dataesr/scientific-paragraphs-categorization huggingface dataset:
More in details, we choose k = 16 for SANS, and k m = 16 and 7 http:// www. hiv. lanl. gov/ τ = 0. 5 for phyBWT2 (parameter setting similar to other datasets). We observe that phyBWT2 clusters in clades each ECOR group (i. e. groups A, B1, B2, D, E and S), apart from S. dysenteriae that is placed externally to Group S, more precisely as sister to Group E. However, we note that also in the reference tree S. dysenteriae is placed externally, as sister to the pathogenic E. coli O157:H7 isolates (Group E). Also the tree reconstructed by SANS shows such a relationship between S. dysenteriae and Group E. Differently from the reference tree, both phyBWT2 and SANS placed groups A and B1 as sister groups. Time and memory The time usage of phyBWT 2 and SANS for this dataset is comparable (including the time for the preprocessing step completed by the internal Fig.
11  The phylogenetic tree on the 42 HiV-1 sequences by phyBWT2. Re-root the tree in CIV strain AF447763, as it is set outgroup in the reference tree in  [37]  memory approach gsufsort  [45] ), which is also comparable to the time spent by the older version phyBWT. By keeping the data structures on disk, phyBWT2 improves the memory usage of phyBWT. Finally, also for this datasets the number of iterations performed by phyBWT2 improves on those performed by the previous version.
e. by deducing lcp(R) , ebwt(R) and cda(R) ) from lcp(S) , ebwt(S) and cda(S). To the best of our knowledge, phyBWT and phyBWT2 are the first methods that apply the properties of the Extended Burrows-Wheeler Transform (eBWT) to the idea of phylogenetic reconstruction. Both approaches are based on the eBWT positional cluster framework introduced in  [19] , which allowed us to consider longest shared substrings of varying length, unlike k-mer-based approaches such as SANS. Fig. 13  The phylogenetic tree on Ebolavirus dataset by phyBWT2 Fig. 14  The phylogenetic tree on Ebolavirus dataset by SANS Differently from phyBWT, phyBWT2 combines the inner algorithm based on the eBWT positional clustering to a refinement procedure that reconstructs a phylogeny step-by-step by considering multiple partitions at each step, instead of just one partition as done by phyBWT.
We tested our method on several sequencing datasets, with short reads and de novo assembled sequences. The experimental results show that our algorithm produces trees comparable to the benchmark phylogeny and to the recently introduced tool SANS. Our current implementation requires a preprocessing phase in order to compute the input data structures ( ebwt , lcp and cda ), which are at the heart of several other text and string algorithms. Thus, evaluating the best tool or the combination of tools for the pre-processing phase is out of the scope of this work. More efficient tools for computing them can appear in the literature improving both the time and the memory requirements. the input data structures we used are independent of the parameter settings, so they can be computed only once and re-used for different runs of phyBWT2.
Indeed, by using different types of data (e. g. genomes rather than short reads) phyBWT2 parameters may need to be fine-tuned, and there is no need of rebuilding from scratch the input data structures when changing phyBWT2 parameters. The same remarkable feature does not hold for k-mer-based approach, such as for instance SANS. Phylogenetic analysis is a common practice in HIV studies  [56, 58]. Experimentally we show phyBWT2 is able to distinctly group together the HIV-1 subtypes and to grasp the relationships among the subtypes. Virus subtypes can be clinically significant owing to their associations with variation in pathogenesis. While the worst-case complexity of the method is competitive with existing methods, there are interesting directions for further optimization, such as using Colored Range Queries  [59]  to speed up identification of colors in the various clusters, or exploiting the bounded length of the reads to overcome the computational bottleneck of computing the eBWT and related data structures.
This is the aim of this article. In Section 2, we propose a methodology on a case study located in the city of Saint-Martin-de-Londres, Hérault department in France, whose relevance will be evaluated to carry out the sound mapping of a siren-driven warning system. We collected acoustic and perceptual data during an experiment in the study area which was then compared with calculations carried out using NoiseModelling, a noise mapping software that embeds the Common Noise Assessment Methods in Europe (CNOSSOS-EU) propagation model. Section 3 presents the results obtained through a correlation test between each dataset. We discuss the technical limitations of this study as well as the perspectives on the future development of the methodology in Section 4. Finally, the consequences in terms of estimation of siren audibility by modeling are reviewed in Section 5.
Case study The study area is located in Saint-Martin-de-Londres, a municipality of about 3,000 inhabitants approximately 30 km north of Montpellier, France. The municipality has a warning siren installed on a mast near a municipal building. The experiment took place on October 6, 2021, at 12:15 during the siren's activation of about 1 min and 41 s, as part of the monthly exercise in France every first Wednesday of the month to ensure that they are functioning properly. Twenty-five participants (Natural Risks Management Master students of the University Paul-Valéry Montpellier 3) were deployed at variable distances all around the siren at the points indicated in Figure  1. The farthest participants were approximately 2. 5 km from the siren's location. Sound level measurements and perceptual data regarding the audibility of the siren were collected simultaneously.
For this purpose, participants were equipped with NoiseCapture, an opensource Android application to measure sound levels on a smartphone  [25]. Participants responded simultaneously to a questionnaire, in order to evaluate their perception of the siren. The relationship between these two series of data is addressed in Section 3. 2. 1. The siren was located on a mast 10 m above the ground and activated for 1 min and 41 s emitting a tonal acoustic signal of 135 dB at a fundamental frequency of 380 Hz. It is composed of an 8-horn-type loudspeaker array in a 360°disposition, therefore ensuring an omnidirectional behavior during activation (Figure  2 ). Its theoretical spatial extent is around 3 km.
Acoustic measurements Sound level measurements were achieved thanks to NoiseCapture¹, a free Android application designed to perform acoustic measurements and share the user's sound environment using the microphone on their cell phone  [25]. The data obtained by the NoiseCapture application contain the measured sound level by frequency band (1 s, third octave), the equivalent sound level over the duration of a measurement in dB(A), an identifier of the measuring device, and its global positioning system (GPS) position at the time of the measurement. The GPS track associated with the sound recording has a temporal resolution of 1 s and a mean spatial accuracy of approximately 6 m. Participants were equipped with the micW i436 calibrated measurement microphone, an omnidirectional microphone with a sensitivity of 6.
The time series for L400 one-third octave band, the emergence (L400 with respect to L315), and the  observed equivalent sound level L400 Obs are shown in Figure  4  and Appendix. During the processing of the measured acoustic data, we noticed that 5 out of the 25 measurements were not exploitable due to corrupted data from inadequate handling of the measuring device by the participant, wind, or overall non-optimal conditions. These measurements were then manually removed from the dataset. The technical limitations of this manual approach are discussed in Section 4.
The geometry of the buildings, the ground topography, and the digital elevation model come from the BD TOPO ©databases départementale 2018² and BD ALTI ©25 m 2021³ from IGN (French National Mapping Agency), respectively. The absorption factor G for soil was assigned to the ground layer according to the recommended values given by CNOSSOS-EU. Diffraction from vertical and horizontal building edges were taken into account, as well as reflections 2 from facades within 500 m of the receiving point. The directions of the favorable conditions for propagation were estimated on the basis of meteorological forecasts, as well as field experience. The values retained for each of the cardinal directions are presented in Table  1. The wind direction as informed by⁴ is presented in Figure  6.
This is a clear example of the impact of the topography on sound wave propagation and it is discussed in Section 4. Figure  9  represents the audibility values from the perceptual dataset. Distances does not appear to be the only parameter impacting the audibility of the siren, as some participants perceived the siren at a medium level while being located farther than others perceived the siren at a low level, for example on the east part of the study area. Bias could be due to the propagation model but also due to the different perceptions of each participant. The following section discusses in more detail the links between acoustic measurements, perception, and simulations.
Cross analysis: Acoustic measurements, perception, modeling A cross-analysis has been performed between acoustic measurements, simulated noise levels, and perceptual data in order to compare the different modeling approaches. The Spearman correlation coefficient is calculated to establish the monotonic relationship between each dataset and so it is more adequate for our particular case considering our data. In this section, we introduce five indicators    Method for assessing the audibility of a siren-driven alert system  7  representing different measured and collected information during the experiment: -L400: Equivalent sound level at the 400 Hz one-third octave band of measured levels; -L 400-315 : Difference between the 400 and 315 Hz onethird octave bands of measured levels, which is an indicator of the spectrum emergence of the signal as explained in Section 2.
Discussion A methodology involving on-site measurements, numerical simulation, and perceptual data is proposed to assess the audibility of a warning siren system through the evaluation of its spatial coverage. The acoustic measurements were performed by a group of participants equipped with the NoiseCapture application and some calibrated microphones. Alongside the measured data, we obtained perceptual data through a questionnaire filled out by each participant regarding the audibility of the siren as well as the global sound level at each measuring point. Two numerical models were set up in the study area using NoiseModelling to determine the most adequate set of parameters to carry out the cartography of the sound environment during the activation of the siren. This showed the added value of relying on complete modeling of sound propagation, as considered under the CNOSSOS-EU approach, to assess the spatial coverage of the siren sound signal, compared to a classical concentric circle approach.
Similarly, our results are in line with the results presented in Volkmann and Graham's study  [24]  that suggest a minimum sound level of 80 dB for the siren to be audible. This study also confirms in this specific case the validity of CNOSSOS-EU employed beyond its theoretical threshold distance (800 m)  [28]  through the correlation tests presented in Section 3. These experiments indicate that simple signals such as those of warning sirens can be heard to greater distances than the previously mentioned (800 m) as the furthest measuring point was located at 2. 8 km of the siren; nonetheless, participants placed at further distances indicated having heard the siren at a very low level. This statement is solely valid for the particular study case herein presented. To choose a representative sound level for the siren in each measuring point, we perform a visual analysis of each time series in the dataset, and by evaluating the emergence of the 400 Hz one-third octave band with respect to the 315 Hz band, we propose an equivalent sound level L400 Obs.
Acknowledgments:  Jonathan Siliézar 's thesis is co-financed by the  Gustave Eiffel University  and the  Pays-de-la-Loire region. The authors would like to thank the students of the  Master Gestion des Catastrophes et des Risques Naturels (GCRN)  of the  University Paul-Valéry Montpellier 3  who participated in the experimentation. Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.
MEASURING SPECIFIC PARAMETERS In recent years, we have received several requests to make specific measurements with the sample under carefully controlled conditions. Three of these are now described. Measuring the Mechanical Properties of Ultrathin Polymer Films Using the "Nanobubble" Technique. The first system uses control of the pressure, temperature, and humidity to measure the mechanical properties of ultrathin polymer films (Figure  8 ). The method used is known as the "nanobubble" technique, in which the thin polymer film is placed on a grid of 5 μm diameter holes and the film pressurized from behind to form a "bubble". The curvature is then measured over a period of several hours as the material relaxes, and the data can then be used to measure the dynamic creep compliance. While AFM was used when the technique was first proposed,  23  in the present work we use phase stepping microscopy since it has nanometric axial sensitivity and can be used to measure several bubbles at once and average the measurements to improve the precision.
Data are shown as the means ± SDs. Statistically significant differences were found using Mann-Whitney or unpaired t tests. ***p ≤ 0. 001 controls (Control and Young groups). These libraries were subjected to high-throughput sequencing. Only functional sequences with unique CDR3s, the most diverse part of Ig transcripts, were retained to eliminate potential PCR biases and clonal expansions. We obtained 10,406 to 27,241 unique sequences per sample, of which 16-18% were nonfunctional. These nonfunctional sequences were not further considered, as the purpose of this study was to determine the impact of aging and HU on the expressed IgM repertoire. We also assessed the efficiency of the strategy used to create our libraries by determining the number of functional IGHV gene segments in our datasets.
The International Immunogenetics Information System (IMGT) predicts 125 functional IGHV gene segments in the murine immunoglobulin heavy chain locus (IGH) located on chromosome 12  [23]. Additional file 1 shows that 130 functional IGHV gene segments were detected in our datasets. We are therefore confident that our libraries provide an accurate picture of IGH rearrangements. This is supported by previous studies that Fig. 2  Quantification of pro-B and pre-B cells in the bone marrow of HU and aged mice. A, B, C Gates designed to identify pro-B and pre-B cells. These cells were identified based on the expression of the following markers: pro-B (CD19+/B220low/CD43+/IgM-) and pre-B (CD19+/B220low/ CD43-/IgM-). A Selection of CD19+ lymphocytes from viable bone marrow cells. B Among CD19+ lymphocytes, cells could be divided into B220 high and B220 low populations.
C In the B220 low population, depending on the expression of CD43 and IgM, the pro-B (CD43+/IgM-) and pre-B (CD43-/IgM-) populations could be distinguished. D, E Frequencies of pro-B and pre-B cells in the bone marrow of control (n = 14) vs. HU (n = 13) (D) and young (n = 13) vs. aged (n = 13) (E) mice. Data are shown as the means ± SDs. Statistically significant differences were found using Mann-Whitney or unpaired t tests. *p ≤ 0. 05; **p ≤ 0. 01; ***p ≤ 0. 001 have shown that detected IGHV gene segments assessed without amplification parallel the repertoires reported using more focused amplification methods  [24, 25]. To determine how aging and HU affect the IgM repertoire, dispersion indexes (DIs) were calculated. These indexes vary from 0 (no diversity) to 1 (greatest diversity). Because the two independent HU experiments and the study of aged mice could not be performed simultaneously, several 3.
Discussion To our knowledge, this is the first time that the bone marrow IgM repertoire of aged (18 months) C57BL/6 J mice has been studied by high-throughput sequencing. As this mouse strain is a model used in many research fields (a PubMed database search on June 05, 2023, found 25,982 results containing the word C57BL/6 J) [30], these high-throughput sequencing data deposited in the NCBI Sequence Read Archive could  [31] , beyond the purpose of this study, be useful to the scientific community at large.
Limitations This study is limited by the fact that we might have missed some unique rearrangements corresponding to rare B-cell clones, as indicated by a study that compared datasets generated with or without amplification  [64]. However, we are confident in our results because the number of IGHV segments analyzed and detected in our libraries shows that they provide an accurate picture of IGH rearrangements. Another limitation is that bone marrow contains, in addition to naive B cells, memory and plasma B cells, the contribution of which to the modification of the IgM repertoire could not be determined since our libraries were prepared from whole bone marrow.
The second was performed on an aliquot of the first PCR using another gene-specific primer, GSP2 (see Additional file 4), which anneals upstream of GSP1, and the NUP primer annealing to UPM. PCR products generated by this second PCR were separated on an agarose gel, and those of the expected size (0. 6 kb) were purified using the Nucleospin ® Gel and PCR Clean-up Kit (Macherey Nagel, Hoerdt, France). Libraries were prepared by adding Illumina adapter sequences (NEBNext ® Index Primer for Illumina) to these PCR products, and high-throughput sequencing was performed from both ends (2 × 300 bp paired-end DNA sequencing) using the Illumina MiSeq sequencer of UAR IBSLor from Lorraine University (Vandoeuvre-lès-Nancy, France). Sequencing data were analyzed using IMGT/High V-quest software  [70]  (http:// www.
Software program dedicated to the analysis of VDJ sequences A program written in Perl was created to calculate the necessary parameters for our studies. This program parsed 16 different files, corresponding to 16 different types of samples (4 for young mice, 4 for aged mice, 4 for HU mice and 4 for control mice), produced by IMGT/ HighV-quest  [23]. Two to four seconds of execution was necessary to analyze a file. This execution time was proportional to the number of lines to process, with each line corresponding to 1 sequence. There were 506,399 to 960,860 lines for young mice, 332,443 to 488,167 lines for aged mice, 179,149 to 337,558 lines for HU mice, and 357,791 to 678,075 lines for control mice. The program examined each row and identified those having a CDR3 and a productive functionality.
Statistical analysis Dispersion indexes were used to determine if differences existed between control vs. HU and young vs. aged mice for the analyzed parameters. These indexes were calculated as previously described  [4, 56]. GraphPad Prism 9. 0 software (SAS Institute Inc. , Cary, NC, USA) was used to perform statistical analyses. For two-group comparisons, the homogeneity of variance was determined using the Fisher test, and the normality of distribution was determined using the Kolmogorov-Smirnov test. When homogenous variances and distributions were observed, Student's t tests were performed. When the variance and distribution were not homogeneous, Mann-Whitney nonparametric tests were performed. In the case of multiple comparisons, the homogeneity of variance was determined using the Bartlett test, and the normality of distribution was determined using the Shapiro-Wilk test.
Availability of data and materials The sequencing datasets generated and analyzed during the current study have been deposited in the NCBI Sequence Read Archive (https:// www. ncbi. nlm. nih. gov/ sra)  [31]  under accession numbers PRJNA559699 for young/ aged mice and PRJNA559675 for control/HU mice. All other data generated or analyzed during this study are included in this published article [and its supplementary information files].
MATERIALS AND METHODS This was a cross-sectional prospective study performed in the department of Ophthalmology at Bordeaux University Hospital (France). The signal processing method was developed in the electrophysiology and heart-modeling institute (IHU LIRYC) at Bordeaux University (France). The aim of the study was to analyze and compare the 24-hour monitoring output signal provided by a CLS between 2 groups of patients with OAG with different rates of visual field progression measured with standard automated perimetry. All subjects provided informed written consent for enrollment in the study. The research followed the Declaration of Helsinki's tenets and the study was approved by the institutional review board and by the ethical committee of Bordeaux in 2013. This trial is registered with ClinicalTrials.
24-Hour IOP Related Fluctuations Monitoring Using a CLS We used a CLS with a strain gauge (Triggerfish; Sensimed AG, Lausanne, Switzerland) to assess 24-hour IOP related fluctuations monitoring for each eye included. The technology of the CLS was published by Leonardi et al. 17  strain gauge is a platinum-titanium sensing-resistive gauge that enables a recording of circumferential changes in the area of the corneoscleral junction by varying its voltage according to its deformation. A microprocessor connected to the gauge sends an output signal proportional to changes of the strain gauge's voltage. Wireless power and data transfer are achieved using a patched periorbital antenna, which is made possible by using an inductive coupling system. Two coils are coupled: the first one is a gold coin connected to the strain gauge into the contact lens, and the second one is a copper coil inserted into the patched periorbital antenna.
Signal Processing A three-step dedicated signal processing method was developed and implemented under MATLAB software (Mathworks, Natick, MA, USA). Sensimed (Lausanne, Switzerland) provided the raw outputs of the CLS data for each patient: 300 samples during 30 seconds every 5 minutes during the 24 hours (N = 86,400 samples). The company was masked to clinical data. First, blinking artifacts were removed from the signal. During the day period, the 30-second periods are regularly distorted with abnormal high values that last for about 10 milliseconds. These outlier areas were identified as being associated with blinking movements (Fig. 1B  during the day period, and Fig. 1C  during the night period). An adaptive threshold-based derivative method was developed to automatically detect these areas and linear interpolation was performed to smooth the signal.
Classification Between the Two Groups The objective being to design a classifier that allows the automatic classification of the patients group 1 versus group 2: classification accuracy of each feature presented above used individually (univariate classification) was tested and reported as the area under the curve of the corresponding receiver operating curve (AUROC). Then, a multidimensional classifier (multivariate classification) based on linear discriminant analysis was optimized to account for several features simultaneously: a Downloaded from iovs. arvojournals. org on 04/18/2023 20-fold cross-validation strategy was used to divide the database into training sets and validation sets. The training sets were used to perform (i) feature selection and (ii) classifier parameter fitting. The results are presented on the validation sets.