18Multi-gene and genomic datasets have become commonplace in the field of 19 phylogenetics, but many of the existing tools are not designed for such datasets, 20 which makes the analysis time-consuming and tedious. We therefore present 21 PhyloSuite, a user-friendly workflow desktop platform dedicated to streamlining 22 molecular sequence data management and evolutionary phylogenetics studies. It 23 employs a plugin-based system that integrates a number of useful phylogenetic and 24 bioinformatic tools, thereby streamlining the entire procedure, from data acquisition 25 to phylogenetic tree annotation, with the following features: (i) point-and-click and 26 drag-and-drop graphical user interface, (ii) a workspace to manage and organize 27 molecular sequence data and results of analyses, (iii) GenBank entries extraction and 28 comparative statistics, (iv) a phylogenetic workflow with batch processing capability, 29(v) elaborate bioinformatic analysis for mitochondrial genomes. The aim of 30 PhyloSuite is to enable researchers to spend more time playing with scientific 31 questions, instead of wasting it on conducting standard analyses. The compiled binary 32 of PhyloSuite is available under the GPL license at 33 https://github.com/dongzhang0725/PhyloSuite/releases, implemented in Python and 34 runs on Windows, Mac OSX and Linux. 35 36 37 Advancements in next-generation sequencing technologies (Metzker, 2009) have 38 resulted in a huge increase in the amount of genetic data available through public 39 databases. While this opens a multitude of research possibilities, retrieving and 40 managing such large amounts of data may be difficult and time-consuming for 41 researchers who are not computer-savvy. A standard analytical procedure for 42 phylogenetic analysis is: selecting and downloading GenBank entries, extracting 43 target genes (for multi-gene datasets, such as organelle genomes) and/or mining other 44 data, sequence alignment, alignment optimization, concatenation of alignments (for 45 multi-gene datasets), selection of best-fit partitioning schemes and evolutionary 46 models, phylogeny reconstruction, and finally visualization and annotation of the 47 phylogram. This can be very time-consuming if different programs have to be 48 employed for different steps, especially as they often have different input file format 49 requirements, and sometimes even require manual file tweaking. Therefore, 50 multifunctional, workflow-type software packages are becoming increasingly needed 51 by a broad range of evolutionary biologists (Smith, 2015). Specifically, as single-gene 52 datasets are rapidly being replaced by multi-gene or genomic datasets as a tool of 53 choice for phylogenetic reconstruction (Degnan and Rosenberg, 2009; Rivera-Rivera 54 and Montoya-Burgos, 2016), automated gene extraction from genomic data and batch 55 manipulation in some of the above steps, like alignment, are becoming a necessity. 56 Although there are several tools in existence, designed to streamline this process 57 by incorporat...
Abstract. We present Localizer, a freely available and open source software package that implements the computational data processing inherent to several types of superresolution fluorescence imaging, such as localization (PALM/STORM/GSDIM) and fluctuation imaging (SOFI/pcSOFI). Localizer delivers high accuracy and performance and comes with a fully featured and easy-to-use graphical user interface but is also designed to be integrated in higher-level analysis environments. Due to its modular design, Localizer can be readily extended with new algorithms as they become available, while maintaining the same interface and performance. We provide front-ends for running Localizer from Igor Pro, Matlab, or as a stand-alone program. We show that Localizer performs favorably when compared with two existing superresolution packages, and to our knowledge is the only freely available implementation of SOFI/pcSOFI microscopy. By dramatically improving the analysis performance and ensuring the easy addition of current and future enhancements, Localizer strongly improves the usability of superresolution imaging in a variety of biomedical studies.
The local symmetry of a Eu3+ ion has a crucial effect on its luminescence properties. In this work, we show that the red/orange ratio in the emission of Eu3+-doped MgIn2P4O14 phosphors is tunable by adjusting the Eu3+ concentrations, due to the change in the local symmetry of metal ions. The substitution of Eu3+ for In3+ lowers the distortion in the lattice of monoclinic MgIn2P4O14, and an increase in Eu3+ doping concentration causes the metal ion sites to shift closer to an inverse center, leading to a reversal of the relative emission intensity of a magnetic dipole transition to an electric dipole transition. Meanwhile, the higher asymmetry of metal ion sites occupied by Eu3+ in MgIn2P4O14 makes the luminescence less thermally stable than that in Mg3In4P6O24.
The reconstruction of the trajectories of charged particles, or track reconstruction, is a key computational challenge for particle and nuclear physics experiments. While the tuning of track reconstruction algorithms can depend strongly on details of the detector geometry, the algorithms currently in use by experiments share many common features. At the same time, the intense environment of the High-Luminosity LHC accelerator and other future experiments is expected to put even greater computational stress on track reconstruction software, motivating the development of more performant algorithms. We present here A Common Tracking Software (ACTS) toolkit, which draws on the experience with track reconstruction algorithms in the ATLAS experiment and presents them in an experiment-independent and framework-independent toolkit. It provides a set of high-level track reconstruction tools which are agnostic to the details of the detection technologies and magnetic field configuration and tested for strict thread-safety to support multi-threaded event processing. We discuss the conceptual design and technical implementation of ACTS, selected applications and performance of ACTS, and the lessons learned.
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