Segmented Linear Regression Modelling of Time-Series of Binary Variables in Healthcare.

Introduction:In healthcare, change is usually detected by statistical techniques comparing outcomes before and after an intervention. A common problem faced by researchers is distinguishing change due to secular trends from change due to an intervention. Interrupted time-series analysis has been shown to be effective in describing trends in retrospective time-series and in detecting change, but methods are often biased towards the point of the intervention. Binary outcomes are typically modelled by logistic regression where the log-odds of the binary event is expressed as a function of covariates such as time, making model parameters difficult to interpret. The aim of this study was to present a technique that directly models the probability of binary events to describe change patterns using linear sections. Methods:We describe a modelling method that fits progressively more complex linear sections to the time-series of binary variables. Model fitting uses maximum likelihood optimisation and models are compared for goodness of fit using Akaike's Information Criterion. The best model describes the most likely change scenario. We applied this modelling technique to evaluate hip fracture patient mortality rate for a total of 2777 patients over a 6-year period, before and after the introduction of a dedicated hip fracture unit (HFU) at a Level 1, Major Trauma Centre. Results:The proposed modelling technique revealed time-dependent trends that explained how the implementation of the HFU influenced mortality rate in patients sustaining proximal femoral fragility fractures. The technique allowed modelling of the entire time-series without bias to the point of intervention. Modelling the binary variable of interest directly, as opposed to a transformed variable, improved the interpretability of the results. Conclusion:The proposed segmented linear regression modelling technique using maximum likelihood estimation can be employed to effectively detect trends in time-series of binary variables in retrospective studies

Heroic Self-Fashioning in Statius' Thebaid

This thesis will examine how heroes attempt to create their own heroic identity in Statius’ epic poem, the Thebaid. The Thebaid is a poem with no single central character, but a central group of heroes of relatively equal standing. Among this large crowd, each individual attempts to prove their heroic worth by manipulating narratives about themselves. In this way, they hope to improve their standing in society, and their chances of being remembered well by posterity. But heroic identity relies on the recognition of society, meaning reputation is difficult to control among the public. Therefore, these individuals must perform a heroic identity, so that society would actually recognise them in such a way. However, the Thebaid is a poem about failure. Few of the heroes remain alive by the end of the poem. Fewer still remain with their good reputations intact. In their attempts to push pass the limits of humanity to gain eternal fame, most commit terrible sins. The heroic greatness that they claim to have in their self-presentations is therefore called into question by the Thebaid’s narrative and its narrator, who condemns the actions of the heroes throughout the poem. Throughout my project, I will be interested in the gap that forms behind the heroic image, which the heroes create about themselves in their narratives, and those of the main narrator. The narrator will consistently undermine the efforts of the heroes, encouraging counter-interpretations to the heroic image that the characters hope to cement. In my first chapter, I will examine how the heroes create narratives about themselves by trying to control the discourse about their family. This can involve suppressing or even changing details from their family history, so that their ancestors will have a positive effect on their reputation. In my second chapter, I will examine how the heroes manipulate the rhetoric about monster-slaying. The heroes attempt to portray themselves as forces of good, removing evil monsters from the world; in reality, they themselves become monstrous through their actions, and become a source of evil to the world. My final chapter will examine the relationship between the text and contemporary Flavian society. I suggest that Flavian society was one that was self-conscious about self-portrayal, and that a discourse had arisen about the appropriate ways in which this should be done. I hope to show that the attempts of the heroes to make themselves look like heroes are a reflection of these contemporary anxieties

Minimal effects of waterborne exposure to single-walled carbon nanotubes on behaviour and physiology of juvenile rainbow trout (Oncorhynchus mykiss).

Fish behaviours are often considered to be sensitive endpoints of waterborne contaminants, but little attention has been given to engineered nanomaterials. The present study aimed to determine the locomotor and social behaviours of rainbow trout (Oncorhynchus mykiss) during waterborne exposure to single-walled carbon nanotubes (SWCNTs), and to ascertain the physiological basis for any observed effects. Dispersed stock suspensions of SWCNTs were prepared by stirring in sodium dodecyl sulphate (SDS), an anionic surfactant, on an equal w/w basis. Trout were exposed to control (no SWCNT or SDS), 0.25 mg L(-1) SDS (dispersant control), or 0.25 mg L(-1) of SWCNT for 10 days. Video tracking analysis of spontaneous locomotion of individual fish revealed no significant effects of SWCNT on mean velocity when active, total distance moved, or the distribution of swimming speeds. Hepatic glycogen levels were also unaffected. Fish exposed to SWCNTs retained competitive fitness when compelled to compete in energetically costly aggressive interactions with fish from both control groups. Assessment of the respiratory physiology of the fish revealed no significant changes in ventilation rate or gill injuries. Haematocrit and haemoglobin concentrations in the blood were unaffected by SWCNT exposure; and the absence of changes in the red and white pulp of the spleen excluded a compensatory haematopoietic response to protect the circulation. Despite some minor histological changes in the kidneys of fish exposed to SWCNT compared to controls, plasma ion concentrations and tissue electrolytes were largely unaffected. Direct neurotoxicity of SWCNT was unlikely with the brains showing mostly normal histology, and with no effects on acetylcholinesterase or Na(+)/K(+)-ATPase activities in whole brain homogenates. The minimal effects of waterborne exposure to SWCNT observed in this study are in contrast to our previous report of SWCNT toxicity in trout, suggesting that details of the dispersion method and co-exposure concentration of the dispersing agent may alter toxicity

The microbiome of pest insects:It is not just bacteria

Insects are associated with multiple microbes that have been reported to influence various aspects of their biology. Most studies in insects, including pest species, focus on the bacterial communities of the microbiome even though the microbiome consists of members of many more kingdoms, which can also have large influence on the life history of insects. In this review, we present some key examples of how the different members of the microbiome, such as bacteria, fungi, viruses, archaea, and protozoa, affect the fitness and behavior of pest insects. Moreover, we argue that interactions within and among microbial groups are abundant and of great importance, necessitating the use of a community approach to study microbial-host interactions. We propose that the restricted focus on bacteria very likely hampers our understanding of the functioning and impact of the microbiome on the biology of pest insects. We close our review by highlighting a few open questions that can provide an in-depth understanding of how other components of the microbiome, in addition to bacteria, might influence host performance, thus contributing to pest insect ecology

The Exchange Rate and US Tourism Balance of Trade

This paper investigates evidence on the effect of dollar depreciation on the US tourism balance of trade. Export revenue and import spending functions are estimated separately with structural vector autoregressive methods to better capture the dynamic adjustment to exchange rate shocks. Quarterly data cover the period of floating exchange rates from 1973 through 2007. Depreciation raises long term US export revenue but there is no effect on import spending

The Exchange Rate and US Tourism Balance of Trade

This paper investigates evidence on the effect of dollar depreciation on the US tourism balance of trade. Export revenue and import spending functions are estimated separately with structural vector autoregressive methods to better capture the dynamic adjustment to exchange rate shocks. Quarterly data cover the period of floating exchange rates from 1973 through 2007. Depreciation raises long term US export revenue but there is no effect on import spending

What Does Economics Assume About People’s Knowledge? Who knows?

The purpose of the paper is to explore, from an assessment viewpoint, the ideas below. Economics, as a social science, has always considered sets of individuals with assumed characteristics, namely the level of knowledge, although in an implicit way in most of the cases. In this sense, an influential approach in Economics assumed that society, as a global set of individuals, was characterised by a certain level of knowledge that, indeed, could be associated with the one of its representative agent. In fact, an attentive recall of the evolution of these matters in Economics will immediately recognise that, since the very first economic models of the government, it was assumed that the level of knowledge of society, represented by a set of voters, was not the same as the one of the agent being elected, i.e. the government. The irrelevance of the difference in the level of knowledge of economic agents was soon abandoned after some seminal works of Hayek and Friedman. More recently, the viewpoint of Economics has changed by focusing on the characteristics (e.g. knowledge) of individuals, who may interact in sub-sets of society. From this point of view is clearly relevant, given the close connection with the assumed level of knowledge, to distinguish the adaptive behaviour from the rational one, as well as the full rational from the bounded rationality behaviour by people. Quite recent developments in the Economics of Knowledge, i.e. the so-called learning models, have been considered as more realistic approaches to model the process by which individuals acquire knowledge, for instance from other individuals that are, themselves, acquiring knowledge

The influence of rs53576 polymorphism in the oxytocin receptor (OXTR) gene on empathy in healthy adults by subtype and ethnicity: a systematic review and meta-analysis

Empathy is essential for navigating complex social environments. Prior work has shown associations between rs53576, a single nucleotide polymorphism (SNP) located in the oxytocin receptor gene (OXTR), and generalized empathy. We undertook a systematic review and meta-analysis to assess the effects of rs53576 on subdomains of empathy, specifically cognitive empathy (CE) and affective empathy (AE), in healthy adults. Twenty cohorts of 8933 participants aged 18-98 were identified, including data from the Sydney Memory and Ageing Study, a cohort of older community adults. Meta-analyses found G homozygotes had greater generalized empathic abilities only in young to middle-aged adults. While meta-analyses of empathy subdomains yielded no significant overall effects, there were differential effects based on ethnicity. G homozygotes were associated with greater CE abilities in Asian cohorts (standardized mean difference; SMD: 0.09 [2.8·10-3-0.18]), and greater AE performance in European cohorts [SMD: 0.12 (0.04-0.21)]. The current literature highlights a need for further work that distinguishes between genetic and ethnocultural effects and explores effects of advanced age on this relationship

Some pattern recognitions for a recommendation framework for higher education students’ generic competence development using machine learning

The project presented in this paper aims to formulate a recommendation framework that consolidates the higher education students’ particulars such as their academic background, current study and student activity records, their attended higher education institution’s expectations of graduate attributes and self-assessment of their own generic competencies. The gap between the higher education students’ generic competence development and their current statuses such as their academic performance and their student activity involvement was incorporated into the framework to come up with a recommendation for the student activities that lead to their generic competence development. For the formulation of the recommendation framework, the data mining tool Orange with some programming in Python and machine learning models was applied on 14,556 students’ activity and academic records in the case higher education institution to find out three major types of patterns between the students’ participation of the student activities and (1) their academic performance change, (2) their programmes of studies, and (3) their English results in the public examination. These findings are also discussed in this paperPeer Reviewe