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Real-Time Audio Signal Processing with LabVIEW

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This implementation requires special software and hardware: LabVIEW from National Instruments—we used 2014 service pack 1—and a data acquisition card—we use the National Instruments PCI-6251 card on a PC with an Intel Core i5-4590 processor at 3.7GHz (a relatively low-end machine) with 24 gigabytes of RAM, running Microsoft Windows 8.1 Pro and Windows 10.
This implementation has several drawbacks: it requires expensive hardware and software from National Instruments (a data acquisition card and LabVIEW), Windows (we use hardware features of LabVIEW that are unavailable on MacOS or Linux), and due to the programming language it is difficult to modify and debug—indeed, a persistent bug in our implementation currently renders it substantially less accurate than the other detector implementations on some syllables. However, our test configuration proved itself capable of excellent performance, and further gains should be possible if the implementation were retargeted onto field-programmable gate array (FPGA) hardware—which would have the additional benefit of providing deterministic “hard realtime” guarantees—or just run on a faster desktop system.
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Reflective diSPIM Imaging Control Waveforms

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The control waveforms for implementing single- and dual-color 0.8/0.8 NA reflective diSPIM imaging are similar to those in our previous triple-view light-sheet imaging1 (link), except that excitation was usually introduced from one objective (i.e., we did not use alternating excitation, except for the comparative 0.8 NA/0.8 NA dual-view images and 1.1 NA/0.71 NA quadruple-view images shown in Fig. 4d). The waveforms include a step-wise waveform (e.g., 200 Hz/plane, 250 ms volume imaging rate for 50 planes) to drive the XY piezo stage, and two identical external trigger signals to simultaneously trigger the two sCMOS cameras. Programs controlling DAQ waveforms were written in Labview (National Instruments) and programs controlling image acquisition (via PCO sCMOS cameras) were written in the Python programming language.
The control waveforms for implementing single-color 1.1/0.71 NA reflective diSPIM imaging are similar to those used in our fiber-coupled diSPIM14 (link), and include a step-wise waveform to drive the XY piezo stage and two external trigger signals to sequentially trigger the two sCMOS cameras. Programs controlling DAQ waveforms and Hamamatsu sCMOS image acquisition were both written in Labview (National Instruments). All software programs are available upon request. Supplementary Table 3 summarizes data acquisition parameters used in this work.
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High-Resolution TIMS-MS Proteomics Workflow

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Experiments were performed using a custom TIMS analyzer coupled to a maXis Impact Q-UHRToF instrument (Bruker Daltonics Inc., Billerica, MA). [47] Briefly, TIMS separation is based on using an electric field to hold the ions stationary against a moving gas flow. [48, 49] The separation in a TIMS cell works by the center of the mass frame using the same principles as in a conventional IMS drift tube. The. Data acquisition was controlled using an in-house software, written in National Instruments Lab VIEW (2012, version 12.0f3) and synchronized with the maXis Impact acquisition program. TIMS separation was performed using nitrogen as a bath gas at 300 K, and typical P1 and P2 values were 2.5 and 0.9 mbar, respectively. [50] An 880 kHz radiofrequency and 200-350 Vpp was applied to the TIMS entrance funnel, analyzer section, and exit funnel. A custom-built, nano electrospray ionization source was coupled to the TIMS-TOF MS and further used for all experiments. A typical source voltage of 600-1200 V (positive ion mode) was applied. Both mass and mobility calibrations were performed using Tuning Mix calibration standard (G24221A, Agilent Technologies, Santa Clara, CA). The TIMS operation was controlled using an in-house software, written in National Instruments Lab VIEW, and synchronized with the maXis Impact Q-ToF acquisition program.
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Sound-Evoked Potential Recordings from Antennal Nerve

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Sound-evoked potential (SEP) recordings were performed from the antennal nerve as described (Eberl and Kernan 2011 (link)). Briefly, using a custom LabView (National Instruments) virtual instrument, computer-generated pulse song was delivered frontally from a loudspeaker in the near field to the fly's head through Tygon tubing. Electrolytically sharpened tungsten electrodes were inserted—one dorso–medially between the first and second antennal segments, and the second as a reference electrode penetrating the dorsal head cuticle. Differential signals were amplified 1000×, filtered with a 10-Hz low filter to stabilize the baseline, digitized with a USB-6001 (National Instruments) data acquisition module, and recorded in the LabView virtual instrument. Amplitudes are measured from the average of 10 consecutive recordings from each antenna. Flies of different genotypes were recorded in alternate order to minimize systematic variations. Statistical analysis used pairwise t-tests, with Welch's correction applied when variances were unequal.
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Treadmill-based Optical Stimulation and Behavior Tracking

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The forward and backward movement increments of the treadmill were monitored using two pairs of LED and photosensors that read patterns on a disc coupled to the treadmill wheel, while the zero position was implemented by an LED and photosensor couple detecting a small hole on the belt. From these signals, the mouse position was implemented in real time by an Arduino board (Arduino Uno, arduino.cc), which also controlled the valves for the reward delivery. Position, time and reward information from the Arduino board was sent via USB serial communication to a computer and recorded with custom-made LabView (National Instruments) programs.
To deliver the photostimuli, a blue diode laser (Vortran Laser Technology, StradusTM 473) was divided and collimated into 4 optical fibers (Thorlabs HPSC10-CUSTOM) using fiber ports (Thorlabs, PAFA-X-4-A). The optical fibers were connected to the electrodes’ fibers via LC connectors (single mode LC ferrule, Precision Fiber Products Inc). The waveform of the light stimulus was controlled using LabView (National Instruments) and a USB Interface Board (Intan Technologies, RHD2000) communicating with the analog port of the laser.
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Simultaneous TPF and SHG Imaging of Neuronal Membrane Potential

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Neurons loaded with Ap3 or FM4-64 were illuminated using a 950-nm laser, and TPF and SHG signals were simultaneously collected. In the frame-scan mode, the membrane potential of neurons was manipulated frame by frame in a sequential manner under current clamp (Fig. 5c) using custom-made software (LabVIEW, National Instruments) at 0.2 Hz. In the point-scan recordings, 40-ms-long laser pulses were applied to the target position at 2 Hz up to 100 times using FV10ASW multipoint-scan module (Olympus), and voltage or current pulses were delivered to neurons in every other laser pulse with a 10-ms delay after the start of laser illumination. SHG signals from the PMT were continuously recorded by a data acquisition board (National Instruments) together with electrophysiological signals at 3 kHz using custom software (LabVIEW, National Instruments) after 1 kHz low pass filter using an isolation amplifier (NF Corporation). Data were collected in a randomized order to avoid any systematic changes among groups.
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Multimodal Signal Acquisition and Analysis

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A custom built program written in LabVIEW (National Instruments) was used for signal recording. Data analysis was carried out using LabVIEW (National Instruments) and MATLAB (MathWorks) dedicated scripts, and Origin 2018 (OriginLab Corp., Northampton, MA, USA) and Igor Pro 8 (WaveMetrics, Portlan, OR, USA) software.
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Cardiorespiratory Responses to Mild Intermittent Protocol

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Minute ventilation, breathing frequency, inspiratory and expiratory time and tidal volume were collected on a breath-by-breath basis using commercially available software (LabVIEW, National Instruments, Austin, TX, United States) on each day of the protocol. Similarly, heart rate and oxygen saturation were monitored using a pulse oximeter, along with an electrocardiogram on each day of the protocol. Beat to beat blood pressure was measured using a Finapres on Day 5 and Day 19 of the mild intermittent or sham protocol. These days will be referred to as the initial and final day of the protocol from this point forward. The data was collected using commercially available software (LabVIEW, National Instruments, Austin, TX, United States; WinDaq, Dataq Instruments, Akron, OH, United States) at a sampling rate of 250 Hz.
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Biomechanical Signal Acquisition and Analysis

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Force, motor position and sarcomere length signals were recorded with a multifunction I/O board (PXIe-6358, National Instruments). A program written in LabVIEW (National Instrument) was used for signal generation and data acquisition. All data were analysed using dedicated programs written in LabVIEW (National Instruments) and Microsoft Excel and Origin 2018 (OriginLab Corp., Northampton, MA, USA) software.
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10

Optical Coherence Microscopy Data Processing

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Data acquisition was performed in LabView (LabView 2015, Version 15.0, 64-bit, National Instruments) and the data were stored in a 16-bit binary format for performing further post-processing steps in MATLAB (MATLAB, R2015b, MathWorks). After resampling the spectral data to k-space, background removal was performed. Numerical dispersion compensation was applied as described by Wojtkowski et al. [36 (link)] and Choi et al. [37 (link)]. By Fourier transforming these data, three dimensional OCM images were computed. En-face images were generated by calculating mean projection images at various depths within the tissue.
To further analyze the data, multiple post processing steps were performed which are summarized in a graphical overview in Fig. 3(b).
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