Differential polarization decoding for robust coherent optical packet switched networks

This paper proposes the use of the 2-D differential decoding to improve the robustness of dual-polarization optical packet receivers and is demonstrated in a wavelength switching scenario for the first time.

Phonics instruction using pseudowords for success in phonetic decoding

This study examined a Pseudoword Phonics Curriculum to determine if this form of instruction would increase students’ decoding skills compared to typical real-word phonics instruction. In typical phonics instruction, children learn to decode familiar words which allow them to draw on their prior knowledge of how to pronounce the word and may detract from learning decoding skills. By using pseudowords during phonics instruction, students may learn more decoding skills because they are unfamiliar with the “words” and therefore cannot draw on memory for how to pronounce the word. It was hypothesized that students who learn phonics with pseudowords will learn more decoding skills and perform higher on a real-word assessment compared to students who learn phonics with real words. ^ Students from two kindergarten classes participated in this study. An author-created word decoding assessment was used to determine the students’ ability to decode words. The study was broken into three phases, each lasting one month. During Phase 1, both groups received phonics instruction using real words, which allowed for the exploration of baseline student growth trajectories and potential teacher effects. During Phase 2, the experimental group received pseudoword phonics instruction while the control group continued real-word phonics instruction. During Phase 3, both groups were taught with real-word phonics instruction. Students were assessed on their decoding skills before and after each phase. ^ Results from multiple regression and multi-level model analyses revealed a greater increase in decoding skills during the second and third phases of the study for students who received the pseudoword phonics instruction compared to students who received the real-word phonics instruction. This suggests that pseudoword phonics instruction improves decoding skills quicker than real-word phonics instruction. This also suggests that teaching decoding with pseudowords for one month can continue to improve decoding skills when children return to real-word phonics instruction. Teacher feedback suggests that confidence with reading increased for students who learned with pseudowords because they were less intimidated by the approach and viewed pseudoword phonics as a game that involved reading “silly” words. Implications of these results, limitations of this study, and areas for future research are discussed. ^

Phonics Instruction using Pseudowords for Success in Phonetic Decoding

This study examined a Pseudoword Phonics Curriculum to determine if this form of instruction would increase students’ decoding skills compared to typical real-word phonics instruction. In typical phonics instruction, children learn to decode familiar words which allow them to draw on their prior knowledge of how to pronounce the word and may detract from learning decoding skills. By using pseudowords during phonics instruction, students may learn more decoding skills because they are unfamiliar with the “words” and therefore cannot draw on memory for how to pronounce the word. It was hypothesized that students who learn phonics with pseudowords will learn more decoding skills and perform higher on a real-word assessment compared to students who learn phonics with real words. Students from two kindergarten classes participated in this study. An author-created word decoding assessment was used to determine the students’ ability to decode words. The study was broken into three phases, each lasting one month. During Phase 1, both groups received phonics instruction using real words, which allowed for the exploration of baseline student growth trajectories and potential teacher effects. During Phase 2, the experimental group received pseudoword phonics instruction while the control group continued real-word phonics instruction. During Phase 3, both groups were taught with real-word phonics instruction. Students were assessed on their decoding skills before and after each phase. Results from multiple regression and multi-level model analyses revealed a greater increase in decoding skills during the second and third phases of the study for students who received the pseudoword phonics instruction compared to students who received the real-word phonics instruction. This suggests that pseudoword phonics instruction improves decoding skills quicker than real-word phonics instruction. This also suggests that teaching decoding with pseudowords for one month can continue to improve decoding skills when children return to real-word phonics instruction. Teacher feedback suggests that confidence with reading increased for students who learned with pseudowords because they were less intimidated by the approach and viewed pseudoword phonics as a game that involved reading “silly” words. Implications of these results, limitations of this study, and areas for future research are discussed.

Iterative Phase Optimization of Elementary Quantum Error Correcting Codes

Performing experiments on small-scale quantum computers is certainly a challenging endeavor. Many parameters need to be optimized to achieve high-fidelity operations. This can be done efficiently for operations acting on single qubits, as errors can be fully characterized. For multiqubit operations, though, this is no longer the case, as in the most general case, analyzing the effect of the operation on the system requires a full state tomography for which resources scale exponentially with the system size. Furthermore, in recent experiments, additional electronic levels beyond the two-level system encoding the qubit have been used to enhance the capabilities of quantum-information processors, which additionally increases the number of parameters that need to be controlled. For the optimization of the experimental system for a given task (e.g., a quantum algorithm), one has to find a satisfactory error model and also efficient observables to estimate the parameters of the model. In this manuscript, we demonstrate a method to optimize the encoding procedure for a small quantum error correction code in the presence of unknown but constant phase shifts. The method, which we implement here on a small-scale linear ion-trap quantum computer, is readily applicable to other AMO platforms for quantum-information processing.

Decoding Spontaneous Emotional States in the Human Brain.

Pattern classification of human brain activity provides unique insight into the neural underpinnings of diverse mental states. These multivariate tools have recently been used within the field of affective neuroscience to classify distributed patterns of brain activation evoked during emotion induction procedures. Here we assess whether neural models developed to discriminate among distinct emotion categories exhibit predictive validity in the absence of exteroceptive emotional stimulation. In two experiments, we show that spontaneous fluctuations in human resting-state brain activity can be decoded into categories of experience delineating unique emotional states that exhibit spatiotemporal coherence, covary with individual differences in mood and personality traits, and predict on-line, self-reported feelings. These findings validate objective, brain-based models of emotion and show how emotional states dynamically emerge from the activity of separable neural systems.

Recoding: reprogrammed genetic decoding with an emphasis on antizyme regulatory frameshifting

Recoding embraces mechanisms that augment the rules of standard genetic decoding. The deviations from standard decoding are often purposeful and their realisation provides diverse and flexible regulatory mechanisms. Recoding events such as programed ribosomal frameshifting are especially plentiful in viruses. In most organisms only a few cellular genes are known to employ programed ribosomal frameshifting in their expression. By far the most prominent and therefore well-studied case of cellular +1 frameshifting is in expression of antizyme mRNAs. The protein antizyme is a key regulator of polyamine levels in most eukaryotes with some exceptions such as plants. A +1 frameshifting event is required for the full length protein to be synthesized and this requirement is a conserved feature of antizyme mRNAs from yeast to mammals. The efficiency of the frameshifting event is dependent on the free polyamine levels in the cell. cis-acting elements in antizyme mRNAs such as specific RNA structures are required to stimulate the frameshifting efficiency. Here I describe a novel stimulator of antizyme +1 frameshifting in the Agaricomycotina class of Basidiomycete fungi. It is a nascent peptide that acts from within the ribosome exit tunnel to stimulate frameshifting efficiency in response to polyamines. The interactions of the nascent peptide with components of the peptidyl transferase centre and the protein exit tunnel emerge in our understanding as powerful means which the cell employs for monitoring and tuning the translational process. These interactions can modulate the rate of translation, protein cotranslational folding and localization. Some nascent peptides act in concert with small molecules such as polyamines or antibiotics to stall the ribosome. To these known nascent peptide effects we have added that of a stimulatory effect on the +1 frameshifting in antizyme mRNAs. It is becoming evident that nascent peptide involvement in regulation of translation is a much more general phenomenon than previously anticipated.

Iterative reconstruction as a novel method of radiation dose reduction at computed tomography in patients with Crohn's disease

Prior work of our research group, that quantified the alarming levels of radiation dose to patients with Crohn’s disease from medical imaging and the notable shift towards CT imaging making these patients an at risk group, provided context for this work. CT delivers some of the highest doses of ionising radiation in diagnostic radiology. Once a medical imaging examination is deemed justified, there is an onus on the imaging team to endeavour to produce diagnostic quality CT images at the lowest possible radiation dose to that patient. The fundamental limitation with conventional CT raw data reconstruction was the inherent coupling of administered radiation dose with observed image noise – the lower the radiation dose, the noisier the image. The renaissance, rediscovery and refinement of iterative reconstruction removes this limitation allowing either an improvement in image quality without increasing radiation dose or maintenance of image quality at a lower radiation dose compared with traditional image reconstruction. This thesis is fundamentally an exercise in optimisation in clinical CT practice with the objectives of assessment of iterative reconstruction as a method for improvement of image quality in CT, exploration of the associated potential for radiation dose reduction, and development of a new split dose CT protocol with the aim of achieving and validating diagnostic quality submillisiever t CT imaging in patients with Crohn’s disease. In this study, we investigated the interplay of user-selected parameters on radiation dose and image quality in phantoms and cadavers, comparing traditional filtered back projection (FBP) with iterative reconstruction algorithms. This resulted in the development of an optimised, refined and appropriate split dose protocol for CT of the abdomen and pelvis in clinical patients with Crohn’s disease allowing contemporaneous acquisition of both modified and conventional dose CT studies. This novel algorithm was then applied to 50 patients with a suspected acute complication of known Crohn’s disease and the raw data reconstructed with FBP, adaptive statistical iterative reconstruction (ASiR) and model based iterative reconstruction (MBIR). Conventional dose CT images with FBP reconstruction were used as the reference standard with which the modified dose CT images were compared in terms of radiation dose, diagnostic findings and image quality indices. As there are multiple possible user-selected strengths of ASiR available, these were compared in terms of image quality to determine the optimal strength for this modified dose CT protocol. Modified dose CT images with MBIR were also compared with contemporaneous abdominal radiograph, where performed, in terms of diagnostic yield and radiation dose. Finally, attenuation measurements in organs, tissues, etc. with each reconstruction algorithm were compared to assess for preservation of tissue characterisation capabilities. In the phantom and cadaveric models, both forms of iterative reconstruction examined (ASiR and MBIR) were superior to FBP across a wide variety of imaging protocols, with MBIR superior to ASiR in all areas other than reconstruction speed. We established that ASiR appears to work to a target percentage noise reduction whilst MBIR works to a target residual level of absolute noise in the image. Modified dose CT images reconstructed with both ASiR and MBIR were non-inferior to conventional dose CT with FBP in terms of diagnostic findings, despite reduced subjective and objective indices of image quality. Mean dose reductions of 72.9-73.5% were achieved with the modified dose protocol with a mean effective dose of 1.26mSv. MBIR was again demonstrated superior to ASiR in terms of image quality. The overall optimal ASiR strength for the modified dose protocol used in this work is ASiR 80%, as this provides the most favourable balance of peak subjective image quality indices with less objective image noise than the corresponding conventional dose CT images reconstructed with FBP. Despite guidelines to the contrary, abdominal radiographs are still often used in the initial imaging of patients with a suspected complication of Crohn’s disease. We confirmed the superiority of modified dose CT with MBIR over abdominal radiographs at comparable doses in detection of Crohn’s disease and non-Crohn’s disease related findings. Finally, we demonstrated (in phantoms, cadavers and in vivo) that attenuation values do not change significantly across reconstruction algorithms meaning preserved tissue characterisation capabilities with iterative reconstruction. Both adaptive statistical and model based iterative reconstruction algorithms represent feasible methods of facilitating acquisition diagnostic quality CT images of the abdomen and pelvis in patients with Crohn’s disease at markedly reduced radiation doses. Our modified dose CT protocol allows dose savings of up to 73.5% compared with conventional dose CT, meaning submillisievert imaging is possible in many of these patients.

A parallel pattern for iterative stencil + reduce

We advocate the Loop-of-stencil-reduce pattern as a means of simplifying the implementation of data-parallel programs on heterogeneous multi-core platforms. Loop-of-stencil-reduce is general enough to subsume map, reduce, map-reduce, stencil, stencil-reduce, and, crucially, their usage in a loop in both data-parallel and streaming applications, or a combination of both. The pattern makes it possible to deploy a single stencil computation kernel on different GPUs. We discuss the implementation of Loop-of-stencil-reduce in FastFlow, a framework for the implementation of applications based on the parallel patterns. Experiments are presented to illustrate the use of Loop-of-stencil-reduce in developing data-parallel kernels running on heterogeneous systems.

Low-rank iterative solvers for large-scale stochastic Galerkin linear systems

Otto-von-Guericke-Universität Magdeburg, Fakultät für Mathematik, Dissertation, 2016