dataesr/scientific-paragraphs-categorization huggingface dataset:
Sensitivity analysis A sensitivity analysis was performed by running PLS on data excluding sets where cases were diagnosed within the first 2 years of follow-up. The model was conducted on 271 observations (92 cases, 179 controls), to investigate the performance of the PLS model, ruling out potential reverse causation. The metabolomic profiles of HCC cases diagnosed within 2 years from enrollment could reflect the presence of the tumour rather than informing about tumour aetiology. The variable importance in the projection (VIP) statistic was used to facilitate the comparison of the sensitivity analysis with the main analysis. The VIP expresses the explanatory power of a predictor variable X across all response variables Y (see Supplementary Appendix, available at Mutagenesis Online).
As the outcome (HCC) is rare, direct and indirect effects can be estimated taking into account the case-control design. This is done by using the same formulas for the effects, while running the mediator regression only for the controls  (35). As mediation packages do not yet accommodate conditional logistic models, the outcome and the mediator models, which were accommodated in unconditional logistic regressions, were adjusted for centre and age at blood collection for sake of consistency with previous steps of the analysis. Statistical analyses were performed using R  (36)  and SAS (37) in general, with the following packages for specific purposes: PROC PLS in SAS 9. 4 for PLS analyses, 'paramed' in Stata 12  (38)  for mediation analyses, 'OptimalCutpoints' in R for ROC-related assessments.
The AUC of the X-scores and Y-scores for all 3 PLS factors, adjusted for C-reactive protein concentration, alphafetoprotein concentration and the score of liver damage, was 0. 859 and 0. 853, respectively. An increase in the resampled cross-validated AUC values was also observed for all three X-and Y-scores, albeit smaller, with 0. 836 and 0. 827, respectively. Results from the sensitivity analysis conducted on data excluding sets where cases were diagnosed within the first 2 years of follow-up, showed similarities in terms of lifestyle variables' and metabolites' loadings on the PLS factors (Supplementary Table  2 , available at Mutagenesis Online). Notable differences pertained to the identification of new signals for the first PLS factor including ethanol, histidine and an unknown compound.
time  (53) , and the Human Metabolome Database (HMDB) and other related resources  (18, 54) , that offer richly annotated information continuously increasing the metabolite coverage for users, are mostly exploited through time consuming interactive procedures. In addition, individual metabolites often overlap in NMR signals, which can hinder annotations. These challenges, as well as large variability in metabolite concentrations, and disentangling informative signals from noise, are not specific to NMR and pertain to any type of untargeted technique. Such investigations may profit from complementary targeted metabolomic analytical strategies  (54). Throughout the different steps of this work, the scaling problem was first tackled by normalising spectra to total intensity. NMR data were also centred and Pareto-scaled, together with correction for potential batch effects  (16).
The PC-PR2 method offered a way to investigate major sources of systematic variability in NMR and lifestyle data  (15). The variable 'country of origin' emerged as the variable accounting for the largest proportion of total variability, and the residual method was used to control for this variable in the following steps of the analysis. While this may lead to removing regional gradients of dietary variability, this step is instrumental to avoid unwanted systematic regional-specific bias in the data in country-specific questionnaire assessments. In addition, technical aspects like storage and handling of biological samples, fasting status The sensitivity analysis was conducted excluding sets where cases were diagnosed within the first 2 years of follow-up (X-set = 21, Y-set = 285). a Models were adjusted for C-reactive protein concentration, alphafetoprotein concentration and a composite score for liver damage.
Radio-HPLC system The system consisted of two HPLC Kontron 420 pumps (Kontron, Selabo, France), managed with the HPLC software Diamir (Varian Medical Systems, USA). The HPLC system was equipped with a 500 ml loop and an Interchrom Strategy KR100 column C18 (5 mm, 4. 6 Â 250 mm) (Interchim, France) kept in an oven thermostated at 35 °C and connected to an on-line radioactivity analyzer (Packard Flo-one, Flow scintillation analyzer) using Flo-scint as the scintillation cocktail or connected to a Gilson FC 204 fraction collector (Gilson, France) for 4 tubes/min collection, using Packard Ultima Gold as scintillation cocktail, when appropriate. Two mobile phases were used. Mobile phase A containing: water/acetonitrile/acetic acid: 97. 5/2. 5/0. 1; and mobile phase B containing: water/acetonitrile/acetic acid: 40/60/0.
Chromatograms for 0-6 h and 6-24 h urine and mass spectra were analyzed for 0-6 h and 6-24 h urine and feces samples using Xcalibur software (Thermo Scientific). Twin peaks were detected on the basis of their m/z difference of 2. 0067 a. m. u. corresponding to similar chemical formula for 12 C n and 12 C (n À 2) 13 C 2 compounds using the MetWorks software package (Thermo Scientific). The search criteria for chemical formula determination were restricted to a mass error below 5 ppm and C, H, O, N, S, P, K and Na were the only accepted elements. Further MS/MS fragmentation was achieved on twin peaks, for HNE metabolite identification. For MS/MS experiments, excitation parameters (isolation width (1. 5 a. m. u. ), normalized collision energy (35%), excitation time (30 ms)) were adjusted in order to get maximum structural information for the compound of interest.
METHODS Based on the data gathered in each OPEN work package (ie, conducted surveys, qualitative studies, and systematic reviews; see online supplementary figure), each of these groups formulated 4-7 recommendations on how to reduce dissemination bias tailored to their respective key group in the knowledge translation process. These recommendations were compiled, ordered, and harmonised to form draft recommendations used as the basis for discussion at the OPEN workshop, including further international key stakeholders in clinical research. The focus of these recommendations was on non-dissemination of full trials rather than the selective reporting of outcomes 2 and/or analyses. 18 This workshop was held in Freiburg, Germany, on 23-24 May 2013, in order to reach a consensus and to finalise the recommendations.
It also became evident that metasearching, the possibility of searching across different registries through a single interface, is key to their usefulness. This is highly relevant considering existing language barriers and a lack of awareness of the existence of national registries among users, which might result in relevant registers not being included in their searches. A platform offering a metasearch for trials across multiple registries would help in identifying trials that would otherwise have been missed. This recommendation was considered to have longterm, rather than immediate, impact. Together with the favourable balance of benefits and drawbacks, the knowledge of how limited resources could hinder good implementation led us to make this a strong recommendation. As a result of the US FDA Amendments Act, Section 801, passed in 2007, ClinicalTrials.
4  Funding agencies should implement measures to ensure that the evaluation process of funded projects does not end with the project's final report, but instead is followed up until all agreed data have been disseminated (recommendation) 1. 5 Funding agencies should consider providing incentives for researchers who disseminate their results, or, alternatively, withhold a part of the funding until a project's results are adequately disseminated (recommendation) 1. 6  Funding agencies should create a publicly accessible database of all grants awarded and on how their results were disseminated in order to keep an accurate record of funded projects and publication outcomes (recommendation) Pharmaceutical and device companies 2. 1 Pharmaceutical and medical device companies should make their policies concerning the dissemination of methods and results of clinical trials publicly accessible (strong recommendation) Responsible authorities (such as the EMA for drugs) should mandate that all clinical trials in humans falling under their remit are registered in an EU database that is publicly accessible (strong recommendation) 9.
3  Responsible authorities (such as EMA for drugs) should mandate that, on a trial's registration in an EU database, the full protocol approved by the REC, including the potential protocol amendments, is submitted and made publicly available as a searchable document (strong recommendation) 9. 4  Responsible authorities (such as EMA for drugs) should mandate that the full report, including all results (eg, CSR) of a trial, is made available in the same registry that the trial was registered in, in a timely fashion (ie,1 year after trial completion or inactivity) for all trials registered in the EU database (strong recommendation) 9. 5  Responsible authorities (such as EMA for drugs) should ensure that trial sponsors failing to comply with such result submission requirements are sanctioned (strong recommendation) Benefit assessment institutions 10.
5 Benefit assessment institutions should request from legislators the following items which will allow the consideration of all study results (disclosure of full protocols and full CSRs Legislators should ensure that all data related to the health of patients and the public are NOT commercially confidential/proprietary information (strong recommendation) 11. 3  Legislators should institute a legal obligation for manufacturers to submit all data and other required information for the formal decision-making process (strong recommendation) 11. 4  Legislators should ensure that the raw data (anonymised individual patient data) are made publicly available for all clinical trials (registered in the EU database) (strong recommendation) CSR, clinical study report; EMA, European Medicines Agency; EU, European Union; MA, meta-analysis; NMA, network meta-analysis; REC, research ethics committee; SR, systematic review.
The work of identifying all studies that address a particular question undertaken by authors of systematic reviews helps detect dissemination bias. These efforts include systematic literature searches across electronic databases, the search of trial registries  23  and grey literature as well as contacting experts in the field. Also helpful in detecting dissemination bias are, for example, the exploration of selective reporting of outcomes as part of the detailed risk of bias evaluation within systematic reviews,  24  and the graphical (eg, funnel plots) and statistical assessment of potentially selective publication of whole studies (eg, Egger's test). 25 26 Finally, users of systematic reviews will be made aware of the potential impact of dissemination bias on the interpretation of the findings (if these are clearly described by the review authors).
Related literature For general background to magnesium porphyrin species and their applications, see:  Ghosh et al. (2010). For the synthesis of the [Mg II (TPP)(H 2 O)] complex (TPP is the 5,10,15,20-tetraphenylporphyrinate ligand), see:  Timkovich & Tulinsky (1969). In the Cambridge Structural Database (CSD, Version 5. 35;  Groom & Allen, 2014) , there are six magnesium porphyrin structures with aqua ligands deposited. Four from these structures are monoaqua species, derived from [Mg(TOMePP)(H 2 O)] (TOMePP is the 5,10,15,20-tetrakis(4methoxyphenyl)porphyrinate ligand;  Yang & Jacobson, 1991)  and one is a diaqua derivative, [Mg(TPP)(H 2 O) 2 ]Á(18-C-6) where 18-C-6 is 18-crown-6 ether  (Ezzayani et al. , 2013). For the related porphyrin species [Mg(TPP)(4-pic) 2 ] (4-pic = 4picoline) and [Mg(TPP)(H 2 O)], see:  McKee et al.
Experimental (ii) x þ 1 2 ; y þ 1 2 ; z À 1 2 ; (iii) y; Àx; z. Data collection: APEX2  (Bruker, 2006) ; cell refinement: SAINT  (Bruker, 2006) ; data reduction: SAINT; program(s) used to solve structure: SIR97  (Altomare et al. , 1999) ; program(s) used to refine structure: SHELXL97 (Sheldrick, 2008); molecular graphics: ORTEP-3 for Windows  (Farrugia, 2012) ; software used to prepare material for publication: WinGX  (Farrugia, 2012). Nesrine Amiri, Soumaya Nasri, Thierry Roisnel, Gérard Simonneaux and Habib Nasri.
One of the problems is that HVS is very complex and it is difficult to both study and model HVS. For this reason, existing metrics attempt to incorporate a limited number of HVS specific features trying to match HVS judgment as close as possible. The evaluation of such matching (correspondence) is a challenging task as well. One difficulty consists in the fact that performing subjective tests for collecting the mean opinion scores (MOS) is expensive and time consuming. Many observers are required for assessing the visual quality of a quite large number of distorted images collected in the so-called image databases. Then, mean opinion scores of image quality are determined  [9, 10]  and further exploited. Note that different methodologies for database creation and carrying out experiments have been proposed.
There are also different scales for MOS, different ways to remove outliers (abnormal experiments), and various recommendations to observers  [5, [9] [10] [11]. Because of this, the availability of databases of distorted images is quite reduced. Chandler, in  [5] , mentioned 20 existing databases which can be used for assessment of visual quality metrics. Among them, most used are, probably, LIVE  [10] , TID2008  [11] , and Toyama  [12]. Good databases CSIQ and IVPL  [13, 14]  have appeared recently and design of new databases continues  [5]. Available databases need to be improved. There are, at least, four reasons behind this need. A first reason is that intensive use of a given database reveals its drawbacks and limitations. These can be, for example, a limited number of distortions types.
This was the motivation for creating TID2008 database, containing 17 types of distortions to extend the 5 types of distortions present in the LIVE database. A second reason is in the technology evolution pushing new consumer electronic devices and new applications that are characterized by new types of distortions or combinations of distortion types. To adequately cope with these distortions, test sets containing the new impairments should be designed and their perceptual impact addressed. A third reason is that creation of a new database leads to a certain "competition" among researchers. MSSIM has been reported as the best metric applied to TID2008 in  [11]  but quite many new metrics have overcome this result later, in the period 2009-2013. Such a competition is positive for both theory and practice since it results in more universal visual quality metrics or, at least, in designing metrics well suited for certain sets of distortion types.
A fourth reason is in the suggestion we received to increase the number of color distortions and the just noticeable distortions present in TID2008. Based on these considerations, a novel image database, TID2013, has been designed and published  [15, 16]. Due to limited space in Conference Proceedings, many important aspects have not been addressed and described in  [15, 16]. In particular, this relates to motivations for selecting new types of distortions for the new database and methodologies of their simulation. Besides, a limited set of visual quality metrics has been tested for TID2013. However, the most important aspects, to our opinion, concern the results already obtained for the database TID2013 and perspectives of its exploitation in future. The rest of the paper is organized as follows.
Requirements to distorted image databases and peculiarities of the database TID2013 that differ it from TID2008 are considered in Section 2. Section 3 pays a special attention to the description and motivation of the new types of distortions. Section 4 describes the methodology used in the subjective experiments and the collected results. Analysis of results obtained for a set of popular visual quality metrics is given in Section 5. Section 6 concerns a special analysis for some known metrics showing how to determine drawbacks of metrics exploiting TID2013. Finally, Section 7 describes the modalities for accessing to the database and gives information that can be useful for people planning to employ TID2013.
Peculiarities of the new database As it has been mentioned above, the database TID2008 is the predecessor of TID2013. After its creation five years ago, TID2008 served several purposes, both main and auxiliary. The main purpose of TID2008 was the analysis and verification of full-reference metrics  [15, 17]. To this aim, it has been extensively used  [18] [19] [20] [21] [22]. Meanwhile, TID2008 has been also used for auxiliary purposes as testing and efficiency analysis of blind methods for noise variance estimation  [23, 24] , colour image denoising techniques  [25] , and verification of no-reference metrics  [26]. There are basic requirements to databases intended for HVS metric design and assessment. Such a database should contain a reasonably large number of etalon colour images of various content.
TID2008 contains 25 reference (distortionfree, etalon) colour images where 24 images were obtained (by cropping) from the Kodak database http:// r0k. us/graphics/kodak/. The 25-th reference image was artificially created and added to 24 natural scene images -see all 25 distortion-free images as shown in Fig. 1. As it can be seen, the test images are of different content, some of them are quite textural ones whilst others contain large quasi-homogeneous regions. Thus, the abovementioned requirements are satisfied. Size of images in a database can be, in general, debated. However, there are some restrictions and recommendations. First, restrictions deal with methodology of experiment carrying out. Two or three images are usually displayed simultaneously at the monitor screen and their quality is to be assessed (compared).
This means that image size has to allow simultaneous full representation of these images at screen of devices used in experiments. For both TID2008 and TID2013 it was supposed that images were displayed at computer monitors. Because of this, all images were of the same fixed size 512 Â 384 pixel in TID2008 and we have kept the same size for the images in TID2013. There are two things to be considered. First, image size might influence image perception and this motivates using the same size. Second, some participants of the conferences EUVIP2013 and ACIVS2013 have expressed a desire to have larger size test images being interested in such modern applications as HDTV. We are not able to satisfy them but the need in a database for high-resolution applications should be addressed somehow. Another requirement to a database is that it should contain image distortions typical for practice and, simultaneously, these distortions have to relate to certain peculiarities of HVS.
Almost everybody has nowadays met with distortions due to conditions of image acquiring-noise and blur, chromatic aberrations. Many people encountered distortions originating due to compression and data transmission errors. There are also distortions due to specific operations of image processing as denoising, mean and contrast changing, etc. Seventeen types of distortions were taken into account while creating TID2008. They are presented in 17 first rows in Table  1  with explanations what are the main applications a given distortion can be met with and what peculiarity of HVS this distortion type relates to. More details concerning the reasons for including these distortion types into TID2008 and their modeling can be found in  [17]. The main difference of TID2013 compared to TID2008 is that the new database includes 7 new types of distortions marked by items from 18 to 24 in Table  1.
These types of distortions will be considered more in detail in Section 3. Here, we highlight two main aspects. First, we have tried to pay more attention to "color" distortions (#18, 22, and 23) since the percentage of grayscale images that are in use today decreases and preservation of color information becomes more and more important. Second, we attempted to consider new applications (distortion types #19…22 and 24) for which images with the corresponding distortions are absent in existing databases and for which adequate visual quality metrics are expected to be of prime importance. Table  1  needs some additional comments. By "eccentricity" (see the right-hand column) of HVS we mean noticeability of distorted fragments in images, their difference compared to surrounding fragments of reference image in texture, color or other features.
"Robustness" relates to human ability to "filter out" noise (including impulse noise) in images with "restoring" them. "Evenness of distortions" means that humans perceive distortions spread uniformly and distortions placed compactly in different manner. Also note that a certain type of distortions may relate to a mentioned application only partly. Meanwhile, in practice, there are usually several types of distortions typical for each given application. One more requirement to an image database is that images in the database should be challenging for visual quality assessment. This requirement means, in the first order, that number of situations when all quality metrics evidence in favor of a given image among two compared should not be large. Let us give examples of such situations. For instance, it might happen that an observer during an experiment will be asked to compare visual quality of images presented in Fig.
2. Then, the decision is clear and fast since the right-hand image obviously has better visual quality and visual quality metrics also confirm this. Fig. 3  presents another undesirable type of comparison (quality assessment) situation when the same type but different levels of distortions distort two images presented at a monitor screen. The results of comparisons are clear and predictable. HVSmetrics usually have perfect correspondence to such images. This may cause an illusion that metrics perform well and there are no problems with an adequate assessment. An example in Fig. 3  shows that, on one hand, there should not be a large number of distortion levels. Four or five levels are usually enough for a database  [10, 11]  and there were four levels of distortions in TID2008. On the other hand, the database TID2008 has been criticized for not having images with almost invisible (not apparent) distortions  [27].
To cope with this task, we have introduced the fifth distortion level for all test images and all distortion types present in TID2013. This added level approximately corresponds to a peak signal-to-noise ratio (PSNR) equal to 33 dB (recall that for images with other four levels of distortions in TID2008 and TID2013 the PSNR values are approximately equal to 30, 27, 24, and 21 dB). The presence of five levels of distortions is one more distinctive difference of the new database TID2013 compared to TID2008. As a result, TID2013 contains 3000 distorted images (25 test images with 24 types and 5 levels of distortions) in opposite to 1700 distorted images in TID2008. There are also some differences but they relate not directly to the database but to a methodology to obtain MOS and conditions to carry out experiments.