Blind extraction of cyclostationary signal from convolutional mixtures

Extracting a signal of interest from available measurements is a challenging problem. One property which can be utilized to extract the signal is cyclostationarity, which exists in many signals. Various blind source separation methods based on cyclostationarity have been reported in the literature but they assume that the mixing system is instantaneous. In this paper, we propose a method for blind extraction of cyclostationary signal from convolutional mixtures. Given that the signal of interest has a unique cyclostationary frequency and the sensors are placed close to the concerned signal, we show that the signal of interest can be estimated from the measured data. Simulations results show the effectiveness of our method.

Optimization of zeaxanthin and β-carotene extraction from Chlorella saccharophila isolated from New Zealand marine waters

Zeaxanthin is an important natural pigment which has found commercial application in food and nutritional supplements. Its potential widespread use requires an easy and effective extraction methodology for obtaining higher yields. Extraction from Chlorella sp. under optimized conditions demonstrated a marked reduction in extraction time (13.48min) compared with a control experiment (30min). The extraction conditions such as solvent/cell dry weight (CDW) ratio, power, pulse, time and their combinations were optimized using response surface methodology (RSM). Almost all the variables were shown significantly (p-value <0.05) affect the carotenoid yield. Significant interaction (p-value <0.05) was observed with a substantial effect on zeaxanthin yield for solvent/CDW ratio and power, as well as power and time, whereas the β-carotene control exhibited significant interaction between solvent/CDW ratio and pulse, as well as between pulse and time. The R 2-value approached unity in both models, demonstrating their accuracy. Data obtained from these interactions were used to construct 3D response plots. Solvent/CDW ratio of 67.38μlmg-1, power 27.82% (total power 500W), pulse length of 19.7s and time 13.48min were found to be the optimized conditions for zeaxanthin (11.2mgg-1) and β-carotene (4.98mgg-1) extraction.

Motor imagery data classification for BCI application using wavelet packet feature extraction

The noninvasive brain imaging modalities have provided us an extraordinary means for monitoring the working brain. Among these modalities, Electroencephalography (EEG) is the most widely used technique for measuring the brain signals under different tasks, due to its mobility, low cost, and high temporal resolution. In this paper we investigate the use of EEG signals in brain-computer interface (BCI) systems.

Bayesian nonparametric extraction of hidden contexts from pervasive honest signals

Hidden patterns and contexts play an important part in intelligent pervasive systems. Most of the existing works have focused on simple forms of contexts derived directly from raw signals. High-level constructs and patterns have been largely neglected or remained under-explored in pervasive computing, mainly due to the growing complexity over time and the lack of efficient principal methods to extract them. Traditional parametric modeling approaches from machine learning find it difficult to discover new, unseen patterns and contexts arising from continuous growth of data streams due to its practice of training-then-prediction paradigm. In this work, we propose to apply Bayesian nonparametric models as a systematic and rigorous paradigm to continuously learn hidden patterns and contexts from raw social signals to provide basic building blocks for context-aware applications. Bayesian nonparametric models allow the model complexity to grow with data, fitting naturally to several problems encountered in pervasive computing. Under this framework, we use nonparametric prior distributions to model the data generative process, which helps towards learning the number of latent patterns automatically, adapting to changes in data and discovering never-seen-before patterns, contexts and activities. The proposed methods are agnostic to data types, however our work shall demonstrate to two types of signals: accelerometer activity data and Bluetooth proximal data. © 2014 IEEE.

Understanding response surface optimisation to the modeling of Astaxanthin extraction from a novel strain Thraustochytrium sp. S7

A fast growing, highly orange color pigmented strain of Thraustochytrids was isolated from New Zealand marine waters. This strain showed efficient utilization of glycerol as carbon source and produced significant amount of cell dry biomass (2.08gL-1), TFA (30.15% of dry cell weight), DHA (27.83% of TFA) and astaxanthin (131.56μgg-1). Astaxanthin is the dominant constituent in the carotenoid profile of Thraustochytrium sp. S7 and is an important antioxidant. Different cell disruption methods were applied for efficient astaxanthin extraction. Mechanical disruption of cells via ultrasonication resulted in the highest astaxanthin yield, from 26.78±1.25μgg-1 to 156.07±4.16μgg-1. Optimization of ultrasonication process using response surface methodology resulted into significant decrease in lysis time from 30min to 10min. This strain can be used for concurrent production of lipids and high value co-products such as DHA and astaxanthin.

Comparison of cell disruption methods for improving lipid extraction from thraustochytrid strains

Lipid extraction is an integral part of biodiesel production, as it facilitates the release of fatty acids from algal cells. To utilise thraustochytrids as a potential source for lipid production. We evaluated the extraction efficiency of various solvents and solvent combinations for lipid extraction from Schizochytrium sp. S31 and Thraustochytrium sp. AMCQS5-5. The maximum lipid extraction yield was 22% using a chloroform:methanol ratio of 2:1. We compared various cell disruption methods to improve lipid extraction yields, including grinding with liquid nitrogen, bead vortexing, osmotic shock, water bath, sonication and shake mill. The highest lipid extraction yields were obtained using osmotic shock and 48.7% from Schizochytrium sp. S31 and 29.1% from Thraustochytrium sp. AMCQS5-5. Saturated and monounsaturated fatty acid contents were more than 60% in Schizochytrium sp. S31 which suggests their suitability for biodiesel production.

Schizophrenia, psychotropic medication, and cataract

OBJECTIVE: To compare the distribution of cataract types between psychiatric patients diagnosed with schizophrenia and the general population not exposed to psychotropic medication, and to compare cataract prevalence between users and nonusers of various psychotropic medications in the general community. DESIGN: Case-control. PARTICIPANTS: A total of 151 (93%) eligible patients from a community mental health service and 3271 (83%) eligible residents from the Melbourne Visual Impairment Project (VIP) were examined. MAIN OUTCOME MEASURES: All patients 40 years of age and older from a community mental health service and residents of nine randomly selected areas of Melbourne were eligible. Best-corrected distance visual acuity was determined using a 4-m logarithm of the minimum angle of resolution (LogMAR) chart. The presence of cataract was determined by photographs or slit-lamp examination using direct and indirect retroillumination. Anterior, cortical, nuclear, and posterior subcapsular cataracts were measured. Participants from the Melbourne VIP were classified as to whether they had taken benzodiazepams, phenothiazines, thioxanthenes, butyrophenols, tricyclic antidepressants, or monoamine oxidase inhibitors for at least 12 months during their lifetime. RESULTS: The distribution of cataract type varied between persons with and without schizophrenia. Anterior subcapsular (ASC) cataract was significantly more prevalent (26%) in participants with schizophrenia from the community mental health service than Melbourne VIP participants (0.2%) not exposed to psychotropic medication (chi-square, 1 degree of freedom = 605.5, P = 0.001). This remained significant after controlling for age (odds ratios = 250, 95% confidence interval = 83.3, 1000). The distribution of the age-related cataract was similar across all groups of psychotropic medication users with the exception of the phenothiazine users. They had less of all types of the age-related cataracts, despite being slightly older than the control group (mean age, 60.0 vs. 58.4, t test = 0.85, P = 0.40). However, only cortical cataract in the phenothiazine group was statistically lower (chi-square, 1 degree of freedom = 3.96, P = 0.047). CONCLUSION: This study has identified the need to investigate whether other newer agents, especially high-potency medications, cause ASC opacities if a certain threshold of exposure to psychotropic medications must be attained to develop cataract, or if schizophrenia itself is associated with cataract formation.

The epidemiology of cataract: a review of the literature

Cataract is a major cause of blindness, accounting for nearly half of all blindness worldwide. Epidemiological research provides the principles and methods to assess the extent of cataract, and supplies the necessary information for policy planning. Obtaining accurate epidemiological data on cataract is essential to ascertain and estimate the cost of primary and secondary eye health care needs. Determining risk factors is also necessary to reduce the economic and social repercussions associated with the disease. The following paper presents a review of the epidemiology of cataract in the middle to elderly age group.

Quantitative secondary electron imaging for work function extraction at atomic level and layer identification of graphene

Two-dimensional (2D) materials usually have a layer-dependent work function, which require fast and accurate detection for the evaluation of their device performance. A detection technique with high throughput and high spatial resolution has not yet been explored. Using a scanning electron microscope, we have developed and implemented a quantitative analytical technique which allows effective extraction of the work function of graphene. This technique uses the secondary electron contrast and has nanometre-resolved layer information. The measurement of few-layer graphene flakes shows the variation of work function between graphene layers with a precision of less than 10 meV. It is expected that this technique will prove extremely useful for researchers in a broad range of fields due to its revolutionary throughput and accuracy.

SECC: simultaneous extraction of context and community from pervasive signals

Understanding user contexts and group structures plays a central role in pervasive computing. These contexts and community structures are complex to mine from data collected in the wild due to the unprecedented growth of data, noise, uncertainties and complexities. Typical existing approaches would first extract the latent patterns to explain the human dynamics or behaviors and then use them as the way to consistently formulate numerical representations for community detection, often via a clustering method. While being able to capture high-order and complex representations, these two steps are performed separately. More importantly, they face a fundamental difficulty in determining the correct number of latent patterns and communities. This paper presents an approach that seamlessly addresses these challenges to simultaneously discover latent patterns and communities in a unified Bayesian nonparametric framework. Our Simultaneous Extraction of Context and Community (SECC) model roots in the nested Dirichlet process theory which allows nested structure to be built to explain data at multiple levels. We demonstrate our framework on three public datasets where the advantages of the proposed approach are validated.

Full surplus extraction with dominant strategies

In this note I consider the fuI! surplus extraction in an auction with private but possibly correlated values. I show that fuI! extraction in the continuum of types case is not possible in general. Neither is approximate fuI! surplus extraction if the sel!er is budget constrained.

Comparison of two extraction methods for evaluation of volatile constituents patterns in commercial whiskeys: Elucidation of the main odour-active compounds

An analytical procedure based on manual dynamic headspace solid-phase microextraction (HS-SPME) method and the conventional extraction method by liquid–liquid extraction (LLE), were compared for their effectiveness in the extraction and quantification of volatile compounds from commercial whiskey samples. Seven extraction solvents covering a wide range of polarities and two SPME fibres coatings, has been evaluated. The highest amounts extracted, were achieved using dichloromethane (CH2Cl2) by LLE method (LLECH2Cl2)(LLECH2Cl2) and using a CAR/PDMS fibre (SPMECAR/PDMS) in HS-SPME. Each method was used to determine the responses of 25 analytes from whiskeys and calibration standards, in order to provide sensitivity comparisons between the two methods. Calibration curves were established in a synthetic whiskey and linear correlation coefficient (r ) were greater than 0.9929 for LLECH2Cl2LLECH2Cl2 and 0.9935 for SPMECAR/PDMS, for all target compounds. Recoveries greater than 80% were achieved. For most compounds, precision (expressed by relative standard deviation, R.S.D.) are very good, with R.S.D. values lower than 14.78% for HS-SPME method and than 19.42% for LLE method. The detection limits ranged from 0.13 to 19.03 μg L−1 for SPME procedure and from 0.50 to 12.48 μg L−1 for LLE. A tentative study to estimate the contribution of a specific compound to the aroma of a whiskey, on the basis of their odour activity values (OAV) was made. Ethyl octanoate followed by isoamyl acetate and isobutyl alcohol, were found the most potent odour-active compounds.