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5,573 results for “optimality”
Data from: Optimizing the detection of wakeful and sleep-like states for future electrocorticographic brain computer interface applications
Previous studies suggest stable and robust control of a brain-computer interface (BCI) can be achieved using electrocorticography (ECoG). Translation of this technology from the laboratory to the real world requires additional methods that allow users operate their ECoG-based BCI autonomously. In such an environment, users must be able to perform all tasks currently performed by the experimenter, including manually switching the BCI system on/off. Although a simple task, it can be challenging for target users (e.g., individuals with tetraplegia) due to severe motor disability. In this study, we present an automated and practical strategy to switch a BCI system on or off based on the cognitive state of the user. Using a logistic regression, we built probabilistic models that utilized sub-dural ECoG signals from humans to estimate in pseudo real-time whether a person is awake or in a sleep-like state, and subsequently, whether to turn a BCI system on or off. Furthermore, we constrained these models to identify the optimal anatomical and spectral parameters for delineating states. Other methods exist to differentiate wake and sleep states using ECoG, but none account for practical requirements of BCI application, such as minimizing the size of an ECoG implant and predicting states in real time. Our results demonstrate that, across 4 individuals, wakeful and sleep-like states can be classified with over 80% accuracy (up to 92%) in pseudo real-time using high gamma (70–110 Hz) band limited power from only 5 electrodes (platinum discs with a diameter of 2.3 mm) located above the precentral and posterior superior temporal gyrus.
Data from: Optimal nutrient exchange and immune responses operate in partner specificity in the cnidarian-dinoflagellate symbiosis
The relationship between reef-building corals and phototrophic dinoflagellates of the genus Symbiodinium is fundamental to the functioning of coral reef ecosystems. It has been suggested that reef corals may adapt to climate change by changing their dominant symbiont type to a more thermally tolerant one, although the capacity for such a community shift is potentially hindered by the compatibility of different host-symbiont pairings. Here we combined transcriptomic and metabolomic analyses to characterize the molecular, cellular, and physiological processes that underlie this compatibility, with a particular focus on Symbiodinium trenchii, an opportunistic, thermally tolerant symbiont that flourishes in coral tissues after bleaching events. Symbiont-free individuals of the sea anemone Exaiptasia pallida (commonly referred to as Aiptasia), an established model system for the study of the cnidarian-dinoflagellate symbiosis, were colonized with the "normal" (homologous) symbiont Symbiodinium minutum and the heterologous S. trenchii. Analysis of the host gene and metabolite expression profiles revealed that heterologous symbionts induced an expression pattern intermediate between the typical symbiotic state and the aposymbiotic state. Furthermore, integrated pathway analysis revealed that increased catabolism of fixed carbon stores, metabolic signaling, and immune processes occurred in response to the heterologous symbiont type. Our data suggest that both nutritional provisioning and the immune response induced by the foreign "invader" are important factors in determining the capacity of corals to adapt to climate change through the establishment of novel symbioses.
Data from: Evolution of ischemic damage and behavioural deficit over 6 months after MCAo in the rat: selecting the optimal outcomes and statistical power for multi-centre preclinical trials
Key disparities between the timing and methods of assessment in animal stroke studies and clinical trial may be part of the reason for the failure to translate promising findings. This study investigates the development of ischemic damage after thread occlusion MCAo in the rat, using histological and behavioural outcomes. Using the adhesive removal test we investigate the longevity of behavioural deficit after ischemic stroke in rats, and examine the practicality of using such measures as the primary outcome for future studies. Ischemic stroke was induced in 132 Spontaneously Hypertensive Rats which were assessed for behavioural and histological deficits at 1, 3, 7, 14, 21, 28 days, 12 and 24 weeks (n>11 per timepoint). The basic behavioural score confirmed induction of stroke, with deficits specific to stroke animals. Within 7 days, these deficits resolved in 50% of animals. The adhesive removal test revealed contralateral neglect for up to 6 months following stroke. Sample size calculations to facilitate the use of this test as the primary experimental outcome resulted in cohort sizes much larger than are the norm for experimental studies. Histological damage progressed from a necrotic infarct to a hypercellular area that cleared to leave a fluid filled cavity. Whilst absolute volume of damage changed over time, when corrected for changes in hemispheric volume, an equivalent area of damage was lost at all timepoints. Using behavioural measures at chronic timepoints presents significant challenges to the basic science community in terms of the large number of animals required and the practicalities associated with this. Multicentre preclinical randomised controlled trials as advocated by the MultiPART consortium may be the only practical way to deal with this issue.
Data from: Categorizing and assessing comprehensive drivers of provider behavior for optimizing quality of health care
<p>Inadequate quality of care in healthcare facilities is one of the primary causes of patient mortality in low- and middle-income countries, and understanding the behavior of healthcare providers is key to addressing it. Much of the existing research concentrates on improving resource-focused issues, such as staffing or training, but these interventions do not fully close the gaps in quality of care. By contrast, there is a lack of knowledge regarding the full contextual and internal drivers–such as social norms, beliefs, and emotions–that influence the clinical behaviors of healthcare providers. We aimed to provide two conceptual frameworks to identify such drivers, and investigate them in a facility setting where inadequate quality of care is pronounced. Using immersion interviews and a novel decision-making game incorporating concepts from behavioral science, we systematically and qualitatively identified an extensive set of contextual and internal behavioral drivers in staff nurses working in reproductive, maternal, newborn, and child health (RMNCH) in government public health facilities in Uttar Pradesh, India. We found that the nurses operate in an environment of stress, blame, and lack of control, which appears to influence their perception of their role as often significantly different from the RMNCH program's perspective. That context influences their perceptions of risk for themselves and for their patients, as well as self-efficacy beliefs, which could lead to avoidance of responsibility, or incorrect care. A limitation of the study is its use of only qualitative methods, which provide depth, rather than prevalence estimates of findings. This exploratory study identified previously under-researched contextual and internal drivers influencing the care-related behavior of staff nurses in public facilities in Uttar Pradesh. We recommend four types of interventions to close the gap between actual and target behaviors: structural improvements, systemic changes, community-level shifts, and interventions within healthcare facilities.</p>
The formulation of optimal mixtures with Generalized Disjunctive Programming: A solvent design case study
<p>The files contain all the formulations implemented in GAMS for this publication.</p> <p>All problems are solved in GAMS version 24.2.3 and are run on a single core of a dual 6 core Intel Xeon X5675 machine at 3.07 GHz.</p>
Designing Optimal Mixtures using Generalized Disjunctive Programming: Hull Relaxations
<p>The files contain all the mixture design problems implemented in GAMS for this publication.</p> <p>All problems are solved in GAMS version 24.2.3 and are run on a single core of a dual 6 core Intel Xeon X5675 machine at 3.07 GHz.</p>
ROS-specific Huntingtin Interactions: Oxidative Stress Optimization 3NP
<p>Optimization step in the lead up to mass spec identification of ROS-specific huntingtin protein-protein interactions.</p>
Optimization of global crop distribution could reduce greenhouse gas emissions by one third but requires expanding international trade
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Sub-optimal Drug Allergy Management Systems – a multi-national qualitative study
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Dipper Throated Optimization with Deep Convolutional Neural Network-based Crop Classification on Remote Sensing Image Analysis
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Data and Scripts for Anonymous et al. "How to optimally allocate sampling effort in experimental ecology"
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Dataset for manuscript: Boosting ensemble refinement with transferable force field corrections: synergistic optimization for molecular simulations
<p>See https://github.com/bussilab/force-field-ensemble-refinement for analysis scripts</p>
DETERMINATION OF PROFITABILITY OF AN ECONOMIC SUBJECT WITH THE HELP OF OPTIMIZATION OF FINANCIAL STATEMENTS ON THE BASIS OF INTERNATIONAL STANDARDS.
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Detection of PatIent-Level distances from single cell genomics and pathomics data with Optimal Transport (PILOT)
<p><strong>Datasets for PILOT</strong></p> <p>Although clinical applications represent the next challenge in single-cell genomics and digital pathology, we are still lacking computational methods for the analysis of single-cell and pathomics data at a patient level for finding patient trajectories associated with diseases. This is challenging as a single-cell/pathomics data is represented by clusters of cells/structures, which cannot be compared with other samples. We propose here patient Level analysis with Optimal Transport (PILOT). PILOT uses optimal transport to compute the Wasserstein distance between two single single-cell experiments. This allows us to perform unsupervised analysis at the sample level and to uncover trajectories associated with disease progression. Moreover, PILOT provides a statistical approach to delineate non-linear changes in cell populations, gene expression and tissues structures related to the disease trajectories. We evaluate PILOT and competing approaches in disease single-cell genomics and pathomics studies with up to 1.000 patients/donors and millions of cells or structures. Results demonstrate that PILOT detects disease-associated samples, cells, and genes from large and complex single-cell and pathomics data.</p>
Supplementary Materials for "Generating Cheap Representative Functions for Expensive Automotive Crashworthiness Optimization"
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Data Used for Article: Speeding up large wind farms layout optimization using gradients, parallelization, and a heuristic algorithm for the initial layout
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An Integrated Self-Optimizing Programmable Chemical Synthesis and Reaction Engine
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Figure 3 from: Nguyen N-VT, Nguyen CV, Duong NT, Dai X-TT, Nguyen KT, Le C-TT (2024) Optimization of ultrasound-assisted extraction using response surface methodology and quantification of polyphenol compounds in Avicennia officinalis L. from Vietnam. Pharmacia 71: 1-9. https://doi.org/10.3897/pharmacia.71.e115528
Figure 3 3D response surface curve showing the influences of independent variables on the TFC (A–F).
Figure 2 from: Nguyen N-VT, Nguyen CV, Duong NT, Dai X-TT, Nguyen KT, Le C-TT (2024) Optimization of ultrasound-assisted extraction using response surface methodology and quantification of polyphenol compounds in Avicennia officinalis L. from Vietnam. Pharmacia 71: 1-9. https://doi.org/10.3897/pharmacia.71.e115528
Figure 2 3D response surface curve showing the influences of independent variables on the TPC (A–F).
Figure 4 from: Nguyen N-VT, Nguyen CV, Duong NT, Dai X-TT, Nguyen KT, Le C-TT (2024) Optimization of ultrasound-assisted extraction using response surface methodology and quantification of polyphenol compounds in Avicennia officinalis L. from Vietnam. Pharmacia 71: 1-9. https://doi.org/10.3897/pharmacia.71.e115528
Figure 4 HPLC chromatogram of A. officinalis leaves extract. a Mobile phase solvent; b Solute sovent; c Extraction solvent; d Spiked sample; e Mixed standards solution; f Standard addition. (C1: Chlorogenic acid, C2: p-coumaric acid, C3: Sinapic acid, C4: Taxifolin, C5: Luteolin -7-O-glucoside, C6: Cinnamic acid).
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.