We introduce an instrument for a wide spectrum of experiments on gravities other than our planet's. It is based on a large Atwood machine where one of the loads is a bucket equipped with a single board computer and different sensors. The computer is able to detect the falling (or rising) and then the stabilization of the effective gravity and to trigger actuators depending on the experiment. Gravities within the range 0.4 g-1.2 g are easily achieved with acceleration noise of the order of 0.01 g. Under Martian gravity, we are able to perform experiments of approximately 1.5 s duration. The system includes features such as WiFi and a web interface with tools for the setup, monitoring, and data analysis of the experiment. We briefly show a case study in testing the performance of a model Mars rover wheel in low gravities.
During the COVID−19 pandemic, the relevance of evaluating the effectiveness of face masks –especially those made at home using a variety of materials– has become obvious. However, quantifying mask protection often requires sophisticated equipment. Using a frugal stain technique, here we quantify the "ballistic" droplets reaching a receptor from a jet-emitting source which mimics a coughing, sneezing or talking human –in real life, such droplets may host active SARS−CoV−2 virus able to replicate in the nasopharynx. We demonstrate that materials often used in home-made face masks block most of the droplets. Mimicking situations eventually found in daily life, we also show quantitatively that less liquid carried by ballistic droplets reaches a receptor when a blocking material is deployed near the source than when located near the receptor, which supports the paradigm that your face mask does protect you, but protects others even better than you. Finally, the blocking behavior can be quantitatively explained by a simple mechanical model.
During the COVID-19 pandemic, the relevance of evaluating the effectiveness of face masks–especially those made at home using a variety of materials–has become obvious. However, quantifying mask protection often requires sophisticated equipment. Using a frugal stain technique, here we quantify the “ballistic” droplets reaching a receptor from a jet-emitting source which mimics a coughing, sneezing or talking human–in real life, such droplets may host active SARS-CoV-2 virus able to replicate in the nasopharynx. We demonstrate that materials often used in home-made face masks block most of the droplets. Mimicking situations eventually found in daily life, we also show quantitatively that less liquid carried by ballistic droplets reaches a receptor when a blocking material is deployed near the source than when located near the receptor, which supports the paradigm that your face mask does protect you, but protects others even better than you. Finally, the blocking behavior can be quantitatively explained by a simple mechanical model.
Recording time in invasive neuroscientific empirical research is short and must be used as efficiently as possible. Time is often lost due to long setup times and errors by the researcher. Minimizing the number of manual actions reduces both and can be achieved by automating as much as possible. Importantly, automation should not reduce the flexibility of the system. Currently, recording setups are either custom-made by the researchers or provided as a module in comprehensive neuroscientific toolboxes, and no platforms exist focused explicitly on recording. Therefore, we developed a lightweight, flexible, platform- and measurement-independent recording system that can start and record experiments with a single press of a button. Data synchronization and recording are based on Lab Streaming Layer to ensure that all major programming languages and toolboxes can be used to develop and execute experiments. We have minimized the user restrictions as much as possible and imposed only two requirements on the experiment: The experiment should include a Lab Streaming Layer stream, and it should be able to run from a command line call. Further, we provided an easy-to-use interface that can be adjusted to specific measurement modalities, amplifiers, and participants. The presented system provides a new way of setting up and recording experiments for researchers and participants. Because of the automation and easy-to-use interface, the participant could even start and stop experiments by themselves, thus potentially providing data without the experimenter's presence.
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