dataesr/scientific-paragraphs-categorization huggingface dataset:
Data on child's health and use of healthcare services were obtained from the parental questionnaire. Parents were asked whether, since discharge from NICU, their child had received care at a healthcare centre (NICU or other unit in the hospital, a community maternal and child care or rehabilitation centre, or a hospital emergency Conclusion: Rehospitalisation and outpatient care are frequent in VP children, confirming a substantial health and economic burden. These findings should inform the allocation of resources to preventive and rehabilitation services for these children.
| Statistical analysis We investigated two main outcome variables describing the use of healthcare resources between discharge from NICU and 2 years CA: (a) any rehospitalisation and (b) overall healthcare cost (in euros) per child, including both in-and outpatient care. We used a multivariable modified Poisson analysis with extension to correlated data  19  to model the adjusted risk ratios (aRRs) of rehospitalisation. For overall healthcare costs, we carried out multivariable log-linear regression analysis, with natural logarithmic transformation of the outcome variable (costs per child) due to its asymmetric right-skewed distribution. 20 For both models, the cluster option by mother identification code was used to take into account data correlation for twins and higher order multiple births.
Variables statistically associated with any of the two outcomes at P <. 05 plus region, child CA at follow-up, maternal country of birth and age were retained in the final models. We used multiple imputation with chained Equation  21 to generate values for missing maternal country of birth (n = 3) and education (n = 11), severe brain damage (n = 5), necrotising enterocolitis and/or sepsis (n = 6) and BPD (n = 10). All variables included in the models as predictors or outcomes were used to impute missing values. Data were assumed to be 'missing at random'. 21 One hundred datasets were imputed. Finally, we carried out mediation analysis to assess whether the effect of GA was mediated by the prematurity-related morbidities diagnosed in NICU. As independence of effects could not be assumed, the mediators were considered together according to the inverse odds weighting approach.
The following functionalities should be mandatory. In any case, automatic transmission of exposure data should be possible for computed tomography (CT) and interventional radiology (IR), as the data due to their higher radiation dose levels must be analysed especially for these modalities. The EU-BSS puts a special focus on exposures from CT and IR modalities (Art. 60 3. (d, e) and Art. 61 1. ). For the implementation of all tasks, a complete connection of all devices is necessary even if central connection to the PACS is preferable. However, this can be limited to some extent when using computed radiography (CR) systems, as not all relevant data are automatically attached to the image data. The transfer of the data into the database of a DMS can be done in different ways but should be done automatically.
Direct network connections to the imaging modalities, the image archiving and communication system (PACS) and the radiological information system (RIS) are recommended, depending on the systems used. It must be ensured that each modality dose descriptor and the respective examination parameters used, including information on the device, are transferred to the database of the DMS in order to enable targeted evaluation. Manually recorded dose descriptors are always problematic, since this method has the potential to store incorrect or not useful values in the database. This is a situation occurring frequently in practice leading to incorrect values in a DMS. An IT infrastructure in which all dosimetric data are automatically linked to the image or automatically transferred to the RIS or PACS is the better solution.
DMS must be able to correctly assign information sent in the form of the Radiation Dose Structured Report (RDSR) and dosimetric data extracted from DICOM image headers to the corresponding examinations, series or images. The analysis of dosimetric data inserted in the database must support the listed tasks: & To calculate median doses for individual types of examinations and devices in order to check compliance with the local, regional or national DRLs. & If unintended exposures according to the EU-BSS occur, to alert automatically the radiation protection officer and the MPE so that it can be determined whether a reportable event has occurred. & To obtain information on the temporal development of the median dose for individual types of examinations in order to be able to quickly determine the success of optimisation measures.
Requirements In addition to the requirement profile, the prerequisites for the installation and operation of a DMS in a clinical environment should also be checked or created. Each DMS requires a considerable amount of work for configuration and maintenance. The database of a DMS receives new exposure data every day. A considerable amount of work is involved in the maintenance of the device configuration, the types of examination and protocols; furthermore, incoming data must be regularly checked for plausibility and completeness. Examination protocols must be kept up-to-date and, depending on the number of users of a DMS, the administrative workload should not be underestimated. Depending on the number of integrated devices, the number of protocols and the users, the complete configuration time of a DMS can take a few months.
Integration into the IT infrastructure The basic tasks of a DMS include optimisation, QA, monitoring of national and local DRLs, detection of significant events or exposures and dose documentation of patients. In order to ensure this, it is essential to integrate the system into a central IT structure. This integration includes different levels of administrative data structures. Here, the level of patient data must be mentioned, to ensure that a patient has a unique ID, name, date of birth, sex, etc. in all systems in order to guarantee unique identification. Since normally all patient data are managed/ changed in a super ordinated master system (HIS or RIS), the DMS must track any changes. Otherwise, the dataset in the systems will diverge and reliable dose documentation will no longer be possible.
Image data Using the DICOM metadata associated with the image data can be a good alternative or addition for transfer of dosimetric data. In most cases, many other examination parameters that are not available in the RDSR can be extracted. However, this is inevitably associated with a high network load and system load if the image pixel data are not stripped from the headers. Some DMS cannot distinguish between secondary reconstructed images and the primary acquisition (e. g. in CT). Therefore, examinations with one primary acquisition and several secondary reconstructions with multiple dose entries can be registered in a DMS. When using image data, this should be checked carefully.
It must be clearly defined if exposure data are linked on image, series or procedure level. The integration of interventional procedures beyond the simple storage of air kerma-area products (P ka ) is complex, as calculation of skin doses and skin dose mapping requires RDSR datasets with field size, tube and C-arm positions for all fluoroscopic steps of a procedure. Challenges are criteria for detection and reporting of unintended exposures as there is a wide range of implementations of the EU-BSS into national law like absolute doses, multiples of DRLs, effective dose or just plain text. In summary, there are a number of important requirements that must be met and that determine the success or failure of the introduction of a DMS. & A network connection with DICOM standard of all relevant modalities either to a PACS or directly to a DMS system.
, 1993; Kushnerenko et al. , 2002; Novak, Kurtzberg, Kreuzer, & Vaughan, 1989). The current study thus focuses on infants' neural processing of prosodic information from IDS as reflected in the P2 component of the ERP. Because previous studies of infants' neural activity suggest that the capacity to process different types of emotional prosody in language develops around the age of 6 or 7 months  (Grossmann, Oberecker, Koch, & Friedericki, 2010) , we observed infants in this age range. When speaking to infants, most adults readily adapt the way they talk. In English, IDS, sometimes referred to as "motherese," is characterized by simplified sentence structures, a higher pitch, greater variation in pitch, longer pauses, and a slower rate of speech compared to adult-directed speech Grant/Award Number: RGY-0073-2014; ANR grant, Grant/Award Number: ANR-15-CE37-0009-01 frontal asymmetry did not moderate effects of sensitivity or intrusiveness.
| Participants A total of 33 infants and their mothers participated in two experimental sessions. Another 10 motherinfant pairs participated in the first session only (as infants neural activity was recorded during the second session, these 10 pairs are not included in the current analyses). Participation was rewarded with a diploma for the infant. Complete datasets were available for 22 of the 33 mother-infant pairs (one infant's EEG was not recorded due to technical error, for one infant data collection was stopped within 1 min because the infant did not tolerate the cap, ERPs were unavailable for three infants because of a poor connection of the mastoid electrodes, two infants provided insufficient artifact-free baseline and ERP data, three babies provided insufficient artifact-free ERP data only, and one baby provided insufficient artifact-free baseline data only).
| Procedure Informed consent was obtained from parents at the start of the first session. The first session took place at the Laboratoire Psychologie de la Perception (Paris Descartes University & CNRS) and consisted of a 15-min observation of mother-infant interaction (see details below), after which mothers completed the Reading the Mind in the Eyes Test (RMET). The second session took place at the Robert Debré Hospital (Paris, France). During the second session, babies' brain activity was measured using both EEG and NIRS (see details below). The NIRS data will be reported elsewhere. Brain activity was recorded first during a 1-to 3-min baseline period and then while babies listened to directives pronounced with a happy or an angry prosody by a female adult. Throughout the recording session, infants were seated on their mother's lap and watched an experimenter silently building towers with foam blocks in a standardized sequence to maintain the infant's attention and avoid excessive movement.
| EEG Infants' EEG was recorded from 12 electrodes (located at F3, Fz, F4, C3, C4, P3, Pz, P4, O1, O2, left mastoid, and right mastoid) with a Cz reference and a ground placed at FPz. The EEG was filtered with a 0. 01-100 Hz passband range and digitized at 500 Hz using a Brain Vision ActiChamp amplifier and PyCorder software (Brain Products GmbH). Impedances were kept below 50 kΩ as much as possible. Further processing of the EEG was done offline using Brain Vision Analyzer 2 (Brain Products GmbH). Infants sat on their mothers' lap during the entire recording. Mothers were instructed to try and keep the baby's hands away from the wires, but otherwise not to interfere or interact with the infant and to remain silent throughout the recording procedure.
To rate the inherent valence of the utterances, seven adult French native speakers were presented with a written list of 46 simple directives and rated each utterance on a 7-point scale ranging from "very negative" to "very positive. " We selected only those utterances that had an average rating larger than 3 and smaller than 5, and for which the extreme scores of 1 and 7 were not selected by any rater. A female French native speaker then recorded each of the 24 utterances three times with an angry prosody and three times with a happy prosody. Sound files for each utterance were edited using Audacity 2. 1. 0 software. A hard limiter (-10 dB) was applied to approximately equalize the volume of all sounds, and a linear fade over the first 100 ms (0 to -10 dB) of the sound was applied to approximately match onset envelopes.
The experimenter continued to silently build towers of foam blocks in a standardized sequence throughout the experiment to maintain the infant's attention and avoid excessive movement. The experimenter avoided eye contact with both baby and mother throughout the experiment. 2. 5. 2 | Data processing: Baseline frontal asymmetry EEG data collected during the baseline period were bandpass filtered between 0. 3 and 30 Hz (highpass: -3 dB, 12 dB/octave; lowpass: -3 dB, 48 dB/octave) and segmented into 1 s segments with 0. 5 s overlap. Baseline data obtained from the electrodes placed at the mastoids were discarded (the mastoid electrodes were included to function as a reference in ERP computation only and have no function in the measurement of frontal asymmetry). Next, following standard practice in EEG/ERP research, segments and channels affected by artifacts were rejected (see, e.
Power values were averaged across all segments and then averaged across the frequency range of 6-9 Hz to obtain measures of power within the alpha band (the 6-9 Hz range is considered the infant equivalent of the 8-12 Hz adult alpha band;  Marshall et al. , 2002). To normalize data distribution, the natural logarithm (ln) of these values was computed. As a measure of frontal asymmetry, values obtained at F3 (i. e. , alpha activity over the left frontal cortex) were subtracted from values obtained at F4 (i. e. , alpha activity over the right frontal cortex): ln(F4)-ln(F3). A zero value on this measure thus represents no frontal alpha asymmetry, whereas more negative values result from greater alpha power over left compared to right frontal cortex and therefore represent greater relative right frontal cortical activity.
| Data processing: ERPs EEG data collected while the infants listened to the utterances were bandpass filtered between 0. 3 and 30 Hz (highpass: -3 dB, 12 dB/octave; lowpass: -3 dB, 48 dB/octave) and rereferenced to the average activity at left and right mastoids. Segments extending from 200 ms before to 600 ms after the onset of each utterance were extracted. Then, following standard practice in ERP research to discard data contaminated by artifacts (see, e. g. ,  Luck, 2015) , an automatically aided artifact rejection was performed as follows: Segments were automatically rejected if the difference between the minimum and maximum voltage in the segment exceeded 160 µV for at least three channels (if such an artifact only occurred on one or two channels, the individual channels were removed from the segment).
| Analyses Statistical analyses were performed using IBM SPSS 23 software. In a first set of preliminary analyses, we tested the correlations between all maternal variables (sensitivity, intrusiveness, and RMET performance), as well as between maternal sensitivity and intrusiveness on the one hand and infants' frontal asymmetry on the other. We tested the main hypotheses in a second set of analyses. Specifically, a repeated-measures ANCOVA with P2 amplitude as the dependent variable, condition (happy vs. angry) as a categorical independent variable, maternal sensitivity and maternal intrusiveness as continuous independent variables, and maternal RMET scores as a covariate was used to test whether maternal behavior was associated with infants' ERP responses to happy and angry utterances. To test whether infants' frontal asymmetry moderated any associations between ERP amplitudes and maternal variables, a second repeated-measures ANCOVA was performed with infant frontal asymmetry as an additional continuous independent variable.
ACKNOWLEDGMENTS RH was supported by a  Marie Curie Intra-European Fellowship , Grant number  626598. MJBK was supported by research awards from the  Netherlands Organization for Scientific Research  ( VICI grant  no. 453-09-003 ) and the  European Research Council  ( ERC AdG 669249 ), and JG acknowledges the support of the  LABEX EFL  ( ANR-10-LABX-0083 ), a  Fyssen Foundation Startup Grant , an  Emergence(s) Programme Grant  from the  City of Paris , a  Human Frontiers Science Program Young Investigator Grant  ( RGY-0073-2014 ), and an  ANR  grant (nr. ANR-15-CE37-0009-01 ).
Funding information Marie Curie Intra-European Fellowship , Grant/Award Number:  626598 ;  Netherlands Organization for Scientific Research , Grant/Award Number:  453-09-003 ;  European Research Council , Grant/ Award Number: AdG 669249; LABEX  EFL, Grant/Award Number :  ANR-10-LABX-0083 ;  Fyssen Foundation   Startup Grant; Emergence(s) Programme Grant  from the  City of Paris ;  Human Frontiers Science Program Young Investigator Grant ,.
METHODS Serum allergen-specific IgE levels to 112 components were measured at ages 18 months and 8/ 9 years by ImmunoCAP ISAC. IgE concentrations (in ISAC standardised units) were discretized into four categories according to the manufacturer's guidelines. K-means clustering was used to group children with regard to their IgE levels. Health data were prospectively collected using standardised questionnaires and health examination. Associations between sensitisation patterns and doctor-diagnosed allergic diseases at age 8/9 years were studied using logistic regression models.
Burnout is a mental disorder that leads to difficulties for the entrepreneur in controlling his or her personal and professional life. The most common consequences of entrepreneurial burnout include the subject experiencing low motivation, low organizational commitment, loss of energy, demoralization in connection with their work, poor quality of work, feeling of failure, and the perception that his or her company is performing poorly. We used a sample of 157 Spanish entrepreneurs selected at random from the Iberian Balance Sheet Analysis System database. We employed the Spanish version of the Reflective Functioning Questionnaire to measure mentalizing and the Spanish version of the Maslach-Burnout Inventory-General Survey (MBI-GS) to measure burnout. This research showed that entrepreneurial burnout could be avoided in part if the entrepreneur achieved a good capacity for mentalizing.
Design and Procedure Data were collected through an online questionnaire using the collaborative software Google Forms. An email containing a brief explanation of the study's objectives was sent by the researchers, along with a link to the questionnaire. All procedures followed in this work were in accordance with the responsible committee's ethical standards on human experimentation (institutional and national) and with the Helsinki Declaration of 1975, as revised in 2000. Informed consent was the first question on the online questionnaire. It was not possible to continue completing the online questionnaire until informed consent was accepted. Two reminders were sent to increase the response rate: the first was sent 7 days after the initial email and the second was sent 15 days after the initial email.
Online selfreports have the same validity and reliability as those carried out conventionally  [32]. The sample needed for this study, calculated with the help of the G* Power v. 3. 1. 9. 2  [33] , taking into account an effect size (f 2 ) of 0. 15 and a statistical significance level of 0. 05, was 138 observations  [34]. The entrepreneurs were randomly selected from companies in the Iberian Balance Sheet Analysis System database that met the inclusion criteria. The participants were volunteers. They were surveyed twice in 2019. In June 2019 (T1), the data collected was related to mentalizing. In September 2019 (T2), the data obtained was on burnout. This was done to avoid common method variance. Of the 1100 online questionnaires sent out on T1, 231 returned useable questionnaires (21%). Of the 231 questionnaires sent out on T2, 160 were returned, although 3 were discarded as they were incomplete (response rate = 69.
Data Analysis We used hierarchical linear regression analysis to determine the role of mentalizing factors in explaining each of the dimensions of burnout. In these analyses, the dimensions of burnout (professional efficacy, cynicism, and emotional exhaustion) were the outcome variables, and the explanatory variables were the two dimensions of mentalizing (hypermentalizing and hypomentalizing). The three models' validity was evaluated according to the R 2 , the corrected R 2, and the F-test of statistical significance. All analyses were performed with the SPSS Statistics software, version 26. 0  [35]. Before the online questionnaires were sent, a preliminary investigation was carried out with 35 entrepreneurs who lived in the same region as the researchers. All of them decided to participate voluntarily.
Background: This paper reports the construction and use of a specific method for qualitative medical research: The Inductive Process to Analyze the Structure of lived Experience (IPSE), an inductive and phenomenological approach designed to gain the closest access possible to the patients' experience and to produce concrete recommendations for improving care. This paper describes this innovative method. Methods: IPSE has five steps: 1) set up a research group, 2) ensure the originality of the research, 3) organize recruitment and sampling intended to optimize exemplarity, 4) collect data that enable entry into the subjects' experience, and 5) analyze the data. This final stage is composed of one individual descriptive phase, followed by two group phases: i) structure the experience, and ii) translate the findings into concrete proposals that make a difference in care.
The IPSE inductive approach does not, however, imply disregarding either practical or theoretical medical knowledge when formulating research questions and objectives. The starting point of an IPSE study is always an unanswered question about the experience of individuals involved in medical care, unanswered questions by experienced physicians specializing in the topic. These specialized physicians are part of the research group and contribute to all the stages, including the definition of the areas to be explore in the data collection procedure. However, in line with the grounded theory approach  [12] , the physicians are not to share their knowledge with the qualitative researchers conducting interviews and analyzing data. A qualitative researcher is his or her own instrument  [53]  and his or her preexisting knowledge and preconceptions (i.
Stage 1: setting up a research group The research group always includes two physicians specializing in the topic, generally three researchers with expertise in qualitative methods, and, when possible one or two patients who experience the phenomenon under study. In total an IPSE research group ideally contains five to seven members. This number is necessary to ensure that the study is rigorous and trustworthy. -The two physicians specializing in the topic are necessary because they both perform the systematic review (stage 2) and ground all the research process into practical and theoretical medical knowledge without impeding the inductive process. -The three qualitative researchers collect the data (stage 4) and analyze it (stage 5, descriptive individual phase). We consider that three are necessary to avoid confining the data collected and analyzed in the sole perspective of one researcher, or confronting only two opposing points of view.