dataesr/scientific-paragraphs-categorization huggingface dataset:
Discussion Previous studies on NTM-PD are often general reviews mainly on the MAC complex  [3, 10] , or epidemiological studies based on laboratory data without clinical or radiological criteria  [11, 12]. Few cohort studies met ATS criteria  [13, 14]. Our cohort included 477 patients who met the 2007 ATS/IDSA criteria for NTM-PD from 18 centers between Unfortunately, this study did not include all NTM-PD cases in France as only 18 centers participated, and does not permit to calculate the exact incidence and prevalence in France. Nevertheless, these 18 centers from the MycoMed network are among the biggest hospitals in France. One other limitation was the delay between the last included patients and the final analysis. Indeed, as it is retrospective study, we needed some administrative authorizations, and some time to give information to all concerned patients.
5%) patients infected with M. fortuitum were treated. Results obtained by Park et al. showed that there was no clinical worsening or persistent positive cultures among the 25 untreated patients on a 12-month follow-up  [17]. These data confirm the low pathogenicity of this species, most often responsible of colonization or transient infection that does not require generally a treatment  [1, 23]. Our results highlight the conformity of practices of French clinicians with the ATS/IDSA guidelines. Most patients received at least three drugs during 12 months or more. These results are in contrast with those of US and European countries  [5, 6]. These differences could be partly explained by the study methodology and physician expertise. These physicians were randomly surveyed to generate nationally representative analyses of practice.
These physicians included practitioners outside of reference centers and in non-specialized fields. These adequacy between French practices and ATS/IDSA guidelines found in our study could maybe explain the good prognosis of treated patients in our cohort in contrast to literature data especially for MAC and M. xenopi  [22, 24, 25]. Indeed, a more favorable evolution was observed in our treated patients, whether or not patients are positive for direct examination. The decision to initiate a treatment should be individualized, based on clinical factors, radiological lesions, and some microbiological data (NTM specie, number and type of positive samples, and probably positive smear, often associated with cavitary lesions), as recommended by the 2 recent NTM guidelines  [2, 9]. In our study, the treatment rate was high, but we have strictly selected patients: all have ATS/ IDSA NTM disease diagnosis criteria, with a low rate of patients with an unique smear negative BAL.
Data and Sample Collection A multidisciplinary team comprising a veterinarian, medical doctor and animal health technician visited each farm. The animal health technician served as the translator, if and when needed, and was therefore, pre-trained on the administration of the questionnaire. The veterinarian administered the questionnaire whilst the medical doctor collected blood samples from the study participants. The sampling of veterinary officials took place at the veterinary offices on appointed days for each State Vet Area. Five millilitres of blood from each participant was drawn into two tubes: (1) clot activator without serum separation and (2) EDTA anticoagulant tube. Blood samples were transported on ice, respecting the biosecurity regulations for human samples transport, to the National Institute for Communicable Diseases, Centre for Emerging Zoonotic and Parasitic Diseases Unit by the medical doctor following the farm visit, for further processing.
Data Management and Analysis Completed questionnaires were captured into the electronic form function of Microsoft ® Access ® (2013), for Microsoft 365, Redmond, WA, USA. Laboratory results were captured into the appropriate record, by matching the unique identifiers of the samples. Descriptive statistics were done in Microsoft ® Excel ® for Microsoft 365, Redmond, WA, USA. Univariable analyses were conducted in STATA 14 ® StataCorp College Station Texas 77845 United States, for outcomes (1) RBT ® , IgM ELISA ® positive and IgG ELISA ® positive, (2) RBT ®. IgG ELISA ® positive and IgM ELISA ® negative, and (3) RBT ® , IgM ELISA ® negative and IgG ELISA ® positive and (4) BrucellaCapt ® seropositivity amongst farm workers and veterinary officials (N = 230). Univariable associations between each variable and the outcomes were assessed using Fisher's exact test.
Acknowledgments: This study would not have been possible without the support and encouragement of the  Gauteng Department of Agriculture and Rural Development. The authors wish to acknowledge the animal health technicians (AHTs), state vets and managers of the department. This study would not have been possible without the following people:  Nolo Moeketsi  (data capturer),  Gerbrand van der Zel and Theo Serebolo (epidemiology AHTs) ,  Peter Geertsma  and  Johan Walters. We also wish to acknowledge  Anastasia Trataris-Rebisz  for performing the testing of the human samples.
Statistical analysis Statistical analysis was performed using MedCalc @ 12. 1. 4. 0 (MedCalc SoftwareÒ, Ostend, Belgium). The number of horses in each group was chosen arbitrarily. Normality of distribution was assessed using the Shapiro-Wilk test. Normal data were expressed as mean ± standard deviation (SD) whereas skewed data were expressed as median and interquartile range  [IQR]. Demographic data was compared between groups using Student's t test. An analysis of variance (ANOVA) for repeated measures was used to detect any signi cant variations of PTA and MAP within 1 min and 5 min at each time-point for both Colic and Elective groups. In case of signi cant variation, post-hoc Tukey multiple paired comparisons were performed. Variations of PTA and MAP within time were compared between groups using two-way ANOVA with Bonferroni correction for post hoc analysis.
It is known that bisphenol dermal exposure is very specific to thermal paper manipulation and/or cosmetics. However, thermal papers contain exclusively free bisphenols, meaning that people, and more precisely cashiers, are handling free bisphenols with their hands. In fact, it has been shown that using hand sanitizer two seconds after handling thermal paper released 235 μg of BPA on hands  51. We also chose to work with 5 and 50 µg/kg BW/d based on data from literature. Indeed, Mielke et al. (2011) simulated the concentration of BPA in blood after dermal transfer from thermal paper by using physiologically based toxicokinetic modeling  50. Their results showed comparable range of BPA concentrations between dermal and oral exposure. Indeed, the estimated daily intake (EDI, occupational exposure) via dermal transfer from cash receipt has been calculated in the range of 18-3119 ng/kg BW/d 3.
At PND70, offspring were euthanized, and blood, jejunum, colon and feces were harvested. Small intestine Lamina Propria (siLP) and spleen were collected for primary cell culture. Sample size ranged from n = 5 to 12 for analyses and the exact number in each group is mentioned in Supplementary data Fig. 1. Humoral response in plasma and feces. Intracardiac blood was collected with a heparinized syringe, and plasma were kept at -80 °C. Fecal proteins were isolated through mechanical extraction in PBS with complete antiprotease cocktail (Roche Diagnostic, Meylan, France) and frozen at -80 °C. Plasma and fecal IgG and IgA concentrations were measured by ELISA as described previously  26. Immunoglobulin specificity against commensal E. coli lysate. Anti-E. coli IgG lysate was measured as described previously  53.
Surface and intracellular staining were performed as previously described  26. Cytokine measurements. SiLP and splenic cells were also seeded on 24-well plates at 1 × 10 6 cells per well for cytokines assays in Cerrotini culture medium (Malaisé et al. , 2018) in presence or absence of 5 μg/mL hamster anti-mouse CD3 and hamster anti-mouse CD28 (BD biosciences) coated wells. Culture supernatants were collected after 3 days of stimulation and frozen at -80 °C prior to cytokines secretion measurement. Cytokines were also analyzed in supernatant of jejunal, colonic fragments or feces resuspended in RIPA buffer as previously described  26. Jejunal, colonic or fecal protein concentrations were measured using BCA uptima kit (Interchim). Multivariate data processing. Mixomics package (6. 8. 2 version) with RStudio software (Boston, MA) (https ://rstud io.
Statistical analysis. Statistical analysis was performed using GraphPad Prism version 6. 00 (GraphPad Software, San Diego, California, USA, https ://www. graph pad. com/scien tific -softw are/prism ). Results were expressed as means ± SEM. Kruskal-Wallis one-way ANOVA comparing each BP group (5 and 50 µg/kg BW/d) to the vehicle group followed by Dunn's post hoc for multiple comparisons were used for statistical analysis. P-values < 0. 05 were considered significant (indicated by asterisks): *P < 0. 05; **P < 0. 01; ***P < 0. 001; ****P < 0. 0001.
Physicochemical characterization The morphology of the processed P(VDF-TrFE) membranes and commercial substrates were characterized by scanning electron microscope (SEM, Hitachi S-4800). Samples were previously sputtered (Polaron SC502) with a thin gold layer. Mean fibre diameter was calculated from measuring approximately 50 fibres using ImageJ software. The porosity of the P(VDF-TrFE) membranes was measured by liquid displacement method using a pycnometer  31 32. The weight of the pycnometer filled with ethanol was measured and labelled as W1. The P(VDF-TrFE) membranes, whose weight was Ws, were immersed in ethanol; after the sample was saturated by ethanol, additional ethanol was added to fill the volume of the pycnometer. Then, the pycnometer was weighted and labelled as W2. The sample filled with ethanol was then taken out of the pycnometer and the residual weight of the ethanol and the pycnometer was labelled W3.
The reaction chambers were first functionalized using 15 µL of the glucose solution under study. After approximately 5 min, the reagent was introduced in the inlet of the microfluidic system, reaching the reaction chambers by capillarity. After 10 min of reaction, a red/orange colour with intensity proportional to the glucose concentration was obtained. The substrates were then scanned (Brother DCP-1610W) and colour analysis was performed with the aid of ImageJ software by measuring mean grey values and the corresponding standard deviation on each reaction chamber of the microfluidic systems. These results were used to build the calibration curves  37.
dL -1 , as described in Section 2. 4. 3. Scanned images of the microfluidic systems after the glucose assays are presented in Figure  6a  and their corresponding calibration curves as well as the extrapolated linear fittings are shown in Figures  6b  and 6c , respectively. For that, mean grey values are presented as a function of the logarithm of the glucose concentration. ImageJ software according to the method described in ref. 37  ; c) Corresponding linear fitting. With respect to the wax print quality, it is confirmed that all microfluidic substrates present good resolution, with the exception of the Whatman TM no. 1 substrates where the wax expands ~1. 2 mm during the thermal post-treatment. This behaviour may affect the capillary flow rate and thus attention must be paid when Whatman TM no.
ACKNOWLEDGMENT This work was supported by the  Portuguese Foundation for Science and Technology (FCT)  under strategic funding  UID/FIS/04650/2020 ,  UIDB/04436/2020 ,  UIDP/04436/2020  and  projects PTDC/EMD-EMD/28159/2017  ( POCI-01-0145-FEDER-028159 ). The authors also thank the  FCT  for financial support under grant  SFRH/BD/140698/2018  (R. B. P. ) The authors also acknowledge funding from the  Basque Government Industry and Education Departments  under the ELKARTEK and PIBA ( PIBA-2018-06 ) programs, respectively. Technical and human support provided by  SGIker (UPV/EHU , MICINN, GV/EJ, EGEF and ESF) is gratefully.
J. V. and M. K. were additionally supported by NordForsk (the Nordic Research Programme on Health and Welfare, grant 75021). S. R. , O. T. , J. V. , J. P. , and H. L. had full access to all the data in the study. S. R. , O. T. , J. V. , and H. L. contributed to the conception and design of the study. J. V. and J. P. analyzed the data; and S. R. , O. T. , J. V. , and H. L. drafted the article. All authors contributed to discussion and reviewed the article critically for important intellectual content, and had final responsibility for the decision to submit for publication. The dataset supporting the conclusions of this article can be made available upon request from the corresponding author after approval is obtained from the STEPS Study Executive Committee. The authors report no conflicts of interest.
To test this hypothesis, we sought to establish the association between neighborhood socioeconomic disadvantage and childhood BMI development from birth to 7 years of age in a population-based longitudinal birth cohort linked to detailed residential histories. The prospective register-based data and annual measurements of height and weight enabled us to assess the BMI trajectories at different exposure levels although controlling for maternal risk factors and parental socioeconomic status (SES). Our results will aid in targeting preventive measures to specific neighborhoods and age groups, which is likely to improve the efficacy of the interventions.
Child Weight and Length Development During the First 7 Years of Life all municipalities are under the obligation to organize a minimum of 15 preventive childcare visits during the first 6 years of the child's life. Children enter the school health care system in the autumn term of the year they turn 7 years of age and, consequently, the municipal well-baby clinic follow-up is completed at the age of 6-7 years. The follow-up clinics use standardized methods for the measurement of length/height and weight provided by the Finnish Institute for Health and Welfare. The anthropometric data at birth and closest to the time points of 1 and 2 years of age (within 3 months), and 3, 4, 5, 6, and 7 years of age (within 6 months) were used in the analyses. The World Health Organization growth charts  19  were used to obtain age-specific z scores for BMI.
Characteristics of Local Environments Data regarding neighborhood social disadvantage were derived from a grid database established and maintained by Statistics Finland. The database contains socioeconomic information from each residence at a spatial resolution of 250 m by 250 m. 20  The grid data were obtained with 5-year intervals between 1990 (the first time point available from Statistics Finland) and 2015. The neighborhood disadvantage score is based on the proportion of adults with low education, the unemployment rate, and the average annual income of households in each 250 m × 250 m grid area. 21, 22 We replaced missing data (i. e. , areas with fewer than 10 residents in the neighborhood) with the mean neighborhood disadvantage score of the eight adjacent map squares. For each of the three variables, we derived a standardized z score based on the total Finnish population (mean = 0, SD = 1).
We then calculated a score for neighborhood disadvantage by taking the mean value across the three z scores. Higher scores on the continuous index denote greater disadvantage. For the statistical analyses, the neighborhood disadvantage score was classified into four categories based on national means as follows: <-1 SD (lowest disadvantage), -1 to 0 SD, ≥0 to 1 SD, and >1 SD (highest disadvantage). We obtained high-quality residential mobility data, based on a complete history of the residential addresses with latitude and longitude coordinates, from the Population Register Center for each mother and her child until the child was 7 years old. Using open-source Geographical Information Systems (QGIS, http://www. qgis. org/en/site/), data on the cumulative residential neighborhood disadvantage for each time point were linked to the cohort participants' home addresses by the latitude and longitude coordinates.
The quality of the residential mobility data in Finland is high as all residential addresses are accurately recorded in the national population register. We were able to accurately calculate cumulative exposure to neighborhood socioeconomic disadvantage based on the residential history of the children using geographically precise and regularly updated spatial information. The prospective study design with serial standardized anthropometric measurements provides reliable growth data and allows assessing the age at which the BMI trajectories diverge. The marginal structural models with inverse probability weighting correct for the differences in the baseline characteristics between included and censored participants and minimize the potential of selection bias that could be introduced because of these differences.
This study has a number of limitations. Data on paternal education or income were not available. It is therefore possible that some of the results are owing to the influence of individual SES. However, the strong association between parental SES and neighborhood disadvantage at birth implies that a major bias owing to such residual confounding is unlikely. Furthermore, data on paternal BMI or smoking had not been recorded. We did not have data on the age at onset of puberty, which has been associated with both individual SES  30, 31  and the risk of obesity. 32, 33 However, it is unlikely that differences in puberty onset explain the observed associations given that the follow-up ended at the age of 7 years while the onset of puberty typically occurs considerably later in children with and without obesity.
The Quantum Self-Consistent Ab-Initio Lattice Dynamics package (QSCAILD) is a python library that computes temperaturedependent effective 2nd and 3rd order interatomic force constants in crystals, including anharmonic effects. QSCAILD's approach is based on the quantum statistics of a harmonic model. The program requires the forces acting on displaced atoms of a solid as an input, which can be obtained from an external code based on density functional theory, or any other calculator. This article describes QSCAILD's implementation, clarifies its connections to other methods, and illustrates its use in the case of the SrTiO 3 cubic perovskite structure.
General workflow The code is a Python library that can perform two tasks: 1. Starting from a set of interatomic force constants and a crystal structure, compute the thermal displacement matrix and generate a number of displaced configurations. 2. After the forces on the atoms in those configurations have been computed from DFT, collect the results and generate new effective force constants. Between those two tasks, the user has to perform the DFT calculations using a workflow that is system-dependent and is thus not implemented by the code. This scheme has to be iterated until convergence is reached. The program keeps track of the successive iterations and can monitor the convergence. At present, the code is written to use input from the Vienna Abinitio Simulation Package  [11, 12]  and Phonopy  [13]  force constants in full format, but it can be adapted to use another DFT code.
[19] ): σ αβ = σ αβ DFT - 1 2V i u α i f β i + u β i f α i (5) The present version of the code only handles the diagonal elements of this stress tensor and thermal expansion is implemented for lattice vectors along the cartesian directions or cubic lattices. In practice, lattice parameters are iteratively modified until the calculated internal pressure equals the target pressure within a chosen tolerance (of the order of kbar).
Symmetries and acoustic sum rules In a first step, irreducible elements of the 2nd and 3rd order interatomic force constants are identified using the crystal symmetries. Within the matrix space that can be constructed from those irreducible elements, we then identify eigenvectors that fulfill the acoustic sum rules using singular value decomposition, so that any force constants matrix generated by a combination of those eigenvectors respects the acoustic sum rule by construction. The operations that generate the full force constants matrix from each of those final irreducible elements are then stored in sparse format. They are characteristic of the crystal symmetry, so they can be used for compounds with the same structure but different chemistry. This part of the code does not run in parallel at present.
This paper proposes an optimization approach for an automatic buck converter printed circuit board (PCB) design regarding the electromagnetic compatibility (EMC) constraints. The proposed solution is based on the combination of a genetic algorithm (GA) and a Dijkstra algorithm to generate the different PCB layout designs. Afterwards, a numerical modeling approach, taking into account all the stray elements, is proposed to obtain an accurate equivalent circuit for the PCB layout using ANSYS Q3D software. Subsequently, the complete behavior of the converter is simulated within SIMPLORER, including the electrical models of the components, the Line Impedance Stabilization Network (LISN) module as well as the PCB layout model. This aims to compute the conducted disturbances such as the common and the differential mode voltages.
The ground plane is modeled like a copper sheet located under the PCB circuit. To extract the parasitic elements, different nets are assigned in the circuit. In our case, we defined five nets, bus+, bus-, switching cell, signal control, and GND. After assigning the desired nets, we place automatically the different components pins on the PCB layout. Pins are then excited by the source and sink terminals in order to set up the simulation solution. A frequency sweep is performed between 10 kHz to 30 MHz. Finally, an equivalent circuit has been exported to the SIMPLORER software which allow the electrical behavior evaluation of the circuit under test (see Figure  9 ). The simulation parameters of the electrical circuit are given in table  2.
The whole optimization process includes three steps. In the first step, an automatic routing algorithm has been applied, which is based on Dijkstra algorithm and governed by a GA. This latter is developed to execute the routing of the interconnected tracks. For the first generation, this algorithm allows to randomly generate several PCB layouts candidates by connecting the position of the components with copper trace. These candidates are grouped together as initial solutions within the same family. In the second step, after obtaining the PCB layout, it will be modeled through ANSYS Q3D. The coupling between MATLAB software and Q3D extractor software is established automatically thanks to DXF file. Subsequently, the PCB layouts are modeled to characterize the parasitic elements. All these elements, such as resistive, inductive and capacitive effects, are taken into account to obtain an accurate equivalent circuit of the layout.
The paths obtained under MATLAB are used to build the tracks. For example, from a path between two nodes A and B with A (X A , Y A ) and B (X B , Y B ), we built a rectangle representing the conductive track (see Figure  15 ). It was therefore necessary to determine the coordinates of the points F = (X F , Y F ) and C = (X C , Y C ). We will start by computing the angle θ which is given as: θ = tan -1 DX DY (7) Since the width of the track l and X A are known, the relation between points A and C are described by the following two relations: Thus, we get such that: cos π 2 -θ = X C -X A l/2 (8) sin π 2 -θ = Y A -Y C l/2 (9) VOLUME 9, 2021 X C = l/2 cos π 2 -θ + X A ( 10 ) Y C = -l/2 sin π 2 -θ +Y A (11) Likewise, we can determine the coordinates of point F, so we have: X F = -l/2 cos π 2 -θ +X B ( 12 ) Y F = l/2 sin π 2 -θ +X B ( 13 ) The degrees of freedom in the path generation procedure are based mainly on: 1) PCB trace width, designed according to input rated voltage, current and over-heating  [30] ,  [31].