dataesr/scientific-paragraphs-categorization huggingface dataset:
-The task utilizations were generated using UUnifast  (Bini and Buttazzo 2005)  with an equal utilization assumed for each core. -Task periods were set based on task utilization and base WCET, i. e. , T i = C i /U i. -Task deadlines were implicit. -Priorities were assigned in deadline monotonic order. -Tasks were assumed to be independent, i. e. no shared software resources. -The tasks were assumed to be located in memory sequentially in priority order. (We note that improvements in layout can reduce CRPD  (Lunniss et al. 2012) ; however, such optimisations were not considered here). The utilization per core was varied from 0. 025 to 0. 975 in steps of 0. 025. For each utilization value, 1000 task sets were generated and the schedulability was determined for each architectural configuration.
Acknowledgements This work was supported in part by the  COST Action IC1202 TACLe , by the  NWO   Veni  Project 'The time is now:  Timing Verification for Safety-Critical Multi-Cores ' by the  Deutsche Forschungsgemeinschaft  as part of the project PEP, by  National Funds through FCT/MEC (Portuguese Foundation for Science and Technology)  and co-financed by  ERDF  ( European Regional Development Fund)  under the PT2020 Partnership, within project  UID/CEC/04234/2013  ( CISTER Research Centre ), by  FCT/MEC  and the  EU ARTEMIS JU  within project  ARTEMIS/0001/2013-JU Grant No. 621429  ( EMC2 ), by the  INRIA   International Chair program , and by the  EPSRC  projects  MCC  ( EP/K011626/1 ) and  MCCps  ( EP/P003664/1 ). EPSRC Research Data Management: no new primary data was created during this study.
Background--Thoracic endovascular aortic repair is characterized by a substantial need for reintervention. Secondary open aortic procedure becomes necessary when further endoluminal options are exhausted. This synopsis and quantitative analysis of available evidence aims to overcome the limitations of institutional cohort reports on secondary open aortic procedure. Methods and Results--Electronic databases were searched from 1994 to the present date with a prospectively registered protocol. Pooled quantification of pre/intraoperative variables, and proportional meta-analysis with random effect model of early and midterm outcomes were performed. Subgroup analysis was conducted for patients who had early mortality. Fifteen studies were elected for final analysis, encompassing 330 patients. The following values are expressed as "pooled mean, 95% confidence interval.
As opposed to primary open repair, SOAP has scant reports in the literature. This is because SOAP is a relatively new procedure created by the advent of TEVAR, its incidence is lower compared with primary open repair, and centers with the necessary human expertise and structural resources necessary to perform it are few. Our aim was to systematically review all the available information on SOAP in the literature, and to overcome the intrinsic limitations of individual series with relatively small populations. This was obtained with a quantitative analysis of the gathered data, with pooling of pre/peri/postoperative data of SOAP and meta-analysis of its immediate and mediumterm outcomes.
Eligibility criteria The criteria followed were as follows: 1. Inclusion criteria: our analysis included original articles describing pre/intra/peri/postoperative variables of patients undergoing SOAP. There was no date limit on publications, and no age or sex limit on patients. 2. Clinical exclusion criteria were the following: series reporting mixed data where the variables regarding patients undergoing SOAP and secondary endovascular aortic procedure could not be distinguished, particularly with no specific and distinguishable indications for and outcomes of SOAP; series not detailing quantitatively the specified inclusion criteria; series limited to a specific subpopulation and so not contributing to derive a comprehensive "full picture" analysis of the whole SOAP population (ie, series focusing only on a specific indication for SOAP; series focusing only on a specific SOAP; series encompassing only a specific TEVAR population).
Search strategy The databases were searched with an unrestricted search strategy, applying exploded Medical Subject Headings (MeSH) and keywords combined with the Boolean operators AND or OR to retrieve relevant reports: "failed TEVAR" (MeSH); "thoracic endovascular repair"; "TEVAR"; "open reintervention"; "open conversion" (MeSH); "endovascular aneurysm repair"; "open aortic surgery" (MeSH); "TEVAR complication"; "retrograde type A dissection"; "endoleak"; "aneurysm progression"; "aortic stent infection"; "aortic stent migration"; "aortic stent collapse"; "TEVAR secondary intervention. " A second-level search included a manual screen of the reference lists of the articles identified through the electronic search.
Data collection process Data retrieved from the primary sources were entered into a spreadsheet, which was pilot-tested in 3 randomly selected articles and refined accordingly. One author extracted the data from the included studies (I. G. ) and a second author checked the extracted information (C. S. ). Disagreements were resolved by discussion with a third author (M. G. ). Data were identified in published material only. Some authors did not report follow-up data in a fashion suited for our statistical analysis purposes, as stated in the "O" component of PICOS and specified in the prospectively registered protocol. In some instances the information was present but sparse in a narrative form throughout the text (describing morbidity and mortality of individual patients over time, sometimes in a fragmented fashion between the sections "Results" and "Discussion"), rather than extrapolated and explicitly stated in an alphanumeric fashion (eg, in a table): in those cases we retrieved the necessary information by methodically reading the text narrative about each patient reported and so deriving the outcome of interest at 2-year follow-up.
Risk of Bias Assessment Selective treatment bias was excluded a priori, since series limited to only a specific type of SOAP, a specific type of TEVAR population, or a specific indication for SOAP were not included in the analysis. Methods of assessment of publication bias are described in the Data Synthesis section below. The methodological quality of observational cohort studies was assessed with the Newcastle-Ottawa scale. 13 Using the tool, each study was judged on 8 items, categorized into 3 groups: the selection of the study groups; the comparability of the groups; and the ascertainment of outcome of interest. Stars awarded for each quality item served as a quick visual assessment. Stars were awarded such that the highest quality studies were awarded up to 9 stars. Furthermore, the system developed by the Grades of Recommendation, Assessment, Development and Evaluation (GRADE) working group was used for grading the quality of evidence as high, moderate, low, and very low, based on within-study risk of bias, directness of evidence, heterogeneity, precision of effects estimates, and risk of population bias.
Methods of analysis A preoperative profile and intraoperative treatment conduct of the total SOAP population were obtained by data pooling of category 1 to 5 variables of subpopulations from the included series using simple descriptive statistics. Early and late outcomes of SOAP were obtained by meta-analyzing data from category 6 to 7 variables of the subpopulations from the included series. The pooled proportion was calculated as the back transformation of the weighted mean of the transformed proportions. We anticipated considerable clinical betweenstudy heterogeneity and therefore, we applied the random effects model proposed by DerSimonian and Laird. 15 The unit of analysis was the individual patient.
Pathology at index TEVAR 24] [25] 27, 28, 30  These data are expressed alphanumerically in Table  2  and graphically in Figure  3. Dissection was the most common pathology at index TEVAR, in patients who subsequently required SOAP. Whereas the contribution of type A dissection was negligible (1. 0%, 95% CI, 0. 3-3. 5), type B aortic dissection was the original pathology in more than half of patients who subsequently needed TEVAR (51. 2%, 95% CI, 44. 4-57. 9). In the series providing specifications about the subgroup of type B dissection, chronic (31. 2%, 95% CI, 24. 5-38. 8) was more problematic compared with acute dissection (16. 6%, 95% CI, 11. 6-23. 2). Degenerative aneurysm was the second most common aortic pathology at the time of TEVAR: it affected about one third of patients who subsequently needed SOAP (34.
Accordingly, operative mortality was 37. 5% when SOAP included a concomitant esophageal procedure. Consequently, deploying a stent into an infective field should be highly discouraged, and especially in Degenerative aneurysm and SOAP. As pathology at index TEVAR, degenerative aneurysm was substantially less frequent (34. 3% versus 52. 2%) but almost 10 times more deadly (8. 45% versus 0. 92%) than dissection in patients who underwent SOAP. Regarding indication for SOAP, aneurysm progression was 5 times more frequent than aneurysm expansion (15% versus 2. 9%). This means that the most Figure  9. Adverse outcomes at 2-year follow-up of secondary open aortic procedure after thoracic endovascular aneurysm repair. Data on overall mortality were available from 7 studies involving 174 patients,  2, 5, [7] [8] [9] [10] 12  and their meta-analytic results are depicted in the top forrest plot.
Limitations One intrinsic limitation of our quantitative analysis lies in its material: retrospective cohort studies from institutional databases. Corresponding strengths were a rigorous methodology, ensured by a prospectively registered protocol and Preferred Reporting Items for Systematic Reviews and Meta-Analyses standards, and a high quality of the retrospective studies included as indicated by Newcastle-Ottawa assessment. Another limitation could be the potential Variables are expressed as absolute numbers (done=census of patients with a certain variable who underwent SOAP; dead=census of the patients with the same variable who died during the operative period) and their ratio (DD=done to dead). RTAD indicates retrograde type A aortic dissection; SOAP, secondary open aortic procedure; TEVAR, thoracic endovascular aortic repair.
Data availability and preoperative considerations The body of evidence regarding SOAP in the literature is represented mainly by institutional series of small-medium size, and our meta-analysis aimed to overcome some of their intrinsic limitations. Most series report on SOAP performed on patients who underwent TEVAR both at the same and in another institution. Consequently, this body of evidence analyzes the numerator represented by SOAP, but not the denominator represented by the whole population of patients who underwent TEVAR. The population undergoing SOAP is relatively young (mean age 62. 13 years) and there is no sex skewing (49. 69% male). Surgeons usually face SOAP within 2 years (20. 14 months) from index TEVAR, and in one third of cases (34. 6%, 95% CI, 27. 7-42. 2) perform it in a nonelective setting.
A 181. 8 m ice core was recovered from a borehole drilled into bedrock on the western plateau of Mt El'brus (43 • 20 53. 9 N, 42 • 25 36. 0 E; 5115 m a. s. l. ) in the Caucasus, Russia, in 2009 (Mikhalenko et al. , 2015). Here, we report on the results of the water stable isotope composition from this ice core with additional data from the shallow cores. The distinct seasonal cycle of the isotopic composition allows dating by annual layer counting. Dating has been performed for the upper 126 m of the deep core combined with 20 m from the shallow cores. The whole record covers 100 years, from 2013 back to 1914. Due to the high accumulation rate (1380 mm w. e. year -1 ) and limited melting, we obtained isotopic composition and accumulation rate records with seasonal resolution. These values were compared with available meteorological data from 13 weather stations in the region and also with atmosphere circulation indices, backtrajectory calculations, and Global Network of Isotopes in Precipitation (GNIP) data in order to decipher the drivers of accumulation and ice core isotopic composition in the Caucasus region.
Dating The chronology is based on the identification of annual layers. These are prominent in δ 18 O with an average seasonal amplitude of 20 ‰. For annual mean values we calculated averages of δ 18 O from one minimum of this parameter to another one as well as from one maximum to another. As we found no significant differences between the records obtained by two different ways of year allocation, we used minimum to minimum dating as a more common method. We compared annual layer counting performed independently using the seasonal cycles in the isotopic composition and the ammonium concentration. The discrepancy between two independent chronologies is 2 years at a depth of 126 m. We used the dating based on the isotopic composition data in this paper. This dating is also best fit for the correlation analysis with the meteorological data.
Meteorological data We used the daily meteorological data (precipitation rate and mean daily temperature) from several weather stations around the drilling site (see map in Fig. 1  and Table  1 ) for comparison with the ice core data. We also investigated records of precipitation isotopic composition based on monthly sampling, performed at three stations to the south of the Caucasus within the WMO-IAEA GNIP program (Table 1). Clim. Past, 13, 473-489, 2017 www. clim-past. net/13/473/2017/ For comparison we used the NCEP/NCAR reanalysis temperature data  (Kalnay et al. , 1996)  for the 500 mbar level, which corresponds to the drilling site altitude. Two different models were used to calculate back trajectories: FLEX-PART (FLEXible PARTicle dispersion model;  Forster et al. , 2007; Stohl and Thompson, 1999)  and HYSPLIT (Hybrid Single Particle Lagrangian Integrated Trajectory Model;  Draxler and Hess, 1998; Stein et al.
The negative index corresponds to the less prominent centres of action in the Northern Hemisphere. Usually this index is calculated as a difference of atmospheric pressure measured at Reykjavík and Lisbon, Ponta Delgada or Gibraltar. Here we used data from  Vinther et al. (2003)  and https://crudata. uea. ac. uk/~timo/datapages/naoi. htm that www. clim-past. net/13/473/2017/ Clim. Past, 13, 473-489, 2017 were calculated using data from the Gibraltar station. A negative NAO leads to an increase in the precipitation rate in southern Europe, while a positive NAO leads to an increase in the precipitation rate in northern Europe  (Hurrel, 1995; Jones et al. , 2003; Vinther et al. , 2003). The AO is also a characteristic of the Northern Hemisphere circulation. It is used to analyse climatic variability with periods longer than 10 years.
It is calculated as EOF (empirical orthogonal function) of 500 hPa surface. Negative values correspond to high pressure at the North Pole and the cooling of Europe, while positive values correspond to low pressure at the North Pole and the drying of the Mediterranean  (Thompson and Wallace, 2001). We used AO data from NOAA (http://www. cpc. ncep. noaa. gov/products/ precip/CWlink/). The NCP index is less widely used although it has been proved that it is convenient to use it in Mediterranean climate studies  (Kutiel et al. , 1996; Brunetti et al. , 2011). The index is calculated as a normalized difference of geopotential heights between the Caspian and northern seas. Positive values correspond to stronger meridional circulation in Europe and lower summer temperatures, while negative values reflect the strengthening of zonal circulation and higher summer temperatures in Europe  (Brunetti et al.
3 • C per 1000 m) and highest (5. 2 • C per 1000 m) in June-August (Fig. S3 ). Based on the lapse rate, we calculated the temperature at the drilling site taking into account its seasonal variability shown on the Fig. S3. This record was used for the estimation of the δ 18 O-temperature relationship. For the comparison with the ice core data, we used the dataset of the normalized temperature data. Normalized temperature time series were calculated for each station for each season or for the whole year, and results were then averaged (Fig. 8 ). For precipitation data, available in this region since 1966, we show all the data (Fig. S4 ), while in the calculations we used data from the Klukhorskiy Pereval station as an example of a station without a seasonal cycle and from the Mineral'nyye Vody station as an example of one with a prominent cycle.
The maximum daily mean temperature at the drilling site according to the reanalysis data was -1. 3 • C for the whole dataset. The temperature in the glacier at 10 m depth, which corresponds to the annual mean temperature at the drilling altitude, is -17 • C  (Mikhalenko et al. , 2015) ; the annual mean temperature at the drilling altitude from the NCEP reanalysis is -14 • C, and the same value calculated from meteorological observations and corrected for the lapse rate is -11 • C. We then investigated long-term trends in the meteorological records. Mean annual temperatures show a significant increase during the last 2 decades. We also observe higher than average values of mean decadal temperature in 1930-1940. The beginning of the observations in the region, i. e. the period from 1881 until 1900, was as cold as the 1990s.
S4 ). A significant anti-correlation is observed between temperature and the NAO index, both in the cold and warm seasons (Table  2 , the information about the time series used for the correlation analysis can be found in Table  1 ). Stronger anti-correlations are identified between temperature and the NCP index, especially in the cold season, as also reported by  Brunetti et al. (2011). Relationships with indices of largescale modes of variability are systematically weaker for precipitation, with contradictory results for the south/north Caucasus stack; they appear significant for the NCP in both seasons (Table  2 ). GNIP data are only available at low-elevation stations. They show a rather uniform distribution of the isotopic composition of precipitation in the region during summer and a gradual depletion of δ 18 O at higher altitudes in winter.
GNIP records are too short and intermittent (1-2 years with gaps) to investigate the variability and relationships with the local temperature on an interannual scale. We therefore restrict the discussion of GNIP data to seasonal variations. The δ 18 O and δD in precipitation have a distinct seasonal cycle with maximum values observed in the warm season (JJA) and minimum values observed in the cold season (DJF). As an example we show the seasonal cycle of δ 18 O and d for the Bakuriani station in 2009 (Fig. 7 ). This station is the only one in the region for which the whole uninterrupted dataset for one annual cycle is available. The seasonal amplitude of δ 18 O is about 17 ‰. The slope between δ 18 O and temperature is 0. 32 ‰ • C -1. The d variations show no seasonal cycle, varying randomly between 10 and 25 ‰.
The precipitation-weighted temperature was calculated using daily meteorological data. We used data from two stations: Klukhorskiy Pereval (as representative of the southern stations) and Mineral'nyye Vody (as representative of the northern stations). Obviously, the above inferences strongly depend on the uncertainties of the timescale used. If one concedes that the error of the timescale could be significantly greater than ±2 years, quite different conclusions may be reached by adjusting the scale of the δ 18 O and T records against each other. For instance, by contracting the δ 18 O record by 8 years with respect to the initial timescale in Figs. 9 and 10, one would find much better correlation between δ 18 O and temperature, thus reaching the conclusion that the local temperature is the main driver of the δ 18 O variability.
However, for the El'brus ice core this correlation was found in the warm season only. Other research carried out in the Alps by  Bohleber et al. (2013)  revealed a significant correlation between modified local temperature and the ice core isotopic composition on a decadal scale. The authors also report that there are some periods of correlation absence. The main finding is that for the periods of less than 25 years the difference between the modified dataset according to the authors' method and original dataset temperature is crucial, but for longer periods the two temperature datasets are close to each other. That conclusion implies that the isotopic composition reflects the local temperature in the high mountain regions to a limited extent. It seems to be impossible to calculate the modified temperature for the Caucasus region according to the methods described by  Bohleber et al.
(2013)  because of the relatively short and sparse original datasets. The seasonal accumulation rate is seasonal layer thickness corrected for densification using the density profile from  Mikhalenko et al. (2015)  and for the layer thinning due to glacier flow using the Nye model  (Nye, 1963; Dansgaard and Johnsen, 1969). It is linked to the precipitation rate at the stations situated south of the Caucasus in both seasons (r = 0. 49) and even more closely related to precipitation from the Klukhorskiy Pereval station (r = 0. 63 for both seasons). We therefore establish a linear regression model for the period 1966-2013 and use this methodology to reconstruct past precipitation rates for the Klukhorskiy Pereval station  when meteorological records are not reliable or unavailable. The reconstructed records are shown in Figs.
This may suggest different influences of large-scale atmospheric circulation on precipitation at lower versus higher elevations. For the cold season, the ice core δ 18 O record shows a positive correlation with the NAO index (r = 0. 41), while the NAO index is negatively correlated with regional temperature (r = -0. 42). It also contradicts the findings of  Baldini et al. (2008) , who, based on the GNIP low-elevation dataset, extrapolated a negative correlation between the δ 18 O of precipitation and the NAO in this region. This finding also suggests different drivers of temperature and δ 18 O at low and higher elevation. We propose the following explanation for this correlation. During the positive NAO phase, the predominant moisture source for the Caucasus precipitation is the www. clim-past.
Acknowledgements. The research was supported by the  RFBR  grants  14-05-31102 mol_a  and  17-05-00771  a. The analytical procedure ensuring a high accuracy of isotope data obtained at CERL was made possible with financial support from the  Russian Science Foundation , grant  14-27-00030. The study of dust layers was conducted with the support of  RFBR  grant  14-05-00137. The measurement of the samples in IAEA was conducted according to research contracts  16184/R0  and  16795. This research work was conducted within the framework of the  International Associated Laboratory (LIA) "Climate and Environments from Ice Archives "  2012-2016 , linking several Russian and French laboratories and institutes. We thank  Obbe Tuinenburg  and  Jean-Louis Bonne  for the back-trajectory calculations. We thank  Alice Lagnado  for improving the English.
AUTHOR'S PROOF U N C O R R E C T E D P R O O F Slow Loris Behavioral Observations To examine the presence of chayote in slow loris home ranges, we surveyed the study site to locate each chayote frame, measuring their perimeters and monitoring change in their presence from January 2014 to May 2015. To examine the behavior of slow lorises in relation to chayote frames, we analyzed behavioral data collected on collared slow lorises from the first time we saw them enter a chayote frame in June 2014 until June 2016. Because Javan slow lorises live in stable unimale-unifemale pairs with almost 100% range overlap and share sleep sites (Nekaris 2014), we examined the impact of chayote frames on social groups rather than individuals. We focus on adult individuals belonging to eight focal unimale-unifemale social pairs (Table  I ).