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615 results for “tuning”
Dataset for 'Mapping twist-tuned multi-band topology in bilayer WSe$_2$'
<p>Datasets and code for the manuscript 'Mapping twist-tuned multi-band topology in bilayer WSe2.' See 'README.txt' for further details. </p>
Analysis workflow and dataset for Maxillary palps of tephritidae are tuned to food rather than oviposition volatiles and converge on ecology
<p>In this repository all data and scripts for generating the figure in the manuscript "Maxillary palps of tephritidae are tuned to food rather than oviposition volatiles and converge on ecology" can be found. <br><br>Data is found under /Data with recording for each fruit and the combined lure can be found under its respective name.</p> <p>In Data/sample GC-EPD .pptx there are also sample traces.</p> <p>In workflow most of the script needed to generate the figure that ends up in Output is available</p>
Supplementary material of article "Stem-loop-induced ribosome queuing in the uORF2/ATF4 overlap fine-tunes stress-induced human ATF4 translational control"
Open the record for dataset details and reuse information.
Rapid evolutionary tuning of endospore quantity vs. quality trade-off via a phase variable contingency locus
<p>Sequencing data and downstream bioinformatics analysis</p>
Data from: Diversity and evolution of frog visual opsins: spectral tuning and adaptation to distinct light environments
<p>Datasets for the publication Diversity and evolution of frog visual opsins: spectral tuning and adaptation to distinct light environments.</p>
Artifact from "A Little Goes a Long Way: Tuning Configuration Selection for Continuous Kernel Fuzzing"
<p>Artifact from "A Little Goes a Long Way: Tuning Configuration Selection for Continuous Kernel Fuzzing"</p>
Dataset for paper "MMO: Meta Multi-Objectivization for Software Configuration Tuning"
<p>This contains the dataset matched with the code on the GitHub page: https://github.com/ideas-labo/mmo</p>
Physiology and acclimation potential are tuned with phenology in larvae of a prolonged breeder amphibian
Due to the speed of climate changes, rapid buffering mechanisms such as phenotypic plasticity – which may depend on breeding phenology – could be key to avoid extinction. The links between phenology and plasticity, however, remain understudied. Here we explored the matching between phenology and the thermal sensitivity of standard (SMR) and routine metabolic rates (RMR), metabolic scope (i.e. the difference between RMR and SMR), survival and growth-development trajectories in larvae of a prolonged breeder amphibian (Alytes almogavarii) acclimated to 10 and 20ºC, belonging to three cohorts: autumn pre-overwintering, autumn overwintering and spring tadpoles. At 20ºC, survival of autumn pre-overwintering larvae was lower than for the rest. Although all cohorts showed acclimation potential, patterns for SMR and RMR differed, leading to differences in metabolic scope. Regardless of temperature, overwintering tadpoles arrested growth and development, while pre-overwintering and spring tadpoles showed higher growth and development at 20ºC. At 10ºC pre-overwintering tadpoles allocated more energy to development compared to spring tadpoles to advance development before winter. Overall, we demonstrate that the effects of temperature depend on phenology, consistent with future, expected thermal regimes. This suggests that extreme events can yield different vulnerability to climate change within populations (e.g., associated to discrete within-year cohorts), and not only between species or populations.
Dataset for paper "Do Performance Aspirations Matter for Guiding Software Configuration Tuning? An Empirical Investigation under Dual Performance Objectives"
<p>This contains the dataset matched with the code on the GitHub page: https://github.com/ideas-labo/aspiration-study.</p>
Dataset for: Spatial tuning of face part representations within face-selective areas revealed by high-field fMRI
<p>Regions sensitive to specific object categories as well as organized spatial patterns sensitive to different features have been found across the whole ventral temporal cortex (VTC). However, it is unclear that within each object category region, how specific feature representations are organized to support object identification. Would object features, such as object parts, be represented in fine-scale spatial tuning within object category-specific regions? Here we used high-field 7T fMRI to examine the spatial tuning to different face parts within each face-selective region. Our results show consistent spatial tuning of face parts across individuals that within right posterior fusiform face area (pFFA) and right occipital face area (OFA), the posterior portion of each region was biased to eyes, while the anterior portion was biased to mouth and chin stimuli. Our results demonstrate that within the occipital and fusiform face processing regions, there exist systematic spatial tuning to different face parts that support further computation combining them.</p>
Raw single-molecule imaging data for "Tuning levels of low-complexity domain interactions to modulate endogenous oncogenic transcription"
<p><strong>Raw single-molecule imaging data for "Tuning levels of low-complexity domain interactions to modulate endogenous oncogenic transcription"</strong></p> <p>Shasha Chong<sup>1</sup>, Thomas G.W. Graham<sup>2</sup>, Claire Dugast-Darzacq<sup>2,5</sup>, Gina M. Dailey<sup>2</sup>, Xavier Darzacq<sup>2,5</sup>, Robert Tjian<sup>2,3,4,5</sup>*</p> <p><sup>1 </sup>Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA, USA</p> <p><sup>2 </sup>Department of Molecular and Cell Biology, University of California, Berkeley, CA, USA.</p> <p><sup>3 </sup>Howard Hughes Medical Institute, University of California, Berkeley, CA, USA.</p> <p><sup>4</sup><sup> </sup>Li Ka Shing Center for Biomedical & Health Sciences, University of California, Berkeley, CA, USA.</p> <p><sup>5</sup><sup> </sup>CIRM Center of Excellence, University of California, Berkeley, CA. </p> <p>* Lead contact</p> <p><strong>Overview</strong></p> <p>This repository contains 1) movies of endogenously expressed EWS::FLI1-Halo in genome-edited A673 cells acquired using stroboscopic photo-activatable single particle tracking (spaSPT) and 2) images of exogenously expressed mNeonGreen-EWS-NPM1 fusion protein in the above cells before and after spaSPT movies were acquired. The uploaded files include data acquired from 80 live cells on 4 different days. The imaging data, after being processed, were used to generate Figure 4C-E of the manuscript in the title. </p> <p><strong>Method details</strong></p> <p>The genome-edited A673 cells (described in https://www.science.org/doi/10.1126/science.aar2555) with inducible expression of mNeonGreen-EWS-NPM1 were grown on 25 mm circular No. 1.5 cover glasses (Azer Scientific, 200251) that were plasma-cleaned prior to use. We induced the cells with 200 ng/ml of doxycycline for 96 hours, stained the cells with 20 nM PA-JF646 and 200 nM JFX549 HaloTag ligands, and performed single-molecule imaging of EWS::FLI1-Halo on a custom-built Nikon (Nikon Instruments Inc.) TI microscope described in (https://elifesciences.org/articles/25776). We took images with a 100x/NA 1.49 oil-immersion TIRF objective (Nikon apochromat CFI Apo TIRF 100x Oil) under highly inclined and laminated optical sheet (HILO) illumination (https://www.nature.com/articles/nmeth1171) using following laser lines: 488 nm for mNG; 561 nm for JFX549; 405 nm and 633 nm for photo-activation and excitation of PA-JF646, respectively. The incubation chamber maintained a humidified 37°C atmosphere with 5% CO<sub>2</sub> and the objective was similarly heated to 37°C for live-cell experiments. </p> <p>High-concentration JFX549 staining allows visualization of the intracellular distribution of EWS::FLI1-Halo. We chose cells with EWS::FLI1-Halo enriched in the nucleolus to perform spaSPT. The procedure of spaSPT largely follows what is described in (https://elifesciences.org/articles/25776). Both the excitation laser (633 nm) and the photo-activation laser (405 nm) for PA-JF646 were pulsed. Each frame consisted of a 7-ms camera exposure time followed by a ~500 μs camera ‘dead’ time. The excitation laser (633 nm) was pulsed for 1 ms starting at the beginning for the 7 ms camera exposure time. The photo-activation laser (405 nm) was pulsed during the ~500 μs camera ‘dead’ time, minimizing fluorescence background. Each cell was imaged for 20,000 frames corresponding to ~1.5 min. Images of mNeonGreen-EWS-NPM1 were collected with a camera exposure time of 500 ms before and after the acquisition of each spaSPT movie.</p>
Raw confocal imaging and FRAP data for "Tuning levels of low-complexity domain interactions to modulate endogenous oncogenic transcription"
<p><strong>Raw confocal imaging and FRAP data of "Tuning levels of low-complexity domain interactions to modulate endogenous oncogenic transcription"</strong></p> <p>Shasha Chong<sup>1</sup>, Thomas G.W. Graham<sup>2</sup>, Claire Dugast-Darzacq<sup>2,5</sup>, Gina M. Dailey<sup>2</sup>, Xavier Darzacq<sup>2,5</sup>, Robert Tjian<sup>2,3,4,5</sup>*</p> <p><sup>1 </sup>Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA, USA</p> <p><sup>2 </sup>Department of Molecular and Cell Biology, University of California, Berkeley, CA, USA.</p> <p><sup>3 </sup>Howard Hughes Medical Institute, University of California, Berkeley, CA, USA.</p> <p><sup>4</sup><sup> </sup>Li Ka Shing Center for Biomedical & Health Sciences, University of California, Berkeley, CA, USA.</p> <p><sup>5</sup><sup> </sup>CIRM Center of Excellence, University of California, Berkeley, CA. </p> <p>* Lead contact</p> <p><strong>Overview</strong></p> <p>This repository contains 1) raw three-color confocal fluorescence images of a transiently expressed protein (mNeonGreen-EWS, mNeonGreen, EGFP-TAF15, EGFP, mNeonGreen-EWS-NPM1, or mNeonGreen-NPM1), endogenously expressed EWS::FLI1-Halo labeled with JFX549 Halo ligand, and intron RNA fluorescence in situ hybridization (FISH) targeting <em>ABHD6</em>, <em>CAV1</em>, or<em> GAPDH </em>in genome-edited A673 cells, 2) raw fluorescence recovery after photobleaching (FRAP) movies of endogenously expressed EWS::FLI1-Halo labeled with TMR Halo ligand in genome-edited A673 cells in the presence and absence of transient expression of mNeonGreen-EWS-NPM1. The imaging data, after being processed, were used to generate Figure 1D-G (also S1A, S3, and S4), 2E-G (also S5A and S7), 3C-E (also S9), 4A, S2, S6, and S8 of the manuscript in the title. </p> <p><strong>Method details</strong></p> <p>1. RNA fluorescence in situ hybridization (FISH)</p> <p>The genome-edited A673 cells (described in https://www.science.org/doi/10.1126/science.aar2555) were plated on 18 mm circular No. 1 cover glasses (VWR VistaVision, 16004-300) and transfected with a protein expression plasmid using Lipofectamine 3000. 24 hours after transfection, we stained the cells with 200 nM JFX549 HaloTag ligand following the protocol described above, fixed the cells, and then proceeded with RNA FISH. To measure nascent transcription levels of <em>ABHD6</em>, <em>CAV1</em>, and <em>GAPDH </em>genes, we performed intron RNA FISH following the published Stellaris RNA FISH protocol for adherent cells (https://biosearchassets.blob.core.windows.net/assets/bti_stellaris_protocol_adherent_cell.pdf) using Quasar 670-labeled FISH probes designed with the online software Stellaris Probe Designer (https://www.biosearchtech.com/support/tools/design-software/stellaris-probe-designer) and purchased from LGC Biosearch Technologies. </p> <p>2. Confocal fluorescence imaging of protein and nucleic acid distribution</p> <p>Two confocal microscopes were used to image intron RNA FISH samples. One is an inverted laser scanning confocal microscope (Zeiss, LSM 710 AxioObserver) equipped with 34-channel spectral detection, a motorized stage, a full incubation chamber maintaining 37°C and 5% CO<sub>2</sub>, a heated stage, an X-Cite 120 illumination source as well as several laser lines (405, 458, 488, 514, 561, 591, 633 nm). Images were acquired with a 40x Plan NeoFluar NA1.3 oil-immersion objective under control of the Zeiss Zen software. The other is an inverted laser scanning confocal microscope with Airyscan super-resolution capability (Zeiss, LSM 900 with Airyscan 2) and equipped with four laser lines (405, 488, 561, 640 nm). Images were acquired with a 40x oil objective (Zeiss Plan-Apochromat 40x/1.3 Oil DIC) in the confocal (CO) mode under control of the Zen software. We acquired z stacks of RNA FISH samples with a slice interval of 0.3 mm. 405 nm, 488 nm, 561 nm, and 633 or 640 nm lasers were used to excite the fluorescence of Hoechst-labeled nuclei, EGFP or mNeonGreen-labeled proteins, JFX549-labeled EWS::FLI1-Halo, and Quasar 670-labeled intron RNA FISH, respectively. Before acquiring any fluorescence image, we carefully set the laser intensity and microscope detectors to make sure that no pixel in the image was saturated. We used proper emission filters for sequential four-color imaging and ensured no bleed-through between the four channels by imaging cell samples that contain only one of the four fluorophores (Hoechst, EGFP or mNeonGreen, JFX549, and Quasar 670) under the four-color imaging settings.</p> <p>3. Fluorescence recovery after photobleaching (FRAP)</p> <p>FRAP was performed on the inverted laser scanning confocal microscope (Zeiss, LSM 710 AxioObserver) described above. The 561 nm laser and the epi-illumination mode were used for FRAP measurements. Images were acquired with a 40x Plan NeoFluar NA1.3 oil-immersion objective. The knock-in A673 cells were grown on glass-bottom (No. 1.5, 14 mm diameter) 35 mm dishes (MatTek, P35G-1.5-14-C). To measure the FRAP dynamics of EWS::FLI1-Halo in the nucleolus, we transfected the knock-in cells with a plasmid encoding mNG-EWS-NPM1 and stained the cells with 500 nM HaloTag TMR ligand (Promega, G8251) following the protocol described above. We acquired 1000 frames at one frame per 0.3 seconds with the first 5 frames acquired before the bleach pulse for the measurement of baseline fluorescence of the bleach spot and the whole nucleus. We chose to photobleach a circular spot with a radius of 1 μm within a nucleolus using the 561 nm laser at maximum intensity. To measure the FRAP dynamics of EWS::FLI1-Halo in the nucleoplasm, we followed the same procedure as above, except that the knock-in cells were not transfected and a circular bleach spot with a radius of 1 μm was chosen within the nucleoplasm of a cell and at least 1 μm from nuclear and nucleolar boundaries. </p>
Spectral tuning of biotemplated ZnO photonic nanoarchitectures for photocatalytic applications
<p>The photocatalytic activity of a flat surface can be increased by micro- and nanostructuring the interface to increase the area of the contact surface between the photocatalyst and the solute, moreover, optimize charge carrier transfer. Further enhancement can be achieved by using photonic nanostructures, which exhibit photonic band gap (PBG). Structurally colored butterfly wings offer a rich "library" of PBGs in the visible spectral range which can be used as naturally tuned sample sets for biotemplating. We used conformal atomic layer deposition (ALD) of ZnO on the wings of various butterfly species (<em>Arhopala asopia</em>, <em>Hypochrysops polycletus</em>, <em>Morpho sulkowskyi</em>, <em>Polyommatus icarus</em>) possessing structural color extending from the near UV to the blue wavelength range, to test the effects arising from the nanostructured surfaces and from the presence of different types of PBGs. Aqueous solutions of rhodamine B were used to test the enhancement of photocatalytic activity that was found for all ZnO coated butterfly wings. The best reaction rate of decomposing rhodamine B when illuminated with visible light was found in 15 nm ZnO coated <em>M. sulkowskyi</em> wing the reflectance of which had the highest overlap with the absorption band of the dye and had the highest reflectance intensity.</p>
Benchmarks for the paper "A Comprehensive Timing Model for Accurate Frequency Tuning in Dataflow Circuits"
<p>The zip file contains the benchmarks used for the results presented in<br> <br> ```<br> Carmine Rizzi, Andrea Guerrieri, Paolo Ienne, and Lana Josipović. "A Comprehensive Timing Model for Accurate Frequency Tuning in Dataflow Circuits". In Proceedings of the 32nd International Conference on Field-Programmable Logic and Applications (FPL’22)<br> ```<br> <br> Feel free to download and test them following the instructions present in the README<br> <br> If you have any questions, do not hesitate to send an email to crizzi@ethz.ch</p>
The material properties of a bacterial-derived biomolecular condensate tune biological function in natural and synthetic systems. Source data
<p>Supplementary information for manuscript titled "The material properties of a bacterial-derived biomolecular condensate tune biological function in natural and synthetic systems"</p>
Defect-induced tuning of polarity-dependent adsorption in hydrophobic–hydrophilic UiO-66
<p>Simulations outputs from DFT and MC calculations on UiO-66 structures</p>
Optimal Sacrificial Domains in Mechanical Polyproteins: S. epidermidis Adhesins Are Tuned for Work Dissipation
<p>Data underlying the figures in the publication: Liu, H. <em>et al</em>. “Optimal Sacrificial Domains in Mechanical Polyproteins: <em>S. epidermidis</em> Adhesins Are Tuned for Work Dissipation” <em>JACS Au</em> <strong>2022</strong> <em>2</em>, 1417-1427, <a href="https://doi.org/10.1021/jacsau.2c00121">https://doi.org/10.1021/jacsau.2c00121</a></p>
Supplementary Dataset for the Paper: "Parameter-Adaptive Approximate MPC: Tuning Neural-Network Controllers without Re-Training"
<p>Supplementary dataset for paper Hose, Henrik, Alexander Gräfe, and Sebastian Trimpe. "Parameter-Adaptive Approximate MPC: Tuning Neural-Network Controllers without Re-Training." <em>arXiv preprint arXiv:2404.05835</em> (2024).</p> <p>The code to use this dataset is publicly available at <a href="https://github.com/hshose/Adaptive-AMPC-Cartpole">https://github.com/hshose/Adaptive-AMPC-Cartpole</a></p> <p>The dataset contains training and testing data to train an NN controller for a standart cartpole system.</p> <p>For each system, there are initial conditions as comma separated value in the `x0.txt` file, the MPC input trajectory in the `U.txt` file and the corresponding predicted state sequence in the `X.txt` file. Additionally, sensitivities (i.e. gradients dU/dtheta with respect to some system parameters theta) are provided in a file called `J.txt`.</p>
Data - Ultrafast generation of hidden phases \\ via energy-tuned electronic photoexcitation in magnetite
Open the record for dataset details and reuse information.
Protein sequences for Dephosphorylation sites and fine-tuning notebook
<p>Protein sequences for Dephosphorylation sites</p>
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Allen Brain Atlas
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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
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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.
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