We introduce an Active Vertex Model (AVM) for cell-resolution studies of the mechanics of confluent epithelial tissues consisting of tens of thousands of cells, with a level of detail inaccessible to similar methods. The AVM combines the Vertex Model for confluent epithelial tissues with active matter dynamics. This introduces a natural description of the cell motion and accounts for motion patterns observed on multiple scales. Furthermore, cell contacts are generated dynamically from positions of cell centres. This not only enables efficient numerical implementation, but provides a natural description of the T1 transition events responsible for local tissue rearrangements. The AVM also includes cell alignment, cell-specific mechanical properties, cell growth, division and apoptosis. In addition, the AVM introduces a flexible, dynamically changing boundary of the epithelial sheet allowing for studies of phenomena such as the fingering instability or wound healing. We illustrate these capabilities with a number of case studies.

In this chapter, we introduce core functionality of the Jalview interactive platform for the creation, analysis, and publication of multiple sequence alignments. A workflow is described based on Jalview’s core functions: from data import to figure generation, including import of alignment reliability scores from T-Coffee and use of Jalview from the command line. The accompanying notes provide background information on the underlying methods and discuss additional options for working with Jalview to perform multiple sequence alignment, functional site analysis, and publication of alignments on the web.

This study focused on the performance of commercial AlGaN/InGaN/GaN blue light emitting diodes ͑LEDs͒ under high current pulse conditions. The results of deep level transient spectroscopy ͑DLTS͒, thermally stimulated capacitance, and admittance spectroscopy measurements performed on stressed devices, showed no evidence of any deep-level defects that may have developed as a result of high current pulses. Physical analysis of stressed LEDs indicated a strong connection between the high intrinsic defect density in these devices and the resulting mode of degradation.

We introduce an Active Vertex Model (AVM) for cell-resolution studies of the mechanics of confluent epithelial tissues consisting of tens of thousands of cells, with a level of detail inaccessible to similar methods. The AVM combines the Vertex Model for confluent epithelial tissues with active matter dynamics. This introduces a natural description of the cell motion and accounts for motion patterns observed on multiple scales. Furthermore, cell contacts are generated dynamically from positions of cell centres. This not only enables efficient numerical implementation, but provides a natural description of the T1 transition events responsible for local tissue rearrangements. The AVM also includes cell alignment, cellspecific mechanical properties, cell growth, division and apoptosis. In addition, the AVM introduces a flexible, dynamically changing boundary of the epithelial sheet allowing for studies of phenomena such as the fingering instability or wound healing. We illustrate these capabilities with a number of case studies. Author summaryWe present a detailed analysis of the Active Vertex Model to study the mechanics of confluent epithelial tissues and cell monolayers. The model combines the commonly used Vertex Model for describing epithelial tissue mechanics with the active matter dynamics extensively studied in soft matter physics. We utlise an exact mathematical mapping that enables a very efficient numerical implementation using standard methods for simulating particle-based models. System sizes accessible to this model allow us to probe the dynamical motion patterns that occur in tissues over a range of length-and time-scales previously inaccessible to available simulation tools. Our model also includes a number of essential features required to properly describe actual biological systems such as cell growth, cell division and aptotsis, as well as the dynamic boundary of the epithelial sheet. This allows us to study phenomena such as the finger-like protrusions in cell monolayers and processes related to wound healing. The model is implemented into the SAMoS PLOS Computational Biology | https://doi

SummaryJABAWS 2.2 is a computational framework that simplifies the deployment of web services for Bioinformatics. In addition to the five multiple sequence alignment (MSA) algorithms in JABAWS 1.0, JABAWS 2.2 includes three additional MSA programs (Clustal Omega, MSAprobs, GLprobs), four protein disorder prediction methods (DisEMBL, IUPred, Ronn, GlobPlot), 18 measures of protein conservation as implemented in AACon, and RNA secondary structure prediction by the RNAalifold program. JABAWS 2.2 can be deployed on a variety of in-house or hosted systems. JABAWS 2.2 web services may be accessed from the Jalview multiple sequence analysis workbench (Version 2.8 and later), as well as directly via the JABAWS command line interface (CLI) client. JABAWS 2.2 can be deployed on a local virtual server as a Virtual Appliance (VA) or simply as a Web Application Archive (WAR) for private use. Improvements in JABAWS 2.2 also include simplified installation and a range of utility tools for usage statistics collection, and web services querying and monitoring. The JABAWS CLI client has been updated to support all the new services and allow integration of JABAWS 2.2 services into conventional scripts. A public JABAWS 2 server has been in production since December 2011 and served over 800 000 analyses for users worldwide.Availability and implementationJABAWS 2.2 is made freely available under the Apache 2 license and can be obtained from: http://www.compbio.dundee.ac.uk/jabaws.

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The fluorescent microthermal imaging technique (FMI) involves coating a sample surface with an inorganic-based thin film that, upon exposure to W light, emits temperaturedependent fluorescence [l-81. FMI offers the ability to create thermal maps of integrated circuits with a thermal resolution theoretically limited to 1 m°C and a spatial resolution which is diffraction-limited to 0.3 pm. Even though the fluorescent microthermal imaging (FMI) technique has been around for more than a decade, many factors that can significantly affect the thermal image quality have not been systematically studied and characterized. After a brief review of FMI theory, we will present our recent results demonstrating for the first time three important factors that have a dramatic impact on the thermal quality and sensitivity of FMT. First, the limitations imparted by photon shot noise and improvement in the signal-tonoise ratio realized through signal averaging will be discussed. Second, ultraviolet bleaching, an unavoidable problem with FMI as it currently is performed, will be characterized to identify ways to minimize its effect. Finally, the impact of film dilution on thermal sensitivity will be discussed. FLUORESCENT MICROTHERMAL IMAGING THEORYTo better understand the theory behind FMI, we need to discuss the process which gives the fluorescing film a temperature dependent fluorescent quantum yield. Figure 1 shows the molar excitation coefficient (or loosely, the absorption spectra) versus wavelength for europium thenoyltifluoroacetonate (EuTTA) in an ethanol solution. There are several characteristics associated with absorption spectrum of EuTTA. First, there is a broad absorption peak centered around 335 nm where the TTA ligand absorbs energy. Second, the amount of incident radiation that is absorbed falls off strongly after about 360 nm. The two peaks at 460 nm and 525 nm are consistent with E d f absorption levels. Third, there is a lack of absorption for wavelengths much above 500 nm.The UV radiation used to excite the EuTTA fluorescence does so through an intermolecular energy transfer. The TTA ligand absorbs the UV light then transfers the energy to the europium ion. While several fluorescent lines are excited, the transition from the Eu3+ 5Do energy level to the 7F2 level is the most efficient. This transition generates a DISCLAIMERPortions of this document may be illegible in electronic image products. Images are produced from the best available original document.bright fluorescent line at 612 nm which is used for FMI. Figure 2 shows the emission spectrum for crystalline EuTTA at 25 "C.For thermal imaging applications, we need to know how the emission spectra changes with temperature. Figure 3 shows the measured absolute quantum yield versus temperature and figure 4 shows the decay time of the fluorescent yield versus temperature. Both of these plots were generated for EuTTA in an ether:iso-pentane:ethanol (552) solution. For the FMI application, a curve will need to be generated for each compound mixture that is us...