Functional activation during the Rapid Visual Information Processing task in a middle aged cohort: An fMRI study

The Rapid Visual Information Processing (RVIP) task, a serial discrimination task where task performance believed to reflect sustained attention capabilities, is widely used in behavioural research and increasingly in neuroimaging studies. To date, functional neuroimaging research into the RVIP has been undertaken using block analyses, reflecting the sustained processing involved in the task, but not necessarily the transient processes associated with individual trial performance. Furthermore, this research has been limited to young cohorts. This study assessed the behavioural and functional magnetic resonance imaging (fMRI) outcomes of the RVIP task using both block and event-related analyses in a healthy middle aged cohort (mean age = 53.56 years, n = 16). The results show that the version of the RVIP used here is sensitive to changes in attentional demand processes with participants achieving a 43% accuracy hit rate in the experimental task compared with 96% accuracy in the control task. As shown by previous research, the block analysis revealed an increase in activation in a network of frontal, parietal, occipital and cerebellar regions. The event related analysis showed a similar network of activation, seemingly omitting regions involved in the processing of the task (as shown in the block analysis), such as occipital areas and the thalamus, providing an indication of a network of regions involved in correct trial performance. Frontal (superior and inferior frontal gryi), parietal (precuenus, inferior parietal lobe) and cerebellar regions were shown to be active in both the block and event-related analyses, suggesting their importance in sustained attention/vigilance. These networks and the differences between them are discussed in detail, as well as implications for future research in middle aged cohorts.

A Bayesian Framework for the Assessment of Vision-based Weed and Fruit Detection and Classification Algorithms

This paper proposes new metrics and a performance-assessment framework for vision-based weed and fruit detection and classification algorithms. In order to compare algorithms, and make a decision on which one to use fora particular application, it is necessary to take into account that the performance obtained in a series of tests is subject to uncertainty. Such characterisation of uncertainty seems not to be captured by the performance metrics currently reported in the literature. Therefore, we pose the problem as a general problem of scientific inference, which arises out of incomplete information, and propose as a metric of performance the(posterior) predictive probabilities that the algorithms will provide a correct outcome for target and background detection. We detail the framework through which these predicted probabilities can be obtained, which is Bayesian in nature. As an illustration example, we apply the framework to the assessment of performance of four algorithms that could potentially be used in the detection of capsicums (peppers).

Optimisation-based Design of a Manipulator for Harvesting Capsicum

This paper presents a global-optimisation frame-work for the design of a manipulator for harvesting capsicum(peppers) in the field. The framework uses a simulated capsicum scenario with automatically generated robot models based on DH parameters. Each automatically generated robot model is then placed in the simulated capsicum scenario and the ability of the robot model to get to several goals (capsicum with varying orientations and positions) is rated using two criteria:the length of a collision-free path and the dexterity of the end-effector. These criteria form the basis of the objective function used to perform a global optimisation. The paper shows a preliminary analysis and results that demonstrate the potential of this method to choose suitable robot models with varying degrees of freedom.

On Visual Detection of Highly-occluded Objects for Harvesting Automation in Horticulture

Developing accurate and reliable crop detection algorithms is an important step for harvesting automation in horticulture. This paper presents a novel approach to visual detection of highly-occluded fruits. We use a conditional random field (CRF) on multi-spectral image data (colour and Near-Infrared Reflectance, NIR) to model two classes: crop and background. To describe these two classes, we explore a range of visual-texture features including local binary pattern, histogram of oriented gradients, and learn auto-encoder features. The pro-posed methods are evaluated using hand-labelled images from a dataset captured on a commercial capsicum farm. Experimental results are presented, and performance is evaluated in terms of the Area Under the Curve (AUC) of the precision-recall curves.Our current results achieve a maximum performance of 0.81AUC when combining all of the texture features in conjunction with colour information.

Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans

Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same region.

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.

Generalizability of established prostate cancer risk variants in men of African ancestry

Genome-wide association studies have identified more than 80 risk variants for prostate cancer, mainly in European or Asian populations. The generalizability of these variants in other racial/ethnic populations needs to be understood before the loci can be used widely in risk modeling. In our study, we examined 82 previously reported risk variants in 4,853 prostate cancer cases and 4,678 controls of African ancestry. We performed association testing for each variant using logistic regression adjusted for age, study and global ancestry. Of the 82 known risk variants, 68 (83%) had effects that were directionally consistent in their association with prostate cancer risk and 30 (37%) were significantly associated with risk at p < 0.05, with the most statistically significant variants being rs116041037 (p = 3.7 × 10(-26) ) and rs6983561 (p = 1.1 × 10(-16) ) at 8q24, as well as rs7210100 (p = 5.4 × 10(-8) ) at 17q21. By exploring each locus in search of better markers, the number of variants that captured risk in men of African ancestry (p < 0.05) increased from 30 (37%) to 44 (54%). An aggregate score comprised of these 44 markers was strongly associated with prostate cancer risk [per-allele odds ratio (OR) = 1.12, p = 7.3 × 10(-98) ]. In summary, the consistent directions of effects for the vast majority of variants in men of African ancestry indicate common functional alleles that are shared across populations. Further exploration of these susceptibility loci is needed to identify the underlying biologically relevant variants to improve prostate cancer risk modeling in populations of African ancestry.

Conceptualising the challenge of integrating digital technologies in pedagogy

The integration of digital technologies in pedagogy is positioned as an important change in education, but widespread innovative use of digital technologies is yet to be truly realised. The gap between the potential and the reality of digital technology integration is commonly attributed to a range of challenging extrinsic and intrinsic influences. Activity Theory (Engeström, 2009) is used to analyse challenges created by extrinsic influences (Nielsen, Miller, & Hoban, 2012); a complementary theory is needed to conceptualise intrinsic influences. System 1 and System 2 thinking theory (Kahneman, 2011) will be advanced as a conceptual framework for understanding conscious and unconscious aspects of teacher practice, particularly the interaction between innovation and teacher routine, attitudes and beliefs. Transformative Learning Theory (Mezirow, 2009) will be positioned to comprehend the nexus of extrinsic and intrinsic influences. This paper will propose how, when faced with extrinsic and intrinsic influences on innovative practice, educators can use these theories to conceptualise the challenge of integrating digital technologies in pedagogy.

A Sketch of the Phonology and Grammar of Rajbanshi

This dissertation is a synchronic description of the phonology and grammar of two dialects of the Rajbanshi language (Eastern Indo-Aryan) as spoken in Jhapa, Nepal. I have primarily confined the analysis to the oral expression, since the emerging literary form is still in its infancy. The grammatical analysis is therefore based, for the most part, on a corpus of oral narrative text which was recorded and transcribed from three informants from north-east Jhapa. An informant, speaking a dialect from south-west Jhapa cross checked this text corpus and provided additional elicited material. I have described the phonology, morphology and syntax of the language, and also one aspect of its discourse structure. For the most part the phonology follows the basic Indo-Aryan pattern. Derivational morphology, compounding, reduplication, echo formation and onomatopoeic constructions are considered, as well as number, noun classes (their assignment and grammatical function), pronouns, and case and postpositions. In verbal morphology I cover causative stems, the copula, primary and secondary agreement, tense, aspect, mood, auxiliary constructions and non-finite forms. The term secondary agreement here refers to genitive agreement, dative-subject agreement and patient (and sometimes patient-agent) agreement. The breaking of default agreement rules has a range of pragmatic inferences. I argue that a distinction, based on formal, semantic and statistical grounds, should be made between conjunct verbs, derivational compound verbs and quasi-aspectual compound verbs. Rajbanshi has an open set of adjectives, and it additionally makes use of a restricted set of nouns which can function as adjectives. Various particles, and the emphatic and conjunctive clitics are also considered. The syntactic structures studied include: non-declarative speech acts, phrase-internal and clause-internal constituent order, negation, subordination, coordination and valence adjustment. I explain how the future, present and past tenses in Rajbanshi oral narratives do not seem to maintain a time reference, but rather to indicate a distinction between background and foreground information. I call this tense neutralisation .

Preliminary phonological analysis of the Limi dialect of Humla Bhotia

The purpose of this research was to analyse the phonological system of the Limi dialect of Humla Bhotia. Humla Bhotia is a Tibeto-Burman language that is spoken by approximately 4000 5000 people in the far northwestern Humla province of the Kingdom of Nepal. The language has not previously been the subject of analysis. The data base for this thesis was collected on two different dialects of Humla Bhotia in Kathmandu, the capital of Nepal, from February to May 2000. I had three language informants who speak Humla Bhotia as their mother tongue. One of the informants speaks the Upper Humla dialect and the other two informants speak the Limi dialect. In this thesis I have concentrated on the phonology of the dialect of Limi but occasionally I also make reference to the Upper Humla dialect. The Limi data base consists of 600 words elicited in isolation, sentences where words have been checked for consonantal and pitch variation, and five texts comprising 117 sentences. Firstly, I have studied the geographical location, population and dialects of Humla Bhotia. Five dialects were identified: Limi, Upper Humla, La Yakba, Nyinba and Humli Khyampa. Information on the dialect areas is based on the accounts of seven mother tongue speakers of the language and on Nancy Levine s (1988) anthropological research of the ethnic group Nyinba. Secondly, I have analysed the phonological system of Limi from the viewpoint of American stucturalism much along the lines followed by Pike 1966 [1947] ja 1967 [1948]. In defining the prosodic elements I have also used acoustic analysis. In the Limi dialect there are 7 vowel phonemes. No vowel clusters occur within the same syllable. In this preliminary analysis 29 contrastive plosives, 8 affricates and 5 6 fricatives were found. The data also revealed 4 nasal phonemes, two rhotic phonemes, one lateral phoneme and two central approximants. Further research is however called for to check the phonemic status of these segments. Four contrastive prosodic elements were encountered: nasalisation, length, phonation type and pitch movement. There are two contrastive types of phonation: tense and lax. Many words were found with a third type of phonation, modal phonation. How modal phonation relates to the prosodic system is unclear at this stage and is therefore left for further research to determine. There are two contrastive pitch movement tonemes: a rising toneme and falling toneme. The falling toneme occurs in free variation with a level pitch contour. Rising appears to be linked with lax phonation and falling with tense phonation.

miR-514a regulates the tumour suppressor NF1 and modulates BRAFi sensitivity in melanoma

To identify ‘melanoma-specific’ microRNAs (miRNAs) we used an unbiased microRNA profiling approach to comprehensively study cutaneous melanoma in relation to other solid malignancies, which revealed 233 differentially expressed (≥ 2 fold, p < 0.05) miRNAs. Among the top 20 most significantly different miRNAs was hsa-miR-514a-3p. miR-514a is a member of a cluster of miRNAs (miR-506-514) involved in initiating melanocyte transformation and promotion of melanoma growth. We found miR-514a was expressed in 38/55 (69%) melanoma cell lines but in only 1/34 (3%) other solid cancers. To identify miR-514a regulated targets we conducted a miR-514a-mRNA ‘pull-down’ experiment, which revealed hundreds of genes, including: CTNNB1, CDK2, MC1R, and NF1, previously associated with melanoma. NF1 was selected for functional validation because of its recent implication inacquired resistance to BRAFV600E-targeted therapy. Luciferase-reporter assays confirmed NF1 as a direct target of miR-514a and over-expression of miR-514a in melanoma cell lines inhibited NF1 expression, which correlated with increased survival of BRAFV600E cells treated with PLX4032. These data provide another mechanism for the dysregulation of the MAPK pathway which may contribute to the profound resistance associated with current RAF-targeted therapies.

The freezing characteristics of wheat at ear emergence

Wheat is occasionally exposed to freezing temperatures during ear emergence and can suffer severe frost damage. Few studies have attempted to understand the characteristics of freezing and frost damage to wheat during late development stages. It was clearly shown that wheat appears to have an inherent frost resistance to temperatures down to −5 °C but is extensively damaged below this temperature. Acclimation, whilst increasing the frost resistance of winter wheat in a vegetative state was incapable of increasing frost resistance of plants at ear emergence. It is proposed that the ability to upregulate frost resistance is lost once vernalisation requirement is fulfilled. Culms and ears of wheat were able to escape frost damage at temperatures below −5 °C by supercooling even to as low as −15 °C and evidence collected by infrared thermography suggested that individual culms on a plant froze as independent units during freezing with little or no cross ice-nucleation strategies to protect wheat from frost damage in the field appear to revolve around avoiding ice nucleation.

Applications of pedigree-based genome mapping in wheat and barley breeding programs.

The aim of the pedigree-based genome mapping project is to investigate and develop systems for implementing marker assisted selection to improve the efficiency of selection and increase the rate of genetic gain in breeding programs. Pedigree-based whole genome marker application provides a vehicle for incorporating marker technologies into applied breeding programs by bridging the gap between marker-trait association and marker implementation. We report on the development of protocols for implementation of pedigree-based whole genome marker analysis in breeding programs within the Australian northern winter cereals region. Examples of applications from the Queensland DPI&F wheat and barley breeding programs are provided, commenting on the use of microsatellites and other types of molecular markers for routine genomic analysis, the integration of genotypic, phenotypic and pedigree information for targeted wheat and barley lines, the genomic impacts of strong selection pressure in case study pedigrees, and directions for future pedigree-based marker development and analysis.

Accelerating Pseudo-Marginal MCMC using Gaussian Processes

Pseudo-marginal methods such as the grouped independence Metropolis-Hastings (GIMH) and Markov chain within Metropolis (MCWM) algorithms have been introduced in the literature as an approach to perform Bayesian inference in latent variable models. These methods replace intractable likelihood calculations with unbiased estimates within Markov chain Monte Carlo algorithms. The GIMH method has the posterior of interest as its limiting distribution, but suffers from poor mixing if it is too computationally intensive to obtain high-precision likelihood estimates. The MCWM algorithm has better mixing properties, but less theoretical support. In this paper we propose to use Gaussian processes (GP) to accelerate the GIMH method, whilst using a short pilot run of MCWM to train the GP. Our new method, GP-GIMH, is illustrated on simulated data from a stochastic volatility and a gene network model.