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Action spectroscopy using photon excitation in the VUV range (photon energy 4.5–9 eV) was performed on protonated uracil (UraH+) and uridine (UrdH+). The precursor ions with m/z113 and m/z245, respectively, were produced by an electrospray ionization source and accumulated inside a quadrupole ion trap mass spectrometer. After irradiation with tunable synchrotron radiation, product ion mass spectra were obtained. Fragment yields as a function of excitation energy show several maxima that can be attributed to the photoexcitation into different electronic states. For uracil, vertically excited states were calculated using the equation-of-motion coupled cluster approach and compared to the observed maxima. This allows to establish correlations between electronic states and the resulting fragment masses and can thus help to disentangle the complex de-excitation and fragmentation pathways of nucleic acid building blocks. Photofragmentation of the nucleoside uridine shows a significantly lower variety of fragments, indicating stabilization of the nucleobase by the attached sugar.

We present chemical kinetics measurements of the luminol oxidation chemiluminescence (CL) reaction at the interface between two aqueous solutions, using liquid jet technology. Free-flowing liquid microjets are a relatively recent development that have found their way into a growing number of applications in spectroscopy and dynamics. A variant thereof, called flat-jet, is obtained when two cylindrical jets of a liquid are crossed, leading to a chain of planar leaf-shaped structures of the flowing liquid. We here show that in the first leaf of this chain, the fluids do not exhibit turbulent mixing, providing a clean interface between the liquids from the impinging jets. We also show, using the example of the luminol CL reaction, how this setup can be used to obtain kinetics information from friction-less flow and by circumventing the requirement for rapid mixing by intentionally suppressing all turbulent mixing and instead relying on diffusion.

Due to its rising importance in science and technology in recent years, particle tracking in videos presents itself as a tool for successfully acquiring new knowledge in the field of life sciences and physics. Accordingly, different particle tracking methods for various scenarios have been developed. In this article, we present a particle tracking application implemented in Python for, in particular, spherical magnetic particles, including superparamagnetic beads and Janus particles. In the following, we distinguish between two sub-steps in particle tracking, namely the localization of particles in single images and the linking of the extracted particle positions of the subsequent frames into trajectories. We provide an intensity-based localization technique to detect particles and two linking algorithms, which apply either frame-by-frame linking or linear assignment problem solving. Beyond that, we offer helpful tools to preprocess images automatically as well as estimate parameters required for the localization algorithm by utilizing machine learning. As an extra, we have implemented a technique to estimate the current spatial orientation of Janus particles within the x – y -plane. Our framework is readily extendable and easy-to-use as we offer a graphical user interface and a command-line tool. Various output options, such as data frames and videos, ensure further analysis that can be automated. Program Title: AdaPT CPC Library link to program files: https://doi.org/10.17632/xxpnsbv3cs.1 Developer's repository link: https://git.ies.uni-kassel.de/adapt/adapt Licensing provisions: MPL-2.0 Programming language: Python 3.6 Supplementary material: We provide supplementary material to increase the traceability of the provided example. It consists of an exemplary input video, the corresponding annotated video with tracked particles, a data frame including the tracking information, and a plot displaying the trajectories. Nature of problem: Particle tracking in videos is an important tool for acquiring new knowledge in diverse fields. Several particle tracking methods have been developed for these diverse applications. The presented particle tracking software has been developed for the motion analysis of spherical or close to spherical magnetic particles. Up until now, no easily extensible automated particle tracking software for close to spherical microparticles and their current positioning status is available. Solution method: AdaPT is an extensible, easy-to-use microparticle tracking application developed explicitly for lab on chip applications but easily extensible to other applications and further functionalities. Currently implemented linking algorithms are a frame-by-frame linking approach as well as an approach solving linear assignment problems. In addition to many assistance possibilities for the user in the form of estimates of parameter values through machine learning, we offer the particular option to determine the orientation and rotation of spherical polymer particles with hemispherical metallic caps (Janus particles). The application can be used via console and graphical user interface. Additional comments including restrictions and unusual features: This software requires video data with spherical or close to spherical magnetic particles. It was tested on videos containing spherical superparamagnetic and magnetic Janus particles. Only mobile particles are detected; immobile particles are ignored by the software, reducing the amount of output data considerably. As a unique feature, the spatial orientation within the x – y -plane of Janus particles can be determined. The application has been tested on a variety of two-dimensional particle motion patterns. The latest version of AdaPT can be found here: https://git.ies.uni-kassel.de/adapt/adapt. [ABSTRACT FROM AUTHOR]