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4,563 results for “correlations”
From Noise to Signal: Multi-layer Speckle Correlation with Applications in Visible Light Communication
<p>Dataset for journal article "Enhanced Secrecy in Optical Communication using Speckle from Multiple Scattering Layers"</p> <p>The basic publication is:<br> Alfredo Rates, Joris Vrehen, Bert Mulder, Wilbert L. IJzerman, and Willem L. Vos, "Enhanced Secrecy in Optical Communication using Speckle from Multiple Scattering Layers", Opt. Express <strong>31</strong>, 23897-23909 (2023).<br> <br> We have uploaded to the Zenodo database all data enabling everyone to reuse our data, and to reproduce all the figures of our paper.</p> <p>The upload contains the file "Metadata.txt" explaining the content of the upload.</p>
Consequences of cross-season demographic correlations for population viability
<p class="MsoNormal"><span>Demographic correlations are pervasive in wildlife populations and can represent important secondary drivers of population growth. Empirical evidence suggests that correlations are in general positive for long-lived species, but little is known about the degree of variation among spatially segregated populations of the same species in relation to environmental conditions. We assessed the relative importance of two cross-season correlations in survival and productivity, for three Atlantic puffin</span><span> (</span><span><em>Fratercula</em> <em>arctica</em></span><span>) </span><span>populations with contrasting population trajectories and non-overlapping year-round distributions. The two correlations reflected either a relationship between adult survival prior to breeding on productivity or a relationship between productivity and adult survival in the subsequent year. Demographic rates and their correlations were estimated with an integrated population model, and their respective contributions to variation in population growth were calculated using a transient life table response experiment. For all three populations, demographic correlations were positive at both time lags, although their strength differed. Given the difference in year-round distributions of these populations, this variation in the strength of population-level demographic correlations points to environmental conditions as an important driver of demographic variation through life-history constraints. Consequently, the contributions of variances and correlations in demographic rates to population growth rates differed among puffin populations, which has implications for – particularly small – populations' viability under environmental change as positive correlations tend to reduce the stochastic population growth rate.</span></p>
Fluorescence correlation spectroscopy TCSPC data with and without peak artifacts - PEX5 applied experiment
<p>This is a dataset of Fluorescence Correlation Spectroscopy (FCS) Time-Correlated Single Photon Counting (TCSPC) data with and without peak artifacts. The provenance of the data is recorded in <a href="https://github.com/aseltmann/fluotracify/blob/data/data/exp-220120-correlate-ptu/LabBook-exp-220120-correlate-ptu.org">this file</a> (see a rendered version <a href="https://aseltmann.github.io/fluotracify/data/LabBook-all.html#sec-2-5">here</a>). This parent project (<a href="https://github.com/aseltmann/fluotracify">https://github.com/aseltmann/fluotracify</a>) also contains examples of how to use these models and related Python code.</p> <p>The following connected paper is currently under review and should be cited together with these model versions: <em>Seltmann, A.; Carravilla, P.; Reglinski, K.; Eggeling, E.; Waithe, D. Neural Network Informed Photon Filtering Reduces Artifacts in Fluorescence Correlation Spectroscopy Data. 2023 (currently under review)</em></p> <p><strong>Note on the file formats and notation:</strong></p> <p>"Primary data" refers to the <code>.ptu</code> files, so the actual TCSPC data. "Secondary data" refers to the <code>.pqres</code> files, which are derived files by the proprietary PicoQuant software.</p> <p><strong>Note on sample preparation (from the Supplementary Note of the paper above):</strong></p> <p>The peak artifacts measurements were produced by 20 nM Trypanosoma brucei-PEX5 N-term fused to eGFP in solution, and the corresponding control measurements by 5 nM Homo sapiens-PEX5 N-term fused to eGFP in solution. The detailed sample preparation is described elsewhere. We prepared the samples on #1.5 coverslips mounted on Attofluor Cell Chambers (Thermo Fisher Scientific). We acquired the data on a MicroTime 200 microscope (PicoQuant) equipped with an Olympus UPlanSApo 60× 1.2NA water immersion objective lens and a HydraHarp 400 TCSPC module (PicoQuant). Excitation was achieved with a 488 nm pulsed laser (PicoQuant) with a power of 5 mW measured at the sample plane. We used a 20 nM solution of Alexa Fluor for calibrating the correction collar. One TCSPC measurement had a length of 20 s for PEX5 experiments.</p>
Fluorescence correlation spectroscopy TCSPC data with and without peak artifacts - AlexaFluor 488 applied experiment
<p>This is a dataset of Fluorescence Correlation Spectroscopy (FCS) Time-Correlated Single Photon Counting (TCSPC) data with and without peak artifacts. The provenance of the data is recorded in <a href="https://github.com/aseltmann/fluotracify/blob/data/data/exp-220120-correlate-ptu/LabBook-exp-220120-correlate-ptu.org">this file</a> (see a rendered version <a href="https://aseltmann.github.io/fluotracify/data/LabBook-all.html#sec-2-5">here</a>). This parent project (<a href="https://github.com/aseltmann/fluotracify">https://github.com/aseltmann/fluotracify</a>]) also contains examples of how to use these models and related Python code.</p> <p>The following connected paper is currently under review and should be cited together with these model versions: <em>Seltmann, A.; Carravilla, P.; Reglinski, K.; Eggeling, E.; Waithe, D. Neural Network Informed Photon Filtering Reduces Artifacts in Fluorescence Correlation Spectroscopy Data. 2023 (currently under review)</em></p> <p><strong>Note on the file formats and notation:</strong></p> <p>"Primary data" refers to the <code>.ptu</code> files, so the actual TCSPC data. "Secondary data" refers to the <code>.pqres</code> files, which are derived files by the proprietary PicoQuant software.</p> <p><strong>Note on sample preparation (from the Supplementary Note of the paper above):</strong></p> <p>The peak artifact measurements were produced by mixing 20 nM of the small dye Alexa Fluor 488 (Thermo Fisher Scientific) with 10 μM of slow, large (100 nm) unilamellar vesicles (LUVs) labelled with DiO in the membrane (0.1 % mol lipid:dye). The corresponding control measurements were 20 nM Alexa Fluor 488 in solution. We prepared the LUVs by the extrusion method: 1−palmitoyl−2−oleoyl−glycero−3−phosphocholine (POPC, Avanti Polar Lipids) was vacuum dried on a glass vial for 1 h and resuspended on phosphate buffered saline to form lipid vesicles. The vesicles were extruded 30 times through 100 nm pore size polycarbonate membranes using a Mini-Extruder (Avanti Polar Lipids). We prepared the samples on #1.5 coverslips mounted on Attofluor Cell Chambers (Thermo Fisher Scientific). We acquired the data on a MicroTime 200 microscope (PicoQuant) equipped with an Olympus UPlanSApo 60× 1.2NA water immersion objective lens and a HydraHarp 400 TCSPC module (PicoQuant). Excitation was achieved with a 488 nm pulsed laser (PicoQuant) with a power of 5 mW measured at the sample plane. We used a 20 nM solution of Alexa Fluor for calibrating the correction collar. One TCSPC measurement had a length of 10 s for AF488 experiments.</p>
Fluorescence correlation spectroscopy time-series data with and without peak artifacts - simulated data
<p>This is a dataset of FCS time-series with and without peak artifacts. It was created by 2D Monte Carlo simulations of diffusing particles. The provenance of the data is recorded in <a href="https://github.com/aseltmann/fluotracify/blob/data/data/exp-201231-clustsim/LabBook-exp-201231-clustsim.org">this file</a> (see a rendered version <a href="https://aseltmann.github.io/fluotracify/data/LabBook-all.html#sec-2-2">here</a>). This parent project (<a href="https://github.com/aseltmann/fluotracify">https://github.com/aseltmann/fluotracify</a>]) also contains examples of how to use this data and related Python code to load it.</p> <p>The following connected paper is currently under review and should be cited together with this dataset: Seltmann, A.; Carravilla, P.; Reglinski, K.; Eggeling, E.; Waithe, D. Neural Network Informed Photon Filtering Reduces Artifacts in Fluorescence Correlation Spectroscopy Data. 2023 (currently under review)</p> Data structure inside each .csv file <table><tbody> <tr> <td><header></td> <td> <p>10 to 12 lines, contains metadata</p> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td>...</td> <td>...</td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td><source_1></td> <td><target_1a></td> <td><target_1b></td> <td><source_2></td> <td><target_2a></td> <td><target_2b></td> <td>...</td> </tr> <tr> <td> <p>FCS time-series with artifact</p> </td> <td>Artifact time series</td> <td> <p>FCS time series without artifact</p> </td> <td> <p>FCS time series with artifact</p> </td> <td>Artifact time series</td> <td> <p>FCS time-series without artifact</p> </td> <td>...</td> </tr> <tr> <td>...</td> <td>...</td> <td>...</td> <td>...</td> <td>...</td> <td>...</td> <td>...</td> </tr> </tbody> </table> <p> </p>
Рис. 26. Сравнение среΑних значений частоты изменчивости эΛементов рисунка и инΑекса пигментации Mesobuthus eupeus в посеΛениях из разнотипных (А) и оΑнотипных (В) биотопов в кажΑой из выборок: I – Северо-ЗапаΑный Гобустан; II – Северо-Восточный Гобустан; III – ЦентраΛьный Гобустан; IV – Юго-Восточный Гобустан; V – Юго-Восточный Ширван. ИнΑекс корреΛяции r в преΑеΛах 0.744–0.989; p <0.05. Fig. 26. Comparison of the average values of the frequency of variability of pattern elements and the pigmentation index of Mesobuthus eupeus in conglomerations from habitats of different types (A) and of the same type (B) in each sample: I – northwestern Gobustan; II – northeastern Gobustan; III – central Gobustan; IV – southeastern Gobustan; V – southeastern Shirvan. Correlation index r = 0.744–0.989; p <0.05. in Materials on the colour pattern variability of Mesobuthus eupeus (C.L. Koch, 1839) (Arachnida: Scorpiones) in southeastern Shirvan and Gobustan (Eastern Azerbaijan)
Рис. 26. Сравнение среΑних значений частоты изменчивости эΛементов рисунка и инΑекса пигментации Mesobuthus eupeus в посеΛениях из разнотипных (А) и оΑнотипных (В) биотопов в кажΑой из выборок: I – Северо-ЗапаΑный Гобустан; II – Северо-Восточный Гобустан; III – ЦентраΛьный Гобустан; IV – Юго-Восточный Гобустан; V – Юго-Восточный Ширван. ИнΑекс корреΛяции r в преΑеΛах 0.744–0.989; p <0.05. Fig. 26. Comparison of the average values of the frequency of variability of pattern elements and the pigmentation index of Mesobuthus eupeus in conglomerations from habitats of different types (A) and of the same type (B) in each sample: I – northwestern Gobustan; II – northeastern Gobustan; III – central Gobustan; IV – southeastern Gobustan; V – southeastern Shirvan. Correlation index r = 0.744–0.989; p <0.05.
Adopted Ranking Methodology for Emerging National Importance Technical Institutions: A Correlation Analysis and Dominance of Research Performance Indicators
<p>The article presents the research performance of newly established technical institutes in India. It gives an overview of NTU and NIRF ranking methodologies. This research would help institutions to check their performance and identify ways to strengthen their rank by producing more output with high-impact research work. The article provides appropriate input to the technical institutions under the study to set out practical and pedagogical approaches, and cross-institutional as well as international collaboration to achieve their research goals. The article gives rank to the technical institutes under the study based on their research performance using the NTU ranking methodology.</p>
Figures 1–3 in Individual variation in the advertisement call of Aplastodiscus albosignatus (Anura: Hylidae) is correlated with body size and environmental temperature
Figures 1–3. Location of the study area: (1) map of Brazil highlighting the state of Paraná; (2) map of Paraná indicating the study area; (3) map of Paraná highlighting the physiognomy of the vegetation.
Noise Resistant Phase Imaging with Intensity Correlation
<p>Raw data for the arXiv:2301.11969 "Noise Resistant Phase Imaging with Intensity Correlation"</p> <p>Supported by the National Science Centre, Poland, grant number 2022/45/N/ST2/04249</p>
Data for: Probing visual sensitivity and attention in mice using reverse correlation
<p>Visual attention allows the brain to evoke behaviors based on the most important visual features. Mouse models offer immense potential to gain a circuit-level understanding of this phenomenon, yet, how mice distribute attention across features and locations is not well understood. Here, we describe a new approach to address this limitation, by training mice to detect weak vertical bars in a background of checkerboard noise while spatial cues manipulated their attention. By adapting a reverse correlation method from human studies, we linked behavioral decisions to stimulus features and locations. We show that mice voluntarily deploy attention to a small rostral region of the visual field. Within this region, mice attended to multiple features (orientation, spatial frequency, contrast) that indicated the presence of weak vertical bars. This attentional tuning grew with training, multiplicatively scaled behavioral sensitivity, approached that of an ideal observer, and resembled the effects of attention in humans. Taken together, we demonstrate that mice can simultaneously attend to multiple features and locations of a visual stimulus.</p>
Plane waves versus correlation-consistent basis sets: A comparison of MP2 non-covalent interaction energies in the complete basis set limit
<p>Supporting data and analysis scripts for the work</p> <p><a href="https://doi.org/10.26434/chemrxiv-2023-203z9">Plane waves versus correlation-consistent basis sets: A comparison of MP2 non-covalent interaction energies in the complete basis set limit</a></p>
Survival of juvenile Florida Scrub-Jays is positively correlated with month and negatively correlated with male breeder death
<p>Juvenile survival in birds is difficult to estimate, but this vital rate can be an important consideration for management decisions. We estimated juvenile survival of cooperatively breeding Florida Scrub-Jays (<em>Aphelocoma</em> <em>coerulescens</em>) in a landscape degraded by fire suppression and fragmentation using data from marked (n = 325) and unmarked juveniles (n = 1,306) with an integrated hierarchical Bayesian model. To assess the combined analyses, we also analyzed these datasets separately, with a Cormack–Jolly–Seber model (marked) and a young model (unmarked). Our data consisted of monthly censuses of territorial family groups from Florida Scrub-Jay populations in East Central Florida collected over a 22-year period. Juvenile survival was estimated from July when young Florida Scrub-Jays begin developing independence to March when they become first-year individuals and grouped according to the habitat quality class of their natal territory that were based on shrub height (with intermediate shrub heights being optimal and short and tall shrub heights being suboptimal) and the presence of sandy openings (the preferred open having many sandy openings; closed not having enough). Parameter estimates in the combined analysis were intermediate to the separate analyses. Notable differences among the separate analyses were that suboptimal habitat survival was lower in the unmarked analysis, the unmarked analysis showed a linear effect of time not seen in the marked analysis, and there was an effect of male breeder death in the marked but not unmarked analysis. The combined data analysis provided more inference than did either dataset analyzed separately including juveniles in optimal-closed territories unexpectedly had higher survival than those in optimal-open, survival increased through time, and male breeder death had a negative effect on survival. This study suggests that optimal-closed habitat may play an important role in juvenile Florida Scrub-Jay survival perhaps by providing better cover from predators and warrants further investigation for management implications.</p>
Data from: Correlation of Microstructure and Local Mechanical Properties Along Build Direction for Multi-layer Friction Surfacing of Aluminum Alloys
<p>This dataset contains the data for the publication " Correlation of Microstructure and Local Mechanical Properties Along Build Direction for Multi-layer Friction Surfacing of Aluminum Alloys".</p>
zEPHYR - Noise and performance correlation of a Savonius type vertical axis wind turbine.
The presented data set consists of noise measurement and performance characteristics obtained as a part of the experimental campaign in the Open Jet Facility (OJF) at Delft University of Technology. The observations have been recorded for a typical Savonius vertical axis wind turbine. Refer to the file "setup" for further experimental campaign details.
Data from: Transgression-regression cycles drive correlations in Ediacaran-Cambrian rock and fossil records
<p>Strata of the Ediacaran Period (635-538.8 Ma) yield the oldest known fossils of complex, macroscopic organisms in the geologic record. These "Ediacaran-type" macrofossils (known as the Ediacaran biota) first appear in mid-Ediacaran strata, experience an apparent decline through the terminal Ediacaran, and directly precede the Cambrian (538.8-485.4 Ma) radiation of animals. Existing hypotheses for the origin and demise of the Ediacaran biota include: changing oceanic redox states, biotic replacement by succeeding Cambrian-type fauna, and mass extinction driven by environmental change. Few studies frame trends in Ediacaran and Cambrian macroevolution from the perspective of the sedimentary rock record, despite well-documented Phanerozoic covariation of macroevolutionary patterns and sedimentary rock quantity. Here we present a quantitative analysis of North American Ediacaran–Cambrian rock and fossil records from Macrostrat and the Paleobiology Database. Marine sedimentary rock quantity increases nearly monotonically and by over a factor of five from the latest Ediacaran to the late Cambrian. Ediacaran–Cambrian fossil quantities exhibit a comparable trajectory and have strong (r<sub>s</sub> > 0.8) positive correlations with marine sedimentary area and volume flux at multiple temporal resolutions. Even so, Ediacaran fossil quantities are dramatically reduced in comparison to the Cambrian when normalized by the quantity of preserved marine rock. Although aspects of these results are consistent with the expectations of a simple fossil-preservation induced sampling bias, together they suggest that transgression-regression and a large expansion of marine shelf environments coincided with the diversification of animals during a dramatic transition that is starkly evident in both the sedimentary rock and fossil records.</p>
The neural correlates of embodied L2 learning Does embodied L2 verb learning affect representation and retention?
<p>We investigated how naturalistic actions in a highly immersive, multimodal, interactive 3D virtual reality (VR) environment may enhance word encoding by recording EEG in a pre/post-test learning paradigm. While behavior data has shown that coupling word encoding with gestures congruent with word meaning enhances learning, the neural underpinnings of this effect have yet to be elucidated. We coupled EEG recording with VR to examine whether “embodied learning” improves learning and creates linguistic representations that produce greater motor resonance. Participants learned action verbs in an L2 in two different conditions: Specific action (observing and performing congruent actions on virtual objects) and Pointing (observing actions and pointing to virtual objects). Pre and post-training participants performed a Match-mismatch task as we measured EEG (variation in the N400 response as a function of match between observed actions and auditory verbs) and a Passive listening task while we measured motor activation (mu (8-13 Hz) and beta band (13-30Hz) desynchronization during auditory verb processing) during verb processing. Contrary to our expectations, post-training results revealed neither semantic nor motor effects in either group when considered independently of learning success. Behavioral results showed both groups learned the verbs, but also a great deal of variability in learning success. When considering performance, Low performance learners showed no semantic effect and High performance learners exhibited an N400 effect for Mismatch vs Match trails post-training, independent of the type of learning. Taken as a whole, our results suggest that embodied processes can play an important role in L2 learning.</p>
Dataset: Parameter estimation by learning quantum correlations in continuous photon-counting data using neural networks
<p>Dataset for the paper E. Rinaldi, M. González Lastre, S. García Herreros, S. Ahmed, M. Khanahmadi, F. Nori, and C. Sánchez Muñoz (2023), <a href="https://arxiv.org/abs/2310.02309">¨Parameter estimation by learning quantum correlations in continuous photon-counting data using neural networks¨, arxiv: 2310.02309</a></p> <p>This dataset can be used to populate the [datapath] folder in the repository <strong>ParamEst-NN</strong> (<a href="https://github.com/CarlosSMWolff/ParamEst-NN">github.com/CarlosSMWolff/ParamEst-NN</a> ) and reproduce the results shown in the paper.</p> <p>The dataset consist of four folders:</p> <ol> <li><strong>Training trajectories.</strong> Records of quantum-jump trajectories simulated with the Monte-Carlo solver of the <a href="https://qutip.org/">QuTiP</a> library, used to train neural networks for the problem of quantum parameter estimation. The records consist of time delays between quantum jumps.</li> <li><strong>Models. </strong>Models trained with the training trajectories provided, and used to obtain the results shown in the paper.</li> <li><strong>Validation trajectories. </strong>Trajectories used to benchmark the trained models. For the 2D case, the same trajectories are provided as a single .npy file, and split in 10 separated batches inside a ```batches``` folder. These are the batches that we used to generate Bayesian estimations on a cluster using nested sampling (see README file of the <a href="http://github.com/CarlosSMWolff/ParamEst-NN">repository</a>).</li> <li><strong>Cached results. </strong>Here we provide pre-computed Bayesian estimations for the 2D multi-parameter estimation case using nested sampling.</li> </ol> <p> </p> <p><em>E.R. was supported by Nippon Telegraph and Telephone Corporation (NTT) Research during the early stages of this work.<br> C.S.M. acknowledges that the project that gave rise to these results received the support of a fellowship from “la Caixa” Foundation (ID 100010434) and from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No.847648, with fellowship code LCF/BQ/PI20/11760026, and financial support from the MCINN project PID2021-126964OB-I00 (QENIGMA) and the Proyecto Sinérgico CAM 2020 Y2020/TCS- 6545 (NanoQuCo-CM).</em></p>
Data for: Speciation in kleptoparasites of oak gall wasps often correlates with shifts into new tree habitats, tree organs, or gall morphospace
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Data from: Insights from a 31-year study demonstrate an inverse correlation between recreational activities and red deer fecundity, with body weight as a mediator
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Short-range correlation of stress chains near solid-to-liquid transition in active monolayers
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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.