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849 results for “linear”
Quantitative evaluation of mantle flow traction on overlying tectonic plate: Linear versus power-law mantle rheology
<p>Dataset for <strong>Quantitative evaluation of mantle flow traction on overlying tectonic plate: Linear versus power-law mantle rheology</strong></p>
Phonons from Density-Functional Perturbation Theory using the All-Electron Full-Potential Linearized Augmented Plane-Wave Method FLEUR
<p>The archive files contain the input and result files for the corresponding publication in IOP Electronic Structure - Technical Notes, as well as a short python script to plot them.</p>
Time-bin entanglement in the deterministic generation of linear photonic cluster states
<p>We investigate strategies for the efficient deterministic creation of trains of time-bin entangled photons using an individual quantum emitter described by a $\Lambda$-type electronic system. We explicitly demonstrate generation of high-quality linear cluster states of substantial length in our full microscopic numerical simulations. The underlying scheme is based on the manipulation of ground state coherences through precise optical driving. One important finding is that the most easily accessible quality metrics, the achievable rotation fidelities, fall short in assessing the actual quantum correlations of the emitted photons in the face of losses. To address this, we explicitly calculate stabilizer generator expectation values as a superior gauge for the quantum properties of the many-photon state. Our results illustrate that with controlled minimization of losses and realistic system parameters for quantum-dot type systems, useful linear cluster states of significant lengths can be generated, showcasing promise of scalability for quantum information processing endeavors.</p>
Fig. 7 in Identification and characterization of two bisabolene synthases from linear glandular trichomes of sunssower (Helianthus annuus L., Asteraceae)
Fig. 7. Phylogenetic analysis and partial sequence comparison. (A) Phylogenetic tree based on 27 plant STSs. (Z)-γ-bisabolol synthases from sunssower and Arabidopsis thaliana are boxed, and bootstrap values are given in each node. Gymnosperm Abies grandis STSs were used to serve as a root. Sequences used (but not described in the Figure) are: GhCDS, δ-cadinene synthase [Gossypium hirsutum]; GaCDS δ-cadinene synthase [Gossypium arboreum]; CsAFS, α-farnesene synthase [Cucumis sativus]; CsCS, δ- caryophyllene synthase [Cucumis sativus]; CsVS, valencene synthase [Citrus sinensis]; CjFS, δ-farnesene synthase [Citrus junos]; ObGDS, germacrene D synthase [Ocimum basilicum]; CmCDS, δ-cadinene synthase [Cucumis melo]; CmAFS, α-farnesene synthase [Cucumis melo]; CaEAS, 5-epi-aristolochene synthase [Capsicum annuum]; AaGAS, germacrene A synthase [Artemisia annua]; AtCS, δ-caryophyllene synthase [Arabidopsis thaliana]; AtATP12 (Z)-γ-bisabolene synthase 1 [Arabidopsis thaliana]; AtTPS13 (Z)-γ- bisabolene synthase 2 [Arabidopsis thaliana]; AtBAS α-barbatene synthase [Arabidopsis thaliana]; ObCDS γ-cadinene synthase [Ocimum basilicum]; AmNS nerolidol synthase [Antirrhinum majus]; LaBERS α-bergamotene synthase [Lavandula angustifolia]; AgHS γ-humulene synthase [Abies grandis]; AgSS δ-selinene synthase [Abies grandis]. (B) Amino acid sequences neighboring the Y402 residue of A. annua β-farnesene synthase are compared among the clustered STSs (β-farnesene, α-bisabolol, amorpha-4,11-diene synthases, see the bracket in A). Accession numbers of HaTPS12_K7 and HaTPS12_K11 are KU674381 and KU674382, respectively.
Fig. 6 in Identification and characterization of two bisabolene synthases from linear glandular trichomes of sunssower (Helianthus annuus L., Asteraceae)
Fig. 6. Observed longrange coupling (solid arrow) and nuclear overhauser effects (dotted arrow) in COSY and ROESY 1H NMR 2D experiments with the purified enzyme product cis-γ-bisabolene.
Fig. 5 in Identification and characterization of two bisabolene synthases from linear glandular trichomes of sunssower (Helianthus annuus L., Asteraceae)
Fig. 5. Quantification of cis-γ-bisabolene produced in yeast expression experiments with HaTPS12_K7 und HaTPS12_K11 and the corresponding N-terminal thioredoxion fusion (Trx) constructs. The values represent means and standard deviations of n = 5 independent experiments; different letters indicate statistical significance at the level of p> 0.05.
Fig. 3 in Identification and characterization of two bisabolene synthases from linear glandular trichomes of sunssower (Helianthus annuus L., Asteraceae)
Fig. 3. GC–MS analysis of sesquiterpene products of the in vivo expression of HaTPS12_K7 and HaTPS12_K11 in S. cerevisiae EPY300. The GC diagrams show metabolite profiles of extracts from yeast cultures transformed with the candidate genes in the high-level expression plasmid pESCLeu2d in compared to a yeast train transformed with the empty vector (NC, negative control). Mass spectra of the identified peak A (γ-bisabolene) and B (farnesyl/nerolidol) are shown.
Fig. 1 in Identification and characterization of two bisabolene synthases from linear glandular trichomes of sunssower (Helianthus annuus L., Asteraceae)
Fig. 1. Bisabolene-type sesquiterpenes reported from sunssower Helianthus annuus (Spring et al., 1992; Macias et al., 1999).
Fig. 2 in Identification and characterization of two bisabolene synthases from linear glandular trichomes of sunssower (Helianthus annuus L., Asteraceae)
Fig. 2. Alignment of the deduced amino acid sequences of bisabolene synthase genes HaTPS12_K7 and HaTPS12_K11 from linear glandular trichomes of sunssower. Boxes: typical amino acid sequence motives of sesquiterpene synthases (RxR and DDxxD motive). Arrows: amino acid differences between the two enzyme isoforms.
Fig. 4 in Identification and characterization of two bisabolene synthases from linear glandular trichomes of sunssower (Helianthus annuus L., Asteraceae)
Fig. 4. GC analysis of sesquiterpene products from in vivo expression of HaTPS12_K7Trx and HaTPS12_K11Trx in S. cerevisiae EPY300 compared to HaTPS12_K7 and HaTPS12_K11.A (γ-bisabolene), B (farnesyl/nerolidol).
SAN: Inducing Metrizability of GAN with Discriminative Normalized Linear Layer
<p>This repository contains a pre-trained checkpoints for StyleSAN-XL proposed in the paper <a href="https://arxiv.org/abs/2301.12811">SAN: Inducing Metrizability of GAN with Discriminative Normalized Linear Layer</a> by Sony.</p> <p>More information about StyleSAN-XL including our code is available at <a href="https://github.com/sony/san">https://github.com/sony/san</a>.</p>
Supporting data for "A method for non-linear inversion of the stellar structure applied to gravity-mode pulsators"
<p>These are the inlist and run_star_extras required to reproduce the stellar and asteroseismic models presented in 'A method for non-linear inversion of the stellar structure applied to gravity-mode pulsators', run with MESA r22.05.1.</p>
Data and code for the publication 'Fully Non-Linear Neuromorphic Computing with Linear Wave Scattering'
<p>This repository contains the source code for the paper <a href="https://arxiv.org/abs/2308.16181" rel="nofollow">https://arxiv.org/abs/2308.16181</a> on nonlinear neuromorphic computing via linear wave scattering as well as the source data for the figures in the paper.</p> <p>The idea behind this work is to send optical waves through a linear scattering system like an array of waveguides and optical resonators. These optical resonators or other elements may have tuneable parameters. These tuneable parameters now serve two functions in trying to use the system to solve a machine-learning task: Some of the parameters can be used to inject the input (e.g. images to be classified). Other parameters are trainable and will be slowly updated during training. The code given here simulates physical scattering setups, observes the scattering response for many different training samples, and updates the trainable parameters via gradient descent to minimize the deviation from the desired target output for the training samples. Evaluation of the scattering response as well as calculation of the gradients is done using jax, and training updates are implemented via jax or optax.</p> <p>See the two subdirectories for the code used in handwritten-digit recognition (a scaled-down version of MNIST) and for fashion-MNIST (with many more neurons and trainable parameters). This code can be run directly to reproduce the results shown in the figures (although a GPU is advisable). To run the code, you need to install jax and optax (and tensorflow for importing data sets).</p>
Research on UAV Autonomous Recognition and Approach Method for Linear Target Splicing Sleeves Based on Deep Learning and Stereo Vision
<p><span>Link to the video as supplementary material for the paper-《Research on UAV Autonomous Recognition and Approach Method for Linear Target Splicing Sleeves Based on Deep Learning and Stereo Vision》.</span></p>
Linear and Nonlinear refractive index of ITO(n&k)
Open the record for dataset details and reuse information.
HOMULA-RIR: A Room Impulse Response Dataset for Teleconferencing and Spatial Audio Applications Acquired Through Higher-Order Microphones and Uniform Linear Microphone Arrays
<p>In this paper, we present HOMULA-RIR, a dataset of room impulse responses (RIRs) acquired using both higher-order microphones (HOMs) and a uniform linear array (ULA), in order to model a remote attendance teleconferencing scenario. Specifically, measurements were performed in a seminar room, where a 64-microphone ULA was used as a multichannel audio acquisition system in the proximity of the speakers, while HOMs were used to model 25 attendees actually present in the seminar room. The HOMs cover a wide area of the room, making the dataset suitable also for applications of virtual acoustics. Through the measurement of the reverberation time and clarity index, and sample applications such as source localization and separation we demonstrate the effectiveness of the HOMULA-RIR dataset.</p>
On this side of the fence: Functional responses to linear landscape features shape the home range of large herbivores
<p>1. Understanding the consequences of global change for animal movement is a major issue for conservation and management. In particular, habitat fragmentation generates increased densities of linear landscape features that can impede movements.</p> <p>2. While the influence of these features on animal movements has been intensively investigated, they may also play a key role at broader spatial scales (e.g. the home range scale) as resources, cover from predators/humans, corridors/barriers, or landmarks. How space use respond to varying densities of linear features has been mostly overlooked in large herbivores, in contrast to studies done on predators. Focusing on large herbivores should provide additional insights to understand how animals solve the trade-off between energy acquisition and mortality risk.</p> <p>3. Here, we investigated the role of anthropogenic (roads and tracks) and natural (ridges, valley bottoms and forest edges) linear features on home range features in five large herbivores. We analysed an extensive GPS monitoring data base of 696 individuals across nine populations, ranging from mountain areas mostly divided by natural features to lowlands that were highly fragmented by anthropogenic features.</p> <p>4. Nearly all of the linear features studied were found at the home range periphery, suggesting that large herbivores primarily use them as landmarks to delimit their home range. In contrast, for mountain species, ridges often occurred in the core range, probably related to their functional role in terms of resources and refuge. When the density of linear features was high, they no longer occurred predominantly at the home range periphery, but instead were found across much of the home range. We suggest that, in highly fragmented landscapes, large herbivores are constrained by the costs of memorising the spatial location of key features, and by the requirement for a minimum area to satisfy their vital needs.</p> <p>5. These patterns were mostly consistent in both males and females and across species, suggesting that linear features have a preponderant influence on how large herbivores perceive and use the landscape.</p>
Single-molecule analysis of specificity and multivalency in binding of short linear substrate motifs to the APC/C
<p>Robust regulatory signals in the cell often depend on interactions between short linear motifs (SLiMs) and globular proteins. Many of these interactions are poorly characterized because the binding proteins cannot be produced in the amounts needed for traditional methods. To address this problem, we developed a single-molecule off-rate (SMOR) assay based on microscopy of fluorescent ligand binding to immobilized protein partners. We used it to characterize substrate binding to the Anaphase-Promoting Complex/Cyclosome (APC/C), a ubiquitin ligase that triggers chromosome segregation. We find that SLiMs in APC/C substrates (the D box and KEN box) display distinct affinities and specificities for the substrate-binding subunits of the APC/C, and we show that multiple SLiMs in a substrate generate a high-affinity multivalent interaction. The remarkably adaptable substrate-binding mechanisms of the APC/C have the potential to govern the order of substrate destruction in mitosis.</p>
Figure 5 with linear speedup
<p>Figure 5 with linear speedup.</p>
The density of anthropogenic features explains seasonal and behaviour-based functional responses in selection of linear features by a social predator
<p>Anthropogenic linear features facilitate access and travel efficiency for predators, and can influence predator distribution and encounter rates with prey. We used GPS collar data from eight wolf packs and characteristics of seismic lines to investigate whether (1) ease-of-travel or (2) access to areas presumed to be preferred by prey best explained seasonal selection patterns of wolves near seismic lines, and whether the density of anthropogenic features led to functional responses in habitat selection. At a broad scale, wolves showed evidence of habitat-driven functional responses by exhibiting greater selection for areas near low-vegetation height seismic lines in areas with low densities of anthropogenic features. We highlight the importance of considering landscape heterogeneity and habitat characteristics, and the functional response in habitat selection when investigating seasonal behaviour-based selection patterns. Our results support behaviour in line with search for primary prey during summer and fall, and ease-of-travel during spring, while patterns of selection during winter aligned best with ease-of-travel for the less-industrialized foothills landscape, and with search for primary prey in the more-industrialized boreal landscape. These results highlight that time-sensitive restoration actions on anthropogenic features can affect the probability of overlap between predators and threatened prey within different landscapes.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.