dataesr/scientific-paragraphs-categorization huggingface dataset:
CO 2 measurements Atmospheric CO 2 concentrations have been measured with a cavity ring-down spectrometer (CRDS) from Picarro (model G2301). This analyzer measures the concentration of CO 2 , CH 4 , and H 2 O every 2-3 s. The analyzer was calibrated upon a suite of four calibrated compressed air cylinders provided by LSCE (Laboratory for Sciences of Climate and Environ-ment) central laboratory (calibrated against the WMO scale) every 2-4 weeks, and quality control of the data was ensured by regular analysis of two target gases (with known and calibrated concentrations); one short-term target gas analyzed for 30 min at least twice a day and one long-term target gas analyzed for 30 min during the calibration procedure. Those regular measurements indicate a repeatability of 0. 04 ppm. Ambient air is pumped from the roof platform through Dekabon tubing.
Hourly data averaging We generally worked with hourly averages to allow for easy synchronization of measurements from different instruments. Hourly averages were based on the arithmetic mean of all data taken within an hour (starting at 0 and ending at 59 min). In the case of TGM, if more than 50 % of the singular data points within an hour were invalid (missing data or flagged as bad data), a no-data value was assigned to the respective hourly average and it was excluded from further analysis. In the case of CO 2 , where measurements were obtained every few seconds, the hourly averages were based on previously computed minute averages.
Solar-induced fluorescence (SIF) -SIFTER As a remotely sensed proxy for vegetation activity, we examined satellite data on solar-induced fluorescence (SIF). More concretely, the SIFTER v2 product de-scribed in  Koren et al. (2018) , provided under the DOI https://doi. org/10. 18160/ECK0-1Y4C, and based on the TEMIS SIFTER v2 product, which uses GOME-2A data  (Kooreman et al. , 2020). SIF has been previously shown to be a good proxy for photosynthetic activity and gross primary production (GPP)  (Frankenberg et al. , 2011; Koren et al. , 2018; Qiu et al. , 2020; Sanders et al. , 2016; Zhang et al. , 2014). Particularly, satellite-obtained SIF is thought to be a more direct measure of plant chemistry than retrieval products based on spectral reflectance, such as the normalized difference vegetation index (NDVI) and the enhanced vegetation index (EVI)  (Luus et al.
, 21, 3447-3472, 2021 The red line shows the robust linear model (iteratively reweighted least squares) between TGM and CO, defined as the difference between actual measurement and assumed background concentrations, for all data in pollution signatures with a >51 % occurrence during the NC BB season (all cells with gray or black "BB" letters in panel a). The resulting slope, which can be interpreted as the TGM / CO emission ratio, is given in units of ppbv TGM ppbv -1 CO (blue) and (ng m -3 ) TGM ppbv -1 CO (green) with its 95 % confidence interval. During the wet season, eBC at CHC station tended to be very low, which is likely linked to the increased wet deposition of particulate matter during that season, whereas CO concentrations were very variable. The absence of a visible pattern concerning TGM in those pollution signatures suggests that TGM concentrations during the wet season are either not importantly affected by combustion of any kind or that different combustion sources are indistinguishable through their eBC and CO signatures around this time.
The TGM / CO emission ratio Having established a clear link between TGM and longrange-transported BB in our data, we aimed to estimate an average biomass burning TGM / CO emission ratio on the continent. A first obstacle arises from the fact that BB is not the only source of TGM and CO measured at Chacaltaya. CO in particular is also readily emitted by anthropogenic activities (e. g. , urban and traffic sources) in the surrounding Altiplano, as can be inferred from CO diel patterns (Fig. 4b ) and previous work  (Wiedensohler et al. , 2018). As a consequence, simply computing TGM vs. CO in the entire unfiltered CHC dataset would not provide the BB-related TGM / CO emission ratio, but a sort of "net emission ratio" over different sources of pollution with distinct emission ratios. To remove this distorting factor as much as possible and obtain a best guess biomass burning TGM / CO emission ratio, we used the results from the previous section (pollution signatures): we attempted to isolate highly BB-influenced air masses by selecting only data with pollution signatures occurring preferentially during the BB season (>51 % of signature data taken in BB season; Fig.
Therefore, we selected Amazonian cluster C1 as the sole representative of Amazonian air masses. We explored two different proxies for a possible vegetation sink effect: CO 2 concentrations measured at CHC (detrended, assuming a Southern Hemisphere linear trend of 2 ppm yr -1 ; trend based on AIRS (Atmospheric Infrared Sounder) CO 2 data between January 2010 and January 2015, averaged over whole South America) and satellite-obtained solar-induced fluorescence (SIFTER) averaged over the (legal) Amazon rainforest as a proxy for Amazon GPP. We then computed the slope of robust linear models for the combinations of TGM vs. CO 2 (TGM = a + b • CO 2 ) and TGM vs. SIFTER (TGM = a + b • SIFTER) for C1 dominant air masses at increasing selection thresholds. We observe an interesting trend, where the magnitude of the slopes becomes more important and slope uncertainty (compare to Sect.
Concerning our second vegetation proxy, remotely sensed SIFTER averaged over the Amazon rainforest, we have to emphasize the difficulty in linking satellite-obtained data with in situ single measurements at CHC, which can only be done under strong assumptions. We chose the whole legal Amazon as a bounding box under the hypothesis that it is, on average, representative of the vegetation that Amazonian C1 dominant air masses are subject to before arriving at CHC. We further assumed that the average transport time between the Amazon and CHC station is much shorter than 1 month; thus, no lag has to be introduced between monthly averaged satellite and in situ observations (see typical transport times in Appendix C). Considering these assumptions, our results have to be taken with care, especially as the seasonality of transport pathways does not allow us to discern if the Amazon rainforest would act as a net sink during the entire year or only as a temporary sink during seasons of high vegetation uptake.
(2016). In our dataset, mean TGM concentrations in western Altiplanic air masses (C5 relative influence >70 %) were significantly higher during the wet season (summer) than during the dry season (winter) (0. 93 ± 0. 07 ng m -3 vs. 0. 77 ± 0. 01 ng m -3 , p = 6. 65×10 -7 , Mann-Whitney test), which is in very good agreement with previous measurements at Lake Titicaca  (Guédron et al. , 2017). Due to sparse vegetation coverage for cells of that cluster, we can mostly exclude a seasonal influence of vegetation, and anthropogenic influences can be considered unlikely candidates to introduce this sort of seasonal variation considering the low population density and the infrequent use of domestic heating and cooling. To further explore possible causes, we computed the TGM difference between the wet season and the rest of the NC period as a pollution map and found that air masses originating close to the Pacific coast showed much higher TGM concentrations in the wet season (austral summer), compared to the rest of the NC period (Fig.
CO 2 is provided by the French monitoring network SNO ICOS-France Atmosphere. SIFTER data, as described in  Koren et al. (2018) , can be found at https://doi. org/10. 18160/ECK0-1Y4C. MOPITT CO gridded daily averages (near-and thermal-infrared radiances) were obtained from the NASA Langley Research Center Atmospheric Science Data Center. Author contributions. AMK performed the data analysis and prepared the figures and paper. OM collected TGM data and took part in scientific discussions, data interpretation, and paper preparation. PL and LB took part in scientific discussions and paper preparation. MA, KS, and MR provided data and took part in scientific discussions and paper preparation. IM and FV collected data and took part in scientific discussions and paper preparation. GS collected data and performed data analysis.
CHC TGM data were collected via instruments coordinated by the IGE-PTICHA technical platform dedicated to atmospheric chemistry field instrumentation. Moreover, we acknowledge the logistical and financial support from IRD (Institut de Recherche pour le Développement) and LFA during the field campaign in Bolivia. CO 2 observations are obtained as part of the SNO IFA French monitoring network. We acknowledge the financial support provided by the PAPILA (Prediction of Air Pollution in Latin America and the Caribbean) mobility project. Analyses and visualizations used in this study were produced with the Giovanni online data system, which is developed and maintained by the NASA GES DISC. Financial support. This research has been supported by the EU H2020 (grant no. 860497). Review statement. This paper was edited by Ashu Dastoor and reviewed by two anonymous referees.
Code hfodd is distributed in the hope that it will be useful, but without any warranty; without even the implied warranty of merchantability or fitness for a particular purpose. See the GNU General Public License http://www. gnu. org/licenses/, for more details. The authors would gladly receive any communication regarding the code, however, no dedicated workforce is available for providing user support of any kind. In Section 2, we review the modifications introduced in the version (v3. 06h) of the code hfodd. Section 3 lists all additional new input keywords and data values, introduced or modified in version (v3. 06h). The rules of building the input data file were defined in Section II-3  [2]  and in the serial mode of version (v3. 06h) they remain exactly the same. These rules specify the generic structure of the input data file, irrespective of which specific keywords are used.
In particular, the keywords can be read in any order and, unless explicitly stated in their description, they are independent of one another. In every new version of the code hfodd, the list of keywords grows and covers new implementations, but they always abide by the same rules specified in Section II-3  [2]. With the new keywords introduced in the present version (v3. 06h) of the code hfodd, the list of available keywords already contains 311 items and their descriptions are scattered over nine different publications. The new User's Guide  [12]  will contain comprehensive coverage of the complete information.
06h) of the code hfodd is the one defined in Refs. [22, 23] , v3 (i, j, k) = 3 u 0 δ(r ij ) δ(r ik ). ( ) 2 In the literature, t 3 = 3 u 0 is often used for the coupling constant instead  [14, 24]. Skyrme's article  [13]  also proposed a gradientless four-body contact interaction, which in some recent beyond mean-field calculations  [25]  was used to complement the threebody pseudopotential of Eq. (  2 ). The form implemented in the version (v3. 06h) of the code hfodd is again the one defined in Ref. [22] , v4 (i, j, k, l) = 12 v 0 δ(r ij ) δ(r ik ) δ(r il ). The factors three and twelve in Eqs. (  2 ) and (3), respectively, count the number of different permutations of the coordinates in the delta functions  [22]. The contributions from these two terms in the particle-hole and like-particle particle-particle channels of the energy density as detailed in Ref.
Zero-range tensor terms The Skyrme interaction, in a majority of practical implementations, does not include tensor terms. In version (v3. 06h) of the code hfodd, we implemented the conventional zero-range tensor interaction considered already by Skyrme in his seminal work  [13] , see also Refs. [26, 27, 28, 29, 30, 31]  and references therein: vT (i, j) = 1 2 t e 3(σ i • k ′ )(σ j • k ′ ) -(σ i • σ j )k ′2 δ (r ij ) + δ (r ij ) 3(σ i • k)(σ j • k) -(σ i • σ j )k 2 + t o 3 2 (σ i • k ′ )δ (r ij ) (σ j • k) + 3 2 (σ j • k ′ )δ (r ij ) (σ i • k) -(σ i • σ j )k ′ δ (r ij ) k , (5) where the first term acts in the relative S-and D-waves whereas the second component acts in the P-wave. Parameters t e and t o are new low-energy coupling constants (LECs) which have to be adjusted to experimental data.
It only modifies the conventional Skyrme EDF coupling constants  [27]. Hence, within the single-reference DFT the effect of the tensor interaction can be mimicked by readjusting the Skyrme-force values of C J 0 t , C J 1 t , and C J 2 t what explains why the tensor interaction is often neglected within the standard Skyrme force. In particular, in version (v3. 06h) of the code hfodd, separate use of the coupling constants C J 0 t , C J 1 t , and C J 2 t has not yet been implemented. Nevertheless, a readjustment or, in general, a direct fit of functional's coupling constants to a dedicated set of empirical data is well within the spirit of the single-reference DFT, which treats EDF as a primary physical object  [28, 30, 31]. One should bear in mind, however, that it breaks bonds between the functional and the underlying interaction what precludes its application within the multi-reference extensions due to singularities that appear in the energy kernels  [17, 18, 19, 20].
It is of importance to underline, that the contributions of class-III local force  (22)  depend on the standard nn and pp densities. This force can be, therefore, taken into account within the conventional pnseparable DFT approach. In contrast, contributions due to the class-II force  (23)  depend explicitly on the mixed pn-densities and require the use of pn-mixed DFT formulated in Refs. [44, 45]  and implemented in the previous version (v2. 73y) of code hfodd  [8]  together with the isocranking method  [46, 47, 44] , which allows control of the isospin degree of freedom. Inclusion of spin-exchange terms in the ISB contact forces  (20)  and (  21 ) leads to a simple rescaling of the t II i and t III i (for i=0, 1, and 2) parameters. Hence, the spinexchange terms are effectively redundant and can be omitted from the ISB contact forces.
and M (n) j , can also be expressed by the strength parameters t (n) j , x (n) j , y (n) j , and z (n) j as W (n) j = t (n) j , B (n) j = t (n) j x (n) j , H (n) j = t (n) j y (n) j , M (n) j = t (n) j z (n) j. (26) Up to sixth order (n = 6), a full classification of operators Ô(n) j (k ′ , k) was presented in Eqs. (  39 )-(54) of Ref. [51]. The EDF generated from the pseudo-potential functional generators for both the particle and pairing channels can be found in  [55]. All fields are implemented self-consistently in the present version (v3. 06h) of the code hfodd and the computation of the HO-basis spatial matrix elements of pseudopotentials is coded using the following integrated-by-parts form, n ′ 1 n ′ 2 | Ô(n) j |n 1 n 2 ≡ dr ′ 1 dr ′ 2 dr 1 dr 2 δ(r ′ 1 -r 1 )δ(r ′ 2 -r 2 )g a (r 1 -r 2 ) × Ô(n) j (k ′ , k)ψ n ′ 1 (r ′ 1 )ψ n ′ 2 (r ′ 2 )ψ n 1 (r 1 )ψ n 2 (r 2 ), (27) where ψ n (r) ≡ ψ nxnynz (x, y, z) are the 3D deformed HO wave functions, Eqs.
The standard way to proceed, which for the local LO term Ô(0) 1 = 1 was developed in Ref. [56] , is to replace the products of HO wavefunctions ψ n ′ 1 (r 1 )ψ n 1 (r 1 ) and ψ n ′ 2 (r 2 )ψ n 2 (r 2 ) by sums of the HO wavefunctions. Then, use the Moshinsky brackets to introduce the relative coordinate r 1 -r 2 on which the Gaussian form factor depends. At higher orders, this approach requires explicit treatment of terms that stem from expanding powers of relative-momentum operators that appear in Eq. (29). Although this tedious procedure was up to 4th order implemented in version (v3. 06h) of the code hfodd, an alternative and more compact procedure is to reverse the order of steps and begin by performing two Moshinsky transformations, ψ n ′ 1 (r ′ 1 )ψ n ′ 2 (r ′ 2 ) = n ′ 1 +n ′ 2 N ′ =0 M n ′ 1 n ′ 2 N ′ ψ N ′ (R ′ )ψ n ′ 1 +n ′ 2 -N ′ (r ′ ), (32) ψ n 1 (r 1 )ψ n 2 (r 2 ) = n 1 +n 2 N =0 M n 1 n 2 N ψ N (R)ψ n 1 +n 2 -N (r), (33) for R ′ = r ′ 1 +r ′ 2 √ 2 , r ′ = r ′ 1 -r ′ 2 √ 2 , R = r 1 +r 2 √ 2 , and r = r 1 -r 2 √ 2.
Finite-range separable terms The separable pairing force in the isovector 1 S 0 channel, introduced by Tian et al. in the spherical case  [59]  and by Nikšić et al. in the 3D deformed case  [60, 61] , is implemented in version (v3. 06h) of the code hfodd. The general expression of this interaction in the 3D Cartesian coordinates is V S (r ′ 1 r ′ 2 ; r 1 r 2 ) = W 1σ 1τ + B1 τ P σ -H1 σ P τ -M P σ P τ × δ(R ′ -R)P (r ′ )P (r), (57) where formfactor P (r) is equal to a sum of Gaussians  (25) , P (r) = K k A k g a k (r), (58) and r ′ =r ′ 1 -r ′ 2 , r=r 1 -r 2 , R ′ = 1 2 (r ′ 1 + r ′ 2 ) , and R= 1 2 (r 1 + r 2 ) are the relative and center-of-mass coordinates. To avoid redundancy with coupling constants W , B, H, and M, one should use normalisation k A k = 1. A detailed derivation of the matrix elements of the separable generators in zero order can be found in  [62]  and references therein.
Multi-quasiparticle blocking The quasiparticle blocking was initially introduced in version (v2. 40h) of the hfodd code (see VI) to allow for the description of odd-A or odd-odd paired nuclei. It consists in looking for a solution of the HFB equations with as ansatz a vacuum |Φ onto which a single-quasiparticle excitation β † k is applied, |Φ k = β † k |Φ. Specifically, at each iteration, the code selects the quasiparticle state k in the matrix ϕ and exchanges its upper (B * ) and lower (A * ) components with those (A, B) of its partner of opposite quasiparticle energy, see Eqs. (VI-83)-(VI-86)  [6]. According to the option requested by the user, see keywords BLOCKFIX_N or BLOCKFIX_P in Section VI-3. 3  [6] , the blocked quasiparticle k may be kept the same throughout the calculation, or selected at each iteration as the one having the maximum overlap with a single-particle state (or its time-reversed image) chosen beforehand.
Pfaffian overlaps Computation of the overlap kernels between HFB wave functions is of crucial importance in multi-reference calculations and for symmetry restoration. Up to recently, such scalar products were most often evaluated using the Onishi formula  [65] , which suffers from a sign ambiguity due to a square-root appearing there. This limitation was then overcome by Robledo via a new expression involving a Pfaffian  [66]. Version (v3. 06h) of the code hfodd includes a new module, based on an equivalent Pfaffian formulation derived in Ref. [67] , which allows for determining the overlap between two arbitrary, potentially blocked HFB states of the general form  (59)  as Φ k |Φ ′ k ′ = (-1) M (M -1)/2 (-1) r(r-1)/2 pf      B T A B T p † B T q ′T B T B ′ * -p * B q * p † q * q ′T q * B ′ * -q ′ B -q ′ q † p ′ q ′T p ′ B ′ * -B ′ † B -B ′ † q † -B ′ † p ′T A ′ † B ′ *     .
Particle-number and parity symmetry restoration The HFB method accounts for pairing correlations through the breaking of the U(1) symmetry associated with particle-number conservation. The above computation of overlaps allows us to implement the restoration of correct proton and neutron numbers by projection after variation of a symmetry-unrestricted HFB state |Φ  [68]. In version (v3. 06h) of the code hfodd, projections on the total particle number A and isospin projection T z = (N -Z)/2 were implemented by introducing two new independent keywords. Activating only one of those projections thus allows for a full particle-numbersymmetry restoration for nuclei where one of the species, protons or neutrons, are unpaired in |Φ. In future releases, this implementation will be optimised by considering a 1D gauge-angle integration that allows for the simultaneous restoration of both protonand neutron-number symmetries, according to the methodology presented in Ref.
[15]  and routinely used in other implementations, see, e. g. , Ref. [69]. Version (v3. 06h) of the code hfodd also incorporates the parity restoration by means of the projector Pπ = (1 + π Π)/2 where π = ± and Π is the inversion transformation. Finally, a state with good quantum numbers A, T z , I π , M, and K is obtained as |AT z ; I π MK = PA PTz P I M K Pπ |Φ (62) = 2I + 1 16π 4 π 0 dφe -iφA π 0 dφ T e -iφ T Tz dΩD I * M K (Ω)e iφ Âe iφ T Tz R(Ω)(1 + π Π)|Φ. The operations detailed in Section VI-2. 1  [6]  for angular-momentum projection of Slater determinants were generalized to the HFB states. Quasiparticles φT , transformed by generic symmetry operators T that appear in Eq. (  62 ), read φT = T 0 0 T * B * A * = T B * T * A * , for φ = B * A * (63) characterizing state |Φ and T denoting representation of T in the single-particle basis.
Then, kernels of observables are computed according to the generalised Wick's theorem  [70]  in terms of the transition normal and pairing densities, and the overlap kernels are evaluated according to Eq. (  61 ). In version (v3. 06h) of the code hfodd, particle-number projection is realized by using the Gauss-Tchebyschev quadratures, whereas the discrete parity projector is applied explicitly. The numerical treatment of the integration over the Euler angles Ω was described in Section VI-2. 1  [6].
Axialization In version (v3. 06h) of the code hfodd, axial self-consistent solutions can be obtained by projecting wave functions on the axial shape, with the symmetry axis oriented along the z axis. This is achieved by projecting the particle-hole or pairing mean-field and/or particle-hole or pairing density matrix (pairing tensor) on those corresponding to the axial symmetry. Specifically, this is achieved by expanding the Cartesian harmonic-oscillator basis used by the code on states having good quantum numbers Ω k , which are the eigenvalues of the z component of the single-particle angular momentum. Then, at each iteration, only the matrix elements of the particle-hole matrices that are diagonal in Ω k are kept and/or only the off-diagonal (Ω k , -Ω k ) matrix elements of the pairing matrices are kept.
Wigner functions To perform the angular-momentum-and isospin-projection calculations, previously the code hfodd used the Wigner formula to compute the Wigner d functions, d j m,n (θ). For j ≥ 50, the Wigner formula is known to suffer from a loss of precision  [71] , which is due to the fact that with j >> 1 and θ = 0, π, it relies on a cancellation of very large terms with alternating signs. In Ref. [71] , a robust procedure of computing the d functions was proposed. In this method, the d functions were expended using the Fourier series. In Ref. [72] , another method was proposed, which was based on the diagonalization of the angular-momentum operator J y in the basis of eigenstates of J z. Version (v3. 06h) of the code hfodd, after implementing a few corrections, uses the code published in Ref.
Choice of the harmonic-oscillator basis To fix the HO basis used in the program (see Section II-4  [2] ) one needs to choose suitable oscillator constants b k or, equivalently, oscillator frequencies ω k or oscillator lengths, L k , in three Cartesian directions, b k = mω k , L k = mω k , for k = x, y, z. (64) There are many possible ways to determine b k or ω k. The methods implemented in version (v3. 06h) of the code hfodd are described below. They correspond to different values of variable INPOME set by using new functionalities of keyword FREQBASIS, see Section 3. 9, which are described below. (o) For the default value INPOME=0, the code uses values of the basis-deformation input parameters α 2µ to define surface Σ, Σ : R(θ, φ) = c(α) 1 + λµ α λµ Y * λµ (θ, φ) , (65) and then it determines mean squared values of positions r 2 k over the interior of Σ: R 2 k = r<R(θ,φ) r 2 k dV, k = x, y, z.