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122 results for “Monitoring methods”
Data from Yellow Sigatoka monitoring methods in the subtropical climate of southern Brazil
<h2>Description of the data and file structure</h2> <p>In this study four methods of disease monitoring were tested under field conditions: Biological Pre Warning (BPW); Stage of Evolution (SE); youngest Leaf Spotted (YLS); Infection Index (II). The BPW system evaluates the youngest leaves (2, 3, and 4), assigning a value for each type of lesion present, as well as for intensity of the lesion on the leaves (BUREAU et al., 1992). In the dataset is cited as the variable gross sum (points).</p> <p>The SE evaluates more leaves (1, 2, 3, 4, and 5) and scores only the most advanced symptoms of leaf disease, but without considering lesion intensity (GANRY et al., 2008). The SE calculation also corrects the gross sum of the disease according to leaf emission. The leaf emission rate was calculated using the Brun scale, which evaluates cigar leaf growth in decimals from 0.0 to 0.8. In the dataset is cited as the variable corrected gross sum (points).</p> <p>YLS is evaluated as the first leaf that has 10 spots with gray centers (CARLIER et al., 2003). In the dataset is cited as the variable YLS, which means the leaf position counted from the top to the botton of the plant (leaf number 3, leaf number 4...).</p> <p>Sigatoka Infection Index is quantified by assessing the severity of banana leaf disease using the Stover scale, with indexes from 0 to 50%, by means of the following formula: Infection Index =% (IF): [Σn × b / (N- 1) × T] × 100, in which: n = the number of leaves at each Stover scale level; b = degree according to the scale; N = the number of degrees employed in the scale (6); T = the total number of leaves evaluated (CARLIER et al., 2003). In the dataset is cited as the variable Infection index that should be understood like the severity of this leaf disease.</p> <p>In the second phase of the study, two monitoring methods were applied in commercial orchards in order to compare the standard model (Biological Pre-Warning – BPW) with the alternative method selected in the experimental phase (Youngest Leaf Spotted – YLS). The methods were applied, as described before in three sites in Criciúma (site 1) and Siderópolis (sites 2 e 3), municipalities in the southern coast of the state of Santa Catarina, from March 2016 to November 2018. During this period, 37 disease evaluations were performed at each location.</p> <p>Disease data of the experimental area were submitted to descriptive analysis and Pearson correlation at 5% probability of error. Disease progress curves were also plotted. The disease development data in commercial orchards were analyzed by plotting disease progress curves for BPW and by frequency distribution (%) for the YLS variable during all period of the experiment.</p>
Regional Estimates of Chemical Composition of Fine Particulate Matter Using a Combined Geoscience-Statistical Method with Information from Satellites, Models, and Monitors: V4.NA.02.MAPLE
<p>We estimate ground-level fine particulate matter (PM<sub>2.5</sub>) total and compositional mass concentrations over North America by combining Aerosol Optical Depth (AOD) retrievals from the NASA MODIS, MISR, and SeaWIFS instruments with the GEOS-Chem chemical transport model, and subsequently calibrated to regional ground-based observations of both total and compositional mass using Geographically Weighted Regression (GWR) as detailed in the provided reference for V4.NA.02. V4.NA.02.MAPLE further modified the V4.NA.02 GWR method with additional developments as part of the MAPLE (Mortality–Air Pollution Associations in Low-Exposure Environments) project. This adjustment was of particular value over low concentrations. The GWR method of individual components remains unchanged from V4.NA.02, but are provided are percentages to ensure mass closure and recommended to be applied to the V4.NA.02.MAPLE total PM<sub>2.5</sub>.</p> <p>Annual datasets are provided in NetCDF [.nc]. Gridded files use the WGS84 projection. Compositional estimates are provided for sulfate (SO4), nitrate (NO3), ammonium (NH4), organic matter (OM), black carbon (BC), mineral dust (DUST), and sea-salt (SS). Percentages are denoted with a ‘p’ after component identifiers within filenames. A slight change in file name has been included for 2017, corresponding to minor internal changes compared to earlier years. Overall, however, the dataset is consistent throughout its entire time period and can be appropriately used for trend analysis.</p> <p><strong>Reference:</strong><br> van Donkelaar, A., R. V. Martin, et al. (2019). <strong>Regional Estimates of Chemical Composition of Fine Particulate Matter using a Combined Geoscience-Statistical Method with Information from Satellites, Models, and Monitors.</strong> Environmental Science & Technology, 2019, doi:10.1021/acs.est.8b06392.</p>
Optimizing sampling across methods improves the power of ecological monitoring data
Transect-based monitoring has long been a valuable tool in ecosystem monitoring. These transects are often used to measure multiple ecosystem attributes. The line-point intercept (LPI), vegetation height, and canopy gap intercept methods comprise a set of core methods, which provide indicators of ecosystem condition. However, users struggle to design a sampling strategy that optimizes the ability to detect ecological change using transect-based methods. We assessed the sensitivity of these core methods on a one-hectare plot to transect length, number, and sampling interval to determine: 1) minimum sampling required to describe ecosystem characteristics and detect change for each method and 2) optimal transect length and number for all three methods to make recommendations for future analyses and monitoring efforts. We used data from 13 National Wind Erosion Research Network locations spanning the western US, which included 151 measurements over time across five biomes. We found that longer and increased numbers of transects were more important for reducing sampling error than increased sample intensity along transects. For all methods and indicators across plots, three 100-m transects reduced sampling error so that indicator estimates fall within an 95% confidence interval of +/- 5% for canopy gap intercept and LPI-total foliar cover, +/- 5 cm for height and +/- two species for LPI-species counts. For the same criteria at 80% confidence intervals, two 100-m transects are needed. Site-scale inference was strongly affected by sample design, consequently our understanding of ecological dynamics may be influenced by sampling decisions.
Data for Wang and Kent, GRL, 2021, "RESET: A method to monitor thermoremanent alteration in Thellier-series paleointensity experiments"
<p>This zip file contains data presented in the GRL paper “RESET: A method to monitor thermoremanent alteration in Thellier-series paleointensity experiments” by Wang and Kent, 2021. </p> <p>Folder “Figure2e” contains a subfolder that contains all the raw hysteresis measurements (with heated temperatures in degree Celsius in file names) and an Excel spreadsheet that summarizes the hysteresis parameters, which are used in plotting the Day diagram as shown in Figure 2e.</p> <p>Folder “Figure2f-s” contains raw FORC data of specimens GA79.5y and GA84.6y measured after each heating treatment (with heated temperatures in degree Celsius in file names) that are used in plotting the FORC diagrams as shown in Figure 2f to 2s.</p>
Data of microbiological decomposition monitoring of pine coniferous litter in the soils at the Moscow region by the ICP IM method
<p>Данные мониторинга микробиологического разложения хвойного опада сосны в почвах Московской области по методу ICP IM</p> <p>Data of microbiological decomposition monitoring of pine coniferous litter in the soils at the Moscow region by the ICP IM method</p> <p> </p> <p>Исследования проведены на базе двух особо охраняемых природных территориях (далее ООПТ) в Московской области и г. Москве, расположенных на расстоянии 90 км друг от друга. На обеих ООПТ работы проводились на постоянных пробных площадках (ППП) площадью 1 га.</p> <p>Эталон – Приокско-Террасный государственный природных биосферный заповедник. В заповеднике заложены 4 ППП, расположенные в бассейне малой реки Тоденка, большая часть бассейна которой находится в границах Заповедника. ППП расположены не далее 2 км от русла реки, в преобладающих по площади в ООПТ типах лесах: сосняке сложном (две ППП), березняке сложном широкотравном и дубраве широкотравной. В сосняках Заповедника были заложены 2 ППП, различающиеся по увлажнению и месторасположению, на террасе и на коренном берегу.</p> <p>Модельная находится под более высокой антропогенной нагрузкой в г. Москве с лесопарковая часть природно-исторического парка «Кузьминки-Люблино» (далее – Лесопарк), имеющая также схожий с Заповедником рельеф и породный состав лесов. Территории Заповедника и Лесопарка имеют сходство физико-географических условий формирования: обе ООПТ расположены на надпойменных террасах крупных рек Волжского бассейна (рек Оки и Москвы соответственно), на обеих территориях формируются слабо дифференцированные дерново-подзолистые почвы ржавоземы на флювиогляциальных песках (Brunic Arenosols) под сосновыми и березовыми лесами. Основные физико-химические свойства почв Лесопарка соответствуют естественным аналогам.</p> <p><strong>Метод изучения скорости разложения опада.</strong> Методической основой проводимых измерений скорости биоразложения опада является метод подпрограммы «MB Microbial decomposition» программы ICP IM [https://www.syke.fi/en-US/Research__development/Nature/Monitoring/Integrated_Monitoring/Manual_for_Integrated_Monitoring] с некоторыми изменениями.</p> <p>Изменения методики касались срока экспозиции. Мы использовали стандартный срок экспозиции в 1 год и отказались от экспозиции иголок более 1 года, как рекомендовано в методике ICP IM. Такая модификация метода позволила существенно сократить трудозатраты при получении сравнимых результатов.</p> <p>Измерение разложения опада проводились методом закладки конвертов из нейлоновой сетки 8 на 8 см с ячеей 1 мм с упакованными в них пробами на срок 1 год. Конверты запечатывались металлическими скобами. Пробы закладывались и снимались в последней декаде октября – начале ноября. В таблицах и тексте год указывается по году снятия образца, соответственно, пробы, заложенные в 2013 г. и собранные в 2014 г. относятся к 2014 г.</p> <p>Согласно методике, в экспериментах по изучению разложения опада использовались иголки сосны обыкновенной (<em>Pinus</em> <em>sylvestris</em> L.), которые собирались с ветвей невысоких деревьев (10–20 лет) в одном и том же квартале Заповедника и только пожелтевшие, перед их массовым опадом (обычно в начале октября). Предварительно все пробы высушивались до абсолютно сухого веса при 85 <sup>0</sup>С и взвешивались перед упаковкой в конверты. Взвешивание осуществлялось с точностью до 0.001 г, вес проб соснового опада 1 г.</p> <p>Конверты каждый год раскладывались на каждой ППП размерами 100×100 м возле углов и в центре пробных площадей в пределах квадрата 3×3 м в фиксированных точках. Конверты располагались в верхних 5 см почвы, под углом в 15<sup>0</sup>, под моховым покровом (при его наличии) или подстилкой и привязывались леской для удобства поиска. Не допускалось размещение конверта в приствольном круге деревьев. После экспозиции в течение 12 месяцев (350–380 суток) конверты снимались, а содержимое проб аккуратно с использованием пинцета промывалось дистиллированной водой от твердых частиц субстрата и мицелия грибов до остатков иголок и высушивалось до абсолютно сухого веса. Измерение потери массы каждой пробы проводилось методом взвешивания с точностью 0.001 г. Ежегодно закладывалось по 5 проб на каждой ППП в сосняке и березняке, но через год не всегда удавалось найти все заложенные конверты, так как происходили ветровалы и иные нарушения. На ППП в дубняке закладывалось по 10 конвертов.</p>
A comparison of density estimation methods for monitoring marked and unmarked animal populations
<p>These data were generated to compare different methods of estimating population density from marked and unmarked animal populations. We compare conventional live trapping with two more modern, non-invasive field methods of population estimation: genetic fingerprinting from hair-tube sampling and camera trapping for the European pine marten (Martes martes). We used arrays of camera traps, live traps, and hair tubes to collect the relevant data in the Ring of Gullion in Northern Ireland. We apply marked spatial capture-recapture models to the genetic and live trapping data where individuals were identifiable, and unmarked spatial capture-recapture (uSCR), distance sampling (CT-DS), and random encounter models (REM) to the camera trap data where individual ID was not possible. All five approaches produced plausible and relatively consistent point estimates (0.41 – 0.99 animals per km<sup>2</sup>), despite differences in precision, cost, and effort being apparent.</p> <p>In addition to the data, we provide novel code for running unmarked spatial capture-recapture (uSCR) and random encounter models (REM) to the camera trap data where individual ID was not possible. </p>
Comparison of methods to identify and monitor mold damages in buildings
<p>Molds thrive in indoor environments challenging the stability of building materials and occupants’ health. Diverse sampling and analytical techniques can be applied in microbiology of buildings with specific benefits and drawbacks. We evaluated the use of two methods, microscopy of visible mold growth (tape lifts) and DNA metabarcoding of mold and dust samples (swabs), for mapping mold-damage indicator fungi in buildings in Oslo. Overall, both methods provided consistent results for mold samples, where nearly 80% of the microscopy-identified taxa were confirmed by DNA analysis. <em>Aspergillus </em>was the most abundant genus colonizing all materials, while some taxa were associated with different substrates: <em>Acremonium </em>with gypsum board, <em>Chaetomium</em><em> </em>with chipboard, <em>Stachybotrys </em>with gypsum board and wood, and <em>Trichoderma</em> with wood. Based on DNA data, community composition was clearly different between mold and dust with a much higher alpha diversity in dust. Most genera identified in mold were also detected with a low abundance in dust from the same apartments. Their spatial distribution indicated some local spread from the mold growth to other areas, but there was no clear correlation between relative abundances and the distance to the damages. To study mold damages, different microbiological analyses (microscopy, cultivation, DNA and chemistry) should be combined with a thorough inspection of buildings. The interpretation of such datasets requires the collaboration of skilled mycologists and building consultants.</p>
Рис. 1. Схема мониторинговых станций на озере Кенон: 1–1.6 — ТЭЦ; 2–2.1 — КСК; 3 — Нефтебаза; 4 — Центр озера; 5 — КаΑаΛинка Fig. 1. Diagram of monitoring stations on Kenon lake: 1–1.6 — TPP; 2–2.1 — KSK; 3 — Tank farm; 4 — Lake Center; 5 — Kadalinka in Toxic pollution assessment of Chita TPP-1 cooling reservoir by applying the method of head capsule morphological deformations in chironomid larvae
Рис. 1. Схема мониторинговых станций на озере Кенон: 1–1.6 — ТЭЦ; 2–2.1 — КСК; 3 — Нефтебаза; 4 — Центр озера; 5 — КаΑаΛинка Fig. 1. Diagram of monitoring stations on Kenon lake: 1–1.6 — TPP; 2–2.1 — KSK; 3 — Tank farm; 4 — Lake Center; 5 — Kadalinka
Fig. 5 in Veterinary monitoring of gastrointestinal parasites in European bison, Bison bonasus designated for translocation: Comparison of two coprological methods
Fig. 5. The relationship between the prevalence of Eimeria spp. oocysts in European bison feces measured by the Willis and modified McMaster techniques (each point represents an individual parasite species).
Fig. 1 in Veterinary monitoring of gastrointestinal parasites in European bison, Bison bonasus designated for translocation: Comparison of two coprological methods
Fig. 1. Probability of detection of Eimeria spp. oocysts with the modified McMaster technique based on the number of oocysts detected using the Willis technique.
Fig. 4 in Veterinary monitoring of gastrointestinal parasites in European bison, Bison bonasus designated for translocation: Comparison of two coprological methods
Fig. 4. The relationship between the prevalence of various taxa eggs/oocysts in European bison feces measured by the Willis and modified McMaster techniques (each point represents an individual taxon/genus, blue points stand for oocysts and red point for eggs). (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Fig. 3 in Veterinary monitoring of gastrointestinal parasites in European bison, Bison bonasus designated for translocation: Comparison of two coprological methods
Fig. 3. Probability of detection of Trichostrongylidae eggs with the modified McMaster technique based on the number of eggs detected using the Willis technique.
Fig. 2 in Veterinary monitoring of gastrointestinal parasites in European bison, Bison bonasus designated for translocation: Comparison of two coprological methods
Fig. 2. Probability of detection of Trichuris sp. eggs with the modified McMaster technique based on the number of eggs detected using the Willis technique.
Anesthetic management of a case of pheochromocytoma using bioreactance method with Cheetah-NICOM monitor
<p><strong>Pheochromocytoma is a rare neoplasm originating from the chromaffin cells of the adrenal gland. The number of diagnosed and excised adrenal lesions has steadily increased over the last few decades. Contemporarily, improved monitoring systems and therapeutic advances have reduced mortality associated with this disease. During surgery the anesthesiologist must be ready to face sudden hemodynamic, metabolic and electrolyte fluctuations due to the release of catecholamines. In this Case Report, we describe a particularly complex anesthesiologic management of a large secretory lesion by using Cheetah Non-Invasive Cardiac Output Monitor (Cheetah-NICOM monitor), non-invasive hemodynamic monitoring system. A 72-year-old female patient was subjected to adrenalctomy after a diagnosis of an adrenal mass (5 cm) compatible with pheochromocytoma (highlighted by metanephrine dosage). Patient reports recurrent episodes of hypertensive crisis, sweating and precordial pain and was also affected by Type 2 diabetes mellitus. Adrenal surgery for pheochromocytoma results in a significant increase in heart rate and peripheral vascular resistance, which should therefore be monitored to guide the infusion of medicinal products. Although a preoperative preparation with Alpha and beta blockers was carried out, high doses of short-lived beta-blockers and alphalytic and vasodilator were required during the intervention. This case report shows that Cheetah-NICOM monitor allowed us to manage prompty and optimally the catecholaminergic storm and the volemic filling obtaining a rapid postoperative recovery.</strong></p>
A comparison of density estimation methods for monitoring marked and unmarked animal populations
Open the record for dataset details and reuse information.
Towards a method for monitoring the coupling evolution of microservice-based architectures
<p>Backup video for the presentation of the paper "Towards a method for monitoring the coupling evolution of microservice-based architectures", published in SBCARS - CBSoft 2020</p>
Data archive for the peer-reviewed journal article "Detailed characterization of the CAPS single scattering albedo monitor (CAPS PMssa) as a field-deployable instrument for measuring aerosol light absorption with the extinction-minus-scattering method"
<p>Data archive accompanying the peer-reviewed journal article "Detailed characterization of the CAPS single scattering albedo monitor (CAPS PMssa) as a field-deployable instrument for measuring aerosol light absorption with the extinction-minus-scattering method". In 2020 this article was accepted for publication in the journal <em>Atmospheric Measurement Techniques</em>. Data are uploaded in the form of ascii text files, Igor Pro experiment files (.pxp), and Jupyter notebook files. In addition, a Jupyter notebook file is included containing an implementation of the error model used in the paper.</p>
NuBe-DBBM: Numerical Benchmark for Drive-By Bridge Monitoring methods
<p>This repository contains an extensive dataset of numerically simulated vehicle responses crossing a range of bridge spans with various damage conditions. In addition, the dataset includes results for different road profile conditions, vehicle models, vehicle mechanical properties and speeds. The intention is to provide a useful resource to the research community that serves as a reference set of results for testing and benchmarking new developments in the field of drive-by bridge monitoring.</p> <p>The dataset is made of a collection of individual files, each containing results and information about single vehicle crossing events. The dataset provides results for different dimensions of the problem, which are: monitoring scenario (DSA, DSB), bridge spans (B09, B015, B21, B27, B33, B39), damage location (DL25, DL50), damage magnitude (DM00, DM020, DM40), vehicle model (V1, V2, V5), road profile (P00, PA1, PA2), and event number (E0001, E0002, …, E0800). In total, the dataset contains 518 400 separate files conveniently categorized into a system of subfolders. Each file contains the simulated responses from a 2D representation of the vehicle-bridge interaction problem in Matlab environment. The files here are in <em>.mat</em> format. Refer to the document <em>ReadMe.pdf</em> for extended explanations about the filing structure and file contents. In addition, an extended description of the dataset and numerical modelling can be found in the associated journal publication listed below.</p> <p>Cantero D, Sarwar Z, Malekjafarian A, Corbally R, Makki Alamdari M, Cheema P, Aggarwal J, Noh HY, Liu J. Numerical benchmark for road bridge damage detection from passing vehicles responses applied to four data-driven methods. Archives of Civil and Mechanical Engineering, Vol. 24, Article number 190, 2024.</p> <p>DOI: <a href="https://doi.org/10.1007/s43452-024-01001-9">https://doi.org/10.1007/s43452-024-01001-9</a></p>
Multi-method monitoring of rockfall activity along the classic route up Mont Blanc (4809ma.s.l.) to encourage adaptation by mountaineers
<p>The file Mourey et al._NHESS_2021_128.xlsx gathers the data used in the article "Multi-method monitoring of rockfall activity along the classic route up Mont Blanc (4809ma.s.l.) to encourage adaptation by mountaineers" at an hourly time scale. </p>
Comparison of Monitoring Methods during L-DED of Inconel 718
<p>Videos showing 4 different monitoring techniques during L-DED (BeAM Magic 2.0) of Inconel 718</p>
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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)
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.