dataesr/scientific-paragraphs-categorization huggingface dataset:
Absorbance at 600 nm (A 600 ; i. e. , optical density at 600 nm [OD 600 ]) was measured for each well at 20-min intervals. Data were processed using Gen5 software (BioTek) and Microsoft Excel. Growth was quantified in each assay by first identifying a minimum time point (A min ) at which A 600 had increased by 15% over a baseline reading taken during the first 500 min of incubation. Next, we identified the time point at which A 600 reached its maximum (A max ) immediately after exponential growth. The growth rate for each well was defined by (A max Ϫ A min )/(T max Ϫ T min ), where T max and T min are the corresponding time values for each absorbance. To account for variations in inoculum density, for each strain, the lag time (T min ) on glucose was subtracted from the lag time for the substrate of interest; in all cases, cultures had shorter lag times on glucose than other glycans.
Cells were washed with PBS and then resuspended in 0. 4 ml of a 1/500 dilution of Alexa Fluor 488 goat anti-rabbit IgG (Life Technologies) in blocking solution and incubated with rocking for 1 h at 20°C. Cells were washed three times with an excess of PBS and then resuspended in 20 l of PBS plus 1 l of ProLong Gold antifade (Life Technologies). Cells were spotted on 0. 8% agarose pads and imaged at the Center for Live Cell Imaging at the University of Michigan Medical School, using an Olympus IX70 inverted confocal microscope. Images were processed with Metamorph Software. Crystallization and data collection. All X-ray diffraction data for both native and selenomethionine-substituted protein crystals were collected at the Life Science Consortium (LS-CAT) at the Advance Photon Source at Argonne National Laboratory in Argonne, IL.
1 M sodium acetate (pH 4. 6). All SGBP-B crystals were flash-frozen prior to data collection by briefly soaking in a solution of 80% mother liquor-20% glycerol plus 10 mM xylogluco-oligosaccharide. Data were processed and scaled using HKL2000 and Scalepack  (53). SAD phasing from a selenomethioninesubstituted protein crystals was used to determine the structure of SGBP-B. The AutoSol  (54)  and Autobuild (55) algorithms within the Phenix (56) suite of programs were used to locate and refine the selenium positions and automatically build an initial model of the protein structure, respectively. Successive rounds of manual model building and refinement in Coot  (57)  and Phenix, respectively, were utilized to build a 2. 7-Å model of the selenomethionine-substituted protein, which then was placed in the unit cell of the native data set.
ACKNOWLEDGMENTS We thank  Eric C. Martens  and his laboratory at the  University of Michigan Medical School  for the use of their anaerobic chamber and plate reader for kinetic growth assays, as well as for the providing the B. ovatus ⌬tdk strain and B. ovatus ⌬XyGUL strain for genetic manipulation and growth experiments, respectively. We thank  Eric C. Martens  and  Darrell W. Cockburn  at the  University of Michigan Medical School  for helpful discussions on experimental design and data interpretation. Work in Vancouver was initially supported by a  Discovery Grant  from the  Natural Sciences and Engineering Research Council of Canada and UBC Faculty funding , followed by  Canadian Institutes for Health Research Operating Grants  (FRN:  MOP-137134  and  MOP-142472 ). Infrastructure support was provided by the  Canadian Foundation for Innovation  and the  British Columbia Knowledge Development Fund.
To reduce redundancy in the Principal Component Analysis (PCA), we used Pearson correlation coefficients (through linear regression analyses) for data exploration. Those characters from the morphometric dataset that expressed more significant linear relationships among the   4 ), anterior length (5), posterior length  (18) , asymmetry (5/18), height of ligamental area  (6) , length of ligamental area  (7) , median height of hinge plate (directly below umbo)  (8) , height of ligamental area / height of hinge plate (6/8), height of anterior tooth row  (15) , height of posterior tooth row  (16) , distance between last anterior and posterior teeth  (14) , height of anterior adductor scar  (9) , length of anterior adductor scar  (10) , area of anterior adductor scar (9*10/2), height of posterior adductor scar  (11) , length of posterior adductor scar  (12) , area of posterior adductor scar (11*12/2), distance between inner margins of adductor scars  (13) , adductor moment = sum of adductor scar areas*mean distance from hinge axis, height of crenulated extra-pallial margin  (17)  and the width (W).
Due to the wide range of variables at different scales a correlation matrix was used in the PCA. A Linear Discriminant Analysis was sought to discriminate differences among populations. Statistical analyses were carried out using the open software PAST v3. 0  [35]. Landmark-basedgeometric morphometrics (GM). The GM analyses implemented in software MorphoJ  [36]  were used to quantify shape variation from 60 images of Glycymeris sp. from different localities (15 samples from each group). For all specimens, the inner side of the right valve was photographed and digitized with the software TPS dig2  [37]. From these images 12 landmarks and 2 semi-landmarks were defined (Fig  3 ). Landmarks were subjected to a standard generalized Procrustes alignment to remove differences between specimens based on scale, rotation, and location.
(Seul, Korea) on an ABI 3730 automatic sequencer. From GenBank database, 5 species of Arcida (Arca ventricosa, Accession number AB076935. 1; Tegillarca granosa, HQ896817. 1; Cucullaea labiata, AB050892. 1; Cosa waikikia, AB084107. 1; G. glycymeris, KC429093. 1) were additionally used as ingroup samples for COI reconstruction while two pteriomorph species from different orders (Isognomon legumen, AB076950. 1; Spondylus gaederopus, JF496776. 1) and the protobranch Nucula atacellana (KJ950273. 1) were chosen as outgroups (see  [34] ). To fulfill ITS2 data set, G. glycymeris (FN667988. 1) originating from Tuscan Archipelago, Mediterranean Sea  [32]  were used to accommodate intra family analysis. Sequences were screened using BLAST searches (ncbi. nlm. nih. gov), trimmed and aligned in ClustalW 2.
Genetic diversity and phylogenetic analyses Molecular diversity was measured using Dnasp 5. 10  [41]  calculating the number of haplotypes (H), polymorphic sites (S), haplotype and nucleotide diversity. Intra-and interspecific distance was calculated in MEGA6  [42]. The demographic histories for G. glycymeris and G. pilosa were tested using Tajima's D  [43]  and Fu's FST  [44] , where negative values indicated population expansion or historical bottleneck  [45]. The significance of tests were assessed using 10,000 samples simulated under a model of constant population size in Arlequin 3. 5. 1. 2 [46]. Phylogenetic reconstructions were estimated using maximum likelihood (ML) and Bayesian (BI) analysis on COI and ITS2 datasets. jModelTest  [47]  was used to determine the most suitable model of sequence evolution under the Akaike information criterion (AIC).
Divergence time estimates Divergence times of G. glycymeris and G. pilosa were estimated using BEAST 1. 8. 1  [51]  as implemented on the CIPRES web portal  [52] , on the COI dataset. In respect to Combosch & Giribet  [34] , three fossil-based calibration points were used: (i) the root age of Bivalvia between 520. 5 and 530 Ma, (ii) the age of Arcida at 478. 6 (±5) Ma based on Glyptarca serrata  [53] , and (iii) the age of Glycymerididae at 167. 7 (±5) Ma based on Trigonarca tumida  [54]. Analyses were performed under relaxed uncorrelated lognormal clocks and a constant size coalescent population model. These priors were selected according to the Bayes factors from TRACER 1. 6  [55]  calculated to compare models, although all tested models including strict or relaxed molecular clock combined to exponential growth coalescent population model or Yule process speciation model produced similar divergence time estimates.
Morphometric analysis Classical morphometric variables showed significant differences among populations (MAN-OVA, Wilk's Lambda test, F = 17. 43, P < 0. 001). As a result of bivariate analysis among all the 24 measured characters, the dataset to carry out PCA was reduced to those areas representing the umbo region, adductor muscles and shell dimensions contributing in a total of 10 ratios (W/L, L/H, A/H, HL/H, LA/H, LL/L, AM/S, PM/S, M/H, logAM). Linear regression analyses indicated the shell width to be highly correlated with the shell length in populations of G. pilosa (r > 0. 94, p < 0. 001, with a R 2 > 0. 89) and somewhat less for G. glycymeris (r > 0. 77, p < 0. 001, with a R 2 = 0. 57). Geographically, Pag presented the most dispersed data. The height of the ligament to shell height showed a high correlation in all populations except Pašman (R 2 > 0.
Molecular analysis Fragments of 669 and 299 bp were obtained for COI and ITS2 genes, respectively. A total of 16 COI haplotypes and three ITS2 haplotypes were identified among G. glycymeris dataset. The COI gene contained 15 variable sites, whereas the ITS2 gene contained only two variable sites. For the G. pilosa dataset, a total of 32 variable sites and 19 haplotypes were identified for COI gene while the ITS2 gene contained only one variable site and two haplotypes. Genetic diversity indices for each gene and species are summarized in S2  quite higher values of both haplotype and nucleotide diversities (h = 0. 96; π = 0. 056) in comparison to the nuclear gene (h = 0. 62; π = 0. 005). For both genes, the most common haplotypes of G. glycymeris and G. pilosa were presented in both sampling locations (S3 Table ).
COI interspecific divergence accounted for 11% and for ITS2 was 0. 9%, respectively. Mean intraspecific divergence in the G. glycymeris dataset were 0. 4% (COI) and 0. 04% (ITS2), while in the G. pilosa were 1. 1% (COI) and 0. 1% (ITS2), respectively. Neutrality tests applied to search demographic species pattern revealed significant negative values for Tajima's D and Fu's F ST for both G. glycymeris and G. pilosa, indicating a recent expansion of mtDNA haplotypes (S3 Table ). For COI gene, the dated topology (BEAST), Bayesian and ML analysis gave congruent results. Phylogenetic reconstructions distinguished four strongly supported species of Glycymerididae (bootstrap support 97% to 99%, posterior probabilities 0. 95-0. 99) in the ingroup ( Both species delimitation analyses performed by implementing the coalescent tree-based approach (GMYC and bPTP) produced similar results and provided strong support for the a priori defined morphospecies.
Acknowledgments Professor Brian Morton  is acknowledged for suggesting this study. We are grateful to  Paul Butler  and  Isobel Bloor  for the collection of UK samples, to  Montserrat Ramón  for the samples of G. bimaculata and to  Filip Bukša  and  Ivan Župan  for the collection of Croatian specimens. Authors want to thank the two referees ( Graham Oliver  and  Rafael LaPerna ) for their comments which helped improving the quality of our manuscript.
AP and AF were funded by the  European Union Seventh Framework Programme  (FP7-PEOPLE-2013-ITN, http://ec. europa. eu/rea/index_en. htm, grant agreement number:  604802 , ARAMACC " Annually Resolved Archives of Marine Climate Change ," http://aramacc. com/). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Topological Analysis and Supramolecular Assembly Following the procedure of a metal cluster notation  [22]  implemented into the ToposPro package (the Samara Center for Theoretical Materials Science, Samara, Russia)  [23]  we obtained that nickel atoms in compound 1 form in terms of the NDk-m notation the discrete 5M6-1clusters, where 5 is the coordination number of topologically non-equivalent nodes, M denotes a discrete cluster, 6 is the number of metal atoms in the cluster, and 1 is a classification number to distinguish topologically-distinct clusters with equal NDk parameters. A database of topological representations of polynuclear nickel compounds  [24]  contains representatives of the nickel clusters with the 5M6-1 topology, and µ 6 -coordinated Hal ´and S 2´a nions; recently, some of us have synthesized a nickel-silsesquioxane encapsulating the O 2´a nion  [13].
X-ray Diffraction Study X-ray diffraction studies were carried out on Bruker APEX DUO diffractometer (Madison, WI, USA). The structure was solved by direct method and refined in anisotropic approximation against F2. The positions of hydrogen atoms were calculated from geometrical point of view and refined in isotropic approximation (the C-H and O-H distances and displacement parameters of hydrogen atoms are constrained). All calculations were carried out with SHELX (Gottingen, Germany)  [54, 55]  and OLEX2 software (Durham, UK)  [56]. The experimental parameters and crystal data are summarized in Table  2.
Acknowledgments: The authors gratefully acknowledge support of the  Russian Foundation for Basic Research  (projects  14-03-00713 ,  16-03-00206 ,  16-03-00254 ) and the  "Science without Borders Program, Brazil-Russia", CAPES  (grant  A017-2013 ). D. M. is grateful to  CNPq  (grants  311585/2013-2, 472130/2012-9 ).
Conclusions Synthesized in this work complex (PhSiO 1,5 ) 12 (NiO) 6 (NaCl)(C 4 H 8 O 2 ) 13 (PhCN) 2 (H 2 O) 2 represents very rare case of polyhedral complexation of metallasilsesquioxane with benzonitrile. The complex exhibited catalytic activity in oxidation of alcohols with tert-butylhydroperoxide and alkanes with meta-chloroperoxybenzoic acid. Supplementary Materials: Supplementary materials can be accessed at: http://www. mdpi. com/ 1420-3049/21/5/665/s1. CCDC 1471551 contains the supplementary crystallographic data for complex 1. These data can be obtained free of charge from The Cambridge Crystallographic Data Centre via www. ccdc. cam. ac. uk/data_request/cif.
Gel Electrophoresis, Purification and DNA Sequencing All PCR products were run on 1% agarose gels to check for PCR performance and correct amplicon size. PCR products of polA and tp0548 of the correct size were excised from the gel and purified with the Qiagen Gel Extraction Kit (Qiagen, Cat# 28,706) according to the manufacturer's protocol. Unspecific PCR products were occasionally observed, but ignored for further analysis. No sequence variation was expected for tp0574 (tp47). Therefore, only PCR products amplified from two independent fly samples were Sanger sequenced to receive final proof of the correct PCR product (data not shown). Sanger sequencing was performed utilizing the BigDye Terminator Cycle Sequencing kit (Applied Biosystems, Cat# 4,337,455) and the respective forward and reverse amplification primers.
Data Analysis Sequences were analyzed and edited using 4Peaks 1. 8 (Griekspoor and Groothuis, nucleobytes. com) and SeaView 4. 5. 4 software  (Gouy et al. , 2010). Sequences were compared to respective orthologous sequences available in GenBank using the standard nucleotide (nt) BLAST search option (http://blast. ncbi. nlm. nih. gov/Blast. cgi) at the NCBI homepage. Phylogenetic tree reconstruction was conducted using 26 tp0548 sequences obtained from fly samples (accession numbers can be found under 2. 6 or in Table  S2 ) and one of 28 identical sequences from LMNP baboon skin tissue isolates as well as TPA and TPE reference strain sequence data obtained from GenBank. Accession numbers of reference strain sequences are as follows: TPE str. : Gauthier. The accession number of a sequence of tp0548 of type "j", which was obtained from a human, was not available.
Data were copied from the respective publication  (Grange et al. , 2013)  and the extension of these data to cover the full sequence (nt 40 to 344) that was obtained from the flies was added from unpublished data (DS). A maximum parsimony (MP) tree with gaps as fifth character and 1000 bootstrap replicates was constructed in SeaView. Tree visualization and editing was performed in FigTree 1. 4. 2 (http://tree. bio. ed. ac. uk/software/figtree/). Alignment data of sequences used in this study can be found in Fig. S3.
The seven polA and two tp0574 sequences were identical to published orthologs from other T. pallidum subspecies (reference sequences in GenBank: U57757 [polA], M88769 [tp0574]). There was no variation at these two loci in all tested fly specimens. In contrast, in the tp0548 gene (nt 40 to 347, GenBank: CP000805; Fig. S3 ) variation was found among various T. pallidum subspecies and strains, which were included as reference, as well as among sequence data obtained from the fly samples. Among the 308 investigated sites, 66 were variable, of which 24 were parsimony-informative (including gaps; Fig. S3 ). Phylogenetic tree reconstructions based on tp0548 sequence data (Fig. 1 ) show that the T. pallidum sequences obtained from fly specimens were diverse. This does not change even when a neighbor-joining tree is constructed (Fig.
tp0548 sequence data were also evaluated on the basis of the enhanced typing system  (Marra et al. , 2010) , which uses only the sequence region between nt 130 and 215 (with reference to GenBank: CP000805)  (Marra et al. , 2010). As a result and with regard to the currently described subtypes  (Read et al. , 2016) , the subtype distribution within the fly samples encompasses 23 sequences of dominating type "j", two sequences of subtype "a" and a yet undescribed subtype "o" (n = 1; Fig. S5 , Table  S2 ). Fly species varied between the national parks (Fig. 2 ). Two fly species, Chrysomya putoria and Musca sorbens, seem to be disproportionally involved in the acquisition of T. pallidum. A full dataset of all fly specimens is presented in the Supplementary material.
All PCRs applied in this study have been published elsewhere and are frequently used for the detection of T. pallidum in humans. The identity of the tp0548 sequence isolated from olive baboons and the recovery of the same sequence from multiple fly specimens from Tanzania strongly suggests that flies often come into contact with the spirochete on NHPs. Our data are limited in that we did not attempt to isolate viable T. pallidum from the flies, which would be necessary to investigate the contagiousness of insects that carry the bacterium or the organism's ubiquity in the environment. T. pallidum is still not cultivable by standard microbiological techniques. Furthermore, based on the three loci that were amplified, it is not possible to identify the sources of contact with the bacteria, although it is most likely that, within the national park, baboon lesions are the major target for necrophagous flies near baboon groups.
It should be noted, however, that despite the tp0548 identity, other gene sequences differ from the TP str. LMNP sequence (unpublished data). The tree is based on 308 sites of which 24 are parsimony-informative. Gaps were coded as fifth character and 1000 bootstrap replicates were performed. Bootstrap values greater than 90% are displayed at respective nodes. Genbank accession numbers are provided in the Materials and Methods and Table  S2 , as well as the corresponding sequence data alignment, which can be seen in Fig. S3. TPA = T. p. pallidum, TPE = T. p. pertenue, TPEN = T. p. endemicum, str. = strain, F-B = Fribourg-Blanc, TNP = Tarangire National Park; LMNP = Lake Manyara National Park; green symbol: LMNP, blue: TNP. The bar refers to substitutions per site. Fly image source: http://www.
To minimize the effect of water condensing in the tip-tosurface junction, the STM measurements were performed by immersing the tip inside a drop of highly apolar non-solvent, i. e. 1-phenyloctane, which was drop-cast on the pre-assembled organic film prior to the measurement. Alternatively, images were also recorded in air, although at lower resolution. The raw STM data were processed through the application of background flattening. In the case of the HOPG image in fig. 2b , the drift of the piezo was corrected by using the underlying hexagonal graphite lattice as a reference. The lattice of the underlying substrate was visualized by lowering the bias voltage (V t ) to The resistance of the patterned graphene electrodes was measured by a homemade two/four-probe system (Keithley 6517A/Keithley 6514).
Acknowledgments We acknowledge the  European Union Seventh Framework Programme  under grant agreement n°696656  Graphene Flagship , the  EC Marie-Curie ITN-iSwitch  (GA no. 642196 ) and the  FET  project  UPGRADE  (project no. 309056 ). We also acknowledge the  Agence Nationale de la Recherche  through the  LabEx  project  Chemistry of Complex Systems  ( ANR-10-LABX-0026_CSC ), and the  International Center for Frontier Research in Chemistry (icFRC).
The new DUACS DT2014 reprocessed products have been available since April 2014. Numerous innovative changes have been introduced at each step of an extensively revised data processing protocol. The use of a new 20-year altimeter reference period in place of the previous 7-year reference significantly changes the sea level anomaly (SLA) patterns and thus has a strong user impact. The use of upto-date altimeter standards and geophysical corrections, reduced smoothing of the along-track data, and refined mapping parameters, including spatial and temporal correlationscale refinement and measurement errors, all contribute to an improved high-quality DT2014 SLA data set. Although all of the DUACS products have been upgraded, this paper focuses on the enhancements to the gridded SLA products over the global ocean.
Introduction Since its inception in late 1997, the DUACS (Data Unification and Altimeter Combination System) has produced and delivered high-quality along-track (L3) and multi-mission gridded (L4) altimeter products that are used by a large variety of users for different applications. The data are available both in near real time (NRT), with a delay of a few hours to 1 day, and in a delayed time (DT) mode with a delay of a few months. A complete reprocessing of the DT products is done every 4 years approximately. Over the last 2 decades, successive papers have described the evolution of the DUACS system and its associated products  (Le Traon and Hernandez, 1992; Le Traon and Ogor, 1998; Le Traon and Dibarboure, 1999; Le Traon et al. , 1995 , 2003; Ducet et al. , 2000; Pujol and Lamicol, 2005; Dibarboure et al.
, 2011). The quality of DUACS products is affected by several factors, such as the altimeter constellation used for input  (Pascual et al. , 2006; Dibarboure et al. , 2011) , the choices of altimeter standards  (Dibarboure et al. , 2011; Ablain et al. , 2015) , and improve-M. -I. Pujol et al. :  The new multi-mission altimeter data set ments in data processing algorithms  (Ducet et al. , 2000; Dussurget et al. , 2011; Griffin and Cahill, 2012; Escudier et al. , 2013). This paper addresses a new global reprocessing that covers the entire altimeter period and allows us, for the first time, to generate a gridded time series of more than 20 years, identified here as DT2014. The period starts at the beginning of the altimeter era and ranges from 1993 to 2013. Measurements from 10 altimeter missions (repeat track and geodetic orbits) have been used: the TOPEX/Poseidon (TP) and Jason series (Jason-1 (J1) and OSTM/Jason-2 (J2)), ERS-1, ERS-2 and ENVISAT (EN), Geosat Follow On (GFO), Cryosat-2 (C2), Saral/AltiKa (AL) and Haiyang-2A (HY-2A).
The DT2014 reprocessing is characterized by important changes in terms of altimeter standards, data processing and formats. The main changes consist of referencing the SLA products to a new altimeter reference period, taking advantage of the 20 years of measurements that are currently available and optimizing along-track random noise reduction, which affected a large part of the physical signal in the DT2010 version. These changes make a significant impact on the physical content of the SLA and derived products. The gridded SLA products are constructed using more accurate parameters (e. g. , correlation scales, error budgets) and are computed directly at the 1/4 • × 1/4 • Cartesian grid resolution. Other changes that have been implemented allow us to correct a number of different anomalies that were detected in the previous DT2010 product suite.