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621 results for “Methodology”
Standardization of Methodology of Light-to-Heat Conversion Efficiency Determination for Colloidal Nanoheaters
<p>Localized photothermal therapy (PTT) has been demonstrated to be a promising method of combating cancer, that additionally synergistically enhances other treatment modalities such as photodynamic therapy or chemotherapy. PTT exploits nanoparticles (called nanoheaters), that upon proper biofunctionalization may target cancerous tissues, and under light stimulation may convert the energy of photons to heat, leading to local overheating and treatment of cancerous cells. Despite extensive work, there is, however, no agreement on how to accurately and quantitatively compare light-to-heat conversion efficiency (ηQ) and rank the nanoheating performances of various groups of nanomaterials. This disagreement is highly problematic because the obtained ηQ values, measured with various methods, differ significantly for similar nanomaterials. In this work, we experimentally review existing optical setups, methods, and physical models used to evaluate ηQ. In order to draw a binding conclusion, we cross-check and critically evaluate the same Au@SiO2 sample in various experimental conditions. This critical study let us additionally compare and understand the influence of the other experimental factors, such as stirring, data recording and analysis, and assumptions on the effective mass of the system, in order to determine ηQ in a most straightforward and reproducible way. Our goal is therefore to contribute to the understanding, standardization, and reliable evaluation of ηQ measurements, aiming to accurately rank various nanoheater platforms.</p>
Text-fig. 1. Location of Wiesa fossil site in eastern Germany and other fossil sites for comparison. Explanation for map b: all fossil sites – black circles; grey circles – cities; topographic names in italics – German states (Länder). For bio- and lithostratigraphic data of fossil sites, see chapter Methodologies and material and Text-fig. 3. in Assessment Of Phytogeographic Reference Regions For Cenozoic Vegetation: A Case Study On The Miocene Flora Of Wiesa (Germany)
Text-fig. 1. Location of Wiesa fossil site in eastern Germany and other fossil sites for comparison. Explanation for map b: all fossil sites – black circles; grey circles – cities; topographic names in italics – German states (Länder). For bio- and lithostratigraphic data of fossil sites, see chapter Methodologies and material and Text-fig. 3.
Multidimensional impact assessment of a large collection of books using PlumX: methodology, technical limitations and indicators analysis [Complementary material to manuscript]
<p>The main purpose of this macro-study is to shed light on the broad impact of books. For this purpose, the impact a very large collection of books (more than 200,000) has been analysed by using PlumX, an analytical tool providing a great number of different metrics provided by various tools. Furthermore, the study focuses on the evolution of the most significant measures and indicators over time. The results show usage counts in comparison to the other metrics are quantitatively predominant. Catalogue holdings and reviews represent a book’s most characteristic measures deriving from its increased level of impact in relation to prior results. Our results also corroborate the long half-life of books within the scope of all metrics, excluding views and social media. Despite of some disadvantages, PlumX has proved to be a very helpful and promising tool for assessing the broad impact of books, especially because of how easy it is to enter the ISBN directly as well as its algorithm to aggregate all the data generated by the different ISBN variations.</p>
BRAIN Journal-Brain-Like Artificial Intelligence for Automation-Figure 4. Methodology in the Field of Brain-Like Artificial Intelligence for Automation
<p>An overview of the methodology for developing Brain-Like AI architectures for automation– as applied in the research of this article – is sketched in Figure 4.</p>
Diagramms and Figures for a Bachelor Thesis: "Morphological Diversity of Bryophytes: Methodological Approaches and Ecological Implications"
<p>This depository holds all diagramms and figures that were created with the collected data used in the Bachelor's Thesis using R Version 4.4.0 or Python Version 3.12.4. <br><br></p>
Dataset for: Methodology to identify and quantify flight path dependent bird strike scenarios over aircraft
<h1>ScenarioGenerator</h1> <h2>Description</h2> <p>This project is a Python project containing a demonstrations of the methodology developed by J. Bertholdt. <br>The code takes stl files and flight path data in order to create bird strike impact scenarios for each cell. <br>With this data it is possible to approximate the impact intensity and create heat maps over the geometry.</p> <h2>Features</h2> <p>- Data processing: The code creates scenarios (impact vector, angle, velocity and bird data) for hit areas and estimates peak pressure and total impulse. <br>- Data saving: The code saves the data in forms of csv files.<br>- Data reader: The code can read the csv files and recreate the processed data and mesh.<br>- Data visualization: The code contains examples for data filtering and plotting. </p> <h2>Installation</h2> <p>1. Download Code<br>2. Adjust directories in data_reader_demo.py and stl_processing_demo.<br>3. Create a virtual environment:</p> <h3>Required packages:</h3> <p>- numpy<br>- birdpressure<br>- matplotlib<br>- pyvista</p>
Supporting materials for the methodology for optimal combinations of agroecological practices (AEPs)
<p><span>The assessment framework is developed by first reviewing existing agroecological sustainability assessment tools. Indicators are collected based on literature review. Then they are synthesized into the holistic agroecology assessment framework. New indicators are developed during the project and are also used to address any context-specific data needs or cover gaps of the existing tools. </span></p>
Methodology for optimal combinations of agroecological practices (AEPs)
<table> <tbody> <tr> <td>The assessment framework is developed by first reviewing existing agroecological sustainability assessment tools. Indicators are collected based on literature review. Then they are synthesized into the holistic agroecology assessment framework. New indicators are developed during the project and are also used to address any context-specific data needs or cover gaps of the existing tools.<span> </span></td> </tr> </tbody> </table>
Fig. 5 in Comparison of sampling methodologies and estimation of population parameters for a temporary fish ectoparasite
Fig. 5. Histograms of emergence counts from the time-series emergence traps. Count bars for each day are subdivided by individual trap.
Fig. 4 in Comparison of sampling methodologies and estimation of population parameters for a temporary fish ectoparasite
Fig. 4. Scatterplot showing total body length in mm versus estimated volume of blood and plasma extracted in Ml. The box-and-whisker plots are centered on the mean body length for each of the three juvenile stages. The box edges are placed at the 2nd and 3rd quartiles for volume estimates and the whiskers show extreme minimum and maximum volumes. The mean estimate of extracted volume by juvenile stage is shown as a labeled dashed-red horizontal line. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
Fig. 1 in Comparison of sampling methodologies and estimation of population parameters for a temporary fish ectoparasite
Fig. 1. Traps used in the first study. (A) Small emergence trap, (B) fish-baited emergence trap, (C) fish-baited tripod, (D) open-mesh fish-baited trap and (E) lighted plankton trap. Note that the sample container holding a small French grunt fish for the fish-baited emergence trap (B) and the fish-baited tripod trap (C) are identical units other than the sealed floats attached to the top of the sample container when used with the fish-baited emergence trap.
Fig. 2 in Comparison of sampling methodologies and estimation of population parameters for a temporary fish ectoparasite
Fig. 2. Traps used in the second study. The lighted plankton trap, in the left foreground, stands on short legs—four large emergence traps can be seen in the middleground to the right of the lighted plankton trap. A second lighted plankton trap in the background can be seen towards the center of the frame.
Fig. 3 in Comparison of sampling methodologies and estimation of population parameters for a temporary fish ectoparasite
Fig. 3. Scatterplots of total body length in mm plotted against eye length in mm along the long axis. The upper plot shows measurements for zuphea and the lower plot for praniza. The body length cutoff values separating juvenile stages are shown as a dotted-green line. Gnathiids collected from emergence traps are seen as gold-filled squares and those collected from light traps are presented as purple-filled triangles. Differences in the ontological sampling bias of these two trap designs can be seen by comparing the two scatterplots. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
Fig. 6 in Comparison of sampling methodologies and estimation of population parameters for a temporary fish ectoparasite
Fig. 6. Histograms of trap counts by sample day and juvenile stage. The upper histograms show counts from emergence traps and the lower histograms show counts from light traps. Mean count for each histogram is shown as a dashed horizontal line. See text for an explanation of the number of sampling days shown in each plot.
Figure 3. Screenshot of the MQTT broker, publisher, and two subscribers.-Early Warning of Heat/Cold Waves as a Smart City Subsystem: A Retrospective Case Study of Non-anticipative Analog Methodology
<p>As it was mentioned above, IoT needs the appropriate lightweight protocols to transmit the<br> info because web-protocols (e.g. TCP) generate several times more traffic usually for IoT (e.g.<br> remote connection to the Arduino weather station). MQTT (Message Queuing Telemetry Transport)<br> and CoAP (Constrained Application Protocol) IoT protocols are mainly in use nowadays<br> (http://postscapes.com/internet-of-things-protocols). In this activity,Arduino Ethernet Shield and C#<br> console app are connected by MQTT Mosquitto open source software (http://mosquitto.org).Similar<br> work presented against https://iotguys.wordpress.com/2014/11/13/arduino-with-mqtt/.The activity<br> consists of the following steps:<br> 1. Download and installation of Mosquitto software gainst http://mosquitto.org/download/.<br> 2. Download and installation of the latest Arduino software against<br> http://arduino.cc/en/main/software.<br> 3. Development of the MQTT subscriber based on C programming language in Arduino<br> IDE.<br> 3. Development of the MQTT subscriber based on C# console app (laptop HP ProBook 650<br> G1 and Windows 10 are used) in Visual Studio.<br> Screen shot of the software is shown in Fig. 3.</p>
Figure 2. Screenshot of the Google Earth web-site's prototype on the visualization of heat/cold waves-Early Warning of Heat/Cold Waves as a Smart City Subsystem: A Retrospective Case Study of Non-anticipative Analog Methodology-
<p>A non-anticipative analog method consists of four main steps:<br> 1. Generation of the prediction rules.<br> 2. Analysis of the prediction rules. The rules with time slots, which are not concentrated at<br> the same frame, are excluded.<br> 3. Generation of possible extremes.<br> 4. Analysis of the generated possible extremes. The extremes with time slots, which do not<br> correspond to the time slots of the appropriate rules, are excluded.<br> The results of the heat/cold waves’ prediction from 2011 to 2014 at different locations<br> (places are selected randomly) are presented in Table 2.</p>
Figure 1. Azure management portal and VM with two Delphi desktop apps-Early Warning of Heat/Cold Waves as a Smart City Subsystem: A Retrospective Case Study of Non-anticipative Analog Methodology
<p><br> Nowadays, only D-Wave Systems Company produces commercially the 2nd generation<br> adiabatic quantum computer with up to 512 flux qubits (project code name ″Vesuvius″). They are<br> microscopic loops of niobium metal that are capable of quantum behavior at low temperatures.<br> Hence, electrical currents in the loops can flow in clockwise (+1) or counterclockwise (-1)<br> direction, or both, when in quantum superposition. Qubits are connected to neighbors according to<br> the topology of quantum processor. The hardware is controlled by a framework of Josephson<br> junctions that allow individual qubit values to be stored and read, and to influence the states of<br> neighboring qubits.</p>
BRAIN Journal-Image Finder Mobile Application Based on Neural Networks-Figure 3. The used methodology
<p>The training process we use in both trainings is based on neural networks, using the backpropgation algorithm. By using this algorithm, we are going to finally obtain the weights that will be used in our model to make the system recognize the input given by the user. </p> <p>Once the training for the hand drawn sketches is over, we are going to get weights that will be used to recognize any inputted hand drawn sketches. For example, if the user draws a tree, the system will be able to recognize what has been drawn as a tree, using the obtained weights from the neural networks. On the other hand, once the training for the real images is over, it means that if we provide our system with a real image, for example a tree, the system will be able to recognize it using the obtained weights from the training phase. </p>
BRAIN Journal-Image Finder Mobile Application Based on Neural Networks-Figure 1. Methodology used in the research by (Egmont-Petersen et al., 2002)
<p>Figure 1 shows the methodology used by Egmont-Petersen et al. (2002) to come up with an answer to their research question. Their study says that image recognition using neural networks goes through the stages shown in Figure 1. In our research we shall use this general proposed approach. </p>
BRAIN Journal-A Robust Approach of Facial Orientation Recognition from Facial Features-Figure 3. The methodology flowchart
<p>The methodology of our experimental method is described in Figure 3 below.</p> <p>It helps to write our code in C# and to make an application in dot net framework, which collects facial images using a webcam/or other video grabbing tools. Then it implements Haar detection to extract facial features and to draw image pattern for matching both images.</p>
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.