dataesr/scientific-paragraphs-categorization huggingface dataset:
Illustrating example: Spanish energy prices We analyze the data collected on the daily price of energy in Spain between 2002 and 2008. The data, 1784 observations in total, are available in the R package MSwM (Sanchez-Espigares and Lopez-Moreno, 2014). We consider the relationship over time between the price of energy P t and the Euro/Dollar exchange rate r t. The stochastic volatility of financial time series makes the assumption of a fixed relationship between these two variables over time questionable, and it seems natural to consider a Markov-switching regime model. It is also probable that their relationship within a regime is non-linear with unknown functional form, thereby motivating the use of flexible nonparametric predictor functions. Here, our aim is to illustrate the potential benefits of considering flexible MS-GAMs rather than GAMs or parametric Markov-switching models when analyzing time series regression data.
-15 -Preprint of observations P u under the models fitted to all preceding observations, P 1 ,. , P u-1 , considering u = 501,. , 1784 (such that models are fitted to a reasonable number of observations). We obtained the following log-likelihood scores for each model: -2314 for LIN, -2191 for GAM, -2069 for MS-LIN and -1703 for MS-GAM. Thus, in terms of out-ofsample forecasts, the MS-GAM performed much better than any other model considered. Both two-state models performed much better than the single-state models, however the inflexibility of the MS-LIN model resulted in a poorer performance than that of its nonparametric counterpart, as clear non-linear features in the regression data are ignored. For the MS-GAM, the transition probabilities were estimated to be γ 11 = 0. 991 (standard error: 0.
All these site personnel comprised the local TABUL team with responsibility for co-ordinating the study locally and completing the clinical, pathology and ultrasound data collection. The process for ultrasound training is described in the next section. Each site was provided with study training during an initiation visit from the central TABUL study team which consisted of advice on data collection (including completion of study forms) and the process for submitting data. Specific training was provided on the completion of two measures used to assess patients: the Birmingham Vasculitis Activity Score (BVAS) and the Vasculitis Damage Index (VDI). Clinicians and research nurses were required to achieve test scores of 85% for the BVAS and 75% for the VDI (and at least 50% of all individual cases had to be correct) before they were approved for scoring the two measures.
Monitoring ultrasound during the study: quality control by expert review Once a sonographer had successfully completed and passed all three components of the training assessment, they were approved to scan patients with suspected GCA who were recruited to the study. In order to ensure that the quality of scanning was maintained, a process of ongoing quality control was developed and implemented. The ultrasound case report forms and recordings for each patient were submitted and reviewed by at least one of the four expert reviewers. Recordings were uploaded to a central ultrasound database which allowed remote access for reviewers. Reviewers assessed the quality of images collected and their agreement or otherwise with the sonographer's interpretation of the recordings. If the expert reviewers had concerns about the performance of a sonographer, then the sonographer was required to undergo additional training before being approved for scanning patients in the study.
Clinical data collection Patients who were referred with suspected GCA were screened to check their eligibility for recruitment into the study. Patients who were eligible and gave informed consent had a full clinical assessment at presentation. Appointments for ultrasound scans and then biopsy were arranged and patients returned for a follow-up clinical assessment after 2 weeks (Figure  1 ). After the 2-week assessment and after seeing the biopsy report, the clinician (who remained blinded to the ultrasound results) decided whether or not the patient had features consistent with a diagnosis of GCA. The result of the ultrasound was unblinded only if the clinician concluded that the patient did not have features consistent with GCA and was therefore planning to withdraw steroid therapy rapidly.
Additional tests included measurement of full blood count, haemoglobin, biochemistry, ANCA and urine dipstick testing if there was a clinical indication. Data were also collected on whether or not, and when, treatment with high-dose glucocorticoids for suspected GCA had been started, the route and dose and any treatment with an immunosuppressant agent. The patient was asked to complete a EuroQol-5 Dimensions (EQ-5D) 3-levels questionnaire at the assessment. 65 EQ-5D is a generic measure of health-related quality of life, necessary for the calculation of the cost-effectiveness of the two main diagnostic tests.
Patient assessment at 2 weeks and 6 months The biopsy and ultrasound tests were completed prior to the patient assessment at 2 weeks. The results of the biopsy were provided to the clinician before the 2-week assessment but the ultrasound results were not shown. The 2-week assessment included the clinician's assessment of the biopsy report and whether or not the biopsy was consistent with GCA. It was therefore possible for the pathologist and clinician to have different opinions on whether or not the biopsy result was consistent with GCA. The patient assessments at 2 weeks and 6 months comprised changes in current conditions and symptoms, a repeat of the physical examination performed at presentation and the results of laboratory tests. Data for two measures of disease activity and damage were also collected at 2 weeks and 6 months.
Items are reported in the VDI if they have been present for at least 3 months and have occurred since the onset of vasculitis. There is no attribution to cause and it has been used in large cohorts of patients with primary systemic small vessel vasculitis. 70 Data from the BVAS and the VDI can also be used to examine the possible presence of an alternative form of vasculitis. Data were also collected on weight, blood pressure, treatment with steroids and immunosuppressive drugs, and quality of life using the EQ-5D. At the 2-week assessment, the clinician was required to state whether or not the patient had features consistent with GCA and, if responding yes, to indicate which of the following influenced the response: symptoms, signs, blood abnormalities, biopsy or other (to be specified). If the patient's features were not consistent with GCA then the clinician was required to give at least one alternative diagnosis.
Pathologists were required to indicate if there was an inflammatory infiltrate in the sample (and the predominant site of any inflammation) and indicate if any of the following features were present: normal areas, giant cells, calcification or any other unusual features. Data were also captured on presence and causes of complete occlusion of the vessel or presence of thrombus or evidence of recanalisation in at least one section of the vessel. The pathological diagnosis was reported as either normal or any the following: compatible with a diagnosis of GCA, compatible with another vasculitis, compatible with arteriosclerosis and compatible with any other diagnosis as specified by the pathologist. The actual pathological slides were sent to the TABUL office for image acquisition. Digital image acquisition was achieved using an Aperio Scanscope Turbo AT (Leica Biosystems, Buffalo Grove, IL, USA).
Slides were loaded onto the machine's autoloader and pre-snapped to obtain a macroscopic image before proceeding with digital scanning. The macroscopic image was used to set the tissue area, focal plane, focus points, white balance, scan/slide settings and labelling description. Once the settings had been optimised the slides were scanned in fragments and digitally stitched together to form one high-resolution virtual representation of the pathology slide. These virtual slides were stored on an external physical server and a web-based database (Aperio eSlideManager V1. 0, Leica Biosystems) was used to archive and store the eSlides. Slides could be viewed remotely using Aperio's web-based viewing systems (Leica Biosystems).
Furthermore, any patient who had their diagnosis altered during follow-up (typically for a diagnosis altered to GCA from not GCA following unblinding of the ultrasound report) was automatically referred for expert review regardless of any confirmed reference diagnosis given above. The expert review group comprised five rheumatologists involved in the study. Each case requiring expert review was independently assessed by three of the five rheumatologists, and no rheumatologist could review cases from their own site. A summary report for each patient was extracted from the clinical data and included information on symptoms, GCA-related complications, items from the ACR classification criteria and the clinician's diagnosis. Access to the clinical database was also given so that expert reviewers could examine all data collected as part of the study with the exception of the ultrasound results.
Finally, cases were excluded if the quality of the ultrasound images was judged to be poor by expert review during quality control. Disagreement with the original sonographer's interpretation by expert review or difficulty in interpreting the ultrasound by expert review despite adequate quality videos were not criteria for exclusion. Identification of cases was performed in three stages before the start of the exercise because the main TABUL database and the ultrasound and biopsy databases had not been locked at the time of initial selection and because of the work involved in ensuring that videos and images were eligible. The first stage involved identifying potentially eligible cases from the list of patients recruited to the main study who had had their ultrasound videos uploaded. This list of potentially eligible cases was ordered using random numbers generated using Stata version 13 (StataCorp LP, College Station, TX, USA).
The second stage involved populating the 33 rating cases from the top of the list. Any case found to be ineligible was replaced with the next available case from the list. This process was repeated until all 33 rating cases were deemed eligible. The third stage involved pilot testing of the exercise and review of all videos and images by two pathologists (BM, KW) and two sonographers (WAS, JP) to ensure that the criteria relating to the videos and images were met. The five training cases were selected purposively starting at the bottom of the ordered list. These were selected to ensure that there were at least two abnormal and two normal cases for the biopsy images and for the ultrasound videos. A final post-exercise stage involved a further eligibility check of the rating cases against the locked database.
COST-EFFECTIVENESS ANALYSIS NIHR Journals Library www. journalslibrary. nihr. ac. uk All of these 27 patients were included in the clinical vignette exercise as part of the original random sample (as reported in Chapter 6) or in an additional sample for the economic analysis. The panel members rating the vignettes reported their assessment of the diagnosis (definite, probable, possible or not GCA) and the appropriateness of continuing treatment with high-dose steroids (on a scale from 1 = extremely inappropriate to 9 = extremely appropriate) using data collected at presentation and at 2 weeks plus the result of the ultrasound. The economic analysis used the available results from the clinical vignettes, from the first 12 clinicians who completed the exercise. To dichotomise the continuation of high-dose steroids ratings into a yes/no outcome, a score of 5 or higher was used to indicate a decision to continue treatment.
Will my taking part be kept confidential? All patient information is stored on password protected computer databases and in locked filing cabinets and will only be accessible to the TABUL research team and regulatory authorities for auditing and monitoring purposes. You will be allocated a unique study number and staff not directly involved with you will know you only by this number. When the results of the study are reported, individuals who have taken part will not be identified in any way. Again we must emphasise that none of your samples will identify you in any way as we will use your unique study number when storing them. Responsible members of the University of Oxford or the local Hospital NHS Trust may be given access to data for monitoring or audit of the study to ensure we are complying with regulations.
Berkshire Research Ethics Committee have reviewed the study and given it a favourable opinion. In addition your local NHS hospital Trust have and your local rheumatologist or ophthalmologist have approved the study. 17. Further Information If you require more information about this study please call one of the telephone numbers provided to speak to a clinical member of the research team or, alternatively look at the clinical trials website: http://clinicaltrials. gov/ct2/show/NCT00974883. Thank you for reading this. If you have any questions or would like any more information please contact the TABUL Office by phone: XXXX (XXXX) or XXXX (XXXX) DOI: 10. 3310/hta20900 HEALTH TECHNOLOGY ASSESSMENT 2016 VOL. 20 NO. Queen's Printer and Controller of HMSO 2016. This work was produced by Luqmani et al.
Acknowledgements Contributions of authors Raashid Luqmani  (Chief Investigator) conceived the study design, contributed to the management and conduct of the study, acted as a reviewer for reference diagnosis and drafted and revised the report. Ellen Lee  planned and conducted the statistical analysis, drafted and revised Chapters 4 and 5 and reviewed a draft of the report. Surjeet Singh  (Trial Manager) contributed to the design, conduct and management of the study and contributed to drafting and revising the report. Mike Gillett  planned and conducted the cost-effectiveness analysis, drafted and revised Chapter 7 and reviewed a draft of the report. Wolfgang A Schmidt contributed to the design and conduct of the study, was involved in ultrasound training and expert review and reviewed a draft of the report.
Raashid Luqmani received honoraria from  GlaxoSmithKline (GSK), Nordic and Chemocentryx  for training in the use of the  Birmingham Vasculitis Activity Score and Vasculitis Damage Index , and personal fees from  Roche  outside the submitted work. Raashid Luqmani  received grants from  Fundação para a Ciência e Tecnologia (Portugal) ,  Canadian Institute of Health Research, Arthritis Research UK, Trust Innovation Challenge Competition and Vasculitis UK. Raashid Luqmani  has patents pending for a mechanical arm to automate acquisition of ultrasound images and analysis for reviewing ultrasound images. Bhaskar Dasgupta received personal fees from  GSK ,  Servier ,  Roche ,  Merck , and  Mundipharma  and grants from  Napp  outside the submitted work. Andrew Hutchings  was funded by a  Medical Research Council  special training fellowship in health services research during the development of the study.
90 © 90 Berkshire Research Ethics Committee have reviewed the study and given it a favourable opinion. In addition your local NHS hospital Trust have and your local rheumatologist or ophthalmologist have approved the study. 17. Further Information If you require more information about this study please call one of the telephone numbers provided to speak to a clinical member of the research team or, alternatively look at the clinical trials website: http://clinicaltrials. gov/ct2/show/NCT00974883. Thank you for reading this. If you have any questions or would like any more information please contact the TABUL Office by phone: XXXX (XXXX) or XXXX (XXXX) DOI: 10. 3310/hta20900 HEALTH TECHNOLOGY ASSESSMENT 2016 VOL. 20 NO. Queen's Printer and Controller of HMSO 2016. This work was produced by Luqmani et al.
9 12. 3 30. 0 20-35 Ranked from the fastest to the slowest median time. No data were available for scan times at one site. FIGURE 10 Range of times taken to complete scans during the course of the study (n = 371). US, ultrasound. DESCRIPTION OF THE STUDY POPULATION, RECRUITMENT AND ELIGIBILITY NIHR Journals Library www. journalslibrary. nihr. ac. uk © Queen's Printer and Controller of HMSO 2016. This work was produced by Luqmani et al. under the terms of a commissioning contract issued by the Secretary of State forHealth. This issue may be freely reproduced for the purposes of private research and study and extracts (or indeed, the full report) may be included in professional journals provided that suitable acknowledgement is made and the reproduction is not associated with any form of advertising.
Sabetta [2011]  also provides the loss estimates made by the Italian Civil Protection for this earthquake using the SIGE software. From the viewpoint of justifying the nonevacuation of L'Aquila during the seismic crisis,  Zechar et al. [2014]  and  van Stiphout et al. [2010]  estimated the damage using the QLARM software, which is based on EMS98 vulnerability classes. They used a generic vulnerability model for L'Aquila, with 30% of buildings in EMS98 class A (the most vulnerable), 30% in class B, 30% in class C and 10% in class D (the least vulnerable). This generic distribution will be discussed later in the present article. Considering hindcasts for other recent moderate earthquakes in Europe,  Rivas-Medina et al. [2014]  compare predicted and observed damage for the Lorca 2011 earthquake (M w 5.
The final outcome is the distribution in terms of the six levels defined in EMS98: D0 (undamaged), D1 (slight damage), D2 (moderate damage), D3 (heavy damage), D4 (partial collapse) and D5 (total collapse) for each location that is separately considered. This procedure is programmed in the in-house BRGM software Armagedom, which was used for the computations presented here. Details on the procedure and the software are provided by  Sedan et al. [2013].
Observed macroseismic intensities in central Italy The observed intensities using the Mercalli-Cancani-Sieberg (MCS) scale reported by  Galli et al. [2009]  are available in the DMBI database  [Stucchi et al. 2007 , Locati et al. 2011]. So as to facilitate comparisons with the predicted intensities (made at all grid points within the area), these observations are interpolated using kriging with a trend [e. g. Douglas 2007 ] taking account of the fault location. It should be noted that strictly speaking intensities are integers and hence they cannot be processed in this way. The assumption that intensities can be manipulated like continuous variables is, however, commonly made because it enables analyses (in this case, interpolation) that would not be possible if intensities were considered only as integers.
Hindcasting the observations This section discusses several options for hindcasting the damage observations. The first method is called the "standard approach" or "blind scenario". In this approach the only measured data used are the epicentral coordinates and the moment magnitude. Next the median ground motions (PGA or PGV) are estimated using a GMPE taking into account a national EC8 site classification map, the estimation of the macroseismic intensity using a published GMICE and, finally, the damage assessment using, in the present work, the RISK-UE procedure. As noted above two GMPEs adapted to European context have been used and for the Akkar and Bommer [2010] model the fault location available on the INGV (the Italian Istituto Nazionale di Geofisica e Vulcanologia) ShakeMap website has been taken into account.
GMPEs generally assume isotropic attenuation in all directions and the instrumental network was not dense enough to capture the heterogeneities. The historical center of L'Aquila is one of the points where observed and estimated intensities (VIII-IX) are similar. In Italy, the software ShakeMap has been operational at the Istituto Nazionale di Geofisica e Vulcanologia since 2006  [Michelini et al. 2008, Faenza and Michelini 2010 ]. According to  Faenza and Michelini [2010] , this software uses the GMICE of  Wald et al. [1999]. The ShakeMap for the L'Aquila earthquake is available on Shakemap INGV archives  (INGV [2009] , http://shakemap. rm. ingv. it/shake/2206496920/intensity. html). The predicted intensities for this event vary between VII and VIII in the L'Aquila municipality. This estimated intensity map has been used as one of the attempts to better match the observations.
Data and sharing resources Census data and Italian city district delimitation is taken from ISTAT: http://www. istat. it/it/archivio/104 317 (last accessed August 4, 2014). ShakeMaps are taken from: http://shakemap. rm. ingv. it/shake/2206496920/products. html (last accessed August 4, 2014). L'Aquila earthquake observed intensities are taken from DMBI-EMIDIUS database: http://emidius. mi. ingv. it/DBMI11/query_eq/20090406. htm (last accessed  August 4, 2014). Building habitability classifications in L'Aquila municipality are taken from: http://laquila. geoportal. it/ websit/default. aspx?Utente=laquila (last accessed  August 4, 2014). Microzonations data are taken from: http://www. protezionecivile. gov. it/jcms/it/microzonazione_aqui lano. wp (last accessed August 5, 2014). Building damage observations for the center of L'Aquila are taken from  Tertulliani et al.
Acknowledgements. This study was supported by an internal  BRGM  project (Multirisk). Developments of the risk evaluation procedure used here have been supported by various projects, including by the  French Ministry of the Environment , the  World Bank  and the  European Commission. We thank:  Giuseppe Di Capua  for providing the GIS file of the Italian site classification and  Julien Duhauvelle  for data compilation and GIS treatment. Lastly, we are grateful to two anonymous reviewers for their careful and constructive comments on an earlier version of this article.
M. bohemicum genomic DNA was then sequenced in 2 Illumina MiSeq runs (Illumina, Inc. , San Diego, CA, USA) using a 5-kb mate-paired library and one Roche 454 run using a 5-kb paired-end library (Roche, Basel, Switzerland). Reads from the 454 sequencer were assembled using Newbler software (Roche) and reads from Illumina were trimmed using Trimmomatic  (7) , and assembled using SPAdes v3. 5  (8, 9). Contigs were combined together by SSPACE v2  (10) , Opera v2  (11)  helped by GapFiller v1. 10 (12), and homemade tools in Python to refine the set. Finally, the draft genome of M. bohemicum DSM 44277 T consists of 18 scaffolds and 31 contigs containing 5,097,190-bp. The GϩC content of this genome is 68. 64%. Noncoding genes and miscellaneous features were predicted using RNAmmer  (13) , ARAGORN  (14) , Rfam  (15) , Pfam  (16) , and Infernal  (17).
Coding DNA sequences (CDSs) were predicted using Prodigal  (18)  and functional annotation was achieved using BLASTϩ  (19)  and HMMER3  (20)  against the UniProtKB database  (21). The genome was shown to encode at least 75 predicted RNAs including three rRNAs, 57 tRNAs, one transfer-messenger RNA (tmRNA), and 14 miscellaneous RNAs. A total of 4,840 identified genes yielded a coding capacity of 4,578,093 bp (coding percentage, 89. 82%). Among these genes, 255 (5. 27%) were found to be putative proteins and 785 (16. 22%) were assigned as hypothetical proteins. Moreover, 3,383 genes matched a least one sequence in the Clusters of Orthologous Groups database  (22, 23)  with BLASTp default parameters. In silico DNA-DNA hybridization (DDH)  (24)  was performed with nine reference genomes selected on the basis of their 16S rRNA gene proximity with M.