Iterative intersections

Iterative Intersectioning is a body of art works that comes out of the collaboration between author and electronic artist Jen Seevinck and a community of print artists, most particularly Elizabeth Saunders (EJ) and Robert Oakman. The work shown here is concerned with the creative process of collaboration, specifically as this informs visual forms. This is through our focus on process. This process has facilitated a 'conversational' exchange between all artists and a corresponding evolution in the artworks. In each case the dialogue is either between the author, Jen and EJ or between Jen and Robert. It consists of passing work between parties, interpreting it and working into it, before passing it back. The result is a series of art works including those shown here. The concept evolves in parallel to this. Importantly, at each of her iterations of creative work, the author Jen determines a similar 'treatment' or 'interpretation' across both print artists works at that time. A synthesis of EJ and Robert's creative interpretation -- at a high level -- occurs. In this sense the concept and works can be understood to intersect with one another.

Human CD141(+) (BDCA-3)(+) dendritic cells (DCs) represent a unique myeloid DC subset that cross-presents necrotic cell antigens

The characterization of human dendritic cell (DC) subsets is essential for the design of new vaccines. We report the first detailed functional analysis of the human CD141(+) DC subset. CD141(+) DCs are found in human lymph nodes, bone marrow, tonsil, and blood, and the latter proved to be the best source of highly purified cells for functional analysis. They are characterized by high expression of toll-like receptor 3, production of IL-12p70 and IFN-beta, and superior capacity to induce T helper 1 cell responses, when compared with the more commonly studied CD1c(+) DC subset. Polyinosine-polycytidylic acid (poly I:C)-activated CD141(+) DCs have a superior capacity to cross-present soluble protein antigen (Ag) to CD8(+) cytotoxic T lymphocytes than poly I:C-activated CD1c(+) DCs. Importantly, CD141(+) DCs, but not CD1c(+) DCs, were endowed with the capacity to cross-present viral Ag after their uptake of necrotic virus-infected cells. These findings establish the CD141(+) DC subset as an important functionally distinct human DC subtype with characteristics similar to those of the mouse CD8 alpha(+) DC subset. The data demonstrate a role for CD141(+) DCs in the induction of cytotoxic T lymphocyte responses and suggest that they may be the most relevant targets for vaccination against cancers, viruses, and other pathogens.

Automated diagnosis of Age-related Macular Degeneration using greyscale features from digital fundus images

Age-related Macular Degeneration (AMD) is one of the major causes of vision loss and blindness in ageing population. Currently, there is no cure for AMD, however early detection and subsequent treatment may prevent the severe vision loss or slow the progression of the disease. AMD can be classified into two types: dry and wet AMDs. The people with macular degeneration are mostly affected by dry AMD. Early symptoms of AMD are formation of drusen and yellow pigmentation. These lesions are identified by manual inspection of fundus images by the ophthalmologists. It is a time consuming, tiresome process, and hence an automated diagnosis of AMD screening tool can aid clinicians in their diagnosis significantly. This study proposes an automated dry AMD detection system using various entropies (Shannon, Kapur, Renyi and Yager), Higher Order Spectra (HOS) bispectra features, Fractional Dimension (FD), and Gabor wavelet features extracted from greyscale fundus images. The features are ranked using t-test, Kullback–Lieber Divergence (KLD), Chernoff Bound and Bhattacharyya Distance (CBBD), Receiver Operating Characteristics (ROC) curve-based and Wilcoxon ranking methods in order to select optimum features and classified into normal and AMD classes using Naive Bayes (NB), k-Nearest Neighbour (k-NN), Probabilistic Neural Network (PNN), Decision Tree (DT) and Support Vector Machine (SVM) classifiers. The performance of the proposed system is evaluated using private (Kasturba Medical Hospital, Manipal, India), Automated Retinal Image Analysis (ARIA) and STructured Analysis of the Retina (STARE) datasets. The proposed system yielded the highest average classification accuracies of 90.19%, 95.07% and 95% with 42, 54 and 38 optimal ranked features using SVM classifier for private, ARIA and STARE datasets respectively. This automated AMD detection system can be used for mass fundus image screening and aid clinicians by making better use of their expertise on selected images that require further examination.

Decision support system for age-related macular degeneration using discrete wavelet transform

Age-related macular degeneration (AMD) affects the central vision and subsequently may lead to visual loss in people over 60 years of age. There is no permanent cure for AMD, but early detection and successive treatment may improve the visual acuity. AMD is mainly classified into dry and wet type; however, dry AMD is more common in aging population. AMD is characterized by drusen, yellow pigmentation, and neovascularization. These lesions are examined through visual inspection of retinal fundus images by ophthalmologists. It is laborious, time-consuming, and resource-intensive. Hence, in this study, we have proposed an automated AMD detection system using discrete wavelet transform (DWT) and feature ranking strategies. The first four-order statistical moments (mean, variance, skewness, and kurtosis), energy, entropy, and Gini index-based features are extracted from DWT coefficients. We have used five (t test, Kullback–Lieber Divergence (KLD), Chernoff Bound and Bhattacharyya Distance, receiver operating characteristics curve-based, and Wilcoxon) feature ranking strategies to identify optimal feature set. A set of supervised classifiers namely support vector machine (SVM), decision tree, k -nearest neighbor ( k -NN), Naive Bayes, and probabilistic neural network were used to evaluate the highest performance measure using minimum number of features in classifying normal and dry AMD classes. The proposed framework obtained an average accuracy of 93.70 %, sensitivity of 91.11 %, and specificity of 96.30 % using KLD ranking and SVM classifier. We have also formulated an AMD Risk Index using selected features to classify the normal and dry AMD classes using one number. The proposed system can be used to assist the clinicians and also for mass AMD screening programs.

Synthesizing form and data : developing practices for student engagement and learning

We explore the relationship between form and data as a design agenda and learning strategy for novice visual information designers. Our students are university seniors in digital, visual design but novices to information design, manipulation and interpretation. We describe design strategies developed to scaffold sophisticated aesthetic and conceptual engagement despite limited understanding of the domain of designing with information. These revolve around an open-ended design project where students created a physical design from data of their choosing and research. The accompanying learning strategies concern this relationship between data and form to investigate it materially, formally and through ideation. Exemplifying student works that cross media and design domains are described.

Moderate physical activity level as a protective factor against metabolic syndrome in middle-aged and older women

Aims and objectives To investigate whether physical activity is a protective factor against metabolic syndrome in middle-aged and older women. Background Socio-demographic and lifestyle behaviour factors contribute to metabolic syndrome. To minimise the risk of metabolic syndrome, several global guidelines recommend increasing physical activity level. However, only limited research has investigated the relationship between physical activity levels and metabolic syndrome in middle-aged and older women after adjusting for socio-demographic and lifestyle behaviour factors. Design Cross-sectional design. Methods A convenience sample of 326 middle-aged and older women was recruited. Metabolic syndrome was confirmed according to the National Cholesterol Education Program, Adult Treatment Panel III guidelines, and physical activity levels were measured by the International Physical Activity Questionnaire. Results The sample had a mean age of 60•9 years, and the prevalence of metabolic syndrome was 43•3%. Postmenopausal women and women with low socioeconomic status (low-education background, without personal income and currently unemployed) had a significantly higher risk of developing metabolic syndrome. After adjusting for significant socio-demographic and lifestyle behaviour factors, the women with moderate or high physical activity levels had a significantly lower (OR = 0•10; OR = 0•11, p < 0•001) risk of metabolic syndrome and a lower risk for each specific component of metabolic syndrome, including elevated fasting plasma glucose (OR = 0•29; OR = 0•26, p = 0•009), elevated blood pressure (OR = 0•18; OR = 0•32, p = 0•029), elevated triglycerides (OR = 0•41; OR = 0•15, p = 0•001), reduced high-density lipoprotein (OR = 0•28; OR = 0•27, p = 0•004) and central obesity (OR = 0•31; OR = 0•22, p = 0•027). Conclusions After adjusting for socio-demographic and lifestyle behaviour factors, physical activity level was a significant protective factor against metabolic syndrome in middle-aged and older women. Higher physical activity levels (moderate or high physical activity level) reduced the risk of metabolic syndrome in middle-aged and older women. Relevance to clinical practice Appropriate strategies should be developed to encourage middle-aged and older women across different socio-demographic backgrounds to engage in moderate or high levels of physical activity to reduce the risk of metabolic syndrome.

Indirect effects of phytochemicals on offspring performance of Queensland fruit fly, Bactrocera tryoni (Diptera: Tephritidae)

Phytochemical lures such as methyl eugenol (ME) and cue-lure are used in the management of Bactrocera fruit flies for monitoring and control. These lures are not just attractants, but also trigger physiological changes in males that lead to enhanced mating success. Additionally, in the cue-lure-responsive Bactrocera tryoni, females mated with lure-fed males exhibit changes in fecundity, remating receptivity and longevity. While the lures show current generation effects, no research has been carried out on possible multigenerational effects, although such effects have been hypothesized within a ‘sexy-son’ sexual selection model. In this study, we test for indirect, cross-generational effects of lure exposure in F1offspring of B. tryoni females mated with cue-lure-fed, zingerone-fed and lure-unfed (=control) males. The F1 attributes we recorded were immature development time, immature survival, adult survival and adult male lure foraging. No significant differences were found between treatments for any of the three life-history measurements, except that the offspring sired by zingerone-fed males had a longer egg development time than cue-lure and control offspring. However, indirect exposure to lures significantly enhanced the lure-foraging ability of F1 adult males. More offspring of cue-lure-fed males arrived at a lure source in both large flight cages and small laboratory cages over a 2-h period than did control males. The offspring of zingerone-fed males were generally intermediate between cue-lure and control offspring. This study provides the first evidence of a next generation effect of fruit fly male lures. While the results of this study support a ‘sexy-son’ sexual selection mechanism for the evolution of lure response in Bactrocera fruit flies, our discussion urges caution in interpreting our results in this way.

Application of higher-order spectra for automated grading of diabetic maculopathy

Diabetic macular edema (DME) is one of the most common causes of visual loss among diabetes mellitus patients. Early detection and successive treatment may improve the visual acuity. DME is mainly graded into non-clinically significant macular edema (NCSME) and clinically significant macular edema according to the location of hard exudates in the macula region. DME can be identified by manual examination of fundus images. It is laborious and resource intensive. Hence, in this work, automated grading of DME is proposed using higher-order spectra (HOS) of Radon transform projections of the fundus images. We have used third-order cumulants and bispectrum magnitude, in this work, as features, and compared their performance. They can capture subtle changes in the fundus image. Spectral regression discriminant analysis (SRDA) reduces feature dimension, and minimum redundancy maximum relevance method is used to rank the significant SRDA components. Ranked features are fed to various supervised classifiers, viz. Naive Bayes, AdaBoost and support vector machine, to discriminate No DME, NCSME and clinically significant macular edema classes. The performance of our system is evaluated using the publicly available MESSIDOR dataset (300 images) and also verified with a local dataset (300 images). Our results show that HOS cumulants and bispectrum magnitude obtained an average accuracy of 95.56 and 94.39 % for MESSIDOR dataset and 95.93 and 93.33 % for local dataset, respectively.

Pre-lithiation of onion-like carbon/MoS2 nano-urchin anodes for high-performance rechargeable lithium ion batteries

Hybrid urchin-like nanostructures composed of a spherical onion-like carbon (OLC) core and MoS2 nanoleaves were synthesized by a simple solvothermal method followed by thermal annealing treatment. Compared to commercial MoS2 powder, MoS2/OLC nanocomposites exhibit enhanced electrochemical performance as anode materials of lithium-ion batteries (LIBs) with a specific capacity of 853 mA h g−1 at a current density of 50 mA g−1 after 60 cycles, and a moderate initial coulombic efficiency of 71.1%. Furthermore, a simple pre-lithiation method based on direct contact of lithium foil with MoS2/OLC nano-urchins was used to achieve a very high coulombic efficiency of 97.6% in the first discharge/charge cycle, which is at least 26% higher compared to that of pristine MoS2/OLC nano-urchins. This pre-lithiation method can be generalized to develop other carbon-metal sulfide nanohybrids for LIB anode materials. These results may open up a new avenue for the development of the next-generation high-performance LIBs.

Catalyst engineering for lithium ion batteries: The catalytic role of Ge in enhancing the electrochemical performance of SnO2(GeO2)0.13/G anodes

The catalytic role of germanium (Ge) was investigated to improve the electrochemical performance of tin dioxide grown on graphene (SnO(2)/G) nanocomposites as an anode material of lithium ion batteries (LIBs). Germanium dioxide (GeO(20) and SnO(2) nanoparticles (<10 nm) were uniformly anchored on the graphene sheets via a simple single-step hydrothermal method. The synthesized SnO(2)(GeO(2))0.13/G nanocomposites can deliver a capacity of 1200 mA h g(-1) at a current density of 100 mA g(-1), which is much higher than the traditional theoretical specific capacity of such nanocomposites (∼ 702 mA h g(-1)). More importantly, the SnO(2)(GeO(2))0.13/G nanocomposites exhibited an improved rate, large current capability (885 mA h g(-1) at a discharge current of 2000 mA g(-1)) and excellent long cycling stability (almost 100% retention after 600 cycles). The enhanced electrochemical performance was attributed to the catalytic effect of Ge, which enabled the reversible reaction of metals (Sn and Ge) to metals oxide (SnO(2) and GeO(2)) during the charge/discharge processes. Our demonstrated approach towards nanocomposite catalyst engineering opens new avenues for next-generation high-performance rechargeable Li-ion batteries anode materials.

Portrait of Ralph and Joan Grahme with Ralph's sister Ilse Schuster nee Gottschalk and her husband James at restaurant "Old Vienna"; London, England.

Left to right: Ralph Grahme, Joan Grahme, Ilse Schuster nee Gottschalk, and James Schuster;

Portrait of Ralph and Joan Grahme with Ralph's sister Ilse Schuster nee Gottschalk and her husband James at restaurant "Old Vienna"; London, England.

Left to right: Ralph Grahme, Joan Grahme, Ilse Schuster nee Gottschalk, and James Schuster;

Response of Tribolium castaneum and Rhyzopertha dominica to various resources, near and far from grain storage

Tribolium castaneum (Herbst) and Rhyzopertha dominica (F.) are common cosmopolitan pests of stored grain and grain products. We evaluated the relative attraction of T.castaneum and R.dominica to wheat, sorghum and cotton seeds in the field, near grain storage facilities and well away from storages in southern and central Queensland using multiple trapping techniques. The results show that T.castaneum is more strongly attracted to linted cotton seed relative to wheat, whereas R.dominica did not respond to cotton seed at all and was attracted only to wheat. Significantly more adults of T.castaneum (10-15 times) were attracted to traps placed on the ground, near grain storage, than to equivalent traps that were suspended (1.5m above the ground) nearby. These results suggest that Tribolium beetles detect and respond to resources towards the end of their dispersal flight, after which they localize resources while walking. By contrast R.dominica was captured only in suspended traps, which suggests they fly directly onto resources as they localize them. The ability of both species to colonize and reproduce in isolated resource patches within the relatively short time of 1month is illustrated by the returns from the traps deployed in the field (at least 1km from the nearest stored grain) even though they caught only a few beetles. The results presented here provide novel insights about the resource location behaviours of both T.castaneum and R.dominica. In particular, the relationship of T.castaneum with non-cereal resources that are not conventionally associated with this species suggests an emphasis on these other resources in investigating the resource location behaviour of these beetles. This new perspective on the ecology of T. castaneum highlights the potential role of non-cereal resources (such as the lint on cotton seed) in the spread of grain pest infestations.