dataesr/scientific-paragraphs-categorization huggingface dataset:
001). Chemical equivalence and local symmetry restraints were applied on atoms with highest thermal motion (O1 ≈ O2, CH3 groups). The different structural and charge density parameters were refined iteratively till convergence. In order to ensure the neutrality of the molecule during the refinement, the electro-neutrality constraint was applied through the refinement. The correctness of the model was confirmed by the featureless residual density map which was generated by the VMoPro module. The bond-topological properties such as electron density, the Laplacian of the electron density, the bond ellipticity and the atomic charges were estimated by VMoPro. The variation of scale factor Σ(Fo 2 ) / Σ(Fc 2 ), with respect to resolution for the meloxicam sodium monohydrate molecule is given in Sup.
Theoretical Calculations On the basis of Kohn-Sham  [21, 22, 23]  wave-functions, the analysis of the molecule meloxicam sodium monohydrate had been done. The minimum energy structure and corresponding electronic wave functions of the molecule meloxicam sodium monohydrate had been obtained using the Kohn-Sham computations followed by geometry optimization incorporating the B3LYP/6-311G++(d,p)  [24, 25]  level of theory. The software GAUSSIAN09 package  [26]  was utilized for this purpose. The absence of imaginary frequencies confirmed that they correspond to real minima. The electronic wave functions had been generated from GAUSSIAN09 which served as the input for the AIMALL program  [27]  in order to explore the bond topological and electrostatic features at the bond critical point.
It is worth to point out that psammaplysene D (1) was isolated by normal phase MPLC as the major compound (6. 7 g) representing over 50% of the entire n-BuOH extract. striking similarities with the NMR data recorded for the co-isolated psammaplysene D (1), except for the absence of the signal corresponding to the propylamine group, as confirmed by the HRESIMS spectrum. In general, the 1 H NMR spectra of these families of compounds were complicated by the multiplicity of the signals due to the two rotational isomers trans/cis (6:4 ratio) along the amide bond  [21]. The same behavior was already reported for tetrabromotyrosine derivatives psammaplysene A-D, isolated from the sponges Psammaplysilla and Psammoclemma  [21] [22] [23] [24] [25]. 1 ) showed similarity between compounds 1 and 2, which was easily observed by superimposition of their spectra.
The A-B system of two downfield doublets of doublets at δ H 6. 49-6. 52/6. 56-6. 58 (J = 12. 5 Hz, cis) and δ H 6. 13-6. 16/6. 09-6. 12 (J = 12. 5 Hz) were assigned to -CH-7=CH-8 of the cinnamoyl moiety with a Z configuration. Furthermore, the COSY, HSQC, and HMBC analysis data (Figure  2 ) showed the same correlations as previously found for 2. Thus, the tetrabrominated tyrosine 3 was assigned to psammaplysene G. reported in the literature. It is worth to point out that psammaplysene D (1) was isolated by normal phase MPLC as the major compound (6. 7 g) representing over 50% of the entire n-BuOH extract. The molecular formula C23H27 79 Br2 81 Br2N2O3 of compound 2 was determined by HRESIMS (m/z 698. 8675 [M + H] + ) indicating ten degrees of unsaturation. The isotopic pattern of the protonated molecule confirmed the presence of four bromines.
Analysis of the NMR data recorded for 2 revealed striking similarities with the NMR data recorded for the co-isolated psammaplysene D (1), except for the absence of the signal corresponding to the propylamine group, as confirmed by the HRESIMS spectrum. In general, the 1 H NMR spectra of these families of compounds were complicated by the multiplicity of the signals due to the two rotational isomers trans/cis (6:4 ratio) along the amide bond  [21]. The same behavior was already reported for tetrabromotyrosine derivatives psammaplysene A-D, isolated from the sponges Psammaplysilla and Psammoclemma  [21] [22] [23] [24] [25]. The 1D and 2D NMR analysis revealed the existence of four aromatic protons comprising two singlets at δH 7. 78 and 7. 70, assigned to H-3/5, and another broad singlet at δH 7.
These NMR and mass data showed that compound 7 has one methyl group less than compound 6. Examination of the 1 H NMR and HSQC spectra (Table  3 ) displayed signals with similar chemical shifts to those reported for the tetrabromotyrosine compounds anomoians A and B, previously isolated from Anomoianthella popeae  [26]  (order: Verongiida) and from an unknown species of the genus Hexadella (order: Verongiida) collected in Indonesia  [27]. 2D NMR analysis including COSY, HSQC, and HMBC (Table  3 , Figure  4 ), allowed identification of the structures of 6 and 7 as the O-demethyl anomoian B and O-demethyl anomoian A, respectively. Thus, the new compounds were named anomoian C (6) and anomoian D  (7). Compound 8 had a protonated molecular ion at m/z 815. 0068 [M + H] + corresponding to the molecular formula C29H43 79 Br2 81 Br2N4O3, determined by HRESIMS.
Kinetic Study The inhibition mode of psammaplysene D on AChE was determined while measuring the enzyme activity in presence of an increasing concentration of ATCI (0. 024, 0. 049, 0. 098, 0. 19, 0. 39, 0. 78, 1. 57, and 3. 15 µM), in absence or presence of 2 µg/mL final concentration of purified psammaplysene D. The inhibition mode, V max , and K M values were determined by double-reciprocal Lineweaver and Burk plot analysis (1934) of the data obtained. 3. 5. 2. Guppy Bioassay 5 to 8 cm long guppies (Poecilia reticulata) were collected at night in a private fresh water pool at Papara (Tahiti, French Polynesia) and immediately acclimated at the laboratory temperature (25 • C). After acclimatization, fishes were parted in two 2 L tanks: one for the control group treated with solvent (N = 5).
The molecular formula C 23 H 27 79 Br 2 81 Br 2 N 2 O 3 of compound 2 was determined by HRESIMS (m/z 698. 8675 [M + H] + ) indicating ten degrees of unsaturation. The isotopic pattern of the protonated molecule confirmed the presence of four bromines. Analysis of the NMR data recorded for 2 revealed.
Acknowledgments: We thank the  French Polynesian authorities , as well as the communities, for allowing us to collect in Marquesas Islands. Financial support from  CNRS-ICSN, IRD  for the collecting trip aboard  R/V Alis ,  French and French Polynesian governments for the Marquesas and Biopolyval projects, ANR  ( POMARE  project,  2011-EBIM-006-01 ), as well as project  TASCMAR  which is funded by the  European Union  under grant agreement number  634674. Labex MER and Labex CORAIL , are gratefully acknowledged. Amr El-Demerdash 's PhD was granted and financed by the  Egyptian Government  ( Egyptian Cultural Bureau in Paris, Ministry of Higher Education ), they are gratefully acknowledged. We thank  IRD 's diving team (SEOH  IRD Noumea, New Caledonia ) and the R/V crew for their on-field help,  O.
2 kV) in the discharge stack, many collisions with electrons, atoms, and precursor molecules and its fragments occur prior to adiabatic expansion, yielding a rich broth of familiar and exotic molecules. As the gas reaches the beam waist of the cavity, a pulse of resonant microwave radiation polarizes the plasma. The resulting free-induction decay is detected with a sensitive microwave receiver, the Fourier-transform of which yields the frequency spectrum. Powerful and flexible in-house software is used to control, optimize, and acquire data in the 5-40 GHz frequency range of this spectrometer. For isotopic measurements, isotopically-enriched precursors gases such as D 2 S, DCCD, H 13 C 13 CH, etc. , were used instead of the normal sample at the same level of dilution. Once candidate a-type lines of HCCSH were identified, subsequent high-frequency, b-type transitions were sought using double resonance, since these lines are predicted to lie well above the frequency ceiling of the microwave cavity.
Determination of the spectroscopic parameters Spectroscopic parameters were determined using the SPFIT/SPCAT suite of programs. 39 ing to the highly prolate character of HCCSH (κ = -0. 999) and the similar magnitudes *VIUYIRG]1,^ )\TIVMQIRX 7MQYPEXMSR 0 1,^ 22 1, 21 22 0, 22 0 1,F igure 5: Left: Stick representation of the experimental observations (top) and a 300 K simulation (bottom) of the rotational spectrum of HCCSH. The simulated spectrum was calculated using the experimental constants presented in Table  2. Right: Representative trace of the millimeter-wave absorption spectrum; the abscissa indicates the center frequency of the transition. of B and C, a Watson-S Hamiltonian in the I r representation was employed. For the main isotopic species, a total of 9 free parameters were required to reproduce the available data to an RMS of 46 kHz (Table  2 ).
Astronomical implications Because there is very strong evidence the SH + CCH reaction is responsible for HCCSH in our discharge nozzle, and because the HEAT345(Q) energetics confirm this reaction is highly exothermic (-477 kJ/mol), it is conceivable this metastable isomer might form preferentially in the interstellar medium, especially so since both the SH and CCH radicals are widely abundant and widely distributed there. [52]  With the spectroscopic constants listed in Table  2 , it is possible to predict the astronomically most interesting lines over the entire range of interest to radio astronomers. Of particular importance is the strong b-type lines, which can now be predicted to better than 0. 1 km sec -1 in terms of equivalent radio velocity up to 800 GHz. Using the experimental data, we are performing preliminary interstellar searches based on ALMA observations towards star-forming regions, as well as archival and publicly available datasets from the Green Bank Telescope and Herschel Space Telescope.
Acknowledgements We thank  Edward Tong  of the  Submillimeter Array Receiver laboratory at the Smithsonian Astrophysical Observatory  for the loan of a high-power, high-frequency VDI AMC that was used for the 300 GHz DR measurements. The work in Cambridge is supported by  NSF   AST-1615847  and the work in Orsay by the  Programme National "Physique et Chimie du Milieu Interstellaire" (PCMI)  of  CNRS/INSU  with  INC/INP  co-funded by  CEA  and  CNES , and by  "Investissements d'Avenir" LabEx PALM  ( ANR-10-LABX-0039-PALM ). Support for B. A. M. was provided by  NASA  through  Hubble Fellowship grant  # HST-HF2-51396  awarded by the  Space Telescope Science Institute , which is operated by the  Association of Universities for Research in Astronomy, Inc. , for  NASA , under contract  NAS5-6555.
Brief description of the codes This section describes briefly the different codes contributing to this case study (termed case 14). Five codes were involved: two simulation methods and three models. The simulation codes are LSNS and SimU. LSNS involves a numerical integration of the time-dependent Schrödinger equation for the hydrogen wave function under the influence of a fluctuating electric field obtained from a particle simulation. More details can be found in  [3]  and references therein. SimU is well described in  [4] [5]. The three models are PPP  [6] , QC_FFM (  [7]  and the references therein) and ZEST. Since ZEST (ZEeman-STark) line-shape code has been improved and upgraded to a new version  [8] , we describe here the version that has been used for the calculations reported in this paper.
H-β line profiles for the highest density Similarly, the results of the code calculations for the higher density case (ne=10 16 cm -3 ) and the same temperatures as in the previous subsection are respectively illustrated in Figures  4 5 6. For this density, the expected discrepancy between the calculations carried out by the PPP code using the GBK collision operator and those of the other codes are more pronounced confirming the non-validity of this form of this operator at high densities and low temperatures even though it tends to disappear with increasing temperatures. One can see that for the remaining calculations, SimU agrees well with QC_FFM on the one side and ZEST agrees well with LSNS on the other side. Note that the profiles calculated by LSNS and ZEST are a bit broader than those calculated by SimU and QC_FFM.
Electric microfield distributions To be complete in the code comparisons and for a better understanding of the differences between the calculated profiles, we present on Figure  10  for the lowest density ne=10 15 cm -3, the field distribution used by the codes except QC_FFM. One can see no difference between the distributions calculated by LSNS, PPP and ZEST. As SimU simulates both electrons and ions providing the total electric field, it is normal that its field distribution shown is broader and shifted towards higher field values. For the other codes, the field distributions shown here are for ions only.
Hemispheric asymmetry is a cardinal feature of human brain organization. Altered brain asymmetry has also been linked to some cognitive and neuropsychiatric disorders. Here, the ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) Consortium presents the largest-ever analysis of cerebral cortical asymmetry and its variability across individuals. Cortical thickness and surface area were assessed in MRI scans of 17,141 healthy individuals from 99 datasets worldwide. Results revealed widespread asymmetries at both hemispheric and regional levels, with a generally thicker cortex but smaller surface area in the left hemisphere relative to the right. Regionally, asymmetries of cortical thickness and/or surface area were found in the inferior frontal gyrus, transverse temporal gyrus, parahippocampal gyrus, and entorhinal cortex.
These regions are involved in lateralized functions, including language and visuospatial processing. In addition to population-level asymmetries, variability in brain asymmetry was related to sex, age, and intracranial volume. Interestingly, we did not find significant associations between asymmetries and handedness. Finally, with two independent pedigree datasets (n = 1,443 and 1,113, respectively), we found several asymmetries showing significant, replicable heritability. The structural asymmetries identified and their variabilities and heritability provide a reference resource for future studies on the genetic basis of brain asymmetry and altered laterality in cognitive, neurological, and psychiatric disorders. brain asymmetry | lateralization | cortical thickness | surface area | meta-analysis U nderstanding the functional specialization of the cerebral hemispheres is a long-standing and central issue in human neuroscience research.
The ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) Consortium provides the opportunity for largescale meta-analysis studies of brain anatomy based on tens of thousands of participants with structural MRI data  (51). We used a "meta-analysis" model, for which it was not necessary to send individual data out of the laboratories where they were collected. This helped to maximize participation and therefore the overall sample size. In this study, we present the largest analysis of structural asymmetries in the human cerebral cortex, with MRI scans of 17,141 healthy individuals from 99 datasets worldwide, in a harmonized multisite study using meta-analytic methods. Our aim was to identify cortical regions that consistently show asymmetry with regard to either cortical thickness or surface area, to provide a clear picture of population-level asymmetries in the human brain.
We also assessed potential influences of age, sex, handedness, and brain size (indexed by intracranial volume; ICV) on the variability in asymmetries, as well as of the methodological factor of MRI scanner field strength. Furthermore, as a first step toward elucidating the genetic basis of variability in brain asymmetry, we further analyzed two independent pedigree datasets, i. e. , the Genetics of Brain Structure (GOBS; n = 1,443) and Human Connectome Project (HCP; n = 1,113) datasets, to estimate heritability of the asymmetry measures.
Results Ninety-nine independent datasets were contributed by members of the Lateralization Working Group within the ENIGMA Consortium  (51) , including data from 17,141 individuals from population or healthy control cohorts. Fig. 1  summarizes the sample sizes and age ranges of each dataset (for more details, see Dataset S1). Meta-Analysis of Population-Level Asymmetry. Meta-analysis of population-level asymmetry revealed widely distributed asymmetries in both cortical thickness and surface area. Specifically, we found global differences between the two hemispheres, with generally thicker cortex in the left hemisphere (b = 0. 13, Z = 3. 64, P = 0. 00040; Fig. 2 ), but larger surface area in the right hemisphere (b = -0. 33, Z = -11. 30, P = 1. 36e-29; Fig. 3 ). Substantial, regionally specific differences between the two hemispheres were also observed for both cortical thickness and surface area.
In terms of cortical thickness, 76. 5% (26/34) of the regions showed significant asymmetry, after correcting for multiple comparisons (P < 0. 05, Bonferroni corrected). Specifically, regions showing significant leftward asymmetry (i. e. , left > right) of cortical thickness were identified in the anterior cortex, including the lateral, dorsal, and medial frontal cortex, the primary sensory, superior parietal, cingulate, and medial temporal cortices (Fig. 4  and Dataset S2). In contrast, rightward asymmetry (i. e. , right > left) was prominent in the posterior regions, including lateral and medial parts of the temporal, parietal, and occipital cortices. This fronto-occipital asymmetry pattern in cortical thickness is striking (Fig. 4 ) and may also relate to the petalia and Yakovlevian torque effects described above (Discussion).
In addition, three temporal regions (especially the inferior temporal and fusiform gyri) showed a trend of rightward asymmetry as defined by uncorrected P < 0. 05 (inferior temporal: b = -0. 11, Z = -2. 92, uncorrected P = 0. 0035; fusiform: b = -0. 09, Z = -2. 64, uncorrected P = 0. 0082; middle temporal: b = -0. 10, Z = -2. 19, uncorrected P = 0. 029). Similarly, 91. 1% (31/34) of the regions showed significant asymmetries of their surface areas after correcting for multiple comparisons (P < 0. 05, Bonferroni corrected). However, unlike thicknesses, the surface area asymmetries showed no obvious leftward or rightward patterns involving neighboring areas or generally along the fronto-occipital axis (Fig. 5  and Dataset S2). Two language-related regions showed the largest leftward asymmetries of surface area, which were the opercular part of the inferior frontal gyrus (posterior part of the Broca's area) and the transverse temporal gyri (Heschl's gyri).
In contrast, however, another two language-related regions, i. e. , the triangular part of the inferior frontal gyrus (anterior part of the Broca's area) and the inferior parietal gyrus, showed strong rightward asymmetries of surface area. These findings suggest that opposite asymmetries in morphology of regions within a given network (i. e. , language network), or within one functional area (the Broca's area), might be linked to different roles of each constituent part (Discussion). Effect sizes of cortical thickness and surface area were found to be independent, as illustrated by the absence of a significant correlation between thickness and surface area asymmetries across all cortical regions (r = -0. 14, P = 0. 416). Moderator Analyses Using Metaregression. As shown above, we observed moderate to substantial heterogeneity in the asymmetry distributions across datasets.
80, P = 0. 0052). Regionally specific effects of sex on surface area asymmetry were also revealed (Fig. 6 ), located in the frontal (superior frontal gyrus, the pars orbitalis region of the left inferior frontal gyrus), temporal (superior temporal gyrus, temporal pole, parahippocampal gyrus, and fusiform gyrus), parietal (inferior parietal gyrus and supramarginal gyrus), and anterior cingulate cortices. In addition, various other regions showed nominally significant sex effects (uncorrected P < 0. 05) without surviving correction for multiple comparisons. More information can be seen in Dataset S3.
Meta-Analysis of Age Effects on Cortical Asymmetries. An initial analysis of samples with an age range of >5 y showed no significant effects of age on global asymmetries of either cortical thickness or surface area (P > 0. 10). Several regionally specific, nominally significant effects were found: the superior temporal gyrus (cortical thickness: Z = 2. 38, P = 0. 017), the banks of superior temporal sulcus (surface area: Z = -1. 97, P = 0. 049), and the entorhinal cortex (surface area: Z = 2. 84, P = 0. 0045). However, when restricting the analysis to only those datasets with wider age ranges (at least 20-y range), we observed significant age effects. Specifically, increasing age was associated with more pronounced leftward overall asymmetry in cortical thickness (Z = 2. 65, P = 0. 0081), which partly reflects a similar age effect on the thickness asymmetry of the superior temporal gyrus (Z = 3.
17, P = 0. 0015; Fig. 6 ). In addition, a similar effect on regional surface area asymmetry was observed in the entorhinal cortex (Z = 3. 21, P = 0. 0013). An age effect on surface area asymmetry of the banks of the superior temporal sulcus was nominally significant (Z = -1. 96, P = 0. 050). More information can be found in Dataset S4.
Meta-Analysis of Group Differences by Handedness on Cortical Asymmetries. We did not find significant associations of handedness with cortical asymmetries, even with this unprecedented sample size (555-608 left-handers vs. 6,222-7,243 right-handers from 11-14 datasets, depending on the specific regional asymmetry measure). Given the considerable preponderance of righthanders in most datasets, which might complicate the estimation of handedness effects, we further confirmed these findings within one of the datasets (i. e. , BIL&GIN) which was roughly balanced for handedness (right: n = 248; left: n = 205). In the metaanalysis, several temporal regional surface area asymmetries showed nominally significant associations with handedness, including the fusiform gyrus: Z = 2. 00, P = 0. 046; the parahippocampal gyrus: Z = -2.
33, P = 0. 020; and the superior temporal gyrus: Z = -2. 04, P = 0. 042. More information can be found in Dataset S5. Meta-Analysis of ICV Effects on Cortical Asymmetry. ICV showed a significant positive effect (i. e. , increased leftward asymmetry) on the overall asymmetry in cortical thickness (Z = 2. 14, P = 0. 032). Similar regionally specific effects on cortical thickness asymmetry were found for the inferior parietal gyrus (Z = 4. 51, P = 6. 53e-6) and insula (Z = 3. 71, P = 0. 00021). A negative effect of greater ICV (i. e. , decreased leftward asymmetry) was seen in the rostral anterior cingulate gyrus (Z = -5. 23, P = 1. 68e-7) (Fig. 6 ). No significant effect of ICV was found for the overall asymmetry in surface area (P > 0. 10), but a number of regionally specific effects were revealed (in different directions).
Positive effects of greater ICV (i. e. , increased leftward/decreased rightward asymmetry)  were observed in the medial orbitofrontal gyrus (Z = 4. 17, P = 3. 10e-5), two anterior cingulate gyri (caudal: Z = 5. 71, P = 1. 10e-8; rostral: Z = 5. 67, P = 1. 45e-8), and the isthmus cingulate gyrus (Z = 4. 32, P = 1. 59e-5) (Fig. 6 ). In addition, negative effects of greater ICV (i. e. , increased rightward/decreased leftward asymmetry) were seen for the superior frontal gyrus (Z = -6. 58, P = 4. 82e-11), the caudal middle frontal gyrus (Z = -3. 65, P = 0. 00026), the paracentral gyrus (Z = -5. 19, P = 2. 11e-7), the insula (Z = -5. 92, P = 3. 13e-9), the posterior cingulate gyrus (Z = -3. 24, P = 0. 0012), and the cuneus (Z = -4. 49, P = 7. 12e-6) (Fig. 6 ). More information can be seen in Dataset S6.