Evaluation of a skin self examination attitude scale using an item response theory model approach

Introduction The Skin Self-Examination Attitude Scale (SSEAS) is a brief measure that allows for the assessment of attitudes in relation to skin self-examination. This study evaluated the psychometric properties of the SSEAS using Item Response Theory (IRT) methods in a large sample of men ≥ 50 years in Queensland, Australia. Methods A sample of 831 men (420 intervention and 411 control) completed a telephone assessment at the 13-month follow-up of a randomized-controlled trial of a video-based intervention to improve skin self-examination (SSE) behaviour. Descriptive statistics (mean, standard deviation, item–total correlations, and Cronbach’s alpha) were compiled and difficulty parameters were computed with Winsteps using the polytomous Rasch Rating Scale Model (RRSM). An item person (Wright) map of the SSEAS was examined for content coverage and item targeting. Results The SSEAS have good psychometric properties including good internal consistency (Cronbach’s alpha = 0.80), fit with the model and no evidence for differential item functioning (DIF) due to experimental trial grouping was detected. Conclusions The present study confirms the SSEA scale as a brief, useful and reliable tool for assessing attitudes towards skin self-examination in a population of men 50 years or older in Queensland, Australia. The 8-item scale shows unidimensionality, allowing levels of SSE attitude, and the item difficulties, to be ranked on a single continuous scale. In terms of clinical practice, it is very important to assess skin cancer self-examination attitude to identify people who may need a more extensive intervention to allow early detection of skin cancer.

Linear programming for large-scale Markov decision problems

We consider the problem of controlling a Markov decision process (MDP) with a large state space, so as to minimize average cost. Since it is intractable to compete with the optimal policy for large scale problems, we pursue the more modest goal of competing with a low-dimensional family of policies. We use the dual linear programming formulation of the MDP average cost problem, in which the variable is a stationary distribution over state-action pairs, and we consider a neighborhood of a low-dimensional subset of the set of stationary distributions (defined in terms of state-action features) as the comparison class. We propose a technique based on stochastic convex optimization and give bounds that show that the performance of our algorithm approaches the best achievable by any policy in the comparison class. Most importantly, this result depends on the size of the comparison class, but not on the size of the state space. Preliminary experiments show the effectiveness of the proposed algorithm in a queuing application.

Visual analytics for large-scale bioinformatic data sets

Rapid advances in sequencing technologies (Next Generation Sequencing or NGS) have led to a vast increase in the quantity of bioinformatics data available, with this increasing scale presenting enormous challenges to researchers seeking to identify complex interactions. This paper is concerned with the domain of transcriptional regulation, and the use of visualisation to identify relationships between specific regulatory proteins (the transcription factors or TFs) and their associated target genes (TGs). We present preliminary work from an ongoing study which aims to determine the effectiveness of different visual representations and large scale displays in supporting discovery. Following an iterative process of implementation and evaluation, representations were tested by potential users in the bioinformatics domain to determine their efficacy, and to understand better the range of ad hoc practices among bioinformatics literate users. Results from two rounds of small scale user studies are considered with initial findings suggesting that bioinformaticians require richly detailed views of TF data, features to compare TF layouts between organisms quickly, and ways to keep track of interesting data points.

Hydroclimatic influence of large-scale circulation on the variability of reservoir inflow

In this study, the nature of basin-scale hydroclimatic association for Indian subcontinent is investigated. It is found that, the large-scale circulation information from Indian Ocean is also equally important in addition to the El Nino-Southern Oscillation (ENSO), owing to the geographical location of Indian subcontinent. The hydroclimatic association of the variation of monsoon inflow into the Hirakud reservoir in India is investigated using ENSO and EQUatorial INdian Ocean Oscillation (EQUINOO, the atmospheric part of Indian Ocean Dipole mode) as the large-scale circulation information from tropical Pacific Ocean and Indian Ocean regions respectively. Individual associations of ENSO & EQUINOO indices with inflow into Hirakud reservoir are also assessed and found to be weak. However, the association of inflows into Hirakud reservoir with the composite index (CI) of ENSO and EQUINOO is quite strong. Thus, the large-scale circulation information from Indian Ocean is also important apart form the ENSO. The potential of the combined information of ENSO and EQUINOO for predicting the inflows during monsoon is also investigated with promising results. The results of this study will be helpful to water resources managers due to fact that the nature of monsoon inflow is becoming available as an early prediction.

Micro-scale anaerobic digestion of point source components of organic fraction of municipal solid waste

The fermentation characteristics of six specific types of the organic fraction of municipal solid waste (OFMSW) were examined, with an emphasis on properties that are needed when designing plug-flow type anaerobic bioreactors. More specifically, the decomposition patterns of a vegetable (cabbage), fruits (banana and citrus peels), fresh leaf litter of bamboo and teak leaves, and paper (newsprint) waste streams as feedstocks were studied. Individual OFMSW components were placed into nylon mesh bags and subjected to various fermentation periods (solids retention time, SRT) within the inlet of a functioning plug-flow biogas fermentor. These were removed at periodic intervals, and their composition was analyzed to monitor decomposition rates and changes in chemical composition. Components like cabbage waste, banana peels, and orange peels fermented rapidly both in a plug-flow biogas reactor (PFBR) as well as under a biological methane potential (BMP) assay, while other OFMSW components (leaf litter from bamboo and teak leaves and newsprint) fermented slowly with poor process stability and moderate biodegradation. For fruit and vegetable wastes (FVW), a rapid and efficient removal of pectins is the main cause of rapid disintegration of these feedstocks, which left behind very little compost forming residues (2–5%). Teak and bamboo leaves and newsprint decomposed only to 25–50% in 30 d. These results confirm the potential for volatile fatty acids accumulation in a PFBR’s inlet and suggest a modification of the inlet zone or operation of a PFBR with the above feedstocks.

targetTB: A target identification pipeline for Mycobacterium tuberculosis through an interactome, reactome and genome-scale structural analysis

Background: Tuberculosis still remains one of the largest killer infectious diseases, warranting the identification of newer targets and drugs. Identification and validation of appropriate targets for designing drugs are critical steps in drug discovery, which are at present major bottle-necks. A majority of drugs in current clinical use for many diseases have been designed without the knowledge of the targets, perhaps because standard methodologies to identify such targets in a high-throughput fashion do not really exist. With different kinds of 'omics' data that are now available, computational approaches can be powerful means of obtaining short-lists of possible targets for further experimental validation. Results: We report a comprehensive in silico target identification pipeline, targetTB, for Mycobacterium tuberculosis. The pipeline incorporates a network analysis of the protein-protein interactome, a flux balance analysis of the reactome, experimentally derived phenotype essentiality data, sequence analyses and a structural assessment of targetability, using novel algorithms recently developed by us. Using flux balance analysis and network analysis, proteins critical for survival of M. tuberculosis are first identified, followed by comparative genomics with the host, finally incorporating a novel structural analysis of the binding sites to assess the feasibility of a protein as a target. Further analyses include correlation with expression data and non-similarity to gut flora proteins as well as 'anti-targets' in the host, leading to the identification of 451 high-confidence targets. Through phylogenetic profiling against 228 pathogen genomes, shortlisted targets have been further explored to identify broad-spectrum antibiotic targets, while also identifying those specific to tuberculosis. Targets that address mycobacterial persistence and drug resistance mechanisms are also analysed. Conclusion: The pipeline developed provides rational schema for drug target identification that are likely to have high rates of success, which is expected to save enormous amounts of money, resources and time in the drug discovery process. A thorough comparison with previously suggested targets in the literature demonstrates the usefulness of the integrated approach used in our study, highlighting the importance of systems-level analyses in particular. The method has the potential to be used as a general strategy for target identification and validation and hence significantly impact most drug discovery programmes.

Conductivity Scale In Disordered-Systems

A reanalysis of the correction to the Boltzmann conductivity due to maximally crossed graphs for degenerate bands explains why the conductivity scale in many-valley semiconductors is an order of magnitude higher than Mott's "minimum metallic conductivity." With the use of a reasonable assumption for the Boltzmann mean free path, the lowest-order perturbation theory is seen to give a remarkably good, semiquantitative, description of the conductivity variation in both uncompensated doped semiconductors and amorphous alloys.

A large-scale analysis of genetic variants within putative miRNA binding sites in prostate cancer

Prostate cancer is the second most common malignancy among men worldwide. Genome-wide association studies have identified 100 risk variants for prostate cancer, which can explain approximately 33% of the familial risk of the disease. We hypothesized that a comprehensive analysis of genetic variations found within the 3' untranslated region of genes predicted to affect miRNA binding (miRSNP) can identify additional prostate cancer risk variants. We investigated the association between 2,169 miRSNPs and prostate cancer risk in a large-scale analysis of 22,301 cases and 22,320 controls of European ancestry from 23 participating studies. Twenty-two miRSNPs were associated (P<2.3×10(-5)) with risk of prostate cancer, 10 of which were within 7 genes previously not mapped by GWAS studies. Further, using miRNA mimics and reporter gene assays, we showed that miR-3162-5p has specific affinity for the KLK3 rs1058205 miRSNP T-allele, whereas miR-370 has greater affinity for the VAMP8 rs1010 miRSNP A-allele, validating their functional role. SIGNIFICANCE Findings from this large association study suggest that a focus on miRSNPs, including functional evaluation, can identify candidate risk loci below currently accepted statistical levels of genome-wide significance. Studies of miRNAs and their interactions with SNPs could provide further insights into the mechanisms of prostate cancer risk.

Simulating Surface Aeration Systems at Different Scale of Mixing Time

Macro and micromixing time represent two extreme mixing time scales,which governs the whole hydrodynamics characteristics of the surface aeration systems. With the help of experimental and numerical analysis, simulation equation governing those times scale has been presented in the present work.

Development of a stable isotope index to assess decadal-scale vegetation change and application to woodlands of the Burdekin catchment, Australia

Forty-four study sites were established in remnant woodland in the Burdekin River catchment in tropical north-east Queensland, Australia, to assess recent (decadal) vegetation change. The aim of this study was further to evaluate whether wide-scale vegetation 'thickening' (proliferation of woody plants in formerly more open woodlands) had occurred during the last century, coinciding with significant changes in land management. Soil samples from several depth intervals were size separated into different soil organic carbon (SOC) fractions, which differed from one another by chemical composition and turnover times. Tropical (C4) grasses dominate in the Burdekin catchment, and thus δ13C analyses of SOC fractions with different turnover times can be used to assess whether the relative proportion of trees (C3) and grasses (C4) had changed over time. However, a method was required to permit standardized assessment of the δ13C data for the individual sites within the 13 Mha catchment, which varied in soil and vegetation characteristics. Thus, an index was developed using data from three detailed study sites and global literature to standardize individual isotopic data from different soil depths and SOC fractions to reflect only the changed proportion of trees (C3) to grasses (C3) over decadal timescales. When applied to the 44 individual sites distributed throughout the Burdekin catchment, 64% of the sites were shown to have experienced decadal vegetation thickening, while 29% had remained stable and the remaining 7% had thinned. Thus, the development of this index enabled regional scale assessment and comparison of decadal vegetation patterns without having to rely on prior knowledge of vegetation changes or aerial photography.

Short-term responses of leaf growth rate to water deficit scale up to whole-plant and crop levels: An integrated modelling approach in maize.

Physiological and genetic studies of leaf growth often focus on short-term responses, leaving a gap to whole-plant models that predict biomass accumulation, transpiration and yield at crop scale. To bridge this gap, we developed a model that combines an existing model of leaf 6 expansion in response to short-term environmental variations with a model coordinating the development of all leaves of a plant. The latter was based on: (1) rates of leaf initiation, appearance and end of elongation measured in field experiments; and (2) the hypothesis of an independence of the growth between leaves. The resulting whole-plant leaf model was integrated into the generic crop model APSIM which provided dynamic feedback of environmental conditions to the leaf model and allowed simulation of crop growth at canopy level. The model was tested in 12 field situations with contrasting temperature, evaporative demand and soil water status. In observed and simulated data, high evaporative demand reduced leaf area at the whole-plant level, and short water deficits affected only leaves developing during the stress, either visible or still hidden in the whorl. The model adequately simulated whole-plant profiles of leaf area with a single set of parameters that applied to the same hybrid in all experiments. It was also suitable to predict biomass accumulation and yield of a similar hybrid grown in different conditions. This model extends to field conditions existing knowledge of the environmental controls of leaf elongation, and can be used to simulate how their genetic controls flow through to yield.

A study of the use of the Edinburgh postnatal depression scale with parent groups outside the postpartum period

The Edinburgh Postnatal Depression Scale (EPDS) was sent by post to 206 mothers and 201 fathers of toddlers (aged between 19 and 22 months). At the same time these parents also completed subscales of the Crown—Crisp Experiential Index (CCEI). The responses were used to assess the feasibility of postal completion of the EPDS and its acceptability to parents outside the postpartum year, particularly fathers for whom there have been no previous reports of its use. On a small sub-group, the sensitivity, specificity and predictive values of the measures were assessed using the Present. State Examination. Answers to the depression subscale of the CCEI to the EPDS and to the Present State Examination were compared to assess validity. Completion of the postally-administered EPDS was satisfactory, though some difficulties were experienced in a second postal administration to a subsample. The scale was completed without obvious error or omission and this, combined with positive comments from parents, suggests the acceptability of the scale to both mothers and fathers. The mean scores were higher for mothers than for fathers, but the pattern of distribution was similar with a marked positive skew and a distinct decline in scores above 10. Because the subsample of parents interviewed was small the calculation of sensitivity and specificity has to be treated with caution. However, the results for mothers suggest that the EPDS has satisfactory validity for this group and one superior to the depression subscale of the CCEI. Among the fathers interviewed there were insufficient cases to enable calculation of sensitivity and specificity. Other results were encouraging, however, and suggest the merit of further studies of the application and validity of the EPDS with fathers.

The genetic structure of Australasian green turtles (Chelonia mydas): Exploring the geographical scale of genetic exchange

Ecological and genetic studies of marine turtles generally support the hypothesis of natal homing, but leave open the question of the geographical scale of genetic exchange and the capacity of turtles to shift breeding sites. Here we combine analyses of mitochondrial DNA (mtDNA) variation and recapture data to assess the geographical scale of individual breeding populations and the distribution of such populations through Australasia. We conducted multiscale assessments of mtDNA variation among 714 samples from 27 green turtle rookeries and of adult female dispersal among nesting sites in eastern Australia. Many of these rookeries are on shelves that were flooded by rising sea levels less than 10 000 years (c. 450 generations) ago. Analyses of sequence variation among the mtDNA control region revealed 25 haplotypes, and their frequency distributions indicated 17 genetically distinct breeding stocks (Management Units) consisting either of individual rookeries or groups of rookeries in general that are separated by more than 500 km. The population structure inferred from mtDNA was consistent with the scale of movements observed in long-term mark-recapture studies of east Australian rookeries. Phylogenetic analysis of the haplotypes revealed five clades with significant partitioning of sequence diversity (Φ = 68.4) between Pacific Ocean and Southeast Asian/Indian Ocean rookeries. Isolation by distance was indicated for rookeries separated by up to 2000 km but explained only 12% of the genetic structure. The emerging general picture is one of dynamic population structure influenced by the capacity of females to relocate among proximal breeding sites, although this may be conditional on large population sizes as existed historically across this region.

How effective are broad-scale nutrient mass balances for determining the sustainability of lot-feed manure application?

Nutrient mass balances have been used to assess a variety of land resource scenarios, at various scales. They are widely used as a simple basis for policy, planning, and regulatory decisions but it is not clear how accurately they reflect reality. This study provides a critique of broad-scale nutrient mass balances, with particular application to the fertiliser use of beef lot-feeding manure in Queensland. Mass balances completed at the district and farm scale were found to misrepresent actual manure management behaviour and potentially the risk of nutrient contamination of water resources. The difficulties of handling stockpile manure and concerns about soil compaction mean that manure is spread thickly over a few paddocks at a time and not evenly across a whole farm. Consequently, higher nutrient loads were applied to a single paddock less frequently than annually. This resulted in years with excess nitrogen, phosphorus, and potassium remaining in the soil profile. This conclusion was supported by evidence of significant nutrient movement in several of the soil profiles studied. Spreading manure is profitable, but maximum returns can be associated with increased risk of nutrient leaching relative to conventional inorganic fertiliser practices. Bio-economic simulations found this increased risk where manure was applied to supply crop nitrogen requirements (the practice of the case study farms, 200-5000 head lot-feeders). Thus, the use of broad-scale mass balances can be misleading because paddock management is spatially heterogeneous and this leads to increased local potential for nutrient loss. In response to the effect of spatial heterogeneity policy makers who intend to use mass balance techniques to estimate potential for nutrient contamination should apply these techniques conservatively.

Rationale of Length Scale-Down Model Span Testing of Transmission Lines

Length scale-down (LS) model tests have been traditionally employed for laboratory studies on aeolian vibration of transmission line conductors. The span adopted is normally 30 m and is recommended by the relevant Indian, as well as other, standards. The traditionally adopted length of the LS model is reexamined herein to establish the rationale behind the choice. Based on the theoretical studies discussed, certain guidelines for the choice of model span of conductor are emphasized. In addition, the adequacy of the LS span as a tool for predicting the performance of the full span is reestablished.