. 01, z = 5. 33, p < 0. 001; Table  1 ; Fig. 2b ). Overall, these results are consistent with more qualitative works documenting a so-called 'Smile Revolution'  25  and a rise of prosocial displays in paintings and in novels  26. It is worth noting, however, that the historical increase in trustworthiness observed in our datasets parallels the rise of liberal values such as religious tolerance, political freedom and democracy  2, 27, 28. Whether such increased trustworthiness in portraits parallels an actual shift in social trust remains an open question.
To assess the validity of this assumption, we applied our algorithm to selfies posted on Instagram in six cities around the world in 2013 (Bangkok, Berlin, London, Moscow, New York and Sao Paulo; SelfieCity database, pictured analyzed N = 2277  29  ), we found that people located in places where interpersonal trust and cooperation are higher (as assessed in the European and World Value Surveys  30, 31  ) displayed higher levels of trustworthiness in their selfies (cooperation level: b = 0. 13 ± 0. 03, z = 3. 67, p < 0. 001; trust level: b = 0. 81 ± 0. 23, z = 3. 50, p < 0. 001; ±corresponds to standard errors to the mean; Supplementary Figure  6 ). Together, this suggests that the display of trustworthiness in portraits can indeed be used as a reliable proxy of the level of social trust in individuals' environment  32, 33.
This is particularly relevant in light of the fact that the Middle Ages and the early Modern Period were periods of prolonged economic growth for Europe in general and England in particular  40, 41. We thus tested whether higher GDP per capita was associated with the rise of trustworthiness in portraits. Our analysis of the National Portraits Gallery database revealed an association between higher levels of affluence and higher levels of trustworthiness displays between the 16 th and the 21 st centuries (b = 0. 03 ± 0. 01, z = 7. 13, p < 0. 001; Table  1 ; Fig. 2c ), even after adjusting for a monotonous effect of time (b = 0. 02 ± 0. 01, z = 3. 16, p = 0. 002; Table  1 ). Crucially, GDP per capita accounted for the evolution of trustworthiness displays better than a monotonous effect of time (Bayes Factor: 3.
38), which suggests that the observed evolution of trustworthiness displays cannot be reduced to a simple cultural accumulation that would have led to the development of painting techniques making sitters look more trustworthy. We then sought to replicate this result in the Web Gallery of Art database and also found a significant positive association between GDP per capita and trustworthiness displays (b = 0. 09 ± 0. 03, z = 3. 16, p = 0. 002; Table  1 ; Fig. 2d ). This association was robust to adjusting for a monotonous increase of trust displays over time (b = 0. 07 ± 0. 04, z = 1. 98, p = 0. 048; Table  1 ). Again, the model including GDP per capita provided a better account of the variations of trust displays than time alone (Bayes Factor: 130. 16). Institutional change is another possible predictor of increased trust.
75). Moreover, the positive association between more democratic institutions and higher trustworthiness displays was not replicated in the Web Gallery of Art sample (b = -0. 01 ± 0. 01 z = -1. 96, p = 0. 051; with time as a covariate: b = -0. 01 ± 0. 01 z = -0. 96, p > 0. 250; Bayes Factor of the GDP per capita model compared to the democratic institutions model: 6. 16). Changes in affluence precede changes in trustworthiness displays in portraits. Demonstrating that the association between GDP and the rise of trustworthiness is causal would of course require additional data. Based on our dataset however, we were able to investigate the dynamics of these historical changes by running time-lag analyses on trustworthiness displays and GDP per capita. We found that changes in GDP per capita predicted future changes in trustworthiness displays in the National Portraits Gallery two decades later (F(40,1) = 12.
38, p = 0. 001) while changes in political institutions did not (F(15,1) = 0. 11, p > 0. 250). The effect of GDP per capita on trustworthiness displays was generalizable to the other European countries (Web Gallery of Art sample, effect of GDP 20 years before on trustworthiness displays: X(1) = 6. 42, p = 0. 011; Institutions 20 years before: X(1) = 0. 81, p > 0. 250). Importantly, changes in trustworthiness displays did not predict future changes in GDP per capita either in the National Portraits Gallery sample (F(41,1) = 0. 76, p > 0. 250) or in the Web Gallery of Art dataset (X(1) = 2. 02, p = 0. 155), which suggests that changes in GDP per capita may have preceded changes in trustworthiness displays in this dataset. This conclusion is consistent with other works emphasizing the importance of economic growth and psychological changes in history  [44] [45] [46].
02, p > 0. 250; Dominance: X 2 (2) = 0. 01, p > 0. 250). To determine which type of algorithm (linear model, random forest model from the RandomForest R package 51 -Breiman's random forest algorithm  52  -or support vector model either linear or radial from the kernlab R package  53  ) would provide the most accurate evaluations, we ran a repeated 20-folds cross-validation (five repetitions) on the training test of each of these models separately for dominance and trustworthiness using caret R package  54. Each model's hyperparameters were optimized using a random search. The hyperparameters optimized for each model are presented in Supplementary Table  1. This analysis revealed significantly better performance for the random forest model than for the linear model and the linear SVM model in terms of mean absolute error, root square mean error and r-squared and was and better than, for the trustworthiness model, and similar to, for the dominance model, the radial SVM model (Supplementary Table  1 ).
For both trustworthiness and dominance, the optimal m try hyperparameter of the random forest models was found to be equal to 9, corresponding to setting the number of variables to consider at each tree to 9. We then tested the predictions of the random forest model with this optimal hyperparameter obtained by cross-validation on our trustworthiness and dominance test sets. This test revealed a high performance of the model (trustworthiness: r = 0. 85 ± 0. 5, t(75) = 14. 17, p < 0. 001; dominance: r = 0. 86 ± 0. 05, t(75) = 14. 72, p < 0. 001; Supplementary Fig. 2 ; all the reported statistical tests are two-sided). Validation of the algorithm for modeling trustworthiness and dominance evaluations. To assess the accuracy our trustworthiness and our dominance generator algorithm, we tested their predictions on four different face databases: the Karolinska database (N = 70 distinct faces)  55  , the Oslo Face database (N = 185 distinct faces)  56  , the Chicago database (N = 520 distinct faces)  57  and the FEI Face database (N = 520 distinct faces)  58.