The impact of social relationships on cognitive performance in the older adult : emotional loneliness is detrimental to cognitive performance : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Clinical Psychology at Massey University, Palmerston North

The present study examined the influence of loneliness and objective social isolation on cognitive performance at baseline (time 1) and after two years (time 2) among older adults aged 65 - 84 years old. The exploration of the moderating role of objective social isolation on the relationship between loneliness and cognitive performance was investigated. The role education may have in moderating the relationship between loneliness, objective social isolation and cognitive performance was also investigated. This study extends previous work on loneliness and social isolation, and cognition in two ways. While previous research has found a link between loneliness, objective social isolation, and cognition, many studies have considered loneliness and objective social isolation independent of each other when investigating their relationship with cognition. This study investigated the relative and synergistic relationship between loneliness, objective social isolation and cognition. Secondly, Weiss (1973) conceptualised loneliness as emotional loneliness or social loneliness. Social loneliness as a risk factor for cognitive performance in the older adult has been overlooked. This study considered both emotional loneliness and social loneliness, as two different forms of loneliness that may influence cognition in the older adult. The current study examined the impact of three different types of social isolation (emotional loneliness, social loneliness and objective social isolation) on global cognition and cognitive domains (memory, fluency, language and visuospatial ability). Pre-existing data from the New Zealand Longitudinal Study of Ageing (NZLSA; 2010 and 2012) was used for analysis. The relationships between emotional loneliness, social loneliness and objective social isolation were examined using standard quantitative statistical procedures with linear hierarchical multiple regression being the primary technique. Results showed that loneliness (emotional and social) and objective social isolation may be differentially important for cognitive performance in the older adult. Emotional loneliness had an association with global cognition, verbal fluency, language and visuospatial ability, though not memory at baseline. At the two year follow-up emotional loneliness had an association with global cognition, memory, language, and visuospatial ability, though not verbal fluency. Social loneliness did not have an association with cognition at baseline, and was found to be a suppressor variable at the two year follow-up. Objective social isolation had an association at baseline with visuospatial ability only, which did not carry through to the two year analysis. Novel findings were that older adults who were emotional lonely and not socially isolated had poorer cognitive performance at baseline for global cognition, language and visuospatial tasks, than those who were emotionally lonely and socially isolated. Also older adults who had low levels of education and were socially isolated performed better in visuospatial tasks at baseline than older adults with low levels of education who were not socially isolated. Explanations of why emotional loneliness influence cognition is discussed, with a focus on the ‘lonely in the crowd’ subsample of older adults. Limitations of the study and implications for future research, such as need for longitudinal research that includes control variables such as personality factors, stress and sleep is also discussed

Lazy Preemption to Enable Path-Based Analysis of Interrupt-Driven Code

ABSTRACT One of the important factors in ensuring the correct functionality of wireless sensor networks (WSNs) is the reliability of the software running on individual sensor nodes. Research has shown that path-sensitive static analysis is effective for bug detection and fault diagnosis; however, path-sensitive analysis is prohibitively expensive when applied to a WSN application due to the large state space caused by arbitrary interrupt preemptions. In this paper, we propose a new execution model called lazy preemption that reduces this state space by restricting interrupt handlers to a set of predetermined preemption points, if possible. This execution model allows us to represent the program with an inter-interrupt control flow graph (IICFG), which is easier to analyze than the original CFGs with arbitrary interrupt preemptions

Influence of blade aerodynamic model on prediction of helicopter rotor aeroacoustic signatures

Brown’s vorticity transport model has been used to investigate how the local blade aerodynamic model influences the quality of the prediction of the high-frequency airloads associated with blade–vortex interactions, and thus the accuracy with which the acoustic signature of a helicopter rotor can be predicted. The vorticity transport model can accurately resolve the structure of the wake of the rotor and allows significant flexibility in the way that the blade loading can be represented. The Second Higher-Harmonic Control Aeroacoustics Rotor Test was initiated to provide experimental insight into the acoustic signature of a rotor in cases of strong blade–vortex interaction. Predictions of two models for the local blade aerodynamics are compared with the test data. A marked improvement in accuracy of the predicted high-frequency airloads and acoustic signature is obtained when a lifting-chord model for the blade aerodynamics is used instead of a lifting-line-type approach. Errors in the amplitude and phase of the acoustic peaks are reduced, and the quality of the prediction is affected to a lesser extent by the computational resolution of the wake, with the lifting-chord model producing the best representation of the distribution of sound pressure below the rotor

Influence of blade aerodynamic model on the prediction of helicopter high-frequency airloads

Brown’s vorticity transport model has been used to investigate the influence of the blade aerodynamic model on the accuracy with which the high-frequency airloads associated with helicopter blade–vortex interactions can be predicted. The model yields an accurate representation of the wake structure yet allows significant flexibility in the way that the blade loading can be represented. A simple lifting-line model and a somewhat more sophisticated liftingchord model, based on unsteady thin aerofoil theory, are compared. A marked improvement in the accuracy of the predicted high-frequency airloads of the higher harmonic control aeroacoustic rotor is obtained when the liftingchord model is used instead of the lifting-line approach, and the quality of the prediction is affected less by the computational resolution of the wake. The lifting-line model overpredicts the amplitude of the lift response to blade–vortex interactions as the computational grid is refined, exposing the fundamental deficiencies in this approach when modeling the aerodynamic response of the blade to interactions with vortices that are much smaller than its chord. The airloads that are predicted using the lifting-chord model are relatively insensitive to the resolution of the computation, and there are fundamental reasons to believe that properly converged numerical solutions may be attainable using this approach

Multiple recombination events between two cytochrome P450 loci contribute to global pyrethroid resistance in Helicoverpa armigera

The cotton bollworm, Helicoverpa armigera (Hübner) is one of the most serious insect pest species to evolve resistance against many insecticides from different chemical classes. This species has evolved resistance to the pyrethroid insecticides across its native range and is becoming a truly global pest after establishing in South America and having been recently recorded in North America. A chimeric cytochrome P450 gene, CYP337B3, has been identified as a resistance mechanism for resistance to fenvalerate and cypermethrin. Here we show that this resistance mechanism is common around the world with at least eight different alleles. It is present in South America and has probably introgressed into its closely related native sibling species, Helicoverpa zea. The different alleles of CYP337B3 are likely to have arisen independently in different geographic locations from selection on existing diversity. The alleles found in Brazil are those most commonly found in Asia, suggesting a potential origin for the incursion of H. armigera into the Americas

Fragment-based discovery of a new class of inhibitors targeting mycobacterial tRNA modification.

Translational frameshift errors are often deleterious to the synthesis of functional proteins and could therefore be promoted therapeutically to kill bacteria. TrmD (tRNA-(N(1)G37) methyltransferase) is an essential tRNA modification enzyme in bacteria that prevents +1 errors in the reading frame during protein translation and represents an attractive potential target for the development of new antibiotics. Here, we describe the application of a structure-guided fragment-based drug discovery approach to the design of a new class of inhibitors against TrmD in Mycobacterium abscessus. Fragment library screening, followed by structure-guided chemical elaboration of hits, led to the rapid development of drug-like molecules with potent in vitro TrmD inhibitory activity. Several of these compounds exhibit activity against planktonic M. abscessus and M. tuberculosis as well as against intracellular M. abscessus and M. leprae, indicating their potential as the basis for a novel class of broad-spectrum mycobacterial drugs

Development of Cancer Surveillance Guidelines in Ataxia Telangiectasia: A Delphi-Based Consensus Survey of International Experts

BACKGROUND/OBJECTIVES: Ataxia telangiectasia (A-T) is a multiorgan disorder with increased vulnerability to cancer. Despite this increased cancer risk, there are no widely accepted guidelines for cancer surveillance in people affected by A-T. We aimed to understand the current international practice regarding cancer surveillance in A-T and agreed-upon approaches to develop cancer surveillance in A-T. DESIGN/METHODS: We used a consensus development method, the e-Delphi technique, comprising three rounds. Round 1 consisted of a Delphi questionnaire and a survey that collected the details of respondents\u27 professional background, experience, and current practice of cancer surveillance in A-T. Rounds 2 and 3 were designed based on previous rounds and modified according to the comments made by the panellists. The pre-specified consensus threshold was ≥75% agreement. RESULTS: Thirty-five expert panellists from 13 countries completed the study. The survey indicated that the current practice of cancer surveillance varies widely between experts and centres\u27. Consensus was reached that evidence-based guidelines are needed for cancer surveillance in people with A-T, with separate recommendations for adults and children. Statements relating to the tests that should be included, the age for starting and stopping cancer surveillance and the optimal surveillance interval were also agreed upon, although in some areas, the consensus was that further research is needed. CONCLUSION: The international expert consensus statement confirms the need for evidence-based cancer surveillance guidelines in A-T, highlights key features that the guidelines should include, and identifies areas of uncertainty in the expert community. This elucidates current knowledge gaps and will inform the design of future clinical trials

Developing Transdisciplinary Approaches to Sustainability Challenges: The Need to Model Socio-Environmental Systems in the Longue Durée

Human beings are an active component of every terrestrial ecosystem on Earth. Although our local impact on the evolution of these ecosystems has been undeniable and extensively documented, it remains unclear precisely how our activities are altering them, in part because ecosystems are dynamic systems structured by complex, non-linear feedback processes and cascading effects. We argue that it is only by studying human–environment interactions over timescales that greatly exceed the lifespan of any individual human (i.e., the deep past or longue durée), we can hope to fully understand such processes and their implications. In this article, we identify some of the key challenges faced in integrating long-term datasets with those of other areas of sustainability science, and suggest some useful ways forward. Specifically, we (a) highlight the potential of the historical sciences for sustainability science, (b) stress the need to integrate theoretical frameworks wherein humans are seen as inherently entangled with the environment, and (c) propose formal computational modelling as the ideal platform to overcome the challenges of transdisciplinary work across large, and multiple, geographical and temporal scales. Our goal is to provide a manifesto for an integrated scientific approach to the study of socio-ecological systems over the long term