Multiple liquid-crystals and NMR

The use of more than one liquid crystal solvents to determine molecular structure and conformation is discussed. Liquid crystals of similar and opposite signs of diamagnetic anisotropies are considered separately since they lead to different novel applications. Advantages of such experiments over those employing single solvents are pointed out with illustrative examples.

Porphyrins with multiple crown ether voids: novel systems for cation complexation studies

Porphyrins appended with crown ether, benzo-15-crown-5, at the methine positions have been synthesized and characterized. The fully and partially substituted porphyrins and their metallo (Co, Cu, and Zn) derivatives describe one or more ether cavities in the periphery that are capable of recognizing spherical cations. The ability of these macrocycles to complex cations (Na+, K+, Mg2+, Ca2+, Ba2', and NH4+) is investigated by use of visible, 'H NMR, ESR, and emission spectral studies. The tetrasubstituted crown porphyrin (TCP) exhibits very high selectivity for K+. The cations (K', Ba2+, and NH4+) that require two crown ether cavities for complexation promote dimerization of the porphyrins. The ESR study of the cation-induced porphyrin dimers reveals axial symmetry with the porphyrin planes separated by -4.2 A. This distance increases from the fully substituted to partially substituted porphyrins. The cations (K', Ba2+, and NH4') quench efficiently the fluorescence of the free base porphyrins and their metallo derivatives. The quenching process is attributed to the steric geometry of the dimers.

Levels and predictors of exercise referral scheme uptake and adherence: A systematic review

Background The effectiveness of exercise referral schemes (ERS) is influenced by uptake and adherence to the scheme. The identification of factors influencing low uptake and adherence could lead to the refinement of schemes to optimise investment. Objectives To quantify the levels of ERS uptake and adherence and to identify factors predictive of uptake and adherence. Methods A systematic review and meta-analysis was undertaken. MEDLINE, EMBASE, PsycINFO, Cochrane Library, ISI WOS, SPORTDiscus and ongoing trial registries were searched (to October 2009) and included study references were checked. Included studies were required to report at least one of the following: (1) a numerical measure of ERS uptake or adherence and (2) an estimate of the statistical association between participant demographic or psychosocial factors (eg, level of motivation, self-efficacy) or programme factors and uptake or adherence to ERS. Results Twenty studies met the inclusion criteria, six randomised controlled trials (RCTs) and 14 observational studies. The pooled level of uptake in ERS was 66% (95% CI 57% to 75%) across the observational studies and 81% (95% CI 68% to 94%) across the RCTs. The pooled level of ERS adherence was 49% (95% CI 40% to 59%) across the observational studies and 43% (95% CI 32% to 54%) across the RCTs. Few studies considered anything other than gender and age. Women were more likely to begin an ERS but were less likely to adhere to it than men. Older people were more likely to begin and adhere to an ERS. Limitations Substantial heterogeneity was evident across the ERS studies. Without standardised definitions, the heterogeneity may have been reflective of differences in methods of defining uptake and adherence across studies. Conclusions To enhance our understanding of the variation in uptake and adherence across ERS and how these variations might affect physical activity outcomes, future trials need to use quantitative and qualitative methods.

A systematic review of studies identifying predictors of poor return to work outcomes following workplace injury

BACKGROUND: Injuries occurring in the workplace can have serious implications for the health of the individual, the productivity of the employer and the overall economic community. OBJECTIVE: The objective of this paper is to increase the current state of understanding of individual demographic and psychosocial characteristics associated with extended absenteeism from the workforce due to a workplace injury. METHODS: Studies included in this systematic literature review tracked participants' return to work status over a minimum of three months, identified either demographic, psychosocial or general injury predictors of poor return to work outcomes and included a heterogeneous sample of workplace injuries. RESULTS: Identified predictors of poor return to work outcomes included older age, female gender, divorced marital status, two or more dependent family members, lower education levels, employment variables associated with reduced labour market desirability, severity or sensitive injury locations, negative attitudes and outcome perceptions of the participant. CONCLUSIONS: There is a need for clear and consistent definition and measurement of return to work outcomes and a holistic theoretical model integrating injury, psychosocial and demographic predictors of return to work. Through greater understanding of the nature of factors affecting return to work, improved outcomes could be achieved.

Natural Abundant Solid State NMR Studies in Designed Tripeptides for Differentiation of Multiple Conformers

Solid state NMR (SSNMR) experiments on heteronuclei in natural abundance are described for three synthetically designed tripeptides Piv-(L)Pro_(L)Pro-(L)Phe-OMe (1), Piv-(D)Pro_(L)Pro_(L)Phe-OMe (2), and Piv-(D)Pro_(L)Pro_(L)Phe-NHMe (3). These peptides exist in different conformation as shown by solution state NMR and single crystal X-ray analysis (Chatterjee et al., Chem Eur J 2008, 14, 6192). In this study, SSNMR has been used to probe the conformations of these peptides in their powder form. The C-13 spectrum of peptide (1) showed doubling of resonances corresponding to cis/cis form, unlike in solution where the similar doubling is attributed to cis/trans form. This has been confirmed by the chemical shift differences of C-beta and C-gamma carbon of Proline in peptide (1) both in solution and SSNMR. Peptide (2) and (3) provided single set of resonances which represented all transform across the di-Proline segment. The results are In agreement with the X-ray analysis. Solid state N-15 resonances, especially from Proline residues provided additional information, which is normally not observable in solution state NMR. H-1 chemical shifts are also obtained from a two-dimensional heteronuclear correlation experiment between H-1-C-13. The results confirm the utility of NMR as a useful tool for identifying different conformers in peptides in the solid state. (C) 2009 Wiley Periodicals, Inc. Biopolymers 91: 851-860, 2009.

The plasticity of NBS resistance genes in sorghum is driven by multiple evolutionary processes

Background Increased disease resistance is a key target of cereal breeding programs, with disease outbreaks continuing to threaten global food production, particularly in Africa. Of the disease resistance gene families, the nucleotide-binding site plus leucine-rich repeat (NBS-LRR) family is the most prevalent and ancient and is also one of the largest gene families known in plants. The sequence diversity in NBS-encoding genes was explored in sorghum, a critical food staple in Africa, with comparisons to rice and maize and with comparisons to fungal pathogen resistance QTL. Results In sorghum, NBS-encoding genes had significantly higher diversity in comparison to non NBS-encoding genes and were significantly enriched in regions of the genome under purifying and balancing selection, both through domestication and improvement. Ancestral genes, pre-dating species divergence, were more abundant in regions with signatures of selection than in regions not under selection. Sorghum NBS-encoding genes were also significantly enriched in the regions of the genome containing fungal pathogen disease resistance QTL; with the diversity of the NBS-encoding genes influenced by the type of co-locating biotic stress resistance QTL. Conclusions NBS-encoding genes are under strong selection pressure in sorghum, through the contrasting evolutionary processes of purifying and balancing selection. Such contrasting evolutionary processes have impacted ancestral genes more than species-specific genes. Fungal disease resistance hot-spots in the genome, with resistance against multiple pathogens, provides further insight into the mechanisms that cereals use in the “arms race” with rapidly evolving pathogens in addition to providing plant breeders with selection targets for fast-tracking the development of high performing varieties with more durable pathogen resistance.

QTL analysis in multiple sorghum populations facilitates the dissection of the genetic and physiological control of tillering

Tillering in sorghum can be associated with either the carbon supply–demand (S/D) balance of the plant or an intrinsic propensity to tiller (PTT). Knowledge of the genetic control of tillering could assist breeders in selecting germplasm with tillering characteristics appropriate for their target environments. The aims of this study were to identify QTL for tillering and component traits associated with the S/D balance or PTT, to develop a framework model for the genetic control of tillering in sorghum. Four mapping populations were grown in a number of experiments in south east Queensland, Australia. The QTL analysis suggested that the contribution of traits associated with either the S/D balance or PTT to the genotypic differences in tillering differed among populations. Thirty-four tillering QTL were identified across the populations, of which 15 were novel to this study. Additionally, half of the tillering QTL co-located with QTL for component traits. A comparison of tillering QTL and candidate gene locations identified numerous coincident QTL and gene locations across populations, including the identification of common non-synonymous SNPs in the parental genotypes of two mapping populations in a sorghum homologue of MAX1, a gene involved in the control of tiller bud outgrowth through the production of strigolactones. Combined with a framework for crop physiological processes that underpin genotypic differences in tillering, the co-location of QTL for tillering and component traits and candidate genes allowed the development of a framework QTL model for the genetic control of tillering in sorghum.

Isolation of multiple novel paramyxoviruses from pteropid bat urine

Bats have been found to harbor a number of new emerging viruses with zoonotic potential and there has been a great deal of interest in identifying novel bat pathogens to determine risk to human and animal health. Many groups have identified novel viruses in bats by detection of viral nucleic acid, however virus isolation is still a challenge and there are few reports of viral isolates from bats. In recent years, our group has developed optimized procedures for virus isolation from bat urine, including the use of primary bat cells. In previous reports we have described the isolation of Hendra virus, Menangle virus and Cedar virus, in Queensland, Australia. Here, we report the isolation of four additional novel bat paramyxoviruses from urine collected from beneath pteropid bat (flying fox) colonies in Queensland and New South Wales during 2009-2011.

Plant composition modulates arthropod pest and predator abundance: Evidence for culling exotics and planting natives

We investigate the role of plant species in crops, pasture and native vegetation remnants in supporting agronomic pests and their predators. The study was conducted in three Australian States and across 290 sites sampled monthly for two years. Pastures played a key role in harbouring pest species consistent across States, while native vegetation hosted relatively more predators than other habitat types within each State. Furthermore, native plant species supported the lowest pest density and more predators than pests; in contrast, 75 of the exotic weed species surveyed hosted more pests than predators. Despite the role of pasture in harbouring pests, we found in NSW that pasture also supported the highest proportion of juvenile predators, while native vegetation remnants had the lowest. Our results indicate that non-crop habitat (native remnants or pasture) with few exotic weeds supports high predator and low pest arthropod densities, and that weeds are associated with high pest densities. By linking broad response variables such as ‘all pests’ with specific predictors such as ‘plant species’, our study will inform on-farm management actions of which weeds to control and which natives to plant or regenerate. This study shows the importance of knowing the function of habitats and plants species in supporting pests and predators in agricultural landscapes across multiple regions.

Multiple instance dictionary learning for activity representation

This paper presents an effective feature representation method in the context of activity recognition. Efficient and effective feature representation plays a crucial role not only in activity recognition, but also in a wide range of applications such as motion analysis, tracking, 3D scene understanding etc. In the context of activity recognition, local features are increasingly popular for representing videos because of their simplicity and efficiency. While they achieve state-of-the-art performance with low computational requirements, their performance is still limited for real world applications due to a lack of contextual information and models not being tailored to specific activities. We propose a new activity representation framework to address the shortcomings of the popular, but simple bag-of-words approach. In our framework, first multiple instance SVM (mi-SVM) is used to identify positive features for each action category and the k-means algorithm is used to generate a codebook. Then locality-constrained linear coding is used to encode the features into the generated codebook, followed by spatio-temporal pyramid pooling to convey the spatio-temporal statistics. Finally, an SVM is used to classify the videos. Experiments carried out on two popular datasets with varying complexity demonstrate significant performance improvement over the base-line bag-of-feature method.

A data fusion approach of multiple maintenance data sources for real-world reliability modelling

A central tenet in the theory of reliability modelling is the quantification of the probability of asset failure. In general, reliability depends on asset age and the maintenance policy applied. Usually, failure and maintenance times are the primary inputs to reliability models. However, for many organisations, different aspects of these data are often recorded in different databases (e.g. work order notifications, event logs, condition monitoring data, and process control data). These recorded data cannot be interpreted individually, since they typically do not have all the information necessary to ascertain failure and preventive maintenance times. This paper presents a methodology for the extraction of failure and preventive maintenance times using commonly-available, real-world data sources. A text-mining approach is employed to extract keywords indicative of the source of the maintenance event. Using these keywords, a Naïve Bayes classifier is then applied to attribute each machine stoppage to one of two classes: failure or preventive. The accuracy of the algorithm is assessed and the classified failure time data are then presented. The applicability of the methodology is demonstrated on a maintenance data set from an Australian electricity company.

Factors influencing hospital readmission and length of stay of Vietnamese patients with type 2 diabetes and cardiac disease

Background: Increased hospital readmission and longer stays in the hospital for patients with type 2 diabetes and cardiac disease can result in higher healthcare costs and heavier individual burden. Thus, knowledge of the characteristics and predictive factors for Vietnamese patients with type 2 diabetes and cardiac disease, at high risk of hospital readmission and longer stays in the hospital, could provide a better understanding on how to develop an effective care plan aimed at improving patient outcomes. However, information about factors influencing hospital readmission and length of stay of patients with type 2 diabetes and cardiac disease in Vietnam is limited. Aim: This study examined factors influencing hospital readmission and length of stay of Vietnamese patients with both type 2 diabetes and cardiac disease. Methods: An exploratory prospective study design was conducted on 209 patients with type 2 diabetes and cardiac disease in Vietnam. Data were collected from patient charts and patients' responses to self-administered questionnaires. Descriptive statistics, bivariate correlation, logistic and multiple regression were used to analyse the data. Results: The hospital readmission rate was 12.0% among patients with both type 2 diabetes and cardiac disease. The average length of stay in the hospital was 9.37 days. Older age (OR= 1.11, p< .05), increased duration of type 2 diabetes (OR= 1.22, p< .05), less engagement in stretching/strengthening exercise behaviours (OR= .93, p< .001) and in communication with physician (OR= .21, p< .001) were significant predictors of 30-dayhospital readmission. Increased number of additional co-morbidities (β= .33, p< .001) was a significant predictor of longer stays in the hospital. High levels of cognitive symptom management (β= .40, p< .001) significantly predicted longer stays in the hospital, indicating that the more patients practiced cognitive symptom management, the longer the stay in hospital. Conclusions: This study provides some evidence of factors influencing hospital readmission and length of stay and argues that this information may have significant implications for clinical practice in order to improve patients' health outcomes. However, the findings of this study related to the targeted hospital only. Additionally, the investigation of environmental factors is recommended for future research as these factors are important components contributing to the research model.

Making and changing wills: Prevalence, predictors, and triggers

Wills are important social, economic, and legal documents. Yet little is known about current will making practices and intentions. A comprehensive national database on the prevalence of will making in Australia was developed to identify who is or is not most likely to draw up a will and triggers for making and changing wills. A national survey of 2,405 adults aged above 18 years was administered by telephone in August and September 2012. Fifty-nine percent of the Australian adult population has a valid will, and the likelihood of will making increases with age and estate value. Efforts to get organized, especially in combination with life stage and asset changes trigger will making; procrastination, rather than a strong resistance, appears to explain not making a will. Understanding will making is timely in the context of predicted significant intergenerational transfers of wealth, changing demographics, and a renewed emphasis on retirement planning.

A Reactive Inverse PN Algorithm for Collision Avoidance among Multiple Unmanned Aerial Vehicles

While performing a mission, multiple Unmanned Aerial Vehicles (UAVs) need to avoid each other to prevent collisions among them. In this paper, we design a collision avoidance algorithm to resolve the conflict among UAVs that are on a collision course while flying to heir respective destinations. The collision avoidance algorithm consist of each UAV that is on a collision course reactively executing a maneuver that will, as in `inverse' Proportional Navigation (PN), increase Line of Sight (LOS) rate between them, resulting in a `pulling out' of collision course. The algorithm is tested for high density traffic scenarios as well as for robustness in the presence of noise.