dataesr/scientific-paragraphs-categorization huggingface dataset:
After that, the measured u and v components are used to compare and validate the simulated results of MO and SCSOFS. X. Zhu et al. :  Comparison and validation of global and regional ocean forecasting systems The TS data from the five cruises were measured by the SeaBird 19 plus CTD (conductivity, temperature, and depth) instrument with 1 m vertical resolution. Among the five cruises, one is the Qiongdong cruise in the NSCS, which was conducted for 9 days from 12 to 20 July at 90 stations along six sections (see Fig. 1 ); another one is the Nansha cruise around the Nansha Islands, which was conducted for 5 days from 24 to 28 August at 17 stations along a 10 • N section from 109. 5 to 117. 5 • E. The TS data from these two cruises will be used to compare and validate the TS distribution from MO and SCSOFS in the vertical and horizontal.
16 m on the surface. The bathymetry was extracted from the ETOPO1 datasets published by US National Geophysical Data Center (NGDC), which is a global relief model of Earth's surface that integrates ocean bathymetry and land topography, with 1 arcmin resolution  (Amante and Eakins, 2009). The ETOPO1 dataset has combined the satellite altimeter observations, shipping load sonar measurements, a multi-resolution digital terrain database and the global digital terrain model, and many other data sources, and it has been widely used in the global and regional oceanic models. Additionally, the original ETOPO1 bathymetry was revised in the area near the coast of mainland China, according to the in situ data collected in NMEFC, then smoothed according to  Shapiro (1975). The maximum depth was set to be 6000 m and the minimum depth to be 10 m in the model  (Wang, 1996).
The initial temperature and salinity conditions were derived from the climatology monthly mean SODA in January. However, the initial velocities and elevation were set to zero, which means the model was integrated from a static status. The model's western lateral boundary was treated as a wall. The other three (northern, southern, eastern) lateral boundaries were opened, whose temperature, salinity, velocity, and elevation were prescribed by spatial interpolation of the monthly mean SODA dataset. The 2-D and 3-D velocities, through the open boundaries, are modulated to guarantee the conservation of volume flux in the whole model domain. In addition, the nudging technology was used for 3-D velocity, temperature, and salinity to the three open lateral boundaries with a 30-day timescale for outflow and 3-day timescale for inflow.
The system conducted a hindcast run from 2000 to 2011 after a 15-year climatology run for spin-up  (Wang et al. , 2012). The instantaneous model results were archived with a 5-day interval, which were used as the ensemble members for the EnOI (Ensemble Optimal Interpolation) method assimilation. After the hindcast run, the system conducted an assimilation run in 2012 using the EnOI method; the alongtrack SLA data from AVISO had been assimilated as the observations with a 7-day time window. Details of the EnOI applied in SCSOFS can be referred to in  Ji et al. (2015). The daily-averaged assimilated results were archived during the assimilation run, and were compared and validated in this paper. The system has been implemented into operations in NMEFC since 1 January 2013. It runs on a daily basis for 6-day simulations (1-day nowcast and 5-day forecast) to provide 120 h forecasting products of 3-D ocean temperature, salinity, and currents with a 24 h interval.
The atmospheric fields are taken from the ECMWF (European Centre for Medium Range Weather Forecasts) Integrated Forecast System at a daily average frequency. Momentum and heat turbulent surface fluxes are computed from CLIO bulk formulae  (Goosse et al. , 2001). A viscous-plastic rheology formulation is used for the LIM2_VP ice model  (Fichefet and Maqueda, 1997; LIM2_VP in Hunke and Dukowicz, 1997). A multivariate data assimilation (Kalman Filter kernel with SEEK formulation;  Pham et al. , 1998)  of in situ temperature (T ) and salinity (S) (from Coriolis/Ifremer), along-track MSLA (from AVISO, with MDT from  Rio and Hernandez, 2004) , and intermediate resolution SST (0. 25 • × 0. 25 • SST product RTG from NOAA) is performed with the SAM2 software  (Lellouche et al. , 2013 ). An Incremental Analysis Update (IAU) centered on the fourth day of the 7-day assimilation window ensures a smooth correction of T , S, U, V, and SSH (sea surface height).
Correlation analysis between model and in situ data In order to better compare and validate the performance of the two systems, we collected all the measured TS data from five cruises in the SCS in 2012 to conduct a comprehensive correlation analysis. Figure  9  shows the comparison of TS between the model results from MO and SCSOFS and the in situ observations by scatter points, respectively. Each point in the Fig. 9  corresponds to two values of temperature or salinity, one is from the in situ observations along the x axis, and the other one is from the model results from MO or SC-SOFS along the y axis. The correlation coefficients of temperature are 0. 987 and 0. 982, and those of salinity are 0. 717 and 0. 897, between MO, SCSOFS, and in situ observations, above the 95 % significance level, respectively.
(3) Closed contours of SLA around the eddy center must exist. (4) The eddy radius must be larger than 45 km. (5) The eddy amplitude must be larger than 4 cm. In this study, the amplitude is defined as the absolute value of the SLA difference between the eddy center and the SLA along the eddy edge. The eddy-tracking method used is the one developed by  Chaigneau et al. (2008) , and we only keep eddies with a life span of no less than 28 days. Eddies were analyzed and compared based on MO, AVISO, and SCSOFS in 2012. The numbers of eddies for three types of data are in Table  1 ; cyclones and anticyclones were counted separately and seasonally. The spatial distribution of eddy origin is shown in Fig. 12. MO shows more eddies, and especially more anticyclones formed than in AVISO; most of the excessive eddy cores were found near the middle of SCS.
SCSOFS has more anticyclones as well and fewer cyclones than AVISO. Both MO and SCSOFS show excessive eddies formed in the middle of the basin and fewer eddies in the east of Vietnam. The SLA of SCSOFS and MO is calculated simply by subtracting mean SSH (14 years mean for SCSOFS and only 1-year mean for MO) instead of a uniformed mean sea surface, which might cause the excessive anticyclones in both models. Observations of AVISO and model results from MO and SCSOFS show that fewer eddies formed in the middle part of NSCS. As for the seasonal distributions (figures not shown), all three data have most eddies in spring. Both AVISO and SC-SOFS have fewer eddies in fall, and more cyclones than anticyclones in spring and fall, and all three have fewer cyclones than anticyclones in summer. SCSOFS differs with AVISO mainly in winter, while they agree reasonably in the other three seasons.
Conclusions Two operational ocean analysis and forecasting systems, MO and SCSOFS, have been built, based on the state-of-the-art hydrodynamic ocean models, ROMS and NEMO, in France and China, respectively. This paper demonstrated the results of comparison and validation for the performance of both systems on the ocean circulation, the structures of the TS, and mesoscale activities in the SCS, based on the observed satellite and in situ data in 2012. The comprehensive performances for the both systems are summarized as follows. Both systems have capabilities to simulate the main basinscale circulations in the SCS and model results are in good agreement with the AVISO data. MO shows a better performance than SCSOFS in simulating several main branches of the SCS ocean circulations and eddies in January.
SCSOFS is in much better agreement with OISST than MO for both the range and the domain of SST decrease. MO has more eddies formed near the middle of SCS than AVISO, especially for anticyclones. SCSOFS has more anticyclones, but fewer cyclones than AVISO. AVISO data and model results from MO and SCSOFS all show most eddies in spring and fewer in fall, and fewer cyclones than anticyclones in summer. Both AVISO and SCSOFS have more cyclones than anticyclones in spring and fall. In order to improve performance of MO and SCSOFS in the SCS in future based on the results of the comparison and validation for the two systems, some recommendations are proposed as below. For MO, we would like to suggest (1) modifying the model bathymetry in the coast area for the depth less than 200m to improve the model performance in the shallow water area, such as the SST front; (2) changing the initial conditions of TS to improve the TS vertical structures, especially for the salinity in the deep water area.
Acknowledgements. We would like to thank the anonymous reviewers and the editor,  Ivan Federico , for their valuable contributions that allowed us to improve the manuscript substantially. This study is supported by the  National Natural Science Foundation of China  under contract nos. 41222038 ,  41376016 , and  41206023 , and the  Strategic Priority Research Program  of the  Chinese Academy of Sciences , grant no. XDA11020104 03. Edited by: I. Federico Reviewed by:  L. Lusito  and one anonymous referee.
Dengue transmission in urban areas is strongly influenced by a range of biological and environmental factors, yet the key drivers still need further exploration. To better understand mechanisms of environment-mosquito-urban dengue transmission, we propose an empirical model parameterized and cross-validated from a unique dataset including viral gene sequences, vector dynamics and human dengue cases in Guangzhou, China, together with a 36-year urban environmental change maps investigated by spatiotemporal satellite image fusion. The dengue epidemics in Guangzhou are highly episodic and were not associated with annual rainfall over time. Our results indicate that urban environmental changes, especially variations in surface area covered by water in urban areas, can substantially alter the virus population and dengue transmission.
1 ). Complete DENV envelope (E) gene sequences with a known date and location of sampling were collected from GenBank. This resulted in a final data set of 193 sequences isolated in Guangzhou from 1978 to 2014. Supplementary Table  1  shows the number, date of isolation, and origin of the included isolates. Daily records of climatic variables were obtained from local meteorological stations, and were used to calculate monthly average values. There were no missing values during the study period (January 1978-December 2014).
Spatiotemporal reflectance blending in urban environment Time series Landsat scenes from 1978 to 2014, covering the entire city area of Guangzhou (113. 2644°E, 23. 1292°N) were used to detect land cover changes, especially changes in water area. Landsat standard data products (cloud o10%) were acquired from the Earth Explorer (http://earthexplorer. usgs. gov/), processed through the Level 1 Product Generation System (LPGS), and carefully selected to be close to the dates of peak dengue activity. The path/row of Landsat images used in geo-referenced mosaicking were following the WRS-1 (the Worldwide Reference System) as 131/44 and 131/43, or WRS-2 as 122/44 and 122/43 (see Supplementary Table  2 ). To reduce the possible influence of seasonal change of water area, the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM)  (Zhu et al.
, 2010) was applied to generate the fusion images in summer time, based on the Landsat images in winter time (with the resolution of 30 m) and MODIS images in summer time (extracted from MOD09GA, with the resolution of 500 m). Considering the cloud cover and the strong striping noise in the scenes, we developed CESTARFM (Customized Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model) to improve the method by adding temporal weight interpolation of coarse resolution images before the first step of the ESTARFM  (Michishita et al. , 2015 (Michishita et al. , , 2012)). Iterative self-organizing data analysis techniques algorithm (ISODATA) with fixed numbers of clusters were applied to classify five land cover types, including water, urban, cropland, bare land, and forest. The sites of field record collection were determined by visual interpretation with reference to high-resolution images in Google Earth.
Phylogenetic analysis Nucleotide sequences were aligned using Muscle 3. 8. 31 program  (Edgar, 2004)  and later manually edited in BioEdit (v7. 0)  (Hall, 1999). Phylogenetic relationships of the 193 DENV sequences in Guangzhou were constructed using the neighbor-joining (NJ) approach and the GTR þIþ Γ 4 model of nucleotide substitution by PAUP 4. 0. Tree topology reliabilities were tested with 1000 bootstrap replicates. RDP3 was used to detect recombination in dengue viruses  (Martin et al. , 2010). To generate temporal phylogenies using time-stamped sequence data, we applied a relaxed-clock Bayesian Markov chain Monte Carlo (MCMC) method as implemented in BEAST v1. 7  (Drummond et al. , 2012). All analyses were executed with a codon-structured SDR06 substitution model  (Shapiro et al. , 2006) , a relaxed uncorrelated lognormal clock  (Drummond et al.
e. the radius at which the mean density of the cluster is 2500 times the critical density of the universe at the cluster redshift), in contrast to previous results (e. g  Kettula et al. 2013 ) that were derived within r 500 , indicating that the mass temperature relation may depend on the cluster centric radius within which the mass is measured. We present the mass calibration of the XXL bright cluster sample (XXL-100-GC) based on a new mass-temperature relation that we constrain using the largest sample used to date for such studies: 96 groups and clusters spanning X-ray temperatures of T ≃ 1 -10 keV and a redshift range of z ≃ 0. 1 -0. 6. Thirty-eight of these systems come from XXL-100-GC itself. We combine the XMM-Newton survey data and the high-fidelity weak-shear catalog from the CFHTLenS survey to obtain independent temperature and halo mass measurements, respectively.
2013 ) and an additive component (c) derived from the data  (Heymans et al. 2012). The observed ellipticity can be written as e obs = (1 + m)e int + c + ∆e (2) where e int is the intrinsic ellipticity and ∆e is the noise on the measurement. The multiplicative component m is dependent on both galaxy size and S/N and gives, on average, a 6% correction. The additive component c is similarly dependent on the galaxy size, and the S/N determined by Lensfit. For the CFHTLenS data c 1 is consistent with zero and c 2 is subtracted from e 2 for each galaxy. The multiplicative correction is applied as an average ensemble of each bin. A weighting is also applied that corrects for the geometry of the lens-source system in the form of the lensing kernel ξ = D LS /D S , where D LS and D S are the angular diameter distances between the lens and the source, and between the observer and the source, respectively.
When the number of data points is small, the Gibbs sampler will have difficulty in reaching convergence. linmix err also has the option of running as a Metropolis-Hastings algorithm, which is more efficient for small sample size. Tests implementing the Metropolis-Hastings algorithm give consistent results. We fit the model to the measured values of M 500,WL and T 300kpc. For some galaxy clusters, the weak-lensing S/N is so low that the we are only able to obtain an upper limit on M 500,WL. The posteriors of these systems are truncated by the lower bound prior on mass. Despite this, it is important to include these systems in the fit because they are X-ray detected at high significance, and to exclude them would add a further selection in addition to the primary X-ray selection. The fitting method used is able to incorporate upper limits as censored data using a likelihood that integrates over the censored and uncensored data separately (see  Kelly 2007 , for more details).
However their implementation is not suitable for our problem since we have prior knowledge of the X-ray detection we know that these systems should have a mass greater than 10 13 M ⊙ , flagging them as censored data would contradict the mass prior used in fitting the NFW profile. Tests to recover scaling relation parameters on simulated toy data show that censoring leads to a positive bias in the slope. For systems where the lower credible region is truncated by the mass prior and hence underestimated we set the lower mass error equal to the upper mass error. In our toy model tests this gave the least bias in scaling relation parameters, with biases < 10%. The mass-temperature relation based on the 38 clusters that overlap between the XXL-100-GC and the CFHTLenS shear catalog has a slope of b = 1.
The grey shaded region shows the overlap between cool core and undisturbed clusters. ments. Given that the CCCP systems are more massive than ours, we do not expect this difference in aperture to have a significant affect on our results. We confirm that this is indeed the case (see section 4. 1 for more details). We fit the mass-temperature relation to the joint data set following the same procedure as applied to the XXL-only sample in §3. 1. The statistical precision of the fit is much higher than that of the XXL-only fit, and has very similar central values for all fit parameters between the two fits (Table  3 ). The slope parameter of the joint fit is b = 1. 67 +0. 14 -0. 10 with an intrinsic scatter of σ int(ln M | T ) = 0. 41 +0. 07 -0. 06.
3 (e. g  Maughan 2014). In our model this corresponds to less than 5% bias in both slope and normalisation. Kettula et al. (2015)  apply a correction for Eddington bias to both masses and temperatures to a sample similar to ours in their scaling relation. Their results indicate a 10% bias on the slope when uncorrected for; however, this is detected at 0. 7σ significance. For the CCCP clusters used in this paper, a selection function model is not possible. The CCCP sample is selected from a variety of archived data and various selection criteria. We note that the selection function test above only applies to the XXL-only sample, but will be modelled comprehensively in a future XXL paper, when an alternative massive cluster sample with a well-defined selection function is available. Outliers -One particular outlier in our sample is XLSSC 110.
This relation has a slope of 1. 78 +0. 37 -0. 32. -We find that the scatter in our XXL-only mass-temperature relation is dominated by systems with significant offsets between their BCG and X-ray centroids. This suggests that ongoing/recent merging activity may act to increase the scatter by affecting the accuracy of our weak-lensing mass measurements and/or by perturbing the temperature of the merging systems. We will return to this issue when better quality data become available. -We increased the sample by incorporating 48 massive clusters from CCCP and 10 X-ray selected groups from COSMOS. This extended sample spans the temperature range T ≃ 1 -10 keV. The mass-temperature relation for this extended sample is steeper than the self-similar prediction, with a slope of 1. 67 +0. 14 -0. 10 and intrinsic scatter of σ ln M|T = 0.
Our future programme will extend mass-observable scaling relations for groups and clusters in the XXL and related surveys to include other mass proxies, including gas mass and Kband luminosity. We will also expand the sample of groups and poor clusters available for this work as deeper weak-lensing data becomes available for XXL-N from Hyper Suprime-CAM, and high-quality weak-lensing data become available for XXL-S from our ongoing observations with Omegacam on the ESO VLT Survey Telescope. These enlarged samples and the improved statistical precision will also motivate careful modelling and the incorporation of the selection function into our analysis.
Acknowledgements. This work is based on observations obtained with  MegaPrime/MegaCam , a joint project of CFHT and CEA/DAPNIA, at the  Canada-France-Hawaii Telescope (CFHT) , which is operated by the  National Research Council (NRC)  of  Canada , the  Institut National des Sciences de l'Univers of the Centre National de la Recherche Scientifique (CNRS) of France , and the  University of Hawaii. This research used the facilities of the  Canadian Astronomy Data Centre  operated by the  National Research Council of Canada  with the support of the  Canadian Space Agency. CFHTLenS data processing was made possible thanks to significant computing support from the  NSERC   Research Tools and Instruments grant program. We thank the anonymous referee for useful comments and  Doug Applegate ,  Mark Birkinshaw ,  Gus Evrard ,  Will Farr ,  Catherine Heymans ,  Henk Hoekstra ,  Kimo Kettula ,  Sarah Mulroy ,  Nobuhiro Okabe ,  Thomas Reiprich ,  Tim Schrabback ,  Mauro Sereno  and  Trevor Sidery  for helpful discussions and assistance.
53 for an in-depth discussion). Our CGTNS ansatz operates in an active space of selected orbitals and hence approximates a CAS-CI wave function. While this is no issue for the analysis of the CGTNS parameterizations, reliable predictions will require to consider dynamic correlation, which can, for instance, be included by short-range DFT. 54, 23   ence, the theoretical reference for our study will be the CAS-SCF result rather than the CASPT2 data by Phung et al. 52  Density Functional Theory (DFT) structure optimizations of manganocene were conducted with the TURBOMOLE program version 6. 5  55, 56  in the doublet and sextet states. The hybrid Perdew-Burke-Ernzerhof (PBE0)  57  density functional together with triple-ζ valence polarized (def2-TZVP)  58  (for carbon and hydrogen atoms) and quadruple-ζ valence polarized (def2-QZVPP)  59  (for the manganese atom) basis sets were chosen.
1 package. 16 he extended ANO-RCC basis sets (with a total of 1487 basis functions) were employed with [6s4p3d1f] contraction for hydrogen,  66  [8s8p4d3f2g] contraction for carbon,  67  and [10s9p8d6f4g2h] contraction for manganese. 68 Two-electron integrals were approximated with a Cholesky decomposition technique 69 using a threshold of 10 -6 Hartree. Also in these calculations, the second-order scalar-relativistic Douglas-Kroll-Hess Hamiltonian 62, 63, 64, 70 was chosen. The CGTNS program reads one-and two-electron molecular orbital integrals for the second-quantized electronic Hamiltonian generated by MOLCAS. The integrals are calculated from the natural orbitals of the corresponding CAS-SCF reference calculations. For the CGTNS calculations we improved on our original implementation presented in Ref.
Note, that for vinylic substitutions also other mechanisms such as S RN 1-type single-electron transfer may operate  [27e29]. With the exception of 5a, 5b and 5d, which were isolated as viscous oils, all other derivatives (Scheme 3) formed yellow solids. An X-ray structure analysis has been carried out on a crystal of 5i grown from EtOH (Fig. 1 ). The s-trans conformation of the azabutadiene chain found in precursor 4a and in 5f, 5g and 5j is also observed in the solid-state structure of 5i. Metric parameters and crystallographic data are gathered in Tables  1  and 2.
Crystal structure determinations Single crystals of 5i, 7a, 7b, 10 and 11 were mounted on a Nonius Kappa Apex-II CCD diffractometer equipped with a nitrogen jet stream low-temperature system (Oxford Cryosystems). The X-ray source was graphitemonochromated Mo-K a radiation (l ¼ 0. 71073 Å) from a sealed tube. The lattice parameters were obtained by leastsquares fit to the optimized setting angles of the entire set of collected reflections. Intensity data were recorded as f and u scans with k offsets. No significant intensity decay or temperature drift was observed during data collections. Data were reduced by using DENZO software  [56] ; the missing absorption corrections were partially compensated by the data scaling procedure in the data reduction. Absorption correction was further applied by using MULTI-SCAN  [57].