dataesr/scientific-paragraphs-categorization huggingface dataset:
This approach had ensured repeatability of the experiments and transferability of the data. We have developed and validated personalised SOPs for the handling of biological samples for the management and traceability of samples from patients enrolled in a multicenter multidisciplinary -omics study, in order to guarantee reliable results, independent of the clinical centre that isolated the sample. Our results, obtained from the first 10 patients enrolled from each clinical centre, suggest that the three SOPs are suitable for the -omics analyses. Moreover, strict adherence to these SOPs and centralized data analysis, with clinical data stored in an annotated database, it resulted in with a better reproducibility obtaining high- quality clinical endpoints correlating our genomics, glycomics and activomics data with others new -omics determinants  [20].
Nevertheless, SOPs remain largely exploratory and may require a re-evaluation from the practical point of view after their implementation in the ongoing worldwide study. Next step will be to implement even more our SOPs introducing cryotubes with a chipreadable database connected to an laboratory information management system (LIMS). In this way we can trace better all the activities performed with this sample, making it traceable and identifying the most suitable samples for subsequent analysis. All these data could be uploaded in a web-based database in order both to have a online access to all data and, eventually, to change SOPs accordingly to specific needs of the study (improving the quality of the single study).
Acknowledgments This work was carried out in framework of the European Community's  Seventh Framework Programme funded PainOmics project  (Grant agreement n. 602736). The research was conducted in collaboration with the "PainOmics Group", involved in scientific support and data collection, leaded by  Massimo Allegri  (massimo. allegri@unipr. it),and represented as below:  Marco Baciarello  (mbaciarello@parmanesthesia. com), Maurizio Marchesini  (mmarchesini@parmanesthesia. com) and  Christian Compagnone  (ccompagnone@gmail. com),  Anesthesia, Critical Care and Pain Medicine Unit, Division of Surgical Sciences, Department of Medicine and Surgery, University of Parma, Parma, Italy ;  Maja Pučić Baković  (mpucicbakovic@genos. hr) and  Mislav Novokmet  (mnovokmet@genos. hr),Genos,  Glycoscience Research Laboratory ,  Hondlova 2/11 , HR-10000 Zagreb;  Lennart C.
The present study is not funded by Industry or any other commercial sponsors. This trial is funded academic research; it is supported by funding from the  European Commission FP7  Project in the context of the THEME [HEALTH. 2013. 2. 2. received from the European grant provided support in the form of salaries for authors (CD, MDG, GL, JMD, YA) but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the 'author contributions' section.
Patients and Methods (15)  The second patient group was from a center that favored the second resection strategy (University of Tokyo Hospital, Tokyo, Japan). (9, 16) election criteria of salvage LT  (13) (14) (15)  and second resection  (9, 16)  have been previously described by the authors from the 2 centers. Informed consent was obtained from each patient upon enrollment in the chosen strategy. After approval from the institutional review board of each institution, data on all consecutive HCC patients who underwent primary liver resection between 1994 and 2011 were retrieved from the prospectively maintained database of each center. The study population included all patients meeting the following criteria: 1. Primary resection had been performed for a resectable and transplantable tumor (see definitions below).
First, patients who underwent primary resection for initially resectable and transplantable HCC, analyzed on an intention-to treat basis, were matched at a 1:1 ratio. Second, patients who achieved the salvage LT or second resection strategy were matched at a 1:2 ratio after excluding patients without tumor recurrence, ie, postoperative (salvage LT or second resection) death and/or the absence of HCC upon histological examination of a resected or explanted specimen. Two-tailed P values < 0. 05 were considered significant. Statistical analyses were performed using SPSS software, version 22 (IBM SPSS Statistics, Armonk, NY). The present study complies with REporting of studies Conducted using Observational Routinely-collected Data (RECORD) guidelines.
MosaiquesVisu was used to analyse the CE-MS data  27. Twenty nine collagen peptides that have been identified previously as being of high abundance and without apparent association to disease were used as internal standards  11. Briefly, ion counts are employed as measure of relative abundance, and are calibrated based on the abundance of the 29 predefined internal standards, using linear regression analysis  11. This approach has been tested extensively and used in over 100 studies and over 10000 samples  28  , and is being routinely employed in a number of large randomized controlled trials  [29] [30] [31]. All detected peptides were deposited, matched, and annotated in a MicrosoftSQL database  26  , allowing for further analysis and comparison between case and control groups. Sequencing of target peptides was performed as described  32  , using Dionex Ultimate 3000 RSLS nano flow system (Dionex, Camberly UK) and a Beckman CE, coupled to an Orbitrap Velos MS instrument (Thermo Scientific).
Statistical analysis and classifier development. After testing for normal distribution, continuous data were compared by Wilcoxon t-test, as this test has proven to be of superior statistical power in proteomics datasets  14. A p-value of < 0. 05 was considered to be statistically significant. In order to control for the false discovery rate, the p-values were adjusted by the Benjamini and Hochberg method  33. For the development of classifiers, the amplitudes of the single peptides that were selected as biomarkers were combined using a support vector machine (SVM), to result in a single variable (SVM score)  14. The process of statistical analysis and subsequent classifier development has been previously optimized specifically for urinary peptide data from CE-MS analysis  14  and has been applied as routine procedure in multiple studies, some also jointly with regulatory agencies  34  , and acknowledged as being of significant value by regulators  35.
Inert Case The first simulation was performed under non-reactive conditions in order to demonstrate the validity of the spray model. Figure  4  shows the LES results compared to experimental data provided by Sandia National Laboratories via the ECN online data base [2]. The vapor penetration was extracted from schlieren measurements, while the liquid penetration length was obtained by both, Diffusive Backlight Illumination (DBI) and the Mie-Scattering. The numerical values have been calculated according to the ECN modeling standards. The vapor penetration is defined as the maximum distance from the nozzle orifice to the position, where the fuel mass fraction of 0. 1% is exceeded. The liquid penetration denotes the farthest axial distance from the nozzle to the position of 0. 1% liquid volume fraction, which is evaluated over cylindrical volumes of 1 mm length and 1 mm diameter.
SUMMARY AND CONCLUSION A MRIF model for LES was presented and applied to the Spray A case of the ECN. The spray model imposes droplet information that have been extracted from a coupled LES/DNS of the nozzle-internal flow and primary breakup and no further parameter tuning of the Lagrangian spray model was required. The spray model results were compared with experimental data in a non-reactive setup, showing very good agreement in terms of spray penetration, but simultaneously slightly underpredicting the fuel mass within the spray core. Nevertheless, in the reactive case, the combustion showed fairly good agreement with the characteristics of both, low temperature and high temperature combustion and hence, the MRIF model seems to capture the relevant physical processes of Diesel type combustion.
ACKNOWLEDGMENTS The authors from RWTH Aachen University gratefully acknowledge funding from the Cluster of Excellence "Tailor-Made Fuels from Biomass" funded by the Excellence Initiative by the German Federal and State governments to promote science and research at German universities. This work was performed as a part of the GRK 1856 funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation). The authors gratefully acknowledge computing time granted for the project JHPC18 by the JARA-HPC Vergabegremium and provided on the JARA-HPC Partition part of the supercomputer JUQUEEN  [41].
Materials and methods The data on the epizootological and epidemiological situation of zoonotic infectious diseases in the territories of Altai Krai and Altai Republic in the preflood period were used in the current work. There was analyzed the information on the zoonotic infections and the data of the epizootological monitoring obtained by the Irkutsk Antiplague Research Institute of Siberia and Far East of Rospotrebnadzor, Plague control station of Rospotrebnadzor, Federal Service on Surveillance in the Sphere of Consumer Rights Protection and Human Welfare in Altai Krai, Federal Service on Surveillance in the Sphere of Consumer Rights Protection and Human Welfare in Altai Republic.
Statistical analysis Data are presented as mean AE S. D. Kolmogorov-Smirnov analysis was used to check for normality of data. Statistical analyses were performed using the Student's t-test, and the Mann-Whitney test for non-parametric data, using SPSS 19. 0. 1 (SPSS, Inc. , Chicago, IL). Associations between sLRP1 and blood lipid levels or clinical variables were assessed by Pearson correlation for continuous variables and linear regression for categorical variables. Differences were considered significant when P < 0. 05.
Acknowledgements The authors thank  Dr. Francisco S anchez-Madrid  and  Dr. Mar ıa Ya ñez-Mo  for kindly gifting anti-CD9 and CD81 antibodies, and  Beatriz Gonz alez ,  Roser Cabanes ,  Margarita Rodr ıguez ,  Carmen Rivas ,  Nuria Benito  and  Alba Ros  for invaluable work in the Heart Failure Clinic. We specially express gratitude to the reviewers and editors for helpful comments and advice.
Funding source This work was supported by grants from the  Ministerio de Educaci on y Ciencia  ( SAF2014-59892-R) , the  Ministerio de Econom ıa y Competitividad  ( Juan de la Cierva ,  JCI-2012-14025 ),  Fundaci o La MARAT O de TV3  ( 201502 ,  201516 ,  201521_10 ), the  Fundaci o Daniel Bravo Andreu , the  Sociedad Espa ñola de Cardiolog ıa , the  Societat Catalana de Cardiologia , the  Generalitat de Catalunya  ( SGR 2014 ,  CERCA Programme ), and the  Fundaci o Banc aria La Caixa. This work was also funded by the  Red de Terapia Celular -TerCel  ( RD16/0011/ 0006 ), the  CIBER Cardiovascular - ( CB16/11/00403 ) and  Fondo de Investigaci on Sanitaria, Instituto de Salud Carlos III  ( FIS PI14/01682 ,  FIS PI14/01729  and  CD14/00109 ) as part of the  Plan Nacional de I+D+I  cofounded by  ISCIII-Sudirecci on General de Evaluaci on y el Fondo Europeo de Desarrollo Regional (FEDER).
( 11 ) The time response of the model defined by  (11)  was obtained by transforming it into the form presented graphically in Fig. 3 , where integration and differentiation operations are of fractional order α. This model was used during the process of estimation of supercapacitor parameters. The tested supercapacitor was identified using the system presented in Fig. 4a. The control procedure of the entire system was developed using the Matlab/Simulink software with xPC Toolbox. The system consisted of a desktop PC (xPC Target) with the installed measurement card NI-DAQ and master computer (xPC Host). The computers were interconnected through the Ethernet network. The supercapacitor was charged and discharged by (voltage-controlled) voltage source (Fig. 4b ) of current efficiency up to ± 3 A.
sample description In total, data were collected from 382 cigarette smokers with the response rate of 92%, ranging from 88% to 96% in different collection centers. Study participants were mainly males (61%). Around 49. 2% were 45 years. The mean age was 44. 52 years (standard deviation [SD] =14. 1; Table  1 ). Concerning the smoking habits of smokers, 52. 4% of our participants indicated that they smoked around 10-25 cigarettes a day, compared to 38% who reported smoking 25 cigarettes per day and 10% reported smoking 10 cigarettes daily. The median duration of cigarette tobacco use was 20 years (IQR =10-31), and the median age of smoking first cigarette was 18 years (IQR =16-21). In regard to the Fagerström scale, around 69% of our participants were classified as highly dependent on nicotine.
The concept of BIM use is closely linked to the level of detail of information concept to describe which project information has to be exchanged  (Kreider and Messner 2013; Penn State 2011). In linear infrastructure project, we have to integrate geospatial information. In geospatial information modeling and in Geospatial Information System (GIS), the level of detail concept is generally dedicated to model objects with the most relevant geometry and representation according to a specific objective of analysis and working scale  (Ruas 2004). A Level Of Detail (LOD) defined in the CityGML standard facilitates the visualization and the analysis of data for 3D city models. For instance, an object can have different representations for each LOD which enables analysis and visualization of the same object with several degrees of resolution  (Groger and Plumer 2012).
Used formalisms To maintain consistency between defined models in each use case, we selected proven and well known formalisms. The first one is UML: it is used modeling conceptual data models for instance. It allows to describe many aspects of models, keep consistency and facilitate interaction between collaborators defining the project conceptual data model  (Nugroho and Chaudron 2009). The second formalism is also well known in the industry. It is called Structured Analysis and Design Technique (SADT). It allows giving a framework to define an activity: incoming, outgoing, all constraints and also supports of the activity. The last one called PER-CEPTORY is used to describe spatio-temporal database. It is a UML profile  (Bédard 1999 ) (Fig. 6 , right hand side). We propose to use a combination of these three formalisms to clearly define 3D objects workflows and also geometric and semantic transformations they undergo during the entire process to meet requirements (Fig.
Applying system engineering and requirement engineering on design project The second stage of the bottom-up approach is to identify all the elements impacting the product-system. For a design project, we consider that the product-system, the design result, is composed of the conceptual data model of the infrastructure project and the data base of the project. That means object modeling with the relevant level of detail of the information, according to the design phase (or phases). It is a part of the whole product-system (Fig. 7 ). In the design project, the deliverable is only the modeling of the project and not the constructed project with its digital mockup and database. The product-system of the construction phase has to be, considering BIM processes, the constructed project with operating system and its digital mockup, modeling the project as-realized.
The mitoSOX fluorescence intensity of mitochondrial regions of interest were determined using the ImageJ software. Protein extraction and sub-cellular fractionation. Cells were suspended in 500 µL lysis buffer (150 mM NaCl, 1% v/v Triton X-100, 20 mM Tris pH 7. 4) containing protease inhibitor cocktail (Roche, 05892791001) for 20 min on ice. Cell debris was removed by centrifugation at 12,000 g for 10 min to obtain the supernatant whole cell lysate. When sub-cellular fractionation was required, cells were suspended in 500 μL fractionation buffer (250 mM Sucrose, 10 mM KCl, 1. 5 mM MgCl 2 , 1 mM EDTA, 1 mM EGTA, 20 mM HEPES, pH 7. 4) containing protease inhibitor cocktail and passed through a 26-gauge needle 20 times using a 1 mL syringe, followed by 20 minutes incubation on ice. Unbroken cells and nuclei were removed by centrifugation at 800 g for 5 minutes at 4 °C.
Determination of cellular Oxygen Consumption Rate (OCR). On the day before experiment, treated and untreated cells were seeded in triplicate on Seahorse XFp cell culture miniplates (3 × 10 4 cells per well). OCR was measured with a Seahorse XFp extracellular flux analyser, using a Seahorse XFp cell mito stress test kit and following manufacturer's instructions (as reported in Supplemental Experimental Procedures). Data obtained from the assay were analysed with the Seahorse XFp analysis software and normalized to the amount of mitochondrial protein of each sample, in order to avoid misinterpretation of data due to differences in mitochondrial mass between samples (as explained in ref. 23). Western blotting. Sample proteins were quantified using a bicinchoninic acid (BCA) protein assay kit (Fisher Scientific, 13276818).
After a further washing step (TBS-T, 3 × 5 mins at RT), proteins were detected using an ECL Plus western blotting detection kit (Fisher Scientific, 12316992). ImageJ software was used to analyze immunoreactive bands by densitometry. Immunofluorescence. Cells were treated as indicated in the figure legends and then fixed in 4% paraformaldehyde (PFA) for 10 mins at room temperature followed by washing with PBS (3 × 5 min). The cells were then permeabilized with 0. 5% Triton-X in PBS (15 mins, RT), rinsed with PBS (3 × 5 min) and blocked with 10% goat serum and 3% bovine serum albumin in PBS for 1 h at room temperature. The cells were then incubated with primary antibodies diluted in blocking solution overnight at 4 °C. Following a further wash step, secondary antibodies were incubated for 1 h in blocking solution.
Acknowledgements The research activities led by M. C. are supported by the following funders, which are gratefully acknowledged:  Biotechnology and Biological Sciences Research Council  [grant numbers  BB/M010384/1  and  BB/N007042/1 ]; the  Medical Research Council  [grant number  G1100809/2 ],  Bloomsbury Colleges Consortium PhD Studentship Scheme ; The  Petplan Charitable Trust ;  Umberto Veronesi Foundation ;  Marie Curie Actions and LAM-Bighi Grant Initiative. G. W. acknowledges  Cancer Research UK  ( C9344/A10268 ), the  BBSRC  ( BB/L01923X/1 ) and  UCL School of Pharmacy  for financial support.
Corresp ondence to: R. Denysiuk; e mail: roman@ dep. uminho. pt Contract grant sponsor: The Portuguese Funda9llo para a Ciencia e Tecnolo gia under grant PEst C/CTMJLA0025/2013; contract grant number: Proj ecto Estrategico LA 25 2013 2014 Strategic Project LA 25 2013 2014; contract grant sponsor: project Matepro "Optimizing Materials and Proc esses" ; contract grant number: ref. NORTE (J7 01 24 FEDER 000037 sup ported by the ON. 2 program, Portugal); Contract grant sponsor: The European Comission under proj ect SEACW: Social &osystem for anti aging, capacitation and wellbeing.
The Open Journal of Bioresources (OJB) A second tool to help track bioresources comes in the form of a new journal called The Open Journal of Bioresources (OJB, http://openbioresources. metajnl. com) which Bfeatures peer-reviewed short papers helping researchers to locate and cite bioresources with high reuse potential^. The OJB is a socalled meta-journal with articles that are citable, and such citations can be tracked. The idea behind OJB is to provide a permanent Bmarker^article so that users can always cite a bioresource they have accessed or referred to. It is important to note that a bioresource article does not replace a research article (e. g. where original analyses of data are presented). It is meant to describe the resource as such, not to report any results obtained using the resource.
Ongoing contacts and discussions with journal editors also serve to push its inclusion in the instructions to authors and reviewers. Additional work is currently being conducted with the Research Data Alliance (which has an aim to facilitate all types of data sharing, https:// www. rd-alliance. org) as an interest group to target at the institutional level. Through these different activities, it is likely that there is greater awareness of the BRIF now than there was in 2013 (including greater awareness of the CoBRA guideline and the Open Journal of Bioresources). We consider that it would take a number of years before awareness would increase significantly. We, therefore, assess that a survey of stakeholders in the coming couple of years would be informative and a good moment to reassess the need for additional dissemination activities.
The BRIF can increase fairness in publication policies by recognising more accurately the different works done by different actors The trend for fair and increased (e. g. open) access to bioresources (especially for data) has been heavily promoted by funding agencies and by Biomedical journals. This said, there remains nonetheless resistance by various stakeholders to granting (greater) access to bioresources. Among the reasons for this resistance is the lack of measures to grant credit to institutions and ensure fair and accurate recognition of the work performed by groups that planned, studied, collected and prepared the collections and the datasets. A recent editorial by  Taichman et al. (2016)  regarding a proposal from the International Committee of Medical Journal Editors (ICMJE) emphasises the need for alternative incentives to recognise contribution in the context of clinical trial data.
If widely implemented, the BRIF could have an important positive impact on the responsible use of bioresources and related datasets. Clearly, we have focussed herein on the positive aspects of the BRIF initiative, as we believe that these clearly outweigh the potential negative aspects. This said, there could also be negative points to consider. As with any method or metric that attempts to measure use (or citations), such as the journal impact factor, perfection is impossible. There is always a possibility that the measuring method may not be adequate for all resources, and that it will not be used or interpreted properly within each resources' specific context. (Ramsden 2009)  Undeniably, the term Bimpact factor^carries a lot of connotations, and the word framework has been added to the BRIF term over the years (from Bioresource Research Impact Factor to Bioresource Research Impact Factor/Framework) to move somewhat away from the strict notion of the impact factor and to more adequately reflect the work-in-progress and the overall approach which includes many different tools.
With respect to the ethical aspects and impacts of the BRIF, by providing an easily accessible overview of existing uses of a bioresource, the BRIF can promote a better use of the bioresource through a virtual cycle and promote the virtues of transparency, fair recognition of work, as well as allow for better informing and potential empowering research participants and patients. One could consider the last two decades as a period of time where a lot of resources were spent creating and developing biobanks and datasets. Now that many different bioresources exist and function, we can consider the time ripe to prioritise the use of funds, time and (human) resources to ensure that these bioresources are used in a responsible and sustainable way; the BRIF clearly contributes to this aim, and as such should be further supported both financially and politically.