dataesr/scientific-paragraphs-categorization huggingface dataset:
Consequently, the system is no longer limited to identifying the predominant circulating strains. It can also estimate the significance of ILI to health care activity, through syndromic surveillance. Furthermore, other syndromes have been included in the surveillance, and in particular, the network has been extended to cover suspected malaria cases, dengue-like syndromes and diarrhea. This improved Senegalese surveillance system, now called the 4S network, is based on reporting nonspecific indicators as epidemiological data to the health-care authorities, and on (1. 0) SAINT LOUIS 700 ( * number of ILI reported to the total number of ILI. **number of ILI reported to the number of all ILI by sentinel site. # number of ILI reported to the number of visits by sentinel site et age group. doi:10.
Nevertheless, the health burden associated with influenza may be far greater in Africa than in developed countries, due to co-circulating tropical disease, immunosuppression and malnutrition  [15]. Thus, the next step of the 4S network will be to collect data corresponding to hospital admissions for acute respiratory infection (ARI) and to ARI mortality. Hospital-based sentinel surveillance can provide substantial insights into the contribution of influenza infection to the global burden of disease  [3]. A clear understanding of the epidemiology of severe influenza-associated disease is essential for decisions about vaccine recommendations. The 4S network will implement population-based sentinel surveillance, with reporting by mobile phone, to evaluate the incidence of the respiratory infections in the community  [1].
Acknowledgments This study would not have been possible without the excellent support from all the health-care workers of the 4S network. We are deeply indebted to all staff who contribute, every day, to the surveillance network. We also acknowledge the tremendous work of all technicians of the virology unit. We particularly thank  Kathleen Victoir  and  Marc Jouan  from the  International Network of Pasteur Institutes and AndreSpiegel , director of the  Pasteur Institute in Dakar. Disclaimer: The views expressed in this article are those of the authors and do not necessarily reflect the official policy or position of the Ministry of Health. Contributors: Members of the 4S network group: Coordination:  V. Richard , Epidemiology.
THE CURRENT THERAPEUTIC LANDSCAPE Many of the therapeutics that have been tested for PD-MCI and PDD are those that have been tested for MCI and AD, including cholinesterase inhibitors and memantine. This seems a reasonable strategy given the overlap in many of the cognitive symptoms although to date rivastigmine is the only approved drug for PDD, albeit modestly effective. Therapeutics currently being tested for PD-MCI include rasagiline, rivastigmine, droxidopa, and AVE8112, a PDE4 inhibitor (see clinicaltrials. gov NCT01723228, NCT01519271, NCT02066571, NCT01803945). In addition to pharmacological interventions, nonpharmacolocial interventions such as cognitive training, exercise programs, and brain stimulation techniques are being explored  [25] [26] [27]. While this is a growing area of research there is a need for rigorous studies with appropriate control groups to definitively test these approaches.
Forward for Cognitive Impairment in PD General Path Forward • The FDA is open to an indication for mild cognitive impairment in PD • For regulatory consideration, it may be appropriate to pursue a PD-MCI indication without reference to the underlying cause of impairment• Drug approvals for an indication of PD-MCI will likely require a co-primary measure (a cognitive outcome measure and a functional measure) Short Term Path: Long Term Path: For immediate drug development using existing scales and diagnostic criteria Includes efforts to validate diagnostic criteria and/or create new instruments Diagnostic Criteria Diagnostic Criteria • Current MDS PD-MCI diagnostic criteria can be used to identify a patient population for clinical testing • If a sponsor chooses not to use the criteria, they must demonstrate that the study participants have a cognitive deficit • MDS will work to validate and modify the PD-MCI diagnostic criteria (where needed) so the field can have a standardized approach for identifying and classifying study participants Outcome Measures Outcome Measures • Existing cognitive scales are sufficient for use in clinical trials on PD-MCI • Sponsors should select the outcome measure/scale most likely to demonstrate change in the patient population • The scale does not have to be specific to Parkinson's nor does it need to be an established measure of response to treatment • In addition to a cognitive scales, sponsors will be required to include a measure of function to demonstrate clinical meaningfulness • The field should work at analyzing PD-MCI datasets across a number of research studies in order to identify the scale items and domains most sensitive to change • If the existing scale instruments, either cognitive of functional, prove to be sub-optimal in clinical testing, the PD field could develop a new scale or a composite measure Biomarkers • The field should work toward the development of an imaging, fluid, or combination biomarker.
Box 1 Path 1 Forward for Cognitive Impairment in PD General Path Forward • The FDA is open to an indication for mild cognitive impairment in PD • For regulatory consideration, it may be appropriate to pursue a PD-MCI indication without reference to the underlying cause of impairment• Drug approvals for an indication of PD-MCI will likely require a co-primary measure (a cognitive outcome measure and a functional measure) Short Term Path: Long Term Path: For immediate drug development using existing scales and diagnostic criteria Includes efforts to validate diagnostic criteria and/or create new instruments Diagnostic Criteria Diagnostic Criteria • Current MDS PD-MCI diagnostic criteria can be used to identify a patient population for clinical testing • If a sponsor chooses not to use the criteria, they must demonstrate that the study participants have a cognitive deficit • MDS will work to validate and modify the PD-MCI diagnostic criteria (where needed) so the field can have a standardized approach for identifying and classifying study participants Outcome Measures Outcome Measures • Existing cognitive scales are sufficient for use in clinical trials on PD-MCI • Sponsors should select the outcome measure/scale most likely to demonstrate change in the patient population • The scale does not have to be specific to Parkinson's nor does it need to be an established measure of response to treatment • In addition to a cognitive scales, sponsors will be required to include a measure of function to demonstrate clinical meaningfulness • The field should work at analyzing PD-MCI datasets across a number of research studies in order to identify the scale items and domains most sensitive to change • If the existing scale instruments, either cognitive of functional, prove to be sub-optimal in clinical testing, the PD field could develop a new scale or a composite measure Biomarkers • The field should work toward the development of an imaging, fluid, or combination biomarker.
Otherwise, our work focuses on a soft approach to stakeholder perceptions and ideas, whereas biophysical impacts have to be evaluated and trade-offs explained before implementing adaptation options  (Kalaugher et al. , 2013). This kind of stronger assessment process will be performed in the later stages of the CANTOGETHER project with life cycle assessment and economic assessment of several CS. The assessment will be based on collection of local data to inform quantitative assessment procedures. Regarding socio-economic aspects, the light design framework could evolve to fit local challenges and priorities, with adaptation of proposed criteria and definition of adequate indicators and significant thresholds. This deeper assessment is required to contribute to the development of innovative farming systems  (Diaz et al.
The variability of the blazar Markarian 421 in TeV gamma rays over a 14-year time period has been explored with the Whipple 10 m telescope. It is shown that the dynamic range of its flux variations is large and similar to that in X-rays. A correlation between the X-ray and TeV energy bands is observed during some bright flares and when the complete data sets are binned on long timescales. The main database consists of 878. 4 hours of observation with the Whipple telescope, spread over 783 nights. The peak energy response of the telescope was 400 GeV with 20% uncertainty. This is the largest database of any TeV-emitting active galactic nucleus (AGN) and hence was used to explore the variability profile of Markarian 421. The time-averaged flux from Markarian 421 over this period was 0. 446 ± 0.
Rapid variations in TeV emission have also been observed in other AGN  [13, 14]. It has been shown that the energy spectrum of Mrk421 hardens with increasing intensity  [9]. In this paper, we summarize intensive observations of Mrk421 with a single gamma-ray telescope over a long period. The principal telescope used in this study, the 10 m reflector and imaging camera at the Whipple Observatory, is described in Section 2. Section 3 describes the database of TeV observations taken over the 14-year epoch. Correlations with simultaneous X-ray observations are presented in Section 4. The level of variability in the TeV signal is explored in Section 5. Section 6 explores those intervals in which the TeV signal was particularly strong and the source may be said to have been flaring.
Whipple Observations. The principal data reported here were taken at TeV energies with the Whipple 10 m atmospheric Cherenkov telescope and imaging camera over a 14-year period (December 1995 -May 2009). Although observations were made both before and after this period, this time interval was chosen as it represents the best period of uniform operation and performance of the telescope. The Whipple photomultiplier (PMT) camera evolved during this time  [15]. From 2001 to 2009, the camera consisted of a hexagonal array of 379 PMTs of diameter 1. 2 cm, giving a total field of view of 2. 8 •. Winston light cones in front of the PMTs minimized the light loss and gave a relatively uniform sensitivity across the face of the camera. The camera was triggered when the light level in at least three tubes exceeded a preset threshold.
Often no OFF runs were taken, so that the source was tracked continuously (TRACKING mode) and the background determined from the known image parameter distributions in the absence of a source. Observations were taken on clear moonless nights. For much of this time, Mrk421 was the prime target, and it was observed whenever it was at an elevation greater than 55 •. Where possible, one or two ON/OFF pairs were also taken on the Crab Nebula each night for calibration purposes. The rest of the darktime was used to observe other candidate sources (mostly AGN) or gamma-ray bursts. The Cherenkov images of air showers recorded with the telescope were characterized by the moments of the angular distribution of light as determined by the output of the PMTs. The division of the data into candidate gamma-ray images and background images was made on the basis of selection criteria optimized by Monte Carlo simulations of gamma-ray and hadron shower images and checked (and again optimized) on known sources such as the Crab Nebula  [17].
On-line analysis was performed at the conclusion of each data run so that the state of the source was known promptly and the observing program adjusted if necessary. Only data taken on clear nights (judged by fluctuations in the background trigger rate and by the observers' comments) were used in the final database. At the beginning of each observing season, the trigger threshold was raised or lowered, if required, to compensate for changes in the telescope and in the camera; these changes included replacement of PMTs, recoating of mirrors, upgrades to trigger electronics, optimisation of mirror-facet alignments, and improvements in telescope pointing corrections. The adjustment to the trigger level from one season to the next was never more than ±10%, and the threshold was always maintained well above the noise trigger level.
In order to analyze all the Mrk421 data in a uniform manner, the average Crab Nebula flux for each observing season was used for calibration. Although the MeV-GeV flux from the Crab Nebula has recently been shown to exhibit short-term flares  [20, 21, 22] , they are infrequent (<2 per year) and their duty cycle is short (∼10 days); a search of the Whipple database  [23]  did not show any evidence for such flares over a ten-year epoch. Long-term secular variations such as those seen in X-ray experiments  [24]  have not been seen at TeV gammaray energies, so that the Crab Nebula can still be regarded as a standard candle in this energy regime. On-source observations of Mrk421 (ON runs and TRACKING runs) were chosen and selection criteria as described above applied to identify gamma-ray candidate events.
Estimation of the background was based on the distribution of the angle θ between the major axis of the event image and the line from camera centre to image centroid. The region θ < 15 • was taken as the signal region and the region 20 • ≤ θ < 65 • as control region. The background in the signal region was estimated by multiplying the number of events in the control region by a "tracking ratio". The tracking ratio ρ for each season was determined from a set of "darkfield" runs (i. e. , observing runs with no known source in the field of view) as the number of size-and shape-selected events in the signal region divided by the corresponding number of events in the control region  [18]. Usually the OFF runs from ON/OFF observations of Mrk421 were used as darkfield runs, but where these were insufficient they were supplemented by OFF data on other sources.
Gamma-ray Database The gamma-ray data for Mrk421 between December 1995 and May 2009, in runs of (generally) 28-minute duration, comprise the database for this work; in all cases, the measured flux is given in Crab units based on the Crab signal recorded that season. These Mrk421 runs were combined (weighted average) to give the mean flux over larger time intervals: nightly (individual nights of 1-6 hour duration), monthly (entire dark runs) and yearly. The peak energy response of the telescope during these observations was 400 GeV with a 20% uncertainty. In this work, the assumption is made that the Crab Nebula flux at TeV energies is constant over the season. The typical nightly rate from the Crab Nebula as measured by the Whipple telescope for one season is shown in Figure  1. Although the energy spectrum of Mrk421 has been observed to harden when the flux level is high  [9] , the spectral shape in the energy range 400 GeV to 4 TeV is typically similar to that of the Crab Nebula, so that for most nights (when Mrk421 is not flaring strongly) the rates expressed in Crab units are insensitive to small changes in peak energy response.
Some results from this data set have been published previously  [25, 26, 27, 11, 12]. Several of these reports were motivated by the observation of exceptional activity (May 1996  [10] ; February 2001  [11] ; May 2008  [28] ) and the reports included light curves on short timescales and spectral analysis. These flares are discussed in Section 6. The Mrk421 observations reported here represent a total exposure time of 878. 4 hours over 14 years. The nightly gamma-ray rate from Mrk421 for the typical 2007-2008 observing season, expressed in Crab units, is shown in Figure  2 ; the horizontal line indicates the average rate for this season. Mrk421 varies on many time scales. The mean gamma-ray rate from Mrk421 was calculated for each observing season; the results are given in Table  1  and plotted in Figure  3.
The table includes the ON-source observing time (all the time in which the telescope was pointing at Mrk421) and the statistical significance of the detection for each season. For the hypothesis that the annual rate is a constant, equal to the overall mean rate for the complete 14-year data set, the χ 2 value is 1022 for 13 degrees of freedom, corresponding to a chance probability of P < 10 -300. During some observing seasons Mrk421 was the brightest TeV source in the sky, whereas in others it was barely detectable with the Whipple telescope. Figure  4  (bottom) shows the gamma-ray rate averaged over each darkrun (monthly) for the 14 years of data. With this unique dataset, it is possible to look for long-term temporal changes in flux levels, slow periodicities and correlation with experiments at other wavelengths with long time constants.
The discrete autocorrelation function (DACF) allows the study of the level of autocorrelation in unevenly sampled datasets  [29, 30]  without any interpolation or addition of artificial data points. It can reveal the presence of periodicity (intrinsic or spurious) in the time series. The DACF for the gamma-ray dataset for Mrk421 is plotted in Figure  5 ; it shows no evidence for periodicity at any period between 2 months and 7 years.
Correlations We correlated these Whipple 10 m observations with archival data taken at other wavelengths for part or all of the epoch 1995-2009. The most complete overlap was with the Rossi X-ray Timing Explorer (RXTE) database for the entire 14 years  [31, 32]. There was also significant overlap with Milagro  [33]. There was partial overlap with observations by Fermi-LAT  [34]  and with data from three radio AGN monitoring programs (Metsähovi Radio Observatory  [35] , the University of Michigan Radio Observatory  [36] , and MOJAVE  [37] ). The correlation with the X-ray data from RXTE will be considered here; the correlation with Milagro, Fermi-LAT and the radio programs will be the subject of a separate publication. RXTE has three non-imaging X-ray detectors, one of which is the All-Sky Monitor (ASM); it was launched in December 1995 and was operational for the period of the Whipple 10 m monitoring program described here.
The ASM scanned nearly 80% of the sky in each orbit and was sensitive to X-rays of energy 2-10 keV. Systematic uncertainties in the ASM rate were large, but relative flux estimates were available for month-scale monitoring. In the ASM database  [38] , each data point represents the one-day average of the fitted source fluxes from a number (typically 5-10) of individual ASM dwells (90 seconds each). The selection criteria for the observations are described in  [38]. The data are quoted as nominal 2-10 keV rates in ASM counts per second, where the Crab Nebula rate is about 75 counts per second. The daily rates were combined (weighted average) in ∼21-day intervals to reduce statistical errors. The gamma-ray rates for the 1995-2009 Mrk421 Whipple observations were compared with the X-ray flux from the ASM.
The light curves for the X-ray and gamma-ray data on Mrk421 from December 1995 to May 2009 are plotted in Figure  4  (top and bottom, respectively). The data are plotted for the Whipple 10 m darkrun periods (6 -8 for each season) in which both X-ray and gammaray data were taken, i. e. , the X-ray data were averaged for each period in which Whipple gamma-ray data were available (usually 21-day periods). The RXTE ASM data  (1995) (1996) (1997) (1998) (1999) (2000) (2001) (2002) (2003) (2004) (2005) (2006) (2007) (2008) (2009)  show evidence for emission correlated with the gamma-ray data on monthly and yearly timescales, as shown in Figure  6. In previous papers  [11, 12, 39] , the correlation on short timescales was treated in detail. Here, we concentrate on the longer timescales which are uniquely available in our large database.
The correlation coefficients are R = 0. 75 and R = 0. 89 for the monthly-and yearly-binned data, respectively. There is general agreement between these values and those obtained in previous studies of parts of this database  [11, 12]. The strong correlation suggests that the X-rays and gamma rays are emitted by the same population of electrons in the same region of the jet. During one flaring episode, a 2. 1 ± 0. 7 ks time lag of the TeV flare with respect to the 2-4 keV X-ray band was observed  [11]. For the 14-year data set, the discrete correlation function (DCF) between the gamma-ray and X-ray monthly-averaged fluxes for time lags (gamma ray relative to X-ray) between -4800 and +4800 days is shown in Figure  7. The TeV and keV fluxes are seen to be significantly correlated (with a DCF value of 0.
Variability Mrk421 is the brightest AGN at TeV energies (on average) and was the first such AGN to be discovered at TeV energies. Mrk421 is thus the ideal candidate for the detailed study of the variability of this type of object, with the caveat that it may have a greater degree of variability than the norm for such objects on all timescales. It is remarkable also in being the closest TeV-emitting AGN. It is certainly the most studied of the known TeV blazars. Most of the variations seen in Mrk421 on the various timescales have been seen also in other AGN, but the statistics are sparse. It is probably the youngest such AGN. Because it is so close, it has the lowest spectral distortion due to absorption by pair production with the extragalactic background light. It is difficult to compile a large data sample from a variety of observatories, because observing modes may be quite different and the relative sensitivity of the experiments is often not well-defined.
The Whipple 10 m database is comparatively uniform and covers a long time interval; during the period 1995-2009, the system was operated in a relatively stable configuration of telescope and camera  [15]. It is thus useful to use this database to investigate the statistical distribution of the time variability of Mrk421 and, by inference, that of other AGN. If Mrk421 is typical of all (or a subclass of) TeV AGN, then we can use these distributions to predict how often a more distant AGN might flare or be above a certain level of brightness. Four different timescales are considered: yearly, monthly, daily and run-by-run (half-hourly). Yearly variations: As seen in Figure  8 , there are significant variations on a yearly timescale, with mean annual rates ranging from 0. 23 Crab units to 1. 86 Crab units.
The distribution of the run-by-run rates is shown in Figure  11. This distribution is not a completely unbiased sample, since for a subset of the data there was a tendency for the observers to continue observations when the initial observed signal was high. There is therefore some bias towards including observations when Mrk421 was in a high state (there is no bias against runs where the signal was low, as all observations were included in the analysis irrespective of the apparent flux level). However, when only the first run in each night is considered, this bias was not found to be strong, as can be seen in Figure  12  which shows the flux using all the data satisfying weather, hardware and elevation criteria and a smaller set of data where the fluxes are based on only the first run of each night.
Conclusions Atmospheric Cherenkov telescopes are ideally suited for studying AGN, but observations are most sensitive on clear dark nights. The large collection areas associated with the technique make them particularly suited to the study of time variations. Because of their small fields of view, they are generally limited to the study of just one AGN at a time. The profusion of sources and the small number of sensitive telescopes available makes long-term monitoring of a particular source difficult. The Whipple 10 m telescope, while lacking the flux sensitivity of the major new observatories, H. E. S. S. , MAGIC and VERITAS, was devoted over a 14-year timespan to observations of Mrk421 (along with a small number of other AGN) and thus provided a unique database. The Whipple 10 m gamma-ray telescope has since been mothballed in the summer of 2011, after 43 years of operation.