dataesr/scientific-paragraphs-categorization huggingface dataset:
The A. fulva complex is a challenging group with several closely related, but well-separated species, distributed globally (Fig. 2 ). Habitat and distribution: Associated with Pinus sylvestris on acidic soil and with P. nigra on calcareous soil. Distribution is currently uncertain due to the confusion with A. fulva. Currently known from Europe (France and Hungary -own collections and one GenBank entry: MH508370) and United States (Pennsylvania, Indiana, Massachusetts and Virginia according to ITS sequence data from GenBank entries: JX860436, KP284293, MK522007, MK522008, MZ668288, ON392627, ON243897, OR026696). Comments this taxon is recognizable by its reminiscent of that of Amanita fulva habitus, by the variable colour of the pileus, by the particular colour of the inner and the upper outer surfaces of the volva.
and Carpinus betulus, but possibly also with Betula pendula. One sequence-veri ed record is originated under Pinus nigra as host tree (GenBank: OQ327043). Known from France, Germany, Greenland (UNITE: UDB002307), Hungary, and the United Kingdom (Andy Overall, pers. comm. ), but with several records, thus it can potentially be more widespread in Europe. Comments: Amanita opaca is one of the many rather anonymous greyish, greyish-brown 'vaginata' species occurring in thermophilous woodlands of Europe. Currently, morphological differentiation towards other similar species is often di cult. The closely related A. coryli has whitish volva, less robust habit, an always strictly vaginate volva and smaller basidiospores (Figs. [12] [13] [14]. The recently described A. prudens  (Plaza 2022 ) has a rst hemispherical pileus with a moiré aspect, somewhat more or less iridescent.
Amanita sect. Vaginatae in Hungary and the bene t of national data to improve diversity knowledge Despite their taxonomically challenging nature and their widespread occurrence in Hungary, little local data of species within the section Vaginatae were available, and no study on their taxonomy and phylogenetics was carried out before our work. These species are found in many habitats throughout the country, especially in hilly and mountainous forests dominated by tree species belong to the genera Fagus, Quercus, Carpinus, Betula, Pinus and Picea. Based on morphological identi cation, 15 taxa were documented from Hungary: Amanita argentea, A. battarrae, A. umbrinolutea, A. beckeri, A. ceciliae, A. crocea, A. dryophila, A. friabilis, A. fulva, A. lividopallescens, A. lividopallescens var. tigrina, A.
Acknowledgements The work was supported by the  National Research, Development and Innovation O ce of Hungary  ( OTKA FK-143061 ) and the  ELTE Institutional Excellence Program 2020  ( TKP2020-IKA-05 ) and Diagnostics and Therapy 2 nanced by the  National Research, Development and Innovation O ce of Hungary. Bálint Dima  is grateful to the  János Bolyai Research Scholarship  of the  Hungarian Academy of Sciences. We thank to  Csilla Gergely  for her assistance in lab work. We are grateful to many researchers and amateur mycologists for providing us invaluable specimens, photos and eld notes:  László Albert ,  Katalin Gáborné Békés ,  Egil Bendiksen ,  André Bidaud ,  Gyula Bodó ,  Lajos Boros ,  Valéria Borsi ,  Tor Erik Brandrud ,  Gilles Corriol ,  Katalin Erdélyi Császárné ,  Francesco Dovana ,  Ica Fedor ,  Péter Finy ,  Denis Lucas ,  Gabriella Mokánszki ,  Edit Molnár ,  Jean-Luc Muller ,  Angelina Nagy ,  Gábor Pelles ,  Péter Orbán ,  István Ölvedi ,  Serge Rousset ,  István Sárközi ,  Edit Szilvásy ,  Béla Szűcs ,  Zsanett Tusnády ,  László Vajda ,  Gyula Vidra ,  György Vrba ,  Márk Wabrosch.
Taxonomy Amanita de exa Hanss, Dima & L. Albert, sp. nov. , Fig. 3a-c, Fig. 4a-b, Fig. 5a MycoBank: MB#846787 Holotype France, Haut-Rhin, la Gauchmatt, Soulzmatt, in a Pinus nigra forest, J. -L. Muller, 1 Sept 2014, LIP 0004489 (isotype JMH2019039 in herb. J. -M. Hanss); GenBank XY123456 (ITS).
Additional collections examinedFrance, Haut-Rhin, la Gauchmatt, Soulzmatt, under Pinus nigra, 29 Oct 2019, J. -L. Muller, JMH2019039 (herb. J. -M. Hanss); Vienne, Chavigny, Forêt de Mareuil, 26 Oct 2022, Y. Bellanger, JMH2022008 (herb. J. -M. Hanss). Hungary, Vas County, Őrség, Orfalu, "Blueberry Trail", 3 Oct 2022, L. Albert, B. Dima, DB-2020-10-03-1 (ELTE) (AD52). Amanita griseofulva Hanss, P. -A. Moreau, Dima & D. Varga, sp. nov. , Figs. 3d-i, 4c-d, 5b MycoBank: MB#846788 Holotype France, Mayenne, forêt d'Ombrée-d'Anjou-Combrée, under Betula pendula and Quercus petraea on oligotrophic soil with Pteridium aquilinum, A. Gasch & P. -A. Moreau, 21 Aug 2021, LIP 0404490 (ex PAM21081109); GenBank XY123456 (ITS).
MycoBank -Abaúj-Zemplén County, Zemplén Mts, Újhuta, under Quercus petraea, Pinus sylvestris, Carpinus betulus and Betula pendula, A. Nagy, B. Szűcs, B. Dima, 31 July 2021, DB-2021-07-31-2 (BP) (AD115); GenBank XY123456 (ITS). Etymology the epithet albida refers to the white basidiomata of this form. Diagnosis Differs from typical Amanita griseofulva by an entirely white pileus. Comments Genetically this apigmented form of A. griseofulva shows no difference from the sequences of the typical form and the two collections studied are nested within the A. griseofulva clade. Additional collections examined Borsod-Abaúj-Zemplén County, Zemplén Mts, Újhuta, in mixed forest, K. Gábor Békésné, 31 July 2021, DB-2021-07-31-3 (ELTE) (AD117). Amanita opaca Hanss, Dima, Bidaud & D. Varga, sp. nov. , Fig.
4e-f, Fig. 5c, Fig. 6 MycoBank: MB#846789 Holotype France, Ain, Marchamp, locality "le Moyeux", alt. 800 m, under Quercus pubescens and Carpinus betulus on calcareous soil, A. Bidaud, 12 Aug. 2011, LIP 0004500 (isotype AB11-08-60 in herb. A. Bidaud); GenBank XY123456 (ITS).
Nagy, B. Dima, 27 Sept 2020, DB-2020-09-27-3 (ELTE) (AD51); Borsod-Abaúj-Zemplén County, Rudabánya Mts, Zubogy, under Quercus petraea and Carpinus betulus, I. Fedor, 7 July 2018, DB-2018-07-07-7 (ELTE) (AD23); Pest County, Buda Mts, Budakeszi, Hidegvölgy, under Quercus cerris and Q. petraea, A. Nagy, B. Dima, 28 Jun 2020, DB-2020-06-28-8 (ELTE) (AD86); Heves County, Mátra Mts, Szuha, under Betula pendula, Populus tremula and Carpinus betulus, A. Nagy, B. Dima, 2 Aug 2020, DB-2020-08-02-3 (ELTE) (AD39). Amanita opaca f. cettoi Hanss & Dima, f. nov. , Figs. 6h-i MycoBank: MB#846790 Holotype France, Doubs, Laviron, in a mixed forest on calcareous soil, S. Rousset, 05 Oct 2016, LIP 0004499 (isotype JMH2016027 in herb. J. -M. Hanss); GenBank MN493559 (ITS, as 'A. supravolvata').
2018)  or is rapidly erased through dynamical interactions of the stars and expulsion of the gas  (Parker & Meyer 2012; Fujii & Portegies Zwart 2016). A dozen studies have investigated the mass segregation of 0. 002-0. 1 pc cloud structures, but only five found clear evidence of segregation  (Lane et al. 2016; Parker 2018; Plunkett et al. 2018; Dib & Henning 2019; Nony et al. 2021). Dib & Henning (2019)  and  Nony et al. (2021)  proposed that the level of core mass segregation depends on how the gas mass is assembled to form the molecular clouds. Environmental factors could therefore have an impact on both core mass segregation and CMF shape. The paper is organized as follows: in Sect. 2 we present the database used in this work, separate the W43-MM2&MM3 into six subregions, compute their column density maps, and estimate their characteristics, such as mass, volume density, and column density PDF.
Observations and core catalog The W43-MM2&MM3 mini-starburst ridge is among the targets of the ALMA-IMF Large Program (Paper I,  Motte et al. 2022) , whose observations were taken between December 2017 and December 2018. The present paper uses the 12 m array continuum images in the ALMA band 6 (1. 3 mm, central frequency ν c ≃ 228. 4 GHz) and band 3 (3 mm, ν c ≃ 99. 66 GHz) and the core catalog 2  all reported in Paper III  (Pouteau et al. 2022). Images of individual ALMA-IMF fields W43-MM2 and W43-MM3 were first cleaned using the iterative self-calibration pipeline scripts 3  developed by the ALMA-IMF consortium and fully described in Paper II  (Ginsburg et al. 2022). Paper III  (Pouteau et al. 2022 ) used the multi-scale option of the TCLEAN task, with parameters of 0, 3, 9, 27 pixels (up to 81 at 3 mm), to minimize interferometric artifacts associated with missing short spacings.
This first-order correction probably overestimates, by up to ∼0. 15 × 10 23 cm -2 , the column density values in low-density subregions such as Outskirts and MM51, and underestimates it, by up to ∼0. 3 × 10 23 cm -2 , in centrally concentrated subregions such as MM2 and MM3. We therefore assumed a different background column density for each subregion: N = (1. 0 ± 0. 2) × 10 23 cm -2 for MM2 and MM3. Future studies will be performed on maps combining present ALMA 12 m array data with ALMA-IMF data of the 7 m array and total power antennas. Their reduction and combination is not simple but the ALMA-IMF consortium is working on it  (Ginsburg et al. 2022; Cunningham et al. 2023). Figure  1  presents the resulting column density image of the W43-MM2&MM3 ridge, with N H 2 values varying from ∼1×10 22 cm -2 , in region where missing large-scale emission creates interferometric artifacts consisting of negative bowls, to ∼2.
Summary and conclusions We have used the most complete and most robust sample of cores obtained to date as part of the ALMA-IMF Large Program to study the dependence of the CMF on the cloud and protocluster properties. Our main results and conclusions can be summarized as follows. -We used a database consisting of the 1. 3 mm continuum image and core catalog produced by Paper III  (Pouteau et al. 2022)  for the W43-MM2&MM3 mini-starburst ridge. The ALMA image covers the ∼10 pc 2 cloud and hosts a cluster of 205 cores with sizes of ∼3400 au and masses ranging from 0. 1 M ⊙ to 70 M ⊙ (see Sect. 2. 1 and Fig. 1 ). The pre-stellar versus protostellar nature of cores is taken from Paper V  (Nony et al. 2023)  to estimate the protostellar fraction. -Using the MnGSeg technique, we separated the W43-MM2&MM3 ridge into six subregions that are expected to simultaneously form stellar clusters.
Acknowledgements. This paper makes use of the ALMA data ADS/JAO. ALMA# 2017. 1. 01355. L. ALMA is a partnership of  ESO  (representing its member states),  NSF (USA)  and  NINS (Japan) , together with  NRC (Canada) ,  MOST  and  ASIAA (Taiwan) , and  KASI (Republic of Korea) , in cooperation with the  Republic of Chile. The  Joint ALMA Observatory  is operated by  ESO ,  AUI/NRAO  and  NAOJ. This project has received funding from the  European Research Council (ERC)  via the  ERC Synergy Grant ECOGAL  (grant  855130 ), from the  French Agence Nationale de la Recherche (ANR)  through the project  COSMHIC  ( ANR-20-CE31-0009 ), and the  French Programme National de Physique Stellaire and Physique et Chimie du Milieu Interstellaire (PNPS and PCMI)  of  CNRS/INSU  (with  INC/INP/IN2P3). Y. P. acknowledges funding from the  IDEX Université Grenoble Alpes  under the  Initiatives de Recherche Stratégiques (IRS)  " Origine de la Masse des Étoiles dans notre Galaxie " (OMEGa).
Y. P. , B. L. and G. B. acknowledge funding from the  European Research Council (ERC)  under the European Union's  Horizon 2020 research and innovation programme , for the  Project "The Dawn of Organic Chemistry" (DOC) , grant agreement No  741002. G. B. also acknowledges funding from the  State Agency for Research (AEI)  of the  Spanish MCIU  through the  AYA2017-84390-C2-2-R  grant and from the  PID2020-117710GB-I00  grant funded by  MCIN/AEI/10. 13039/501100011033. R. G. M. , T. N. , and D. D. G. acknowledge support from  UNAM-PAPIIT  project  IN108822. R. G. M. is also supported by  CONACyT Ciencia de Frontera  project  ID 86372. T. N. acknowledges support from the postdoctoral fellowship program of the  UNAM. A. Gi acknowledges support from the  National Science Foundation  under grant No.
2008101. T. Cs and M. B. have received financial support from the  French State  in the framework of the  IdEx Université de Bordeaux Investments  for the future Program. P. S. was supported by a  Grant-in-Aid for Scientific Research (KAKENHI  Number  18H01259 ) of the  Japan Society for the Promotion of Science (JSPS). P. S. and H. -L. L. gratefully acknowledge the support from the  NAOJ   Visiting Fellow Program  to visit the  National Astronomical Observatory of Japan  in 2019, February. A. S. gratefully acknowledges funding support through  Fondecyt Regular  (project code  1180350 ), from the  ANID BASAL  project  FB210003 , and from the  Chilean Centro de Excelencia en Astrofísica y Tecnologías Afines (CATA)   BASAL  grant  AFB-170002. F. L. acknowledges the support of the  Marie Curie Action of the European Union  (project  MagiKStar , Grant agreement number  841276 ).
S. B. acknowledges support from the  French Agence Nationale de la Recherche (ANR)  through the project  GENESIS  ( ANR-16-CE92-0035-01 ). T. B. acknowledges the support from  S. N. Bose National Centre for Basic Sciences  under the  Department of Science and Technology, Govt. of India. L. B. gratefully acknowledges support by the  ANID BASAL  projects  ACE210002  and  FB210003. K. T. was supported by  JSPS KAKENHI  (Grant Number  20H05645 ).
Kinetics and Mechanisms of α-Glucosidase Inhibition Figure  3  shows the Lineweaver-Burk plots of α-glucosidase inhibition kinetics in the presence of various concentrations of substrate (p-nitrophenyl-α-D-glucopyranoside, PNPg) and of increasing concentrations of TOTUM-63 or acarbose. Analysis of these data with the SigmaPlot software 12 (Systat Software Inc. , San Jose, CA, USA) indicated a mixed inhibitory mechanism for TOTUM-63 and a competitive inhibitory mechanism for acarbose (as the main mechanisms, they obtained the best R² and Akaike Information Criterion corrected for small sample size, AICc values). As described for these mechanisms, the lines intersected to the left of the Y-axis and on the negative side of the X-axis for TOTUM-63, whereas they intersected on the Y-axis (X = 0) for acarbose.
The dissociation constant between a protein and a hypothetical ligand can be determined if an interaction occurs, as the temperature-induced behavior of the protein-ligand couple would differ from that of each free entity. The binding affinity of TOTUM-63 and acarbose for α-glucosidase was assessed using MST. We analyzed the results of the experiments with TOTUM-63 (i. e. , the ligand) using the Initial Fluorescence Analysis mode in the MO Affinity Analysis software (NanoTemper Technologies, Munich, Germany) because ligand binding directly led to a change in the initial fluorescence (ligand-induced fluorescence changes). We verified that the fluorescence changes recorded for α-glucosidase tagged with the fluorescent RED-NHS dye were ligand specific (TOTUM-63) and not due to any material loss.
α-Glucosidase Inhibition Kinetics α-glucosidase inhibition kinetics was investigated in vitro using the method described in Section 4. 2. 1. Inhibition models were determined by analysis of the Lineweaver-Burk plots using four concentrations of substrate and four concentrations of test products (including a "0", without inhibitor). All initial rates were fitted to all enzymatic kinetic models with one substrate and one inhibitor provided by the Enzyme Kinetics Module of Sigma Plot 12 (Systat Software Inc. , San Jose, California, USA), using non-linear least-square regression models to determine the inhibition model and calculate the inhibitory constant (Ki). The mechanism of α-glucosidase inhibition by TOTUM-63 was confirmed using Lineweaver-Burk plots (1/[S] against 1/v). The acarbose inhibition model was verified and compared with the literature to validate the obtained results  [86].
Equations (  2 ) and (3) (below) were used for data analysis and corresponded to the inhibition models that best fitted our data according to the SigmaPlot software 12 (Systat Software Inc. , San Jose, California, USA)  [73]. Equation (  2 ), for acarbose, corresponded to the competitive (full) inhibition mechanism where v corresponds to the reaction velocity (also called reaction rate), Vmax to the maximum reaction velocity, Km to the amount of substrate required to obtain half of the Vmax (also called Michaelis constant), Ki to the inhibitor dissociation constant, [S] to the substrate concentration, and [I] to the inhibitor concentration. Equation (3), for TOTUM-63, corresponded to the mixed (full) inhibition mechanism with a new factor, Ki', introduced compared with Equation (2). Ki' corresponds to the second inhibitor dissociation constant because, in a mixed model, the constants for E + I ↔ EI and ES + I ↔ ESI are different.
3125 g/L to 9. 5367 µg/L and from 10 g/L to 305. 1758 µg/L, respectively. Standard capillaries for red fluorescence emission recording were filled with a 1:1 (v/v) mixture of tagged enzyme and diluted ligand. Fluorescence was measured using the NanoTemper Monolith NT. 115 instrument (NanoTemper Technologies, Munich, Germany) at 37 °C, with a fluorescence excitation power of 80% and MST power set to Medium. Data were analyzed with the NanoTemper analysis software (NanoTemper Technologies, Munich, Germany).
Statistical Analysis of In Vivo Data Prism V. 7. 0 and 8. 0 (GraphPad Software, San Diego, CA, USA) and the SAS/STAT software V. 9. 4 (SAS Institute, Cary, NC, USA) were used for statistical analyses and figure drawing. For pair comparisons, the Shapiro-Wilk normality test was used to determine whether data followed a Gaussian distribution, and then the F-test (Fisher) was used to compare variances. If normal distribution was assumed and variances were homogenous, the unpaired t-test was used to compare groups. If variances were heterogenous, the unpaired t-test with Welch correction was used. If data were not consistent with a Gaussian distribution, the Mann-Whitney test was used. For measurements repeated over time, differences were tested using a repeated-measure two-way ANOVA followed by the Sidak post hoc test for multiple comparisons if the interaction was statistically significant.
Acknowledgments: The authors wish to thank  Mehdi Djelloul-Mazouz  ( UMR 1019 UNH, INRAE, Theix ),  Valérie Rousseau  ( UMR 0454 ,  UCA, Clermont-Ferrand ), and  Christophe De L'Homme  ( UMR 1019 UNH, INRAE, Theix ) for the care and the attention to the animals. We are also grateful to  Geoffrey Delcros  ( Valbiotis, Riom ),  Monique Etienne  ( AME2P ,  UCA, Clermont-Ferrand ),  Clara Laurent  ( Valbiotis, Riom ), and  Mahëva Maura  ( Valbiotis, La Rochelle ) for their technical skills in laboratory experiments. We thank  Odd-Erik Johansen  ( Nestlé Health Science, Vevey ) and  Elisabetta Andermarcher  for critical reading of the manuscript.
Sample size calculations Evidence from previous semi-eld studies suggests that insecticidal tube produces about 50% reduction in overnight mosquito survival  12, 13, 16, 17. Based on this, the number of release night required to detect a 50% reduction in survival with 80% power and signi cance level of 5% was determined for each treatment in the R software using the "pwr" package. Eight replicates of release-recapture were performed for each treatment, which according to the sample size calculation was above the number required to demonstrate the expected effect size. Insecticide susceptibility assays Insecticide susceptibility assays were performed to measure susceptibility to the constituent actives in the LLINs and pirimiphos methyl in the local An. gambiae mosquito population. Diagnostic concentration of the pyrethroids deltamethrin (0.
Data analysis All statistical analysis was performed using the R software version 3. 5. 3. Residual e cacy data across treatments was analysed using generalized linear models (GLMs) with the "arm" package. The models included insecticide treatments as independent variable and mosquito mortality as the outcome. Interactions between insecticides and residual e cacy testing interval were also included in the models. Pairwise comparisons were performed with the nal model using the "multcomp" package. For the release-recapture experiments, generalized linear mixed models (GLMMs) with a binomial distribution and a logit link function was tted to the data using the "lme4" package. The models included treatment as xed effect. Enclosure, sleepers, and release-recapture study nights were treated as random effects.
Our analysis of the 2007/2008 grubbing up campaign Any economic policy decision taken at a level as aggregated as viticulture in Europe cannot take into account all the situations of grape growers and all their motivations for grubbing up their vines. Few data have been published on either the age of grape growers or on their economic performance to justify the a priori choices made. Being considered as common knowledge was enough to make these facts relevant. Furthermore, the success of this policy according to selected criteria has substantiated the merits of the common knowledge. To us, it seemed interesting to deepen the thought process on the EU 2008/2011 grubbing-up policy by analyzing the technical and microeconomic data originating from a genuine database capturing the grape growers' motivations and behaviors adopted during the last subsidized grubbing-up campaign (2007/2008) using the previous 1999 wine CMO rules.
Econometric model: ordinary least square regression In order to further explain the reasons for grubbing up within the data gathered from our 51 grape growers, we have used an ordinary least square (OLS) regression where Xi are the k explanatory variables and Y is the dependent variable. The model is linear and for each sample n the value yn is: 𝑦 𝑛 = ∑ ß 𝑖 𝑥 𝑛𝑖 + 𝜖 𝑛 𝑘 𝑖=0 The coefficient ß are found by minimizing the error of prediction. In our model Y is the grubbing rate and the k Xi explanatory variables are: grape grower's sex and age, his need for cash and profitability, his agricultural activity, belonging to a cave coop, having an heir to take over the vineyard, if the grape grower had already previously been in a grubbing up campaign. Other variables included are the age of the vines being grubbed up and several important varietals: Carignan, Syrah, Aramon, Grenache, Merlot, Cinsault and Sauvignon.
A final step for melting curve analysis from 58. 5°C to 95°C, measuring fluorescence every 0. 5°C, was added. Primers for defensin (Hi-DEF) and cecropin (Hi-CEC) coding genes were designed on AMP protein sequences predicted by transcriptome analysis by  Vogel et al. (2018)   (Table 1 ). For qPCR, actin (forward: 5 -TTCGAGCAGGAAATGGCCAC-3 and reverse 5 -TTGGAAGAGAGCCTCTGGAC-3 ) was used as reference gene  (Shin & Park, 2019). Results were analyzed using the CFX Manager TM Software (Bio-Rad, Hercules, CA, USA) for Ct determination. Relative quantification of target genes was calculated using the 2 -Ct method  (Livak & Schmittgen, 2001)  and expressed as a foldchange.
Statistical analysis Statistical analyses were performed with SPSS Statistics 27 (IBM Corp. Released 2017, Armonk, NY, United States). All the data were subjected to logarithmic (log10) transformation for normality before statistical analysis. AMP expression levels recorded from the analysis of insect reared on OFMSW were subject to pair-wise comparison of the mean with Student's t-test. In the other AMP expression level analyses, data were checked for homogeneity of variance (Levene test) and normality (Kolmogorov-Smirnov test), and compared using a oneway analysis of variance (ANOVA); in the case of significant differences the means were separated by a Tukey's test. If the assumptions of ANOVA were not met, the data were compared using Kruskal-Wallis test, and the means were separated using a Mann-Whitney U test.