dataesr/scientific-paragraphs-categorization huggingface dataset:
To speed up the acquisitions, both channels were acquired in two separate scans. To account for micro-movements of the samples that may occur between the scans, a 3D image affine registration was performed to align both channels using ClearMap. ClearMap analysis. All analysis and quantifications were performed with our open source ClearMap software as shown in the example scripts, and the associated documentation and as described in reference  14. The latest version of ClearMap, scripts and documentation can be obtained from http://www. idisco. info. The settings used for analyzing the data were as follows: the background was removed by subtraction of the morphological opened image with a disk shape structure element with main axis of seven pixels in diameter. Cells were detected from peaks and subsequent watershedding, removing background pixels below an intensity cutoff of 700 (700 is the rounded average value of the background intensity after the background subtraction) and selecting cells with sizes between 20 and 500 voxels.
We targeted neurons in the same area and layers characterized in vitro (L2/3 140-300 μm below the cortical surface) using patch electrodes containing the same intracellular solution described in the section below. Stimuli. A sound booth (Industrial Acoustics Company, Bronx, NY) was used to conduct all recordings. We used a custom built real-time Linux system (200 kHz sampling rate) driving a high-end Lynx L22 audio card (Lynx Studio Technology Inc. , Newport Beach, CA) with an ED1 electrostatic speaker (Tucker-Davis Technologies, Alachua, FL) in free-field configuration (speaker located 8 cm lateral to, and facing, the contralateral ear). The stimuli used were 100 ms long pure tones of 16 frequencies logarithmically spaced between 1 and 40 kHz, presented at 5, 20, 50, and 80 dB SPL, and logarithmic frequency modulated sweeps between 1 and 40 kHz with speeds of 25-150 octaves s -1 , at 60 dB SPL.
We used the custom software package ephus  39  (http://www. ephus. org) for instrument control and acquisition written in Matlab (MathWorks, Natick, MA, USA). LSPS by glutamate uncaging. Brain slices were prepared and maintained  40, 41  in vitro as described in the preceding section, except that the ACSF was supplemented with (in mM): 0. 2 nitroindolinyl (NI)-caged glutamate (Tocris), 0. 005 CPP (Tocris), and a final concentration of 4 CaCl 2 and 4 MgCl 2. To accomplish focal photolysis (UV flash) of the caged glutamate compound, we used a 1 ms light stimulus consisting of 100 pulses from a pulsed UV laser (wavelength, 355 nm with a repetition rate of 100 kHz; DPSS Lasers, Santa Clara, California USA). A 16 × 16 stimulus grid with 75 μm spacing was used for LSPS mapping of synaptic input in mouse cortical slices.
The hotspot distance from soma is the horizontal distance from the hotspot's weighted centroid to the soma. Laminar boundaries were determined for every slice. The L3/L4 boundary was determined from cytochrome oxidase staining density  43  , and L2/L3, L4/5, and L5/L6 differ in cell density and morphology readily visible under the differential interference contrast optics used in our experiments. The markings in each figure represent the averages of the thicknesses measured (for details, see ref. 13  ). Interpolated maps of population data are for display purposes only and were not used for analysis. Viral injections and noise rearing. Anesthesia was performed as described above for in vivo recordings. For the CRACM slice experiments, we injected AAV-EF1a-DIO-hChR2-EYFP (a generous gift from Cold Spring Harbor Lab) in the left ACx of p21 Ntsr1-cre (Gensat) male mice.
Acknowledgements We thank  Anthony M. Zador  for support in the early stages of this project,  Barry Burbach ,  Zach Saccomano , and  Sang-geol Koh  for invaluable technical help, and  Jonathan Levitt  for use of the Neurolucida system. All LSPS hardware control and data acquisition was performed using ephus (http://www. ephus. org). The project described was supported by Grant Number  5G12MD007603  (H. V. O. ) from the  National Institute On Minority Health and Health Disparities. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute on Minority Health and Health Disparities or the  National Institutes of Health. This project was also funded by a  Whitehall Foundation   Research Grant  (H. V. O. ), and an  NSF   Career Award  ( IOS-1652774 , H.
We first construct an indicator of functioning failures for each individual (i. e. their lack of access to basic needs) as the sum of the scores in the above four domains of a decent life. This indicator thus takes on values between 0, for individuals who are never deprived in any of the domains, and 16, for individuals who are always deprived in all domains. See  Shenga (2010)  for an alternative approach using the same dataset, recoding the responses so that 0 refers to Never or Just once or twice, and 1 to Several times, Many times or Always. Let N denote the set of all positive integers and R (R + ) the set of all (all non-negative) real numbers. The distinct levels of functioning failures are collected in a vector q 1 ,. ,q k , where k ∈ N ⧵ {1}. Let j indicate the population share of individuals who have the same q j level of functioning failures.
One of the motivations behind the introduction of this measure is to better capture societal conflict (see  Esteban and Ray, 1999). For this reason, the larger the relative size of the group the louder their voice may be when it comes to protesting against others. The index of income polarisation is due to  Esteban and Ray (1994). Polarisation considers the clustering of individuals in different parts of the distribution, particularly at the extremes. The individual measure of polarisation considered in the analysis is that of effective antagonism introduced by Esteban and Ray (1994), the function EA i : Ω → R + , which, rewritten in terms of functioning failures, is: for all , q ∈ Ω. This index has been shown to capture societal conflict (Esteban and Ray, 1999). We will below apply all of these measures to data on functioning failures from five waves of the Afrobarometer to explore their relation with well-being, as measured by current self-assessed living conditions.
The other four years are  2005 , 2008 , 2011 -2013 and 2016 (Waves 3-6) (Waves 3-6) , covering, respectively, 18, 20, 34 and 36 countries. The data set is cross-sectional, with the sample size per country per round ranging from 1200 to 2400. One person is interviewed per household. The sample details appear in Appendix Table  A1. Our dependent variable is self-assessed current living conditions, which we will denote for individual i in year t, as wb it. Respondents, who were aged 18 and over, were asked to answer the following question: "In general, how would you describe your own present Our regression analyses control for age, age-squared, gender, living in an urban or rural area, the highest level of education achieved (with three levels: at most primary, at most secondary and at least postsecondary) and labour force status (not in the labour force, unemployed and looking for a job, employed part-time and employed full-time).
ACKNOWLEDGEMENTS We are very grateful to  Anthony Lepinteur  for excellent research assistance above and beyond the call of duty. Conchita D'Ambrosio  gratefully acknowledges financial support from the  Fonds National de la Recherche Luxembourg. We thank two anonymous referees,  Válerie Berenger  and participants at the Conference "Inclusive Growth in Mozambique" which took place in Maputo on November 27th 2017 for comments and suggestions. We are also grateful to the Editors and two anonymous referees for constructive comments that helped to improve our work.
Both living conditions and basic needs are self-reported by the same individual at the same point in time. This produces potential problems with common-method variance, whereby mood effects may similarly affect both the evaluation of living conditions and the respondent's evaluation of how much they lack food, water etc. This would lead to upward bias in the correlation between the two variables. Self-reported income or consumption data are also likely affected by these biases. We unfortunately do not have any useful variables with which to instrument access to basic needs in this cross-section dataset, and therefore cannot be sure to estimate causal relationships. Note, however, that the measures of deprivation and satisfaction are less subject to this bias: the respondent's own mood will not affect the basic needs responses that other members of her reference group give.
We also included a short version of Openness. Participants were invited to describe themselves on the traits such as "creative" or "imaginative" (1 = totally wrong; 5 = totally right). The whole scale was based on 6 items, Cronbach's Alpha = 0. 749)  [87]. No other personality dimensions from the Big Five Model were included in the survey, but there were additional items on food preferences and representations which are not reported here. Missing data or the use of the non-response option (<2% per variable) were imputed using a straightforward linear interpolation method. Participants who did not indicate their gender (n = 38, 0. 14%) were not included in the analysis.
10, t = -7. 48, p < 0. 000). Moreover, the number of weeks participants practiced Green Monday was lower among participants with higher educational level (beta = -0. 05, t = -3. 72, p < 0. 000) and who lived in larger cities (beta = -0. 04, t = -2. 85, p < 0. 004) but was higher among older participants (beta = 0. 16, t = 11. 35, p < 0. 000). Finally, participants with higher Openness applied Green Monday longer than the others (beta = 0. 03, t = 2. 62, p < 0. 009). Participants' gender or affluence, the number of vegetarians in their social network and their weekly consumption of fish were not significantly associated with the length of their commitment. The value of the adjusted R 2 of the final model was 0. 056. In order to rule out the possibility that the older people (aged over 65 years) may not willing to eat meat more than younger people do by aging, we also analyzed the data without participants aged over 65 and confirmed the inverse effect of age on the length of the Green Monday practice.
Localities and Key Informants Field work was conducted from February to July 2018, in December 2018, and from February to April 2019. We surveyed for edible Orthopteran diversity in 47 localities covering most of the ecoregions of Madagascar and corresponding to 12 of the 19 ethnic groups (Figure  1 ). All localities were rural villages with rice cultivation as the main subsistence activity. Data was collected with key informants, i. e. , rural villagers, who are highly knowledgeable about which insects are edible, where they can be found, how to collect them, and how they are used as food and feed. The key informants were identified via intermediaries, i. e. , market vendors, hotel staff, taxi drivers, and agricultural extension offices in rural towns. We explained our research objectives to the intermediaries who then suggested potential key informants and localities and provided contact details and directions.
Insect Specimens Edible Orthoptera specimens were sampled during field trips with key informants in natural areas, agricultural areas, and home gardens. The insects were photographed both in their natural habitat and close up (profile, head, and dorsal). Specimens were sampled by hand, with tweezers, and with sweep nets, and stored in 95% alcohol in vials and Whirl-Pak ® bags (Nasco, Fort Atkinson, WI, USA). Specimens are permanently stored in the entomology collections of the California Academy of Sciences, San Francisco, USA. Specimens were identified by Sylvain Hugel, co-author of the present study, with data from Dirsh and Descamps  [19]. Geographical distributions and threats to crops were determine by referring to Braud et al. [20]. Calculations were performed with Microsoft Excel.
Acknowledgments: Administrative assistance and assistance in data collection was provided by  Balsama Rajemison ,  Jean-Jacques Rafanomezantsoa ,  Claver E. Randrianandrasana , and  Chrislain Ranaivo  of the  Madagascar Biodiversity Center, Parc Botanique et Zoologique de Tsimbazaza, Antananarivo 101 ,  Madagascar. Jane Hooper ,  George Mason University, United States of America , is thanked for providing literature on the historical use of Orthoptera as food and feed in Madagascar. All necessary permits were obtained for the collection of insects in Madagascar. Permits to research, collect, and export arthropods were obtained from the  Ministry of Environment and Sustainable Development  as part of an ongoing collaboration between the  California Academy of Sciences  and the  Ministry of Environment and Sustainable Development, Madagascar National Parks , and  Parc Botanique  et  Zoologique de Tsimbazaza.
Preprocessing All EEG processing steps were carried out using Letswave 6 (http:// nocions. webnode. com/letswave) and Matlab 2017 (The Mathworks). EEG data was segmented in 47-s segments (2 s before and 5 s after each sequence), bandpass filtered (0. 1 to 100 Hz) using a fourth-order Butterworth filter, and downsampled to 256 Hz. Generally, at the group level, there were no differences in eye-blinks (T(44) = 0. 375, p = 0. 71). For one participant of the control group who blinked excessively (0. 66 times/s, which is more than 2SD above the mean (M = 0. 43 times/s, based on all participants from both groups) blinks were corrected by means of independent component analysis (ICA) using the runica algorithm  (Bell and Sejnowski 1995; Makeig et al. 1996)  as implemented in EEGLAB. For this participant, the first component, accounting for most of the variance, representing vertical eye movements was removed.
The pCREB-positive nuclei in the areas of interest were measured using our homemade ImageJ/Fiji developed by G. Courtand (INCIA, Bordeaux, France). Briefly, for each animal, regions of interest were delineated by an observer blind to experimental groups and labeled neurons were automatically counted given that they were above a threshold determined from each side of 3-4 sections. The data obtained in both sides of each section were pooled and expressed as mean number of pCREB immunopositive nuclei/mm 2 in the PL subregion of the PFC, the dCA1 and the vCA1 according to  Paxinos and Franklin atlas (2001).
Statistical analysis Statistical analyses were performed using the Statview 5. 0 software ®. Data were expressed as mean ± SEM. Behavioral and immunohistochemical data were analyzed using one-or two-way ANOVAs with UCMS exposure, Drugs and brain regions as independent factors. Results of multiple trials and time points were compared using two-way repeated measures ANOVA. Comparisons of WM performance with chance level were calculated with one-sample Student's t-test (with hypothesized mean-chance level = 50%). An analysis per block of three consecutive trials (Block A: trials 2 + 3+4; Block B: trials 5 + 6+7) were made in order to study proactive interference effects. Post-hoc Bonferroni/Dunnett's multiple comparisons analyses were performed when adequate. Significance was set at P ≤ 0. 05.
Effects of UCMS exposure on physical state and anxiety-like behavior Measurements of the physical states (coat state score and body weight) were assessed weekly on mice randomly taken from the UCMS (n = 29) and non-stressed (n = 21) groups. As shown in http://www. sciencedirect. com. gate1. inist. fr/science/article/pii/ S0166432812002124 Fig. 1B , the coat state scores of mice in each group did not differ between UCMS and non-stressed groups before the beginning of the UCMS procedure (week 0: both P > 0. 1). A repeated measure ANOVA on data related to the coat state scores indicated a significant effect of UCMS (F (1,48) = 61. 03, P < 0. 0001), a significant effect of time (F (5,240) = 17. 5; P < 0. 0001) as well as a significant UCMS X time interaction (F (5,240) = 14. 81; P < 0. 0001). Specifically, UCMS exposure produced a significant deterioration of the coat state score that began after three weeks of stress exposure (versus nonstressed: P < 0.
Materials and methods Patients were randomly assigned in a 1:1 ratio to either the active or sham tDCS group. We used a block randomization with a block size of four. The study was approved by the local ethics committee (Comité de Protection des Personnes of Sud-Est 6, Lyon, France). All subjects gave their written informed consent after receiving a full description of the study. This study was preliminarily registered on the clinicaltrials. gov database (clinicaltrials. gov identifier NCT 02407288).
Statistical analysis Statistical analyses were performed using SPSS (version 22). Fisher's exact tests and two-tailed Student's t-tests were applied to compare the demographics and clinical measures at baseline between the active and sham groups for categorical and continuous variables, respectively. The primary analysis investigated acute changes in the YBOCS score. Acute changes in clinical scores between baseline and after the 10 tDCS sessions (at M0) were compared using repeatedmeasures analysis of variance (ANOVA) with treatment as the intergroup factor and time as the intrasubject factor. For significant changes, post hoc comparisons were performed using Fisher's least significant difference tests. Secondary clinical analyses investigated maintenance effects on the YBOCS score, response rate and effects on other symptoms.
Accompanying common software, development platforms -often open-source ones like ROS and Gazebo, YARP and Choreonoid -play an important role as well for the researchers and engineers because they allow them to share and exchange their newest software. For instance, the installation of HRP-2 in the Laboratory for Analysis and Architecture of Systems at the Centre National de la Recherche Scientific, in France, triggered collaborative research on humanoid robots involving many European institutes through EU projects, leading to many joint publications  (Yoshida, 2009). Since mid-2000s, different full-size humanoid robots have been developed including WABIAN-2, TORO (Figure  5a ), Hubo (Figure  5b ), iCub (Figure  5c ), and Talos, some of which are also used as research platforms for joint research.
The data acquisition was driven by AMA 254 V5. 0. 2. 4 software. The routine quality assurance metrics included in the standardized analytical method were fulfilled by all samples. The mercury content of the standard reference materials namely LGC6139 (River clay sediment-Metals) and BCR 277R (Estuarine sediment) was recovered within certified limits:1. 2 (±0. 05) µg. g -1 and 0. 128 (±0. 017) µg g -1 respectively. Likewise, triplicated samples passed the method criteria of <20% RSD (Relative Standard Deviation) for liquids samples and <5 % RSD for solids samples.
Statistical analyses The statistical analyses were performed using the Statgraphics software (Centurion XVI, Sigma Plus, France). For the concentrations of total (THg), mobile Hg (MHg) and the ratio of MHg to THg, the data was not normally distributed (Shapiro-Wilk test at 95% confidence). Therefore, the non-parametric Kolmogorov-Smirnov test was used to assess the significance of the differences in concentration, with p < 0. 05. MeHg concentrations were, however, normally distributed. Differences between samples of each termite species were analyzed using one-way ANOVA. Correlations between the various mercury fractions were tested using Spearman's rank correlation (p < 0. 05) and the correlation curves were constructed using ggplot2 and ggpubr packages in R version 3. 4. 4.
Methods: The Arksey and O'Malley (Int J Soc Res Methodol 8:19-32, 2005)  methodological framework was used. A search of 16 peer-review and grey literature databases, websites, and relevant journals  was conducted. To identify relevant studies, two reviewers independently applied the inclusion criteria to all abstracts or full articles. Inclusion criteria were: participants were people living with HIV; the intervention was any mind-body practice; and the study design was any research study evaluating one or several of these practices. Data extraction and risk of bias assessment were performed by one reviewer and checked by a second, as needed, using the criteria that Cochrane Collaboration recommends for systematic reviews of interventions (Higgins and Green, Cochrane handbook for systematic reviews of intervention.
Identifying relevant studies To attempt to answer the research question, we identified primary studies and reviews in the literature, by searching electronic databases, websites, reference lists and key journals. A search strategy for electronic databases was developed according to the research question and key concepts. We used the following search terms: HIV OR AIDS AND mind-body therapy OR Alternative Medicine OR meditation OR yoga OR Tai Chi OR Qigong OR relaxation OR relaxation therapy OR biofeedback training OR biofeedback OR neurofeedback OR autogenic training OR deep-breathing OR guided imagery OR imagery OR progressive relaxation therapy OR muscle relaxation OR Jacobson progressive relaxation OR hypnosis OR hypnotherapy. Table  1  shows our Ovid search strategy. This was adapted for other databases, and details of those strategies may be obtained from the authors on request.
A total of 16 peer-review and grey literature databases from 1983 (when HIV was discovered) to October 2015 were searched. The peer-review database searched were: Cochrane Central Register of Controlled Trials (CCTR), Cochrane Database of Systematic Reviews, Cumulative Index to Nursing and Allied Health Literature (CINAHL), Database of Abstracts of Reviews of Effects (DARE), Health Technology Assessment, EMBASE, MEDLINE, PsycINFO and Web of Knowledge. The grey literature databases searched were: Google Scholar, Scirus, Archimède (Université Laval), Papyrus (Université de Montréal), Dissertations & Theses (ProQuest), the New York Academy of Medicine Grey Literature and OpenGrey. To identify ongoing clinical studies, we searched the following sites: ClinicalTrials, World Health Organization International Clinical Trials Registry Platform and Canadian trials.
Our goal was to conduct a sensitive, rather than a specific, search of the literature. We enlisted the services of a qualified librarian (MD) to conduct the electronic database search. The last search was run on  October 31, 2015. This search was completed by examining the reference lists and citations of all included studies and by hand searching key journals, such as BMC Complementary and Alternative Medicine, Journal of Evidence-Based Integrative Medicine, The Open Complementary Medicine Journal, Evidence-Based Complementary and Alternative Medicine, Complementary Therapies in Medicine, Complementary Therapies in Clinical Practice, Journal of Alternative and Complementary Medicine, Journal of Complementary & Integrative Medicine and European Journal of Integrative Medicine. We considered publications in any language, as long as there was an English, French, or Spanish abstract.
Charting the data We developed an electronic data extraction form in Microsoft Excel with the following items: study ID, aims of the study, study design, total study duration, population, number of participants, setting, country, details and type of intervention (total number of intervention groups, specific intervention, length of intervention, number of contacts, provider and method of delivery), outcomes and time points, scales, and authors' conclusions. Two reviewers (PRG & MPG) extracted data independently from 10 studies to determine if the approach to data extraction was consistent with the research question and purpose. The data were then extracted by one reviewer (PRG) and checked by another (MPG), as required. Discrepancies were resolved through discussion.