Multiresolution Area-based Fractal Dimension Estimation of Signals Applied to EEG Data

In this paper, we present an approach to estimate fractal complexity of discrete time signal waveforms based on computation of area bounded by sample points of the signal at different time resolutions. The slope of best straight line fit to the graph of log(A(rk)A / rk(2)) versus log(l/rk) is estimated, where A(rk) is the area computed at different time resolutions and rk time resolutions at which the area have been computed. The slope quantifies complexity of the signal and it is taken as an estimate of the fractal dimension (FD). The proposed approach is used to estimate the fractal dimension of parametric fractal signals with known fractal dimensions and the method has given accurate results. The estimation accuracy of the method is compared with that of Higuchi's and Sevcik's methods. The proposed method has given more accurate results when compared with that of Sevcik's method and the results are comparable to that of the Higuchi's method. The practical application of the complexity measure in detecting change in complexity of signals is discussed using real sleep electroencephalogram recordings from eight different subjects. The FD-based approach has shown good performance in discriminating different stages of sleep.

Application of various viscosity theories to the viscosity data of methyl methacrylate-acrylonitrile random copolymersstar

Values of Ko, Flory constant related to unperturbed dimensions, are evaluated for methyl methacrylate-acrylonitrile random copolymers using Flory-Fox, Kurata-Stockmayer and Inagaki-Ptitsyn methods and compared with the Ko values obtained by Stockmayer-Fixman method. Ko values are seen to be less in solvents which have large a (Mark-Houwink exponent) values. A correlation between Ko and a is developed to arrive at a more reliable estimate of Ko for this copolymer system.

Big data

Making Sense of Mass Education provides an engaging and accessible analysis of traditional issues associated with mass education. The book challenges preconceptions about social class, gender and ethnicity discrimination; highlights the interplay between technology, media, popular culture and schooling; and inspects the relevance of ethics and philosophy in the modern classroom. This new edition has been comprehensively updated to provide current information regarding literature, statistics and legal policies, and significantly expands on the previous edition's structure of derailing traditional myths about education as a point of discussion. It also features two new chapters on Big Data and Globalisation and what they mean for the Australian classroom. Written for students, practising teachers and academics alike, Making Sense of Mass Education summarises the current educational landscape in Australia and looks at fundamental issues in society as they relate to education.

Normative values for corneal nerve morphology assessed using corneal confocal microscopy: A multinational normative data set

OBJECTIVE Corneal confocal microscopy is a novel diagnostic technique for the detection of nerve damage and repair in a range of peripheral neuropathies, in particular diabetic neuropathy. Normative reference values are required to enable clinical translation and wider use of this technique. We have therefore undertaken a multicenter collaboration to provide worldwide age-adjusted normative values of corneal nerve fiber parameters. RESEARCH DESIGN AND METHODS A total of 1,965 corneal nerve images from 343 healthy volunteers were pooled from six clinical academic centers. All subjects underwent examination with the Heidelberg Retina Tomograph corneal confocal microscope. Images of the central corneal subbasal nerve plexus were acquired by each center using a standard protocol and analyzed by three trained examiners using manual tracing and semiautomated software (CCMetrics). Age trends were established using simple linear regression, and normative corneal nerve fiber density (CNFD), corneal nerve fiber branch density (CNBD), corneal nerve fiber length (CNFL), and corneal nerve fiber tortuosity (CNFT) reference values were calculated using quantile regression analysis. RESULTS There was a significant linear age-dependent decrease in CNFD (-0.164 no./mm(2) per year for men, P < 0.01, and -0.161 no./mm(2) per year for women, P < 0.01). There was no change with age in CNBD (0.192 no./mm(2) per year for men, P = 0.26, and -0.050 no./mm(2) per year for women, P = 0.78). CNFL decreased in men (-0.045 mm/mm(2) per year, P = 0.07) and women (-0.060 mm/mm(2) per year, P = 0.02). CNFT increased with age in men (0.044 per year, P < 0.01) and women (0.046 per year, P < 0.01). Height, weight, and BMI did not influence the 5th percentile normative values for any corneal nerve parameter. CONCLUSIONS This study provides robust worldwide normative reference values for corneal nerve parameters to be used in research and clinical practice in the study of diabetic and other peripheral neuropathies.

Annual forecasting of the Australian macadamia crop - integrating tree census data with statistical climate-adjustment models

To facilitate marketing and export, the Australian macadamia industry requires accurate crop forecasts. Each year, two levels of crop predictions are produced for this industry. The first is an overall longer-term forecast based on tree census data of growers in the Australian Macadamia Society (AMS). This data set currently accounts for around 70% of total production, and is supplemented by our best estimates of non-AMS orchards. Given these total tree numbers, average yields per tree are needed to complete the long-term forecasts. Yields from regional variety trials were initially used, but were found to be consistently higher than the average yields that growers were obtaining. Hence, a statistical model was developed using growers' historical yields, also taken from the AMS database. This model accounted for the effects of tree age, variety, year, region and tree spacing, and explained 65% of the total variation in the yield per tree data. The second level of crop prediction is an annual climate adjustment of these overall long-term estimates, taking into account the expected effects on production of the previous year's climate. This adjustment is based on relative historical yields, measured as the percentage deviance between expected and actual production. The dominant climatic variables are observed temperature, evaporation, solar radiation and modelled water stress. Initially, a number of alternate statistical models showed good agreement within the historical data, with jack-knife cross-validation R2 values of 96% or better. However, forecasts varied quite widely between these alternate models. Exploratory multivariate analyses and nearest-neighbour methods were used to investigate these differences. For 2001-2003, the overall forecasts were in the right direction (when compared with the long-term expected values), but were over-estimates. In 2004 the forecast was well under the observed production, and in 2005 the revised models produced a forecast within 5.1% of the actual production. Over the first five years of forecasting, the absolute deviance for the climate-adjustment models averaged 10.1%, just outside the targeted objective of 10%.

Analysis of EXAFS data of multiphasic heterogeneous catalysts

Cu K-edge EXAFS spectra of Cu-Ni/Al2O3 and Cu-ZnO catalysts, both of which contain more than one Cu species, have been analysed making use of an additive relation for the EXAFS function. The analysis, which also makes use of residual spectra for identifying the species, shows good agreement between experimental and calculated spectra.

Harnessing information from injury narrative in the 'big data' era: Understanding and applying machine learning for injury surveillance

Objective Vast amounts of injury narratives are collected daily and are available electronically in real time and have great potential for use in injury surveillance and evaluation. Machine learning algorithms have been developed to assist in identifying cases and classifying mechanisms leading to injury in a much timelier manner than is possible when relying on manual coding of narratives. The aim of this paper is to describe the background, growth, value, challenges and future directions of machine learning as applied to injury surveillance. Methods This paper reviews key aspects of machine learning using injury narratives, providing a case study to demonstrate an application to an established human-machine learning approach. Results The range of applications and utility of narrative text has increased greatly with advancements in computing techniques over time. Practical and feasible methods exist for semi-automatic classification of injury narratives which are accurate, efficient and meaningful. The human-machine learning approach described in the case study achieved high sensitivity and positive predictive value and reduced the need for human coding to less than one-third of cases in one large occupational injury database. Conclusion The last 20 years have seen a dramatic change in the potential for technological advancements in injury surveillance. Machine learning of ‘big injury narrative data’ opens up many possibilities for expanded sources of data which can provide more comprehensive, ongoing and timely surveillance to inform future injury prevention policy and practice.

100 Years of U.S. Consumer Spending: Data for the Nation, New York City, and Boston

[From Preface] The Consumer Expenditure Survey is among the oldest publications of the Bureau of Labor Statistics. With information on the expenditures, incomes, and demographic characteristics of households, the survey documents the spending patterns and economic status of American families. This report offers a new approach to the use of Consumer Expenditure Survey data. Normally, the survey presents an indepth look at American households at a specific point in time, the reference period being a calendar year. Here, the authors use consumer expenditure data longitudinally and draw on information from decennial census reports to present a 100-year history of significant changes in consumer spending, economic status, and family demographics in the country as a whole, as well as in New York City and Boston.

The Effect of Framing on Layoff Decisions: Are More-Experienced Managers More Rational? Does Computerized Data Make Any Difference?

[Excerpt] The effects of framing on decisions has been widely studied, producing research that suggests individuals respond to framing in predictable and fairly consistent ways (Bazerman, 1984, 1990; Tversky & Kahneman, 1986; Thaler, 1980). The essential finding from this body of research is that "individuals treat risks concerning perceived gains (for example, saving jobs and plants) differently from risks concerning perceived losses (losing jobs and plants)" (Bazerman, 1990, pp. 49-50). Specifically, individuals tend to avoid risks concerning gains, and seek risks concerning losses.

Application of phytotoxicity data to a new Australian soil quality guideline framework for biosolids

To protect terrestrial ecosystems and humans from contaminants many countries and jurisdictions have developed soil quality guidelines (SQGs). This study proposes a new framework to derive SQGs and guidelines for amended soils and uses a case study based on phytotoxicity data of copper (Cu) and zinc (Zn) from field studies to illustrate how the framework could be applied. The proposed framework uses normalisation relationships to account for the effects of soil properties on toxicity data followed by a species sensitivity distribution (SSD) method to calculate a soil added contaminant limit (soil ACL) for a standard soil. The normalisation equations are then used to calculate soil ACLs for other soils. A soil amendment availability factor (SAAF) is then calculated as the toxicity and bioavailability of pure contaminants and contaminants in amendments can be different. The SAAF is used to modify soil ACLs to ACLs for amended soils. The framework was then used to calculate soil ACLs for copper (Cu) and zinc (Zn). For soils with pH of 4-8 and OC content of 1-6%, the ACLs range from 8 mg/kg to 970 mg/kg added Cu. The SAAF for Cu was pH dependant and varied from 1.44 at pH 4 to 2.15 at pH 8. For soils with pH of 4-8 and OC content of 1-6%, the ACLs for amended soils range from 11 mg/kg to 2080 mg/kg added Cu. For soils with pH of 4-8 and a CEC from 5-60, the ACLs for Zn ranged from 21 to 1470 mg/kg added Zn. A SAAF of one was used for Zn as it concentrations in plant tissue and soil to water partitioning showed no difference between biosolids and soluble Zn salt treatments, indicating that Zn from biosolids and Zn salts are equally bioavailable to plants.

Australian Bat Lyssavirus

In Chapter 1, the literature relating to rabies virus and the rabies like lyssaviruses is reviewed. In Chapter 2, data are presented from 1170 diagnostic submissions for ABLV testing by fluorescent antibody test (Centocor FAT). All 27 non-bat submissions were ABLV-negative. Of 1143 bat accessions 74 (16%) were ABLV-positive, including 69 of 974 (7.1%) flying foxes (Pteropus spp.), 5 of 7 (71.4%) Saccolaimus flaviventris (Yellow-bellied sheathtail bats), none of 151 other microchiropteran bats, and none of 11 unidentified bats. Statistical analysis of data from 868 wild Black, Grey-headed, Little Red and Spectacled flying foxes (Pteropus alecto, P. poliocephalus, P. scapulatus, and P. conspicillatus) indicated that three factors; species, health status and age were associated with significant (p< 0.001) differences in the proportion of ABLV-positive bats. Other factors including sex, whether the bat bit a person or animal, region, year, and season submitted, were not associated with ABLV. Case data for 74 ABLV-positive bats, including the circumstances in which they were found and clinical signs, is presented. In Chapter 3, the aetiological diagnosis was investigated for 100 consecutive flying fox submissions with neurological signs. ABLV (32%), spinal and head injuries (29%), and neuro-angiostrongylosis (18%) accounted for most neurological syndromes in flying foxes. No evidence of lead poisoning was found in unwell (n=16) or healthy flying foxes (n=50). No diagnosis was reached for 16 cases, all of which were negative for ABLV by TaqMan PCR. The molecular diversity of ABLV was examined in Chapter 4 by sequencing 36 bases of the leader sequence, the entire N gene, and start of the P gene of 28 isolates from pteropid bats and 3 isolates from Yellow-bellied sheathtail (YBST) bats. Phylogenetic analysis indicated all ABLV isolates clustered together as a discrete group within the Lyssavirus genera closely related to rabies virus and European bat lyssavirus-2 isolates. The ABLV lineage consisted of two variants; one (ybst-ABLV) consisted of isolates only from YBST bats, the other (pteropid-ABLV) was common to Black, Grey-headed and Little Red flying foxes. No associations were found between the sequences and either the geographical location or year found, or individual flying fox species. In Chapter 5, 15 inocula prepared from the brains or salivary glands of naturally-infected bats were evaluated by intracerebral (IC) and footpad (FP) inoculation of Quackenbush mice in order to select and characterize a highly virulent inoculum for further use in bats (Inoculum 5). In Chapter 6, nine Grey-headed flying foxes were inoculated with 105.2 to 105.5 MICED50 of Inoculum 5 divided into four sites, left footpad, pectoral muscle, temporal muscle and muzzle. Another bat was inoculated with half this dose divided into the footpad and pectoral muscle only. Seven of 10 bats developed clinical disease of 1 to 4 days duration between PI-days 10 and 19 and were shown to be ABL-positive by FAT, HAM immunoperoxidase staining, virus isolation in mice, and TaqMan PCR. Five of the seven bats displayed overt aggression, one died during a seizure, and one showed intractable agitation, pacing, tremors, and ataxia. Viral antigen was demonstrated throughout the central and peripheral nervous systems and in the epithelial cells of the submandibular salivary glands (n=4). All affected bats had mild to moderate non-suppurative meningoencephalitis and severe ganglioneuritis. No ABLV was detected in three bats that remained well until the end of the experiment on day 82. One survivor developed a strong but transient antibody response. In Chapter 7, the relative virulence of inocula prepared from the brains and salivary glands of experimentally infected flying foxes was evaluated in mice by IC and FP inoculation and TaqMan assay. The effects in mice were correlated to the TaqMan CT value and indicated a crude association between virulence and CT value that has potential application in the selection of inocula. In Chapter 8, 36 Black and Grey-headed flying foxes were vaccinated with one (day 0) or two (+ day 28) doses of Nobivac rabies vaccine and co-vaccinated with keyhole limpet haemocyanin (KLH). All bats responded to the Nobivac vaccine with a rabies-RFFIT titer > 0.5 IU/mL that is nominally indicative of protective immunity. Plasma from bats with rabies titres >2 IU/mL had cross-neutralising ABLV titres >1:154. A specifically developed ELISA detected a strong but transient response to KLH.

Kadonneet pojat : Monitapaustutkimus ESY-poikien kompleksisesta koulu-urasta ja elämänkulusta

Lost boys. A multiple case study of the complex school career and life-course of male students who have attended special classes for the emotionally and behaviourally maladjusted The purpose of this thesis is to describe the school career and the life-course of eight former special-class students from the comprehensive school to their further education and into adulthood. The members of the target group have been students of special classes for pupils with emotional and behavioural difficulties in southern Finland. The interviews were made 1994-1997 at school and for follow-up interviews 2002-2003, when the participants were already adults. Six mothers were also interviewed. The qualitative data was gathered using individual interviews and Adult Attachment Interview. The aim was to explore the life-histories of subjects from early childhood to early adulthood. Information was gathered also from the documents concerning the students´ school attendance. Every single life-history is illustrated as a life-course graphic. The data has been analysed using different frames of reference and combining different theories. In addition to theories considering developmental risk factors and protective factors, the data is considered using theories of control over life, attribution, self-efficacy and identity and attitudes towards education. The experiential living mode of the students has been studied, as well. The results of this study show that the frames of references which are used complement each other. The target students clustered identically in spite of the frames of reference. As a result, the study has illustrated the same phenomenon from different points of view. The results of the study consist of three types of school careers: The winding career, the vicious circle career and the straight career. The three careers differ from each other in developmental risk and protective factors and post-school life-courses of the students. The type of childhood families and especially the fathers´ attention to the school education as well as the free time of their sons was important. Keywords: Pupils with emotional and behavioural difficulties, maladjustment to school, life-course, identity

Estimating cell diffusivity and cell proliferation rate by interpreting IncuCyte ZOOM™ assay data using the Fisher-Kolmogorov model

Background: Standard methods for quantifying IncuCyte ZOOM™ assays involve measurements that quantify how rapidly the initially-vacant area becomes re-colonised with cells as a function of time. Unfortunately, these measurements give no insight into the details of the cellular-level mechanisms acting to close the initially-vacant area. We provide an alternative method enabling us to quantify the role of cell motility and cell proliferation separately. To achieve this we calibrate standard data available from IncuCyte ZOOM™ images to the solution of the Fisher-Kolmogorov model. Results: The Fisher-Kolmogorov model is a reaction-diffusion equation that has been used to describe collective cell spreading driven by cell migration, characterised by a cell diffusivity, D, and carrying capacity limited proliferation with proliferation rate, λ, and carrying capacity density, K. By analysing temporal changes in cell density in several subregions located well-behind the initial position of the leading edge we estimate λ and K. Given these estimates, we then apply automatic leading edge detection algorithms to the images produced by the IncuCyte ZOOM™ assay and match this data with a numerical solution of the Fisher-Kolmogorov equation to provide an estimate of D. We demonstrate this method by applying it to interpret a suite of IncuCyte ZOOM™ assays using PC-3 prostate cancer cells and obtain estimates of D, λ and K. Comparing estimates of D, λ and K for a control assay with estimates of D, λ and K for assays where epidermal growth factor (EGF) is applied in varying concentrations confirms that EGF enhances the rate of scratch closure and that this stimulation is driven by an increase in D and λ, whereas K is relatively unaffected by EGF. Conclusions: Our approach for estimating D, λ and K from an IncuCyte ZOOM™ assay provides more detail about cellular-level behaviour than standard methods for analysing these assays. In particular, our approach can be used to quantify the balance of cell migration and cell proliferation and, as we demonstrate, allow us to quantify how the addition of growth factors affects these processes individually.

Maize kernel hardness classification by near infrared (NIR) hyperspectral imaging and multivariate data analysis.

The use of near infrared (NIR) hyperspectral imaging and hyperspectral image analysis for distinguishing between hard, intermediate and soft maize kernels from inbred lines was evaluated. NIR hyperspectral images of two sets (12 and 24 kernels) of whole maize kernels were acquired using a Spectral Dimensions MatrixNIR camera with a spectral range of 960-1662 nm and a sisuChema SWIR (short wave infrared) hyperspectral pushbroom imaging system with a spectral range of 1000-2498 nm. Exploratory principal component analysis (PCA) was used on absorbance images to remove background, bad pixels and shading. On the cleaned images. PCA could be used effectively to find histological classes including glassy (hard) and floury (soft) endosperm. PCA illustrated a distinct difference between glassy and floury endosperm along principal component (PC) three on the MatrixNIR and PC two on the sisuChema with two distinguishable clusters. Subsequently partial least squares discriminant analysis (PLS-DA) was applied to build a classification model. The PLS-DA model from the MatrixNIR image (12 kernels) resulted in root mean square error of prediction (RMSEP) value of 0.18. This was repeated on the MatrixNIR image of the 24 kernels which resulted in RMSEP of 0.18. The sisuChema image yielded RMSEP value of 0.29. The reproducible results obtained with the different data sets indicate that the method proposed in this paper has a real potential for future classification uses.

Comprehensive Path-sensitive Data-flow Analysis

Data-flow analysis is an integral part of any aggressive optimizing compiler. We propose a framework for improving the precision of data-flow analysis in the presence of complex control-flow. W initially perform data-flow analysis to determine those control-flow merges which cause the loss in data-flow analysis precision. The control-flow graph of the program is then restructured such that performing data-flow analysis on the resulting restructured graph gives more precise results. The proposed framework is both simple, involving the familiar notion of product automata, and also general, since it is applicable to any forward data-flow analysis. Apart from proving that our restructuring process is correct, we also show that restructuring is effective in that it necessarily leads to more optimization opportunities. Furthermore, the framework handles the trade-off between the increase in data-flow precision and the code size increase inherent in the restructuring. We show that determining an optimal restructuring is NP-hard, and propose and evaluate a greedy strategy. The framework has been implemented in the Scale research compiler, and instantiated for the specific problem of Constant Propagation. On the SPECINT 2000 benchmark suite we observe an average speedup of 4% in the running times over Wegman-Zadeck conditional constant propagation algorithm and 2% over a purely path profile guided approach.