dataesr/scientific-paragraphs-categorization huggingface dataset:
Methodology The two test scenarios defined in 3. 3 were instantiated and executed in order to collect data on two testbeds: Fed4Fire's w-iLab. t [30]  in Ghent and Inria's OpenTestbed  [26]  in Paris. The data collection procedure was as following. Each scenario was instantiated for a total of 30 nodes in a generic setting including the root of the network. Then, a mapping was provided for each testbed, consisting of the testbed node_id to use, as well as the radio transmission power that is to be configured by OpenBenchmark. Listing 1 illustrates an example scenario instantiation and its mapping on w-iLab. t testbed. The duration of each scenario execution was set to 3 hours and 30 minutes, with 30 minutes of allowance time for the network to form and stabilize before the benchmarking process would begin.
Conclusion The article presents the design of a benchmarking platform for IoT use cases OpenBenchmark and the benchmarking results of the reference implementation of the 6TiSCH protocol stack, the OpenWSN open-source project. OpenBenchmark is designed with end users in mind; it abstracts network and firmware specifics from the user and as an output presents the user with a set of KPIs relevant from the industrial point of view. The platform is also useful for evaluating research proposals using a well-defined methodology and a common set of KPIs. The source code of OpenBenchmark is available in open source. We used OpenBenchmark to evaluate the performance of the reference implementation of 6TiSCH in industrial monitoring and home automation test scenarios. Each scenario was executed in two different radio environments, Inria's OpenTestbed in Paris, France and w-iLab.
However, due to the lack of seismic data for these earthquakes, some were not displayed in the app. This lack of information and understanding of how the system functioned led to additional mistrust toward this citizen seismology tool. This paper combines sociological observations with an empirical approach. First, a sociological analysis of this independent citizen science network enables an identification of the reasons for its creation and the pitfalls caused by the absence of collaboration with the scientific community. Then, an empirical case study of the LastQuake system exposes how it has been improved to offer information, while admittedly more incomplete, is nevertheless closer to citizens' needs. It concludes that citizen seismology requires a stronger collaboration between citizens' and scientists' communities in order to be more efficient.
This was supplemented by a series of 10 semi-structured interviews  (Edwards and Holland, 2013)  2 with people living in Mayotte, in August 2018. The interviews aimed at getting insights on how citizens in Mayotte experienced the seismic activity and assess their satisfaction level regarding their information needs. Questions targeted citizens' perception of seismological actors and authorities, which were not primarily mentioned by the interview leader in order to identify the perceived legitimate FIGURE 1 | Seismo-sociological phases of Mayotte case study. Number of earthquakes corresponds to M>4 events displayed on LastQuake. Many more earthquakes were felt by the population but due to lack of sensors, no data was available. For phase 4, 20 additional earthquakes were displayed with no magnitude or location, thanks to the new version of the app.
Felt reports correspond to testimonies left by eyewitnesses on EMSC's services, including LastQuake. actors. The panel of interviewees is composed of a variety of profile in terms of geographical origin (born in Mayotte or in mainland France), age, gender and social background. It also includes a local journalist and an imam. Results have been pseudonymized; therefore, names have been changed. Consent to the publication of their quotes and indirectly identifiable data was obtained from the participants. All interviews were led in French. Interviewees were canvassed on social media, based on volunteering and on recommendations from other interviewees. This constitutes a bias as most interviewees are therefore globally more educated than the general population of Mayotte. Nevertheless, as part of a qualitative approach the study is not aiming to provide a representative picture of the situation, but to contribute to identifying key aspects of the context.
This intense seismic activity left everyone, scientists, authorities and the population, puzzled. Phase 2 runs from beginning of June to November 11. During this period, seismic activity continued but at a lower rate. LastQuake was able to display 68 M>4 earthquakes in the app during this phase. Seismologists and authorities set up an interministerial mission 3  to ensure that a reliable organization and logistical means would be operational in the event of a worsening of the seismic crisis. It was complemented by a scientific mission in order to explain the phenomenon. However, many citizens' questions remained unanswered. Indeed, despite the installation of three new seismic stations, data was often lacking on felt earthquakes and scientists needed time to conduct research. This was not well-understood by citizens.
Basic seismological concepts such as magnitude and intensity were explained in a pedagogical way. Comparisons with other earthquake swarms were made. Historical data about Mayotte seismicity was documented along with information about seismological knowledge limits, and safety measures to take. Citizens thus took the lead on collecting data and reviewing the existing scientific literature which they had access to. In addition, they also started to produce collated forms of knowledge, as one of the members started to list all felt earthquakes declared on the group and compare it to BRGM's seismic reports. Moreover, a few months after the beginning of the crisis, a user suggested launching a crowdfunding operation in order to equip the island with Raspberry Shakes. Raspberry Shakes are relatively affordable seismic sensors that can be installed easily in schools or in citizens' homes and that are used in many citizen seismology projects  (Calais et al.
LASTQUAKE, A CITIZEN SCIENCE PROJECT EVOLVING WITH CITIZENS An Innovative Citizen Seismology Project, Popular in Mayotte LastQuake is an innovative earthquake detection and information system developed by the EMSC. It is a multichannel system composed of a Twitter bot (@LastQuake), a mobile site and a free and ad-free mobile application. Its main goals are to provide information for the public as well as to collect data via 14 Accessible at: https://www. change. org/p/m-le-pr%C3%A9fet-de-mayotteplus-d-informations-et-de-communication-sur-les-s%C3%A9ismes-%C3%A0mayotte crowdsourcing. It detects peaks in web traffic and app launches that are characteristics of felt earthquakes. Indeed, when citizens feel an earthquake, they tend to look for information, quickly launching the LastQuake app, finding EMSC's website or tweeting about earthquakes.
, 2019 ). LastQuake's strategy of using visual content helps to address the challenges linked to its global distribution. Indeed, being used all over the world, the content must be as universally understandable as possible, regardless of language, cultural background, or literacy level. LastQuake is a pioneering citizen seismology project that uses digital technologies, especially social media. As the system uses crowdsourcing to detect felt earthquakes, citizens are placed at the core of its system  (Bossu et al. , 2011). It was and continues to be developed by seismologists, however, in order to efficiently develop these citizen science tools, users feedback is crucial  (Bossu et al. , 2019). Few weeks after the beginning of the seismic activity, more than 1% of the population in Mayotte had downloaded LastQuake, which is another sign of citizen's information needs  15.
These events have been designed in a way that underlines their specificity and their incomplete nature. They also follow the constraint that they must be understood at a global scale, regardless of cultural factors, language or literacy level. The term "earthquake" has been chosen from the beginning in order to stay simple and limit text in the app to keep it as universal as possible. However, if in most cases these events are indeed earthquakes, LastQuake can also detect felt shaking issued by sonic booms or meteors  19. EMSC will then consider replacing "earthquake" by "shaking" in the event description, which would require translation in every language available in the app. They appear in brown in the app, whereas events with complete seismic information are represented in a range of colors from green to red depending on their intensity and impact.
When associated with a magnitude and location they turn from brown FIGURE 6 | A new type of event has been implemented in LastQuake (in brown). Though incomplete, the presence of some information has been found to be essential to users. to their associated color. A seismic wave symbol is displayed instead of the magnitude to indicate the incomplete nature of the information (Figure  6 ). When clicking on this new type of event, users access the event page, stating that the earthquake has been felt, but that magnitude and location are not available yet (Figure  6 ). This implies that information will be updated when and if possible. Textual contents were translated into all languages available in the app. As for any event, users can contribute and share their experience, stating how intensively they felt it.
Even though magnitude mapping effects were found to be important information, they appeared secondary compared to the confirmation of the seismic nature of what eyewitnesses had just experienced. Additionally, EMSC's communication strategy has been revised in order to include materials explaining the nature of the detection system. Indeed, as LastQuake relies on the one hand on crowdsourcing and on the other hand on seismic data, citizens have to understand that not only are they a crucial part of the detection system, but also that no complete data can be published if sensors are lacking in a given region. This was made through a motion design video posted on social media and available on EMSC's website 20. It is accessible easily on Twitter as it is the @LastQuake pinned post on Twitter.
Understanding Information Needs and Cultural Background The example of both the STTM Facebook group and of LastQuake users' show that seismologists need to acknowledge citizens' questions and efforts in order to lead successful citizen seismology projects. Even though the public's expectations may not be realistic they can be managed. Seismologists could help leverage expectations by explaining the way they work, their constraints and what type of data they need. Re-asserting that, as of today, earthquakes cannot be predicted or that aftershocks will occur may be useful. In order to communicate efficiently, information needs must be assessed locally as they vary depending on cultural factors as well as previous knowledge and experience. Research has found that the type of information, the legitimate and trusted actor, as well as the way the public want to receive it will vary depending on risk culture, technology culture, gender roles, age or religion for instance  (Tagliacozzo and Magni, 2016; Appleby et al.
CONCLUSION To date, earthquakes in Mayotte have fascinated seismologists around the world for nearly 2 years. Due to an initial lack of data and understanding of the phenomenon, information had been scarce at the beginning of the crisis. In this very specific seismic and cultural context, citizens, experiencing a high level of anxiety, expressed high information needs and expectations toward the scientific community. Facing an information vacuum, they seized the opportunity to use already existing citizen seismology tools such as LastQuake. They also launched their own network through Facebook. Due to a certain level of mistrust toward seismologists and communication failures, they created a community of citizen seismologists, without initially conceptualizing it as such. The reasons for the creation of such a group should call to mind seismologists as well as all citizen seismology actors, including authorities.
In addition, most of the research results are based on simulations and implementation on hardware is still lacking  [18]. Li Q. et al. in  [9]  implemented an FLC model in the Advisor platform. They proposed two structures: FC/BAT and FC/BAT/SC in order to increase the fuel economy and the mileage considering driving modes to design the fuzzy parameters. Results show better performances for these two proposed structures than the power tracking controller (PTC_ADV) embedded in the Advisor software. Hemi et al. in  [6]  propose three configurations: FC/BAT, FC/SC and FC/BAT/SC. These models are implemented in a modified Simulink model proposed by Tremblay et al. in  [21]. They are evaluated in real time driving cycles, simulation results show that the proposed models satisfy the power requirement.
The last configuration enables a fast charging and discharging which improves the battery lifespan. Zhang G. et al. in  [25]  propose a fuzzy EMS for a FC/BAT hybrid locomotive based on the Advisor software. They use the Advisor auto-optimization method to optimize the size of the FC and the Acid battery in order to improve their efficiencies and the fuel economy. They use a fuzzy model to control the power flux between these sources. A comparison of results between the developed models with the power following strategy (PFS) under a real operating subway's driving cycle shows an improvement of fuel economy, dynamic priorities, and a large increase of FC efficiency. However, the battery, as well as other components' efficiencies, decrease in comparison with PFS. In these previous studies, the selection of the fuzzy parameters is not focused enough.
In this work an energy management and monitoring strategy is presented, based on fuzzy first order of Sugueno, its membership function and weights are selected by PSO. The main objectives of this development are to tune the fuzzy EMS under different conditions to maximize the fuel economy mile per gallon (MPG) and maintain the SOC variation in the lowest range at the end of the trip while keeping the vehicle performance. The development of the fuzzy EMS model is implemented in the Advisor simulator software. Four driving cycles are engaged independently and altogether in the optimization process. Therefore, five tuned fuzzy are obtained and evaluated under the considered driving cycles. In this paper, the second section introduces initially an overview of the proposed approach followed by a description of the FCHEV model in the Advisor.
We aimed at measuring the impact of a school-based sleep education program (ENSOM: 'EN' for 'ENfant' and SOM for 'SOMmeil' in French)  on sleep, cognitive functioning and academic performance in children. In contrast with existing sleep education programs, ENSOM was designed by sleep experts with the intent of being autonomously achieved by teachers. One-hundred and thirty children aged 8-9 years took part in control versus ENSOM interventions. Compared to the control intervention, total sleep time was extended by 31 minutes per night, sleep efficiency improved by 2. 9%, and sleep latency and wake after sleep onset were shortened by 7. 7 and 4. 5 minutes respectively after the ENSOM program. Sleep improvement remained significant at one-year follow-up. Attention, executive functioning, academic performance and parents' sleep knowledge also improved significantly.
, 2015). Few studies investigated the effect of sleep education in younger children. The Canadian program 'Sleep for Success' explored the effect of sleep education conducted in primary school. The program consisted of 6 interactive interventions of 2-hours duration given by 'sleep-experts' (physicians, researchers or trained teachers) over a 6-week period. This program succeeded in extending sleep duration, increasing sleep efficiency and improving results in mathematics and English in children who participated to the program compared to a control group matched in age  (Gruber, Somerville, Bergmame, Fontil, & Paquin, 2016). However, the need of 'sleep-experts', who directly conduct the program or train teachers or parents, might prevent a wild use and dissemination of such programs. We created a sleep education program  (ENSOM program: 'EN' for 'ENfant' and SOM for 'SOMmeil' which means 'child' and 'sleep' in French)  integrated into primary school curricula, which can be autonomously conducted by teachers, without the intervention of 'sleep-experts'.
Participants A total of 130 school children aged 8 to 9 years (Mage = 8. 43, SDage = 0. 29; 62 girls), all in third grade of 5 primary schools, participated in the study (Nschool 1= 26, Nschool 2 = 25, Nschool 3 = 25, Nschool 4 = 28, Nschool 5 = 26). There were two rural schools (schools 1 and 4) and three urban schools (schools 2, 3 and 5). Exclusion criteria were history of psychiatric or neurological illness, developmental disorder, learning disability or reported sleep disorders, according to parental reports. One child initially included in the study was later diagnosed ADHD. As the other children, she took part in the lesson, but her data were excluded from the analyses. This experiment was approved by the Ethics Committee of [information removed for reasons of anonymity]. All the children and their parents gave their written informed consent.
ENSOM sleep education program The ENSOM program was based on a multidisciplinary and collaborative approach involving children, parents, researchers, sleep physicians, primary school teachers, as well as art school students who produced the illustrations. During the construction process, each lesson was systematically pretested by the teachers with their students (N = 62) and, following their feedback, improvements were introduced when necessary. During this 'pre-testing', children evaluated their satisfaction about the program at 4. 60/5 ± 0. 05. The teachers involved in the construction of the ENSOM program were not the same than those who took part to the experimental protocol. The sleep education program was developed to build awareness and understanding of the importance of sleep in children and their teachers, but also to help children to become responsible for their sleep and health.
The ENSOM package contained a 30-page training manual for teachers with complete information about sleep, a step-by-step description of each lesson and eight structured lessons (8 cartoons and 8 comic-strips) covering four themes: the sleep rhythms, the role of sleep, the need for sleep and the friends and foes of sleep (2 lessons per theme). Sleep tips were presented to the children at the end of each lesson to promote good sleep practices (see Table  1 ). To encourage the interactions between children and their parents regarding the sleep education program, children had three occasions to collect at-home information about their own sleep and the sleep of family members.
Sleep assessment Each child was requested to wear a wristwatch-like device (Actiware 2, Philips Respironics, Bend, OR, USA) on the non-dominant wrist for 1 week (5 school days and 2 weekends) at the 5 time points. Sleep was recorded during nights preceding school days (Sunday through Thursday) and during weekends (Friday and Saturday). Actigraphy has been shown to provide a valid estimate of sleep patterns in children and adolescents  (Meltzer, Montgomery-Downs, Insana, Salvatore, & Walsh, Colleen, 2012). The Actiware 2 devices are equipped with an event marker and a light sensor. At night, when children were in bed ready to fall asleep, they were told to use the event marker to indicate their bedtime. In the morning, when they woke up, they were instructed to mark the actigraph again. All actigraphy data were visually reviewed by a sleep specialist and bedtimes were checked according to the event marker, the sleep diaries completed by the children and the data from the light sensor (in particular when children forgot to push the 'bedtime button').
Actigraphic sleep data were analyzed in 30-sec epochs using Actiware Sleep software 6. 0. 9. Epochs with activity count equal or below the threshold sensitivity value set at 40 (medium sensitivity), were scored as   & Fischer, 2015). Analyses were performed on actigraphic data when at least four nights (including at least one during the weekend) were available. Among the 105 children recorded between T1 and T4, 79,5% reported usable data (T1= 76. 2%; T2= 89%: T3= 88. 6%; T4= 67. 6%). From the 85 recordings at T5, 70,6% were usable. 89% of missing data resulted from partially missing data (< 4 nights), the remaining corresponded to a complete loss of the recordings.
Discussion The overall aim of this study was to evaluate the beneficial effect of a school-based sleep education program conducted by teachers without sleep expert's intervention on children sleep and on their cognitive and academic performance. Our main findings are that the ENSOM program was effective in inducing changes in sleep habits and increasing cognitive and school performance. Children's sleep duration was significantly extended by an average of 31 min per night following sleep education, and this improvement was maximal in children with shorter sleep duration at baseline. This beneficial effect was also larger during school days than weekends. Sleep efficiency was enhanced by 2. 9 %, due to a significant shortening of 12. 2 min in the time spent awake after bedtime (SOL and WASO).
, 2018). Because executive functioning is also crucial for emotional and behavioral self-regulation, it would be interesting to evaluate whether the ENSOM program results in behavioral changes at school. In our study, memory performance was the only cognitive measure that failed to improve after the sleep education program. While the improvement in executive functioning and attention resulting from sleep may be big enough to be detected with relatively simple tests, the change in memory performances may have been too subtle to be detected with our tasks, which involving only a relatively low cognitive load  (Blunden, 2017). Alternatively, of course, it may well be that memory performances were genuinely unchanged despite the improvement in sleep. To fully assess the preventative potential of school-based programs, studies need to determine if the effect on sleep persists in the years beyond those of the intervention.
Indeed, purely introspective data (questionnaires or diaries) may fail to detect significant improvements in sleep duration or efficiency, including in the long term, that can easily be observed with actigraphy. The co-construction of the ENSOM program with educational professionals, researchers and families was, in our opinion, the key factor in its success (e. g. ,  Mcdowall, Galland, Campbell, & Elder, 2017). Several studies conducted in schools reported difficulties in engaging schools, teachers and parents  (Gruber et al. , 2016). Interestingly, while our program was performed during school time, it also increased parents sleep knowledge. The present study does not allow determining by what means parents increased their sleep knowledge and how this contributed to improve their children sleep habits.
Acknowledgements We sincerely thank the children, parents and teachers for participating in this study. We thank  Marie-Josèphe Challamel ,  Patricia Franco ,  Aurélia Guichard  and the members of  Réseau Morphée  for the proofreading of the sleep educational package. Thank you to  Chloé Rippol ,  Lisa Rongen ,  Clémence Vincent  and  Julie Saine  for their help in the process of actigraphic data. Finally, we would like to thank  Dr Hélène Bastuji  and  Dr Michel Magnin  for her comments on the manuscript.