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43 results for “loop analysis”
Figure 1. (a) Classical set and (b) Fuzzy set 2.3.-An Efficient Expert System Generator for Qualitative Feed-Back Loop Analysis
<p>A membership function is a curve that represents the degree of points which belong to the<br> specific fuzzy variable. Selecting the appropriate membership function plays an essential rule in<br> design of a fuzzy logic controller. The shape of membership function could be defined based on the<br> simplicity, convenience, speed and efficiency. Many different membership functions are introduced<br> in the literatures such as triangular, trapezoidal and Gaussian. The membership function which<br> represented in figure 1(b) is a trapezoidal type.</p>
Figure 2. Causal loop diagram for the problem situation-An Efficient Expert System Generator for Qualitative Feed-Back Loop Analysis
<p>The problem situation could be represented in the following form of a causal loop diagram<br> as shown in Figure 2.</p>
CTCF loop analysis and prediction scripts and datasets
<p>Additional files accompanying the study of experimental and predicted CTCF loops in human cell lines by Oti et al.</p> <p>ctcfloopscripts_v1.0.zip: Scripts used in the analysis of CTCF-mediated loops in human cell lines; both experimental ChIA-PET loops as well as predicted loops based on ChIP-seq data. Zipped file.</p> <p>ctcf_predictedloops_ENCODE_chipseq_datasets.tar.gz: Predicted CTCF loops for 100 ENCODE ChIP-seq datasets. Gzipped tar file.</p> <p>fimo_ctcfmotifs_MA0139_hg19_2.5e-4.bed.gz: genome-wide CTCF motifs in human genome (hg19) detected by FIMO tool.</p>
Binding of Cholesterol to the N-terminal Domain of the NPC1L1 Transporter: Analysis of the Epimerisation-Related Binding Selectivity and Loop Mutations
<p>Input files, topologies and trajectories of the work "Binding of Cholesterol to the N-terminal Domain of the NPC1L1 Transporter: Analysis of the Epimerisation-Related Binding Selectivity and Loop Mutations". </p>
Datasets for Insights into prismatic loop formation in irradiated Fe-Cr alloys from hypothesis-driven active learning and causal analysis
<p>Datasets for irradiated Fe-Cr alloys are collected from the experimental reports on dislocation loop type and dislocation density. We have constructed a data set from experimental literature containing 182 data points. To address such challenges to predict dislocation density, we have implemented a three-step ML approach as listed in the following:</p> <div> <div> <div> <ul> <li> <p>impute dataset to fill in the missing data to construct a predictive model using the RF regression algorithm. </p> </li> <li> <p>generate functionalized features and evaluate feature importance using the predictive model</p> </li> <li> <p>use the physics-based important functionalized features as hypotheses (physics-augmented GP models) in a hypothesis-driven active learning scheme to learn and predict dislocation density for all alloys. </p> </li> </ul> </div> </div> </div>
CERN PS Radial and Phase Loop Gain Analysis
<p>Dataset containing measurements and simulations of the PS radial and phase loop. These were used to determine the proportional gains, determining the conversion from measured radial or phase offset to frequency steering, of both loops.</p> <p>Contents:</p> <p><code>Kick_Data:</code> Measurements of the phase and radial loops. </p> <ul> <li><code>20degkick_staticphaseloop_C948_05(-2/-3).npz</code>: Measurements of the phase loop acting on a single bunch (normally sent to the East Area) around 948 ms cycle time. In these datasets, the RF phase is offset by 20 degrees without adjusting the target phase of the phase loop.</li> <li><code>40degkick_followingPL_C948_05(1-/-2/-3/-4).npz</code>: Measurements of the phase loop acting on a single bunch (normally sent to the East Area) around 948 ms cycle time. In these datasets, the RF phase is offset by 40 degrees while adjusting the target phase of the phase loop accordingly by 40 degrees.</li> <li><code>radial_loop_response_C910(-2/-3).npz</code>: Measurements of the radial loop acting on a single bunch (normally sent to the East Area) around 910 ms cycle time. In these datasets, the target radial offset is set from 13.6 mm to 0 at 910 ms cycle time</li> </ul> <p><code>Kick_Simulations:</code> Simulations reproducing the measurements for different values of the loop gains.</p> <ul> <li><code>2023_11_17.2-LoopsKick_finePL</code>: Simulations to reproduce the measurements in <code>20degkick_staticphaseloop_C948_05(-2/-3).npz</code> with different phase loop gains. (See arguments.txt, line 36 of each subfolder for the gain in each simulation)</li> <li><code>2023_11_17.2-LoopsKick_RL</code>: Simulations to reproduce the measurements in <code>radial_loop_response_C910(-2/-3).npz</code> with different radial loop gains. (See arguments.txt, line 36 of each subfolder for the gain used in each simulation.</li> </ul> <p><code>Plots:</code> Figures produced in the course of the analysis</p> <p><code>PSLoop_Technical_Info:</code> Documentation of the phase and radial loops and their developed models.</p> <p><code>PSLoop_GainDetermination.ipynb:</code> Python Notebook where the analysis is performed.</p>
Research data: "Effects of Network Structures on the Production Planning in Closed-loop Supply Chains – A Case Study based Analysis for Lithium-ion Batteries in Europe"
<p>This data set belongs to the paper Effects of Network Structures on the Production Planning in Closed-loop Supply Chains – A Case Study based Analysis for Lithium-ion Batteries in Europe in the International Journal of Production Economics (DOI). The BatPac model, as well as, the model for the economic assessment of the recycling route are not included. The needed data can be found in the file (name). Further, the BatPaC model can be gather from the website of Argonne National Laboratory and the assessment tool for the recycling routes via this DOI: 10.5281/zenodo.6500946.</p> <p> </p> <p>This work is part of the research project Recycling 4.0 (EFRE | ZW 6-85018080), which is funded by the European Regional Development Fund and managed by the development bank for the German federal state of Lower Saxony (NBank).</p>
Text-fig. 2. Scheme of position of primers on mtDNA D-loop (adopted from Gundry et al. 2007). in Genetic Analysis Of Possibly The Oldest Greyhound Remains Within The Territory Of The Czech Republic As Proof Of A Local Elite Presence At Chotěbuz-Podobora Hillfort In The 8 -9 Century Ad
Text-fig. 2. Scheme of position of primers on mtDNA D-loop (adopted from Gundry et al. 2007).
Thermal melting and smFET analysis of UUCG stem-loop
<p>Raw data generated for the purpose of the research project titled: "RNA adapts its flexibility to efficiently fold and resist unfolding".</p> <p> </p>
Data analysis results for: "MoDLE: High-performance stochastic modeling of DNA loop extrusion interactions"
<p>Due to technical issues we are unable to upload the updated version of this dataset on Zenodo.<br> <br> The latest version of this dataset can be found on the NRID research data archive at DOI <a href="https://doi.org/10.11582/2022.00056">10.11582/2022.00056</a>.</p>
N-TIMP2 CD loop extension NGS data and analysis script
<p><strong>NGS data and analysis script for the YSD sorts described in Bonadio et al. "Using designed loop extension and combinatorial screening to enhance specificity of a broad matrix metalloproteinase inhibitor"</strong></p>
Spot Urinary Analysis to Assess Loop Diuretic Efficiency in Stable Heart Failure
ClinicalTrials.gov study NCT02288819. IPD Sharing: NO. Countries: 1. Publications: 3.
Haplotype analysis of the mitochondrial DNA d-loop region reveals the maternal origin and historical dynamics among the indigenous goat populations in east and west of the Democratic Republic of Congo (DRC)
<p><span>This study aimed at assessing haplotype diversity and population dynamics of three Congolese indigenous goat populations that included Kasai goat (KG), small goat (SG), and dwarf goat (DG) of the Democratic Republic of Congo (DRC). The 1,169 bp <em>d-loop</em> region of mitochondrial DNA (mtDNA) was sequenced for 339 Congolese indigenous goats. The total length of sequences was used to generate the haplotypes and evaluate their diversities, whereas the hypervariable region (HVI, 453 bp) was analyzed to define the maternal variation and the demographic dynamic. A total of 568 segregating sites that generated 192 haplotypes were observed from the entire <em>d-loop</em> region (1,169 bp <em>d-loop</em>). Phylogenetic analyses using reference haplotypes from the six globally defined goat mtDNA haplogroups showed that all the three Congolese indigenous goat populations studied clustered into the dominant haplogroup A, as revealed by the Neighbor-joining (NJ) tree and median-joining (MJ) network. Nine haplotypes were shared between the studied goats and goat populations from Pakistan (1 haplotype), Kenya, Ethiopia and Algeria (1 haplotype), Zimbabwe (1 haplotype), Cameroon (3 haplotypes), and Mozambique (3 haplotypes). The population pairwise analysis (<em>F<sub>ST</sub></em>) indicated a weak differentiation between the Congolese indigenous goat populations. Negative and significant (<em>p</em>-value < 0.05) values for <em>F</em>u's <em>F</em>s (-20.418) and Tajima's (-2.189) tests showed the expansion in the history of the three Congolese indigenous goat populations. These results suggest a weak differentiation and a single maternal origin for the studied goats. This information will contribute to the improvement of the management strategies and long-term conservation of indigenous goats in DRC</span><span>.</span></p>
FIGURE 1 in Analysis of primary structure loops from Hairpins 35 and 48 of the Nematoda SSU rRNA gene provides further evidence that the genera Tripylina Brzeski, 1963, Trischistoma Cobb, 1913 and Rhabdolaimus de Man, 1880 are members of Enoplida
FIGURE 1. Localisation of synapomorphic molecular traits in 18S r RNA genes of Enoplida. A. Fragments of alignments of aligned gene sequences corresponding to SSU rRNA regions of hairpins 35 and 48. Presumed synapomorphies of Trichistoma, Tripylina and other Enoplida are marked and given a dark background. B. Secondary structures of Hairpin 35 of Loricera foveata. C. Secondary structures of Hairpin 35 of Trischistoma and Tripylina. Arrowed, 1280 A → G substitution. D. Secondary structures of Hairpin 48 of Loricea foveata. E. Secondary structures of Hairpin 48 of Trischistoma and Tripylina. Arrowed: 1820 G → Y substitution.
Rosetta Loop Modeling Data for "A Systematic Approach for Evaluating the Role of Surface-Exposed Loops in Trypsin-like Serine Proteases: Analysis of the 170 loop in Coagulation Factor VIIa"
<p>Rosetta Loop Modeling data for the publication "A Systematic Approach for Evaluating the Role of Surface-Exposed Loops in Trypsin-like Serine Proteases: Analysis of the 170 loop in Coagulation Factor VIIa." See the included readme.txt for more details. Please cite the paper if you use these data.</p>
All data support the published articel "Loop-optimization of Trichoderma reesei endoglucanases for balancing the activity–stability trade-off through cross-strategy between machine learning and the B-factor analysis"
<p><em>Trichoderma reesei</em> endoglucanases (EGs) have limited industrial applications due to its low thermostability and activity. Here, we aimed to improve the thermostability of EGs from<em> T.reesei</em> without reducing its activity counteracting the activity-stability trade-off. A cross-strategy combination of machine learning and B-factor analysis was used to predict beneficial amino acid substitution in EG loop optimization. Experimental validation showed single-site mutated EG concomitantly improved enzymatic activity and thermal properties by 17.21%–18.06% and 49.85%–62.90%, respectively, compared with wild-type EGs. Furthermore, the mechanism explained mutant variants had lower RMSD values and a more stable overall structure than the wild type. According to this study, EGs loop optimization is crucial for balancing the activity-stability trade-off, which may provide new insights into how loop region function interacts with enzymatic characteristics. Moreover, the cross-strategy between machine learning and B-factor analysis improved superior enzyme activity-stability performance, which integrated structure-dependent and sequence-dependent information.</p>
Haplotype analysis of the mitochondrial DNA d-loop region reveals the maternal origin and historical dynamics among the indigenous goat populations in east and west of the Democratic Republic of Congo (DRC)
Open the record for dataset details and reuse information.
Comparative transcriptome analysis by RNAseq of Necrotic Enteritis Clostridium perfringens in ligated intestinal chicken loops and in vitro conditions.
GEO Series GSE79456. Clostridium perfringens. 4 samples. Type: Expression profiling by high throughput sequencing.
Three-dimensional analysis of regulatory features reveals functional enhancer-associated loops
GEO Series GSE68858. Homo sapiens. 6 samples. Type: Genome binding/occupancy profiling by high throughput sequencing; Other.
Performance Analysis of Hermetic Closed-loop Anesthesia Delivery System
ClinicalTrials.gov study NCT05967403. IPD Sharing: NO. Countries: 1. Publications: 0.
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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)
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DANDI Archive for NWB datasets
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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.