From image processing to topological modelling with <Emphasis Type="Italic">p</Emphasis>-adic numbers

Encoding the hierarchical structure of images by p-adic numbers allows for image processing and computer vision methods motivated from arithmetic physics. The p-adic Polyakov action leads to the p-adic diffusion equation in low level vision. Hierarchical segmentation provides another way of p-adic encoding. Then a topology on that finite set of p-adic numbers yields a hierarchy of topological models underlying the image. In the case of chain complexes, the chain maps yield conditions for the existence of a hierarchy, and these can be expressed in terms of p-adic integrals. Such a chain complex hierarchy is a special case of a persistence complex from computational topology, where it is used for computing persistence barcodes for shapes. The approach is motivated by the observation that using p-adic numbers often leads to more efficient algorithms than their real or complex counterparts.     

Inducing models of behavior from expert task performance in virtual environments

We developed an end-to-end process for inducing models of behavior from expert task performance through in-depth case study. A subject matter expert (SME) performed navigational and adversarial tasks in a virtual tank combat simulation, using the dTank and Unreal platforms. Using eye tracking and Cognitive Task Analysis, we identified the key goals pursued by and attributes used by the SME, including reliance on an egocentric spatial representation, and on the fly re-representation of terrain in qualitative terms such as “safe” and “risky”. We demonstrated methods for automatic extraction of these qualitative higher-order features from combinations of surface features present in the simulation, producing a terrain map that was visually similar to the SME annotated map. The application of decision-tree and instance-based machine learning methods to the transformed task data supported prediction of SME task selection with greater than 95 % accuracy, and SME action selection at a frequency of 10 Hz with greater than 63 % accuracy, with real time constraints placing limits on algorithm selection. A complete processing model is presented for a path driving task, with the induced generative model deviating from the SME chosen path by less than 2 meters on average. The derived attributes also enabled environment portability, with path driving models induced from dTank performance and deployed in Unreal demonstrating equivalent accuracy to those induced and deployed completely within Unreal.     

Specific resistivity of dislocations and vacancies for super-pure aluminium at 4.2 K determined in-situ and post-recovery deformation and correlated to flow stress

ABSTRACT

The evolution of dislocations during shape-change of metal forms results from microstructural shear mechanism that is essential to enhance ductility. However, at room temperatures for face-centred cubic metals, this evolution results in the generation of vacancies that tend to form nano-voids, the growth of which leads to ductile failure. The correlated occurrence of dislocations and vacancies may be differentiated using the change of resistivity with plastic strain at 4.2?K, because resistivity is very sensitive to single vacancies compared to the formation of stacking faulted defects and dislocations. In order to assess the microstructure, the specific resistivity of these defect species was measured at 4.2?K, whereby thermal recovery processes are non-existent. The resistivity per dislocation line-length per volume was determined to be 1.87?×?10^?25?Ωm³ for super-pure aluminium. The change in resistivity directly correlated to the shear flow stress squared. Vacancy-like defects formed during plastic flow were correlated to the recoverable resistivity after 298?K anneal and the derived volume fraction (C_V) from mechanical data. The magnitude could be expressed as 12.9?×?10^?9?Ωm per C_V in % or as 1.21?×?10^?25?Ωm³ in terms of line-length of vacancies per volume. The choice of representation depends on the presumed vacancy distribution. However, the recoverable flow stress upon 298?K anneal only appear to be proportional to √ C_V at low strains; that is, at high strains the generated vacancies had transformed to defects that give rise to a small decrease in resistivity but a more notable increase in the flow stress. The possible mechanisms for this transformation are discussed.     

Arylation Chemistry for Bioconjugation

Bioconjugation chemistry has been used to prepare modified biomolecules with functions beyond what nature intended. Central to these techniques is the development of highly efficient and selective bioconjugation reactions that operate under mild, biomolecule compatible conditions. Methods that form a nucleophile–sp² carbon bond show promise for creating bioconjugates with new modifications, sometimes resulting in molecules with unparalleled functions. Here we outline and review sulfur, nitrogen, selenium, oxygen, and carbon arylative bioconjugation strategies and their applications to modify peptides, proteins, sugars, and nucleic acids     

Scalable Biosynthesis of the Seaweed Neurochemical,Kainic Acid

Kainic acid, the flagship member of the kainoid family of natural neurochemicals, is a widely used neuropharmacological agent that helped unravel the key role of ionotropic glutamate receptors, including the kainate receptor, in the central nervous system. Worldwide shortages of this seaweed natural product in the year 2000 prompted numerous chemical syntheses, including scalable preparations with as few as six‐steps. Herein we report the discovery and characterization of the concise two‐enzyme biosynthetic pathway to kainic acid from l ‐glutamic acid and dimethylallyl pyrophosphate in red macroalgae and show that the biosynthetic genes are co‐clustered in genomes of Digenea simplex and Palmaria palmata. Moreover, we applied a key biosynthetic α‐ketoglutarate‐dependent dioxygenase enzyme in a biotransformation methodology to efficiently construct kainic acid on the gram scale. This study establishes both the feasibility of mining seaweed genomes for their biotechnological prowess.     

The intelligibility of speech in elementary school classrooms

This is the second of two papers describing the results of acoustical measurements and speech intelligibility tests in elementary school classrooms. The intelligibility tests were performed in 41 classrooms in 12 different schools evenly divided among grades 1, 3, and 6 students (nominally 6, 8, and 11 year olds). Speech intelligibility tests were carried out on classes of students seated at their own desks in their regular classrooms. Mean intelligibility scores were significantly related to signal-to-noise ratios and to the grade of the students. While the results are different than those from some previous laboratory studies that included less realistic conditions, they agree with previous in-classroom experiments. The results indicate that +15 dB signal-to-noise ratio is not adequate for the youngest children. By combining the speech intelligibility test results with measurements of speech and noise levels during actual teaching situations, estimates of the fraction of students experiencing near-ideal acoustical conditions were made. The results are used as a basis for estimating ideal acoustical criteria for elementary school classrooms.     

Evaluation of acoustical conditions for speech communication in working elementary school classrooms

Detailed acoustical measurements were made in 41 working elementary school classrooms near Ottawa, Canada to obtain more representative and more accurate indications of the acoustical quality of conditions for speech communication during actual teaching activities. This paper describes the room acoustics characteristics and noise environment of 27 traditional rectangular classrooms from the 41 measured rooms. The purpose of the work was to better understand how to improve speech communication between teachers and students. The study found, that on average, the students experienced: teacher speech levels of 60.4 dB A, noise levels of 49.1 dB A, and a mean speech-to-noise ratio of 11 dB A during teaching activities. The mean reverberation time in the occupied classrooms was 0.41 s, which was 10% less than in the unoccupied rooms. The reverberation time measurements were used to determine the average absorption added by each student. Detailed analyses of early and late-arriving speech sounds showed these sound levels could be predicted quite accurately and suggest improved approaches to room acoustics design.     

Differential etching of chalcogenides for infrared photonic waveguide structures

Chemical etching rates for two different chalcogenide glass compositions, As₄₀S₆₀ and As₂₄S₃₈Se₃₈, were studied using sodium hydroxide based etchant solutions. Etching was performed using a variation of standard photolithographic masking and wet-etching techniques. Variations in etch rate with NaOH concentration and glass composition were observed. The depth of etch was characterized using an optical profilometer. Etch rate differences as large as three orders of magnitude between these two glasses were observed at low NaOH concentration (0.053 M). We present a single variable etch rate curve of etch depth per time (nm/s) versus NaOH overall solution concentration (in M) for these two different chalcogenide glasses. This technology shows promise for fabricating photonic structures and has potential applications in fabricating novel photonic bandgap structures that will function in the long-wave infrared (LWIR) regime.