dataesr/scientific-paragraphs-categorization huggingface dataset:
About 6. 5 independent variables (from 6. 3 for the south polar scenario to 6. 7 for the polluted China case) can be retrieved in the altitude range between 0 and 60 km. This corresponds to a mean vertical resolution of about 9 km. Between 0 and 18 km, the synthetic retrievals show around 1. 5 DOF. This means that somewhat more information than the total ozone content can be determined in the troposphere. In summary, profile information in the troposphere is severely limited and thus dependent on the a priori ozone profile. It should be noted here that the number of independent variables might change in the retrievals using real TROPOMI data because of additional pseudo-absorbers which cannot be applied to the synthetic data. These pseudo-absorbers serve to compensate for inestimable calibration errors in the measured radiation.
Calibration correction for TROPOMI measurements The UV channels of TROPOMI have been the subject of intensive analysis and calibration before launch and during space operation  (Ludewig et al. , 2020). First tests with our retrieval applied to the most recent V2 TROPOMI spectral data revealed, however, large deviations in the retrieved ozone profiles, especially in the altitude range above 40 km. Therefore we decided to introduce additional spectral corrections as part of the retrieval. This type of correction, often referred to as vicarious calibration or soft calibration, is described, for example, in  Liu et al. (2010). The approach is to simulate TROPOMI radiance for a selected set of measurements using ozone profiles from a comparison instrument, here MLS/Aura, and use the difference of the simulated to the TROPOMI-measured radiance as the calibration correction.
, 2017)  as already provided in the MLS data files. Allowing a maximum 1000 km between MLS and TROPOMI pixels, we assume not to introduce a significant systematic error in the tropics, as ozone distribution is relatively homogeneous in this region. At higher latitudes, atmospheric dynamics may lead to higher variability. Here, TROPOMI measurements were only simulated if total ozone from MLS/MERRA-2 and TROPOMI (WFDOAS total ozone) agrees to within 5 %. The surface albedo (retrieved at 378 nm) was taken from the TROPOMI WFDOAS L2 product. The relative difference between the measured and simulated radiances is shown in Fig. 5  exemplarily for ground pixels (viewing angles) 15, 34, and 52 (across-track ground pixel numbers of UV2). Since we identified a slight but stable latitude dependence in all radiance differences, we decided to use independent calibration corrections for the tropics and extra-tropics.
Validation To assess the accuracy and quality of the TOPAS algorithm, the retrieved ozone profiles were compared with ozonesondes and ozone lidar data. Both reference data sets have very good quality and a higher vertical resolution than ozone profiles from nadir satellite measurements (see Sect. 2). Ozonesondes are mainly used for comparisons in the troposphere and the lower stratosphere up to a maximum of 35 km. The middle stratosphere (15-50 km) is validated with lidar measurements.
Ozonesondes Figure  7  shows the results of the comparison of TROPOMI ozone profiles with ozonesonde measurements. Here, the relative mean difference and its standard deviation SD( ) are shown, which are defined by = n i=1 (r i -s i ) n i=1 s i , SD( ) = n √ n -1 n i=1 (r i -s i -1 n n i=1 (r i -s i )) 2 n i=1 s i , (10) where r i and s i are the data from the ith collocated pair of TROPOMI and sonde measurements, respectively. The relative mean deviation between the TOPAS retrieval results and high-resolution ozonesonde data from all collocations (panel a, black curves) is about 5 % down to about 13 km increasing to about 10 % below. The standard deviation varies between 10 % and 20 % in the lower stratosphere (18-30 km) and between 25 % and 50 % below 18 km. The comparison of the retrieved O 3 profiles from TROPOMI and ozonesondes convolved with the TOPAS averaging kernels (panel a, red curves; see Eq.
A better choice of the a priori in southern latitudes could possibly improve the retrieval results. With increasing latitudes the viewing geometries change, and especially the SZA becomes larger. There is a connection between SZA and vertical resolution so that at larger angles the vertical resolution between 8 and 18 km Figure  7. Comparison of the ozone profiles retrieved from TROPOMI and those from ozonesondes for different zonal bands. The relative mean difference between the retrieval results and the high-resolution sonde data (solid line), as well as the standard deviation of the differences (dashed line), is shown in black. The comparison with the sonde profiles convolved with the TOPAS averaging kernels is shown in red. In grey the relative difference between the a priori ozone profiles and high-resolution ozonesonde profiles is displayed, along with the corresponding standard deviations.
Lidar Figure  9  shows the relative mean differences (solid line) and the standard deviations (dashed line) between the retrieved profiles form TROPOMI and lidar data (black) for five individual stations and the all-station average (panel a). In addition, the difference between the TOPAS results and the collocated MLS ozone profiles (convolved with TOPAS averaging kernels) is shown in green. When all stations are considered, the deviations between 15 and 45 km are below ±5 % (grey bar). There is a small positive bias between 25 and 45 km https://doi. org/10. 5194/amt-14-6057-2021 Atmos. Meas. Tech. , 14, 6057-6082, 2021 that comes mainly from the Table Mountain station data set, which contains the largest number of comparison profiles. The standard deviation of the differences is about 10 % in the range of 20 to 40 km.
The lower wavelength range (below 300 nm) is more strongly affected by the SAA, which leads to the largest uncertainties in high-altitude ozone. If necessary, the SAA region can be filtered out easily by the given flags in the TROPOMI L1B data product. Figure  12a  shows the zonal mean ozone number density as a function of the altitude and latitude for 1 October 2018. All 14 orbits were binned at 1 • latitude and averaged. The ozone maxima at about 25 km in the tropics and at about 20 km at southern mid-latitudes are clearly seen. Furthermore, a slight curvature of the ozone peak region with decreasing the peak altitude towards the poles is evident. In the high southern latitudes, the Arctic spring ozone hole is notable. The mean vertical resolution, shown in Fig. 12d , is determined from the inverse main diagonal elements of the TOPAS averaging kernel matrix.
The closest MLS and OMPS profiles were selected for each retrieved TROPOMI pixel (maximum 1. 5 h time difference and 1000 km distance). The direct comparison with MLS, i. e. without convolving MLS data with TOPAS averaging kernels (panel e), shows a good agreement between 20 and 50 km, with differences being mostly below ±10 %. Between 20 and 30 km, there are several spots, with the differences reaching ±20 %. Above 50 km, where the TOPAS retrieval has a low sensitivity, positive differences of up to +20 % in the mid-latitudes and tropics are observed. At high southern latitudes, the positive differences increase to about 40 %, while for high northern latitudes, negative differences are seen. Below 20 km, small-scale patterns with higher differences are evident. Below 15 km, the comparison results are less reliable as the precision of MLS data significantly decreases  (Livesey et al.
, 2020) , a radiometric calibration correction was determined using radiative transfer simulations and MLS ozone profiles. For the shortest wavelengths, radiometric adjustments of +20 % and more are needed. The correction drops below ±10 % for longer wavelengths. The TOPAS ozone profile retrieval was validated by comparisons with ozonesonde and stratospheric ozone lidar data. For the limited TROPOMI data set available so far, we found very good agreement with both validation data sets. The validation with ozonesondes shows good agreement in the lower stratosphere, with deviations of less than ±10 % at all latitudes in the altitude range 18-30 km. The standard devia-tion of the mean differences is about 10 %. Below 18 km, the mean difference and the standard deviation increases strongly but decreases when the sondes are convolved with the TOPAS averaging kernels.
Good agreement in total ozone compared to TROPOMI WFDOAS (within ±2 %) was found. When a continuous L1B version 2 data set is made available for TROPOMI, we plan to close the data gaps by processing these data. This will enable us to extend the validation using a larger data set from early 2018 until present and to investigate time series. The verification of the temporal stability of the ozone profile retrieval is still ongoing. The assessment of the calibration correction using MLS data as implemented in this study is also of particular importance in this context. If the finding of this study, that a temporally independent but spectrally dependent radiometric correction factor is sufficient and holds for the full data set, the final data product can be created which is independent of MLS apart of the initial correction.
That would enable the use of TROPOMI ozone profiles for trend analysis and monitoring. Thus, the goal to use TROPOMI measurements to mitigate consequences of a possible lack of limb instruments may become feasible. Data availability. All data and source codes are available upon request from Nora Mettig (mettig@iup. physik. uni-bremen. de) or Mark Weber (weber@uni-bremen. de). The L1B version of the S5P data is available upon request to the S5P Validation Team. MLS ozone profiles can be downloaded from the NASA Goddard Space Flight Center Earth Sciences Data and Information Services Center (GES DISC;  Schwartz et al. , 2020 , https://doi. org/10. 5067/Aura/MLS/DATA2516). OMPS limb ozone profiles are available upon request from Carlo Arosio (carloarosio@iup. physik. uni-bremen. de), and S5P WFDOAS total ozone and albedo data are available from Mark Weber.
Ozonesonde data from the WOUDC can be downloaded from https://doi. org/10. 14287/10000008 (WOUDC Ozonesonde  Monitoring Community et al. , 2021). Ozonesonde data from SHADOZ https://doi. org/10. 5194/amt-14-6057-2021 Atmos. Meas. Tech. , 14, 6057-6082, 2021.
Acknowledgements. The S5P L1b version 2 data have been provided by  ESA/KNMI  via the S5P validation team ( S5P-VT ) activities. We acknowledge all ozonesonde providers and their funding agencies for performing regular sonde measurements and thank the WOUDC and SHADOZ network for archiving these data. The same applies to the teams from all the lidar stations we used. Ozone profiles of the MLS limb measurements have been provided by  NASA. Financial support. This study has been supported and funded by the  BMWi/DLR  project " S5P Datennutzung " (grant no. 50EE1811A ), the  University of Bremen , and the federal state Bremen. All calculations reported here were performed on the HPC facilities of the  IUP, University of Bremen , funded under  DFG/FUGG  (grant nos. INST 144/379-1  and  INST   144/493-1 ).
Study design Our research is an open-label, retrospective study, single arm of the clinical and laboratory data collected who have prescribed the drug within the stated time and agreed to take part in this study. The Ethics Committee of our hospital gave permission and authorization for a retrospective analysis of patient data. The study group included patients with HFrEF who sought treatment with sacubitril/valsartan between JanuaryeJune 2020 and who were followed up for 6-months. Our analysis was divided into two phases: symptomatic HFrEF despite GDMT initiated on ARNI and symptomatic HFrEF on GDMT including ARNI initiated on dapagliflozin.
Drug therapy and follow-ups Symptomatic patients with HFrEF despite GDMT were transferred to the ARNI after 36 h of stopping the ACEI. The initial starting dose of ARNI was 24/26 mg twice daily [target dose 97/ 103 mg twice daily] along with other GDMT, and ARNI was only administered to patients with blood pressures of !110/70 mm Hg. Despite the overall tolerated dosage of ARNI and other GDMT, the signs and symptoms of HF persisted; in those cases, an initial dose of 5 mg was administered, and after 6e8 weeks, even with no clinical improvement, the dose was increased to 10 mg. We recorded their data in our electronic medical records (EMR), which included their demography, risk factors, past medical history, clinical presentations, vital parameters, clinical examinations, baseline investigations, and coronary angiography.
2 ). In this retrospective study, open-label study, we analysed results in patients receiving dapagliflozin in addition to therapy with ARNI. Our study included data for 104 (27. 4%) patients aged 68 ± 20. 5 years, of which 37. 6% were females. The treatment protocol has been used in patients in NYHA class II e IV and LVEF was 18e40% (mean 29 ± 4). The mean weight was 68 ± 35. 6 kg and the BMI were 34 ± 12. 4 kg 32% of patients were in NYHA class II, 40% were in NYHA class III, and 28% were in NYHA class IV. Progressive breathlessness was a prominent symptom in 98% accompanied by chest pain and easy fatigue in 52% of patients. 78% of patients had a history of paroxysmal nocturnal dyspnoea while 36% had orthopnoea. The baseline characteristics are presented in Table  1. Mean systolic blood pressure (SBP) was 124 ± 21 mm Hg, while mean diastolic blood pressure (DBP) was 81 ± 9 mm Hg and the pulse rate of 106/min±27.
End organ changes limit the ability of the failing heart to respond to standard therapy to the same degree as patients with milder forms of HF. 26, 27  Limitations of the study A retrospective non-randomized research was conducted, with a small sample size for the studied population. As this was a realworld retrospective data collection, we included patients on various tolerated doses, including maximum tolerated dosages of the ARNI. In addition, our results included changes in LVEF and NYHA class, which might be operator dependent and subjective. Longer follow-ups are required for hard outcomes such as mortality and hospitalization for heart failure. We emphasize multicentre clinical experience and better follow-up evidence in larger randomized controlled trials in the Indian subset.
, 1993; Ota et al. , 2006; Linzer et al. , 2008). Dalman et al. (2010)  proposed that the H. annosum complex originated in Laurasia, H. annosum s. s. /H. irregulare arose in Eurasia, and H. parviporum/H. abietinum/H. occidentale, which occurred in eastern Asia or western North America, emerged between 45 and 60 Ma in the Palaearctic; this conclusion was based on non-coding regions of elongation factor 1-α (EFA), glutathione-S-transferase (GST1), GAPDH, and transcription factor (TF). Recently, based on more species and samples of Heterobasidion and the fossil record, molecular dating suggested that ancestral Heterobasidion species originated in Eurasia occurred mainly during the Early Miocene  (Chen et al. , 2015; Zhao et al. , 2017). Based on a larger set of Heterobasidion samples from Asia, Oceania, Europe and North America, and using combined RPB1 and RPB2 sequence dataset, a further phylogenetic investigation on the genus is carried out.
Phylogenetic Analysis Bondarzewia occidentalis Jia J. Chen, B. K. Cui and Y. C. Dai and B. submesenterica Jia J. Chen, B. K. Cui and Y. C. Dai were used as outgroups  (Chen et al. , 2015). Sequences were aligned with BioEdit  (Hall, 1999)  and ClustalX  (Thompson et al. , 1997). Sequence alignments were deposited at TreeBase 2 (submission ID 25908). Maximum parsimony (MP) analysis was applied to singlelocus genealogies for ITS, nrLSU, RPB1, PPB2, and GAPDH, and combination datasets that contained the RPB1-RPB2 sequences. The tree construction procedure was performed in PAUP * version 4. 0b10  (Swofford, 2002). All characters were equally weighted, and gaps were treated as missing data. Trees were inferred using the heuristic search option with TBR branch swapping and 1000 random sequence additions.
Max-trees were set to 5000, branches of zero length were collapsed, and all parsimonious trees were saved. Clade robustness was assessed using a bootstrap analysis with 1000 replicates  (Felsenstein, 1985). Descriptive tree statistics tree length (TL), consistency index (CI), retention index (RI), rescaled consistency index (RCI), and homoplasy index (HI), were calculated for each maximum parsimonious tree generated. Phylogenetic trees were visualized using Treeview  (Page, 1996). MrMODELTEST2. 3  (Nylander, 2004)  was used to determine the best-fit evolution model for the combined dataset for Bayesian inference (BI). The BI was calculated with MrBayes 3. 1. 2 (Ronquist and Huelsenbeck, 2003)  with a general time reversible model of DNA substitution and an invgamma distribution rate variation across sites.
Eight Markov chains were run from random starting tree for 1 M generations of RPB1 and RPB2 dataset, and sampled every 100 generations. The burn-in was set to discard the first 25% of the trees. A majority rule consensus tree of all remaining trees was calculated. Branches that received bootstrap values for MP and Bayesian posterior probabilities (BPP) greater than or equal to 75% (MP) and 0. 95 (BPP) were considered as significantly supported. To determine if the datasets were significantly conflicted, the partition homogeneity test option in PAUP 4. 0b was used between the loci in all possible pairwise combinations using 2 https://treebase. org/treebase-web/home. html 1000 replicates and the heuristic general search option. This test randomly shuffles phylogenetically informative sites between two paired loci: if the datasets are compatible, shuffling sites between the loci should not produce summed tree lengths that are significantly greater than those produced by the observed data  (Farris et al.
Molecular Phylogeny All targeted DNA loci were successfully amplified and sequenced from our Heterobasidion samples and the outgroup species. Partition homogeneity test showed no conflicts for the RPB1 and RPB2 combined loci (P = 0. 019, P ≥ 0. 01). Therefore, the amino acid sequences from RPB1 and RPB2 were combined into a single sequence set. The combined dataset included sequences from 46 specimens representing 18 species. The dataset had an aligned length of 2505 characters, of which 1796 characters were constant, 671 were variable and parsimony-uninformative, and 38 were parsimony-informative. The maximum parsimony analysis yielded four equally parsimonious tree (TL = 1033, CI = 0. 789, HI = 0. 925, RI = 0. 730, RC = 0. 211). The best model for the combined RPB1 + RPB2 estimated and applied in the Bayesian analysis: GTR + I + G, lset nst = 6, rates = invgamma; prset statefreqpr = dirichlet (1,1,1,1).
Background: Homelessness may result in the breakdown of regular health services, including routine vaccination programmes. A scoping review was conducted to describe vaccine-preventable diseases (VPD) other than tuberculosis in people experiencing homelessness (PEH). Methods: We followed the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). We searched peer-reviewed literature published in English, French, Spanish or Portuguese reporting the outbreak of VPD or VPD prevalence in both infant and adult homeless populations published between 1980 and 2020, using PubMed/Medline, SciELO, Google Scholar, and Web of Science databases. Relevant information from the studies was charted in Microsoft Excel and results were summarised using a descriptive analytical method.
Information source A literature search was performed to identify relevant articles published from 1980 to December 8th, 2020 in PubMed/Medline (in English), Scopus (in English), Web of Science databases (in English), SciELO (in English, Portuguese and Spanish), and Google Scholar (in French), using Harzing's Publish or Perish software (version 7. 0, Harzing. com, UK). Search strings were tailored to each database. The combinations (#3) of homelessness terms (#1) and disease terms (#2) were used as following: #1: ''homeless" OR ''homelessness" OR ''street people" #2: ''diphtheria" OR ''Corynebacterium diphtheriae" OR ''tetanus" OR ''Condyloma accuminata" OR ''polio" OR ''poliovirus" OR ''poliomyelitis" OR ''pertussis" OR ''whooping cough" OR ''Bordetella pertussis" OR ''Haemophilus influenzae type b" OR ''hepatitis B" OR ''pneumococcal" OR ''Streptococcus pneumoniae" OR ''meningococcal" OR ''meningococcus" OR ''Neisseria meningitidis" OR ''mumps" OR ''measles" OR ''rubella" OR ''Human papillomavirus" OR ''influenza" OR ''flu" OR ''hepatitis A" OR ''shingles" OR ''Varicella" OR ''chickenpox" OR ''typhoid" OR ''Salmonella" OR ''Rotavirus" OR ''cholera" OR ''Vibrio cholerae '' OR ''yellow fever" OR ''rabies" OR ''lyssaviruses" OR ''Japanese encephalitis" OR ''leptospirosis" OR ''Leptospira" #3: #1 AND #2 Combinations of the search terms in Spanish, Portuguese and French are shown in Supplementary data.
Data analysis Search results were compiled in the Endnote software (version 9. 3, Clariate, USA), and duplicates were removed. The screening based on title and abstract were performed independently by two investigators (TD and SC) for inclusion. All disagreements were resolved by discussion and mutual agreement, and full-texts were reviewed if necessary. For eligible articles, full texts were assessed by two investigators (TD and VT). Relevant information from the studies was charted in Microsoft Excel 2016 (Microsoft, USA). Data table elements were created and were reviewed by all authors to ensure consistency of information extraction. Data extracted included date of study, study design, place of study, setting, population at risk, disease attack rate, age, sex, diagnostic tools, vaccine recommendations from authors, risk factors for diseases, mortality rate, co-infections with other VPD, and previous vaccination rate when available.
Using spatiotemporal Gaussian process regression, we produced location-specific and year-specific estimates of 11 routine childhood vaccine coverage indicators for 204 countries and territories from 1980 to 2019, adjusting for biases in countryreported data and reflecting reported stockouts and supply disruptions. We analysed global and regional trends in coverage and numbers of zero-dose children (defined as those who never received a diphtheria-tetanus-pertussis [DTP] vaccine dose), progress towards GVAP targets, and the relationship between vaccine coverage and sociodemographic development.
8, 9 1] [12]  At this pivotal juncture, it is important to clearly understand where-and for which vaccines-gains and gaps in coverage occurred before the onset of COVID-19. Robust and comparable estimates of vaccine coverage over time are thus key inputs for evaluating progress towards GVAP targets and serve as a baseline for IA2030's ambitions. Vaccination data can be sparse, subject to bias, and inconsistent, complicating coverage estimation at both national and global levels. 4] [15]  Although WUENIC's approach has its strengths, such as incorporating qualitative knowledge and engagement via country consultation processes, statistical models offer import ant advantages. For instance, in the WUENIC method, country-reported data are only calibrated to survey-based estimates when both datapoints are available for a given vaccine-countryyear and a discrepancy of ten percentage points or more is observed between survey data and country-reported data.