dataesr/scientific-paragraphs-categorization huggingface dataset:
Despite the above mentioned limitations, this study also has a number of strengths. To our knowledge, this study quantified for the first time mismatch at neighbourhood level by comparing aggregated residents' perceptions and objectively measured data from an innovative and comprehensive validated virtual audit tool  24. Additionally, perceptions of environmental features were collected from a large population in the audited areas. The standardized data collection (survey and virtual audit and) across heterogeneous neighbourhoods led to a comparison of different measures of built environment across European regions and neighbourhoods. In conclusion, this study shows moderate agreement between perceived (residents' perceptions) and objectively measured (based on a virtual audit) obesogenic built environment features.
Methods We selected countries for which comparable data on mortality, as well as income by education, were available for the same time periods (or slightly later for mortality than for income) and for at least two points in time. Our study covers six countries, representing different European regions: Belgium, Denmark, England & Wales, France, Slovenia, and Switzerland. Years of income measurement are shown in Table  1  and periods of mortality data are shown in Table  2. We calculated rates for all-cause and cause-specific mortality for four causes of death: cardiovascular diseases (CVD) (code of the 10th Revision of the International Classification of Diseases I00-I99), cancer (C00-D48), external causes (V01-Y98) which are mainly composed of deaths from accidents, violence, and suicide. Our mortality data covered the whole population, except for England & Wales and France, where a 1 % representative sample was used.
5. While for most countries and years income was measured as a continuous variable, Denmark used 12, 17 and 13 income categories (in 1994, 2000 and 2005 respectively), England & Wales used 21 categories in 1990 and then adopted a continuous measurement, and France used 12 categories. This categorical data was translated into continuous amounts by taking the midpoint of each income category. For the highest and open category an algorithm was applied that takes into account the overall income distribution. The trends of income inequalities for England & Wales showed no jumps between years in which categories were used (until 1990) and years with continuous measurement (1996 onwards), suggesting that a high number of income categories limits the bias due to the categorical measurement. In order to compare absolute income differences across periods and countries, the given amounts from the survey data have been adjusted by purchasing power parities (PPP) by the OECD [47] to be interpretable as comparable US dollars.
The recent availability of large databases allows to study macroscopic properties of many complex systems. However, inferring a model from a fit of empirical data without any knowledge of the dynamics might lead to erroneous interpretations  [6]. We illustrate this in the case of human mobility [1-3] and foraging human patterns  [4]  where empirical long-tailed distributions of jump sizes have been associated to scale-free super-diffusive random walks called Lévy flights  [5]. Here, we introduce a new class of accelerated random walks where the velocity changes due to acceleration kicks at random times, which combined with a peaked distribution of travel times  [7] , displays a jump length distribution that could easily be misinterpreted as a truncated power law, but that is not governed by large fluctuations.
On the other hand, the first question, generally characterized by the distribution of the spatial displacements P (∆r) across all users, although apparently simple is still far from being completely understood. Indeed, even if the study of P (∆r) has become a trademark for recent studies on human mobility, there are still no consensus about the functional form of this distribution. At a large scale (national or inter-urban), one may observe a long tail behavior  [1, 2, 8, 34, 37, 38, 40, 41, 43]  characterized by a power law decay for long displacements. At a smaller (urban) scale, the distribution seems to have an exponential tail  [15-17, 35, 36, 42, 43]. The unclear nature of this probability distribution makes its interpretation difficult and dependent on the dataset used, the scale and possible empirical errors (see Table  I ).
In this paper, we show that the observed truncated power laws in the jump size distribution can be the consequence of simple processes such as random walks with random velocities  [24]. We test this model over a large GPS database describing the mobility of 780, 000 private vehicles in Italy, where travels and pauses can be easily separated, as the transition is identified by the moment when the engine is turned on or off (but we introduce a lower threshold of 5 minutes in the elapsed time, to distinguish real stops from accidentaly switched off of the engine during a trip). This allows us to evaluate accurately not only the displacements ∆r, but also travel-times t, speeds v, and rest times τ. We first analyze the distribution P (t) of the travel times of individual vehicle in different cities.
Displacement distribution Finally, the shape of the displacement distribution P (∆r) can be computed as a superimposition of Poisson distributions (see Fig. 6 right ) P (∆r) = ∞ 0 dt v2 v1 dvδ(∆r -vt)P (t)P (v|t) = ∞ 0 dt tt exp -p + 1 t t + log(p t) ∆r/t-v0 δv ∆v Γ 1 + ∆r/t-v0 δv ( 6 ) where δ is the Dirac delta function. The exact form for Eq. (  6 ) cannot be analytically computed but the limiting behavior of for large ∆r is again Eq. (  3 ) (see Supplementary information). In particular, this distribution is not broad, FIG. 6 : Distribution of displacements (Left). We show (blue circle) the aggregated empirical distribution P (∆r) for all the ≈ 780, 000 cars in our dataset. The orange dashed line represents a fit with a truncated power law of the form P (∆r) ∝ (∆r + ∆r0) -β exp(-∆r/κ) with β = 1.
Private Transportation Data We compute spatial displacements and travel times for private transportation from a database of GPS measures describing the trajectories of private vehicles in the whole Italy during the month of May 2011. This database is mainly set up by private vehicles, since Taxi or delivery companies use their own GPS systems and do not contribute to the database. A small percentage of vehicles belongs to private companies and are used for professional reasons. This database includes ≈ 2% of the vehicles registered in Italy, containing a total of 128, 363, 000 trips performed by 779, 000 vehicles. Records contain information about engine starts and stops, and travel-times also include the eventual time spent looking for parking. When the quality of the satellite signal is good, we have an average spatial accuracy of the order of 10 meters, but in some cases it can reach values up to 30 meters or more  [31].
We display here the values for all cities with at last 500 drivers that are monitored. The average travel-time (computed here over all trips in a given city) is in the approximate range  [9, 18]  minutes. These values are correlated r = 0. 40 with the city population. The solid line represents a fit for a power law t ∝ population γ with γ = 0. 07 ± 0. 02. 0 0. 5 1 1. 5 2 2. 5 10 -4 10 -3 10 -2 10 P (t) ∝ (1 -exp(-t/c)) exp(-c exp(-t/c)/b -t/b) proposed in Dependence of velocities over time in public transportation. We estimate velocities for public transportation trips from an open dataset providing a complete snapshot of the multilayer temporal network of public transport in Great Britain in October 2010  [52]. This dataset assumes a waiting time before a flight of 2 hours, a waiting time after a flight of 30 minutes and, where not explicitly defined by the transportation agencies, a walking distance of 250 m.
The starting time in our analysis of a week is Monday, 8am. Starting from that time, we consider for all trips from a node i to a node j, the time spent in transportation after departing from the node i in any direction. The shortest time-respecting path  [30]  is then identified with a Dijskstra algorithm, where also the time spent walking (at 5 km/h) between two adjacent stops of any modes of transport and the time spent waiting at the connection is integrated to the total travel-time. The euclidean distance between origin and destination is then used for estimating velocities. Both the averages and the distribution of Fig. S3  are not computed on real flows, which are not available with the same spatial extension and definition of the dataset. In this study, we implicitly assumed a uniform travel demand by including all possible origin-destination pairs.
After that, pig farming, in XWG, relied on local livestock and a gradual change of husbandry practices overtime. This was characterized by a gentle increase in millet foddering and animal protein intake, until a complete change over to household management during the Han dynasty. The only rupture in this steady trend of husbandry occurred during the Longshan period, with the appearance of small sized and idiosyncratic pigs with specific feeding practices (relying on millet and household scraps). From three exploratory hypothesis, we explored the possibility of anti-elite pig production in XWG during the Longshan period, as a means to resist incorporation into a new economic model promoting intensified domestic production. This exploratory hypothesis is the most suitable to our dataset; however, numerous areas need to be explored further in order to adequately document the role of pigs in the rise of China's complex societies.
All the archaeological specimens are deposited in the Institute of Archaeology of the Chinese Academy of Social Science (IA CASS), 27 Wangfujing Street, Beijing, 100710, China, under the responsibility of one of the co-authors, Pr Yuan Jing. The museum reference numbers and the archaeological contexts for each specimen from this study can be found with the GMM dataset available at Figshare (doi: 10. 6084/m9. figshare. 3394915. ). Domestication and population changes through dental GMM. In order to track the domestic process and population changes in the archaeological record of the XWG and XZ sites, we used the second lower molar (M 2 ) as a phenotypic marker to track population history  [10, 24] , since its development shows less ecophenotypic plasticity than M 3. Furthermore, M 2 are measurable in wild and domestic pigs of between one and three years; while M 3 is only be measurable in specimens over two years  [38] , which is another advantage to document domestication and husbandry processes.
The form of M 2 was quantified with a geometric morphometric approach of its 2D occlusal view  [10] , combining landmarks on anatomical points located on the occlusal surface and semi-landmarks  [39]  equidistantly sampled along the external outline of the crown's occlusal view. All the forms' configurations were standardized with a Procrustes superimposition to obtain comparable shapes cleared from scale, position and orientation. The semi-landmarks were slid on tangent lines to the crown's outline using the bending energy sliding method  [40]. The new set of shape (Procrustes coordinates) and size (centroid size) variables obtained after the Procrustes superimposition provided the input dataset for statistical analyses. The centroid size of the molar was computed as the square root of the sum of the squared distance of each landmark and semi-landmark, to the center of gravity of the points' configuration.
However, according to this proelite hypothesis, we would expect to see an increase in pig size during the Longshan period, along with an increase of their occurrence in burials (due to feasting) as a display of political power. On the contrary, our dataset shows a drastic decrease in pig size, and the archaeological evidence suggests a decline of pigs in burials during the Longshan period  [77]. Indeed, during the Chinese Neolithic, the interment of pig skulls or of complete animals within human burials (as a display of social status differentiation) reached its peak during the Middle Neolithic, and then reduced during the Longshan, in both the Shandong  [77]  and the middle Yellow River  [78, 79]. This suggests that the Longshan elites did not invest in mortuary events to demonstrate their political and social power, but preferred to concentrate on the construction of community buildings and defensive walls which required greater public input  [80].
Therefore, this pro-elite hypothesis is supported neither by our morphological dataset nor by the available archaeological record. The second sociopolitical pathway is an anti-elite hypothesis which considers that pig production in a farming village, such as in XWG, could have been a way to avoid the incorporation of new economic models dictated by rising political authorities  [81, 82]. Household pig production, relying on domestic and farm refuse  [83] , would have provided farming communities with the flexibility to adapt to unfolding changes and/or evade enforced directives  [84]. This anti-elite hypothesis would better suit our results for two main reasons. Considering the deleterious effect of confinement and poor diet on a suid's body growth  [85] [86] [87] , a household management system could have induced developmental changes that would explain the drastic size reduction and morphological divergence from the free-ranging herd.
Among the climatic and politico-economic hypotheses we presented, our dataset seems to support the anti-elite hypothesis of XWG's pig production being used as a barrier against the new economic model of intensive domestic production driven by the Longshan elite. However, our discussion must be viewed as exploratory. Further multidisciplinary studies covering as much cultural and sociopolitical entities as possible, are required to fully understand the role played by pig husbandry in the making of China's complex societies.
Acknowledgments We are most grateful to  Curator Kang Le ,  Institute of Zoology, CAS; Curator Zhou Zhonghe, Institute of vertebrate paleontology and paleoanthropology, CAS  for allowing us access to modern sample samples of domestic pigs and wild boars. The ERAnet (https://ec. europa. eu) Co-Reach  project  n°137  ( European-Chinese Bioarchaeological Collaboration, Euch-Bioarch ). We would also like to thank  Allowen Evin  ( CNRS-ISEM ) for her technical support in the image acquisition of molars for the GMM study. This research was carried out within the framework of the joint CNRS- CAS program  for the training of Chinese PhD students.
(2015) , groups of persons less than 10 years old and over 75 years old are more fragile and evacuation is more difficult if this should be necessary. The same applies to people with reduced mobility. Persons in makeshift shelters are also more fragile and more exposed to all kinds of risk  (Rufat 2007). Furthermore, education level was also used as an indicator of the ability to find solutions in case of catastrophe, with capacity being proportional to this level  (Cutter et al. 2003; Kreimer et al. 2003; Borden et al. 2007 ), leading us to taking into account the population of persons over 15 years old with no qualifications. For human assets, this hierarchical structure was constructed using the INSEE census at the scale of IRIS 1 (the last census available (2011) has been used here). Information on environmental and equipment assets were drawn from the GIS database for Greater Lyon.
These facies, connected to a paleoshoreline with cliff and deep cavities cut into older formations, record a sea level highstand that predates OIS 15  [61, 62]. Between 1994 and 2011, several new hominin fossils were recovered from stratigraphic Unit 4. In addition to the femur described below, they consist of several isolated teeth, cranial fragments, vertebrae, a complete mandible of an adult and a partial mandible of a young child. Laser ablation ICP-MS dating combining ESR and U-series data for modelling U-uptake has given a US/ESR age of 501 +94  76 ka for a human premolar, while OSL measurements indicate an age of circa 400 ky for embedding sediments. Nevertheless, biochronological and lithostratigraphic evidence point to a greater antiquity, closer to the base of the Middle Pleistocene  [65, 66].
Shi et al. (2013)  analyzed a large pedigree with two sons affected with ASD and six unaffected siblings, focusing on inherited mutations. They identified ANK3 as the most likely candidate gene. In 2015, Yuen et al. analyzed 85 families with two children affected with ASD. This study represents the largest published WGS data set in ASD. They identified 46 ASD-relevant mutations present in 36 of 85 (42. 4 %) families. Only 16 ASD-relevant mutations of 46 (35 %) identified were de novo. Very interestingly, for more than half of the families (69. 4 %; 25 of 36), the two affected siblings did not share the same rare penetrant ASD risk variant(s). Whole genome sequencing is also very efficient to identify mutations in regions of the human genome that are wrongly annotated and in regions that are highly GC rich.
Acknowledgments We thank  Roberto Toro  for critical reading of the manuscript. This work was funded by the  Institut Pasteur , the  Bettencourt-Schueller foundation ,  Centre National de la Recherche Scientifique, University Paris Diderot ,  Agence Nationale de la Recherche (SynDiv-ASD) , the  Conny-Maeva Charitable Foundation , the  Cognacq Jay Foundation , the  Orange Foundation , and the  Fondamental Foundation.
Field settings range from sportscards shows  (List and Lucking-Reiley, 2000)  to primary schools  (Angerer et al. , 2013)  to online labor markets  (Chen, 2012)  to financial trade fairs  (Cohn et al. , 2015). The field provides external validity and taps a subject pool other than students. It is difficult to take a Windows-desktop networked environment to field settings. This has required either ad hoc programming solutions and thereby hindered experiments. The situation for field experiments is akin to what the situation for laboratory experiments was prior to the release of z-Tree. Second, computing devices have seen a sea change in the last years. Usage has shifted from desktop computers to phones and tablet computers. Graphics and user interfaces have been revolutionized. This calls for software that is platform-independent and deployable on these devices.
Third, the programming paradigm has shifted. It is now clear that open-source and industry-standard compatible solutions are a better fit for many scientific needs. Experimental software should use existing industry-standards wherever possible, be extensible and compatible with plug-ins and allow users to inspect the source code. oTree addresses these desiderata. oTree has been used in the laboratory setting with over a thousand participants in actual experiments at laboratories in Zurich, Magdeburg, and Hamburg. Papers using data gathered by oTree in the laboratory now include  Chen and Schonger (2014a) ,  Chen and Schonger (2014b) ,  Chen and Schonger (2015a)  and  Chen and Schonger (2015b). In addition to the laboratory, oTree has also been used for experiments on Amazon's Mechanical Turk.
Thus, several new features have already been successfully demonstrated: The flexible and easy implementation of graphical and experimental features, such as different background colors and randomization of graphical elements in the presentation, has been shown to work. Second, the mobility of the setup was shown by running the same or similar experiments across various laboratories. oTree is open-source, licensed under an adaptation of the MIT license. 2  We ask that people cite this paper when using oTree for academic or other publications. The source code for oTree can be downloaded for free at www. oTree. org. Contributions and improvements to the source code are welcome and should be submitted via GitHub.
I. Usage: Lab, online, field, and classroom The basic experimental setup in oTree consists of (i) an experiment written within oTree, (ii) a server computer, which can be a cloud server or a local laptop and (iii) subjects' devices with a web browser. oTree creates an experimental session on the server, as well as links for all the participants and the experimenter. With these links, participants are sent to individualized web pages displaying the experiment and recording their answers. The experimenter accesses the Progress Monitor, where real-time information about the progress and entries of all participants is displayed. This architecture enables oTree to be used in almost any experimental scenario. The software and hardware requirements of the laboratory are minimal: only a connection to the server and a browser are needed, no other software needs to be installed.
It is sufficient to either have an internet connection or a local area network, both are not necessary. The architecture is also robust to failure; if, for example, there is a hardware failure on anything but the server, the link of that participant or experimenter can be loaded immediately on another device. Section II lists the most useful oTree features. There are many ways in which oTree is an improvement over existing instruments, many of which might only be appreciated in actual usage. An easy way to get a first feel for oTree is to play some games from the library of dozens of sample games. Not only is the code for these sample games available, but these samples are online using oTree's demo mode. This means that anyone can play them at any time using a web browser without any installation whatsoever.
The library of sample games can be found at http://demo. otree. org/demo/. One example of a sample game is our implementation of  Basu (1994) 's traveler's dilemma. Via the sample game website, go to http://demo. otree. org/demo/traveler dilemma/, which hosts the program in demo mode. On that start page there are two start links, one for each of the two players in that game. One can play both players using different tabs in a browser, or open the links on different devices. Section III elaborates on programming in oTree. Almost any graphical or design feature can be implemented (i. e. , visual styles, animations, dynamic adaptation to screen sizes, and multimedia). oTree's user interface is based on HTML5, which is supported in all modern browsers and is familiar to every web developer and designer.
The programming language used in oTree is Python, an easy-to-learn modern object-oriented computer language widely used in science for analysis and modeling. Hence, many researchers already possess the necessary programming skills to use oTree, and will require little time to learn to use oTree efficiently and to implement experiments. oTree is easy to use, and even complex experiments are reasonably easy to program by taking advantage of the capabilities of Python. oTree is based on the Django web application framework; oTree applications are web applications. Once oTree is installed on a web server, applications can be played instantly from any web browser by opening the game's URL, and experimenters can log in to the admin dashboard from anywhere to monitor the experiment. oTree works on any device with a modern web browser, whether it is a desktop, tablet, or smartphone.
It works on all major operating systems, including Windows, Mac OS X, iOS, Android, and Linux. The user interface automatically adjusts to the appropriate screen resolution, eliminating the need for every application to have separate designs for desktop and mobile platforms. oTree is built to last. The source code is highly organized and follows best practices, allowing for easy further development and extension. Features are added sparingly and with thought to long-term needs. It is also robust to changes in the market share of various technologies. Some software tool sets require a particular software program to run on the client machine, such as Windows, Java, or Flash. These tool sets risk becoming obsolete when the market share of that platform declines. In contrast, oTree only requires a web browser on the clients' devices.