dataesr/scientific-paragraphs-categorization huggingface dataset:
The differences are typically below 0. 005, but increase over SC 19 to 0. 02 for daily values. This gives a rough estimate of the uncertainty in our official composite series due to the selection of individual datasets to act as the reference. We note, however, that the overlap between most of the series used as backbones for this test is not optimum and is always worse compared to that of the Ko and MW series. Furthermore, by averaging the Ko and MW backbone series we reduce the uncertainty due to the choice of the reference series. Figure  15 a ) shows the composite based on using RP1 as a backbone series (blue). It is plotted along with the RP1 series on its own (black). These two series match almost perfectly, with only small differences (RMS difference of 0. 002 in disc fraction) which are greatest in 1998 (reaching 0.
008 in disc fraction). Also shown in Fig. 15 a ) is the composite using the RP1 backbone series when only the days included in the individual RP1 series are considered (red). In this case the differences are reduced, with an RMS difference of 0. 001 and a maximum difference in 1999 of 0. 003 in disc fraction. This illustrates the accurate cross-calibration of the individual series to the RP1 backbone. Finally, we also test the effect of including data taken with different bandwidths in the backbone series. For this purpose, we use the RP1 backbone and produce 3 different versions of it: i) keeping only datasets with either bandwidths narrower than 2 Åor broader than 3 Å (Ba, CL, Co, Kh, PS, RP2, SF1, SF2, Te, Up). Since the RP1 bandwidth is 2. 5 Å, these limits imply that the chosen bandwidths differ by at least ±0.
5 Å from that of RP1. ii) including only datasets with the nominal bandwidth between 2 Å and 3 Å, i. e. within ±0. 5 Å of the bandwidth of RP1. In this case, we further subdivide the datasets according to whether the bandwidths that have been assigned to them ii a) appear to be consistent with their actual behaviour (BB, Br, ML) ii b) or their assigned bandwidth does not appear to be consistent with their actual behaviour (Ka, PM, VM). For this test, we considered the BB and ML datasets only over the periods when the final instrumentation was used (see Appendix B), in order to avoid inconsistencies due to instrumental changes. Figure  15 b ) displays the three test backbone series in comparison to the one used in our composite. All three reconstructions of the RP1 backbone series lie within the uncertainties.
Summary and conclusions We have processed 43 datasets of full-disc Ca II K observations spanning the period 1892-2019 to derive the evolution of plage areas over the last 12 solar cycles. We processed the data consistently with the method developed by  Chatzistergos et al. (2018b Chatzistergos et al. ( , 2019b ). An extra step in the processing was added to ensure accurate results from the analysis of images from the Ky and YR datasets, which suffer from specific artefacts along arcs on the solar disc. We adapted our processing such that these artefacts can be precisely accounted for and showed that we can obtain accurate results for those datasets as well. We used our results for the 38 datasets with observations centred at the Ca II K line to create a plage area composite by applying the backbone approach employed by  Chatzistergos et al.
Previous results in the literature were based on considerably poorer temporal coverages. We also illustrated the importance of using multiple datasets to improve the annual coverage in comparison to the case when the results derive from observations from the Ko and MW datasets alone, which are the ones most employed in studies of the plage areas evolution so far. Many observatories, whose data have been analysed here, have stopped the solar monitoring in the Ca II K line. However, observations in the Ca II K line continue at the Ba, Br, CL, Co, Ka, Kh, Ki, KW, MD1, Mi2, PM, RP1, RP2, SF1, SF2, Te, UP, and VM sites to this day. A combination of the data from all those sites provides a full annual coverage. There is no day without an observation in our composite series since 2010. However, there are still gaps in our composite.
Acknowledgements. The authors thank the observers at the  Arcetri, Baikal, Big Bear, Brussels, Calern, Catania, Coimbra, Kanzelhöhe, Kharkiv, Kenwood, Kislovodsk, Kodaikanal, Kyoto, Manila, Mauna Loa, McMath-Hulbert, Mees, Meudon, Mitaka, Mt Wilson, Pic du Midi, Rome, Sacramento Peak, San Fernando, Schauinsland, Teide, Upice, Valašské Meziřičí, Wendelstein , and Yerkes sites for all their work in carrying out the observing programs. We thank  Isabelle Buale  for all her efforts to digitise the Meudon archive. We thank  Jeff Kuhn  and  Cindy Maui  for locating and sharing with us the Mees Ca II K data. We thank  Satoru Ueno  and  Reizaburo Kitai  for providing the Kyoto observations. We thank the anonymous referee for the constructive comments that improved this manuscript. We thank  Ester Antonucci ,  Alexi Baker ,  Angie Cookson ,  Martina Exnerová ,  Bernhard Fleck ,  Detlef Groote ,  Laurent Koechlin ,  Libor Lenža ,  Mustapha Meftah ,  Werner Pötzi ,  Roger Ulrich ,  John Varsik , and  Hubertus Wöhl  for providing information about various Ca II K data.
This work was supported by  FP7 SOLID , and by the  BK21 plus program  through the  National Research Foundation (NRF)  funded by the  Ministry of Education of Korea. This research has received funding from the  European Union 's  Horizon 2020 research and innovation program  under grant agreement No  824135  ( SO-LARNET ). The Coimbra researchers thank the project  ReNATURE  ( CENTRO-01-0145-FEDER-000007-BPD16 ). We acknowledge the "Observateurs associés" for their commitment to image acquisition and processing; IRAP for the instrumental and database management;  Université de Toulouse ,  CNRS, and Fiducial  for the funding. We acknowledge  Paris Observatory  for the use of spectroheliograms and the  Royal Observatory of Belgium, Brussels for USET data. The Kanzelhöhe Ca II K data were provided by the  Kanzelhöhe Observatory, University of Graz, Austria.
Non-invasive monitoring of in vivo NIS biodistribution As soon as tumors reached a volume of approximately 500 mm 3 , 5 x 10 5 HSP70B-NIS-MSCs were injected systemically via the tail vein every second day for a total of three times. 3 days later, regional hyperthermia was applied (41 °C or, as control, 37 °C for 1 h). The mice received 18. 5 MBq (0. 5 mCi) of 123 I (GE Healthcare Buchler GmBH & Co. KG, Braunschweig, Germany) intraperitoneally (i. p. ) after 0, 6, 12, 18, 24, 36, 48, and 72 h and gamma camera imaging (e. cam, Siemens, Munich, Germany) was performed using a low-energy, high-resolution collimator. Intrinsic thyroidal iodide uptake was reduced by the addition of 5 mg/ml L-thyroxine (L-T4; Sigma Aldrich) to the drinking water ten days before 123 I administration. Using the HERMES GOLD (Hermes Medical Solutions, Stockholm, Sweden) software, regions of interest were evaluated and tumoral iodide uptake was calculated and expressed as percentage of injected dose (ID) per tumor (% ID/tumor).
Ex vivo immunohistochemical NIS protein staining Paraffin-embedded tumor sections and a series of control organs from the mice used for 123 Iscintigraphy were immunohistochemically stained as described previously  [51]. Staining was performed using a primary mouse monoclonal NIS-specific antibody (Merck Millipore; dilution 1:500) for 90 min followed by a biotin-SP-conjugated goat anti-mouse IgG antibody (Jackson Immunoresearch; dilution 1:200) for 20 min and then peroxidase-conjugated streptavidin (Jackson Immunoresearch; dilution 1:300) for an additional 20 min. Immunohistochemically stained tumor sections were scanned using the Pannoramic MIDI digital slide scanner and pictures taken with Caseviewer software (3DHISTECH Ltd. , Budapest, Hungary) and control organs were imaged on an Olympus BX41 microscope equipped with an Olympus XC30 CCD camera (Olympus, Shimjukum Tokio, Japan).
Ex vivo immunofluorescence assay Immunofluorescence staining on dissected frozen tissue samples of HuH7 tumors and quantitative analysis of cellular proliferation (Ki67; Abcam, Cambridge, UK; dilution 1:200) and blood vessel density (CD31; BD Pharmingen, Heidelberg, Germany; dilution 1:100) were performed according to the protocol described previously  [28]. Pictures were taken using a Leica DMI6000B microscope equipped with a Leica DFC365 FX camera and Leica MM AF software (Leica Microsystems GmbH, Wetzlar, Germany). Quantification of six visual fields per tumor section was performed using ImageJ software.
Radioiodide biodistribution in vivo after MSC-mediated NIS gene transfer By placing a thermo probe intratumorally, we confirmed rapid, stable and sufficient tumoral temperature (41. 0 ± 0. 1 °C or, as control, 37. 0 ± 0. 1 °C respectively) delivery, while the body temperature of the mice stayed within physiological levels [data not shown]. Following these studies, subsequent analyses were conducted without the invasive tumoral probe, which could distort results as the wound caused by the probe could potentially influence MSC recruitment. After three HSP70B-NIS-MSCs injections, tumorbearing mice were heat-treated regionally for 1 h at 41 °C, to activate the heat-inducible HSP70B promoter, or as control at 37 °C. 0 to 72 h later, 18. 5 MBq 123 I were administrated and functional NIS expression was analyzed by gamma camera imaging.
The potential use of exogenously applied NIS to induce radioiodine accumulation in non-thyroidal tumors has been investigated in a variety of in vitro and in vivo tumor models, such as anaplastic thyroid cancer  [55] , glioma  [22] , acute myeloid leukemia  [21] , multiple myeloma  [7] , cancer of the prostate  [6, 15, 16, 23, 56] , the liver  [37] , the colon  [27, 36] , the breast  [8] , and the pancreas  [19, 39, 57]  by several groups including our own. These very promising proof-ofprinciple studies have led to phase I/II clinical studies with NIS as a reporter gene and / or therapy gene using virus-mediated NIS gene delivery for locally recurrent prostate cancer (NCT00788307), multiple myeloma (NCT00450814, NCT02192775, NCT030178 20), and for various other non-thyroidal cancer types (NCT01503177, NCT01846091, NCT02364713, NCT027 00230, NCT02919449, NCT02962167, NCT03120624, NCT03171493, NCT03647163)  [58] [59] [60] [61].
The adaption of engineered MSCs as a therapeutic approach to treat solid cancers using NIS has proceeded towards clinical application with the initiation of a first series of phase I/II trials using measles virus (MV)-NIS transfected MSCs in recurrent ovarian cancer (NCT02068794). In addition, a clinical trial using MSCs as gene delivery vehicles based on our previous work was completed using MSCs modified with CCL5-driven HSV-TK for the treatment of gastrointestinal cancer  [42]. In additional clinical trials, researchers are evaluating IFN-β expressing MSCs in ovarian cancer (NCT02530047) at MD Anderson Cancer Center, and the safety and anti-tumor capacity of TRAIL-modified MSCs in metastatic non-small cell lung cancer (NCT03298763) at University College London Hospital. While MSCs show significant tumor tropism, a portion of the adoptively applied MSCs potentially also home to normal tissues, such as the spleen or the lung  [35].
Acknowledgments We are grateful to  Dr Barbara von Ungern-Sternberg ,  Rosel Oos , and  Dr Markus Strigl  ( Department of Nuclear Medicine, LMU Munich, Munich, Germany ), and  Jakob Allmann  ( Department of Nuclear Medicine, Klinikum rechts der Isar der Technischen Universität München, Munich, Germany ) for their support with imaging and therapy studies. The authors thank  Prof Doris Mayr  ( Department of Pathology, LMU Munich, Munich, Germany ) for preparation of paraffin-embedded slides. The authors owe special thanks to  Prof Julia Mayerle ,  Dr Ujjwal Mahajan  and  Dr Ivonne Regel  ( Department of Internal Medicine II, LMU Munich, Munich, Germany ) for always allowing the use of their equipment and giving assistance. This work was supported by a grant from the  Wilhelm Sander-Stiftung  to C.
Methods and results The CardioMEMS Post-Market Study is a prospective, international, single-arm, multicentre, open-label study (NCT02954341) designed to examine the feasibility of haemodynamic guided heart failure management using a small pressure sensor permanently implanted in the pulmonary artery (PA). Daily uploaded PA pressures will be reviewed weekly to remotely guide medical management of patients with persistent NYHA Class III symptoms at baseline and a hospitalization in the prior 12 months. The study will enrol up to 800 patients from 85 sites across the United Kingdom, Europe, and Australia. The primary safety endpoint will assess device or system-related complications or sensor failures after 2 years of follow-up. Efficacy will be estimated after 1 year of follow-up comparing HF hospitalization rates before and after sensor implantation.
8, 12 here remains a clinical need for innovative remote monitoring tools (acceptable to patients and physicians) that can guide clinical management and effectively reduce HF hospitalization rates. 19 The CardioMEMS Heart Sensor Allows Monitoring of Pressure to Improve Outcomes in New York Heart Association (NYHA) Class III HF patients trial (CHAMPION, ClinicalTrials. gov NCT00531661) was a prospective, randomized single-blinded clinical trial that utilized remotely obtained PA pressures, measured daily and reviewed weekly, to guide medical management of previously hospitalized symptomatic patients with HF, regardless of ejection fraction. 20 Pulmonary artery pressure guided care was superior to traditional clinical management strategies resulting in more pressure guided medication changes, significant reduction in PA pressure, clinically meaningful reductions in HF hospitalizations, and improved quality of life.
The PA pressure monitoring system (CardioMEMS TM HF System, Abbott, Atlanta, GA, USA) has the CE mark and Therapeutic Goods Administration approval and is modelled to possibly be cost-effective in other geographies. 27 Additionally, the CardioMEMS TM HF System has Food and Drug Administration approval based on the safety and efficacy demonstrated in the CHAMPION Trial. Demonstration of the feasibility of utilizing remote PA pressure monitoring in other healthcare systems is required to support worldwide implementation of this management strategy. Health-care systems including patients, providers, and governmental regulatory or reimbursement agencies vary significantly across geographies. Practical considerations, such as regional cellular connectivity, patient's willingness to be frequently monitored, availability of health-care providers with expertise and structured workflow to monitor remotely obtained data may influence the effect of hemodynamic guided HF care.
Investigators will review uploaded PA pressure measurements on a secured website database (Merlin. net ™ patient care network, Abbott, Sylmar, CA, USA) at least weekly. Investigators will utilize the pressure information to guide medication adjustments to lower PA pressures, if abnormally high, and respond to pressure increases that may occur over time. Follow-up study visits will be scheduled at Month 1, Month 6, and every 6 months thereafter for 2 years following PA pressure sensor implant. In addition to official study visits, frequency, purpose, and outcome of all contacts between site staff and study subjects post implant will be recorded. The study protocol is consistent with the Declaration of Helsinki and approved by ethics committees at each institution involved.
Study device The CardioMEMS TM HF System is indicated for wirelessly measuring and monitoring PA pressure and heart rate in New York Heart Association (NYHA) Class III HF patients who have been hospitalized in the previous 12 months. The system provides the physician with the patient's PA pressure waveform including systolic, diastolic, and mean pressures as well as heart rate. Haemodynamic data are used by physicians for HF management with the goal of reducing HF hospitalizations. The system is comprised of an implantable wireless microelectromechanical sensor, which is empowered by interrogation and does not require an indwelling lead or battery. The sensor is permanently implanted into the distal PA using transcatheter techniques and fluoroscopic guidance. A patient electronics system will be used to collect daily PA haemodynamic measurements; an electronics system for hospital use is available, and a patient database (Merlin.
All investigators and clinical investigation personnel will attend training sessions detailing the implant, use, and follow-up of the haemodynamic monitoring system. Investigators are instructed to carefully review haemodynamic information from the baseline right heart catheterization at the time of implant to have a clear understanding of intravascular volume, vascular resistance, and diastolic transpulmonary gradient. These data guide both short-and long-term medical decision-making. Pulmonary artery pressure goals, initially set to normal values in the Merlin. net system, are individualized along with the notification thresholds. Thresholds account for normal pressure variability and define the range of pressures the physician considers acceptable. Typically, defining individual pressure goals and thresholds is a process that takes several weeks of medication adjustment with remote haemodynamic feedback to reach appropriate status.
General guidance recommends more frequent pressure reviews in the first 3-6 months following Figure  1  The CardioMEMS TM HF System sensor is permanently implanted into the distal pulmonary artery (PA) using transcatheter techniques in the catheterization laboratory (A); the sensor baseline is set to the mean PA pressure using a pulmonary artery catheter. Daily PA haemodynamic measurements are taken by the patient in a supine position at home. The patient measurement system consists of an antenna and electronics unit that guides the patient through the short reading process (B). The data can be recorded from the home, hospital, physician's office, or clinic. The haemodynamic data is transmitted to the website which is accessible via a secure website to the patient's heart failure clinician (C).
Haemodynamic guided HF management has sound physiologic plausibility as an effective means to reduce decompensation events and lower risk for disease progression in ambulatory HF patients. In fact, a recent report from the HFrEF patients in the CHAMPION trial discovered a synergy between haemodynamic guided care and the effectiveness of neurohormonal antagonism, with the best outcomes in those already receiving maximally tolerated GDMT at target doses. 23 Furthermore, outcomes from the pivotal prospective randomized trial are consistent with those found in large database analyses suggesting this management strategy is generalizable to US clinical healthcare delivery systems. 31 mportantly, haemodynamic guided care is the only intervention and treatment strategy to demonstrate improved outcomes in patients with HFpEF.
Methodology This section presents the proposed FLES for the sustainable evaluation of optimal M&R strategies based on the general architecture of the FLES shown in Figure  1. At this point, it is important to remind that the main goal of the proposed system is to assist pavement managers in the selection of the most preferred solution among a Pareto set of solutions. The set of optimal solutions of a MOOP belongs to a multidimensional space which is not endowed with a natural order as the unidimensional data does. Therefore, to decide which of the solutions in the set is the most appropriate in a given context, an ordering scheme must be defined. In this study, each solution contained in the Pareto set represents an optimal M&R strategy according to different objectives. Through the application of the proposed FLES, the DM will be able to assess the global performance (GP) of each solution in the Pareto set and therefore rank and select the one having a higher GP value.
In this study, we tested for geographical variations in habitat relationships for a suite of cetacean taxa using data from two separate regions of an ocean basin. Satellite remote sensing generates environmental data over basin scales that are compatible with the extensive distributional ranges of cetaceans, providing readily available predictors for modeling these species distributions. Environmental predictors may describe important characteristics of the physical marine environment (e. g. sea surface temperature), or proxies of dynamic processes that enhance resource availability (e. g. primary productivity)  (Redfern et al. 2006). While cetaceans are unlikely to respond to temperature or primary productivity directly, their prey, which are ectothermic and characterized by intermediate trophic levels, are expected to respond to these predictors more directly.
Cetacean visual survey data We relied on visual sightings of cetaceans from systematic aerial and shipboard line transect survey programs conducted in two regions of the western North Atlantic (WNA) and the eastern North Atlantic (ENA) in summer between 2004 and 2007 (Supplementary material Appendix 1). Surveys represented comparable effort on both sides of the basin (20 763 km in the WNA and 19 823 km in the ENA). All visual survey data were collected following a standard distance sampling methodology  (Buckland et al. 2001). For each cetacean sighting, observers recorded identification to the closest possible taxonomic level (species, genus or family), group size, perpendicular distance and detectability covariates (e. g. sea state). Twelve cetacean taxa (including ten species, one genus and one family) that were sighted on both sides of the North Atlantic basin were retained for the analysis.
Sea surface temperature (SST) shapes the distribution of ectothermic prey via physiological processes  (Dolomatov et al. 2013). It was derived from the GHRSST Level 4 CMC 0. 2deg Global Foundation Sea Surface Temperature Analysis (< https://podaac. jpl. nasa. gov/dataset/CMC0. 2deg-CMC-L4-GLOB-v2. 0 >) at 1 day (d), 0. 2° resolution. Primary productivity (PP) influences mid-trophic level prey of cetaceans (including zooplankton, fish and squid) via trophic coupling  (Croll et al. 2005). PP was derived from the vertically generalized production model  (Behrenfeld and Falkowski 1997 ) (< www. science. oregonstate. edu/ocean. productivity/ >) at 8 d, 9 km resolution and was log-transformed to reduce skewness. After obtaining the original covariate grids, we projected them to the 10 × 10 km resolution Albers equal area grid used for the analysis, then sampled them at the survey segment centroids.
We used bilinear interpolation for depth and trilinear interpolation with the date of the segment as the time dimension for dynamic covariates. While the range of sampled depth values was similar between regions, the sampled ranges of SST and PP were broader in the WNA (which included some warmer and less productive waters not present in the ENA) (Supplementary material Appendix 3). We performed all geoprocessing using ArcGIS 10. 2. 2 and the Marine Geospatial Ecology Tools software  (Roberts et al. 2010).