Spectral analysis of pair-correlation bandwidth: Application to cell biology images

Images from cell biology experiments often indicate the presence of cell clustering, which can provide insight into the mechanisms driving the collective cell behaviour. Pair-correlation functions provide quantitative information about the presence, or absence, of clustering in a spatial distribution of cells. This is because the pair-correlation function describes the ratio of the abundance of pairs of cells, separated by a particular distance, relative to a randomly distributed reference population. Pair-correlation functions are often presented as a kernel density estimate where the frequency of pairs of objects are grouped using a particular bandwidth (or bin width), Δ>0. The choice of bandwidth has a dramatic impact: choosing Δ too large produces a pair-correlation function that contains insufficient information, whereas choosing Δ too small produces a pair-correlation signal dominated by fluctuations. Presently, there is little guidance available regarding how to make an objective choice of Δ. We present a new technique to choose Δ by analysing the power spectrum of the discrete Fourier transform of the pair-correlation function. Using synthetic simulation data, we confirm that our approach allows us to objectively choose Δ such that the appropriately binned pair-correlation function captures known features in uniform and clustered synthetic images. We also apply our technique to images from two different cell biology assays. The first assay corresponds to an approximately uniform distribution of cells, while the second assay involves a time series of images of a cell population which forms aggregates over time. The appropriately binned pair-correlation function allows us to make quantitative inferences about the average aggregate size, as well as quantifying how the average aggregate size changes with time.

Undead yakuza: The Japanese zombie movie, cultural resonance and generic conventions

The zombie has long been regarded as a “fundamentally American creation” (Bishop 2010) and a western monster representing the fears and anxieties of Western society. Since the renaissance of the zombie movie in the early 2000s, a subsequent surge in international production has seen the release of movies from Norway, Cuba, Pakistan and Thailand to name a few. Although Japanese zombie movies have been far more visible for Western cult audiences than in mainstream markets, Japanese cinema has emerged as one of the more prolific producers of zombie films outside of Anglophone or Western European countries in recent years. Films such as Helldriver (2010), Zombie TV (2013), Versus (2000), Tokyo Zombie (2005), Happiness of the Katakuris (2001) and anime television series High School of the Dead (2010) have generated varying degrees of popularity and critical attention internationally. At first glance Japanese zombie films, with musical zombie interludes, undead yakuza henchmen and revenge-seeking yūrei zombies, appear fundamentally different to their Western counterparts. Yet, on closer examination, the Japanese zombie movie could be regarded as a hybrid and intertextual generic form drawing on syntactic conventions at the core of a universal zombie sub-genre established by Western filmmaking traditions, while also distilling culturally specific tropes unique to various Japanese horror cinema sub-genres. Most importantly, the Japanese zombie film extracts, emphasises and revises particular conventions and motifs common within Western zombie films that are particularly relevant to Japanese audiences. This chapter investigates the cultural resonance of key generic motifs identifiable in the Japanese zombie film. It establishes a production context and the influence of Japanese horror cinema on style and thematic concerns. It then examines the function of prominent narrative conventions, namely: the source, outbreak and spread of infection; mutation and the representation of the monster; and the inclusion of supernatural and religious motifs.

Magnetic resonance microimaging of cancer cell spheroid constructs

BACKGROUND Hydrogel-based cell cultures are excellent tools for studying physiological events occurring in the growth and proliferation of cells, including cancer cells. Diffusion magnetic resonance is a physical technique that has been widely used for the characterisation of biological systems as well as hydrogels. In this work, we applied diffusion magnetic resonance imaging (MRI) to hydrogel-based cultures of human ovarian cancer cells. METHODS Diffusion-weighted spin-echo MRI measurements were used to obtain spatially-resolved maps of apparent diffusivities for hydrogel samples with different compositions, cell loads and drug (Taxol) treatment regimes. The samples were then characterised using their diffusivity histograms, mean diffusivities and the respective standard deviations, and pairwise Mann-Whitney tests. The elastic moduli of the samples were determined using mechanical compression testing. RESULTS The mean apparent diffusivity of the hydrogels was sensitive to the polymer content, cell load and Taxol treatment. For a given sample composition, the mean apparent diffusivity and the elastic modulus of the hydrogels exhibited a negative correlation. CONCLUSIONS Diffusivity of hydrogel-based cancer cell culture constructs is sensitive to both cell proliferation and Taxol treatment. This suggests that diffusion-weighted imaging is a promising technique for non-invasive monitoring of cancer cell proliferation in hydrogel-based, cellularly-sparse 3D cell cultures. The negative correlation between mean apparent diffusivity and elastic modulus suggests that the diffusion coefficient is indicative of the average density of the physical microenvironment within the hydrogel construct.

Robust nanostructured silver and copper fabrics with localized surface plasmon resonance property for effective visible light induced reductive catalysis

Inspired by high porosity, absorbency, wettability and hierarchical ordering on the micrometer and nanometer scale of cotton fabrics, a facile strategy is developed to coat visible light active metal nanostructures of copper and silver on cotton fabric substrates. The fabrication of nanostructured Ag and Cu onto interwoven threads of a cotton fabric by electroless deposition creates metal nanostructures that show a localized surface plasmon resonance (LSPR) effect. The micro/nanoscale hierarchical ordering of the cotton fabrics allows access to catalytically active sites to participate in heterogeneous catalysis with high efficiency. The ability of metals to absorb visible light through LSPR further enhances the catalytic reaction rates under photoexcitation conditions. Understanding the mode of electron transfer during visible light illumination in Ag@Cotton and Cu@Cotton through electrochemical measurements provides mechanistic evidence on the influence of light in promoting electron transfer during heterogeneous catalysis for the first time. The outcomes presented in this work will be helpful in designing new multifunctional fabrics with the ability to absorb visible light and thereby enhance light-activated catalytic processes.

Statistical analysis of spectral data: A methodology for designing an intelligent monitoring system for the diabetic foot

Early detection of (pre-)signs of ulceration on a diabetic foot is valuable for clinical practice. Hyperspectral imaging is a promising technique for detection and classification of such (pre-)signs. However, the number of the spectral bands should be limited to avoid overfitting, which is critical for pixel classification with hyperspectral image data. The goal was to design a detector/classifier based on spectral imaging (SI) with a small number of optical bandpass filters. The performance and stability of the design were also investigated. The selection of the bandpass filters boils down to a feature selection problem. A dataset was built, containing reflectance spectra of 227 skin spots from 64 patients, measured with a spectrometer. Each skin spot was annotated manually by clinicians as "healthy" or a specific (pre-)sign of ulceration. Statistical analysis on the data set showed the number of required filters is between 3 and 7, depending on additional constraints on the filter set. The stability analysis revealed that shot noise was the most critical factor affecting the classification performance. It indicated that this impact could be avoided in future SI systems with a camera sensor whose saturation level is higher than 106, or by postimage processing.

Preventing infections through cleaner hospitals (PITCH): An environmental cleaning bundle

Translating the numerous lengthy cleaning standards and guidelines into meaningful and sustained improvements in cleaning practice is challenging. This research hypothesized that an evidence based cleaning bundle would improve cleaning performance, knowledge and attitudes, and ultimately reduces healthcare associated infections (HAI) in a way that is value for money. A bundle is a small, straightforward set of evidence based practices, that when performed collectively and reliably, improves patient outcomes.

Spectral Values

This series of drawings takes a diagrammatically creative approach to understanding the economic theories and personalities at the centre of the Global Financial Crisis. Mimicking the form of US currency, the work removes labels from common economic diagrams and portrays financial titans in repose as a way to express a personal and ambivalent experience of contemporary capitalism.

Characterization of anomalous relaxation using the time-fractional Bloch equation and multiple echo T2 *-weighted magnetic resonance imaging at 7T

PURPOSE To study the utility of fractional calculus in modeling gradient-recalled echo MRI signal decay in the normal human brain. METHODS We solved analytically the extended time-fractional Bloch equations resulting in five model parameters, namely, the amplitude, relaxation rate, order of the time-fractional derivative, frequency shift, and constant offset. Voxel-level temporal fitting of the MRI signal was performed using the classical monoexponential model, a previously developed anomalous relaxation model, and using our extended time-fractional relaxation model. Nine brain regions segmented from multiple echo gradient-recalled echo 7 Tesla MRI data acquired from five participants were then used to investigate the characteristics of the extended time-fractional model parameters. RESULTS We found that the extended time-fractional model is able to fit the experimental data with smaller mean squared error than the classical monoexponential relaxation model and the anomalous relaxation model, which do not account for frequency shift. CONCLUSIONS We were able to fit multiple echo time MRI data with high accuracy using the developed model. Parameters of the model likely capture information on microstructural and susceptibility-induced changes in the human brain.

Spectral unmixing with estimated adaptive endmember index using Extended Support Vector Machine

The most difficult operation in the flood inundation mapping using optical flood images is to separate fully inundated areas from the ‘wet’ areas where trees and houses are partly covered by water. This can be referred as a typical problem the presence of mixed pixels in the images. A number of automatic information extraction image classification algorithms have been developed over the years for flood mapping using optical remote sensing images. Most classification algorithms generally, help in selecting a pixel in a particular class label with the greatest likelihood. However, these hard classification methods often fail to generate a reliable flood inundation mapping because the presence of mixed pixels in the images. To solve the mixed pixel problem advanced image processing techniques are adopted and Linear Spectral unmixing method is one of the most popular soft classification technique used for mixed pixel analysis. The good performance of linear spectral unmixing depends on two important issues, those are, the method of selecting endmembers and the method to model the endmembers for unmixing. This paper presents an improvement in the adaptive selection of endmember subset for each pixel in spectral unmixing method for reliable flood mapping. Using a fixed set of endmembers for spectral unmixing all pixels in an entire image might cause over estimation of the endmember spectra residing in a mixed pixel and hence cause reducing the performance level of spectral unmixing. Compared to this, application of estimated adaptive subset of endmembers for each pixel can decrease the residual error in unmixing results and provide a reliable output. In this current paper, it has also been proved that this proposed method can improve the accuracy of conventional linear unmixing methods and also easy to apply. Three different linear spectral unmixing methods were applied to test the improvement in unmixing results. Experiments were conducted in three different sets of Landsat-5 TM images of three different flood events in Australia to examine the method on different flooding conditions and achieved satisfactory outcomes in flood mapping.

Context-based assessment: Creating opportunities for resonance between classroom fields and societal fields

There is on-going international interest in the relationships between assessment instruments, students’ understanding of science concepts and context-based curriculum approaches. This study extends earlier research showing that students can develop connections between contexts and concepts – called fluid transitions – when studying context-based courses. We provide an in-depth investigation of one student’s experiences with multiple contextual assessment instruments that were associated with a context-based course. We analyzed the student’s responses to context-based assessment instruments to determine the extent to which contextual tests, reports of field investigations, and extended experimental investigations afforded her opportunities to make connections between contexts and concepts. A system of categorizing student responses was developed that can inform other educators when analyzing student responses to contextual assessment. We also refine the theoretical construct of fluid transitions that informed the study initially. Implications for curriculum and assessment design are provided in light of the findings.