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870 results for “Model development”
Data for the publication "Developing a climatological simplification of aerosols to enter the cloud microphysics of a global climate model" - part 1
<p>The data is split into two datasets, for each to be smaller than 50 GB.</p>
Data for "Leveraging a Disdrometer Network to Develop a Probabilistic Precipitation Phase Model in Eastern Canada"
<p><a name="_Toc157072893"></a><strong>Abstract</strong>. This study presents a probabilistic model that partitions the precipitation phase based on hourly measurements from a network of radar-based disdrometers in eastern Canada. The network consists of 27 meteorological stations located in a boreal climate for the years 2020-2023. Precipitation phase observations showed a 2-m air temperature interval between 0-4°C where probabilities of occurrence of solid, liquid, or mixed precipitation significantly overlapped. Single-phase precipitation was also found to occur more frequently than mixed-phase precipitation. Probabilistic phase-guided partitioning (PGP) models of increasing complexity using random forest algorithms were developed. The PGP models classified the precipitation phase and partitioned the precipitation accordingly into solid and liquid amounts. PGP_basic is based on 2-m air temperature and site elevation, while PGP_hydromet integrates relative humidity. PGP_full includes all the above data plus atmospheric reanalysis data. The PGP models were compared to benchmark precipitation phase partitioning methods. These included a single temperature threshold model set at 1.5°C, a linear transition model with dual temperature thresholds of –0.38 and 5°C, and a psychrometric balance model. Among the benchmark models, the single temperature threshold had the best classification performance due to a low count of mixed-phase events. The other benchmark models tended to over-predict mixed-phase precipitation in order to decrease partitioning error. All PGP models showed significant phase classification improvement by reproducing the observed overlapping precipitation phases based on 2-m air temperature. In terms of partitioning error, PGP_full had the lowest RMSE and the least variability in performance. The RMSE of the single temperature threshold model was the highest and showed the greatest performance variability. The improvement of mixed-phase prediction remains a challenge. This study establishes a basis for integrating automated phase observations into a hydrometeorological observation network and developing probabilistic precipitation phase models.</p>
Toward consumer-centric sustainability development model: A reverse logistics multi-criteria decision-making analysis datasets
<p>Toward consumer-centric sustainability development model: A reverse logistics multi-criteria decision-making analysis datasets</p>
Novel disease state model finds most juvenile green turtles develop and recover from fibropapillomatosis
<p>Fibropapillomatosis (FP) is a sea turtle disease characterized by benign tumor development on skin, eyes, and/or internal organs. It primarily affects juvenile green turtles (Chelonia mydas) in coastal foraging sites. The Indian River Lagoon (IRL), Florida, USA, is a coastal green turtle foraging site where the observed FP annual rate averaged 49% between 1983 and 2018. FP is not a major cause of sea turtle mortality and most individuals fully recover; however, the overall dynamics of this disease are poorly understood because prior disease history is unknown for individuals without FP at capture time, and future disease outcome is unknown for individuals with FP at capture time. To better evaluate FP dynamics for green turtles in the IRL, we developed a hierarchical model for predicting disease state change. We used data from 4,149 captures of 3,700 individual green turtles captured in the IRL. The hierarchical disease state model contained two levels: level one modeled whether an individual would develop FP, and level two modeled disease state progression, including states for pre-FP affliction, active FP affliction, and full recovery from FP. From the hierarchical model, we estimated 99.8% (95% credibility intervals 99.1-100%) of juvenile green turtles in the IRL developed FP, indicating that nearly every individual in the IRL is affected by this disease. The model also suggested that turtles quickly developed FP upon recruitment to the IRL and then recovered at different rates, with most completely recovering before emigrating from the IRL as they mature. This is the first analysis of long-term sea turtle data suggesting nearly every turtle in an aggregation both develops and recovers from FP.</p>
Data Archive: 2021 Development of a Virtual Diagnostic for the Advanced Particle Accelerator Modeling Code WarpX
<p><strong>A current promising field of research, laser-driven ion acceleration has the potential to reduce the size, cost, and energy consumption of particle accelerators by orders of magnitude.</strong></p> <p> </p> <p><strong>To better refine the instrumentation, we have developed a virtual diagnostic to measure electromagnetic radiation such as radiation produced from scattered and transmitted laser beams which has been implemented into WarpX, an advanced Particle-in-Cell code that simulates laser-driven particle acceleration. This “FieldProbe” diagnostic provides field measurements and is parallelized using the Message Passing Interface (MPI) and can thus run on High Performance Computing systems such as the NERSC Cori cluster.</strong></p>
Development of a machine learning model to predict non- durable response to anti-TNF therapy in Crohn's disease using transcriptome imputed from genotypes
<p>This is the expression value predicted using PrediXcan version 7 to find a gene feature that can distinguish between patients with and without effect on infliximab.</p> <p>Among the various tissue models provided by PrediXcan v7, three models were selected and used: whole blood, Colon transverse, and terminal ileum of small intestine, and the predicted gene counts of each model were 6,294, 5,612 and 3,107.</p> <p>For each of the three models, predicted gene expression values and phenotype information per sample were submitted.</p>
Development and implementation of a tool for measuring the training effectiveness of the patient-centered consultation model
<p><strong>Background:</strong> The patient-centered consultation model comprises four elements: exploring health, illness, and disease experiences, understanding the whole person, finding common ground, and enhancing the patient-doctor relationship. This method is taught at the course in general practice at Copenhagen University. The aim of the study was to develop a simple tool consisting of a questionnaire about the patient-centered elements and a test video consultation. The outcome is the change in the students’ ability to identify these elements. Used as a pre-course and post-course test it can inform the teachers which elements of the patient-centered consultation need intensifying in the teaching.<br> <strong>Methods:</strong> The students from a course in general practice volunteered to participate in all steps of the development. They took part in individual interviews to select items from an already existing questionnaire (DanSCORE). The preliminary questionnaire was tested for face and content validity, pilot-tested and tested for test-retest reliability. All video consultations were transcribed and assessed for patient-centered elements through a conversation analysis. The videos showed medical students seeing real patients.<br> <strong>Results:</strong> The preliminary version of the questionnaire (called DanOBS) <a href="#_msocom_1">[CM1]</a> <a href="#_msocom_2">[MJ2]</a> had 23 items. In the subsequent interviews, items were reduced to 17, each with three response options. After the pilot test, the questionnaire was further reduced to 13 items, all strictly relevant to the model and with two response options. The final questionnaire had acceptable test-retest reliability. The number of test consultation videos underwent a reduction from six videos to one.<br> <strong>Conclusions:</strong> The DanOBS combined with a test video consultation, used as a pre-and post-course test demonstrates for teachers which elements in the patient-centered consultation need to be intensified in the teaching.</p> <p> </p> <p> </p>
UF & UAB's Phase 2 Demonstration Study: Developing a Model to Support Transportation System Decisions considering the Experiences of Drivers of all Age Groups with Autonomous Vehicle Technology (Project A3)
<p>Enclosed you will find the data collected during our STRIDE Phase II research project (A3) and a data dictionary.</p>
Gastruloids as in vitro models of embryonic blood development with spatial and temporal resolution
<p>Rawdata (images and flow cytometry) for the manuscript "Gastruloids as in vitro models of embryonic blood development with spatial and temporal resolution". <br> </p>
Supplementary figures supporting the corrigendum on the PARASO Geoscientific Model Development paper
<p>Figures supporting the corrigendum to the PARASO GMD paper. In the original version of the code, the COSMO wind stress were not properly rotated from the COSMO grid to NEMO's. figure_windstress_fix.png provides an illustration of the bug, and the other figures are a selection of diagnostics performed with a fixed version of PARASO, sharing the same experimental design and numbering as the original paper.</p> <p><strong>Original paper</strong>: Pelletier, C., Fichefet, T., Goosse, H., Haubner, K., Helsen, S., Huot, P.-V., Kittel, C., Klein, F., Le clec'h, S., van Lipzig, N. P. M., Marchi, S., Massonnet, F., Mathiot, P., Moravveji, E., Moreno-Chamarro, E., Ortega, P., Pattyn, F., Souverijns, N., Van Achter, G., Vanden Broucke, S., Vanhulle, A., Verfaillie, D., and Zipf, L.: PARASO, a circum-Antarctic fully coupled ice-sheet–ocean–sea-ice–atmosphere–land model involving f.ETISh1.7, NEMO3.6, LIM3.6, COSMO5.0 and CLM4.5, Geosci. Model Dev., 15, 553–594, <a href="https://doi.org/10.5194/gmd-15-553-2022">10.5194/gmd-15-553-2022</a>, 2022.</p>
(c) simulation on Repast: after queen adaptive development-MODELING SELF-ORGANIZING SYSTEMS WITH SOCIAL INSECTS ALGORITHMS
<p>On figures (b) and (c), simulations on RePast [11, 16, 18] are<br> provided at successive times. The last figure shows the adaptive mechanism<br> of the queen which grows with time according to the material density around<br> it, like in natural observations.</p>
Figure 4 in Dactylorhiza Fuchsii (Druce) Soó As A Model Object In In Vitro Culture Study For Development Of Terrestrial Orchids
Figure 4. Root of D. fuchsii growing in the Figure 5. Root of D. fuchsii one year after exposition in NBG: arrow indicates elaborate transplanting ex vitro: arrow indicates some coiled structures known as pelotons of peloton-like structure as they do within the orchid mycorrhizal fungi in the root cortex (section was cells (section was stained with Trypan Blue; bar stained with Trypan Blue; bar = 50 mm) = 50 mm).
Figure 1 in Dactylorhiza Fuchsii (Druce) Soó As A Model Object In In Vitro Culture Study For Development Of Terrestrial Orchids
Figure 1. Development of Dactylorhiza fuchsii (Druce) Soó in vitro conditions: A – beginning of morphogenesis after germination with development of protocorms, characteristic for orchids; B – initialization of rooting; C – sterile plantlets after exposition at 2 °C in the dark, simulating the natural dormancy period; D – plantlet before transplanting ex vitro (ro – root; tu – tuber).
Figure 5 in Development of predictive models for determining fetal age-at-length in belugas (Delphinapterus leucas) and their application toward in situ and ex situ population management
Figure 5. Illustration of the linear relationships between fetal age and growth measurements of biparietal diameter (BPD: top graph), thoracic diameter (TD: middle graph) and thoracic circumference (TC: bottom graph) in belugas.
Figure 4 in Development of predictive models for determining fetal age-at-length in belugas (Delphinapterus leucas) and their application toward in situ and ex situ population management
Figure 4. Comparisons of regression curves of TL growth during the first (●) and second half (○) of gestation (top graph) and the early (●), mid (○) and late (▲) pregnancy (bottom graph). The slopes of the regression lines for first half of gestation (F = 63.31, P <0.0001, df1 = 1, df2 = 33) and for early (F = 50.05, P <0.0001, df1 = 1, df2 = 37) and mid pregnancy (F = 135.04, P <0.0001, df1 = 1, df2 = 32) were different than those for the second half of gestation and late pregnancy, respectively. Note that the animals double in length during late pregnancy (315–473 d).
Figure 3 in Development of predictive models for determining fetal age-at-length in belugas (Delphinapterus leucas) and their application toward in situ and ex situ population management
Figure 3. Individual growth rate data from three animals (Animal 1, 2, 3). Regression line slopes during the first two-thirds of pregnancy (top graph) were similar (F = 0.48, P = 0.62, df1 = 2, df2 =18), while regression slopes where different (F = 15.13, P = 0.03, df1 = 2, df2 =3) from the second half to term. Animal 1 (▲) did not have any TL data beyond the first half of gestation so TL length data were used from the farthest in gestation and then again at term. Note that while growth rates were similar during the first two-thirds of pregnancy, fetuses were already different in size when initially detected.
Figure 2 in Development of predictive models for determining fetal age-at-length in belugas (Delphinapterus leucas) and their application toward in situ and ex situ population management
Figure 2. Fetal growth curve comparison illustrating different growth rates resulting in wide range in estimated gestation length as compared to known gestation length determined in this study. Data from Heide-Jørgensen and Teilmann (1994; dotted line) predicts a gestation length of 310 d for a 150 cm calf and similar to our study used a 2nd order polynomial regression to describe their data. Kleinenberg et al. ([1964] 1969: dashed line) developed a curve of the average monthly embryo/fetal growth. They did not provide the curve, only the predicted age at TL, which we then used to fit to a growth curve, which predicts 150 cm calf as 338 d.
Figure 1 in Development of predictive models for determining fetal age-at-length in belugas (Delphinapterus leucas) and their application toward in situ and ex situ population management
Figure 1. Ultrasonographic images of beluga fetuses. All images have yellow caliper lines used to measure dimensions. Biparietal diameter (A, B) at two different stages of gestation show the ovoid shaped skull and echo produced from falx (arrows) located midline between the parietal bones (arrowheads). The thoracic diameter (C) as measured between the yellow caliper marks (arrowheads) on the lateral side of the fetal thorax (d1 = 6.66 cm) at the level of the heart (white arrow) and thoracic circumference (c = 24.04 cm) determined by using the elliptical measurement caliper function to include the dorsal to ventral diameter (d2 = 8.67 cm). The total length of a fetus (D) which is bent in utero, thus requiring the addition of two separate measurements (arrowheads), 1) 8.38 cm from the cranial most aspect of the skull to mid abdomen and 2) 6.91 cm from mid abdomen to distal most portion of the peduncle for a total length of 15.29 cm.
Fig. 7 in Simulation modelling as a decision support in developing a sterile insect-inherited sterility release strategy for Eldana saccharina (Lepidoptera: Pyralidae)
Fig. 7. The average Eldana saccharina larval infestation with the passage of time simulated for the SIT/IS pilot site near the Eston area of KwaZulu-Natal, South Africa with weekly releases commencing only in fields of age at most 6 mo at the start of the release. Time, t, is measured in days. The density, e/100s, is the number of borers, e, per 100 stalks of sugarcane. The graph shows that the average infestation level in the second yr of the control program is substantially reduced.
Fig. 5 in Simulation modelling as a decision support in developing a sterile insect-inherited sterility release strategy for Eldana saccharina (Lepidoptera: Pyralidae)
Fig. 5. The discretization of the spatial domain. On the lef a typical sugarcane field layout is illustrated with different colors representing crop age, and on the right the discretized domain corresponding to the area within the red square. This was done by transforming the spatial information obtained from the shapefiles to a matrix data structure in Matlab containing the entries '0', '1' and '2' denoting non-sugarcane patches, patches inside a field and edge patches, respectively. In the right half of the figure these data are represented by white, blue and green, respectively.
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.