dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgments The authors would like to thank  Dana Creanga, PhD , a contractor employed by  Forest Research Institute, Inc. , at the time of these analyses, for assistance with data analysis. Sioux Falls. He has received industry-sponsored grants from  AstraZeneca ,  Biomarck ,  Centocor ,  GlaxoSmithKline ,  Mpex ,  Nabi ,  Novartis ,  Otsuka , and  Pfizer. Peter M A Calverley  has given presentations at symposia sponsored by  Astra Zeneca ,  Boehringer ,  GlaxoSmithKline , and  Nycomed , and has received fees for advising  Astra Zeneca ,  Boehringer ,  GlaxoSmithKline ,  Novartis , and  Nycomed. Shawn X Sun ,  Stavros Tourkodimitris , and  Paul Rowe  are employees of  Forest Research Institute, Inc. Udo M Goehring  and  Dirk Bredenbröker  are employees of  Takeda Pharmaceuticals International GmbH.
Phytochromes give rise to the largest photosensor family known to date. However, they are underrepresented in the Protein Data Bank. Plant, cyanobacterial, fungal and bacterial phytochromes share a canonical architecture consisting of an N-terminal photosensory module (PAS2-GAF-PHY domains) and a C-terminal variable output module. The bacterium Xanthomonas campestris pv. campestris, a worldwide agricultural pathogen, codes for a single bacteriophytochrome (XccBphP) that has this canonical architecture, bearing a C-terminal PAS9 domain as the output module. Full-length XccBphP was cloned, expressed and purified to homogeneity by nickel-NTA affinity and size-exclusion chromatography and was then crystallized at room temperature bound to its cofactor biliverdin. A complete native X-ray diffraction data set was collected to a maximum resolution of 3.
Phytochromes are underrepresented in the Protein Data Bank (PDB). Moreover, most of the structures correspond to complete or incomplete photosensory module constructs from bacterial phytochromes. This is probably related to the difficulty in obtaining good diffracting crystals of the full-length proteins, taking into account their multi-domain nature, their considerable size and the intrinsic flexibility between domains. To date, the PDB includes only one phytochrome containing both the complete photosensory module and part of the output module, which corresponds to the Rhodopseudomonas palustris CGA009 BphP (PDB entry 4gw9;  Bellini & Papiz, 2012b). Very recently, single-particle electron microscopy allowed the reconstruction of an entire dimeric BphP containing a histidine kinase as output module, that of the extremophilic bacterium Deinococcus radiodurans  (Burgie et al.
Crystallization Initial crystallization trials were performed in 96-well sitting-drop vapour-diffusion Greiner 609120 plates (Monroe, North Carolina, USA) using a Honeybee 963 robot (Digilab, Marlborough, Massachusetts, USA) and the following crystallization kits: Jena Bioscience JBScreen Classic (Jena, Germany) and Hampton Research Crystal Screen, Crystal Screen 2, PEG/Ion, PEG/Ion 2, PEGRx and PEGRx 2 (Aliso Viejo, California, USA). After 5 d of equilibration at room temperature in the dark, eight conditions showed promising hits consisting of tiny green cubes. Some of these conditions were optimized manually with success, and the best diffracting crystals (Fig. 2 ) were eventually obtained as indicated in Table  2. Samples were cryoprotected and then cooled in liquid nitrogen in Hampton Research loops prior to data collection, with minimal exposure to ambient and microscope light during these steps.
Data collection and processing Crystals were tested in-house for diffraction on a Bruker D8 QUEST microfocus diffractometer (Karlsruhe, Germany), and the best data set was collected at the PROXIMA 1 protein crystal-   lography beamline at the SOLEIL synchrotron (France). Fig. 3  shows a particular diffraction pattern from this data set obtained with a PILATUS 6M detector (Dectris, Baden, Switzerland). X-ray diffraction data were processed with XDS (Kabsch, 2010) using the graphical user interface XDSGUI. A total of 5% of the recorded reflections were flagged for cross-validation. Details of datacollection parameters and processing statistics are shown in Table  3.
Ethics Statement Eider nests, eggs and chicks are protected in Denmark according to the Wildlife Management and Hunting Act from  1931. We use existing data for this study that were collected by local wardens and ornithologists, who had permission to count birds according to the national monitoring program. The eiders at Christiansø are breeding in gardens and close to public paths and are used to people close to the nests. Counts of nests are easily made without disturbance of the birds, and counts of eggs in nests are performed by carefully lifting the females off the nests.
[9]  showed a close relationship between fertilizer (sum of artificial and natural fertilizers) use by Danish farmers and the concentration of nutrients in the Danish marine environment due to leakage of fertilizer from arable land to rivers and lakes and eventually the ocean. Information on fertilizer use by Danish farmers dates back to 1900  [36] , and we use this as an indirect estimate of the amount of nutrients, which makes it possible to analyse the effects of nutrients for ecological variables for long time series. The annual amount of fertilizer use is estimated from autumn to spring the following year, e. g. the amount of fertilizer used in 1986 covers the amount used in autumn 1986 until spring 1987. Here the amount of fertilizer used in 1986/1987 is presented as 1986. From the Danish part of the Wadden Sea mussel stock data (metric tonnes) were available for 1987-2007  [25, 37] , and nitrogen and phosphorus concentration for 1989-2009 (data from the Danish Ministry of the Environment).
Statistics on hospital stays were provided by the French hospital discharge databases in the participating hospitals. The same statistics were available at the national level, which made it possible to extrapolate national incidence estimates. Results: Over the 2004-2008 period, the estimated incidence rate of HLIs age-standardized on the European population aged 15 years and over was 48. 7 per 1,000 person-years (95% confidence interval: 39. 4-58. 0), and displayed little variability over time. This rate corresponded to an average of 2. 5 million emergency hospital visits each year due to an HLI in people aged over 15 in France.
However, reliable information about the incidence of HLIs in the general population is often lacking, particularly among adults. The number of HLIs is generally either unknown at a national level or the estimates available are simply extrapolations from the raw data recorded by a small sample of emergency departments (EDs) or based on hypotheses for hospital catchment areas  [16]. In France, a network of emergency rooms ("Enquête permanente sur les accidents de la vie courante," EPAC), provide the surveillance coverage of HLIs. Each year, a fluctuating number of volunteer hospitals in about 10 French cities use a standardized protocol to record all HLIs treated in their EDs. The epidemiological data collected describe the circumstances and consequences of injuries and assist preventative action against HLIs in France.
Until now, these data were also used to make a crude extrapolation of the incidence rates of HLIs in the French population  [17]  based on weak assumptions on the population coverage of the network. The aim of this paper is to propose a statistical model-based approach to predict the rates of HLIs treated in EDs in the French population, using EPAC records between 2004 and 2008 plus an auxiliary source of data available nationwide. This exogenous source is the PMSI system ("Programme de médicalisation des systèmes d'information," www. atih. sante. fr), a medicoadministrative database similar to the Medicare Diagnosis-Related Groups.
Injury data The EPAC surveillance network has been reporting data on HLIs since 1986. It constitutes the French component of the European Injuries Data Base (IDB, formerly designated EHLASS: European Home and Leisure Accident Surveillance System), a systematic, crossnational injury information system that provides data recorded by EDbased surveillance systems within several European Union Member States in a harmonized format  [16]. When an emergency room of one of the EPAC hospitals admits a person with an injury, the medical staff collects some additional information to find out whether the injury took place at home or during a leisure activity. In particular, hospitals participating in the network receive a grant from the French Institute for Health Surveillance ("Institut de Veille Sanitaire," InVS) to employ health care professionals (physicians and data input operators) to select the relevant cases and to code the data using reference guidelines  [18, 19].
Auxiliary data In France, the PMSI system records all admissions to private and public hospitals. This medico-administrative database is used primarily for managing operating costs, but it also includes medical information. Each patient stay is documented with both demographic information (age, gender, postcode of the area of residence) and clinical information (diagnosis and medical procedures). Diagnoses are coded according to the International Classification of Disease and Related Health Problems 10th Revision (ICD-10, www. who. int/classifications/icd). The PMSI does not record the circumstances of health events related to the hospital stay and so does not provide a useful database for studying HLIs. However, the hospital discharge database is available nationwide. We used the PMSI data to estimate the yearly volume of hospital activities related to injuries in each hospital in the EPAC network and more generally in the full set of medical establishments with an Emergency Department in metropolitan France.
The InVS is allowing accessing permanently PMSI data by the CNIL (authorization n°902167). Injury-related hospital stays of patients aged over 15 between 2004 and 2008 were identified using two different algorithms. The first algorithm consisted of selecting all stays with a principal diagnosis code or an associate diagnosis code from Chapter 19 of ICD-10 related to "injury, poisoning and certain other consequences of external causes" (S00 -T98). The second algorithm extended the first by adding the codes of disorders strongly related to injuries (eyes: H05, H16, H26, H27, H40; ears: H72; respiratory conditions: J68-J70; skin: L55-L59). As previously and for each algorithm, the aggregate numbers of hospital stays were determined for each year by gender and age, for each EPAC hospital, and nationally after identifying all hospitals in metropolitan France with an ED.
Standard diagnostic tools were used to assess normality assumptions on random effects and the goodness of fit of the model  [21]. All analytical runs were performed using a quasi-GLMM model with the 'MASS' package  [23]  in R 2. 12. 0 (www. R-project. org), which made it possible to handle overdispersed data. The marginal expectation of the ratio, averaged over the random effects distribution, was then inferred from the fitted model. When implementing the working model (1), the total numbers of HLIs can be provided by a combination of sex and five-year age categories. Estimates of the totals for whole population or separately by sex were computed by adding the estimated totals within the fiveyear age categories. In addition, the rates of HLIs treated in EDs were calculated and expressed as the number of HLIs per 1,000 inhabitants aged 15 years and over each year.
Population figures for each five-year age category were available from the French National Institute for Statistics and Economics Studies datasets. Yearly rates for men, women, and both were age-standardized using the European standard population over the truncated age range of 15 years and over  [24]. The variances of aggregate numbers for the whole population or by sex and the corresponding rates were estimated by the delta-method (see Appendix for more details) and used to compute 95% confidence intervals. Number estimates and age-specific rates were presented graphically (R code  [25] ). The ability of the model to yield robust estimates despite the small sample size of hospitals was tested using crossvalidation reasoning. The number of HLIs and rates for the overall period 2004-2008 were estimated using the marginal expectation of the ratio obtained when one hospital was excluded.
Discussion The goal of this study was to find a way to estimate the numbers of HLIs in adults treated in ED hospitals throughout metropolitan France. This national number of HLIs is difficult to estimate because in France, as in most European countries, the HLI surveillance system is based on data from the EDs of a restricted number of hospitals. To achieve our goal, we used a model-assisted approach that combined data available from the ED surveillance system with information available at the population level (hospital discharge statistics). Based on this approach, we estimated a yearly average number of HLIs in the population over 15 years of age of 2. 5 million between 2004 and 2008. This number of HLIs in adults accounted for 15% of ED activity in metropolitan France (without any age limit), with about 17 million ED visits recorded each year  [29].
Acknowledgments We would like to thank the health care professionals, physicians, and data entry operators who work on a day-to-day basis with the EPAC network and contribute to data collection in the participating hospitals. The  EPAC network ("Enquête permanente sur les accidents de la vie courante ") is supported by the  French Institute for Public Health Surveillance  (" Institut de Veille Sanitaire," InVS ). The authors wish to thank  Zoé Uhry , of the  French Institute for Public Health Surveillance , for her many suggestions and  Laura Tondeur , student at the  Bordeaux School of Public Health, Université Bordeaux Segalen , for her contribution to the initiation of this project.
The possibility to exploit low thrust propulsion or non gravitational perturbations with passive de-orbiting devices (and a combination of the two) was analyzed, in view of possible applications in the design of the future generations of the constellations satellites. Several upgrades in the long-term evolution software SDM and DAMAGE were undertaken to properly handle the constellation simulations in every aspect from constellation maintenance to orbital dynamics. A thorough approach considering the full time evolving covariance matrix associated to every object was implemented in SDM to compute the collision risk and associated maneuver rate for the constellation satellites. Once the software upgrades will be completed, the effectiveness of the different disposal strategies will be analyzed in terms of residual collision risk and avoidance maneuvers rate.
• Exploitation of non-gravitational perturbations: following the results of Sec. 6, a few disposal scenario involving drag augmentation devices will be explored. An analysis of the associated collision risk will be performed too. • Collision consequences: a scenario where a fragmentation takes place in the MEO region will be explored to highlight the possible longterm consequences of this event and the corresponding increase in maneuver rate. In order to simulate the above scenarios the SDM and DAMAGE software are being adapted to properly reproduce the complex maintenance and disposal practices described in the paper. As an example, the capability to control the RAAN of the constellation planes within a pre-defined window, a refined specific traffic model for constellations building, the possibility to de-orbit the satellites and upper stages in selected disposal orbits are some of the changes introduced up to now.
Conclusions and Future Work A comprehensive study of the disposal strategies to be adopted for the GNSS constellation is undergoing under an ESA/GSP Contract. The main focus is on the forthcoming Galileo, but as it is been stressed several times the whole MEO regime must be taken into consideration. An analysis of the historical practices of the GNSS constellations was performed in order to properly define the reference scenario for the future simulations. The dynamics in the MEO region is under study to define a map of the resonances in the region with the aim of finding the best disposal orbits, either stable or unstable. A number of software upgrades were performed and are undergoing in SDM and DAMAGE to properly simulate the MEO regime and the constellations maintenance and disposal strategies.
In our study, the question of amplitude-phase coaction is explored by a computational model for image quality assessment (IQA). We model subjective image quality as a function of amplitude-phase combinations, test this model on a large collection of subjective image quality databases, and find the essential phase and the effective amplitude-phase combination leading to the most accurate quality prediction. We use the independent subspace analysis (ISA;  Hyvärianen & Hoyer, 2000 , 2001)  as the functional form of simple and complex cells, and thus, the amplitude and the phase are simulated by the magnitude and the phase angle of the ISA response vector, respectively. Similar to independent component analysis (ICA;  Jutten & Hérault, 1991) , ISA is a method for finding underlying factors or bases from multidimensional statistical data, as reviewed briefly in Appendix A.
It often happens for the subjective IQA protocols (ITU-R BT. 500-11, P. 910) and most psychological measurements  (Aron, Aron, & Coups, 2006)  except, for example, 2AFC experiment. It may be fitted by a sigmoid or Naka-Rushton-type curve. A log-logistic curve is adopted in video quality assessment standard ITU-T P. 1202. 2 Mode 2  (Zhang, Lin, Chen, & Ngan, 2013). It monotonically maps a distortion value f to a quality score q q ¼ 1 1 þ a fðq; h; a; b; cÞ ½ b ða. 0Þ ð 3Þ where parameters a and b control the curve shape and thereby influence how much the floor and ceiling effects impact on the distortion f. The floor and ceiling effects depend on the context of the test materials, so a and b should be associated with each database. In this study, our regression method supports using a single set of {a, b, c} for all databases and an adaptive set of {a, b} for each database (see details in Appendix C).
Using adaptive {a, b} values can compensate the misaligned floor and ceiling effects across multiple datasets. The functional form of V1 is related to only {a, b, c} but not {a, b}. Factually, {a, b} does not change the quality ranking for a database. The proposed perceptual quality metric is depicted in Figure  2. From the psychophysical stimuli to the visual psychological responses, the metric mainly captures the amplitude-phase response of V1, their combination in the ventral system, subspace pooling, spatial pooling, and spatial-frequency pooling, as well as the appraisal process  (Scherer et al. , 2001). For simplicity, we assume spatial pooling as a summation function, spatialfrequency pooling as a linear weighted sum, and treat the appraisal process as a two-parameter log-logistic; we focus on how the amplitude and phase coact in V1.
Evaluate image metrics on experimental data We train the image quality model on existing experimental data. The data are collected from the publicly available and subjectively rated image quality databases  (Winkler, 2012). Each database contains natural images, both original and distorted, and corresponding subjective quality opinions. A total of 11 databases are used, including LIVE, IVC, Toyama, TID2008, A57, WIQ, CSIQ, LAR, BA, FourierSB, and Meerwald. In Table  1 , the test materials (including the number, distortion types, and format of images) and the experiment details (such as subjects, viewing setup, and subjective testing methods) are summarized. The image distortions include various kinds of additive noise, Gaussian blur, compression, channel loss, additive watermarks, and so forth.
e. , a and b) log-logistic mapping in our model. For both criteria, the higher the value, the better the accuracy; q s has a range of [À1, 1], while the likelihood does not have that constant range and its value also depends on the number and the distribution of the data. Hence, we use q s to quantify the accuracy of metrics, and use the likelihood to assist in the comparison. It should be noted that the test conditions were not strictly consistent among the databases, and the subjective data needs to be aligned. Fortunately, the aforementioned additive log-logistic model can align the subjective data automatically and compensate the inconsistency to some extent. More importantly, these 11 databases provide ample data and reduce to the lowest bias about image selection, distortion generation, subjects' preference, and so forth.
Finally, we choose the most accurate and concise model from a group of candidates. For each candidate model, we optimize its parameters to fit the subjective data, and then compare the candidates at their best accuracy. The model candidates use various RFs (i. e. , the ISA bases under different configurations) and neural coactions (i. e. , the amplitude-phase combination function f ). The ISA bases are trained offline using FastICA toolbox from Hyvärianen's group, independent to the quality prediction or the model regression; actually the thirteen natural monochromatic images for ISA bases training are totally different from the images in the 11 databases. We conduct the following two experiments with two questions in mind: Experiment 1 To answer Question 1, we conduct Experiment 1 in two steps.
This is not surprising because only the LF (low spatial-frequency) components are taken into account but the HF is ignored. On one hand, V1 is not sensitive to the HF at the finest image scale; on the other hand the HF at current image scale is overrepresented by the LF at the finer image scale. Indeed, the case of product-based 8D • 4 is as accurate as the state-of-the-art metrics like FSIM  (Zhang, Zhang, Mou, & Zhang, 2011)  and SIQM  (Narwaria, Lin, McLoughlin, Emmanue, & Chia, 2012) , and outperforms the CW-SSIM  (Sampat et al. , 2009)  and MSE (mean squared error), as can be seen in Table  2. We split TID database into two subsets (columns 4 and 5), TID 1;15 with the first 15 distortion types and TID 16;17 with the last two types, namely ''intensity shift'' and ''contrast change,'' which globally adjust the mean and the variance of images, respectively, as shown in Figure  3.
We separate TID 16;17 from the full set because the proposed metric is not good at it, which we will discuss later. Green triangles mark the total log-likelihood, blue circles mark the average q s on all databases, blue vertical bars depict the range of q s on individual database; cyan crosses depict q s on WIQ, red points depict q s on TID 16;17 , while the lowest q s excluding WIQ and TID 16;17 are depicted by red crosses. Figure  3. Typical distortions of TID2008 databases with subjective/objective quality scores  (Ponomarenko et al. , 2009). For each row, the icons respectively annotate the best and the worst score rated by the corresponding method.
In other words, the deformation of stimuli in orientations and locations are detected but they are suppressed in the final analysis. Consequently, only an essential and compressive amount of phase information is factually encoded and forwarded. It is also interesting to note that in the case of a single subspace, i. e. , 64D • 1, Experiment 1 links with the classic SSIM metric. Equation 4 is similar to SSIM as proved in Appendix B. In SSIM, the direction in which the phase deviates is totally neglected; in other words, equal values of phase difference across any orientations and any locations are perceived as being equal. The disadvantage of 64D • 1 over the cases with more subspaces implies that SSIM could be refined with additional consideration of orientations. Note again that we use a single set of parameters {a l , b l , c l jl ¼ 1, 2, 3} for all databases and adaptive parameters {a m , b m jm ¼ 1, 2, Á Á Á, 11} for the m-th database.