dataesr/scientific-paragraphs-categorization huggingface dataset:
Clinical practice Patients' background and admission data A total of 28 patients (39 episodes) were included in the one month survey of practice (1. 26 people/day required rapid tranquilisation). All were adults of Lebanese nationality. Most patients were male, in their early 30s, and presented with their families. In a few instances restraints were used before admission (7%) and people had already received some sort of medical intervention (10%) such as being restraint or given medication by family, friends or self before being presented to the hospital (Table  3 ). The male-only wards experienced a little higher frequency of agitated episodes but not crucially so (Table  4 ). Taken alone, bipolar disorder, was the most frequent single diagnosis (n=12) but the collective schizophrenia-like illness (schizophrenia, schizoaffective disorder, delusional disorder, brief psychotic episode) totalled 13 of the 39 episodes.
Sources of data In 2011, the ESTHER (Ensemble pour une SolidariteTherapeutique Hospitalière en Reseau) hospital partnership initiative has supported the implementation of ESOPE, an electronic medical software system used to monitor the care of people living with HIV, at several care sites in Africa, including the Dakar CTA. This software makes it easier to manage individual patients by creating electronic records of their data that can be easily accessed, searched or shared between treatment centers. ESOPE also provides a powerful means of evaluating HIV / AIDS treatment programs through the automated production of synthetic reports. As of 2012, medical records of all new CTA patients were entered into the software. At the same time, a retrospective entry of all the medical files since 1998 has been carried out, thus expanding the electronic database that can be used for evaluation.
Variables and definitions The data used in this analysis included patient age, sex, marital status, occupation, place of residence, body mass index (BMI), WHO clinical stage of infection, type of HIV, presence of tuberculosis, presence of HbS antigen. These data were recorded at entry. CD4 count at entry (first visit) and at all subsequent visits and date of initiation of ART were also used. Marital status at entry was recorded as single, married (polygamous or monogamous), widowed or divorced. Occupation at entry was classified as unemployed, self-employed or salaried job. Place of residence at entry was categorized in four regions (City of Dakar, Center, North, South-east). BMI was computed as weight/ height 2 (kg/m 2 ) and categorized according to WHO classification (underweight, <18. 5; normal, 18.
; • as CD4 count below 500 regardless of clinical criteria or as WHO stage 3 or 4 regardless of CD4 count from 2014 to 2015 in accordance with WHO guideline published September 30, 2013  [6]. Clinical conditions such as tuberculosis or hepatitis B co-infections, pregnancy were not taken into account to define eligibility in this analysis because these informations were not consistently recorded in the database. Four different time periods were defined according to Senegal's HIV care history and WHO ART eligibility expansions. Period 1 (P1), 1998-2003 which is characterized by the start of the Senegalese Initiative for Access to Antiretrovirals (ISAARV). During this time patients were expected to participate financially in their treatment (on the basis of a scale established after a socio-economic survey); and Period 2 (P2) 2004-2010; Period 3 (P3) 2011-2013 and Period 4 (P4) 2014-2015 based on WHO guidelines publication and ART eligibility expansions for the last two periods.
Statistical analysis Population characteristics and treatment modalities were compared by Chi-2 tests for categorical variables or by non-parametric variance analyzes (Kruskall-Wallis) for continuous variables. Factors associated with treatment initiation among eligible patients were identified using a Cox model that took into account the delay in initiating treatment from the date the subject is eligible. Patients who were not put on treatment during follow-up were censored at the date of the last follow-up visit to the center. The choice of the variables to include in the model was based on the literature and their availability in the ESOPE database. The interaction terms between the time periods and the different variables were tested in order to identify the covariates whose effects varied with time.
Population analyzed As of June 30, 2016, the ESOPE database had 4173 files associated with 51076 visits. We excluded a total of 522 patient files, corresponding to 70 duplicates, 141 outpatients, 36 patients under 15 years of age, 233 patients who were not ART naïve at the opening of the case, 39 patients with files opened between 30 December 2015 and 30 June 2016, and 3 cases for which no visits had been recorded. The population analyzed thus contains 3651 ART-naïve patients for whom a file was opened at CTA between 1998 and 2015 (Fig  1.
From period 2 until the end of the study period, the median CD4 counts increased slightly over time but remained low in the last period (2014-2015) with a median of 240 [97-398] cells/mm 3 and 45% of patients with CD4 count below 200 cells/mm 3. This means that most HIV-infected persons present to care at CD4 counts far below the applicable threshold at this time (i. e. <500 cells/mm 3 ). A meta analysis of 56 studies from Sub-Saharan Africa found no significant change in CD4 count at entry into care from 2002 to 2013, with a mean CD4 count of 309 cells/mm 3 (95% confidence interval, 237-381 cells/mm 3 ) in 2012  [16]. In 2018, an analysis of IeDEA and COHERE database including 951855 patients from 55 countries showed that median CD4 cell count at ART initiation increased in all countries with the smallest increase observed in West-African countries (118 to 186 cells/mm 3 )  [17].
Acknowledgments We thank all patients whose data were used in this study. We also acknowledge the staff from the  CTA  who contributed to recording and entering data and  Abdou Gueye  for his support in data analysis. We thank the  French GIP ESTHER  and the  CNLS (Conseil National de Lutte contre le Sida) in Senegal  for their technical and financial support in implementing the ESOPE computerized medical files system.
There, we assessed the frequency and variability of physical exposures to NHPs, critical factors affecting risk of zoonotic pathogen exposure. We moved beyond identification of at-risk populations to evaluate contact frequency with NHPs by contact type and gender; the influence of NHP ecologies on the frequency of human physical contact with NHPs; and the proportion and condition of NHP meat circulating in local and regional markets. Methods included a regional and longitudinal wild meat survey; a multi-village questionnaire; a 10-month, longitudinal participatory quantitative study among village inhabitants with daily data on their forest activities and NHP contacts; semi-structured individual and group interviews; participant-observations of forestbased activities; and a transect-based survey for an NHP census.
Participatory longitudinal quantitative methodology We developed an original participatory quantitative data collection tool to evaluate physical contacts with NHPs at a granular level. In one target village, we recruited participants ("volunteers") for a 10-month study (April 2016-January 2017). Inclusion criteria were any adult (>21 years-old), able to read and write, and residing in the study village. Each volunteer was trained to fill out a datasheet each day, documenting any NHP contact (injuries, hunting, selling/purchasing, butchering, cooking, eating) by species. VN trained and monitored volunteers' data collection through two full days of participant-observations and frequent meetings with each participant. Of 22 volunteers recruited, 18 were included in the final dataset (8 women, 10 men).
Multi-village questionnaire To evaluate human activities and physical contacts with NHPs in the target and three neighboring villages along the major regional road, we conducted a questionnaire with 449 participants in May 2017. We developed our questionnaire after conducting preliminary analyses of our participatory quantitative tool, interviews, and participant-observations to elaborate a more accurate, locally appropriate data collection tool. In each village, we stratified the number of questionnaires with regional estimates of village populations. Sixteen local assistants conducted data collection by randomly selecting households and proposing the questionnaire to each adult present. Questionnaires gathered socio-demographic data, self-reported type of physical contact with each NHP species.
We circumvented recall problems by asking subjects to estimate whether they had physical contact in the previous day, week, month, year, or more than one year. We coded data as the presence/absence of a specific NHP contact and as the estimated frequency. To do so, we calculated the inverse of the estimated number of days � 100 (0 = never; 0. 1 if >1 year ago; 0. 3 within the past year; 3 within the past month; 14 within the past week, and 100 within the past day).
Data analyses Analyses by gender of proportion of population exposed and mean frequency of contact. For each type of contact and each NHP species (including general categories "ape", "monkey" and "all species), we calculated for men, women and in total, both the proportion of the population exposed at least once and the mean frequency of contact. We used the two independent datasets, one based on the open-ended responses of selected volunteers in our participatory longitudinal quantitative survey, the other on the larger sample assessed via the multivillage, closed-ended questionnaire. Differences in proportion of men and women involved at least once in a contact were tested with Chi2 test or Fisher exact test. We compared mean frequencies by gender and type of contact with the Wilcoxon test.
Influence of relative abundance index. We evaluated transect data using descriptive statistics to obtain the number of signs per species and village proximity (1km, 10km, and 20km) in an index of relative abundance (RAi), in which RAi ¼ Nb signs i at 1 km 1 þ Nb signs i at 10 km 10 þ Nb signs I at 20 km 20 This index allowed us to estimate species abundance according to distance from the target village. Two Spearman correlations were performed for each dataset to assess the influence of this relative abundance index on physical contact with each NHP species. The first correlation evaluated relative abundance and mean estimated frequencies of physical contact for each type of contact, and the second correlation assessed relative abundance and the proportion of population exposed at least once.
Descriptive analyses of wild meat data. We analyzed data from the wild meat survey by producing descriptive statistics to identify the proportion of great apes, monkeys, and specific NHP species of hunted animal species, as well as the state of the meat (fresh/smoked and whole/butchered). We also performed a Spearman correlation to assess the association between the proportion of wild meat for each NHP species and its relative abundance index. Qualitative data analyses. We conducted qualitative content and discourse analysis of our anthropological-historical evidence to gain insight into current and past practices that brought people into physical contact with NHPs, as well as their understanding of the changing relations with and the mobilities and behaviors of NHPs  [50]. After reading all transcriptions and notes, we conducted initial line-by-line inductive and deductive coding.
Population exposed and contact frequency Overall, our data show that physical contact with NHPs is high across the entire population, especially for meat handling, and that it is more frequent with monkeys than with great apes. Tables  1  and 2  summarize the proportion and frequency for each type of physical contact for monkeys, apes, and all species for our single-village participatory longitudinal quantitative survey dataset and for our multi-village questionnaire dataset. (See Supplementary File 1 for details by NHP species). NHP Injury. Injury from an NHP occurred rarely and involved few people. Our participatory longitudinal quantitative data yielded no injuries over the ten-month period, whereas 6. 9% of multi-village questionnaire respondents did sustain injury. More men than women reported an NHP-related injury (10.
Our recruitment for this tool was also biased to favor literate participants. Frequent hunters may also have feared reporting their game offtake, although questionnaires also suffer this bias. Great ape hunting was not recorded during the ten-month participatory survey. Finally, due to study limitations, we do not have prevalence estimates of NHP-transmitted viral infections in human beings. It would be useful to replicate the participatory survey elsewhere in Africa to estimate NHP contact frequency and to conduct seroprevalence studies with the same participants. Several factors counterbalance these shortcomings. The detail of daily participant data compensates for small number of volunteers, and we have relatively high confidence in the accuracy of data reported. One volunteer, for instance, reported hunting almost every two days.
Acknowledgments Our sincere thanks to  Arnaud Fontanet ,  Romulus Breban ,  Antoine Gessain ,  Steven Volant  and  Emeline Perthame  ( C3BI ) for their advice concerning our analyses. We are grateful to  Sara Eyangoh ,  Guy Vernet  and  Elisabeth Carniel  from the  Centre Pasteur du Cameroon  for their support of the field research, and  Marina Vernick  for data entry. We are most indebted to the inhabitants of southeastern Cameroon for their warm welcome and participation in this research.
The  Agence Nationale de la Recherche  (France; http://www. agence-nationale-recherche. fr)funded the study  ANR-14-CE31-004 , including postdoctoral salary and field missions. TGV received this funding. The  Canadian Institute for Advanced Research (https://www. cifar. ca/)provided additional funding for field investigation. TGV received this funding. The  Institut Pasteur Infection and Epidemiology Department  (https:// www. pasteur. fr/en/infection-and-epidemiology)provided supplemental funding for VN's salary. VN received this funding. The  Institut Pasteur International Direction  (https://www. pasteur. fr/fr/international) provided supplemental funding for RN's participation in the study. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
They were in an antero-posterior orientation with respect to the participant's body. The task was to paint the non-colored strip. Performance of the hammering action was assessed, by measuring the depth to which the nail was driven. We could not use any indicator to specify the performance for the brush and roller conditions, but all participants performed these actions effectively. Motion capture. Tools' motion was recorded using an eight cameras optoelectronic motion capture system (Motion Analysis, 200 Hz). Six passive markers attached to each tool were recorded continuously during each tool-use action. Computed trajectories were filtered using a Butterworth low pas filter at 10 Hz cut-off frequency. Data analysis. The x-, y-, and z-axes corresponded to the anteroposterior, lateral and vertical directions with respect to the participant's body.
Acknowledgements We thank  Frédéric Volland  for his help with the experimental setup of the study, and  Karen Reilly  for revising the English. This work was supported by grants from  Inserm ,  Hospices Civils de Lyon  and  ANR (Agence Nationale pour la Recherche ; Project " Cognition and tool-use economy" ECOTOOL ;  ANR-14-CE30-0015-01 ), and was performed within the framework of the  LABEX CORTEX  ( ANR-11-LABX-0042 ) of  Université de Lyon , within the program " Investissements d' Avenir"  ( ANR-11-IDEX-0007 ) operated by the  French National Research Agency (ANR).
Sentence-final target words were controlled for lexical frequency, number of phonemes and number of phonological neighbours using the French lexical databases Lexique 3  [68]  and Manulex (database on words in children books,  [69] ). Sentences were recorded by a French native male speaker (44. 1 kHz, mono, 16 bits) in a sound-attenuated booth using ROCme! Software  [70]. Each sentence was recorded twice, at a normal and then at a fast rate. The procedure was the following: the sentence was first displayed on a computer screen in front of the speaker who was instructed to silently read it and to subsequently produce it aloud as a declarative statement at a normal rate. Once all sentences had been produced at a normal rate, they had to be produced at a faster rate using the same procedure. The speaker could produce each sentence several times so that the recorded version was as fluent as possible.
The durations of the 2 × 300 sentences and the number of produced syllables for each sentence were then calculated with Praat software  [71]. The average speech rate was 6. 76 syllables/sec (SD 0. 57) for natural normal rate sentences and 9. 15 syllables/sec (SD 0. 60) for natural fast sentences. Thus, the overall fast-to-normal ratio was 0. 74 (i. e. , speedup factor of 1. 35). Subsequently, the time-compressed sentences were computed by digitally shortening them with a PSOLA algorithm (Pitch Synchronous Overlap and Add  [72] ), as implemented in Praat. The compression rate was calculated for each sentence, and every individual time-compressed sentence was precisely matched by rate with its paired natural fast sentence. Compression was achieved by the re-synthesis of the normal rate stimulus, changing only the temporal structure without affecting the pitch.
Data analysis Response times (RTs: time-interval between the onset of the sentence-final target word and the button press, in milliseconds) and accuracy (% of correct responses) were measured. Trials for which participants made no response or erroneous responses were considered as errors and were not included in RTs analysis. Trials with RTs below or above 2. 5 standard deviations from the individual mean of the condition were further excluded from the analysis of RTs. We also computed d 0 as an index of sensitivity to semantically incongruent sentence-final words and ß as an index of response bias. This calculation is based on the proportion of hits (i. e. , correct responses for incongruent sentences, p[hits]) and false alarms (i. e. , errors for congruent sentences, p[FAs]). d 0 is defined as z(p[hits])-z(p[FAs]) and ß as z(p[hits])/z(p[FAs]) (see  [73]  for more details).
Acknowledgments We would like to thank parents and their children for participating in this study. We also thank  Lydie Merle  for helping to recruit children with  SLI ,  Emmanuel Ferragne  for his help in the construction of the stimuli and  Damien Gouy  for recording the sentences. This study was conducted as part of the  ODYSSEE  project (PI: V. B;  n˚11 JSH2 005 1 ) funded by the  French National Research Agency (ANR). H. G is funded by a doctoral fellowship from the  LabEx ASLAN  ( ANR-10-LABX-0081 ) of  Universitede Lyon  within the program " Investissements d'Avenir"  ( ANR-11-IDEX-0007 ) of the French government operated by the  ANR.
This study was conducted as part of the  ODYSSEE  project (PI: V. B;  n˚11 JSH2 005 1 ) funded by the  French National Research Agency (ANR ; grant number  11 JSH2 005 1 , http://www. agence-nationale-recherche. fr/). HG is funded by a doctoral fellowship from the  LabEx ASLAN  ( ANR-10-LABX-0081 ) of  Universitede Lyon  within the program " Investissements d'Avenir"  ( ANR-11 -are interpreted in light of temporal sampling and prosodic phrasing frameworks and of oscillatory mechanisms underlying speech perception. IDEX-0007) of the French government operated by the  ANR  (http://aslan. universite-lyon. fr/). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Materials and Methods The analyses conducted in this paper followed a harmonized approach defined within the International Breakfast Research Consortium  [23]. The data were extracted from a nationally representative survey of 7-day food intake in French adults, adolescents, and children in 2012-2013 (the CCAF survey). CCAF surveys are cross-sectional studies carried out at regular intervals in the French population. They collect data on anthropometry, socio-economic status, lifestyle, and diet in representative samples of French consumers characterised by age, sex, body adiposity status, profession and several lifestyle variables, such as smoking and daily screen-watching time. In the CCAF survey methodology, participants are asked to report their intake at the eating event they themselves identify as "breakfast".
Data for children between 3 and 6 years of age were not included in the present analyses. For each participant, self-reported height, weight, and time spent on physical activity and sedentary (screen watching) behaviour were recorded in face-to-face interviews with experienced members of staff. Children reported in the presence of parents or caregivers. The participants then completed a seven-day food intake record, and reported the types and amounts of all foods and beverages consumed. Dietary intake was reported with the help of parents or caregivers for all children aged 9 years or less and for older children who needed assistance. The energy intake reported by the participants was compared with the estimated energy requirements (at least 1. 55 times the metabolic rate), according to Schofield's equation  [27].
Dietary Intake Data The participants reported the types and amounts of all foods and beverages consumed over seven consecutive days. A "diary" was provided to each participant, to be completed either in paper or electronic format, as the participant preferred. Experienced staff visited each household and explained participants how to complete the diary before the start of the reported week. For each eating occasion during the week, all intakes of foods and beverages had to be reported. The diary had separate pages for the various eating occasions during each day, including main meals ("breakfast", "lunch", and dinner") and the various possible eating occasions before or after each of these main meals. To facilitate the reporting of portions, participants were provided with the validated SUVIMAX portion size atlas  [29] , showing photographs of various common foods and beverages in different portion sizes.
Specific Assessment of Wholegrain Consumption The CIQUAL cereal food groups ("Sweet crackers and biscuits", "Breakfast cereals", and "Breads and toasts") were checked for the presence of wholegrain (from wheat, oats, barley, rice, maize, rye, buckwheat, quinoa, bulgur, millet, spelt and amaranth). The wholegrain content of foods was obtained from brand information and quantitative nutrient declarations (QUIDS) on food labels. QUIDs were obtained from MINTEL (a market research database) [32], manufacturer's websites, or online shopping websites. If brand or QUID information was not available, then details of the wholegrain content of similar products were used (products of the same brand with available QUIDs, or similar ingredient list, or similar name and description). Total wholegrain consumption (g/day) was computed as the total intake from the various food sources.
Statistical Analyses The SAS 9. 4 software (SAS Institute, Inc. , Cary, NY, USA) was used for statistical analyses and for database management. Differences between proportions were tested using X 2 tests. Differences in quantitative variables (such as intakes) were tested using ANCOVA, adjusted as appropriate. Multiple comparisons were addressed using Tukey's multiple comparison test for continuous variables and Bonferroni-Holm test for categorical variables. Continuous data are reported as means and standard deviations. The confidence level for calculated confidence intervals was 95%. The statistical significance level was set at p-value < 0. 05.