dataesr/scientific-paragraphs-categorization huggingface dataset:
8%) which are completely in line with several previously conducted studies where missense variants showed a frequency of 61. 5%-71. 4%  (Li et al. , 2014; Liang et al. , 2015; Wissinger et al. , 2001). In contrast, 16 out of 98 sequence changes (16%) in the CNGB3 subunit of the cone photoreceptor CNG channel identified in a large cohort of ACHM patients are missense variants  (Mayer et al. , 2017). This high prevalence of missense substitutions in the CNGA3 gene may indicate a reduced tolerance of CNGA3 for amino acid substitutions regarding the functional maintenance of the channel protein. All "likely disease-causing" variants listed in our CNGA3 database except the c. 682G>A/p. (Glu228Lys) variant have a minor allele frequency (MAF) lower than 0. 1% in gnomAD (Table  S3 ). In contrast, the mentioned variant displays a MAF of 0.
13% (Table  S3 ). In the South Asian population, the c. 682G>A/ p. (Glu228Lys) variant displays an even higher allele frequency of F I G U R E 2 Frequencies of "likely disease-causing" variant types within the CNGA3 variant database. The CNGA3 variant database contains 244 "likely disease-causing" variants. The vast majority are missense variants (66. 8%) followed by small indels (16. 8%), and nonsense variants (12. 3%). Splice variants affecting canonical splice sites (CSS) (2. 5%), noncanonical splice site (NCSS) variants (0. 8%), copy number variations (CNV) (0. 4%), and start loss variants (0. 4%) are the minority of the identified variants. S2 ). In addition, one ACHM patient carrying the c. 682G>A/ p. (Glu228Lys) variant homozygously was described in a previously published study  (Sun & Zhang, 2019).
| Functional studies on CNGA3 variants As a first gene therapy trial for ACHM resulting from defects in CNGA3 has already been completed  (Fischer et al. , 2020) , and several trials are ongoing (ClinicalTrials. gov Identifier: NCT02610582, NCT03278873, NCT03758404, and NCT02935517), the genotypes of patients with CNGA3 missense variants classified as "VUS" unfortunately hamper the inclusion of such patients eligible for these gene therapeutic trials. Therefore, functional studies are needed to validate the possible pathogenic effect of the respective variants. Commonly used methods to characterize the functionality of mutant CNG channels involve calcium imaging and patch-clamp recordings of heterologously expressed mutant channels  (Burkard et al. , 2018; Dai & Varnum, 2013; Koeppen et al.
Whereas the overall majority of variants within the CNGA3 protein are missense substitutions, the sequence changes within the N-terminal region mainly comprise nonsense variants or small indels (17 out of 22) (Figure 3). Of 163 "likely disease-causing" missense variants listed in our database, 94 affect amino acid positions which are completely conserved across CNGA3 orthologues and its rod equivalent CNGA1 (TableS3and FigureS2).
I G U R E 3 Localization of "likely disease-causing" CNGA3 variants identified in the ACHM cohort genetically characterized in Tübingen, mutation databases, and in the literature. (a) The CNGA3 gene locus with its eight exons (GRCh38/hg38, NM_001298. 2) (alternatively spliced exon 3b is not shown) is depicted. Noncoding exonic regions are indicated by small light gray rectangles and coding exonic regions by dark gray rectangles. Introns are depicted by a black line. The location of canonical and noncanonical splice site variants, start loss variants and small insertion, duplication, deletions, and indel variants resulting in frameshift with premature termination codon are depicted above the CNGA3 gene. Variants are color-coded with respect to their location within functional domains of the CNGA3 protein.
F I G U R E 3 Localization of "likely disease-causing" CNGA3 variants identified in the ACHM cohort genetically characterized in Tübingen, mutation databases, and in the literature. (a) The CNGA3 gene locus with its eight exons (GRCh38/hg38, NM_001298. 2) (alternatively spliced exon 3b is not shown) is depicted. Noncoding exonic regions are indicated by small light gray rectangles and coding exonic regions by dark gray rectangles. Introns are depicted by a black line. The location of canonical and noncanonical splice site variants, start loss variants and small insertion, duplication, deletions, and indel variants resulting in frameshift with premature termination codon are depicted above the CNGA3 gene. Variants are color-coded with respect to their location within functional domains of the CNGA3 protein.
Variants in the CNGA3 gene reported in the literature, mutation databases and novel variants identified in the ACHM study cohort genetically characterized in Tübingen SOLAKI ET AL. SOLAKI ET AL. SOLAKI ET AL. SOLAKI ET AL. | 9 | 11 | 13 T A B L E 2 (Continued) T A B L E 2 (Continued) T A B L E 2 (Continued) T A B L E 2 (Continued) T A B L E 2 (Continued) T A B L E 2 (Continued) T A B L E 2 (Continued) Location Location Location Location Location Location Location Alteration nucleotide Alteration nucleotide Alteration nucleotide Alteration nucleotide Alteration nucleotide Alteration nucleotide Alteration nucleotide Location protein Location protein Location protein Location protein Location protein Location protein Location protein ACMG/AMP ACMG/AMP ACMG/AMP ACMG/AMP ACMG/AMP ACMG/AMP ACMG/AMP Location CNGA3 CNGA3 CNGA3 CNGA3 CNGA3 CNGA3 CNGA3 Alteration nucleotide sequence a sequence a sequence a sequence a sequence a sequence a sequence a Alteration polypeptide Alteration polypeptide Alteration polypeptide Alteration polypeptide Alteration polypeptide Alteration polypeptide Alteration polypeptide Location protein domain b domain b domain b domain b domain b domain b domain b References References References References References References References ACMG/AMP classification classification classification classification classification classification classification CNGA3 Exon Exon Exon Exon Exon Exon Exon sequence a c.
Fitting of I c (d N ) After identifying two theoretically possible scenarios of spin current propagation, we can now roughly estimate the absolute magnitude of θ N and λ N by simultaneously fitting Equation (  4 ) to both data sets of the A-normalized rms I c versus d N in Figure  3a, b. The fit minimizes the weighted sum of the squares R 2 of both data sets + - Fe NbSe 2 Ni NbSe 2 2 2 qR q R with the relative weight q that allows us to prioritize one of the trends. Because the normalized data are determined up to a global scaling factor, the fitting process yields only the relative proportion θ θ θ ′ : : NbSe Fe Fe 2. To obtain the absolute value of the spin Hall angles, we compare it to the A-normalized rms I c of the reference samples Fe|Pt and Ni|Pt (Figure  2b, c ) and use θ Pt ≈ 10%  [21]  , as detailed in the Experimental Section.
[21, 40, 45] Since we use only the ratio of simultaneously measured rms I c in Equation (9a), all F-specific factors affecting the emission process are canceled out. Solving Equation (  9 ) for both F yields Ab Initio Calculations: Density functional calculations are performed for the bulk NbSe 2 with an in-plane lattice constant of 3. 44 Å. The distance between the van der Waals layers is 2. 89 Å. The generalized gradient approximation of Perdew-Burke-Ernzerhof  [70]  is used for the exchange-correlation potential as implemented in the FLEUR code. [71] he maximally localized Wannier functions are constructed using the WANNIER90 code in conjunction with the FLEUR package,  [72, 73]  based on which an effective Hamiltonian in a tight-binding scheme is constructed for the calculation of the DC spin Hall conductivity ij l σ according to.
Acknowledgements The authors acknowledge funding by the  German Research Foundation  through the collaborative research center  SFB TRR 227 "Ultrafast spin dynamics " (Project  ID   328545488 , projects  A05 ,  B02 , and  B10 ), the  European Union   H2020 program  through the projects  CoG TERAMAG  (Grant No. 681917 ) and ASPIN (Grant No. 766566 ), the  DFG priority program INTEREST  (project  ITISA ), the  Czech Science Foundation  through Project  GA CR  (Grant No. 21-28876J ), and the  Grant Agency of the Charles University  (Grant No. SVV-2022-260590 ). Y. M. acknowledges funding from  Deutsche Forschungsgemeinschaft (DFG, German Research Foundation ) -TRR  288 -422213477  (Project  B06 ). Y. M. acknowledges the  Jülich Supercomputing Centre  for providing computational resources under Project No.
8 < z < 2. 2, with an ef fecti ve redshift z eff = 1. 48. The covariance matrix of these measurements were obtained using the set of 1000 mock catalogues described in  Zhao et al. ( 2021 ). Besides the QSO sample used here, the full eBOSS data set contains two additional tracers, the luminous red galaxy and emission line galaxy samples (for the corresponding BAO and RSD analyses, see  Gil-Mar ín et al. 2020 ; Tamone et al. 2020 ; Bautista et al. 2021 ; de Mattia et al. 2021  ). These samples o v erlap in redshift among them and with the galaxies from BOSS. We therefore restrict our analysis of eBOSS data to the QSO sample to, in combination with BOSS, co v er the maximum possible redshift range while ensuring that the clustering measurements can be treated as independent in our likelihood analysis.
We therefore opt to focus on σ 12 and quantities that carry no explicit dependence on the Hubble constant h in order to enable us to appropriately combine and compare the constraints from our data sets. We obtain the posterior distribution of all these parameters by performing Markov chain Monte Carlo sampling with COSMOMC  (Lewis & Bridle 2002 ) , which uses CAMB to calculate the lineartheory matter power spectra  (Lewis et al. 2000 ) , adapted to compute the theoretical model of our anisotropic clustering measurements described in Section 2. 2. COSMOMC uses as basis parameters the set θ θ θ base = ( ω b , ω c , MC , A s , n s ) , ( 20 ) where MC is defined by a factor 100 times the approximate angular size of the sound horizon at recombination. With the exception of the physical baryon density, we assign flat uninformative priors to all the parameters of equation (  20 ) as was done in Tr öster et al.
( 2020 ). Our prior for ω b has to be restrictive, as our clustering measurements cannot constrain this parameter by themselv es. Nev ertheless, it is chosen to be approximately 25 times wider than the constraints on this parameter derived from Planck data alone (Planck Collaboration VI 2020 ). Even though we do not sample the Hubble parameter h , we still need to specify the values allowed -our chosen range 0. 5 < h < 0. 9 is wider than that of the KiDS-450 analysis of  Hildebrandt et al. ( 2016 )  and comparable to the one used in the DES-YR1 fiducial analysis of  Abbott et al. ( 2018 ). Joudaki et al. ( 2016 )  showed that the prior on h has no impact on the significance of the σ 8 tension. We list all the priors used in this analysis in Table  1. As discussed by  Sanchez et al. ( 2021 ) , the effect of all evolution parameters on the linear matter power spectrum is degenerate: for a given set of shape parameters, the linear power spectra of all possible combinations of evolution parameters that lead to the same value of σ 12 ( z) are identical.
However, if the shape parameters are fixed, clustering data can provide precise measurements of the evolution parameters. To test the impact of the additional information on the shape of the linear power spectrum, along with the priors described abo v e, we use another set of priors to explore the constraints on the evolution parameters. For these runs, we impose Gaussian priors on the cosmological parameters that control the shape of the linear power spectrum -ω b , ω c , and n s. We derived the covariance matrix and mean values for these priors from our Planck -only posterior distributions. We refer to these constraints as the ' Planck shape' case.
The OUTERRIM  (Heitmann et al. 2019  ) simulation uses 10 240 3 dark matter particles to trace the dark matter density field in a L = 3 h -1 Gpc size box. We use a set of 100 mock catalogues constructed from the snapshot at z = 1. 433, which was populated using an HOD model matching the clustering of the eBOSS QSO sample and tested e xtensiv ely in the mock challenge (labelled as HOD0 in  Smith et al. 2020 ). These realizations include catastrophic redshift failures at a rate of 1. 5 per cent, which corresponds to that of the eBOSS quasars. We measured the mean clustering wedges of the samples from MINERVA and the Legendre multipoles from OUTERRIM with the same binning and range of scales as those of the real data from BOSS and eBOSS and computed their corresponding theoretical covariance matrices using the Gaussian recipe of  Grieb et al.
R E S U LT S Our main results come from the combination of the full shape analyses of the BOSS galaxy clustering wedges and eBOSS QSO Legendre multipoles described in Section 2. 1. We also present combined late-Universe constraints obtained from the joint analysis of these clustering measurements with the 3 × 2pt data set from DES Y1. For comparison, in Appendix A , we present the constraints obtained using instead the cosmic shear measurements from KiDS-450, which lead to similar results. As we find a good agreement between BOSS + eBOSS + DES and Planck , we also present the parameter constraints obtained from the combination of all four data sets. These constraints are summarized in Table  2  and are discussed in Sections 3. 1 -3. 3.
Clustering constraints Here, we present the main result of our work -the combined flat CDM constraints from the anisotropic clustering measurements from BOSS and eBOSS. Fig. 4  shows the posterior distributions for BOSS and eBOSS separately (light blue and orange contours, respectively) as well as their combined constraints (green contours) for two sub-sets of cosmological parameters. For comparison, we also show the Planck -only constraints in dark blue. The panels on the left show the results on the more traditional parameter set of σ 8 , m , and H 0 whereas the ones on the right correspond to the alternative basis discussed in Section 2. 4 of σ 12 , ω m , and ω DE. Regardless of the parameter space considered, we find all of our data sets to be in good agreement with each other. The largest deviation between the joint BOSS + eBOSS constraints and those reco v ered from Planck can be observ ed in the matter density m , which displays a difference at the 1.
AC K N OW L E D G E M E N T S We w ould lik e to thank  Benjam ín Camacho ,  Daniel Farrow ,  Martha Lippich , T ilman T r öster, and  Marco Raveri  for their help and useful suggestions. This research was supported by the  Excellence Cluster ORIGINS , which is funded by the  Deutsche Forschungsgemeinschaft (DFG, German Research Foundation ) under Germany's Excellence Strategy -EXC-2094 -390783311. GR acknowledges support from the  National Research Foundation of Korea (NRF)  through Grants No. 2017R1E1A1A01077508  and No. 2020R1A2C1005655  funded by the  Korean Ministry of Education, Science and Technology (MoEST). Funding for the  Sloan Digital Sky Survey IV  has been provided by the  Alfred P. Sloan Foundation , the  U. S. Department of Energy Office of Science , and the Participating Institutions.
Data analysis To filter the measured photoelectron spectra on a shot-to-shot basis, we used the photon spectrum recorded by the Photon Analysis Delivery and REduction System (PADRES) at FERMI to determine the bandwidth (FWHM) of the XUV pulse. Any shot without the photon spectrum was rejected: out of 355,000 shots, 354,328 shots were retained. All the shots with more than 65-meV FWHM width were discarded (Extended Data Fig. 2a ). It is noted that the simulated value of the photon bandwidth (59 meV) lies within the filtering window of 20-65 meV. In addition, we chose only the shots with integrated spectral intensities ranging from 0. 8 × 10 5 to 1. 6 × 10 5 in arbitrary units (Extended Data Fig. 2b ). The filtered shots were sorted into 30 photonenergy bins, uniformly separated from each other by about 13 meV and covering the entire photon energy window of the wavelength scan (Extended Data Fig.
Acknowledgements We acknowledge financial support from  LASERLAB-EUROPE  (grant agreement number  654148 ,  European Union 's  Horizon 2020 research and innovation programme ). S. N. thanks  CNRS and Fédération de Recherche André Marie Ampère, Lyon  for financial support. J. M. D. acknowledges support from the  Knut and Alice Wallenberg Foundation  ( 2017. 0104and 2019. 0154 ), the  Swedish Research Council  ( 2018-03845 ) and the  Olle Engkvist's Foundation  ( 194-0734 ). R. F. thanks the  Swedish Research Council  ( 2018-03731 ) and the  Knut and Alice Wallenberg Foundation  ( 2017. 0104 )for financial support. P. E. -J. acknowledges support from the  Swedish Research Council  ( 2017-04106 ) and the  Swedish Foundation for Strategic Research  ( FFL12-0101 ).
Ammonia (NH3) is the most abundant alkaline compound in the atmosphere, with consequences for the environment, human health, and radiative forcing. In urban environments, it is known to play a key role in the formation of secondary aerosols through its reactions with nitric and sulphuric acids. However, there are only a few studies about NH3 in Mexico City. In this work, atmospheric NH3 was measured over Mexico City between 2012 and 2020 by means of groundbased solar absorption spectroscopy using Fourier transform infrared (FTIR) spectrometers at two sites (urban and remote). Total columns of NH3 were retrieved from the FTIR spectra and compared with data obtained from the Infrared Atmospheric Sounding Interferometer (IASI) satellite instrument. The diurnal variability of NH3 differs between the two FTIR stations and is strongly influenced by the urban sources.
Finally,  Van Damme et al. (2021)  reported an increasing trend of NH3 over Mexico of (2. 5±1. 5)x10 13 molecules cm -2 yr -1 using 11 years of IASI satellite data  (2008) (2009) (2010) (2011) (2012) (2013) (2014) (2015) (2016) (2017) (2018). In this work, the diurnal and seasonal variability of NH3 over Mexico City is investigated using datasets from two groundbased FTIR spectrometers, including an extension of the FTIR-NH3 total column time series of the station in Mexico City used in  Dammers et al. (2016) , and of the FTIR-NH3 total columns measured at Altzomoni, a remote high-altitude station close to Mexico City, that are retrieved for the first time. The locations of these two sites are shown in Figure  1.
Spectroscopic parameters were obtained from the high-resolution transmission molecular absorption database HITRAN 2008  (Rothman et al. , 2009) , and the a priori profile information about the interfering gases was obtained from 40-year averages of simulations from the Whole Atmosphere Community Climate Model (WACCM)  (Eyring et al. , 2007; Marsh et al. , 2013). Since NH3 profiles are not available from WACCM, scaled a priori profiles derived from the global chemical transport model GEOS-Chem v11 NH3 were used instead. Constructed scaled a priori profiles have been used previously from GEOS-Chem simulations for the retrieval of trace gases  (Shephard et al. , 2011; Shephard and Cady-Pereira, 2015; Bader et al. , 2017). A total of 7992 NH3 columns were retrieved for the UNAM station and 4031 for ALTZ.
IASI-NH3 data product and comparison methodology IASI measures the infrared thermal radiation emitted by the Earth's surface and the atmosphere from a Sun-synchronous orbit on board the MetOp platform. Spectra are recorded in the 645-2760 cm -1 spectral range at a spectral resolution of 0. 5 cm -1  (Clerbaux et al. , 2009). The instrument crosses the equator at mean local solar times of 09:30 and 21:30, providing global coverage of the Earth twice a day. IASI has a field-of-view composed of four circular footprints each with a diameter https://doi. org/10. 5194/acp-2022-217 Preprint. Discussion started: 6 May 2022 c Author(s) 2022. CC BY 4. 0 License. of 12 km at the nadir view and up to 20 km x 39 km elliptical pixels outside the nadir depending on the satellite viewing angle, complemented by scanning along a swath width of 2200 km off-nadir perpendicular to the ground track  (Clarisse et al.
, 2010). For this study, eleven years of the IASI-A NH3 total columns (ANNI-NH3-v3) between 2008-2018 were used; details of this version 3 can be found in Appendix A of  Van Damme et al. (2021) , and was also used by  Yamanouchi et al. (2021)  and  Viatte et al. (2022). The spatial distribution of NH3 over Mexico City was obtained by averaging all the IASI-A morning observations between January 2008 and December 2018 over this region. The FTIR-NH3 total columns at UNAM were compared against the IASI-NH3 total columns over Mexico City to assess the agreement between both data sets. Due to the high spatiotemporal variability of NH3, the temporal and spatial coincidence criteria were tested and assessed using the correlations (both R and slope). In addition, as suggested in  Dammers et al. (2016) , an elevation filter (FTIR station altitude minus IASI observation < 300 m) was applied.
The criteria resulting in the best correlations were elevation filter < 300 m, spatial sampling difference < 20 km, maximum temporal sampling difference ± 40 min, and maximum IASI-NH3 retrieval error of 100%. The seasonal variability comparison and annual averages were performed using only FTIR-NH3 retrievals between 9:00 and 10:59 a. m. (Local Time), corresponding to the IASI overpass time over Mexico City, and the < 20 km spatial criterion for IASI-NH3 total columns. Altzomoni correlation plots with IASI-NH3 data were not included due to the few coincidences between the FTIR and IASI, a consequence of the station's high-altitude location.
Comparisons between the NH3 seasonal variability and time evolution over the UNAM station in Mexico City were performed using morning (9-11 h) FTIR-NH3 columns and IASI-NH3 columns with a spatial criterion of < 20 km from the UNAM station (Figure  9a ). The NH3 seasonal variability over Mexico City in Figure  7a , is similar for both the IASI and ground-based FTIR NH3 columns and is in agreement with Figure  4. However, the IASI-NH3 shown a consistent negative bias. The time evolution is represented with the IASI-NH3 and FTIR-NH3 annual averages in Figure  9b. The datasets suggest an increasing trend in the annual averages of the NH3 total columns, with larger columns observed in the most recent years, even in Altzomoni except for 2013, which was affected by the February 27 event as discussed previously.
Conclusions This work presented the temporal and spatial distribution of NH₃ total columns over the Mexico City Metropolitan Area derived from two ground-based FTIR spectrometers and IASI satellite observations. The average NH3 total column at the urban UNAM site (1. 46 ± 0. 64 x 10 16 molecules/cm²) is considerably higher than that at the remote station Altzomoni (1. 87 ± 2. 40 x 10 15 molecules/cm 2 ), with a clear difference in the diurnal cycle but similar seasonal variability. NH3 spatial distribution from IASI shows the highest NH3 columns in the northeast part of the city, an area surrounded by water bodies, a landfill, a compost plant for the treatment of all the organic waste, and the airport. The IASI ANNI-NH3-v3 data product underestimates the NH3 total columns over Mexico City, with a mean relative difference of 32%, over the period 2008-2018 but showed a similar temporal variability and a good correlation with FTIR measurements (R=0.
Acknowledgements We acknowledge the use of imagery from the Worldview Snapshots application (https://wvs. earthdata. nasa. gov),part of the Earth Observing System Data and Information System (EOSDIS). BH acknowledges  CONACYT  for the scholarship granted. The  RUOA Network  (www. ruoa. unam. mx) is acknowledged for making the meteorological measurements available. IASI is a joint mission of  EUMETSAT  and the  Centre National d'Etudes Spatiales (CNES, France). The authors acknowledge the  ULB-LATMOS team  for providing the IASI data, and for the development of the retrieval algorithms.