dataesr/scientific-paragraphs-categorization huggingface dataset:
What About Bridge Employment in Belgium? Bridge employment was at the centre of the reforms carried out in 2015 when the Belgian government took measures to facilitate and encourage the maintenance of a complementary activity beyond the legal retirement age. Data analysed in this chapter were collected before these measures were implemented. Based on the results presented in the previous section, the hypothesis is that the measures taken in 2015 did not correspond to an aspiration of the workers. The hypothesis can be verified from the number of workers retaining a complementary activity (within the limits provided for by law in 2008) after retirement. The higher this number, the more significant the bridge employment will be. The very low number of workers involved in the labour market after retirement threshold has confirmed this hypothesis: only 12 out of the 1498 people in the sample kept a complementary activity after the statutory retirement age.
, 2020; Van Regenmortel et al. , 2018) , so the SocExc 1 is probably a more consensual measure of SE. The SE indexes, by construction, vary within the interval 0 and 4, being 4 the maximum of SE. Table  11. 2 presents the description of each domain used to construct the SE indexes. Table  11. A2 gives the descriptive statistics of the variables included in each domain revealing the diversity of values. With few exceptions, the values generally remain stable from one year to the other, or have small changes (last column of Table  11. A2). The empirical analysis has two parts. Firstly, following the methodology of  Macleod et al. (2019) , the SE Indexes are built, using data for the birth cohort  1945-1953, for 2002 and 2018. Next, we examine the evolution across time for the same birth cohort, by main activity and by gender.
Eurostat. (2018). Employment rate of older workers, age group 55-64. Retrieved June 7, 2021, from https://ec. europa. eu/eurostat/web/products-datasets/product?code=tesem050 Finnish Government. (2019). Programme of Prime Minister Sanna Marin's Government 10 December 2019. Inclusive and competent Finland -A socially, economically and ecologically sustainable society. Publications of the Finnish Government 2019:33. Helsinki. Retrieved June 7, 2021, from http://urn. fi/ URN:ISBN:978-952-287-811-3. Finnish Government. (2021). Hallituksen esitys 55 vuotta täyttäneiden työllisyysasteen nostamista koskevaksi lainsäädännöksi lausunnolle. Press release 360/2021. Retrieved November 30, 2021, from https://valtioneuvosto. fi/-/1271139/hallituksen-esitys-55-vuotta-tayttaneidentyollisyysasteen-nostamista-koskevaksi-lainsaadannoksi-lausunnolle Forma, P.
Acknowledgements This book is based on work from  COST Action IS1409  'Gender and health impacts of policies extending working life in western countries', supported by  COST (European Cooperation in Science and Technology). vii Acknowledgements Á. N. L. gratefully acknowledges the generosity of the women and men who agreed to be interviewed for this project, and those who helped her recruit individual research participants. The research on which this paper is based was supported by a  Marie Curie International Outgoing Fellowship  within the 7th European Community Framework Programme. This article is also based on work from  COST Action IS1409 , supported by  COST (European Cooperation in Science and Technology). Funding from the  State University of New York College of Arts and Sciences  enabled the authors to collaborate on the paper.
61. 9 with a standard deviation of 5. 2. For women, we find a mean of 59. 9 with a standard deviation of 3. 3. 6 Actual retirement ages in Austria at the time of the survey were 61. 6 in the case of men and 59. 1 in the case of women (data from Pensionsversicherungsanstalt for 2015). 7 According to data from Round 5 of the European Social Survey fielded in 2010/2011, the mean preferred retirement age among German men aged 45 and above was 61. 7 and the mean preferred retirement age of German women age 45 and above was 60. 9 (Hofäcker, 2015).
071) but was significantly elevated at days 30 (sham 11. 60 ± 1. 33, mTBI 13. 20 ± 0. 99, p = 0. 009) and 190 (sham 11. 52 ± 1. 11, mTBI 12. 84 ± 1. 39, p = 0. 026; Figure  4F ). To explore early cardiac molecular changes, we performed a Western blot analysis on tissue from sham (n = 6) and mTBI animals (n = 6) 1 month post-mTBI. We assessed Total p38 mitogenactivated protein kinases (T-p38 MAPK) and cardiac Troponin I (TnI) expression (Figure  4G ). Complete Western blot analyses are provided in supplemental Figure  S4A-C. Our results show that mTBI mice exhibit an increase in T-p38 MAPK cardiac expression (p = 0. 039) and a decrease in cardiac TnI (sham = 1. 74 ± 0. 32, mTBI = 1. 12 ± 0. 28, p = 0. 005; Figure  4H, I ). Collectively, these data show that mTBI in juvenile mice induces a diastolic dysfunction with a molecular signature persisting into adulthood.
| Early post-mTBI neurovascular oxygenation correlates with long-term cardiac dysfunction Thus far, our results show cerebrovascular and cardiac response maladaptations post-mTBI, occurring in a timedependent and mouse-specific manner. Here, we asked whether direct correlations exist between the examined pathophysiological measures to define prognostic criteria. To this end, we correlated the dataset: Oxygen saturation 4 h post-mTBI and long-term (240 days) peak strain, systolic, early diastolic, and late diastolic strain rate from the dobutamine stress test (Figure  6A-D ). Left hemisphere tissue sO 2 correlated with changes in peak strain (r = -0. 548, p = 0. 028) and with late diastolic strain rate (r = 0. 550, p = 0. 027) (Figure  6A, D ). Left hemisphere tissue sO 2 was correlated with the changes in systolic (p = 0.
Here, a principal component analysis was executed to reduce the dimensionality of multivariate datasets and identify underlying patterns. 34 Our results show that combining 13 physiologic measurements from the initial injury and the dobutamine stress test successfully differentiates between sham and mTBI. Hemoglobin was important contributor to the differentiation between groups; however, measures of cardiac dysfunction had a larger influence on the analysis than oxygen saturation. These results align with previous work where PCA has been used to discriminate between clinically stratified groups and identify treatment approach factors. 35, 36 Thus, PCA can distinguish between groups and identify underlying variables that may be important in the clinical management of patients with TBI.
11 Photoacoustic brain imaging was acquired 4 h post-injury, and as 7, 30, 90, and 240 days post-injury (Figure  1A, B ). Corresponding assessments of cardiac function were made at 1, 30, 90, and 190 days post-injury using two-dimensional ultrasound. Additionally, 4DUS data were acquired at days 7, 30, 90, and 190 post-injury to assess spatially specific cardiac function (Figure  1B ). During the dobutamine stress test on day 240 post-injury, both 4DUS and photoacoustic imaging was performed to assess cardiac function and oxygenation, respectively. One-year post-injury, a behavioral evaluation was performed as described below. Of note, one mouse in each group deceased before day 30 and was excluded from the analysis. During the dobutamine stress test, dosing and experimental optimization, reduced sample sizes to sham n = 9 and mTBI n = 7 for the remaining time points.
| Ultrasound imaging High-resolution 2D and 4DUS data were obtained using the Vevo 3100 high-frequency ultrasound system (FUJIFILM VisualSonics) with a 40-MHz center frequency MX550D probe to assess left ventricular function. Mice were anesthetized with 2. 5%-3% isoflurane at 2. 0 ml/min, and the body temperature was controlled with a heating pad. We secured the mice to a stage for imaging, and the ventral thorax hair was removed. The ECG and respiratory rate were monitored throughout the imaging process. We performed 2D echocardiography following the American Physiological Society guidelines for cardiac measurements in mice. 46 The longitudinal strain was analyzed in the parasternal long-axis (PLAX) view. We obtained a four-chamber view in B-mode to evaluate diastolic dysfunction using IVRT and SrE (2D strain rate at early diastole) in conjunction with LA volume based on 4D data.
20 All three measurements give insights into the filling and relaxation of the heart. Offline image analysis was conducted in Vevo Lab Software 5. 5. 1. (FUJIFILM VisualSonics). For 4DUS, the probe was attached to a linear step motor scanning in the parasternal short-axis (PSAX) view from below the apex to above the aortic arch. Acquisition parameters were set to a gain of 48 dB, 3D range of 12 mm, 3D step size of 0. 08 mm, and frame rate of 300 frames/sec. Each image acquisition required 10-15 min to create 4D data throughout one representative cardiac cycle from base to apex. We analyzed the 4D datasets in a custom, interactive toolbox in MATLAB 2021a (MathWorks, Inc. ).
| Four-dimensional ultrasound data strain analysis We conducted the strain analysis using a 4D Strain Toolbox. This custom software enables the visualization and quantification of 4DUS data to produce a 3D strain map over an entire cardiac cycle. 48, 49 We first oriented the 4D images and centered them to PLAX, SAX, and coronal views of the left ventricle. Endocardial boundaries were set at peak systole and diastole for the apex and base. Then, we added automated endo-and epicardial contours to the images based on initial estimates. We manually adjusted the contours over the cardiac cycle using four SAX planes and three PLAX planes. Next, the software created a 4D mesh of the contours from which measurements of global cardiac function (e. g. , ejection fraction, stroke volume) and regional function (strain, volume) can be extracted.
| Western blot analysis To assess early cardiac biochemistry changes, we used a Simple Western™ Automated Western Blot Systems as previously described  50  to detect total p38 MAPK and cardiac TnI expression level in both sham (n = 6) and mTBI (n = 6) mice 30 days after mTBI. Based on capillary electrophoresis, a Simple Western is a reinvention of the Western blot technique allowing for the complete automation of steps from protein loading to quantitative data analysis. 51 Briefly, 1-month post-mTBI, animals were euthanized. Cardiac tissue samples were collected and prepared for Western blot. Cardiac protein lysate was mixed with a fluorescent mix before heating at 95°C for 5 min. Total protein normalization agent, blocking reagent, 3 μl of protein mix, wash buffer, primary antibody, secondary HRP (ready to use "detection module," DM-001), and a chemiluminescent substrate were added into designated wells in a microplate.
We used T-p38 MAPK antibody (cst#9218; Cell Technology) and TnI (cst#4002; Cell Signaling Technology). Once loaded into the instrument, the protein mix was drawn into individual capillaries on a manufacturer 25 capillary cassette (12-230 kDA or 66-440 kDA). Quantification of chemiluminescence was based on peak height after correction for a baseline signal. Raw data were generated and analyzed by Compass software.
All data are shown as mean ± standard (SD). All statistical analysis was performed using Prism 9. 3 (GraphPad Software). The correlation coefficients, r, and corresponding p-values are displayed. A receiver operating characteristic (ROC) analysis was performed to evaluate acute photoacoustic and long-term echocardiographic biomarkers to discriminate between sham and mTBI animals. Acute photoacoustic biomarkers include left hemisphere blood sO 2 , tissue sO 2 , and mean HbT in sham (n = 11) and mTBI (n = 11) mice 4 h post-TBI. Long-term echocardiography markers include the changes in strain and strain rates from the dobutamine stress test 250 days post-mTBI. A 95% confidence interval with a hybrid Wilson/Brown method were employed during this analysis and the area under the curve (AUC) was computed to determine the model's ability to distinguish between the groups at various thresholds.
ACKNOWLEDGMENTS We gratefully thank the staff for animal housing (PhyMedExp) and  Imagerie du Petit Animal de Montpellier (IPAM)  for accessing high-resolution ultrasound and photoacoustic imaging. ( LRQA Iso9001; France Life Imaging  (grant  ANR-11-INBS-0006 ); IBISA;  Leducq Foundation (RETP) ,  I-Site Muse ). We acknowledge the technical support provided by the We-Met Biochemistry platform (I2MC, Toulouse; info@we-met. fr).
In terms of applications, the GSPs are submicronic bright and photostable sources that could be used for example for lighting. More fundamentally, the inhibition of FRET, which is an incoherent energy transfer process, opens the possibility to achieve coherent interactions between NCs that could enable to achieve quantum collective emission regime such as superradiance. Funding. Agence Nationale de la Recherche (GYN project ANR-17-CE24-0046). Disclosures. The authors declare no conflicts of interest. Data Availability. Data underlying the results presented in this paper are not publicly available at this time but may be obtained from the authors upon reasonable request.
Pharmachild Pharmachild was set up in 2011 with the primary aim of studying safety and effectiveness of drug therapies in JIA. Pharmachild collects demographic, clinical and laboratory data of JIA patients from 85 Paediatric Rheumatology International Trials Organisation (PRINTO) medical centers from 31 countries across the globe  [18]. Inclusion criteria are JIA classified according to ILAR criteria while under treatment or previously treated with nonsteroidal anti-inflammatory drugs (NSAIDs), intra-articular corticosteroids, systemic corticosteroids, and/or conventional synthetic (cs-) or biological (b-) disease-modifying antirheumatic drugs (DMARD) as per physician decision. The registry consists of two cohorts. The first is a cohort of all included patients with retrospective information about drug exposure and adverse events (AEs) from disease onset until registration into Pharmachild.
Statistical analysis The retrospective and prospective Pharmachild cohorts were analyzed together. Patient characteristics were compared between patients with and without AITD using univariable logistic regression analyses. When the 95% confidence interval (CI) of the odds ratio (OR) did not contain 1, this was considered a statistically significant effect. All variables that differed statistically significant between AITD and non-AITD patients were considered for inclusion into a complete case multivariable logistic regression model in order to identify independent predictors of AITD. Predictors were selected using a stepwise backward procedure based on the Akaike's Information Criterion (AIC). This measure is used to select a model that best predicts the observed data while adding a penalty for the number of variables in the model  [21].
Predictors for AITD On multivariable analysis, a family history of AITD, female sex, ANA positivity and older age at JIA onset were independent predictors of AITD (Table  3 ). This model included 7345 patients and 82 AITD events due to 1620 patients with missing data. The model had good discriminatory power (AUC = 0. 71, 95% CI: 0. 65 -0. 78). Based on the data in Pharmachild, the number of female ANA positive JIA patients with a family history of AITD needed to screen to detect one case of AITD is 16. This number decreases with increasing age at JIA onset (Table  4 ).
Availability of data and materials All relevant data are reported in the article. Additional details can be provided by the corresponding author upon reasonable request. The Pharmachild registry is registered at Clinicaltrials. gov (NCT01399281) and at the European Network of Centres for Pharmacoepidemiology and Pharmacovigilance (ENCePP; http:// www. encepp. eu/ encepp/ viewR esour ce. htm? id= 19362).
g. , location of a vehicle, energy consumption for a private flat). In a general manner, sensors provide real-time information on real world entities  [5]. In a systematical study, Hui et al. [6]  quantify IoT privacy leakages, by exploiting a mobile network traffic dataset. They conclude that privacy leaks cannot be neglected. End-users usually collect data to make a decision. These consumers generate queries to collect data of interest. These queries describe which data should be collected according to its descriptive metadata, e. g. , location, data type, and ownership. The metadata correspond to specific * Corresponding author. E-mail addresses: caminha@unistra. fr (R. C. J. Neto), merindol@unistra. fr (P. Mérindol), fabrice. theoleyre@cnrs. fr (F. Theoleyre). producers (sensors) that send their measurements to the consumers.
Local authorities may also rely on the same dataset for urban previsions, as well as handling road incidents. Similarly, speed measurements can be acquired by other sources, such as private vehicles and roadside sensors. The multiplicity of sources can improve the decision-making of consumers by diversifying available data. In the future, we envision infrastructures where distinct systems are owned and managed by different entities and disclose selected information to neighboring systems. In other words, each system encloses a domain that discloses selected information to other domains, allowing reuse of data in a controlled manner. Through a multi-domain infrastructure, consumers may query and collect data from producers in other networks and take advantage of data from different owners. By collecting data in such manner, domains enrich the data used by consumers, and both reduce the deployment costs and the amount of redundant devices  [10].
More complex statistical functions such as histograms and density functions also reveal the distribution of values of the samples, while still hiding individual measurements. They spare the network's and device's resources providing directly precomputed data to the consumers  [14]. Instead of sharing raw measurements, the system we envision to deploy share aggregated measurements. For instance, the location of a specific vehicle is kept private while the average speed of vehicles at a road segments can be exported. Obviously, to respect privacy, the collection of vehicles must be sufficiently large to make de-anonymization impractical. Such an aggregation would reach levels of privacy similar to a k-anonymous dataset (if  is the number of samples aggregated per segment). We argue that Named Data Networking (NDN)  [15]  seems to be a very attractive way to orchestrate such inter-domain communications.
The contributions of this paper are as follows: 1. We detail our publication algorithm: each border router selects the data it exports to peering domains, combining different sources of data to respect k-anonymity; 2. We propose a heuristic to merge the data of producers that present the highest similarity in their metadata. Indeed, identifying all possible combinations is intractable, and a border router publishes the most promising dataset; 3. We specify a subscription scheme to allow consumers to subscribe to different streams. In particular, it identifies non overlapping data-streams offered by its peers. Besides, it identifies only the metadata of interest; 4. We assess the performance of our aggregation-based approach compared with a centralized approach, which gives an upper bound. We analyze the performance of our algorithms to aggregate measurements, as well as the memory load and processing costs of our technique.
We are rather interested into data-stream aggregation in IoT networks. Time  [31]  and count  [32]  windows are generally applied in such cases  [33]. An aggregator node will collect measurements for anonymization until a given number of measurements has been collected or an amount of time has passed. Then, it will anonymize the set of measurements collected and transmit the result. While the former enforces k-anonymity, the latter imposes a maximum delay for anonymization. Similarly to k-anonymity, a set of field-structured data is differential if the removal/addition of any entry does not change the resulting value by more than   [34]. If a query is very restrictive (very selective metadata), more noise needs to be added since the number of involved values decreases. Differential privacy is particularly relevant for IoT  [35]  since a collection of Things shares data that should not be distinguishable.
g. , data hash) may also be used if the name of the data in question discloses too much information  [38]. When some data is required, consumers will issue an interest packet with the name of the requested data. Routers will take the name hierarchy created by name components to route packets with longest prefix match tables. In other words, NDN's Forwarding Information Base (FIB) has name prefixes instead of IP address prefixes. Then, NDN introduces the Pending Interest Table (PIT) to allow routers to forward data back to consumers without necessarily knowing the consumer's identity. This table stores the incoming connection of interests that are forwarded to other routers, which essentially stores the reverse path of interests in the network. Then, when routers find the data packet with the requested name, they use the PIT entries to forward data back to consumers.
NDN has also been extended to support aggregation and in-network processing for IoT. Tschudin et al. [40]  proposed Named Function Networking which added support for lambda expressions which are directly evaluated by routers. Besides, functions may be acquired and cached like named data. The aggregation function to apply is directly specified in the name of the data of interest. In turn, Krol et al. [41]  propose to implement named functions as lightweight virtual machines. These virtual machines support complex code that routers execute before forwarding data packets. Krol et al. propose to execute these virtual machines at routers based on three criteria: (i) how frequently they receive interests packets for them (popularity); (ii) compute delay sensitive computations as close as possible to consumers; (iii) compute bandwidth hungry applications as close as possible to producers.
Within these boundaries, any device can freely exchange data generated locally. In particular, data can be exploited by any application part of this domain. Thus, we do not have any privacy issue when data transits within a domain; a border router forwards data among domains. It enforces the privacy policies when exporting data to peering border routers, in neighboring domains. More precisely, it transmits its available data to peering border routers; a dataset defines a data-stream that can be exported, described by its metadata. Metadata are descriptive attributes that characterize dataset (e. g. , geolocation, type of measurements). We will later see that this also includes the list of producers that are used to construct the dataset; an offer announces a dataset that can be shared with peering border routers.
It is defined by the associated producers, their metadata, and its privacy requirement. It is similar to NDN advertisements, but differs slightly for the subscription phase: a consumer selects a subset of the dataset in an offer. This subset has to respect the privacy requirements of producers in the dataset offered; a producer is a device (aka. sensor) that generates data-streams. A data-stream corresponds to a time-series of measurements. We also denote a domain that exports data of its producers as a producer domain; a subscriber is a device that consumes data-streams. More precisely, it constructs a query that specifies its interest, which is transmitted to its border router. Then, our overlay handles the subscription to the data-streams of interest, i. e. , that match the query; a broker is a specific border router that collects several datastreams.