dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgements Thanks to  Martina E. Pocco ,  M. Celeste Scattolini ,  Luis A. Giambelluca  and  Jorge A. Barneche  for their help with fieldwork as well as  Vanesa Di Gerónimo  for her lab assistance. Authors also appreciate the comments of two anonymous reviewers that improved this note. This study was funded by  Agencia Nacional de Promoción Científica y Técnica  ( PICT 2016-0289  and  PICT 2019-3521 ) and  CONICET  ( P-UE 22920160100036CO ). Samplings in protected areas of  Río Negro  province were carried out under provincial permit No  80/2016 DF/FS.
Acknowledgements We are grateful to  Trinity University  students  Ernest "Michael" Leonard  and  Sean Cassingham  for their work formatting and submitting an earlier draft of the manuscript and to  Mariana de Melo Siqueira  for designing Fig. 1. We also appreciated the feedback for improvements provided by  Brandon Bestelmeyer ,  Matt McCaw , and  Lars Brudvig  to an earlier draft of the manuscript. PT was supported by the  Hungarian Academy of Sciences,   Momentum Program , by the  Hungarian Research Found  ( NKFIH K 137573  and  KKP 144068 ) during manuscript preparation. KGL supported by  USDA NRCS   NCAT Soil for Water Grant  ( NR203A750001C025 ) during manuscript preparation. GEO is funded by the  Brazilian Conselho Nacional de Desenvolvimento Científico e Tecnológico  ( CNPq  grant  310345/2018-9 ).
To make this task more appropriate for the Chinese participants, we made two minor modi cations to it. One modi cation related to the actual numbers used in the monetary gains. We used the Chinese currency (¥) to denote the varying amounts of monetary reward at stake: the low amounts were ¥10, ¥15, or ¥20 and the high amounts were ¥80, ¥85, or ¥90. The other modi cation is related to erotic pictures. We selected high-and low-intensity erotic pictures from a recently released Chinese erotic picture dataset 48. Similar to our previous work, the low-intensity erotic pictures displayed Chinese females in underwear or bathing suits, while the high-intensity pictures displayed naked females in an inviting posture.
Statistical analysis Independent sample t-tests were employed to examine between-group differences in age, income, IELT, PEDT, IIEF-5, SAI, BDI, and SAS. For behavioral data (accuracy, reaction times, and hedonic ratings), three separate mixed analyses of variance (ANOVA) were performed, with group as a between-participants factor (lifelong PE patients versus HCs) and reward type (erotic versus monetary rewards), reward intensity (high versus low), and reward probability (25% versus 50% versus 75%) as within-participants factors. All data were analyzed using IBM SPSS 23. 0 (IBM Corp. , Armonk, NY, USA). Statistical comparisons were made at p-values of p < 0. 05, with the Greenhouse-Geisser correction when violations of sphericity occurred.
Statistics Fish count data were used to describe differences in species assemblages between the three types of sites under varying human pressures using a Non-metric Multi-Dimensional Scaling analysis (NMDS). This analysis was performed on the Bray-Curtis similarity matrix using the vegan package in R (version 2. 6-2,  Oksanen et al. 2020). One-way analyses of similarity (ANOSIM) with 9999 permutations were then used to investigate potential differences linked to the month, restriction period, and site. The normality and homogeneity of the variances of density and species richness for both all species and harvested species were verified using Shapiro-Wilk's and Bartlett tests respectively. When normality was not met, the data were square-root transformed, and two-way ANOVAs were used to test the effect of the four restriction periods, sites, and their interaction on density and species richness of adults and juveniles.
If significant interactions were found, a contrast analysis was performed (emmeans package in R, version 1. 8. 3) to identify where these differences appear. In the absence of significant interactions, Tukey's HSD post-hoc tests for multiple pairwise comparisons were performed to identify significant differences for each factor. If the raw and transformed data both did not reach normality, non-parametric Kruskal-Wallis tests were used to compare density and richness between the four restriction periods, and between the three categories of sites (no interaction). When a significant effect was found, Dunn's post-hoc tests for multiple pairwise comparisons with Hochberg's correction (FSA package in R, version 0. 9. 3) were performed in order to identify the differences driving this effect. Species which were most responsible for the differences in fish community composition between groups were identified through an indicator species analysis using the "multipatt" function of the indicspecies package (version 1.
Funding: This work has received several grants:  Fondation de France  ( 2019-08602 ),  Office Français de la Biodiversité  ( AFB/2019/385 -OFB. 20. 0888 ),  Polynésienne   des Eaux ,  ANR-19-CE34-0006-Manini  and  ANR-19-CE14-0010-SENSO ,  ANRT grant  ( CIFRE 2021/1268 ).
Four additional electrodes were used to monitor eye movements and blinks (two placed at lateral canthi and two below the eyes), and two additional electrodes were used for an offline rereferencing (placed behind the ears on the mastoid bone). Continuous EEG was digitized at 1,024 Hz. The EyeLink and BioSemi systems were jointly controlled using OpenSesame on the master computer which sent triggers to the EyeLink through an ethernet cable and to the Bio-Semi software via the parallel port. We used optocouplers (The Black Box Toolkit V2, The Black Box Toolkit Ltd, Sheffield, UK) to synchronize the triggers with a delay of less than 5 ms (validated in previous studies at our lab). The synchronization of the triggers enabled a tight coupling of the eye-movement and EEG data. Raw oculomotor data was parsed into oculomotor events (fixations, saccades) using the default Eyelink software settings.
Oculomotor measures of interest From the eye-tracking data we retrieved the following measures of interest for the target word: the First Fixation Duration (FFD; the duration of the first fixation on the word, reflective of early processing), the Gaze Duration (GD; the summed durations of all fixations on the word during the first pass, reflective of word recognition), the Skipping rate (with greater processing difficulty come fewer skips) and the Refixation rate (with greater processing difficulty come more fixations) (for more information about these measures, we refer to the review of Rayner, 1998).
Pre-processing of EEG data We used the EEGLAB toolbox (version 14. 1. 2 b;  Delorme & Makeig, 2004)  for MATLAB (version 2019b; The MathWorks) to pre-process the EEG data. 4 Ahead of an Independent Components Analysis (ICA), the EEG data were downsampled to 500 Hz and time-aligned with the eye-tracking data using the EYE-EEG toolbox  (Dimigen, 2020). The data were then rereferenced to the averaged mastoids and band-pass filtered between 2. 5 and 100 Hz using the built-in pop_eegfiltnew function in EEGLAB. Anomalous data segments were detected using the pop_clean_rawdata function. These training data underwent pre-saccadic potential overweighting, followed by ICA training according to the procedure proposed in  Dimigen (2020). ICA otherwise used the default settings in the EEGLAB runica function.
EEG analyses EEG data were analyzed with a cluster-mass permutation test using the Mass Univariate ERP Toolbox  (Groppe, Urbach, & Kutas, 2011)  in Matlab. The mass-univariate approach yields a t-statistic over time (sampled at 250 Hz) that reflects whether our established condition difference deviates significantly from a distribution of condition differences sampled from 2500 random permutations of the same data. All 64 scalp electrodes were included, and the test was conducted from À200 to 1000 ms. Spatial neighborhood was prepared using the ft_neighbourselection function with a neighborhood threshold of 40 in chanlocs space. Our two-tailed test used a family-wise error rate (FWER) and p-threshold for cluster inclusion of. 001. We have plotted beta weight traces and topographies in Fig.
Each step up corresponds to 1kV and lasts t ≈ 5sec. The rise time of the Keithley427 is set at 0. 01s and the output is sampled by the acquisition program and averaged (see Section III C). The control and acquisition program is written in Labview2011 version 11. 0. 1 interfacing a National Instrument analog and digital input/output card (USB-6009). After acquisition, data are processed and plotted using Igor Pro 9.
B. Effective pumping speed measurements The effective pumping speed  13  S e , needs to be known in order to plot the conductance. It is measured by monitoring the (exponential) decay of P l p after closing the valve between the highand low-pressure chambers, upstream of the CIS itself. Straightforwardly, neglecting the final limit pressure in the low-pressure chamber: P l p = P l p0 exp(- S e V t) (where P l p0 is the initial pressure and V is the volume of the low-pressure chamber). Starting from typical P l p0 = 10 -2 Pa, P l p decreases in a few seconds, which requires a sufficient bandwidth for pressure measurements. Based on these pressure measurements, performed with the quadrupole mass spectrometer, S e is calculated for four different gases from the exponential fit of these data (see Appendix C).
ACKNOWLEDGMENTS The support of  Orsay Physics Company  and the  Region Sud , providing a joint grant for one of the authors (D. B) and financial support, is gratefully acknowledged. The authors would like to thank  Marjorie Sweetko  for improving the English of this article,  Hubert Klein  for his help with the graphics, and  Stéphane Varta , from  CEA Cadarache , for lending the mass spectrometer.
Acknowledgements F. C. and E. D acknowledge support from the  University of Padova STARS  project " Linear and Nonlinear Problems for the Dirac Equation " (LANPDE), L. M acknowledges support from the  European Research Council (ERC)  under the  European Union 's  Horizon 2020 research and innovation program  (Grant agreement no. 810367 ). This study was funded by  Dipartimento di Matematica 'Tullio Levi-Civita' Università di Padova.
, 2021). One of the most popular building concepts are certainly the lightweight buildings and buildings with large window areas. Due to the high heat reaction -low heat storage of the building -such buildings are easily overheated. This is especially a problem during the cooling season, when they need to be cooled immediately to ensure a comfortable and healthy living environment  (Liu et al. , 2017; Lomas & Porritt, 2017; Bundle et al. , 2018). The topic of PCM, which is integrated into the transparent and non-transparent lightweight building envelope has been widely studied  (Al-Yasiri & Szabó, 2023; Arkar et al. , 2018; De Masi et al. , 2020; Fateh et al. , 2019; Duraković & Mešetović, 2019; Li et al. , 2016; Li et al. , 2018). It has been shown, that such integration improves indoor thermal Abbreviations: AC, air-conditioning; ACH, air change per hour; APS, active-passive system; DO, discrete ordinates; DSC, differential scanning calorimetry; CIBSE, chartered institution of building services engineers; CSM, compact storage module; CV(RMSE), coefficient of variation of the root mean square error; EPBD, European directive on energy performance of buildings; ENTPE, national school of state public works; ESP, energy simulation program; HVAC, heating, ventilation and airconditioning; IEA, international energy agency; IPCC, international panel for climate change; ISO, international standard organisation; NMBE, normalized mean bias error; OH, overheating; PCM, phase change material; R2, coefficient of determination; RANS, Reynold average Navier-stokes; TRY, test reference year; TRNSYS, transient system simulation tools; UDF, user defined function.
For example, on the outside of the building envelope, the ventilated PCM roof (horizontal air gap) was experimentally tested by  Hou et al. (2021) , in which two layers of PCM were separated by the air layer and ventilated by the wind  (Hou et al. , 2021). However, the PCM-improved roof is not practical for renovating only a single building space unit (e. g. office). In addition, while the wind does not consume electricity for ventilation, its absence during the solidification cycle makes the system unreliable. On the inner side of the building envelope, the ventilated PCM ceiling was numerically tested using TRNSYS by  Lizana et al. where PCM was integrated into the suspended ceiling and ventilated  (Lizana et al. , 2019). While the advantages of using TRNSYS software are direct simulation with weather data and direct determination of energy use, the heat transfer calculation from air to PCM is less accurate compared to the one obtained with ANSYS software.
, 2016). The PCM improved concrete slabs are ventilated by circular hollow cores in them. Although microencapsulated PCMs are more suitable for use in load-bearing concrete elements, the amount of material is generally less compared to the macroencapsulated technique and therefore has less impact on thermal performance. Similarly, Yu et al. numerically investigated the ventilated hollow concrete slabs also using ANSYS software tool  (Yu et al. , 2020). However, compared to the previous study, PCM was not incorporated into the concrete, but was applied to the top of the slab as a PCM shape-stabilised layer. None of the last two studies performed a validation of the model by comparing numerical results to the experimental  (Faheem et al. , 2016; Yu et al. , 2020). Using Python 3. 6, Morovat et al.
Furthermore, Hu and Heiselberg used COMSOL Multiphysics to calculate a 2D model of a heat exchanger with PCM plates for summer cooling in Copenhagen, Denmark  (Hu & Heiselberg, 2018). It investigates only one climate type scenario. In addition, Kant et al. studied a PCM layer on the BiPV wall and separated from the concrete wall by an air gap and calculated it using the COMSOL Multiphysics 5. 0 software tool  (Kant et al. , 2019). Similarly, Li et al. created a 2D model of a double-skin glazing façade with laminated composite blinds PCM using the ANSYS Fluent software tool  (Li et al. , 2019). The numerical model was validated with smaller segment of the double-skin glazing. Despite the fact, that in the last two studies several different melting temperatures of the PCM were tested, only one (weather data) inlet air temperature was used  (Kant et al.
Validation of numerical model with experimental data For the purpose of validation, two cases were studied. Table  3  shows the validation analysis of both types of validation of numerical model with experimental data. First, a special validation case was measured in which a complete melting/solidification cycle was studied. Fig. 14  shows and describes the 1st validation set up. In this case, the plates are melted and solidified only by the heated or cooled inlet air. Both phases, melting and solidification, of PCM were studied considering the hysteresis of the material (the properties of PCM (melting/solidification temperature and partial enthalpy) were adopted according to the heating or cooling period) (Fig. 15 ). The errors, Normalized Mean Bias Error (NMBE), Coefficient of Variation of the Root Mean Square Error (CV(RMSE)) and coefficient of determination (R 2 ) are NMBE = -0.
In addition, Kant et al. studied a PCM layer (4 cm; T m = 26. 6 • C; 28. 2 • C and 32 • C) applied on the BiPV wall and separated from the concrete wall by an air gap (8 cm) and calculated it using the COMSOL Multiphysics 5. 0 software tool  (Kant et al. , 2019). The nightly cycle lasted 10 h at an inlet temperature of 25 • C, as the PV system is preheated to temperatures of 60 • C or higher. Similar to Diarce et al. the model was simulated using the radiation model  (Diarce et al. , 2014). The PCM was also modelled using the solidification and melting model. Similarly, Li et al. created a 2D model of a double-skin glazing façade (air gap width of 45 cm) with laminated composite blinds PCM (PX35: T m = 35 • C; 15 cm wide and 0. 3 cm thick) using the ANSYS Fluent software tool  (Li et al. , 2019).
2 • C. Similarly, Yu et al. used ANSYS Fluent to calculate a 3D model of the shape-stabilised outer layer PCM of the ventilated roof (different summers T m = 34-38 • C and thicknesses between 2. 5-3. 5 cm)  (Yu et al. , 2020). The best results were obtained with inlet air velocities between 1. 9-2. 5 m/s and inlet temperatures of 24-25 • C. In two cases studied during the hot summer, the ventilation was conducted from 18:00 h for 13-15 h and from 19:00 h for 11-12 h to fully consolidate the PCM layer. A concept very similar to the one proposed in this study was presented by  Evola et al. using  Energy Plus software to study a ventilated internal PCM (Micronal T23® -60% microencapsulated; peak T m = 26. 7 • C and 2 cm thick) with a 3 cm air gap  (Evola et al. , 2014). The air gap was ventilated with an airflow of 168 m 3 /h and a velocity of 0.
Phase 2. a_Provisional models and localisation scenarios of the interventions The proposed methodology is applied to a municipality in the SNAI "Grecanica" pilot area, where 18,821 people live in 15 municipalities and which, in the last forty years, has lost over 40% of the population and seen the abandonment of entire settlements due to the lack of essential services and environmental instability events. Based on this scenario, a preliminary survey was carried out for the candidacy of 3 inner settlements, verifying the presence of favourable characteristics for the activation of an energy community (location, solar radiation, performance potential of the installable photovoltaic systems). The analysis is performed using the open access tool PhotoVoltaic GIS (PVGIS) 4 , The simulations were carried out on the municipalities of Cardeto, Condofuri and Palizzi, using the PVGIS-SARAH2 database, which considers the use of crystalline silicon photovoltaic technology, with installed power [kWp]=1, system power loss (average) by 14% and a fixing angle of 35°.
ACKNOWLEDGMENTS This work was supported in part by the  STFC Quantum Technology Grants   ST/T005858/1 (R. G. & T. T. ) ,  STFC  Consolidated Grant No. ST/P000371/1  (R. G. ). R. G. also acknowledges support from the  Perimeter Institute. Research at Perimeter Institute  is supported by the  Government of Canada  through the  Department of Innovation, Science and Economic Development Canada  and by the  Province of Ontario  through the  Ministry of Research, Innovation and Science.
The observation period time per patient was 24 months (± 2 months). PRO measurements were captured at baseline, 6 months, 1 year, 18 months, and 2 years. For this analysis, PROs taken at baseline (at time of enrollment in the registry), and at the 1-year and 2-year follow-up collection points were used (Fig. 1 ). Patients were followed prospectively, and data were collected based on the type of treatment strategy. Patients who were actively surveilled during the 2-year observation period were not actually being treated and did not have a planned treatment were categorized as Off-Treatment (n = 79). Patients undergoing active intervention (eg, surgery, systemic therapy) were classified as On-Treatment (n = 97). Of these 97 patients, 84 (either systemic therapy only [n = 45] or surgery only [n = 39]) were included in this analysis.
Subjects A total of 183 patients enrolled in the all-document patient set (APS) fulfilled the inclusion criteria and were available for baseline analysis, resulting in identical APS and baseline analysis set (BAS) datasets. Of the 183 patients from BAS, 4 patients withdrew their informed consent, and no postbaseline documented information was available for 3 patients, hence the full analysis set (FAS) is based on the data of the remaining 176 patients and is the population used in this analysis (Supplementary Fig. S1 ). Most patients (120/176 [68. 2%]) had a knee tumor, and 108/176 (61. 4%) of the patients were female. The mean (±SD) age at enrollment was 43. 5 ± 14. 29 years. Baseline demographics are summarized in Supplementary Table  S1. At baseline, 97/176 patients were On-Treatment (actively treated), whereas 79/176 were Off-Treatment (wait-and-see).
Limitations As this project is an observational study, the quality of the collected data has not been 100% verified. Due to the COVID-19 pandemic, the planned on-site monitoring visits in the United States could not be performed. Instead of on-site monitoring visits, more frequent and detailed remote monitoring visits were performed for these sites. Follow-up data for all enrolled patients were regularly monitored remotely, with additional review to minimize potential errors in data acquisition and reporting. The study spanned only 2 years, although it provides an entire overview of the patient journey in a slowly growing disease that can have effects for decades. Both patients in clinical studies and expanded access programs were allowed to enter the study. The study sites are tertiary sarcoma centers that include a difficult-to-treat population, and this study does not allow for analysis of the entire spectrum of TGCT.
One-third of the patients (n = 61/176, 34. 7%) were enrolled from 2 orthopedic sites in the Netherlands. The results of this study should be evaluated with care, as they might be prone to potential data bias. There remains a lack of systemic treatment options with only 1 agent approved in the United States and none in Europe. As the majority of the patients remained on the same treatment strategy, there were small numbers in some of the groups pertaining to patients that switched treatment courses. In turn, there is no statistical comparison, with the findings being descriptive.
Study Design The design of the BECOME study has been detailed previously  [19]. Briefly, BECOME was a two-part, prospective, non-interventional study conducted between 27 November 2017 and 5 October 2018 to assess the burden of migraine in patients with migraine attending specialised headache centres across 17 European countries and Israel. The study was restricted to specialised headache centres to ensure a more consistent diagnosis of disease within the screening population. In part 1, all patients with migraine visiting the study centres over a 3-month period were counted on a weekly basis, and clinical characteristics were collected. In part 2, patients with C 1 PPTF and C 4 monthly migraine days (MMDs) are identified and were invited to a single study visit within 14 days of consent. During the onsite visit, patient-specific data on clinical characteristics and burden of migraine were collected using validated questionnaires (Fig.
ACKNOWLEDGEMENTS We would like to express our gratitude to all study participants. We thank the BECOME study steering committee members:  David Watson ,  Paolo Martelletti ,  Patricia Pozo-Rosich ,  Charly Gaul ,  Christian Lucas. We thank all participating study sites (principal investigators):  Cabinet Dozier Carouge  ( C. Dozier ),  Cabinet Myers Geneva  ( P. Myers ),  Centre Hospitalier Universitaire Vaudois  ( P. Ryvlin ),  Kantonsspital Aarau  ( O. Findling ),  Kantonsspital St. Gallen  ( D. Flu ¨gel ),  Kopfwehzentrum Hirslanden Zu ¨rich  ( R. Agosti ),  Neurologie  am  Schaulager Mu ¨nchenstein  ( M. Stallmach ),  Ospedale Regionale di Lugano  ( C. Zecca ),  RehaClinic Bad Zurzach  ( A. Gantenbein ),  Universita ¨tsspital Zu ¨rich  ( J. A. Petersen ). Funding. The study was funded and supported by  Novartis Pharma AG  and  Novartis Pharma Schweiz AG, Switzerland.