MATLAB is first and foremost a scientific programming language, not an interactive environment. This software is provided by MathWorks as a one-stop-shop for numerical computation, simulation, and programming. MATLAB comes from the phrase "matrix laboratory," since it is both a multi-paradigm numerical computation environment and a proprietary programming language.
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FieldTrip is the MATLAB software toolbox for MEG, EEG and iEEG analysis, which is released free of charge as open source software under the GNU general public license. FieldTrip is developed by members and collaborators of the Donders Institute for Brain, Cognition and Behaviour at Radboud University, Nijmegen, the Netherlands.
Insect wings have also attracted much attention in the field of biomechanics. Considering the technical challenges associated with direct mechanical measurements on insect wings, many studies in this area have used finite element modelling2,4,20,21,22,23,24,25,26. Finite element software packages, such as SolidWorks, Abaqus and Catia, enable users to develop insect wings models manually. Considering that insect wings are not 2D planar structures but are somewhat wrinkled by intricate patterns of corrugations, which drastically influence their function27,28,29,30,31, manual modelling of wings is a time-consuming and error-prone process, even for an expert user. Hence, many previous efforts have resulted in the development of wing models with huge oversimplifications21,22,24,25,30,32,33,34. To the best of our knowledge, the only existing semi-automated tool for finite element modelling insect wings is our previous app, WingMesh35. However, WingMesh represents a significant drawback: the absence of control on the type and size of the produced mesh.
Over the last 25 years, EthoVision XT has evolved from video tracking software into a software platform. Designed to be at the core of your lab, EthoVision XT offers integration of data and automation of behavioral experiments with any animal.
Video tracking technology is versatile and we want you to have software that fits the bill for all of your experiments, from straight-forward protocols such as open field or Morris water maze testing to high-throughput protocols or the automation of optogenetics or operant conditioning tests.
In addition to tracking, EthoVision XT can also detect activity changes at pixel-level, ideal for studying behaviors such as freezing. You can also manually or automatically score behavioral events, such as rearing or grooming.
Want to know more about behavioral neuroscience? Check out our free downloadable e-book where we explain from A to Z why and how we measure certain behavior in rodents, what they translate to and how you can you put EthoVision XT to the most advantage in your research.
MathWorks is pleased to sponsor RoboNation Competitions 2023. MathWorks will provide software, training, and access to MathWorks engineering mentors and technical support to teams who have completed the Student Competition Software Request Form.
The programming language R is primarily used by statisticians and researchers to perform statistical analysis of datasets. Demographers, insurance actuaries, and other jobs focused on statistics use R. Because of these practical fields of application, its code mass is considerable. As with MATLAB, most of the knowledge needed to work with R relates to statistics. R programmers combine statistics knowledge with the essentials of programming and software development.
Visual Basic (VB) was introduced by Microsoft as a variant of the BASIC programming language. It is an event-driven language and Integrated Development Environment, primarily used to develop Windows applications. VB was designed to be easy to learn and to rapidly produce usable software. Visual Basic for Applications (VBA) is embedded in older versions of Microsoft Office applications, such as Access. VBA was used to provide programmatic manipulation of Office documents. Access databases used VBA to compose mini-applications.
Lua was developed in Brazil, during a time when trade policies made it prohibitively expensive to purchase licensed software from elsewhere in the world. It was designed to be portable and easy to learn for non-technical users. Lua has become popular among novice game developers as a scripting language.
From this page you can download the latest version of PicoScope Test & Measurement oscilloscope software, PicoLog data logging software, software development kits (SDK), brochures and manuals. If you do not own a Pico product you can download the software for the product you are interested in and run in demo mode.
Pico software is free to download and use. In return all we ask is that you complete this simple survey. The survey should only take about 30 seconds to complete and the information you provide helps us to keep improving our products.
MathWorks is pleased to sponsor the 2022 ROBO-ONE competition. MathWorks will provide software, training, and access to MathWorks engineering mentors and technical support to teams who have completed the Student Competition Software Request Form.
MathWorks is pleased to sponsor the 2023 DD-Robocon competition. MathWorks will provide software, training, and access to MathWorks engineering mentors and technical support to teams who have completed the Student Competition Software Request Form.
*Large amounts of free disk space and fast disk reading / writing is especially required for Process Metallurgy Module calculations. Using caching in TC-Python / TC-Toolbox also requires large amounts of free disk space.
In vivo magnetic resonance spectroscopy provides insight into metabolism in the human body. New acquisition protocols are often proposed to improve the quality or efficiency of data collection. Processing pipelines must also be developed to use these data optimally. Current fitting software is either targeted at general spectroscopy fitting, or for specific protocols. We therefore introduce the MATLAB-based OXford Spectroscopy Analysis (OXSA) toolbox to allow researchers to rapidly develop their own customised processing pipelines. The toolbox aims to simplify development by: being easy to install and use; seamlessly importing Siemens Digital Imaging and Communications in Medicine (DICOM) standard data; allowing visualisation of spectroscopy data; offering a robust fitting routine; flexibly specifying prior knowledge when fitting; and allowing batch processing of spectra. This article demonstrates how each of these criteria have been fulfilled, and gives technical details about the implementation in MATLAB. The code is freely available to download from
All of these data need to be processed (i.e. generate results), and to this end many different fitting software solutions have been developed, e.g., LCModel [6], jMRUI [7], TARQUIN [8], ProFit [9]. However, most fitting packages either aim to be a one-size-fits-all solution or to answer one specific problem, which necessarily limits the freedom of researchers investigating new MRS techniques. In order to get the most robust, accurate and useful results, the data processing strategy should be optimised for the chosen acquisition method.
Spectroscopy data can be visualised using the Spectro.PlotCsi GUI (see Fig 2). The GUI works for 1, 2 and 3D CSI, as well as single-voxel or non-localized data. The individual subplots show by default the image stacks that were in the viewer when the spectra were acquired. A red grid is overlaid that shows the location of the voxel or voxels acquired with the sequence, and the selected voxel is highlighted in red. Saturation bands can also be shown, highlighted in yellow. The perpendicular image stacks are shown in blue and green, with the current images highlighted. The contrast of each of the images can be adjusted, and a new stack of localizer images can be loaded interactively. There are buttons for calling the real and imaginary spectra and free-induction decays (FIDs) from the selected voxel, for turning CSI interpolation on and off, and for calling the fitting algorithm. The GUI tool currently assumes reconstructed Cartesian layout of voxels in real space.
We have developed a simple-to-use toolbox to visualise and process Siemens spectroscopy data in MATLAB. The toolbox allows the batch processing of single voxel spectra as well as 1D, 2D and 3D CSI datasets. It has an integrated fitting pipeline that can include additional prior knowledge. This toolkit will give researchers more freedom to rapidly develop customised fitting and processing pipelines best suited to their acquisition protocols. 2ff7e9595c
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