A method to determine the impact of reduced visual function on nodule detection performance

Purpose - In this study we aim to validate a method to assess the impact of reduced visual function and observer performance concurrently with a nodule detection task. Materials and methods - Three consultant radiologists completed a nodule detection task under three conditions: without visual defocus (0.00 Dioptres; D), and with two different magnitudes of visual defocus (−1.00 D and −2.00 D). Defocus was applied with lenses and visual function was assessed prior to each image evaluation. Observers evaluated the same cases on each occasion; this comprised of 50 abnormal cases containing 1–4 simulated nodules (5, 8, 10 and 12 mm spherical diameter, 100 HU) placed within a phantom, and 25 normal cases (images containing no nodules). Data was collected under the free-response paradigm and analysed using Rjafroc. A difference in nodule detection performance would be considered significant at p < 0.05. Results - All observers had acceptable visual function prior to beginning the nodule detection task. Visual acuity was reduced to an unacceptable level for two observers when defocussed to −1.00 D and for one observer when defocussed to −2.00 D. Stereoacuity was unacceptable for one observer when defocussed to −2.00 D. Despite unsatisfactory visual function in the presence of defocus we were unable to find a statistically significant difference in nodule detection performance (F(2,4) = 3.55, p = 0.130). Conclusion - A method to assess visual function and observer performance is proposed. In this pilot evaluation we were unable to detect any difference in nodule detection performance when using lenses to reduce visual function.

Comics as a literary-didactic method and their use for reducing gender differences in reading literacy at the primary level of education

The aim of the present study was to examine the effect of the systematic use of comics as a literary-didactic method to reduce gender differences in reading literacy and reading motivation at the primary level of education. It was assumed that the use of comics would have a positive effect on pupils’ reading literacy and reading motivation, while also reducing the aforementioned differences between boys and girls. The dimensions of reading literacy and reading motivation were examined in experimental and control groups, before and after the intervention, by means of questionnaires and tests for pupils. The sample consisted of 143 pupils from second to fifth grade from two Slovenian primary schools in a rural environment, of which 73 pupils participated in the experimental group and 70 pupils represented the control group. Effects of the use of comics as a literary-didactic method were not found: using comics as a literary-didactic method did not have a statistically significant effect on pupils’ reading literacy and reading motivation. However, when the four-way structure of the research (taking into account the age and gender of the pupils) was considered, some subgroups showed a statistically significant increase in reading interest and attitude towards reading. No reduction of gender differences in reading literacy and reading motivation was found. Based on the results, guidelines for further research are established and suggestions are offered for teachers’ work. (DIPF/Orig.)

The Evolution of Massive Young Stellar Objects in the Large Magellanic Cloud

This thesis presents an analysis of the largest catalog to date of infrared spectra of massive young stellar objects in the Large Magellanic Cloud. Evidenced by their very different spectral features, the luminous objects span a range of evolutionary states from those most embedded in their natal molecular material to those that have dissipated and ionized their surroundings to form compact HII regions and photodissociation regions. We quantify the contributions of the various spectral features using the statistical method of principal component analysis. Using this analysis, we classify the YSO spectra into several distinct groups based upon their dominant spectral features: silicate absorption (S Group), silicate absorption and fine-structure line emission (SE), polycyclic aromatic hydrocarbon (PAH) emission (P Group), PAH and fine-structure line emission (PE), and only fine-structure line emission (E). Based upon the relative numbers of sources in each category, we are able to estimate the amount of time massive YSOs spend in each evolutionary stage. We find that approximately 50% of the sources have ionic fine-structure lines, indicating that a compact HII region forms about half-way through the YSO lifetime probed in our study. Of the 277 YSOs we collected spectra for, 41 have ice absorption features, indicating they are surrounded by cold ice-bearing dust particles. We have decomposed the shape of the ice features to probe the composition and thermal history of the ice. We find that most the CO2 ice is embedded a polar ice matrix that has been thermally processed by the embedded YSO. The amount of thermal processing may be correlated with the luminosity of the YSO. Using the Australia Telescope Compact Array, we imaged the dense gas around a subsample of our sources in the HII complexes N44, N105, N113, and N159 using HCO+ and HCN as dense gas tracers. We find that the molecular material in star forming environments is highly clumpy, with clumps that range from subparsec to ~2 parsecs in size and with masses between 10^2 to 10^4 solar masses. We find that there are varying levels of star formation in the clumps, with the lower-mass clumps tending to be without massive YSOs. These YSO-less clumps could either represent an earlier stage of clump to the more massive YSO-bearing ones or clumps that will never form a massive star. Clumps with massive YSOs at their centers have masses larger than those with massive YSOs at their edges, and we suggest that the difference is evolutionary: edge YSO clumps are more advanced than those with YSOs at their centers. Clumps with YSOs at their edges may have had a significant fraction of their mass disrupted or destroyed by the forming massive star. We find that the strength of the silicate absorption seen in YSO IR spectra feature is well-correlated with the on-source HCO+ and HCN flux densities, such that the strength of the feature is indicative of the embeddedness of the YSO. We estimate that ~40% of the entire spectral sample has strong silicate absorption features, implying that the YSOs are embedded in circumstellar material for about 40% of the time probed in our study.

A survey on prevalence rate of aflatoxigenic species of Aspergillus and residues of aflatoxins by ELISA method in cold-water cultural fish (rainbow trout) feeds in Tehran and West Azarbayjan provinces-Iran

Aflatoxins are one kind of fungal toxins produced by species of toxigenic Aspergillus (A. flavus and A. parasiticus) and in other words they are secondary metabolites which are considered as one of the threatening factors of food consumer's health. In this research 96 samples of cold-water cultural fish feed, rainbow trout, during the seasons of spring and summer of 2007 (every fifteenth of the month) were randomized (by simple and stratified random) to determine: 1. The prevalence rate of aflatoxigenic species of Aspergillus in stored feed of cold-water cultural fish in West Azarbayjan cultural fish farms in both seasons (spring and summer); 2. The residues of total aflatoxin in stored feed of fish in cultural fish farms of West Azarbayjan in both seasons by ELISA method; and 3. The residues of that toxin in feed produced in aquatic feed factories in Tehran and West Azarbyjan provinces with the same method. In order to study prevalence rate of toxigenic species of Aspergillus, pour-plate culture method by general medium such as Malt Extract Agar (M.E.A.) and Sabouraud-Dextrose Agar (S.D.A.) and by standard No.997 of Iranian Standard Institute were used. The produced colonies were examined microscopically. To determine the aflatoxins residues, ELISA method using Agra-Quant kit of Romer Lab company, were applied. The results of this survey indicated that only 8.3% of the samples were infected by A. flavus. A. parasiticus was not observed. There were no significant differences between the prevalence rate of AFT and seasons/months, either (P<0.05). Evaluating mean of aflatoxin rate showed that the rates of this variable are lower than the tolerance levels designated by the joint FAO/WHO expert committee (The mean of AFT in all data was lower than 11 ppb). Furthermore, mean of total AFT residues rates of stored feed of various cultural center of West Azarbayjan and Tehran factories were comparable in spring and summer, and no significant differences were observed (P<0.05). But there were significant differences between the total aflatoxin rates in the feed of West Azarbayjan factory and spring and summer (P<0.05), and AFT residues in spring (8.6 ppb) were higher than summer (6.1 ppb). Prevalence rates of AFT in Tehran feed factories (9.2 ppb) are higher than W. Azarbayjan (7.4 ppb). In other words, location was considered as a decisive factor in total AFT rates of samples. Moreover, the results indicated that there was significant difference between total aflatoxin rates of feed and cultural centers (P<0.05). The mean of AFT rates in embankment dam cultural fish farms (6.75 ppb) and multi-functions cultural fish farms (6.25 ppb) was higher than individual cultural pond (4.67 ppb). In conclusion, the finally results of this survey indicated that the lower rates of Aspergillus is not effective on the presence of total aflatoxin rates in trout feed. Due to low levels of aflatoxin rates (lower than 20 ppb), the produced feed of cold-cultural fishes, Rainbow Trout, in Tehran and West Azarbayjan provinces, in spring and summer of 2007, were safe and healthy both for fish and their consumers.

Spectral graph theory with applications to quantum adiabatic optimization

In this dissertation I draw a connection between quantum adiabatic optimization, spectral graph theory, heat-diffusion, and sub-stochastic processes through the operators that govern these processes and their associated spectra. In particular, we study Hamiltonians which have recently become known as ``stoquastic'' or, equivalently, the generators of sub-stochastic processes. The operators corresponding to these Hamiltonians are of interest in all of the settings mentioned above. I predominantly explore the connection between the spectral gap of an operator, or the difference between the two lowest energies of that operator, and certain equilibrium behavior. In the context of adiabatic optimization, this corresponds to the likelihood of solving the optimization problem of interest. I will provide an instance of an optimization problem that is easy to solve classically, but leaves open the possibility to being difficult adiabatically. Aside from this concrete example, the work in this dissertation is predominantly mathematical and we focus on bounding the spectral gap. Our primary tool for doing this is spectral graph theory, which provides the most natural approach to this task by simply considering Dirichlet eigenvalues of subgraphs of host graphs. I will derive tight bounds for the gap of one-dimensional, hypercube, and general convex subgraphs. The techniques used will also adapt methods recently used by Andrews and Clutterbuck to prove the long-standing ``Fundamental Gap Conjecture''.

A deformation model of flexible, high area-to-mass ratio debris under perturbations and validation method

A new type of space debris was recently discovered by Schildknecht in near -geosynchronous orbit (GEO). These objects were later identified as exhibiting properties associated with High Area-to-Mass ratio (HAMR) objects. According to their brightness magnitudes (light curve), high rotation rates and composition properties (albedo, amount of specular and diffuse reflection, colour, etc), it is thought that these objects are multilayer insulation (MLI). Observations have shown that this debris type is very sensitive to environmental disturbances, particularly solar radiation pressure, due to the fact that their shapes are easily deformed leading to changes in the Area-to-Mass ratio (AMR) over time. This thesis proposes a simple effective flexible model of the thin, deformable membrane with two different methods. Firstly, this debris is modelled with Finite Element Analysis (FEA) by using Bernoulli-Euler theory called “Bernoulli model”. The Bernoulli model is constructed with beam elements consisting 2 nodes and each node has six degrees of freedom (DoF). The mass of membrane is distributed in beam elements. Secondly, the debris based on multibody dynamics theory call “Multibody model” is modelled as a series of lump masses, connected through flexible joints, representing the flexibility of the membrane itself. The mass of the membrane, albeit low, is taken into account with lump masses in the joints. The dynamic equations for the masses, including the constraints defined by the connecting rigid rod, are derived using fundamental Newtonian mechanics. The physical properties of both flexible models required by the models (membrane density, reflectivity, composition, etc.), are assumed to be those of multilayer insulation. Both flexible membrane models are then propagated together with classical orbital and attitude equations of motion near GEO region to predict the orbital evolution under the perturbations of solar radiation pressure, Earth’s gravity field, luni-solar gravitational fields and self-shadowing effect. These results are then compared to two rigid body models (cannonball and flat rigid plate). In this investigation, when comparing with a rigid model, the evolutions of orbital elements of the flexible models indicate the difference of inclination and secular eccentricity evolutions, rapid irregular attitude motion and unstable cross-section area due to a deformation over time. Then, the Monte Carlo simulations by varying initial attitude dynamics and deformed angle are investigated and compared with rigid models over 100 days. As the results of the simulations, the different initial conditions provide unique orbital motions, which is significantly different in term of orbital motions of both rigid models. Furthermore, this thesis presents a methodology to determine the material dynamic properties of thin membranes and validates the deformation of the multibody model with real MLI materials. Experiments are performed in a high vacuum chamber (10-4 mbar) replicating space environment. A thin membrane is hinged at one end but free at the other. The free motion experiment, the first experiment, is a free vibration test to determine the damping coefficient and natural frequency of the thin membrane. In this test, the membrane is allowed to fall freely in the chamber with the motion tracked and captured through high velocity video frames. A Kalman filter technique is implemented in the tracking algorithm to reduce noise and increase the tracking accuracy of the oscillating motion. The forced motion experiment, the last test, is performed to determine the deformation characteristics of the object. A high power spotlight (500-2000W) is used to illuminate the MLI and the displacements are measured by means of a high resolution laser sensor. Finite Element Analysis (FEA) and multibody dynamics of the experimental setups are used for the validation of the flexible model by comparing with the experimental results of displacements and natural frequencies.

Application of the latency insertion method (LIM) to the analysis of large circuit interconnect networks

The focus of this research is to explore the applications of the finite difference formulation based on the latency insertion method (LIM) to the analysis of circuit interconnects. Special attention is devoted to addressing the issues that arise in very large networks such as on-chip signal and power distribution networks. We demonstrate that the LIM has the power and flexibility to handle various types of analysis required at different stages of circuit design. The LIM is particularly suitable for simulations of very large scale linear networks and can significantly outperform conventional circuit solvers (such as SPICE).

Finite difference calculations of permeability in large domains in a wide porosity range.

Determining effective hydraulic, thermal, mechanical and electrical properties of porous materials by means of classical physical experiments is often time-consuming and expensive. Thus, accurate numerical calculations of material properties are of increasing interest in geophysical, manufacturing, bio-mechanical and environmental applications, among other fields. Characteristic material properties (e.g. intrinsic permeability, thermal conductivity and elastic moduli) depend on morphological details on the porescale such as shape and size of pores and pore throats or cracks. To obtain reliable predictions of these properties it is necessary to perform numerical analyses of sufficiently large unit cells. Such representative volume elements require optimized numerical simulation techniques. Current state-of-the-art simulation tools to calculate effective permeabilities of porous materials are based on various methods, e.g. lattice Boltzmann, finite volumes or explicit jump Stokes methods. All approaches still have limitations in the maximum size of the simulation domain. In response to these deficits of the well-established methods we propose an efficient and reliable numerical method which allows to calculate intrinsic permeabilities directly from voxel-based data obtained from 3D imaging techniques like X-ray microtomography. We present a modelling framework based on a parallel finite differences solver, allowing the calculation of large domains with relative low computing requirements (i.e. desktop computers). The presented method is validated in a diverse selection of materials, obtaining accurate results for a large range of porosities, wider than the ranges previously reported. Ongoing work includes the estimation of other effective properties of porous media.

Spectral-based mesh segmentation

In design and manufacturing, mesh segmentation is required for FACE construction in boundary representation (BRep), which in turn is central for featurebased design, machining, parametric CAD and reverse engineering, among others -- Although mesh segmentation is dictated by geometry and topology, this article focuses on the topological aspect (graph spectrum), as we consider that this tool has not been fully exploited -- We preprocess the mesh to obtain a edgelength homogeneous triangle set and its Graph Laplacian is calculated -- We then produce a monotonically increasing permutation of the Fiedler vector (2nd eigenvector of Graph Laplacian) for encoding the connectivity among part feature submeshes -- Within the mutated vector, discontinuities larger than a threshold (interactively set by a human) determine the partition of the original mesh -- We present tests of our method on large complex meshes, which show results which mostly adjust to BRep FACE partition -- The achieved segmentations properly locate most manufacturing features, although it requires human interaction to avoid over segmentation -- Future work includes an iterative application of this algorithm to progressively sever features of the mesh left from previous submesh removals

Inverse Spectral Methods in Acoustic Normal Mode Velocimetry of High Reynolds Number Spherical Couette Flows

Experimental geophysical fluid dynamics often examines regimes of fluid flow infeasible for computer simulations. Velocimetry of zonal flows present in these regimes brings many challenges when the fluid is opaque and vigorously rotating; spherical Couette flows with molten metals are one such example. The fine structure of the acoustic spectrum can be related to the fluid’s velocity field, and inverse spectral methods can be used to predict and, with sufficient acoustic data, mathematically reconstruct the velocity field. The methods are to some extent inherited from helioseismology. This work develops a Finite Element Method suitable to matching the geometries of experimental setups, as well as modelling the acoustics based on that geometry and zonal flows therein. As an application, this work uses the 60-cm setup Dynamo 3.5 at the University of Maryland Nonlinear Dynamics Laboratory. Additionally, results obtained using a small acoustic data set from recent experiments in air are provided.

Soil characteristics in Doon Valley (north west Himalaya, India) by inversion of H/V spectral ratios from ambient noise measurements

Past and recent observations have shown that the local site conditions significantly affect the behavior of seismic waves and its potential to cause destructive earthquakes. Thus, seismic microzonation studies have become crucial for seismic hazard assessment, providing local soil characteristics that can help to evaluate the possible seismic effects. Among the different methods used for estimating the soil characteristics, the ones based on ambient noise measurements, such as the H/V technique, become a cheap, non-invasive and successful way for evaluating the soil properties along a studied area. In this work, ambient noise measurements were taken at 240 sites around the Doon Valley, India, in order to characterize the sediment deposits. First, the H/V analysis has been carried out to estimate the resonant frequencies along the valley. Subsequently, some of this H/V results have been inverted, using the neighborhood algorithm and the available geotechnical information, in order to provide an estimation of the S-wave velocity profiles at the studied sites. Using all these information, we have characterized the sedimentary deposits in different areas of the Doon Valley, providing the resonant frequency, the soil thickness, the mean S-wave velocity of the sediments, and the mean S-wave velocity in the uppermost 30 m.

Reliability of graphite furnace atomic absorption spectrometry as alternative method for trace analysis of arsenic in natural medicinal products

Purpose: To evaluate the comparative efficiency of graphite furnace atomic absorption spectrometry (GFAAS) and hydride generation atomic absorption spectrometry (HGAAS) for trace analysis of arsenic (As) in natural herbal products (NHPs). Method: Arsenic analysis in natural herbal products and standard reference material was conducted using atomic absorption spectrometry (AAS), namely, hydride generation AAS (HGAAS) and graphite furnace (GFAAS). The samples were digested with HNO3–H2O2 in a ratio of 4:1 using microwaveassisted acid digestion. The methods were validated with the aid of the standard reference material 1515 Apple Leaves (SRM) from NIST Results: Mean recovery of three different samples of NHPs, using HGAAS and GFAAS, ranged from 89.3 - 91.4 %, and 91.7 - 93.0 %, respectively. The difference between the two methods was insignificant. A (P= 0.5), B (P=0.4) and C (P=0.88) Relative standard deviation (RSD) RSD, i.e., precision was 2.5 - 6.5 % and 2.3 - 6.7 % using HGAAS and GFAAS techniques, respectively. Recovery of arsenic in SRM was 98 and 102 % by GFAAS and HGAAS, respectively. Conclusion: GFAAS demonstrates acceptable levels of precision and accuracy. Both techniques possess comparable accuracy and repeatability. Thus, the two methods are recommended as an alternative approach for trace analysis of arsenic in natural herbal products.

Functional, clustered, feedforward, and mesoscale brain networks

The brain is a network spanning multiple scales from subcellular to macroscopic. In this thesis I present four projects studying brain networks at different levels of abstraction. The first involves determining a functional connectivity network based on neural spike trains and using a graph theoretical method to cluster groups of neurons into putative cell assemblies. In the second project I model neural networks at a microscopic level. Using diferent clustered wiring schemes, I show that almost identical spatiotemporal activity patterns can be observed, demonstrating that there is a broad neuro-architectural basis to attain structured spatiotemporal dynamics. Remarkably, irrespective of the precise topological mechanism, this behavior can be predicted by examining the spectral properties of the synaptic weight matrix. The third project introduces, via two circuit architectures, a new paradigm for feedforward processing in which inhibitory neurons have the complex and pivotal role in governing information flow in cortical network models. Finally, I analyze axonal projections in sleep deprived mice using data collected as part of the Allen Institute's Mesoscopic Connectivity Atlas. After normalizing for experimental variability, the results indicate there is no single explanatory difference in the mesoscale network between control and sleep deprived mice. Using machine learning techniques, however, animal classification could be done at levels significantly above chance. This reveals that intricate changes in connectivity do occur due to chronic sleep deprivation.

Modeling spectral changes in singing voice for pitch modification

We present an advanced method to achieve natural modifications when applying a pitch shifting process to singing voice by modifying the spectral envelope of the audio ex- cerpt. To this end, an all-pole spectral envelope model has been selected to describe the global variations of the spectral envelope with the changes of the pitch. We performed a pitch shifting process of some sustained vowels with the envelope processing and without it, and compared both by means of a survey open to volunteers in our website.

A COMPARISON OF PIXEL-BASED VERSUS OBJECT ORIENTED ANALYSIS OF LANDSLIDES USING HISTORICAL REMOTE SENSING DATA

With recent advances in remote sensing processing technology, it has become more feasible to begin analysis of the enormous historic archive of remotely sensed data. This historical data provides valuable information on a wide variety of topics which can influence the lives of millions of people if processed correctly and in a timely manner. One such field of benefit is that of landslide mapping and inventory. This data provides a historical reference to those who live near high risk areas so future disasters may be avoided. In order to properly map landslides remotely, an optimum method must first be determined. Historically, mapping has been attempted using pixel based methods such as unsupervised and supervised classification. These methods are limited by their ability to only characterize an image spectrally based on single pixel values. This creates a result prone to false positives and often without meaningful objects created. Recently, several reliable methods of Object Oriented Analysis (OOA) have been developed which utilize a full range of spectral, spatial, textural, and contextual parameters to delineate regions of interest. A comparison of these two methods on a historical dataset of the landslide affected city of San Juan La Laguna, Guatemala has proven the benefits of OOA methods over those of unsupervised classification. Overall accuracies of 96.5% and 94.3% and F-score of 84.3% and 77.9% were achieved for OOA and unsupervised classification methods respectively. The greater difference in F-score is a result of the low precision values of unsupervised classification caused by poor false positive removal, the greatest shortcoming of this method.