Journal: Frontiers in Microbiology

Article Title: Feasible metabolisms in high pH springs of the Philippines

doi: 10.3389/fmicb.2015.00010

Figure Lengend Snippet: Dissolved gas concentrations, obtained via gas-stripping of gas-rich aqueous samples .

Article Snippet: Zambales, ML2 , −9.3 , −60.7 , This study.

Techniques:

Journal: Frontiers in Microbiology

Article Title: Feasible metabolisms in high pH springs of the Philippines

doi: 10.3389/fmicb.2015.00010

Figure Lengend Snippet: Dissolved gas findings (reported in Table ) shown as side-by-side gas doughnut diagrams . Note that the sampled sites range from H 2 - and CH 4 -dominated (ML1 and ML2, inner green and black doughnuts) to nearly completely CO 2 -dominated (BB1, white doughnut).

Article Snippet: Zambales, ML2 , −9.3 , −60.7 , This study.

Techniques:

Journal: Frontiers in Microbiology

Article Title: Feasible metabolisms in high pH springs of the Philippines

doi: 10.3389/fmicb.2015.00010

Figure Lengend Snippet: New data for the stable isotopes of water in springs of the Zambales and Palawan Ophiolites, presented with additional regional data, related to the establishment of a local meteoric water line (Gerardo-Abaya, 2005 ) and documentation of springs with isotopic characteristics signaling interaction with country rock and magmatic processes (Giggenbach, 1992 ) .

Article Snippet: Zambales, ML2 , −9.3 , −60.7 , This study.

Techniques:

Journal: Frontiers in Microbiology

Article Title: Feasible metabolisms in high pH springs of the Philippines

doi: 10.3389/fmicb.2015.00010

Figure Lengend Snippet:

Article Snippet: Zambales, ML2 , −9.3 , −60.7 , This study.

Techniques:

Journal: Frontiers in Microbiology

Article Title: Feasible metabolisms in high pH springs of the Philippines

doi: 10.3389/fmicb.2015.00010

Figure Lengend Snippet:

Article Snippet: Zambales, ML2 , −9.3 , −60.7 , This study.

Techniques:

Journal: Journal of neuroscience methods

Article Title: NIMH MonkeyLogic: Behavioral control and data acquisition in MATLAB

doi: 10.1016/j.jneumeth.2019.05.002

Figure Lengend Snippet: An example task written with the scene framework. This is a working example that is executable in ML2. A video clip of this task and the complete task files are available at NIMH MonkeyLogic website. A. The fixation timer task. The total duration of fixation is indicated by the annulus-shaped counters that continuously change over time. The counter stops when the fixation is broken but resumes if the fixation is re-acquired within 4 s. B. The script for the fixation timer task. Three adapters are used and combined into a chain. Each adapter can be manipulated by changing its properties. The chain is executed via create_scene() and run_scene(). C. The cycle during run_scene(). Each adapter has two member functions: analyze() and draw(). run_scene() calls analyze() and draw() of the top-most adapter, the adapter given as an input argument to create_scene(), which triggers the iteration of all linked adapters. run_scene() repeats this cycle until analyze() of the top-most adapter returns false.

Article Snippet: We developed ML2 to build on the success of ML1 and support the latest (64-bit) MATLAB computing environment.

Techniques:

Journal: Journal of neuroscience methods

Article Title: NIMH MonkeyLogic: Behavioral control and data acquisition in MATLAB

doi: 10.1016/j.jneumeth.2019.05.002

Figure Lengend Snippet: Screenshots of NIMH MonkeyLogic (ML2). A. The subject’s screen. B. The experimenter’s screen. MonkeyLogic Graphics Library (MGL) displays visual stimuli on both screens in parallel but overlays task-related information (fixation window, eye trace, button input, user text, etc.) on the experimenter’s screen only. It supports transparent colors so that the visual stimuli can be overlapped.

Article Snippet: We developed ML2 to build on the success of ML1 and support the latest (64-bit) MATLAB computing environment.

Techniques:

Journal: Journal of neuroscience methods

Article Title: NIMH MonkeyLogic: Behavioral control and data acquisition in MATLAB

doi: 10.1016/j.jneumeth.2019.05.002

Figure Lengend Snippet: Resolution of timestamps and latencies of event markers and stimuli. The timestamp resolution is the minimum interval that the tic and toc commands of MATLAB can measure. The latencies of analog stimulations, sounds and photodiode output were measured from the event markers sent out immediately after the stimuli. A negative number indicates that the signal change due to the stimulus was faster than the event marker. All measures were repeated 100 times. The numbers in parentheses are the results with MATLAB R2018a. Because of the just-in-time compilation of the MATLAB execution engine, the first few measures can be slower than the rest. For example, the first six timestamp intervals measured in ML2 with R2018a were 93.81, 15.78, 13.74, 152.55, 176.22 and 1.17 μs, but the rest of the intervals were all shorter than 1 μs.

Article Snippet: We developed ML2 to build on the success of ML1 and support the latest (64-bit) MATLAB computing environment.

Techniques: Marker

Journal: Journal of neuroscience methods

Article Title: NIMH MonkeyLogic: Behavioral control and data acquisition in MATLAB

doi: 10.1016/j.jneumeth.2019.05.002

Figure Lengend Snippet: Execution time of MonkeyLogic functions. The measured times (mean ± SD) are in milliseconds and based on 100 trials of the performance test (see Methods ), including the first trial. The numbers in parentheses are the results with MATLAB R2018a. The “Entry” time refers to the amount of time required for initialization of each function, before the execution of the core activity. The “Core” time is the amount of time required to execute the essential activity of the function. The “Exit” time reflects the amount of time required to clean up and leave the function, after the core activity has completed. For the “Trial” row, the entry time corresponds to the time required to initialize all the sub-functions and analog data acquisition and the exit time is the time required to store collected data to the disk. The intertrial interval includes the time required to update behavior performance measures on the experimenter’s screen but most of it is the time required to load stimuli. The eventmarker function of ML2 is a one-line function, so there is no entry or exit time. The adapters of ML2 are executed with run_scene(), instead of toggleobject() and eyejoytrack().

Article Snippet: We developed ML2 to build on the success of ML1 and support the latest (64-bit) MATLAB computing environment.

Techniques: Activity Assay