dataesr/scientific-paragraphs-categorization huggingface dataset:
Last, we assume that a failed engine is immediately replaced with a new engine. We implement the ILP in Python using Gurobi, on a computer with an Intel Core i7 processor at 2. 11 GHz and 8Gb RAM. It requires 109 s to create a maintenance planning for a period of ten years. Fig. 13  shows the resulting maintenance planning at present days 𝑑 p = 791 and 𝑑 p = 801. At day 791, a replacement is planned for 6 engines, namely engines 9, 14, 16, 29, 40 and 41. For each engine with a planned replacement, we show the available maintenance slots (blue squares), the actual failure time (red cross in a circle) and the mean predicted failure time (orange cross in a dotted circle). For an engine 𝑣 ∈ 𝑉 at present day 𝑑 p , we use 𝑡 * 𝑘 p ,𝑣 to denote the optimal 𝑡 * 𝑘 from Eq. (  17 ) in Section 4. 1. Here, 𝑑 p + 𝑡 * 𝑘 p,𝑣 thus denotes the optimal replacement moment from the renewal-reward process with a single-component (blue cross).
In 2019 we also performed a nest search in the nestbox plot, during which 16 nests in natural cavities were discovered. Due to their limited accessibility (4 nests were located in very high or dry branches, and 1 nest was too deep to reach nestlings), and to the high number of nest failures before the nests were accessed (7 nests), we sampled nestlings in only three of these nests (a fourth nest was found close to fledging and thus excluded). Therefore, neither parental nor nestling genetic data from these three nests were included in the main analyses because the low sample size would not allow us to make a rigorous comparison between natural cavities and nestboxes within the plot (see details in  Sudyka, Di Lecce, Wojas, et al. , 2022). Whenever possible, each cavity was accessed with ladders or by climbing on trees (except for ground-level cavities) and inspected using portable led lights, mirrors and an NTS200 Digital Inspection Camera (NovoTech Industries Ltd.
| DISCUSS ION We found no differences in levels of extra-pair paternity at the plot level in blue tits and great tits breeding in natural cavities and nestboxes within the same urban forest. The analysis of blue tit data indicated that nearest neighbor distance was longer, and neighbor density and synchronous neighbor density were lower in F I G U R E 5 Distribution of the proportion of extra-pair offspring relative to within-pair offspring per nest in blue tits and great tits, by cavity type. Nests where social father was sampled were included.
Study region and input data In our study, we focus on the boreal forests of Eastern Canada, where ESBW defoliation is a major source of disturbance. Our study area is approximately 2. 9 million km 2 , extending from Manitoba to Newfoundland (102-53 • W; 46-65 • N). The dominant conifers in the region include black and white spruce, balsam fir, jack pine (Pinus banksiana (Lamb. )), and white pine (Pinus strobus L. ). Major broadleaf deciduous trees are trembling aspen (Populus tremuloides Michx. ), balsam poplar (Populus balsamifera L. (BP)) white birch (Betula papyrifera Marsh. ), and yellow birch (Betula alleghaniensis Britt. ). Datasets used to drive our model were prepared as in  Chaste et al. (2018). Except for lightning flashes, climate inputs for our experiments on Eastern Canada span from 1901 -2012 and were generated by BioSIM software from Environment Canada's historical climate database at a 10 × 10 km resolution  (Environment Canada, 2013).
Lightning flashes, in units of number of cloud-to-ground strikes per day per km 2 , were reconstructed for the period of 1901-2012 using the Canadian Lightning Detection Network data set covering the 1999-2010 period as described in  Chaste et al. (2018). Soil texture fractions were derived and interpolated from ISRIC -World Soil Information dataset. Atmospheric CO 2 concentrations for 1901 -2021 were derived from  Pfeiffer et al. (2013)  and  Keeling et al. (2009) , as in  Chaste et al. (2018).
2 ). Outputs include variables characterizing terrestrial vegetation   2016 ) and data originally from  Gray and MacKinnon (2006). Input data, including environmental conditions and PFT-specific parameters (blue), drives biophysical (gray) and tree biological processes (green) including carbon uptake and allocation. Trees are represented by the four typical genera of the Eastern boreal forest (Abies, Picea, Pinus, and Poplar). Mortality due to climate, stress, and fire, or autogenic process such as competition, adds biomass to slow and fast litter pools (brown). The ESBW module and its processes (orange) are activated by a minimum amount of live Abies foliage which initiates host foliage consumption. Fire processes (red) are then calculated with updated litter pools. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.
Model evaluation Consolidated aerial sketch map data on ESBW defoliation in Canada from 1941 to 1998 were sourced from  Gray and MacKinnon (2006)  through personal communication. We developed a ground-truth dataset for model evaluation by creating a binary categorization of the aerial sketch map data. Though Gray and MacKinnon 2006) contained categorical outbreak classes, we chose to convert both model and aerial sketch map data to binary classification given the qualitative nature of ASM outbreak classes. All classifications of outbreak, ranging from very mild, mild, mild-moderate, moderate, moderate-severe, severe, to very severe, were interpreted as outbreak occurrence indications. Shapefiles of outbreak classes were reclassified to the binary categories of 'defoliation present' and 'defoliation absent' and rasterized in alignment with model output in ArcGIS 10.
Using the bottom up controls of host foliage density to trigger initial outbreak, we effectively simulated the spatial patterns of ESBW and produced regular return intervals. We suggest that these results may have physical implications, given that regions of dense fir will eventually experience defoliation over longer timescales and that the regeneration rates of host foliage may play an important role in return interval length, with additional sensitivity to mortality rates of past outbreaks. Thus, the spatial and temporal patterns of ESBW outbreak may be driven by specific aspects of the ecophysiology of balsam fir. Additionally, we found that mortality driven by ESBW defoliation enhanced burnt area, though by a small amount when averaged over space and time. Our study used climate data from the last century calibrated with aerial sketch maps to replicate patterns of the past.
Acknowledgments We would like to give thanks to  Marc Oullette ,  Jemmett Kirk  and  Clara Risk  for help with development and analysis of our project. Funding for this work was provided by the  Ontario Ministry of Natural Resources and Forestry's Climate Change Program , the  Canadian Forest Service , and the  Natural Sciences and Engineering Research Council of Canada and Discovery Grant Program ,. We thank  Melanie Desrochers  and  Xiao Jing Guo  for their help with mapping and computation for this project. We also thank  Daniel Stubbs  from  Calcul Québec and Compute Canada  for helping with the Fortran language and server space facilities for running  LPJ-LMfire.
The optical density (OD 570nm ) was determined spectrophotometrically in duplicate using a microplate reader (Versamax® Molecular Devices, Sunnyvale, USA), and the absorbance values were determined using the software SoftMax Pro Enterprise (version 4. 7. 1). The percent reduction in cell viability in comparison with untreated negative controls was used to predict the skin irritation potential (OECD TG 439). A test chemical is considered a skin irritant in accordance with the United Nations Globally Harmonised System (UN GHS) and European Union Classification Labelling and Packaging (EU CLP) Category 1 or 2, if the tissue viability after exposure and post-treatment incubation is ≤ 50%.
Both activators induce signal broadening resulting from large fluctuations near the effector site as well as the dimer interface. Hence, we compared experimental shifts with those computed from our MD simulations employing the SHIFTX2 package  55. We estimate NMR shifts for each state by averaging over 10,000 configurations extracted from the corresponding 1μs MD simulation (replica 0). Using computed values allows us to account for those residues that are hard to assign experimentally, which is the case at elevated temperature conditions or for exchange-broadening upon effector binding. The full list of NMR assignments is provided as supplementary material. For experimental ΔCα chemical shifts profiles, we refer to the SI (Supplementary Fig. 6 ). Regardless of the state under consideration (apo30, holo30 or apo50), computed and experimental values show near-perfect agreement (Fig.
Molecular dynamics simulations The structural models for apo and holo forms of IGPS were based on the crystal structure of T. Maritima IGPS (PDB ID 1GPW, 2. 4 Å resolution)  76, 77. In this structure, chain C has the particularity to possess loop1 in a conformation prone to effector binding, thus we built the apo structure by extracting chains C and D of the HisH-HisF complex and reversing the D11N engineered mutation back to its wildtype form. The PRFAR-bound structure was built as described previously  46. The protein-ligand complex was parameterized with the CHARMM36m  78, 79  and the generalized CHARMM force fields 80 using the CHARMM-GUI  81. We kept all water molecules associated with the two chains and solvated the structures by using the explicit TIP3P model  76  to obtain a cubic box.
The protein was placed at the center of a 110 × 110 × 110 Å box with a distance of at least 10 Å from the box edges (~20,000 water molecules). Cl -and Na+ ions were added at randomized positions in the box up to neutralization of the total charge. We used AmberTools2021 82 to convert the CHARMM file format to Amber, and the AmberGPU  83, 84  package with the CHARMM36m force field for subsequent minimizations heating, and production runs, (further details of pre-equilibration procedure and MD production runs are described in Supporting Information, SI). To compare the effect of PRFAR and of the increase in temperature, we simulated the apo and the IGPS-PRFAR (holo) structures at 30 °C and 50 °C. We will refer to the simulations of the apo system performed at 30 °C and 50 °C as apo30 and apo50, respectively, and holo30 and holo50 for the holo IGPS protein complexes.
Principal components analysis PCA was performed employing the sklearn. decomposition. PCA function in the Scikit-learn library using python8. 3. 6  90. First, all simulations were aligned with MDAnalysis  91  to the crystal structure coordinates using Cα atoms. Next, we removed instantaneous linear correlations among the coordinates within each trajectory by applying a linear transformation that diagonalizes the respective covariance matrix of backbone atomic displacements. We project the original backbone trajectories onto the first principal components (sorted eigenvectors) and visualize their motion. In order to compare the essential dynamics of three systems (apo30, holo30, and apo50) in their low-dimensional free energy landscapes, we repeated the procedure using the concatenated coordinates of each trajectory to fit a single transformation function.
7 s. For the amide proton chemical shift temperature coefficient analysis, 2D 1 H-15 N TROSY spectra were acquired with 32 scans and 128 increments in the t 1 dimension with corresponding spectral widths of 12,000 Hz and 2800 Hz and a 1 s recycle delay. The temperature was calibrated using an external methanol sample. Amide proton and nitrogen chemical shifts were obtained from the 2D HSQC experiments recorded at 6 temperatures ranging from 20 to 50 °C (20, 25, 30, 35, 40, and 50 °C). Chemical shifts were referenced using DSS as an internal standard with the 1 H resonance frequency of DSS set to 0 ppm. All 2D and 3D NMR data were collected at a static magnetic field strength of 14. 1 T (600 MHz) on a Varian Inova instrument, processed in NMRPipe  94  and analyzed with Sparky  95. Temperature coefficients for individual residues were further analyzed and visualized using GraphPad Prism 9.
Acknowledgements J. P. L. and V. S. B. acknowledge support from  NIH GM   R01-106121. This work was also supported by a generous allocation of high-performance computing time from  NERSC. I. R. gratefully acknowledges the use of HPC resources of the " Pôle Scientifique de Modélisation Numérique " (PSMN) of the  ENS-Lyon, France.
g. [21]. Here we handle those difficulties by employing a similar proof strategy as in  [20, 22] , which leverages on the rigorous analysis of matrix-valued approximate message passing iterations. Although the planted model considered here is more elaborate than in  [20, 22] , we show that this problem is also amenable to a matrix-valued AMP iteration by decomposing the data matrix into two parts aligned and orthogonal to the subspace spanned by the columns of the teacher weights. In this work, we focus on the teacher-student model as a theoretical playground where important practical questions can be quantitatively studied, e. g. the impact of regularisation on the quality of learning or how to optimally tune hyper-parameters. However, the assumption of i. i. d. Gaussian data is too restrictive to capture the structure of real datasets.
10c) S V ≡ V 11 + V 22 + 2 V , (F. 10d) σ 12 ≡ V2 -2 V11 V22 -V22 V V2. (F. 10e) If the label vector is y = [0, 1] ⊤ , one just needs to perform the following trivial changes in the equations above for y = [1, 0] ⊤ : V 11 → V 22 , (F. 11a) V 22 → V 11 , (F. 11b ) ω 1 → ω 2 , (F. 11c ) ω 2 → ω 1 , (F. 11d) Observe that the mapping from appendix A has allowed us to reduce the number of integrals to be numerically computed at each AMP iteration to three, given by equation (F. 6) or equation (F. 9), depending on the one-hot output representation y. These integrals were solved through the integrate. quad module from SciPy  [45]. To speed up the integration, we have also used Numba  [46]  decorators. (F. 15) The denoising functions for this case are computed numerically, via Monte Carlo sampling of the distribution given equation (F.
Acknowledgment We acknowledge funding from the  ERC  under the  European Union 's  Horizon 2020 Research and Innovation Programme  Grant Agreement  714608-SMiLe. R V was partially financed by the  Coordenação de Aperfeiçoamento de Pessoal de Nível Superior-Brasil (CAPES) -Finance   Code 001. R V is grateful to  EPFL  and  IdePHICS lab  for their generous hospitality during the realization of this project. This work started as a part of the doctoral course  Statistical Physics For Optimization  and Learning taught at EPFL in spring 2021.
8, SD = 7. 5). Electrodermal activity data from two additional participants was discarded due to data loss and from an additional participant due to lack of skin conductance responses (SCR; see Implicit embodiment measure: skin conductance response to threat in the Measures section), resulting in a sample size of 19 participants for this measure (N = 19; 9 females; age M = 29. 5, SD = 7. 5).
Visuotactile stimulation An Oculus CV1 HMD was used for stimulation. The software was designed using Unity 2018. 2. 8 for displaying a 235-degree prerecorded video portraying the first-person perspective of a male or female sex person that were previously filmed using a monoscopic Kodak SP360 4 K camera at a resolution of 2160 × 2160 pixels at 30 frames per second. The sex and gender of the seen person was expected to be distinguished from the HMD based on stereotypical associations (see Limitations, considerations, and outlook section), such as clothing, more prominent hair, and distinct body shapes. Another sex-matched person was recorded allocentrically interacting with them, this person synchronized their movements and actions to a previously recorded set of audio instructions to achieve consistent timing between videos.
Statistical analyses and data processing Aligned rank transform (ART) ANOVA, binomial tests, linear mixed models, Cronbach's alpha (reported in the Supplementary Materials), descriptive statistics and data preprocessing were conducted in R version 3. 5. 1 (R Core Team, 2020) and inspected for normality through visual inspection and Shapiro-Wilk tests. Two-tailed comparisons are reported. Additional Bayesian statistics were performed using JASP 0. 11. 1 (JASP Team). The data can be found on https://osf. io/3k86r/. VAS data were analyzed with aligned rank transformation ANOVAs using the package ARTool  (Kay & Wobbrock, 2020)  for each item. We used ART ANOVAs because of their robustness for nonparametric analyses  (Wobbrock et al. , 2011 ). Significant findings were followed up with multiple Bonferroni-corrected Wilcoxon signed-rank for the comparisons of interest.
e. , the fourth component explained 0 % of the random-effects variance). The final model was built as follows (in lme4 syntax): sqrtSCR ~ (congruency * odor. type) + (1 + congruency + odor. type| participant). We used the 'bobyqa' optimizer and set the number of model iterations to 200 ′ 000 to fit the model. Follow-up comparisons were computed with the emmeans  (Lenth, 2020)  package when appropriate and Bonferroni correction was applied to correct for multiple testing. We report Cohen's d for LME models (see  Brysbaert & Stevens, 2018; Westfall et al. , 2014)  as an estimate of effect size and their 95 % CI. Complementary analyses using robust linear mixed effects were computed to ensure that our results were not biased by outliers, these are reported in the Supplementary Materials (section: Robust Linear Mixed Effects Model for the Skin Conductance Responses).
Acknowledgements We thank  Jasmin Schilling  for her support with data collection and  Irene Madoka Scheiwiller  for piloting and preparing the experiment. Maria Ordoñez  for her support with the photography for the figure. Anna Khazina ,  Kelly Gibbs ,  François-Rémy Ringeval  and  Tonino Rizzo  for their participation in the immersive videos. Also, the  Human Perception and Bioresponses Department of the Research and Development Division of Firmenich ,  S. A. , for their invaluable advice and technical competence. This project was funded by the  University of Geneva-University of Zurich  Joint Seed Money Funding 2018. M. R. L. and B. L. were funded by the  Swiss National Science Foundation  (SNSF;  PP00P1_170511 ,  PP00P1_202674 ), and Y. S. was supported by an  Early Postdoc Mobility fellowship  from the  SNSF  ( P2GEP1_187911 ).
Moreover, 1855 transcripts were upregulated and 667 downregulated in the border zone; finally, in the remote region, 284 were increased and 233 decreased on d7 compared to d28 post-surgery (Supplementary Fig. 5 , and Supplementary Data 2-3). DEG data derived from infarcted tissues on d7 and d28 vs healthy samples were analysed by Ingenuity Pathway Analysis (IPA®) to identify which canonical pathways are significantly altered following NSTEMI. Many distinctive pathways associated with myocardial ischaemic pathophysiology were detected, such as Fibrosis, Atherosclerosis and Renin-angiotensin signalling both on d7 and 28 post-surgery (Fig. 3b  and Supplementary Data 6). In addition, several pathways linked to the inflammatory response emerged in the d7 post-NSTEMI group, including Hypoxia-inducible Factor (HIF1α), Endothelial NOS (eNOS), and Interleukin-6, -9, -10, -12 (IL), Leucocyte extravasation and Inflammasome signalling (Fig.
Also, the calponin-1 ratio increased to 1. 87-fold and 2. 5-fold on d7 and to 1. 5-fold and 5. 28-fold on d28 in the border and ischaemic core regions, respectively (Fig. 3d  and Supplementary Data 11). Importantly, gene-annotation enrichment analysis using Database for Annotation, Visualization, and Integrated Discovery (DAVID) software on RNA-seq data highlighted distinctive glycan alterations in the postischaemic remodelling in the current NSTEMI model (Supplementary Fig. 7  and Supplementary Data 12-15). Given the outcome of RNA-seq and proteomic pathway analyses, we noticed a key involvement of glycan moieties, since both on d7 N-glycan biosynthesis (Supplementary Fig. 7a  and Supplementary Data 12) and on d28 GAGs biosynthesis (Supplementary Fig. 7b  and Supplementary Data 15) emerged among the biological functions of Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database with the highest enrichment score.
Distinct glycoprofile in the ischaemic tissue following NSTEMI Considering the findings highlighted by the pathway and functional annotation analyses on RNA-seq data, we scrutinised the altered glycan composition in the cellular membrane and ECM proteins of infarcted NSTEMI tissue. Here, we dissected the glycome under the inflammatory (d7) and fibrotic (d28) conditions following NSTEMI by advanced glycomic analysis of the N-glycans expressed in the left ventricular membrane and ECM protein fraction. To achieve this, during the sample processing N-linked glycans were released and analysed by LC-MS. Following annotation procedures, 103 putative N-glycan structures were identified, including 10 high mannose, 15 hybrid and 78 complex-type glycans (Fig. 4  and Supplementary Data 16). Since the relative abundance of these structures varied across healthy and infarcted tissues, hierarchical clustering analysis was performed for high-mannose and complex N-linked glycans (Fig.
These factors are also potential markers of left ventricular dilatation in response to myocardial injury. However, left ventricular EDD and ESD were not m/z values framed in red indicate N-glycan structures, which were found to increase also in MI patients' sera by Lim et al. 43. g Gene expression levels of SIGLEC-1, -2, -10, -11 and -15 at d7 and 28 post-NSTEMI from RNA-seq data on IS and BZ samples. n = 4 animals per group. Regions of infarcted hearts are labelled as follows: IS = ischaemic core, BZ = border, F = remote zone from the infarct. Data are representative of two independent experiments. In (a-f), each analysed sample was a pool of samples collected from three individuals per group and region and investigated by LC-ESI-MS/MS. In (g), RNA-seq data analysis was run using DESeq2 (dashed line indicates the threshold set to log 2 (fold-change)>1.
5), and significant differences were assessed by two-sided Wald's test using Benjamini-Hochberg method. *P < 0. 05, ***P < 0. 001. Source data are provided as a Source Data file. primary endpoints since the study endpoint was on day 28 post-NSTEMI, which may not have allowed sufficient time for dilation in response to the myocardial injury. Therefore, regional WMI analysis was also evaluated, focusing on the anterolateral walls on TTE. Here we need to consider that scoring is based on a 3-point scoring system indicated by the American Society of Echocardiography and the European Association of Cardiovascular Imaging  56  and remain aware that the difference between a normally contracting wall (1), a hypokinetic wall (2), and even an akinetic wall (3) can be subtle in some cases and may vary depending on the observer.
A chest tube was placed with its tip in the pericardial sac and the remnant holes in the left chest before the thoracotomy was closed in layers, and the animal recovered. The animals were given analgesia and fluids post-operatively as outlined by the institutional protocol. Functional analyses post-surgery. Echocardiography measurements were recorded the day before each surgical procedure and at the study time points of 7 and 28 days. All echocardiographic examinations were performed in calm, unsedated standing animals. A 5 MHz probe was employed and the console and software used were Mindray DP-7 (Mindray Medical, China). Images and windows for the echocardiographic protocol were derived from techniques described for horses and more recently adapted for sheep  55. Two cardiologists performed examinations and agreed on the interpretation and derivation of the data.