dataesr/scientific-paragraphs-categorization huggingface dataset:
Moreover, it is recommended that the AAAM10 tool is adapted to better-fit European needs. Other tools -ICDmap90, DGT, and AAAM9result in an underestimation of MAIS3 + casualties between 3% and 10%. Including less than 4 injuries when determining MAIS results leads to an underestimation in serious injuries. On average, taking into account only 1 injury results in an estimated number of MAIS3 + casualties which is 78% of the number that is estimated on the basis of all injuries. When 2 injuries are taken into account, 90% of the serious road injuries are identified and when 3 injuries are taken into account, on average 95% of the number of MAIS3 + casualties are identified. This study has a number of limitations. In general, most results are based on data from only a few countries so are likely not to be representative of all countries, particularly those that differ in motorisation and share of modes of transport.
Acknowledgments Working group of WP7  SafetyCube  project: Pérez, K. , Olabarria, M. ( ASPB, Agència de Salut Pública de Barcelona ), Spain; Weijermars, W. , Bos, N. ( SWOV Institute for Road Safety Research), Netherlands; Machata, K. , Bauer, R. (KFV, Austrian Road Safety Board ), Austria; Amoros, E. , Martin, JL. , Pascal, L. ( IFSTTAR, French Institute of Science and Technology for Transport, development and Networks ), France; Filtness,  A. ( LOUGH, Loughborough University ), United Kingdom; Dupont, E. , Nuyttens, N. , Van den Berghe, W. (Vias institute); Johannsen, H. ( MHH, Medical University of Hannover ), Germany; Leskovsek, B. (AVP, Slovenian Traffic Safety Agency), Slovenia. We thank  Laurie Brown  from  Loughborough University  for reviewing the manuscript.
Study design and data source We conducted a retrospective cohort study in the Permanent Sample of Beneficiaries (Echantillon Généraliste des Bénéficiaires, EGB). The EGB, set up in 2005, is a permanent, representative, and open national random sample of 1/97th of persons currently affiliated with one of the three major national health insurance funds in France  [13]. At the time of extraction (August 2017), it included 804,089 beneficiaries. For this study, we extracted data for salaried workers (including those who are retired) only (about 86% of the French population  [13] , covered by the French National Health Insurance Fund, NHIF) because people affiliated with the other insurance funds were only included in the EGB in 2011. Data include age, gender, district of residence, reimbursement claims for consultations with private healthcare professionals, medical procedures (e.
Seasonal influenza vaccine uptake For each individual and each SIV season n/n + 1 (temporal statistical units in our analyses), we constructed a binary variable "SIV uptake" (yes, no), based on SIV deliveries (Additional file 2: Table  S2 ) recorded between September 1 of year n and March 31 of year n + 1. Each SIV delivered in a community pharmacy is recorded in the NHIF database.
Using this methodology, we were able to model attrition probabilities (mortality represented the vast majority of attrition in our study) jointly with the estimation of SIV trajectories. The demographic, clinical, and healthcare utilization factors were added to the model as predictors of trajectory group membership. This joint estimation of trajectories and predictors of the probability of group membership allowed us to take into account the uncertainty in participants' trajectory group membership  [15]. We used Zhang's correction to estimate adjusted risk ratios from the estimated ratios  [22]. All statistical analyses were performed with SAS statistical software, version 9. 4 (SAS Institute Inc. , Cary, NC). GBT analyses were conducted with the TRAJ procedure  [16].
Nonetheless, not all patients with diabetes (especially those with diabetes other than type 1) receive the voucher, because some who should have LTI status do not apply for it We acknowledge some limitations. Vaccinations that took place during occupational medicine visits or at vaccination centres or some nursing homes that buy vaccines for their residents (fewer than 20% of all nursing homes  [24] ) are not recorded in the French NHIF databases. However, these limitations are unlikely to affect our results substantially as the vast majority of vaccinations in France are administered by private healthcare workers and are thus recorded in these databases  [25]. As SIV behaviour varies by socioeconomic characteristics  [26] , our results cannot be extrapolated to population categories not covered by the NHIF (e.
g. , farmers, the selfemployed) or the very few people without insurance; nonetheless, the NHIF covers 86% of the French population. Several socioeconomic (e. g. , educational level) and clinical (e. g. , diabetes complications) characteristics are not recorded in NHIF databases and therefore could not be studied. Specifically, no data about individuals' knowledge, attitudes or perceptions towards SIV (e. g. , beliefs about SIV efficacy, side effects) were available, although they are important drivers of SIV behaviours  [27, 28]  and thus probably differ according to trajectories.
Funding This study was conducted with the financial support of the  Institut de Recherche en Santé Publique (IReSP)  as part of its 2014 general call for research projects (convention no. AAP-2015-03 ). This study was also supported by the  Institut Hospitalo-Universitaire (IHU) Méditerranée Infection , the  National Research Agency  under the program « Investissements d'avenir », reference  ANR-10-IAHU-03 , the  Région Provence Alpes Côte d'Azur and European funding FEDER PRIMI.
Acknowledgments. Work partially supported by the  Autonomous Region of Madrid  (grant " MOSI-AGIL-CM " ( S2013/ICE-3019 ) co-funded by  EU Structural Funds FSE and FEDER) , project " SURF " ( TIN2015-65515-C4-4-R (MINECO/FEDER) ) funded by the  Spanish Ministry of Economy and Competitiveness , and through the  Excellence Research Group   GES2ME (Ref. 30VCPIGI05 ) co-funded by  URJC-Santander Bank.
6 mm × 100 mm and a 3. 5-μm particle size). The mobile phase A contained 95% (vol/vol) water, 5% (vol/vol) acetonitrile, 20 mmol/L ammonium hydroxide, 20 mmol/L ammonium acetate, pH 9. 0; B was 100% acetonitrile. The gradient was as follows: 0 minutes, 15% A; 2. 5 minutes, 30% A; 7 minutes, 43% A; 16 minutes, 62% A; 16-18 minutes, 75% A; 18-25 minutes, 15% A with a flow rate of 400 μL/ minute. The capillary of the ESI source was set to 275°C, with sheath gas at 45 arbitrary units, auxiliary gas at 5 arbitrary units and the spray voltage at 4. 0 kV. In positive/negative polarity switching mode, an m/z scan range from 70 to 850 was chosen and MS1 data was collected at a resolution of 70,000. The automatic gain control target was set at 1 × 10 6 and the maximum injection time was 200 ms. The top 5 precursor ions were subsequently fragmented, in a data-dependent manner, using the higher energy collisional dissociation cell set to 30% normalized collision energy in MS2 at a resolution power of 17,500.
Bioinformatic analysis The Cancer Genome Atlas (TCGA) data for Prostate Adenovarcinoma (PRAD) were downloaded from the TCGA data portal (https://portal. gdc. cancer. gov). RNA-seq data were normalized using the Bioconductor package DESeq2. Expression levels of the following genes were evaluated in these patient datasets: PPARGC1A (PGC1α), MYC (c-MYC), AMACR, and ODC1. We compared the expression levels of each individual gene in primary tumors and in a reference population (patients without prostate tumors or metastasis). For TCGA data, we compared the PPARGC1A gene expression levels in tumor samples, distinguished by the Gleason grade. P values were calculated by the Wilcoxon rank sum test.
The silencing of ERRα had no effect on c-MYC expression in shCT cells, but it inhibited the expression of c-MYC induced by the knockdown of PGC1α in LNCaP and DU145 (Fig. 2D ). To confirm the involvement of ERRα in the regulation of c-MYC, we performed a ChIP with ERRα antibodies and a quantitative PCR with the putative binding site of ERRα in the promoter region of c-MYC and TAPBPL as a control  (21). As expected, ERRα occupied the promoter region of TAPBPL, but the downregulation of PGC1α did not increase its recruitment (Fig. 2E ). On contrary, the downregulation of PGC1α significantly increased the recruitment of ERRα on the promoter region of c-Myc. In addition, analysis of the publicly available ChIP-seq data revealed that ERRα is one the regulatory transcription factor of c-MYC in several databases (Supplementary Fig.
On the basis of the TCGA-PRAD database (healthy tissue: n = 52 and primary tumors: n = 498), we constructed a heatmap to visualize the coexpression pattern of the PGC1α/c-MYC/ ODC1 axis genes in normal and tumoral tissues with increasing Gleason grades. PGC1α expression is high in normal tissues and gradually decreases with elevated Gleason scores. In contrast, the expression of ODC1 and c-MYC is low in normal tissue and increased with Gleason grade (Fig. 5B ). To confirm this observation, we performed a correlative analysis using the same database. We observed a weak but significant correlation between PGC1α and ODC1 expression as well as PGC1α and c-MYC in prostate cancer tumors and normal tissue with r = 0. 30 (P = 2. 9 × 10 -13 ) and r = 0. 24 (P = 6. 48 × 10 -9 ), respectively (Fig. 5C ).
We then analyzed the Taylor and colleagues dataset that includes healthy tissues (n = 29), primary tumors (n = 131), and metastasis (n = 19; ref. 25). ODC1 and C-MYC are significantly increased in metastasis and the primary tumor compared with the healthy tissue and PGC1α is dowregulated in the tumor and the metastasis (Supplementary Fig. S5A ). Finally, in accordance with our results and other studies, high expression of ODC1 (P = 0. 0146; Fig. 5D ) and low expression or PGC1α (8) are significantly correlated with progression-free survival. Taken together, our data demonstrate that the low expression of PGC1α is associated with high expression of c-MYC and ODC1 in patients with prostate cancer. It provides evidence that the PGC1α/c-MYC/ODC1 axis defines a gene signature that may have a prognostic value for aggressive prostate cancer and may also be the target of future therapies.
Discussion We demonstrate here that the transcriptional coactivator, PGC1α, is one of the regulators of an onco-metabolic program regulating prostate cancer cell aggressiveness. The downregulation of PGC1α makes prostate cancer cells dependent on the polyamine pathway to promote metastasis. Indeed, the decrease of PGC1α induces the upregulation of c-MYC and ODC1, the rate-limiting enzyme of polyamine synthesis. Both the bioinformatic analysis of a prostate cancer dataset and our results on human biopsies demonstrate that low expression of PGC1α correlates with higher levels of c-MYC and ODC1 in tumors. In addition, we demonstrate, based on the analysis of public databases, that high expression of ODC1 is associated with a lower PFS. Thus, our results highlight the importance of the PGC1α/c-MYC/ODC1 axis as a potential prognostic marker of prostate cancer aggressiveness.
Acknowledgments We thank  Charlotte Hinault  for carefully reading the manuscript. This work was supported by a grant from the  Fondation ARC pour la recherche sur le Cancer , l' Association pour la Recherche sur les Tumeurs de la Prostate (ARTP), ITMO-Cancer. This work has been supported by the  French government , through the  UCAJEDI Investments  in the  Future  project managed by the  National Research Agency (ANR)  with the reference number  ANR-15-IDEX-01. L. Kaminski is supported by the  French Ministry of Research. S. Torrino  has a grant from the  Fondation de France. R. Haider  and  E. Jaune  were supported by the foundation  ARC  and  F. -R. Roustan  by the  CHU of Nice. I. Ben-Sahra  is supported by the  NIH   R00-CA194192  and  LAM Foundation  grants. F. Bost ,  N. M. Mazure , and  J.
Bribery without theft requires the bribe payer to pay the ocial an additional amount in excess of the ocial price in order to access a particular public service. This type of bribe is said to be coercive. Shleifer and Vishny (1993)  suggest that "corruption with theft aligns the interests of the buyers and sellers" and consequently "it will be more persistent than corruption without theft, which pits buyers against sellers. " In this paper, we use rich data from a survey on informal cross-border trade (ICBT) in West Africa to study the frequency and level of bribes paid by traders during their journey to the border. We rst examine whether bribes are widespread. We then study the determinants of the bribes to understand which factors depress or increase the price of bribes. We exploit cross-sectional variations in trade regimes and products, as well as changes in trade barriers over time, to identify their impact on bribes.
We also exploit precise information on transport modes, on the location of traders' starting and arrival points and of border crossing points, and on the alternative routes a trader may use. Because of the dearth of data regarding bribery, only a handful of empirical papers have tried to break down the mechanisms at play when bribes are paid. Most existing studies have examined the trade and transport sectors, where bribery is particularly pervasive  (Lavallée and Roubaud, 2018). Sequeira (2016)  uses data from an audit study of large shipments imported by formal rms into South Africa, with direct data on bribe payments at the border. She nds that bribes paid to customs agents decreased when taris were reduced, with some evidence of a shift from collusive to coercive bribery. Sequeira and Djankov (2014)  link a dataset of bribes paid at ports in South Africa and Mozambique to data on formal importers.
, 2018). In January 2010, the 150 points were surveyed over a 7-consecutive-day period by a team of 225 surveyors, 12 controllers, and 6 supervisors. In 2011, the operation was repeated, with the 171 points surveyed over 10 consecutive days (employing 350 surveyors, 30 controllers, and 12 supervisors). A four-page questionnaire was completed by surveyors and traders. Information on the nature, quantity, and value of goods transported, the origin and destination of the shipments, and the transport mode was collected. In 2011, a total of 8,883 questionnaires were completed (5,173 in 2010)  (INSAE, 2011). After data cleaning, 8,610 observations from 2011 were retained for analysis (5,045 in 2010). The unit of observation is a trader's crossing. Most traders were surveyed only once, although it is possible that traders crossing several times during the survey period could have been interviewed more than once.
Sample statistics Table  5  displays descriptive statistics for our estimation sample. The distribution of the size of shipments is skewed, with many small-scale shipments and a few large ones. This reects the high diversity of our data in terms of trader types and transport modes. Distance measures the road distance between a shipment's market of origin and the border crossing point where the survey took place. We used data from the Google maps API on driving and walking itineraries between each pair of locations. The walking itinerary reports the shortest route on secondary/bush roads available in the application. It is therefore relevant for both pedestrians and motorcycles, and is shorter than the driving route in most cases. 15 We applied the driving distance to traders using cars and trucks.
26 To the best of our knowledge, however, there are no systematic quantitative data studies of dierences in treatment between male and female traders with respect to bribe payments. Our data allow us to test whether bribes paid by female traders dier systematically from those paid by men with otherwise similar observable characteristicsgoods and quantities traded, transport modes, distance traveled. To do this, however, we have to rely on the 2011 survey data, as information on individuals' sex is only available in that dataset. Our results are shown in Table  10. Traders' sex is not associated with any signicant dierence for the sample as a whole (columns 1-3). When focusing on pedestrians only, it appears that women do pay signicantly more than men  (col. 4-6). This eect is not signicant for the other transport modes in the data.
3, a rst attempt to address these issues involves verifying the consistency of the data with other sources of information on the composition of informal trade. Products known to be important in smuggling with Nigeria appear frequently in the data and show up among the top products by trade value recorded in the survey. This conrms that no major product appears to be missing from the data. Many of these products -such as rice, cars, and gasoline -are also the products that face the most stringent controls on smuggling with Nigeria. The survey thus managed to measure a signicant number of these trade activities, despite their high degree of illegality and risk. However, these qualitative assessments do not rule out the possibility of sample selection. To further probe the inuence that such selection may have on our results, we estimate our model excluding products with a high degree of illegality and risk.
In addition to the low objective response rate, the median PFS achieved by T-DM1 in patients with HER2 amp CTC compares unfavorably to that observed in patients with ≥ 1 CTC but no HER2 amp CTC. In our study, the use of T-DM1 allowed assessing the efficacy of "pure" anti-HER2 therapy in the setting of a single-arm phase 2 study, without any other antitumor therapy. A different approach, investigated in the DETECT III study (NCT01619111), is to measure whether adding an anti-HER2 agent to a chemotherapy backbone would benefit to HER2-negative MBC patients with HER2-positive CTC, assessed by immunocytofluorescence (design reviewed in  [28] ). Results of this randomized phase III study are awaited and will complete our current understanding of the clinical actionability of HER2 amp CTC in HER2-negative MBC patients.
The lack of synchronous metastatic tissue biopsy at time of treatment initiation also prevents us from comparing the HER2 amplification status between CTC and metastatic tissue. Recent preclinical experiments suggested that HER2-positive CTC retrieved from HER2negative MBC patients are more proliferative but not addicted to HER2 signaling  [14]. However, trastuzumabderuxtecan, a newer trastuzumab-drug conjugate, demonstrated an efficacy in some patients with HER2negative metastatic cancers  [29] ; this efficacy signal is now investigated in a phase 3 trial (NCT03734029).
To achieve this and to decrease the uncertainties on temperature measurements due the relative quality of integrated reference junction compensation provided by data acquisition manufacturers, the voltage provided by the thermocouples were directly measured using a 34970A data acquisition device equipped with a 34901A card (Agilent, Loveland, Colorado, USA). The cold junctions of the thermocouples were grouped in the same thermally insulated box and the reference junction temperature was measured in this box by two Pt-100 probes. Then, reference junction voltage were added and classic correlations were used to determined temperatures. The data acquisition system was then entirely calibrated to obtain an uncertainty for temperature measurements of less than ± 0. 01 ∘ C.
In our case, the temperature T 3 (t) measured experimentally in z = z 3 was used as one of the two boundary conditions of the problem and only the boundary heat flux q˙c t in z = z 0 remained unknown. Beck's sequential function specification method was chosen to solve this inverse heat transfer problem  (Özişik and Orlande, 2000). It was implemented using Matlab ® R2015a (The MathWorks, Natick, Massachussetts, USA). The principle of this method is to determine the function q t ˙( ) ct which minimises the differences between the experimental and calculated values of T 1 and T 2 evaluated respectively at distances z 1 and z 2 from the origin of the domain. The determined value of q t ˙( ) ct is then used to deduce the value of the temperature of the heating surface at z = z 0 denoted in our study by T HS (t).
The value of 10 W⋅m -2 ⋅K -1 has been calculated with a surface temperature equal to ≈50 ∘ C by the correlation provided by  Incropera et al. (2007)  and assuming that this temperature is of the same order of magnitude as the one reached by the upper surface of the product at the end of the heating test. The system of partial differential equations constituted by equation (3) to equation (  5 ) was solved using COMSOL Multiphysics ® v. 5. 0 software (COMSOL AN, Stockholm, Sweden) in a quarter 3D-geometry piece of meat considering two planes of symmetry within the parallelepiped. The modelled domain was meshed into 63021 free tetrahedral elements. Model was solved by finite element method using backwards differentiation formula method. The absolute tolerance criteria on temperature was 0. 001 ∘ C.
Material properties and model parameters In equation (3), the density of the meat sample ρ was measured by weighing a fixed volume of minced meat and a value of 1125 kg⋅m -3 was found for this property. Values for meat sample thermal conductivity k and heat capacity Cp were identified by comparing the calculated and experimentally measured temperatures within the meat sample during heating. To achieve this, the sum of squared errors between the median temperature values measured in the three zones of the meat sample (see paragraph 2. 4) and the average temperature calculated by the model in the same three zones was calculated and minimised using the Nelder-Mead Simplex algorithm already programmed in the Matlab ® environment.
At 215 ∘ C and 255 ∘ C, this coefficient ranged from 500 at the start of the heating process down to 100 W⋅m -2 ⋅K -1 at the end of it. This result highlights the fact that, for the experimental range covered in this study, the modification of the product's lower surface during contact heating tends to lower the quality of heat exchange with the heating surface. Using the model developed here, it was also shown that the energy consumed by the vaporisation of the water exuding from the product during heating represented 55%, 67% and 65% of the total energy received by it during the tests at 128 ∘ C, 215 ∘ C and 255 ∘ C, respectively. The results also suggested that the level of heating temperature had Average surface temperatures calculated by COMSOL ® software according to section 3. 4. more effect on product moisture loss kinetics than on product temperature rise kinetics, this temperature rise being always limited by the vaporisation of water in the interstitial space between the product and the heating surface.
• As a by-product, we also developed a full experimental setup (with a dedicated transient signal acquisition device) to build our dataset of real transient signals corresponding to different electrical appliances. This dataset is used for our model validation as well as for the performance assessment of the proposed appliance identification method. The rest of the paper is organized as follows: Section 2. 1 describes the proposed data model, Section 2. 2 details the proposed parameter estimation algorithm, Section 3 gives the derivation of the parameters' CRBs, Section 4. 1 gives the assessment of the proposed model and algorithm on simulated and real data, Section 4. 2 shows the usefulness of the model parameters through an appliance classification example, and finally, Section 5 concludes the paper.