Multireflecting gas chromatography-multireflecting time-of-flight mass spectrometer with high dynamic range.

Gas chromatography-mass spectrometry (GC-MS) is a cornerstone technique for analyses of volatile and semivolatile compounds, constantly evolving to meet new challenges. The adoption of time-of-flight mass spectrometers (TOFMS) has enhanced GC-MS with faster spectral acquisition and broader mass coverage, enabling rapid GC separations. Multireflecting TOFMS (MRT) further improves resolution compared to traditional single-reflecting TOFMS, facilitating the detection of minor analytes within complex matrices.

Modeling Known Sources of Mass Calibration Deviations in High Resolution ToF MS.

Modern time-of-flight mass spectrometer instruments exhibit excellent mass accuracy in the parts per billion range. At this level, mass calibration methods should consider potential distortions in the basic calibration. Factors which can cause distortions are to be under control.

Shot noise in next-generation neural mass models for finite-size networks.

Neural mass models is a general name for various models describing the collective dynamics of large neural populations in terms of averaged macroscopic variables. Recently, the so-called next-generation neural mass models have attracted a lot of attention due to their ability to account for the degree of synchrony. Being exact in the limit of infinitely large number of neurons, these models provide only an approximate description of finite-size networks.

Reduction of the collective dynamics of neural populations with realistic forms of heterogeneity.

Reduction of collective dynamics of large heterogeneous populations to low-dimensional mean-field models is an important task of modern theoretical neuroscience. Such models can be derived from microscopic equations, for example with the help of Ott-Antonsen theory. An often used assumption of the Lorentzian distribution of the unit parameters makes the reduction especially efficient.