dataesr/scientific-paragraphs-categorization huggingface dataset:
Furthermore, the data quality of the AgeGuess. org database experiences a trade-off common to citizen science projects, where large quantities of data are won at the expense of representativeness of sample and data accuracy. Neither the AgeGuess users nor the persons displayed in the photograph are representative samples of the population with respect to age, geographic location, or ethnicity. Furthermore, the uploaded photographs are not standardised with respect to posture, lighting, face expression, clothing, background, distance to camera, hairstyle or dye, make-up, or the use of accessories such as hats, jewellery, or glasses. Some of these factors may be used to deliberately conceal age: older adults may use particularly make-up and hair dye to appear younger, while younger adults may manipulate their looks to appear older.
Research opportunities The AgeGuess data provide exceptional opportunities to approach research questions across scientific fields. The research opportunities broadly split into two main directions. The first one relates to ageing research and some of the questions outlined in the introduction, e. g. evaluating ageing processes by studying temporal variation in biological age and the difference between perceived and chronological age. The second direction relates to a more sociological view, where the users themselves are the subject of study, and research questions center around their ability to guess ages. Regarding the first research direction, the collected data on perceived age and chronological age can inform on the basic ageing process. The data can reveal whether more recent birth cohorts are biologically younger than their earlier counterparts, e.
g. is a 40-year-old today biologically younger than a 40-year-old in the 1980s, and does that difference hold in the same way for 30-year-olds? We can investigate how shifts in biological age over time accompany shifts in life expectancy  [12, 18]. Research questions can also focus on how ageing happens within a lifetime, i. e. do we age continuously throughout our lives or are there boosts and arrests of ageing? Furthermore, quantitative geneticists can exploit relatedness among persons in uploaded photographs to study diverse questions, including to what degree biological age is heritable, and how heritability of biological age relates to known heritability of lifespan. Computer scientists can use the data to train and evaluate age estimation algorithms  [19]. Access to the original images requires a close collaboration with the AgeGuess project due to new EU regulations on privacy of identifiable pictures of persons.
The data might furthermore reveal guessing abilities related to exposure to specific ethnic or age groups. For example, opposite to expectation geriatric nurses, who daily work with elderly patients, are not better at guessing ages of elderly citizens than male undergraduate students  [2]. As focus turns from the subject in the photograph to the judgment, the AgeGuess data become highly valuable for answering basic questions about information processing. More specifically, the data provide an outstanding opportunity to investigate to what extent hidden aspects of the environment can be measured using perceptible cues that correlate more or less with these unobservable parts. This problem of inferring hidden aspects is, and has been, fundamental to human survival, and is therefore important for cognitive psychologists and neuroscientists alike  [20].
Moreover, in their development of artificial intelligence, the cue learning problem is, with some controversy, being studied by computer scientists  [21]. How much information about a person can be extracted from the person's facial features, and to what extent it matters how different features of the face are combined in making the judgment  [22]  are interesting questions. They are also questions with potential to challenge the organisation of society, in the event judgments are done at mass scale by computers with live access to extensive networks of cameras  [23]. The questions that we list here are certainly not exhaustive and are meant only as an illustration of the power of the data for answering broad scientific questions. We believe many more questions can be addressed using the AgeGuess data, including those that we as data collection initiators have not thought about and may not be able to imagine.
Materials and methods Participants in this study were aged 18 months (n = 13), 3 years (n = 17), 6 years (n = 12) and adult (n = 13) (for details, see the Supplementary Materials). For the adult, 6-, and 3-year-old participants, the following procedure was used. Six cups were fixed on shelves on an apparatus standing on a table at a distance of 1. 5 m from the seated participant (height of rows, 20 cm apart, with the lower row matched to height of each participant's eyes; distance between cups, 20 cm; Fig. 1, left ). The sessions began with the experimenter explaining to the participant that they would play a game where wooden marbles are hidden under cups, and the participant has to point out the location of the marble. Before the start of data collection, three practice trials were administered in this way: The experimenter placed the ball under one of the cups as the participant watched and then asked the participant to point to its location.
Acknowledgments: We thank  M. Tomasello  and the  Department of Comparative and Developmental Psychology  of the  Max Planck Institute for Evolutionary Anthropology, Leipzig  for the use of the laboratory facilities, where these studies were carried out. We also thank  E. Rossi  who ran the studies and  R. Mundry  for statistical analysis. Funding: This research was supported by funding from the  European Research Council  under the European Union's  Seventh Framework Programme  (FP/2007-2013)/ ERC  grant agreement N°324115-FRONTSEM (PI: Schlenker). C. O'M. and G. K. 's work was supported by the  Max Planck Institute for Evolutionary Anthropology , Leipzig. B. S. 's work was supported by  Institut d'Etudes Cognitives, Ecole Normale Supérieure-PSL Research University. Institut d'Etudes Cognitives  was.
The data for this paper focuses on the US field sites in NYC and LA. Data was collected through qualitative in-depth, semi-structured interviewing with sex workers, migrants, and trafficked persons lasting 60-90 min and ethnographic observations with community members of all genders. Key topics covered in interviews centered on experiences in early life and life before, during, and after migration (if applicable), work life, humanitarian encounters and system-involvement, surveillance and technology, health, relationships, and future goals. In addition, interviews were conducted with key informants from legal, health, and social service organizations and law enforcement institutions, with a focus on the specifics of their service provision, and how they situate their work within the broader anti-trafficking landscape.
We also attended monthly Sex Worker Outreach Project (SWOP) meetings and transgender community gatherings at TransLatin@ Coalition and Bienestar in LA, and Colectivo Intercultural TRANSgrediendo in NYC and participated in a hearing of the NY City Council on the presence of Immigration and Customs Enforcement (ICE) officials in HTICs. Finally, we participated as stakeholders in the United Nations General Assembly Hearing to Combat Trafficking in NYC, and a national sex worker-led summit and strategy session in LA. Interview transcripts were coded, sorted, and analyzed using a combination of thematic analysis guided by the theory of sexual humanitarianism and the constant comparative method for the development of grounded theory. Qualitative coding and data excerpting to select quotes demonstrating the themes related to policing, arrest, incarceration, social services, trafficking/anti-trafficking, system-involvement, violence, health, stigma, and community-based responses were identified and conducted in Dedoose.
Acknowledgments: The authors would like to thank  Samantha Majic  and another anonymous reviewer for providing detailed and insightful feedback on this paper. The authors would also like to thank  Jenna Torres ,  Ceyenne Doroshow ,  Alex Andrews ,  Liaam Winslet  and  Lorena Borjas  for their assistance with this paper. Finally, the authors would like to acknowledge and express their gratitude to all of the migrant, sex worker and trans participants and key informants in our study, as well as the community partners who made this research possible.
In order to compute an analog of a mean field model like van der Waals interactions  [46] [47] [48] , we define and compute the mean information paths that correspond to the homogeneous case of identically distributed random variables. On a dataset of expected interacting genes, the mean information path reproduces the usual behavior of the free energy in the condensed phase (i. e. , with a critical point), while for genes that are less expected to interact, the path exhibits a monotonic decrease without a non-trivial minimum which corresponds to the usual free-energy potential in the uncondensed disordered phase for which the n-body interactions are negligible. However, compared with the non-averaged original information paths as presented in References  [2, 3] , it is clear that this analog mean-field approach erases the multiplicity of critical points and the diversity or richness of the complexes.
The combinatorics of these structures forbid any computation in practice, until quantum computers become available and the severe restriction to the simplicial case of the cohomology with complexity O(2 n )) implies that not all statistical dependencies can be estimated, as shown by James and Crutchfield  [51]. The interpretation makes two phenomena coincide (i. e. , condensation in statistical physics and clustering of data points in data science), which are signed by information and conditional information negativity as studied in the companion paper  [2]. This generalizes the idea and results obtained on networks by the team of Grassberger  [52]. On the side of applied algebraic topology, the identification of the topological structures of a dataset has motivated important research following the development of persistent homology  [53] [54] [55].
See Reference  [63]  for a presentation and preliminary applications to the digit images database of the Mixed National Institute of Standards and Technology (MNIST). The informational approach of topological data analysis provides a direct probabilistic and statistical analysis of the structure of a dataset which allows the gap with neural network analysis to be bridged and may be a step toward their formalization in mathematics and the characterization of the network architecture necessary for a given dataset. The original work based on spin networks by Hopfield  [64]  formalized fully recurrent networks as n binary random variables (N = 2). Ackley, Hinton and Sejnowski  [65]  followed up by imposing the Markov Field condition, allowing the introduction of conditional independence to handle network structures with hidden layers and hidden nodes.
It corresponds to Examples 1 and 4 in Reference  [1] , and to the python scripts shared on Github (cf. Supplementary Materials). For simplicity, we note also the simplicial information structure (Ω, ∆ n , P), ∆ n = (X 1 ,. , X n ; P), as we will not come back to the general setting. Joint (X 1 , X 2 ) and meet (X 1 ; X 2 ) operations on random variables are the usual joint-union and meet-intersection of Boolean algebra and define two opposite-dual monoids, freely generating the lattice of all subsets and its dual. The combinatorics of the simplicial information structure follow binomial coefficients and, for each degree k in an information structure of n variables, we have ( n k ) = n! k!(n-k!) elements that are in one-to-one correspondence with the k-faces (the k-tuples) of the n-simplex of random variables (or its barycentric subdivisions).
As is usually achieved in physics notably in mean-field theory (e. g. , Weiss  [145]  or Hartree), it aims to provide a single function summarizing the average behavior of the system (we will see that in practice it misses the important biological structures, pointing out the constitutive heterogeneity of biological systems; see Section 4. 1. 3). Using the same dataset and results presented in References  [2, 3, 108] , the IP (k) paths estimated on a genetic expression data set are shown for two populations of neurons (A and B) in Figure  5. We quantified the gene expression levels for 41 genes in two populations of cells (A or B) as presented in References  [2, 3, 108]. We estimated H k and I k landscapes for these two populations and for two sets of genes ("genes of interest" and "non-relevant") according to the computational and estimation methods presented in References  [2, 3, 108].
Topological Data Analysis Thanks to the recent success of topological data analysis, a recurrent question has concerned the relation of information cohomology with persistence homology. The answer is not easy, since both appeared independently and are quite different in formalism, algorithms and results on the dataset. It is possible to provide an intuitive non-rigorous interpretation of the present work in persistence terms. Most of the persistent methods consist of approximating the birth and death of the Betti's numbers of the Cech complex obtained by considering balls around each data point while the radius of the ball grows. The Cech complex is given by the intersection of the balls and for combinatorial computational reasons, most of the algorithms restrict to pairwise intersections, giving the Vietoris-Ripps complex as an approximation of the Cech complex.
Notably, the introduction of the multiplicity decomposition of "energy functions" formalizes unsupervised learning in neural networks in terms of a combinatorial family of analytically independent functions I k with independent gradients (Theorem 4 in Reference  [2] ): instead of a single energy and associated gradient descent, mutual information provides a multiplicity of gradients. The application scope is restricted to the general problem of unsupervised learning here but the supervised subcase can be proposed from this and is detailed with some examples of application to the digits MNIST images dataset presented here  [63]  and in a future publication. Notably, the mathematical depth of the back-propagation algorithm  [172] [173] [174]  comes from the fact that it implements the chain rule for derivation with respect to the parameters, allowing learning in the class of differentiable functions.
Once engaged in the experiment, participants were asked to sign a use-of-data confidentiality protocol and an information and consent form for audio and video recordings. We filmed participants experiencing the immersive art installation to study their movements and verbal and non-verbal exchanges in the room. We then recorded the interviews by audio and video to facilitate their analysis and use. Tech Center in Strasbourg, France. In the Science Museum, we chose specific days when various activities were proposed to visitors, such as "Saturday repair cafes", in order to reach a diverse audience in terms of socio-professional categories and ages. Recruitment has been adjusted and redesigned over time to increase the panel's diversification so as to boost the number of female participants in the survey.
People were walking past the glass room where the facility was located, and voluntarily chose to step in. We stayed at the facility during large time slots (from 09:00 to 18:30) to include various participants' profiles in our research. Once engaged in the experiment, participants were asked to sign a use-of-data confidentiality protocol and an information and consent form for audio and video recordings. We filmed participants experiencing the immersive art installation to study their movements and verbal and non-verbal exchanges in the room. We then recorded the interviews by audio and video to facilitate their analysis and use. In the end, 38 interviews were conducted. We did not anticipate that several people would simultaneously participate in the survey. Indeed, a total of 18 interviews were run in groups, either as a couple, a group of friends, or a family, ranging from 2 to 4 people.
We will see that this element, once analyzed, enhanced our conclusions. In total, we interviewed 62 people, almost as many women as men (25 women against 30 men) and 7 children. The ages ranged from 7 to 69 years old. Individuals had diverse professional backgrounds, from journalism to sociology and mathematics. This number of participants is relevant for a qualitative survey. We stopped conducting interviews when we reached saturation point in data collection: When new interviews were not providing us with new information or different ways of understanding our subject.
The sequencing was performed on Illumina HiSeq 2500 at the Translational Science Laboratory of Florida State University. The pooled data were demultiplexed into individual sample data, and adapter primer sequences were removed  [17]. 2. 4. RNA-Sequencing Data Analysis. The sequencing reads were analyzed using RNA-Seq Alignment version 1. 1. 1 (Illumina BaseSpace application). The reads were aligned with TopHat 2  [18]  to the human genome (genome release GRCh38) using default parameters, and counts for each gene were generated. This workflow uses Cufflinks to generate FPKM (fragments per kilobase per million reads) normalized values  [19]. DESeq2 was used to determine statistically significant differentially expressed genes (a false discovery rate (FDR) of <0. 05 was used). 15,585 genes were considered to be expressed in this study by the DESeq2 software  [20].
Acknowledgments The authors thank  Dr. Brian K. Washburn  in the  FSU Department of Biological Sciences  for his help with RNAsequencing and RT-PCR analysis and  Dr. Cynthia Vied  in the  FSU Translational Science Laboratory  for the initial genomics analysis. This work is supported by the  FSU Bridge Grant, NSF Career Award  (No. 1652992  to YL), and by  NIH   R03EB020770  (YL).
9, 10 Although linkage to the RYR1 gene is shown for more than 50% of all MH cases, mutations in two other genes were associated to MH: CACNA1S encoding the L-type plasma membrane channel regulating RyR1, and STAC3, a small adaptor protein interacting with both channels. The search for a new candidate potentially involved in MH led us to the TRPV1 channel. To date, although playing a widely accepted role in nociception, this channel is not clearly linked to any hereditary disease. 11 Efforts have been mainly focused on its implication in chronic pain syndromes,  11  however, the latest available data suggest that TRPV1, as a highly Ca 2+ -permeable channel, also plays an important role in the physiology of skeletal muscle. 12 Indeed, after initial discovery as a neuronal sensory channel, TRPV1 was subsequently found in a few non-neuronal tissues, including skeletal muscle, and recent studies have clearly highlighted its functional role as a sarcoplasmic reticulum (SR) Ca 2+ channel.
Genetic analysis Blood samples used for genetic screening were obtained after a written informed consent was signed by patients according to the French regulation for genetic studies. For each patient, the 15 coding exons of the TRPV1 gene were amplified from genomic DNA (OMIM 602076, transcript: NM_018727. 5, protein: 839 AA, Q8NER1, primer sequences available upon request). The analysis of the entire coding sequence of TRPV1 was performed by direct sequencing on an ABI 3130 DNA sequencer (PE Applied Biosystems®, Foster City, CA, USA). Variations in the sequence were compared with databases (National Center for Biotechnology Information's dbSNP, 1000 Genomes, and the Exome Variant Server), and selected for the study when allele frequency was less than 1%.
Indeed, MH has a dominant mode of inheritance and a pathophysiology related to a hypersensitive RyR1 channel only caused by missense or inframe deletion variants. The T612M variation was found in the databases (rs199539626) with a minor allele frequency (MAF) of 0. 0013 (ExAC browser), and classified as tolerated or benign by SIFT and Polyphen prediction software. The N394del was not reported, but the Asn in the 394 position was found to have mutated to Ser in only one allele in the ExAC database. Overall, the two TRPV1 variants were either unknown or below a low MAF threshold, as compatible with rare and triggered diseases such as MH. Impact of the TRPV1 variants on Ca 2+ homeostasis We characterized the impact of the two TRPV1 variants on Ca 2+ homeostasis by performing Ca 2+ imaging experiments in HEK-293 cells.
Accordingly, two TRPV1 variants were discovered in patients who tested MH sensitive. The first TRPV1 variant (T612M) was found in a patient with a postoperative hyperthermia after anesthesia. The second variant (N394del) was discovered in an asymptomatic patient. The two variations were either unknown or with very low prevalence in human genetic databases, as compatible with a triggered pathology such as MH, but genetic evidence that these TRPV1 variations were responsible for MH was difficult to obtain for these cases. In the second family (N394del), RYR1 compound heterozygous mutations led to myopathy in the two children. Moreover, family members studied were limited, thus it is difficult to clearly establish a genotype to phenotype correlation. We have also shown previously that Ca 2+ release in skeletal muscle stimulated by the TRPV1 agonist capsaicin was a twophase process consisting of a first step of Ca 2+ release that is dantrolene resistant and a second step that is inhibited by dantrolene, which is a known inhibitor of RYR1 function.
ACKNOWLEDGEMENTS This study was supported by grants from the  French Ministère de l'Education Nationale  and the  Institut National de la Santé et de la Recherche Médicale. The study was part of the  OPeRa IHU B research program  ( ANR-10-IBHU-0004 ) within the  "Investissements d'Avenir " operated by the  French National Research Agency (ANR).
The x/y position of each single fly was tracked and analyzed using Drosophila ARousal Tracking (DART) software  (Faville et al. , 2015)  to evaluate the relative speed and activity before, during and after the stimuli event. The speed analysis is used for the "stimuli response trace" and the general activity was used to deduce "active speed," "mean bout length," and "interbout interval" (for details, see  Kottler et al. , 2017)  using a custom-made modification of the DART software  (Faville et al. , 2015). The DART-derived graphs were edited with Adobe Illustrator CC2017 (RRID:SCR_010279). Heat-induced seizure assay. The heat-induced seizure assay was adapted from one described previously  (Sun et al. , 2012). Ten flies per genotype were isolated into plastic vials with food 3 h before the assay.
Brains were dissected into Schneider's medium and transferred directly into a dish filled with Schneider's medium to be imaged. Confocal pictures of each brain were taken within 20 min after dissection. Z-stacks of 1 m sections were taken for each genotype. The microscope settings were established using control flies to have a GFP signal below saturation and kept unchanged throughout all acquisitions. These photographs were taken with a Nikon Spinning Disc confocal microscope and analyzed with ImageJ Fiji software (RRID:SCR_002285). A square of 166 ϫ   UAS-miR-1 ) and long-lived (UAS-miR-100) miRNA lines overexpressed in adult glial cells compared with the screen median lifespan. Each lifespan was done with 60 flies (30 females and 30 males; see Materials and Methods). Log-rank (Mantel-Cox) test p Ͻ 0.