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288 results for “Method development”
Data from: Rearing and sampling methods for estimating spruce budworm development rates at constant temperatures
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Raw data for Urine DNA (uDNA) as a non-lethal method for endoparasite biomonitoring: development and validation
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Figure 4 from: Horyn M, Logoyda L (2020) Bioanalytical method development and validation for the determination of metoprolol and meldonium in human plasma. Pharmacia 67(2): 39-48. https://doi.org/10.3897/pharmacia.67.e50397
Figure 4 Typical multiple reaction monitoring chromatograms of meldonium and internal standard in dipotassium ethylenediaminetetraacetic acid human blank plasma.
Figure 3 from: Horyn M, Logoyda L (2020) Bioanalytical method development and validation for the determination of metoprolol and meldonium in human plasma. Pharmacia 67(2): 39-48. https://doi.org/10.3897/pharmacia.67.e50397
Figure 3 Typical multiple reaction monitoring chromatograms of metoprolol and internal standard in dipotassium ethylenediaminetetraacetic acid human blank plasma.
Replication Package for the Paper: "A Machine Learning Based Ensemble Method for Automatic Multiclass Classification of Decisions: A Study of the Hibernate Developer Mailing List"
<p>This is the replication package for the paper: "A Machine Learning Based Ensemble Method for Automatic Classification of Decisions: A Study of the Hibernate Developer Mailing List". It contains the source code and dataset of our experiment for the replication by other researchers. In the meanwhile, we provide brief description of the files in the replication package below.</p> <p><strong>1. code folder</strong></p> <ul> <li><em>experiment.py </em>contains the source code for our experiment, which is conducted on Windows 10 and Python 3.7.0. <strong>Note that you may get slightly</strong> <strong>different experiment results when conducting the experiments on different environment configurations.</strong></li> <li><em>requirement.txt</em> records all the installation packages and their version numbers needed for the current program to run. You can use "<em>pip install -r requirement.txt</em>" to rebuild the project and install all dependencies. <strong>Note that you may get slightly different experiment results when using different packages or versions. </strong></li> </ul> <p><strong>2. dataset folder</strong></p> <ul> <li><em>decisions.xlsx </em>contains 844 labelled sentence-level decisions from the Hibernate developer mailing list.</li> </ul>
Figure 7 from: Piponski M, Balkanov T, Logoyda L (2021) Development and validation of a fast and simple HPLC method for the simultaneous determination of bisoprolol and enalapril in dosage form. Pharmacia 68(1): 69-77. https://doi.org/10.3897/pharmacia.68.e50919
Figure 7 Linearity illustrating chromatograms obtained using final established, optimized and validated chromatographic method, with 55% methanol. First peak is bisoprolol and second enalapril Dionex Ultimate 3000 UHPLC system.
Figure 6 from: Piponski M, Balkanov T, Logoyda L (2021) Development and validation of a fast and simple HPLC method for the simultaneous determination of bisoprolol and enalapril in dosage form. Pharmacia 68(1): 69-77. https://doi.org/10.3897/pharmacia.68.e50919
Figure 6 Chromatograms chracteristics obtained using final established optimized validated chromatographic method (upper run), compared with more reteaining with 10% less methanol (lower run), with their system suitabilitiy parameters,worked on Dionex Ultimate 3000 UHPLC system.
Figure 5 from: Piponski M, Balkanov T, Logoyda L (2021) Development and validation of a fast and simple HPLC method for the simultaneous determination of bisoprolol and enalapril in dosage form. Pharmacia 68(1): 69-77. https://doi.org/10.3897/pharmacia.68.e50919
Figure 5 Chromatogram obtained using Shimadzu Nexera XR UPLC system and mobile phase 50% metanol and 40% of 0.07% (V/V) perchloric acid, column Zorbax Rx C8 (4.6 mm i.d. × 250 mm, 5 μm), with 3-D UV contour diagram extracted ,analytes UV spectra and peak purity. First peak at about 6.1min is bisoprolol and peak at about 7.1min is enalapril.
Figure 3 from: Piponski M, Balkanov T, Logoyda L (2021) Development and validation of a fast and simple HPLC method for the simultaneous determination of bisoprolol and enalapril in dosage form. Pharmacia 68(1): 69-77. https://doi.org/10.3897/pharmacia.68.e50919
Figure 3 Elution profiles obtained for test samples prepared of bisoprolol+ enalapril tablets (10 + 10) mg using three different mobile phases: a) 55% metanol and 45% of 0.07% (V/V) perchloric acid; b) 40% metanol and 10% acetonitrile and 50% of 0.07% (V/V) perchloric acid; and c) 50% metanol and 50% of 0.07% (V/V) perchloric acid. First peak is bisoprolol and second enalapril. Chromatographic conditions: Shimadzu Nexera XR UPLC system, C-8 column Zorbax Rx (4.6 mm i.d. X 250 mm, 5 μm), flow rate 1.0 mL/min, column temperature 42 °C, injection volume 10 μL.
Figure 4 from: Piponski M, Balkanov T, Logoyda L (2021) Development and validation of a fast and simple HPLC method for the simultaneous determination of bisoprolol and enalapril in dosage form. Pharmacia 68(1): 69-77. https://doi.org/10.3897/pharmacia.68.e50919
Figure 4 Chromatogram obtained using Shimadzu Nexera XR UPLC system and mobile phase 55% metanol and 45% of 0.07% (V/V) perchloric acid, column Zorbax Rx C8 (4.6 mm i.d. × 250 mm, 5 μm), with 3-D UV contour diagram extracted, analytes UV spectra and peak purity. First peak at about 4.7min is bisoprolol and peak at about 5.2min is enalapril.
Figure 1 from: Proskurina K, Yevtifieieva O, Mala O, Mashtaler V (2021) Development of the method for standardization of the medicinal plant raw material of Cichorium intybus L. herb by the total amount of hydroxycinnamic acid derivatives. Pharmacia 68(1): 167-173. https://doi.org/10.3897/pharmacia.68.e49273
Figure 1 The TLC chromatogram of hydroxycinnamic acids in ethanolic extracts of different samples of chicory herb originating from Ukraine. S1–3: chlorogenic acid, caffeic acid and ferulic acid as references; for plant extracts, see abbreviations in Table 3.
Figure 2 from: Proskurina K, Yevtifieieva O, Mala O, Mashtaler V (2021) Development of the method for standardization of the medicinal plant raw material of Cichorium intybus L. herb by the total amount of hydroxycinnamic acid derivatives. Pharmacia 68(1): 167-173. https://doi.org/10.3897/pharmacia.68.e49273
Figure 2 The absorption spectrum of ethanol (50 per cent V/V) chicory herb extracts for 8 sample of the raw plant material. See abbreviations in Table 3. UV/Vis absorption spectra of chlorogenic acid chemical standard at 10.08 µg/ml in ethanol (50 per cent V/V).
Figure 3 from: Proskurina K, Yevtifieieva O, Mala O, Mashtaler V (2021) Development of the method for standardization of the medicinal plant raw material of Cichorium intybus L. herb by the total amount of hydroxycinnamic acid derivatives. Pharmacia 68(1): 167-173. https://doi.org/10.3897/pharmacia.68.e49273
Figure 3 Absorbance values of chlorogenic acid as a function of the solution concentrations. The data correlation was calculated by a linear fit.
Data from: The REporting of studies Conducted using Observational Routinely-collected health Data (RECORD) statement: methods for arriving at consensus and developing reporting guidelines
Objective: Routinely collected health data, collected for administrative and clinical purposes, without specific a priori research questions, are increasingly used for observational, comparative effectiveness, health services research, and clinical trials. The rapid evolution and availability of routinely collected data for research has brought to light specific issues not addressed by existing reporting guidelines. The aim of the present project was to determine the priorities of stakeholders in order to guide the development of the REporting of studies Conducted using Observational Routinely-collected health Data (RECORD) statement. Methods: Two modified electronic Delphi surveys were sent to stakeholders. The first determined themes deemed important to include in the RECORD statement, and was analyzed using qualitative methods. The second determined quantitative prioritization of the themes based on categorization of manuscript headings. The surveys were followed by a meeting of RECORD working committee, and re-engagement with stakeholders via an online commentary period. Results: The qualitative survey (76 responses of 123 surveys sent) generated 10 overarching themes and 13 themes derived from existing STROBE categories. Highest-rated overall items for inclusion were: Disease/exposure identification algorithms; Characteristics of the population included in databases; and Characteristics of the data. In the quantitative survey (71 responses of 135 sent), the importance assigned to each of the compiled themes varied depending on the manuscript section to which they were assigned. Following the working committee meeting, online ranking by stakeholders provided feedback and resulted in revision of the final checklist. Conclusions: The RECORD statement incorporated the suggestions provided by a large, diverse group of stakeholders to create a reporting checklist specific to observational research using routinely collected health data. Our findings point to unique aspects of studies conducted with routinely collected health data and the perceived need for better reporting of methodological issues.
PECULIARITIES OF ACTIVE LEARNING METHODS APPLICATION FOR EDUCATIONAL DEVELOPMENT
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DO ALFALFA PLANTING TIMES AND METHODS AFFECT WHEAT GROWTH AND DEVELOPMENT?
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Dataset for "Development and evaluation of a novel user-operated slider based audiometry method"
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Figure 3 from: Hasanuddin DNA, Garmana AN, Sasongko L (2024) HPLC method for the determination of nifedipine in rat plasma: development, validation, and application to pharmacokinetic drug-herb interaction study. Pharmacia 71: 1-6. https://doi.org/10.3897/pharmacia.71.e119198
Figure 3 A. Concentration-time (mean ± SD) and B. Natural logarithm-time (mean ± SD) of nifedipine in plasma after a single dose of nifedipine 1 mg/kg (n = 3) and co-administration of nifedipine with Gynura procumbens leaf extract 154 mg/kg (n = 3) in male Wistar rats.
Figure 1 from: Hasanuddin DNA, Garmana AN, Sasongko L (2024) HPLC method for the determination of nifedipine in rat plasma: development, validation, and application to pharmacokinetic drug-herb interaction study. Pharmacia 71: 1-6. https://doi.org/10.3897/pharmacia.71.e119198
Figure 1 HPLC chromatogram of nifedipine. A. Plasma sample spiked with 5 mL/mL of kaempferol; B. Nifedipine-free plasma; C. Plasma sample spiked with 1000 ng/mL of nifedipine.
Figure 2 from: Strus O, Fedorovska M, Holota S, Polovko N (2021) Development and validation of standardization methods of aqueous sapropel extract. Pharmacia 68(4): 933-939. https://doi.org/10.3897/pharmacia.68.e71783
Figure 2 The dependence of the concentration of the total mass fraction of HA on the mass of the ASE sample.
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.