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68 results for “meaningfulness”
Novel multi-omics deconfounding variational autoencoders can obtain meaningful disease subtyping
<h3>TCGA pan-cancer mRNA and DNA data augmented with artificial confounders utilised in "Novel multi-omics deconfounding variational autoencoders can obtain meaningful disease subtyping" by Zuqi Li and Sonja Katz (manuscript in preparation).</h3> <p>The following data curation steps were carried out: </p> <ul> <li><strong>Step 1. Download data from TCGA</strong> <ul> <li>R package `TCGAbiolinks`</li> <li>2547 patients (after step 2) with 6 cancer types: <ul> <li>BRCA (731)</li> <li>THCA (408)</li> <li>BLCA (387)</li> <li>LUSC (297)</li> <li>HNSC (412)</li> <li>KIRC (312)</li> </ul> </li> <li>mRNA expression profiles</li> <li>DNAm expression profiles</li> <li>Clinical data: <ul> <li>tumor stage: i, ia, ib, ii, iia, iib, iii, iiia, iiib, iiic, iv, iva, ivb, ivc, x</li> <li>age at diagnosis</li> <li>race: 'white', 'black or african amarican', 'asian', 'american indian or alaska native'</li> <li>gender<br><br></li> </ul> </li> </ul> </li> <li><strong>Step 2. Removal criteria</strong> <ul> <li>Patients with <ul> <li>NA or 'not reported' clinical data</li> <li>race 'american indian or alaska native'</li> <li>tumor stage x</li> </ul> </li> <li>mRNA and DNAm probes with <ul> <li>0 variance across all included patients</li> <li>not shared across all cancer types</li> <li>with missing values<br><br></li> </ul> </li> </ul> </li> <li> <strong>Step 3. Encode clinical vairables and save datasets</strong> <ul> <li>mRNA dataset: 2547 patients x 58,456 mRNAs</li> <li>DNAm dataset: 2547 patients x 232,088 DNAm</li> <li>clinic dataset: 2547 patients x 6 variables<br> 1. patient ID<br> 2. tumor stage: 1, 1, 1, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4<br> 3. age at diagnosis<br> 4. race: asian(1), black or african amarican(2), white(3)<br> 5. gender: female(0), male(1)<br> 6. cancer type: BRCA(1), THCA(2), BLCA(3), LUSC(4), HNSC(5), KIRC(6)<br> </li> </ul> </li> <li><strong> Step 4. Pre-process the datasets</strong> <ul> <li>mRNA dataset: '<em>TCGA_mRNAs_processed.csv'</em><br> <ul> <li>Take the 2000 mRNAs with highest variance</li> <li>Rescale every feature to [0,1]</li> <li>--> 2547 patients x 2000 mRNAs</li> </ul> </li> <li>DNAm dataset: <em>'TCGA_DNAm_processed.csv'</em><br> <ul> <li>Take the 2000 DNAm with highest variance</li> <li>Rescale every feature to [0,1]</li> <li>--> 2547 patients x 2000 DNAm</li> </ul> </li> <li>clinic dataset:<em> 'TCGA_clinic.csv'<br><br></em></li> </ul> </li> <li><strong>Step 5. Simulate confounders (instructions can be found in Methods section of manuscript)</strong> <ul> <li>Linear confounder: <ul> <li><em>'TCGA_confounder_linear.csv' -</em> linear confounding classes<em><br></em></li> <li><em>'TCGA_DNAm_confounded_linear.csv' </em>- linearly confounded DNAm data<em><br></em></li> <li><em>'TCGA_mRNA2_confounded_linear.csv' </em> - linearly confounded mRNA data<em><br></em></li> </ul> </li> <li>Squared confounder <ul> <li><em>'TCGA_confounder.csv' -</em> squared confounding classes<em><br></em></li> <li><em>'TCGA_DNAm_confounded.csv' </em>- squared confounded DNAm data<em><br></em></li> <li><em>'TCGA_mRNA2_confounded.csv' </em> - squared confounded mRNA data</li> </ul> </li> <li>Categorical confounder <ul> <li><em>'TCGA_confounder_categ2.csv' -</em> categorical confounding classes<em><br></em></li> <li><em>'TCGA_DNAm_confounded_categ2.csv' </em>- categorically confounded DNAm data<em><br></em></li> <li><em>'TCGA_mRNA2_confounded_categ2.csv' </em> - categorically confounded mRNA data</li> </ul> </li> <li>Multiple confounders - combined effect (linear + squared + categorical)<br> <ul> <li><em>'TCGA_confounder_multi.csv' -</em> confounding classes for combined effect<em><br></em></li> <li><em>'TCGA_DNAm_confounded_multi.csv' </em>- DNAm data with combined effect<em><br></em></li> <li><em>'TCGA_mRNA2_confounded_multi.csv' </em> - mRNA data with combined effect</li> </ul> </li> </ul> </li> </ul> <p> </p> <p> </p>
Neurophysiologically meaningful motor imagery EEG simulated data
<p><strong>Description</strong></p> <p>This dataset contains different sessions of artificially generated motor imagery electroencephalographic (MI-EEG)-like signals. The data was generated based on PySimMIBCI [1], a framework for generating realistic MI-EEG signals by integrating neurophysiologically meaningful activity into biophysical forward models.</p> <p>Specifically, MI was modeled by simulating an Event-Related Desynchronization (ERD) in the α band (9-11 Hz) over the contralateral motor area, representing the well-known brain dynamic during hand MI tasks. Right hand MI was differentiated from rest activity by a reduction in amplitude (ERD%) on the left hemisphere. For rest trials, idle α activity was simulated without ERD. The simulation includes three types of noise and artifacts: background noise, blink artifacts, and eye movement artifacts. For more information about the simulation process, please refer to [1].</p> <p>Different sessions were simulated, with each session representing different simulated scenarios:</p> <ol> <li> <p><strong>Self-Regulation Capabilities:</strong> To evaluate MI-BCI performance under different self-regulation capabilities, nine sessions were simulated with varying levels of ERD%, ranging from 50% to 10% in steps of 5%. These sessions reflect different user abilities to modulate α-band activity during MI, with higher ERD% indicating stronger MI modulation. The name of each session indicates the ERD% level, which was constant for all the trials of the session. For example, session <em>S_30</em> represents an ERD% of 30%. It is important to mention that in all the simulated sessions, the subject performed the task correctly in every trial, meaning no failed trials were included.</p> </li> <li> <p><strong>Varying MI Modulation:</strong> An MI vs. Rest session was generated where MI trials were simulated with an ERD% sampled from a uniform distribution from 10% to 50%. This session simulates trials with varying levels of MI modulation within the same BCI session, providing a more continuous representation of user performance fluctuations during MI-BCI tasks. The name of this session is <em>S_mix</em>.<strong> </strong>A list of the ERD% corresponding to each trial is included at the <em>S_mix_ERD_list.npy</em> file.</p> </li> <li> <p><strong>Fatigue-Related Artifacts: </strong>An additional MI vs. Rest session that shows the impact of non-MI-related cortical activity, specifically fatigue-related effects. Fatigue was simulated by increasing frontal θ and parietal α power across the course of the session, as described in [1]. The first half of the trials were fatigue-free, while the second half gradually incorporated increasing fatigue levels. The MI trials in this session were simulated with a fixed ERD% of 50% ensuring consistent modulation ability throughout the session. The name of this session is <em>S_fatigue</em>.</p> </li> </ol> <p>Each session contains 100 trials per class (MI vs. Rest), of 4s duration each, simulated at 41 electrodes following the 10-5 electrode system, with a sampling frequency of 1000 Hz. It is important to mention that in all simulated sessions, the task wask correctly performed in the 100% of the trials, meaning no failed trials were included.</p> <p><strong>File Format:</strong></p> <p>Epoched data are provided as <em>.fif </em>files. This data can be easily read by <em>mne.read_epochs</em> function from the MNE-Python library.</p> <p><strong>Potential Use Cases: </strong></p> <p>This dataset is suitable for testing hypothesis during MI-BCI algorithms development, specially to study the impact of subject self-regulation capabilities and non-MI-related cortical activity on BCI efficacy.</p> <p><strong>References:</strong></p> <p>[1] C. M. Galván, R. D. Spies, D. H. Milone and V. Peterson, "Neurophysiologically Meaningful Motor Imagery EEG Simulation With Applications to Data Augmentation," in IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 32, pp. 2346-2355, 2024, doi: 10.1109/TNSRE.2024.3417311.</p>
User-Led Meaningful Activity and Early-Stage Dementia
ClinicalTrials.gov study NCT05159869. IPD Sharing: UNDECIDED. Countries: 1. Publications: 4.
Data from: nlstimedist: an R package for the biologically meaningful quantification of unimodal phenology distributions
Phenological investigation can provide valuable insights into the ecological effects of climate change. Appropriate modelling of the time distribution of phenological events is key to determining the nature of any changes, as well as the driving mechanisms behind those changes. Here we present the nlstimedist R package, a distribution function and modelling framework that describes the temporal dynamics of unimodal phenological events. The distribution function is derived from first principles and generates three biologically interpretable parameters. Using seed germination at different temperatures as an example, we show how the influence of environmental factors on a phenological process can be determined from the quantitative model parameters. The value of this model is its ability to represent various unimodal temporal processes statistically. The three intuitively meaningful parameters of the model can make useful comparisons between different time periods, geographical locations or species' populations, in turn allowing exploration of possible causes.
Dataset for "All field emission experiments are noisy, ... are any meaningful ?"
<p>The dataset are in text format, the files to analyze and generate the figures are in jupyter format for python with a copy in pdf format.</p> <p>Description of files and folders :</p> <p>I) <strong>Data</strong></p> <p>This folder contains the different experimental I-V data</p> <p>II) <strong>Data analysis for a work function of 4.5eV</strong></p> <p>This file analyse the data in the "Data" folder and generates the files in the "<strong>Analyzed</strong>" folder.</p> <p>It includes also the data to plot Figure 2, 3, 5, 9 and 10.</p> <p>III) <strong>Data analysis for a work function of 5eV</strong></p> <p>This file analyse the data in the "Data" folder and generates the files in the "<strong>Analyzed5eV</strong>" folder.</p> <p>IV) <strong>Data analysis of the drift</strong></p> <p>This file analyse the data in the "Analyzed" and "Analyzed5eV" folders.</p> <p>It includes also the data to plot Figure 4 and 8.<br>V) <strong>Figure 6</strong></p> <p>This file analyse the data in ".\Analyzed\paramIV4d.txt".</p> <p>It plots Figure 6.</p> <p>VI) <strong>Figure 7</strong></p> <p>This file analyse the data in ".\Data\IV4d.txt".</p> <p>It plots Figure 7.</p> <p>VII) <strong>Generating noisy data</strong></p> <p>This file contains numerical simulations of I-V data with noise and generates the files in the "Generated_nosiy_data" folder.</p> <p>VIII) <strong>Plotting noisy data</strong></p> <p>This file plots Figure 11 and 12 from the data in the "Generated_nosiy_data" folder.</p>
Meaningful and physically consistent efficiency definition for positive displacement pumps - continuation of the critical review of ISO 4391 and ISO 4409
<p>ISO 4391:1984 gives the common efficiency definition for positive displacement machines. ISO 4409:2019 uses this efficiency definition to specify the procedure for efficiency measurements. If the machine conditions do not correspond with an incompressible flow due to operation at high pressure levels, the compressibility of the fluid and the dead volume of a pump must be taken into account. On this point, ISO 4391:1984 is physically inconsistent.</p> <p>Achten et. al. address this issue in their paper at FPMC 2019 presenting a critical review of ISO 4409:2007. They introduce new definitions of the overall efficiency as well as the mechanical-hydraulic efficiency. At the same time, they question the validity of the volumetric efficiency definition. Li and Barkei continue on this issue in their paper at FPMC 2020 and give a new efficiency definition based on the introduction of a new quantity Φ which describes the volume specific enthalpy of the conveyed fluid.</p> <p>The motivation of this paper is to contribute to the ongoing and fruitful discussion. Our approach starts with the most general efficiency definition, namely the isentropic efficiency. Subsequently, we make assumptions concerning the fluid properties with respect to the compressibility of the conveyed fluid. On the basis of the ideal cycle of a positive displacement pump and the p-v diagram, we derive physically consistent and more meaningful representations of the overall, the mechanical-hydraulic and the volumetric efficiency that address the inconsistency of ISO 4391:1984. Furthermore, we compare our findings with the existing results of Achten et. al. and Li and Barkei.</p>
Data from: Processing citizen science- and machine-annotated time-lapse imagery for biologically meaningful metrics
Time-lapse cameras facilitate remote and high-resolution monitoring of wild animal and plant communities, but the image data produced require further processing to be useful. Here we publish pipelines to process raw time-lapse imagery, resulting in count data (number of penguins per image) and 'nearest neighbour distance' measurements. The latter provide useful summaries of colony spatial structure (which can indicate phenological stage) and can be used to detect movement – metrics which could be valuable for a number of different monitoring scenarios, including image capture during aerial surveys. We present two alternative pathways for producing counts: 1) via the Zooniverse citizen science project Penguin Watch and 2) via a computer vision algorithm (Pengbot), and share a comparison of citizen science-, machine learning-, and expert- derived counts. We provide example files for 14 Penguin Watch cameras, generated from 63,070 raw images annotated by 50,445 volunteers. We encourage the use of this large open-source dataset, and the associated processing methodologies, for both ecological studies and continued machine learning and computer vision development.
Data on the Model of Loneliness and Smartphone Use Intensity as a Mediator of Self-Control, Emotion Regulation, and Spiritual Meaningfulness in Nomophobia
<p><em>The data collection was conducted in June-July 2022, with 355 participants completing the scales provided through offline paper-pencil surveys in the classroom. The research data was collected from three cities, namely Palembang, Jambi, and Yogyakarta, and consisted of junior high school and high school students, as well as university students. The university student participants were recruited from Ahmad Dahlan University, Jambi University, and Charitas Musi Catholic University. The participants completed the Nomophobia NMP-Q scale (Yildirim & Correia, 2015), the R-UCLA Loneliness Scale (Russell et al., 1980), self-control (Tangney, Baumeister & Boone, 2004), The Difficulties in Emotion Regulation Scale (DERS; Gratz & Roemer, 2004), and Spiritual Meaningfulness which was developed based on the theory of Pargament (2007). All the questionnaires for data collection were in the Indonesian version.</em></p>
Managing Cancer and Living Meaningfully (CALM) Therapy in Individuals Diagnosed With a Primary Brain Tumor
ClinicalTrials.gov study NCT04852302. IPD Sharing: YES. Countries: 1. Publications: 1.
Informing Policy to Implement Pediatric Family Engagement in Meaningful Use Stage 3
ClinicalTrials.gov study NCT01966068. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Managing Cancer and Living Meaningfully
ClinicalTrials.gov study NCT04646213. IPD Sharing: NO. Countries: 1. Publications: 1.
Data from: Processing citizen science- and machine-annotated time-lapse imagery for biologically meaningful metrics
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Data from: nlstimedist: an R package for the biologically meaningful quantification of unimodal phenology distributions
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Domestic dogs (Canis familiaris) recognise meaningful content in monotonous streams of read speech
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Commonly used Bayesian diversification methods lead to biologically meaningful differences in branch-specific rates on empirical phylogenies
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Acoustic indices perform better when applied at ecologically meaningful time and frequency scales
Abstract: 1. Acoustic indices are increasingly employed in the analysis of soundscapes to ascertain biodiversity value. However, conflicting results and lack of consensus on best practices for their usage has hindered their application in conservation and land-use management contexts. Here we propose that the sensitivity of acoustic indices to ecological change and fidelity of acoustic indices to ecological communities are severely impacted by signal masking. Signal masking can occur when acoustic responses sensitive to the effect being monitored are masked by less sensitive acoustic groups, or target taxa sonification is masked by non-target noise. We argue that by calculating acoustic indices at ecologically appropriate time and frequency bins, masking effects can be reduced and the efficacy of indices increased. 2. We test this on a large acoustic dataset collected in Eastern Amazonia spanning a disturbance gradient including undisturbed, logged, burned, logged-and-burned, and secondary forests. We calculated values for two acoustic indices: the Acoustic Complexity Index and the Bioacoustic Index, across the entire frequency spectrum (0-22.1 kHz), and four narrower subsets of the frequency spectrum; at dawn, day, dusk and night. 3. We show that signal masking has a large impact on the sensitivity of acoustic indices to forest disturbance classes. Calculating acoustic indices at a range of narrower time-frequency bins substantially increases the classification accuracy of forest classes by random forest models. Furthermore, signal masking led to highly misleading correlations, including spurious inverse correlations, between biodiversity indicator metrics and acoustic index values compared to correlations derived from manual sampling of the audio data. 4. Consequently, we recommend that acoustic indices are calculated either at a range of time and frequency bins, or at a single narrow bin, predetermined by a priori ecological understanding of the soundscape.
Data from: Cluster analysis successfully identifies clinically meaningful knee valgus moment patterns: frequency of early peaks reflects sex-specific ACL injury incidence
Background: Biomechanical studies of ACL injury risk factors frequently analyze only a fraction of the relevant data, and typically not in accordance with the injury mechanism. Extracting a peak value within a time series of relevance to ACL injuries is challenging due to differences in the relative timing and size of the peak value of interest. Aims/hypotheses: The aim was to cluster analyze the knee valgus moment time series curve shape in the early stance phase. We hypothesized that 1a) There would be few discrete curve shapes, 1b) there would be a shape reflecting an early peak of the knee valgus moment, 2a) youth athletes of both sexes would show similar frequencies of early peaks, 2b) adolescent girls would have greater early peak frequencies. Methods: N = 213 (39% boys) youth soccer and team handball athletes (phase 1) and N = 35 (45% boys) with 5 year follow-up data (phase 2) were recorded performing a change of direction task with 3D motion analysis and a force plate. The time series of the first 30% of stance phase were cluster analyzed based on Euclidean distances in two steps; shape-based main clusters with a transformed time series, and magnitude based sub-clusters with body weight normalized time series. Group differences (sex, phase) in curve shape frequencies, and shape-magnitude frequencies were tested with chi-squared tests. Results: Six discrete shape-clusters and 14 magnitude based sub-clusters were formed. Phase 1 boys had greater frequency of early peaks than phase 1 girls (38% vs 25% respectively, P < 0.001 for full test). Phase 2 girls had greater frequency of early peaks than phase 2 boys (42% vs 21% respectively, P < 0.001 for full test). Conclusions: Cluster analysis can reveal different patterns of curve shapes in biomechanical data, which likely reflect different movement strategies. The early peak shape is relatable to the ACL injury mechanism as the timing of its peak moment is consistent with the timing of injury. Greater frequency of early peaks demonstrated by Phase 2 girls is consistent with their higher risk of ACL injury in sports.
Data from: Effectiveness and meaningful use of paediatric surgical safety checklists and their implementation strategies: a systematic review with narrative synthesis
ObjectiveTo examine the effectiveness and meaningful use of pediatric surgical safety checklists (SSCs) and their implementation strategies through a systematic review with narrative synthesis. Summary Background Data Since the launch of the World Health Organization SSC, checklists have been integrated into surgical systems worldwide. Information is sparse on how SSCs have been integrated into the pediatric surgical environment. Methods A broad search strategy was created using Pubmed, Embase, CINAHL, Cochrane Central, Web of Science, Science Citation Index and Conference Proceedings Citation Index. Abstracts and full texts were screened independently, in duplicate for inclusion. Extracted study characteristic and outcomes generated themes explored through subgroup analyses and idea webbing. Results 1826 of 1921 studies were excluded after title and abstract review (kappa 0.77) and 47 after full-text review (kappa 0.86). 20 studies were of sufficient quality for narrative synthesis. Clinical outcomes were not affected by SSC introduction in studies without implementation strategies. A comprehensive SSC implementation strategy in developing countries demonstrated improved outcomes in high-risk surgeries. Narrative synthesis suggests that meaningful compliance is inconsistently measured and rarely achieved. Strategies involving feedback improved compliance. Stakeholder-developed implementation strategies, including team-based education achieved greater acceptance. Three studies suggest that parental involvement in the SSC is valued by parents, nurses and physicians, and may improve patient safety. Conclusions A SSC implementation strategy focused on pediatric patients and their families can achieve high acceptability and good compliance. SSCs' role in improving measures of pediatric surgical outcome is not well established but they may be effective when used within a comprehensive implementation strategy especially for high-risk patients in low-resource settings.
Data from: Low but significant genetic differentiation underlies biologically meaningful phenotypic divergence in a large Atlantic salmon population
Despite decades of research assessing the genetic structure of natural populations, the biological meaning of low yet significant genetic divergence often remains unclear due to a lack of associated phenotypic and ecological information. At the same time, structured populations with low genetic divergence and overlapping boundaries can potentially provide excellent models to study adaptation and reproductive isolation in cases where high-resolution genetic markers and relevant phenotypic and life history information are available. Here, we combined single nucleotide polymorphism (SNP)-based population inference with extensive phenotypic and life history data to identify potential biological mechanisms driving fine-scale subpopulation differentiation in Atlantic salmon (Salmo salar) from the Teno River, a major salmon river in Europe. Two sympatrically occurring subpopulations had low but significant genetic differentiation (FST = 0.018) and displayed marked differences in the distribution of life history strategies, including variation in juvenile growth rate, age at maturity and size within age classes. Large, late-maturing individuals were virtually absent from one of the two subpopulations, and there were significant differences in juvenile growth rates and size at age after oceanic migration between individuals in the respective subpopulations. Our findings suggest that different evolutionary processes affect each subpopulation and that hybridization and subsequent selection may maintain low genetic differentiation without hindering adaptive divergence.
The EEG and fMRI signatures of neural integration: An investigation of meaningful gestures and corresponding speech
<p>One of the key features of human interpersonal communication is our ability to integrate information communicated by speech and accompanying gestures. However, it is still not fully understood how this essential combinatory process is represented in the human brain. Functional magnetic resonance imaging (fMRI) studies have unanimously attested the relevance of activation in the posterior superior temporal sulcus/middle temporal gyrus (pSTS/MTG), while electroencephalography (EEG) studies have shown oscillatory activity in specific frequency bands to be associated with multisensory integration. In the current study, we used fMRI and EEG to separately investigate the anatomical and oscillatory neural signature of integrating intrinsically meaningful gestures (IMG; e.g. “Thumbs-up gesture”) and corresponding speech (e.g., “The actor did a good job”). In both the fMRI (<em>n</em>=20) and EEG (<em>n</em>=20) study, participants were presented with videos of an actor either: performing IMG in the context of a German sentence (GG), IMG in the context of a Russian (as a foreign language) sentence (GR), or speaking an isolated German sentence without gesture (SG). The results of the fMRI experiment confirmed that gesture–speech processing of IMG activates the posterior MTG (GG>GR∩GG>SG). In the EEG experiment we found that the identical integration process (GG>GR∩GG>SG) is related to a centrally-distributed alpha (7–13 Hz) power decrease within 700–1400 ms post-onset of the critical word. These new findings suggest that BOLD response increase in the pMTG and alpha power decrease represent the neural correlates of integrating intrinsically meaningful gestures with their corresponding speech.</p>
ScienceDex guides
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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.