Audible Voice in Context

The term audible voice refers to the sound of the text experienced by the reader during silent reading. It was coined by Elbow in his Landmark Essays to help the field of composition wrestle more productively with the concept of voice in writing. In this dissertation, voice is not a metaphor. Drawing on contemporary work in psycholinguistics, cognitive psychology, and consciousness studies, it examines the phenomenon of audible voice as a form of inner speech[1]. The premise of this study is that the experience of audible voice by the reader is a unique intersection of the individual\u27s inner landscape and the features of the text at a particular moment in time. Therefore, the phenomenology of audible voice is best explored in context, the context of a single individual responding to a specific text. This dissertation presents the results of a mixed-methods study designed to explore the following questions in context: (1) What do readers hear or experience when they read silently? (2) What do writers hear or experience when they write? For scholars studying inner speech and the experience of voice, the value of this study lies in its detailed description of the phenomenology of inner speech during reading and writing in context. For composition-rhetoric scholars, this study is intended as a stepping-stone along a path towards an understanding of style and voice in writing that is centered in the inner experience of individual readers and writers. This lens is critical given the diversity of inner landscapes described in this work, a glimpse into the potential for an invisible diversity that may be present in our classrooms. [1] Also known as inner voice and inner speaking

Likelihood-based estimation of substructure content from single-wavelength anomalous diffraction (SAD) intensity data.

SAD phasing can be challenging when the signal-to-noise ratio is low. In such cases, having an accurate estimate of the substructure content can determine whether or not the substructure of anomalous scatterer positions can successfully be determined. Here, a likelihood-based target function is proposed to accurately estimate the strength of the anomalous scattering contribution directly from the measured intensities, determining a complex correlation parameter relating the Bijvoet mates as a function of resolution. This gives a novel measure of the intrinsic anomalous signal. The SAD likelihood target function also accounts for correlated errors in the measurement of intensities from Bijvoet mates, which can arise from the effects of radiation damage. When the anomalous signal is assumed to come primarily from a substructure comprising one anomalous scatterer with a known value of f'' and when the protein composition of the crystal is estimated correctly, the refined complex correlation parameters can be interpreted in terms of the atomic content of the primary anomalous scatterer before the substructure is known. The maximum-likelihood estimation of substructure content was tested on a curated database of 357 SAD cases with useful anomalous signal. The prior estimates of substructure content are highly correlated to the content determined by phasing calculations, with a correlation coefficient (on a log-log basis) of 0.72

Robust placement and sizing of charging stations from a novel graph theoretic perspective

This paper proposes analytical approaches to extend the capacity of existing networks of electric vehicles (EVs) by placement of additional charging stations (CSs) as well as determining the sizes of existing and new CSs in order to handle future expansions of EVs. The EV flow at CSs is modeled by a graph where nodes are potential locations for CSs and edges are uncertain parameters representing the variable EV flow at CSs. The required extra CS locations are explored by transforming the CS placement problem into a controllability framework addressed by maximum matching principle (MMP). To find the sizes of each CS, the graph of CS network is partitioned featuring only one CS in each subgraph. The size of CS in each subgraph is then determined by transforming the problem into the problem of robust stability of a system with uncertain parameters where each parameter is associated with an edge of subgraph. The zero exclusion principle is then tested for the related Kharitonov rectangles and polygonal polynomials of closed loop system with selected feedback gain as CS capacity. The proposed analytical approach is tested on the existing Tesla CS Network of Sydney. The locations of extra required CSs as well as the sizes of existing and new CSs are determined to maintain the waiting times at all stations below the threshold level

Factors influencing estimates of coordinate error for molecular replacement.

Good prior estimates of the effective root-mean-square deviation (r.m.s.d.) between the atomic coordinates of the model and the target optimize the signal in molecular replacement, thereby increasing the success rate in difficult cases. Previous studies using protein structures solved by X-ray crystallography as models showed that optimal error estimates (refined after structure solution) were correlated with the sequence identity between the model and target, and with the number of residues in the model. Here, this work has been extended to find additional correlations between parameters of the model and the target and hence improved prior estimates of the coordinate error. Using a graph database, a curated set of 6030 molecular-replacement calculations using models that had been solved by X-ray crystallography was analysed to consider about 120 model and target parameters. Improved estimates were achieved by replacing the sequence identity with the Gonnet score for sequence similarity, as well as by considering the resolution of the target structure and the MolProbity score of the model. This approach was extended by analysing 12 610 additional molecular-replacement calculations where the model was determined by NMR. The median r.m.s.d. between pairs of models in an ensemble was found to be correlated with the estimated r.m.s.d. to the target. For models solved by NMR, the overall coordinate error estimates were larger than for structures determined by X-ray crystallography, and were more highly correlated with the number of residues

Likelihood‐based estimation of substructure content from single‐wavelength anomalous diffraction (SAD) intensity data

SAD phasing can be challenging when the signal‐to‐noise ratio is low. In such cases, having an accurate estimate of the substructure content can determine whether or not the substructure of anomalous scatterer positions can successfully be determined. Here, a likelihood‐based target function is proposed to accurately estimate the strength of the anomalous scattering contribution directly from the measured intensities, determining a complex correlation parameter relating the Bijvoet mates as a function of resolution. This gives a novel measure of the intrinsic anomalous signal. The SAD likelihood target function also accounts for correlated errors in the measurement of intensities from Bijvoet mates, which can arise from the effects of radiation damage. When the anomalous signal is assumed to come primarily from a substructure comprising one anomalous scatterer with a known value of f′′ and when the protein composition of the crystal is estimated correctly, the refined complex correlation parameters can be interpreted in terms of the atomic content of the primary anomalous scatterer before the substructure is known. The maximum‐likelihood estimation of substructure content was tested on a curated database of 357 SAD cases with useful anomalous signal. The prior estimates of substructure content are highly correlated to the content determined by phasing calculations, with a correlation coefficient (on a log–log basis) of 0.72

Automated identification of elemental ions in macromolecular crystal structures.

Many macromolecular model-building and refinement programs can automatically place solvent atoms in electron density at moderate-to-high resolution. This process frequently builds water molecules in place of elemental ions, the identification of which must be performed manually. The solvent-picking algorithms in phenix.refine have been extended to build common ions based on an analysis of the chemical environment as well as physical properties such as occupancy, B factor and anomalous scattering. The method is most effective for heavier elements such as calcium and zinc, for which a majority of sites can be placed with few false positives in a diverse test set of structures. At atomic resolution, it is observed that it can also be possible to identify tightly bound sodium and magnesium ions. A number of challenges that contribute to the difficulty of completely automating the process of structure completion are discussed

Graphical tools for macromolecular crystallography in PHENIX.

A new Python-based graphical user interface for the PHENIX suite of crystallography software is described. This interface unifies the command-line programs and their graphical displays, simplifying the development of new interfaces and avoiding duplication of function. With careful design, graphical interfaces can be displayed automatically, instead of being manually constructed. The resulting package is easily maintained and extended as new programs are added or modified

Overview of the CCP4 suite and current developments.

The CCP4 (Collaborative Computational Project, Number 4) software suite is a collection of programs and associated data and software libraries which can be used for macromolecular structure determination by X-ray crystallography. The suite is designed to be flexible, allowing users a number of methods of achieving their aims. The programs are from a wide variety of sources but are connected by a common infrastructure provided by standard file formats, data objects and graphical interfaces. Structure solution by macromolecular crystallography is becoming increasingly automated and the CCP4 suite includes several automation pipelines. After giving a brief description of the evolution of CCP4 over the last 30 years, an overview of the current suite is given. While detailed descriptions are given in the accompanying articles, here it is shown how the individual programs contribute to a complete software package

Transient Fcho1/2⋅Eps15/R⋅AP-2 Nanoclusters Prime the AP-2 Clathrin Adaptor for Cargo Binding.

Clathrin-coated vesicles form by rapid assembly of discrete coat constituents into a cargo-sorting lattice. How the sequential phases of coat construction are choreographed is unclear, but transient protein-protein interactions mediated by short interaction motifs are pivotal. We show that arrayed Asp-Pro-Phe (DPF) motifs within the early-arriving endocytic pioneers Eps15/R are differentially decoded by other endocytic pioneers Fcho1/2 and AP-2. The structure of an Eps15/R⋅Fcho1 μ-homology domain complex reveals a spacing-dependent DPF triad, bound in a mechanistically distinct way from the mode of single DPF binding to AP-2. Using cells lacking FCHO1/2 and with Eps15 sequestered from the plasma membrane, we establish that without these two endocytic pioneers, AP-2 assemblies are fleeting and endocytosis stalls. Thus, distinct DPF-based codes within the unstructured Eps15/R C terminus direct the assembly of temporary Fcho1/2⋅Eps15/R⋅AP-2 ternary complexes to facilitate conformational activation of AP-2 by the Fcho1/2 interdomain linker to promote AP-2 cargo engagement.Supported by NIH R01 GM106963 to L.M.T. and Wellcome Trust grants 090909/Z to D.J.O., 097040 to A.G.W., and 100140 to CIMR.This is the final version of the article. It first appeared from Cell Press / Elsevier via https://doi.org/10.1016/j.devcel.2016.05.00

Macromolecular structure determination using X-rays, neutrons and electrons: recent developments in Phenix.

Diffraction (X-ray, neutron and electron) and electron cryo-microscopy are powerful methods to determine three-dimensional macromolecular structures, which are required to understand biological processes and to develop new therapeutics against diseases. The overall structure-solution workflow is similar for these techniques, but nuances exist because the properties of the reduced experimental data are different. Software tools for structure determination should therefore be tailored for each method. Phenix is a comprehensive software package for macromolecular structure determination that handles data from any of these techniques. Tasks performed with Phenix include data-quality assessment, map improvement, model building, the validation/rebuilding/refinement cycle and deposition. Each tool caters to the type of experimental data. The design of Phenix emphasizes the automation of procedures, where possible, to minimize repetitive and time-consuming manual tasks, while default parameters are chosen to encourage best practice. A graphical user interface provides access to many command-line features of Phenix and streamlines the transition between programs, project tracking and re-running of previous tasks