dataesr/scientific-paragraphs-categorization huggingface dataset:
Initially, accurate localization with a one-Gaussian fitting hypothesis requires effective low-density (LD) imaging conditions (Fig. 1  a, left panel). However, such conditions intrinsically undergo frequent experimental exceptions. Indeed, despite low density per frame, high local densities are possible because of a biological distribution of the particles or the intrinsic stochastic nature of SMLM methods. Moreover, complex variations of the background are highly frequent in terms of both space and time. Altogether, this fully justifies the quantification of SMLM data with an accurate high-density (HD) mode of analysis. A scene with two particles recapitulates the general problem (Fig. 1  a, middle panel). Postulating LD conditions on these data generates not only a lack of precision but also a bias regarding their localizations.
Generation of synthetic data All synthetic data were generated with MATLAB (The MathWorks, Natick, MA). Images had to meet the conditions of a signal-dependent noise model, as defined in Eq. 4, to achieve a controlled scene. The PSF of unitary power was defined by three parameters, SNR, r 0 , and w n , where w n is the size of the window support. Unless otherwise specified, the synthetic data were generated based on the following values: r 0 ¼ 1. 25 pixels, m 0 ¼ 300, G ¼ 1, pixel size ¼ 107 nm, and SNR dB ¼ 25 decibels (dB).
UNLOC algorithm Description UNLOC provides a list of coordinates and associated parameters for each detected particle for a posteriori quantification and image reconstruction. The algorithm is based on the decision theory, which only requires the probability of false alarm (PFA) value to be set without the initialization of any parameters relative to the data (SNR, particle density, or background level). UNLOC uses an iterative up-and-down strategy  (38)  that alternates an overestimation of the number of particles to obtain a minimal fitting residue with a generalized likelihood ratio test (GLRT) to delete useless particles. UNLOC calculates the position errors based on the CRB for particles at high density per frame and without any prior knowledge of their intensity. The UNLOC principle is illustrated in Fig.
Sample preparation, data acquisition, and analysis Alexa Fluor 647-phalloidin labeled actin filaments in fixed COS-7 cells (ATCC CRL 1651; ATCC, Manassas, VA) were prepared as described in  (41). Quantitative experiments were performed on DNA-origami with GATTA-PAINT HiRes 80R and 20R nanorulers (GATTAquant, Hiltpoltsein, Germany). All acquisitions were made using total internal reflection fluorescence illumination on a custom-built microscope, as described in Fig. S15  and Table  S3 , with a 647 nm laser at 4 kW. cm À2 , an axial drift correction by the autofocus module, an EMCCD gain set at 100, and $57,000 frames at 36 ms/frame and $25,000 frames at 120 ms/frame for cell and nanorulers, respectively. Unless otherwise stated, data were analyzed with UNLOC in HD mode with a low spatial frequency variation of background, a reconnection process with one off-state lifetime frame, and an integrated Gaussian rendering process after drift correction by correlation.
None of the results were filtered except those from the nanoruler analyses, for which a localization precision filter was set to reject particles with s xy > 0. 05 pixels $ 7. 6 nm for comparison with the ThunderSTORM analyses. Moreover, ThunderSTORM was tuned to reach the best performances by using the ''multi-emitter fitting'' mode, an image filtering set by ''difference of Gaussian'' for synthetic data or ''wavelet'' for experimental data, and a ''local maximum method'' for the localization of molecules with the ''weighted least squares'' fitting method. The UNLOC and ThunderSTORM results were evaluated using GATTAnalysis v1. 5 software (GATTAquant). The Fourier ring correlation  (42)  was plotted to measure the local resolution in a heterogeneous image (Fig. S14 b ).
Limit of the HD hypothesis It was next necessary to determine the distance from which an enumeration is no longer achievable, namely, the HD/NR transition limit (Supporting Materials and Methods, Note S3). This limit, which is only quantifiable on ground truth data, emphasizes that counting particles from such highdensity data is flawed. The limit was determined by per-forming a likelihood ratio test that yields the best probability of detection (PD) calculated for a tolerable level of error set by a PFA  (45). For a simple NR scene (Fig. 1 b ), two particles separated by a short distance had an almost null PD at the usual PFA (10 À4 ). Similarly to LD cases, the use of an erroneous fitting model (i. e. , a one-Gaussian fit for a scene with two particles) introduced a bias. This detection error altered the localization of the nearest and more distant particles (Fig.
A diagram for SMLM accuracy estimation based on density and SNR Our theoretical study prompted us to link the density and SNR together in a diagram aimed to estimate the localization accuracy achievable on experimental data; the diagram was not intended to cover the experimental complexity of SMLM observations. The transitions distinguish the LD/ HD limit at which an HD algorithm is required and the HD/NR limit at which SMLM analyses become incorrect. The isocurves approximate the percentage of particles localized with a given precision. We chose to plot the isocurves for uniformly distributed particles of equal intensity as, although a more realistic SNR distribution could be considered, the results were found to be comparable (data not shown). Consequently, the diagram defines the precision limits for the simplest case for a large range of realistic D frame and SNR values.
Merged information in a single density-SNR space diagram The color-coded LD/HD/NR transitions were merged with the precision isocurves in a single diagram (Fig. 3 b ). This PFA for the HD/NR transition). Note that the NR subset, which increases with D frame , is only measurable on ground truth data. (b) A density-SNR space diagram is shown. The LD, HD, and NR regions are green, orange, and red color coded, respectively. The LD/HD limit is independent of the SNR. Then, in a green to orange transition, the bias i b becomes of the same order of magnitude as s RMS , the precision of localization. Accurate data analysis then requires an HD algorithm up to a density at which the particles are no longer resolvable (orange to red transition). This limit, which depends on the SNR, is set by the level of PFA stringency acceptable for a given experiment.
The analysis primarily requires an estimation of the background mean and variance to maintain the GLRT robustness. This is ensured by filtering and interpolating the background between the regions of the frame without signals. The list of particles is generated more specifically by iterative addition and deletion of particles after the background estimation step (Fig. 4 ; see also Fig. S9  b for more detail). In all cases, the final particle positions are deter-mined by a global fitting on the background-corrected raw data to delete supernumerary particles from the list. Compared to DAOSTORM  (25) , the UNLOC heuristic optimizes the particle enumeration by an upand-down strategy  (38)  executed conjointly with the optimization of particle position, intensity, and PSF size. Another UNLOC benefit is performing the particle localization on PSF-deconvoluted frames.
UNLOC performance on experimental data We chose to illustrate the UNLOC performance on DNA origami nanorulers, which do not require the control of photoinduced switching conditions. The HiRes 80R and HiRes 20R nanorulers are each made of two ATTO 655binding sites distant by 80 and 20 nm, respectively. The image stacks were analyzed by UNLOC and ThunderSTORM, for which reconnection, drift correction, and data filtering were optimized to be equivalent to those used for UNLOC. Their respective output results evaluated with the GATTAnalysis software illustrated the robustness of UNLOC: the more difficult the sample is, the better the results obtained by UNLOC compared to ThunderSTORM are (see the 20 nm DNA nanorulers) (Fig. 6 ). On cell samples, UNLOC efficiently challenged the variability of background, SNR, or density throughout the stack of experimental acquisitions, as illustrated by the image reconstruction of the actin network in Cos-7 cells (Fig.
S16 ). In terms of analytical speed, UNLOC analyzed in HD mode the density-SNR space diagram chart in $11 min (i. e. , $20 frames/s or $3200 particles/s). For the DNA nanorulers data ($25,000 frames recorded for each DNA origami), the analyses took $30 min as compared to $10 hr for ThunderSTORM. For the experimental biological data set of $57,000 frames of 512 Â 512 pixels with nonhomogeneous background and high variability of local density/frame (Fig. S16 ), UNLOC performed the task in HD mode within $200 min (i. e. , $5 frames/s or $2000 particles/s, for a total of $20 Â 10 6 detected particles).
a 10 nm 87% 12% 1% 34% 59% 7% 2% 91% 7% 87% 12% 1% 34% 62% 4% We have demonstrated that a bias on the precision of localization of one particle starts occurring when another particle is present at relatively long distance ($600 nm). Consequently, the detection of particles should tend to be exhaustive regardless of their intensity because their omission biases the localization accuracy of the others. We systematically validated these conclusions on synthetic data for which the ground truth was known. Altogether, our study led to the identification of LD/HD/NR subsets able to dictate the working range of any localization-based algorithms. Of importance, NR SMLM scenes arise quickly with increased local density/frame. For instance, two particles of 25 dB distant by $170 nm are indistinguishable.
Therefore, any NR scene, which is by definition undeterminable on experimental data, impedes the localization pre-cision, image representation, quantification, and even the benchmarking of algorithms performed with classical metrics. We have thus provided to our knowledge new tools able to help report accurate quantitative SMLM observations:     S1 ). Scale bars, 1 mm (insets, 100 nm). 3) two charts for any SMLM algorithms aiming specifically at providing a list of localizations of single molecules. The reconstructed images provide a visual evaluation of HD performance for which classical benchmarking is erroneous because of the presence of NR particles. In conclusion, analysis of synthetic data has confirmed the reliability of our theoretical study. By taking into account the characteristic of bias on the precision of localization, we designed UNLOC to be able to successfully reconstruct the experimental data obtained with DNA nanorulers or the actin-based meshwork in a fixed sample with reduced computation time.
ACKNOWLEDGMENTS We acknowledge  Marc Allain ,  Sophie Brasselet ,  Hai-Tao He ,  Herv e Rigneault , and  Muriel Roche  for their critical reading of the manuscript and  Emily Witty (AngloScribe)  for language editing. We thank  Christophe Leterrier  for valuable discussions and  Florian Levet  for his advice on the SR-Tesseler analysis. This work was supported by institutional funding from the  CNRS, Inserm ,  Aix-Marseille University  and  Centrale Marseille  and program grants from the  Research National Agency  ( ANR-10-BLAN-1214  to N. B. and D. M. ), the  French ''Investissements d'Avenir''  ( ANR-11-IDEX-0001-02  A * MIDEX to N. B. and D. M. ,  ANR-10-INBS-04  France  ANR-11-LABX-0054   Labex INFORM , and  ANR-14-CE09-0008-02  to D. M. ), the  Fondation pour la Recherche M edicale  ( FRM-DEQ-20090515412  to D.
Although our IBM is driven by a different movement model to that used for stock assessment of WCPO skipjack tuna, this presents independent justification for the appropriateness of the spatial boundary used in the MULTIFAN-CL assessment model. However, we have also shown that during the movements between regions at broad time-scales there can exist potentially significant detours through other regions, which may be subject to different fishing mortality and other forcings. Using the IBM approach, we can quantify this for a cohort or population of individuals. Understanding the proportion of a sub-population that is exposed to differing mortality rates during broad scale movements has considerable implications for modelled population dynamics in stock assessment. It is important to stress that while both SEAPODYM and MULTIFAN-CL use the same catch data (at different spatial aggregations) to estimate their parameters, they have fundamentally different approaches to modelling the spatial distribution of skipjack tuna.
Acknowledgments The authors would like to thank staff of the  Pacific Community's Oceanic Fisheries Programme  for collaboration, funding and providing data and model parameters, in particular  Sam McKechnie  and  Nick Davies. Development of the Parcels framework, upon which Ikamoana is based, was supported by an  EPSRC   Institutional Sponsorship grant  to  EvS  under reference number  EP/N50869X/1  and the  European Research Council (ERC)  under the European Union's  Horizon 2020 research and innovation programme  (grant agreement No  715386 ). Ikamoana was run on resources and services from the  National Computational Infrastructure (NCI) , which is supported by the  Australian Government , and was funding by  Australian Research Council Linkage Project  grant  LP140100327.
Fault reactivation is likely to be the energetically preferred mechanism to relieve thermal stresses, but the amount of observed slip attributable to thermal contraction is unknown. Given the uncertainties in the distribution and magnitude of global seismic moment release on Mars, it is vital to optimize the deployment of the SEIS package. Deployment problems hampered attempts to unambiguously identify marsquakes from the Viking Mission data  (Lazarewicz et al. 1981) ; the seismometer on Viking 1 failed to uncage, and one of the legs of Viking 2 rested on a rock, causing tilting of 8. 2 • and therefore complicating the response of the instrument to seismic noise. The VBBs chosen for the InSight Mission would not operate at such a large angle of tilt, necessitating the use of the LVL system to allow for ground tilt and small rocks that require some ground clearance of the sensor.
Reduction of atmospheric and thermal noise is also a key requirement of a successful seismometer deployment on Mars. A low atmospheric pressure at the surface (∼ 0. 7% that at Earth's surface;  Schofield et al. 1997 ) results in daily temperature variations of > 80 K near the equator  (Clancy et al. 2000) , which generates strong winds in morning and late afternoon. Even with an improved understanding of wind noise, a recent reanalysis of the Viking 2 data resulted in only a single tentative quake identification  (Lorenz et al. 2017). To reduce the amount of noise recorded by InSight, the SEIS instruments will be deployed only about 15 cm above the surface of Mars, with a shield protecting the package from wind and thermal fluctuations (WTS;  Lognonne et al. 2014). Even with these improvements in design, the number N events observed during the nominal 2-year mission is estimated to be within the range log 10 (N ) = 1.
Data Analysis Analysis of seismic signals was conducted using ObsPy  (Beyreuther et al. 2010 ). To calculate transfer coefficients, seismograms were integrated to displacement and detrended. A spectral power estimate was then estimated after padding the signal to a number of samples 4 times the power of 2 higher than the window length and windowing with a Hanning taper. The amplitude of the signal was calculated by taking the square root of the power spectral estimate over a narrow frequency band encompassing the signal (Table  2 ).
The distance-vertical displacement curves for representative values of k are shown in Fig. 6. This formulation assumes that the Young's Modulus at the surface is equal to zero. However,  Delage et al. (2017)  suggest that their data is better represented by a model where the effective confining stress at the surface is non-zero; i. e. z z 0 = 2 cos( kπ 2 ) π(k + 1) r f r k+1 2 F 1 k + 1 2 , k + 1 2 ; k + 3 2 ; r f r 2 (22) σ c ∼ σ c0 + ρgdz (23) In the absence of an analytical solution, we use the finite-element software FEniCS  (Logg et al. 2012; Alnaes et al. 2015)  to model deformation of regoliths with a range of effective confining stresses at the surface (see Supplementary Information). The resulting surface deformation is shown in Fig. 6. As the gradient in Young's modulus increases, the deformation of the regolith in both models is increasingly confined to the area immediately beneath the foot.
2017; Murdoch et al. 2017). This reduction in displacement is illustrated in Fig. 13. -Although teleseismic energy must propagate through the surface layers of regolith to be recorded by the InSight seismometer, the amplitudes of such signals will be less sensitive to these layers relative to local sources (as they will mostly propagate through solid Mars). We therefore expect signal:noise to be somewhat higher than predicted by  Murdoch et al. (2017). -Our analysis raises the possibility of determining regolith properties (Young's modulus, Poissons ratio) using noise data returned from the SEIS instruments. The value of Young's modulus estimated from the tripod resonance in Sect. 5. 1 is low compared with literature estimates for similar regolith at 150 kPa confining pressure (2 MPa vs. 20-150 MPa), which suggests that this resonance is largely sensitive to the top few centimeters of regolith.
The lower gravity on Mars may also result in a somewhat thicker unconsolidated regolith layer at the InSight landing site, which would reduce the effective Young's modulus even further. -Finally, poor consolidation of sands at the landing site will shift horizontal and vertical signals out of phase. This effect is apparently frequency independent, at least between 5 and 20 Hz. In-depth analysis of particle motions from the InSight data must take this effect into account.
Acknowledgements This research was funded by  UK Space Agency (UKSA)   Aurora Grants  to R. M. and N. T. The authors would like to thank  Charles Clapham  and  Donovan Hawley  for fabrication work involved with the field experiments, without which this work would have been impossible. R. M. would like to thank  Charlotte Gilder  for invaluable discussions, and two anonymous reviewers whose careful and insightful comments significantly improved the manuscript. Seismic analysis was conducted using the python toolbox ObsPy (Beyreuther et al. 2010). The map figure was created using the Generic Mapping Tools (Wessel et al. 2013). Other figures were created with the python matplotlib module.
Therefore, it is not possible to quantify leads or lags of less than 500 yr between records from different marine cores, or between marine and ice core records. Here we take advantage of the fact that the northern Brazilian margin core MD09-3257 records both ocean circulation and atmospheric changes. On the one hand, we reconstruct ocean circulation changes based on new sedimentary Pa / Th data and on epifaunal benthic isotopic ratios. On the other hand, sediment Ti / Ca measured by X-ray fluorescence reflects past changes in rainfall on the adjacent continent  (Arz et al. , 1998; Jaeschke et al. , 2007). Because Pa / Th and Ti / Ca are recorded in the same core, their relative phasing can be examined with virtually no relative dating uncertainty. We first present the new sedimentary Pa / Th data and their relation to changes in mid-depth water transport in the western equatorial Atlantic over the last 45 kyr.
Core locations Core MD09-3257 (04 • 14. 7 S, 36 • 21. 2 W, 2344 m) was recovered in 2009 from the northern Brazilian margin during the R/V Marion Dufresne cruise MD173/RETRO3 at approximately the same position as core GeoB3910-2 (04 • 14. 7 S, 36 • 20. 7 W, 2362 m)  (Arz et al. , 2001; Jaeschke et al. , 2007). The improved recovery of deep-sea sediments with little or no deformation of sediment layers was achieved thanks to the systematic use of the CINEMA software  (Bourillet et al. , 2007; Woerther and Bourillet, 2005). This software computes the amplitude and duration of the aramid cable elastic recoil, as well as the piston displacement throughout the coring phase, accounting for the length of the cable (water depth) and total weight of the coring system. At present, the northern Brazilian margin is bathed by southward flowing upper North Atlantic Deep Water (NADW) at these depths  (Lux et al.
, 2014) , transposed from kyr b2k (before 2000) to ka. Greenland interstadials are numbered according to  Rasmussen et al. (2014). To avoid overcrowding the figure, Greenland stadials (GS) and interstadials (GI) are only explicitly named in the case of GS-8 and GI-8. (b) The MD09-3257 core Pa / Th record. Empty symbols denote data points that may be affected by terrigenous fluxes and should be interpreted with caution; crosses denote replicate measurements; the red line connects average values (filled symbols). Pa / Th could not be measured over the first half of PE2 because of the occurrence of two small sand layers  (Burckel et al. , 2015). (c) The MD09-3257 core and GeoB3910-2 core composite δ 13 C Cw record  (Vazquez Riveiros et al. , 2018) ; crosses denote replicate measurements. (d) MD09-3257 ln(Ti / Ca).
Cross-correlation and wavelet analysis Assuming that there is a constant phase shift between two time series over their entire length, one can perform a simple cross-correlation analysis and compute how the correlation coefficient between the two time series varies as a function of the time lag between the two series (e. g. ,  Davis, 1986). We normalized (i. e. , subtracted the mean and divided by the standard deviation) and resampled the time series Pa / Th, δ 13 C Cw and ln(Ti / Ca) to a common age scale using scenarios with constant time steps varying between 50 and 500 yr. We then used the R function cor. test (R package stats version 3. 2. 2) for correlation between paired series (R script in Supplement) to compute the Spearman correlation coefficient between all pairs of the three time series, after having shifted one with respect to the other by increments of the time step.
(2004)  to compute the cross-wavelet spectrum, coherence and relative phase between our time series that were normalized and resampled as previously described. To test for the persistence of regions of high cross-wavelet coherence, we ran all cross-wavelet analyses 1000 times for each dataset pair (i. e. , a Monte Carlo approach). For each of the 1000 runs, each time data point was randomly sampled, whereby a Gaussian distribution of each data point's value (based on the measurement uncertainty) was used to weight the random sampling. Mean and standard deviation values for the coherence and phase direction were calculated using the 1000 runs.
In the last decade, researchers have designed over 70 read mapping tools  [8] , each differing from another with respect to accuracy, sensitivity, specificity, and speed. Today, state-of-the-art read aligners can map tens of thousands of reads per second to the reference genome. While all prior research focuses on improving performance, by reducing mapping time of individual reads, or scalability, by mapping more reads per second, there is no study that analyzes sequence aligners at the microarchitectural level. Such an analysis is important for several reasons. First, it answers the following question-Do state-of-the-art aligners use modern processors efficiently? Microarchitectural analysis in other applications areas, like relational databases and data analytics platforms, showed that these applications do not utilize modern processors efficiently  [1] ,  [6].