dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgements: This work is partially supported by the grants  ANR-12-BS05-0002  and  ANR-13-BS05-0005  of the  French Agence Nationale de la Recherche. CU was supported by the  Delta-ITP consortium , a programme of the Netherlands organization for scientific research (NWO) that is funded by the  Dutch Ministry of Education, Culture and Science (OCW). CU also kindly acknowledges funding by the  STFC  grant  RG84196  ' Revealing the Structure of the Universe '. We thank the  KIAS Center for Advanced Computation  for providing computing resources. CU thanks IAP,  CITA ,  KIAS  and  KASI  for hospitality during the initiation, evolution and completion of this project. SP thanks KIAS for their hospitality. Special thanks to  Steven Appleby  for his help with Fig 9. We acknowledge support from  S.
In fact, many synthetic antibacterial peptidomimetics are currently undergoing clinical trials, including the membrane-disrupting compound LTX-109, the cationic steroid compound CSA-13, and the novel peptidomimetic brilacidin (see https://clinicaltrials. gov/). Recently, short peptidomimetics made of Arg and N-alkyl/aryl pyrazole residues were shown to have good antimicrobial and anti-inflammatory activities, increased proteolytic stability against trypsin digestion, and antimicrobial activity, even in the presence of physiological salts  (Ahn et al. , 2017). Another series of AMP mimetics were synthesized by incorporating a 3 ′ -amino-[1,1 ′ -biphenyl]-3-carboxylic acid backbone in MSI-78, a peptide currently in Phase-III clinical trials  (Kuppusamy et al. , 2018).
Columns Although there is an incomplete understanding of the mechanisms of action of antibiofilm peptidomimetics, it seems that their amphiphilicity improves their hydrogen and electrostatic interactions with matrix components, such as those with surfactants. In the past 40 years, more than 30,000 articles have been published about microbial biofilms (source: PubMed database). This mass of research has been dedicated to understanding biofilms dynamics and to decreasing its effects, but so far no effective treatment has been developed  (Bjarnsholt et al. , 2013). Antibiofilm AApeptides and peptoids are two very promising families of peptidomimetics for the development and refining of new antibiofilm agents to be used in the fight against resistant microorganisms.
FUNDING This study was funded by the  CAPES-COFECUB program. The institutional partners of this partnership between Brazil and France are the  Brazilian Ministry of Education's CAPES (Coordenação de Aperfeiçoamento de Pessoal de Nível Superior) agency , and the  French Ministère de l'Europe et des Affaires étrangères (MEAE)  and the  Ministère de l'Enseignement supérieur, de la Recherche et de l'Innovation (MESRI). This work was also supported by the  French Agence Nationale pour la Recherche and Direction Générale de l'Armement  (# ANR-14-ASTR-0001 ).
Round 1: establishing principles of timely care The Delphi Chairs and analysts derived 21 timerelated principles from the evidence-based recommendations of Brain health: time matters in multiple sclerosis (Supplementary Table  1 ). 3 The principles were grouped into five domains: onset of symptoms; referral and diagnosis; lifestyle and comorbidities; initiating DMT; monitoring. These were presented to the Delphi Panel who were asked if each was 'an appropriate and accurate description of a good standard when considering brain health in people with MS'. Panellists had the opportunity to explain their opinions and/or propose additional principles. Responses were summarised and presented to the Reviewing Group for evaluation. The Chairs agreed that several principles did not require defined timings, for example, 'Regular inclusion of patient data in MS database'.
Subsequently, the Chairs requested two new variables be included. These concerned timings of events following new or worsened symptoms and were intended to supplement timings for routine monitoring. Multiple-choice options for the two new variables were derived from clinical guidelines. 22 me frames for the final consensus rounds were determined based on the 75th percentile values achieved for each core, achievable and aspirational standard in the Round 3 voting. Four additional statements were derived from principles brought forwards from Round 1 that did not require defined timings, for example, 'The MS team should regularly enter patient data into an MS database'.
Rounds 4 and 5: achieving consensus In Round 4, the Delphi Panel was asked to indicate their level of agreement with the core, achievable and aspirational timings associated with each statement on a five-point scale (strongly disagree, disagree, neither agree nor disagree, agree, strongly agree). Data were analysed to quantify consensus. The threshold for Delphi Panel consensus was agreement (agree, strongly agree) by ⩾75% of panellists. For valid consensus, ⩾66% of panellists who completed Round 1 had to respond to all surveys. These percentages were predefined by the Chairs, based on a literature search.
Using a quality improvement cycle, MS clinics will be able to demonstrate service improvement. We encourage MS teams to incorporate data collection into routine care to support re-evaluation, and to share examples of best practice. In some countries, local budget holders may want further evidence of the clinical benefit of timely care -as described by the quality standards. To generate evidence, MS clinics will need to link results from routine service evaluations with long-term clinical outcomes. MS clinics could collaborate with other centres to allow comparisons and, in the future, MS databases could enable largescale analysis by adding relevant data fields.
175031). D. H. has received grants from Czech Ministry of Education project Progres Q27/LF1, and speaker honoraria, travel expenses and consultancy fees from Biogen, Novartis, Merck, Roche, Sanofi Genzyme and Teva. J. O. has received grants, personal fees and non-financial support from Biogen, Novartis, Roche and Genzyme, and personal fees and non-financial support from Allergan, Merck and Teva. F. P. has received research grants from Biogen, Novartis and Genzyme, and fees for serving as Chair of DMC in clinical trials with Parexel. P. V. R. has received grant support from Novartis; has received fees for acting as a consultant or advisory board member for Allergan, Biogen, Merck, Novartis, Roche, Sanofi-Aventis and Teva; and has received speaker fees from Teva.
Acknowledgements The authors are grateful to  Ruth Bentley  of  Oxford Health Policy Forum CIC, UK  for critical review of the study design and manuscript, the Reviewing Group participants for their insights and contribution, and  Danielle Emery  of  Oxford PharmaGenesis  for coordinating the blinded aspects of the Delphi process. J. H. ,  A. Bowen. , G. P. and G. G. -Chairs of the  MS Brain Health Delphi  process; H. C. and L. E. -Analysts; T. B. ,  A. Boyko. , C. B. , H. B. , E. G. C. , J. D. , J. F. , D. H. , C. L. -F. , R. A. M. , J. O. , F. P. , P. V. R. , M. J. S. , C. -A. S. , E. S. , Ø. T. , V. v. P. , T. V. , M. Z. and T. Z. -Members of the  Delphi Consensus Panel.
Using a quality improvement cycle, MS clinics will be able to demonstrate service improvement. We encourage MS teams to incorporate data collection into routine care to support re-evaluation, and to share examples of best practice. In some countries, local budget holders may want further evidence of the clinical benefit of timely care -as described by the quality standards. To generate evidence, MS clinics will need to link results from routine service evaluations with long-term clinical outcomes. MS clinics could collaborate with other centres to allow comparisons and, in the future, MS databases could enable largescale analysis by adding relevant data fields. Other stakeholders will contribute to improving care. MS neurologists and MS nurses should educate col- leagues -including general neurologists and primary care practitioners -on the importance of timely, spe- cialist MS care, and highlight best practice examples to local budget holders, managers and service providers.
175031). D. H. has received grants from Czech Ministry of Education project Progres Q27/LF1, and speaker honoraria, travel expenses and consultancy fees from Biogen, Novartis, Merck, Roche, Sanofi Genzyme and Teva. J. O. has received grants, personal fees and non-financial support from Biogen, Novartis, Roche and Genzyme, and personal fees and non-financial support from Allergan, Merck and Teva. F. P. has received research grants from Biogen, Novartis and Genzyme, and fees for serving as Chair of DMC in clinical trials with Parexel. P. V. R. has received grant support from Novartis; has received fees for acting as a consultant or advisory board member for Allergan, Biogen, Merck, Novartis, Roche, Sanofi-Aventis and Teva; and has received speaker fees from Teva. Declaration of Conflicting Interests The author(s) declared the following potential con- flicts of interest with respect to the research, author- ship, and/or publication of this article: J.
MEthods And AnAlysIs study design This is a multicentre, international, double-blind, two-arm, randomised, placebo-controlled phase II trial ( Clinicaltrials. gov: NCT03099187) that plans to enrol approximately 250 patients across 60 clinical centres in Australia, Canada, Europe and Israel (for details of study sites visit: https:// clinicaltrials. gov/ ct2/ show/ study/ NCT03099187). Patient enrolment began in April 2017. The trial will evaluate the efficacy and safety of pirfenidone in study participants over 24 weeks (figure  1 ). Study data will be managed according to the procedures described in online supplementary appendix 1.
05. The primary analysis will be based on the intent-to-treat population; patients who discontinue treatment prematurely will be analysed based on the available data and no imputation method will be applied for missing data. A linear mixed-effects model will be included as a sensitivity analysis to account for codependency of daily FVC measurements. For the secondary endpoints, all data from baseline to Week 24 will be used without imputation, and p values will be reported in a descriptive fashion with no adjustment for multiplicity (further details of statistical analysis of the secondary endpoints can be found in online supplementary appendix 2). The safety analysis will include investigation of the nature, frequency, severity and timing of treatment-emergent adverse events. The incidence, type and severity of adverse events will be summarised according to primary System Organ Class and subcategorised by Medical Dictionary for Regulatory Activities version 19.
1 12  Both surgical lung biopsy and transbronchial lung cryobiopsy were included as options in this study. Cryobiopsy has been shown to provide meaningful data to aid MDT diagnosis of ILD and is generally considered to be less invasive than surgical lung biopsy. 27 A diagnosis of uILD can be assigned regardless of whether a surgical lung biopsy has been performed, and the current study protocol does not specify which diagnostic tests should be conducted to make a diagnosis of uILD. The number of patients who undergo each procedure will be documented, and if a biopsy (either surgical biopsy or cryobiopsy) has not been conducted, then the protocol requests a reason to be given. Although inclusion of patients without biopsy data is a potential limitation, it does reflect clinical reality where many patients will not or cannot have a biopsy.
28 29 31-33 The dose of pirfenidone (2403 mg/day) and initial dose titration used in this trial will be the same as the clinically recommended dose and titration used in patients with IPF. 32 33 In the absence of any clinically approved treatment for uILD, study participants in the control group will receive placebo during the 24-week double-blind treatment period. Methods of assessing efficacy in the study population are another important consideration to ensure that meaningful clinical data are collected. Change in FVC is a generally accepted measure of disease course and a predictor of mortality risk in patients with ILD and has been examined in clinical studies that enrolled patients with uILD. 5 34 The primary endpoint in this Open access trial will therefore assess rate of FVC decline.
In order to ensure the 24-week treatment period is sufficient to observe any clinically significant differences in FVC decline, FVC will be measured daily by study participants using a handheld spirometer. Recent data collected in patients with IPF demonstrate the feasibility of asking patients to perform daily or weekly FVC measurements. 35 36 Results from Russell et al suggest that daily FVC measurements correlated well with measurements recorded during clinic visits, and daily readings correlated with mortality over 3, 6 and 12 months. 35 Weekly FVC measurements over 24 weeks have been found to result in enhanced precision and power compared with FVC measurements taken in clinic on Weeks 1 and 24. 36 Furthermore, previous studies of pirfenidone in IPF have demonstrated a treatment effect within a 24-week timeframe.
Acknowledgements Medical writing support was provided by  Rebekah Waters  of  CMC AFFINITY, a division of Complete Medical Communications, Ltd. , Manchester, UK, funded by  F. Hoffmann-La Roche, Ltd. TMM is supported by an  NIHR-funded Clinician Scientist Fellowship (NIHR Ref :  CS-2013-13-017 ) and  British Lung Foundation Chair in Respiratory Research  ( C17-3 ).
Acknowledgements We are grateful to  Al Mueller  for a critical reading of the manuscript and many useful discussions. P. T. and B. W. would like to thank  Institut de Physique Théorique de Saclay  for hospitality during the gestation of this work. The work of E. I. is supported in part by the  Agence Nationale de la Recherche  project  ANR-16-CE31-0019-01. P. T. is funded by the  European Union 's  Horizon 2020 research and innovation programme  (grant agreement No. 647981 ,  3DSPIN ).
Acknowledgements We acknowledge discussions with and comments by  B. Basso ,  T. Bargheer ,  J. Caetano ,  V. Goncalves ,  V. Kazakov ,  G. Korchemsky. Especially , we thank  P. Vieira  for helping us with the evaluation of the integral, in particular by suggesting the basis of functions used. T. F. would like to thank the warm hospitality of the  Perimeter Institute and of the Laboratoire de Physique Théorique de l'Ecole Normale Supérieure  were a large part of this work was done. T. F. would like to thank  CAPES/INCTMAT  process  88887. 143256/2017-00 , the  Perimeter Institute  and the  European Research Council  ( Programme ERC-2012-AdG 320769 AdS-CFT-solvable)  for financial support. S. K. is supported by the  US Department of Energy.
Methods and findings We performed a nation-wide search using the Programme de Medicalisation des Systèmes d'Information (PMSI) database which includes anonymous data for all patients hospitalized in France. We identified newly diagnosed cases in 2012 and analyzed the number and duration of hospital stays, coexisting conditions and treatment modalities with data available until the end of 2015. A diagnosis of multiple myeloma was determined for the first time during a hospitalization in France in 2012 in 6,282 patients (3,234 males and 3,048 females). The median age at diagnosis was 74 years (72 in males and 76 in females). A majority (55. 3%) of patients were diagnosed and treated in a single heath center, including 37% in a university hospital and 52% in a non-university public hospital. Comorbidities potentially impacting on myeloma treatment were present in 57.
Introduction Multiple myeloma is classically considered to be the second most frequent hematological malignancy after lymphoma and ranks 14 th among all neoplasia in the SEER database, representing approximately 2% of all new cancer cases (https://seer. cancer. gov/data/). Incidence rates are reported to vary from 0. 3 to 8. 8 /100,000 in males (average 5. 5) and 0. 6 to 5. 5/100,000 in females (average 3. 7) within the European Union in 2012 (http://eco. iarc. fr/eucan/Cancer. aspx?Cancer=39). In 2012 the SEER incidence rate of myeloma in the USA was estimated to be 8. 56/100,000 in males and 5. 18/100,000 in females. In Great Britain and Sweden the ageadjusted incidence was estimated to be in the order of 5/100,000  [1]. Since the median age at diagnosis is reported to be in the order of 69 years it has been suggested that the recent increase of the incidence rate is mainly due to the modification of the age distribution in the entire population  [2].
Overall there is a continuous improvement in the outcome of patients with multiple myeloma although the most significant improvements have concerned patients under the age of 65 years  [7]. Several epidemiological studies have analyzed the incidence and prevalence of neoplastic diseases in different age groups but few have associated the frequency and nature of the ensuing hospitalizations, geographical distribution of patients and types of treatment applied or health centers where patients were treated. In order to better describe the patient characteristics, hospitalization flow, treatment modalities and associated medical conditions of all patients diagnosed with multiple myeloma, we analyzed the PMSI database which provides exhaustive anonymous data for all patients hospitalized in public and private health centers in France.
The PMSI database The PMSI (Programme de Medicalisation des Systèmes d'Information) databank comprises anonymous data for all hospital stays in France, including public and private health centers. It is a nation-wide diagnosis-related group based information system in which each hospital stay is coded by the attending physician and includes at least one main diagnosis and the relevant associated diagnoses  [8]. Additional information includes the type of hospital, where the patient came from and went to after his stay. Some procedures such as radiotherapy and bone marrow transplantation are documented, as well as costly medications, such as the administration of bortezomib. Data were available starting in 2007 and until December 31, 2015 as of the writing of this manuscript. Hospital stays described in the PMSI database include conventional hospitalizations with overnight stays in the hospital as well as outpatient (or "ambulatory") visits.
This database does not however include data on patients seen only in consultation. Data regarding oral medications, stage of disease and response to therapy are not available. Patients included in this study were identified using the diagnostic code C900 for multiple myeloma, either as the main or as an associated diagnosis. We chose patients for whom the code was used in 2012 for the first time, whether or not the patient had previously been hospitalized since 2007. As there is no secondary validation of the diagnoses in the database there may be errors in the codification. To reduce excess diagnoses we sought cases for which there was an alternate diagnosis of hematological malignancy and an unexpected occurrence of the code C900 during one of the hospital stays. This allowed us to eliminate 382 patients for whom the diagnosis of multiple myeloma was unlikely.
Associated medical conditions at first visit We found at least one medical condition potentially related to myeloma or impacting on myeloma treatment in 57. 5 of patients at diagnosis (Table  2 ). These included infectious (14. 5%), renal (15. 2%), cytopenic (14. 5%) and metabolic (14. 5%) conditions or complications of disease. Thrombo-embolic (2. 7%), skeletal (0. 7%) and peripheral neuropathic (0. 7%) were reported less frequently. Comorbidities were as expected more frequent in elderly patients with a median of 2 associated conditions in patients under the age of 65, 3 in patients between 65 and 80 and 4 for those aged 80 or more. There were no differences in the rate of comorbidities between men and women. A total of 1,092 diagnoses of other neoplasia were declared in the database for 931 patients (15% of all patients)(Table  3 ).
Conclusion Our study identified 6,282 new cases of patients hospitalized with a diagnosis of myeloma in 2012, or an incidence of approximately 1/10,000. Limitations to this study include the fact that some cases may have not properly been identified during hospitalization. Another cause of error is the fact that patients treated before 2007 and who had not been hospitalized until 2012 were considered as "new" diagnoses. Excess diagnosis in the case of multiple myeloma may be due to the fact that patients with MGUS have been classified with authentic myeloma while patients who were not hospitalized with a diagnosis of myeloma were not taken into account. Elderly patients with other severe diseases may not have been hospitalized or the diagnosis of myeloma may have been ignored. Notwithstanding these caveats the incidence values observed in our study are similar to those reported for France in 2012 in the Euracan database (6.
Due to phase III, the implementation of the city's objectives and the goals during the operation of the Resilient Thessaloniki office was the cooperation with the World Bank in three main projects that contributed to the institutionalization and establishment of the resilient thinking. The first one was the development of a masterplan for the redevelopment of the waterfront, pointing out projections under the three pillars of sustainable development, economic (and financial), environmental, and societal. The second and third were two projects that provoked resilience as a substantial asset to risk reduction and risk management. Building upon a continuity plan for emergency cases and an Open Risk data platform allowed citizens and stakeholders or local entities to connect with the municipality's operations and planning in an effort to reinforce awareness and preparedness on extreme events.
The classification of radar images is a significant challenging task yet  [18]. Due to the presence of speckle noise and the absence of effective feature presentation, the interpretation and the understanding of radar images are always much different from optical images  [2]. An adequate feature extraction approach, which can abstract spatial information from radar images as well as improve classification accuracy, is required. Feature extraction of these images has been researched for many years, and a lot of methods have been proposed by many researchers. Recently, inspired from artificial intelligence, Deep Learning methods  [6, 11, 19, 20]  are used to classify SAR and ISAR images. In our framework, ISAR and SAR databases are used, the first is composed of aircrafts images and the second is a benchmark of SAR images representing military vehicles.
At first we evaluated the impact of the convolutions layers and the hidden layers of the perceptron on system performances, by the implementation of 4 architectures of CNN. Then we proposed the use of a Convolutional Auto-Encoder (CAE) to generate optimal filters, which will be wormed in the convolution layers. The remainder of this paper is organized as follows. Section II gives an introduction of different deep learning techniques. In section III, details of training are described and some experimental results on the MSTAR and Aircraft datasets are presented. Finally a conclusion will be given in the section IV.
III. EXPERIMENTS AND DISCUSSION In this part, we report and analyze the implementations and classification results obtained on ISAR and SAR images. We are interested in this section both in classical methods and in Deep Learning techniques by combining the auto-encoder and the convolutional auto-encoder with a network of convolutional neurons to enhance system performances. Note that the tests are performed on an Intel processor, CPU 3. 10 with GB of RAM. We introduce in the first of this section the datasets used for different simulations.