You can manually specify what resources your experiment will need when you Configure the online settings of your experiment. However, if you have a large number of files, we recommend you either Specify the files to download at the start using the Resource Manager Component or Specify the files to download each trial using Static Component.
Example use case: fetch a whole set of movies, possibly a custom list, for the participant while they read your instructions (i.e. within the experiment rather than at the start). You can start them loading before the first instructions screen and then make sure they have all downloaded before the trials actually begin. You could even load yor files in two sets - download a few files during instructions and then fetch the rest during practice trials!
While the automatic method is easy, it suffers if you have lots of resources (the participant sits waiting on that dialog box while the resources are fetched) or if each participant uses only a subset of resources. PsychoPy has a new Component called the Resource Manager Component that allows you to specify the files you need and the time you want them to start and/or confirm downloading.
If you request a file and it takes too long to arrive then the onset of the trial will occur at a different time. PsychoPy will pause and will take this in to account in its response times etc. but if you absolutely must have the stimulus appear at very regular times then you should make sure you download your stimuli a long way in advance (as above) or with a very generous time window to allow for slower connections.
For converting movies, you could use VLC Player. See this tutorial for instructions on how to convert multiple movies at once using VLC. To set up the output format correctly, we recommend making a new profile at step 4 in the tutorial above (see videoSettings):
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Liquid-handling robots have many applications for biotechnology and the life sciences, with increasing impact on everyday life. While playful robotics such as Lego Mindstorms significantly support education initiatives in mechatronics and programming, equivalent connections to the life sciences do not currently exist. To close this gap, we developed Lego-based pipetting robots that reliably handle liquid volumes from 1 ml down to the sub-μl range and that operate on standard laboratory plasticware, such as cuvettes and multiwell plates. These robots can support a range of science and chemistry experiments for education and even research. Using standard, low-cost household consumables, programming pipetting routines, and modifying robot designs, we enabled a rich activity space. We successfully tested these activities in afterschool settings with elementary, middle, and high school students. The simplest robot can be directly built from the widely used Lego Education EV3 core set alone, and this publication includes building and experiment instructions to set the stage for dissemination and further development in education and research.
Citation: Gerber LC, Calasanz-Kaiser A, Hyman L, Voitiuk K, Patil U, Riedel-Kruse IH (2017) Liquid-handling Lego robots and experiments for STEM education and research. PLoS Biol 15(3): e2001413.
The Lego Mindstorms EV3 Home Edition software (free download on Lego website: -us/mindstorms/downloads/download-software) was used to program the robots to run experiments. The software is based on LabView, a widely used commercial software. To upload code to the robot, a PC (Mac or Windows), tablet (iOS or Android), or smartphone (iOS or Android) is required. Building instructions were made with the free Lego software, Lego Digital Designer ( ). Both programs are available for PC and Mac. The control software is also available for iOS and Android.
Soviet troops entered the Auschwitz camp in Poland on January 27, 1945. This Soviet military footage shows children who were liberated at Auschwitz by the Soviet army. During the camp's years of operation, many children in Auschwitz were subjected to medical experiments by Nazi physician Josef Mengele.
Soviet troops entered the Auschwitz killing center in January 1945 and liberated thousands of sick and exhausted prisoners. This Soviet military footage was filmed shortly after the camp was liberated. It shows Soviet doctors examining victims of sterilization, poisonous injection, and skin graft experiments.
The Medical Case was one of 12 war crimes trials held before an American tribunal as part of the Subsequent Nuremberg Proceedings. The trial dealt with doctors and nurses who had participated in the killing of physically and mentally impaired Germans and who had performed medical experiments on people imprisoned in concentration camps. Here, chief prosecutor Brigadier General Telford Taylor reads into evidence a July 1942 report detailing Nazi high-altitude experiments and outlines the prosecution's goals for the trial.
The Medical Case was one of 12 war crimes trials held before an American tribunal as part of the Subsequent Nuremberg Proceedings. On trial were doctors and nurses who had participated in the killing of physically and mentally impaired Germans and who had performed medical experiments on people imprisoned in concentration camps. Here, concentration camp survivors Maria Kusmierczuk and Jadwiga Dzido, who had been victims of these experiments, show their injuries to the court as evidence.
The Medical Case was one of twelve war crimes trials held before an American tribunal as part of the Subsequent Nuremberg Proceedings. The trial dealt with doctors and nurses who had participated in the killing of physically and mentally impaired Germans and who had performed medical experiments on people imprisoned in concentration camps. Sixteen of the defendants were found guilty. Of the sixteen, seven were sentenced to death for planning and carrying out experiments on human beings against their will. Here, the court announces sentences for defendants Wilhelm Beigleboeck, Herta Oberhauser, and Fritz Fischer.
The movie emphasizes the idea of contextually supporting students. Typically, as students grow older and progress through the grade levels, the context in which academic tasks is presented is reduced. For example, as students advance in grade levels, they are expected to obtain new information from reading a textbook with fewer visual supports like pictures and diagrams. Students are required to gain new knowledge from classroom lectures and note-taking as opposed to learning with multiple modalities (e.g., pictures, graphs, charts, graphic organizers, word walls, gestures). Likewise, as students get older, the information they are expected to learn becomes more cognitively demanding.
We present Titta, an open-source toolbox for controlling eye trackers manufactured by Tobii AB from MATLAB and Python. The toolbox provides a wrapper around the Tobii Pro SDK, providing a convenient graphical participant setup, calibration and validation interface implemented using the PsychToolbox and PsychoPy toolboxes. The toolbox furthermore enables MATLAB and Python experiments to communicate with Tobii Pro Lab through the TalkToProLab tool. This enables experiments to be created and run using the freedom of MATLAB and Python, while the recording can be visualized and analyzed in Tobii Pro Lab. All screen-mounted Tobii eye trackers that are supported by the Tobii Pro SDK are also supported by Titta. At the time of writing, these are the Spectrum, Nano, TX300, T60XL, X3-120, X2-60, X2-30, X60, X120, T60 and T120 from Tobii Pro, and the 4C from Tobii Tech.
In this article, we therefore present Titta,Footnote 1 a Tobii- specific software package that allows for easy integration of Tobii eye trackers with experiments written in MATLAB with PsychToolbox (Pelli, 1997; Brainard, 1997; Kleiner et al., 2007) and in Python with PsychoPy (Peirce2007, 2009), while providing full access to all features of each of the supported eye trackers. Titta is built upon the C and Python versions of the low-level Tobii Pro SDK and, amongst other features, provides an easy to use participant setup, calibration and validation interface that is implemented directly in PsychToolbox or PsychoPy drawing commands. Titta can be integrated into existing experiments by adding only a handful of lines of code, but at the same time also enables access to all setup and operational features of the supported Tobii eye trackers. The PsychoPy version of Titta furthermore supports PsychoPy builder (Peirce et al., 2019), allowing easy integration of Tobii eye trackers in experiments built with this graphical experiment builder. Titta is available from (MATLAB) and -nystrom/Titta(Python).
To enable development of experiments using Titta and TalkToProLab without access to the eye tracker or the computer with the Tobii Pro Lab license, Titta and TalkToProLab implement a dummy mode. Dummy mode is activated by constructing an object of the TittaDummyMode and TalkToProLabDummyMode types, or, for Titta only, by calling Titta.setDummyMode(). In dummy mode, all the same functionality as for the regular class is available except that most functions do not do anything. When in dummy mode, these functions return empty values () in MATLAB and None in Python. An exception to this are the functions for reading from data streams in the Titta.buffer interface when data for the gaze stream is requested. In this case, a faked gaze sample reporting the current position of the mouse cursor is returned, to aid in implementation of gaze contingent experiments. 2b1af7f3a8