The importance of including habitat-specific behaviour in models of butterfly movement

Dispersal is a key process affecting population persistence and major factors affecting dispersal rates are the amounts, connectedness and properties of habitats in landscapes. We present new data on the butterfly Maniola jurtina in flower-rich and flower-poor habitats that demonstrates how movement and behaviour differ between sexes and habitat types, and how this effects consequent dispersal rates. Females had higher flight speeds than males but their total time in flight was four times less. The effect of habitat type was strong for both sexes, flight speeds were ~2.5x and ~1.7x faster on resource-poor habitats for males and females respectively, and flights were approximately 50% longer. With few exceptions females oviposited in the mown grass habitat, likely because growing grass offers better food for emerging caterpillars, but they foraged in the resource-rich habitat. It seems that females faced a trade-off between ovipositing without foraging in the mown grass or foraging without ovipositing where flowers were abundant. We show that taking account of habitat-dependent differences in activity, here categorised as flight or non-flight, is crucial to obtaining good fits of an individual-based model to observed movement. An important implication of this finding is that incorporating habitat-specific activity budgets is likely necessary for predicting longer-term dispersal in heterogeneous habitats as habitat-specific behaviour substantially influences the mean (>30% difference) and kurtosis (1.4x difference) of dispersal kernels. The presented IBMs provide a simple method to explicitly incorporate known activity and movement rates when predicting dispersal in changing and heterogeneous landscapes

Efficient implementation of video processing algorithms on FPGA

The work contained in this portfolio thesis was carried out as part of an Engineering Doctorate (Eng.D) programme from the Institute for System Level Integration. The work was sponsored by Thales Optronics, and focuses on issues surrounding the implementation of video processing algorithms on field programmable gate arrays (FPGA). A description is given of FPGA technology and the currently dominant methods of designing and verifying firmware. The problems of translating a description of behaviour into one of structure are discussed, and some of the latest methodologies for tackling this problem are introduced. A number of algorithms are then looked at, including methods of contrast enhancement, deconvolution, and image fusion. Algorithms are characterised according to the nature of their execution flow, and this is used as justification for some of the design choices that are made. An efficient method of performing large two-dimensional convolutions is also described. The portfolio also contains a discussion of an FPGA implementation of a PID control algorithm, an overview of FPGA dynamic reconfigurability, and the development of a demonstration platform for rapid deployment of video processing algorithms in FPGA hardware

Teacher self-efficacy and pupil achievement: much ado about nothing? International evidence from TIMSS

Bandura’s influential theory has been used to argue that teachers with high self-efficacy will be more effective at increasing pupil achievement—and a voluminous empirical literature has repeatedly documented associations consistent with this claim. However, few studies have considered whether these correlations reflect an underlying causal relationship. In this paper we utilise across-subject, within-pupil variation in teacher self-efficacy in the Trends in Mathematics and Science Study (TIMSS) 2015 data to provide new evidence on this question. By focusing upon relative differences in teacher self-efficacy and pupil achievement within pupil-teacher pairs, our estimates control for more potential confounders than much of the existing literature. Contrary to that literature, we find no evidence of a relationship. Instead, this paper presents clear and consistent findings of null effects

The relationship between inquiry-based teaching and students’ achievement. New evidence from a longitudinal PISA study in England

© 2019 Elsevier Ltd Inquiry-based science teaching involves supporting pupils to acquire scientific knowledge indirectly by conducting their own scientific experiments, rather than receiving scientific knowledge directly from teachers. This approach to instruction is widely used among science educators in many countries. However, researchers and policymakers have recently called the effectiveness of inquiry approaches into doubt. Using nationally-representative, linked survey and administrative data, we find little evidence that the frequency of inquiry-based instruction is positively associated with teenagers’ performance in science examinations. This finding is robust to the use of different measures of inquiry, different examinations/measures of attainment, across classrooms with varying levels of disciplinary standards and across gender and prior attainment subgroups

Freeing Energy Data: A Guide for Regulators to Reduce One Barrier to Residential Energy Efficiency

This report advocates for improving entrepreneurs' access to residential energy-use data, thereby increasing the deployment of cost-effective energy-efficiency measures, generating saving and improving the environment. While this report does discuss policy, its focus is on informing policy makers on how to address liability, consumer privacy, and administrative concerns that could arise when third parties receive energy-use data from utilities. What makes this report novel compared to other efforts is that it provides model language for laws or rules that lawmakers or regulators can use as building blocks to open up access to energy data

Data on the movement behaviour of four species of grassland butterfly

This Data in Brief article describes data on the movement behaviour of four species of grassland butterflies collected over three years and at four sites in southern England. The datasets consist of the movement tracks of and recorded using standard methods and presented as steps distances and turning angles. Sites consisted of nectar-rich field margins, meadows, and mown short turf grasslands with minimal flowers. In total, 783 unique movement tracks were collected. The data were used for analysing the movement behaviour of the species and for parameterising individual-based movement models

Integrating the influence of weather into mechanistic models of butterfly movement

Understanding the factors influencing movement is essential to forecasting species persistence in a changing environment. Movement is often studied using mechanistic models, extrapolating short-term observations of individuals to longer-term predictions, but the role of weather variables such as air temperature and solar radiation, key determinants of ectotherm activity, are generally neglected. We aim to show how the effects of weather can be incorporated into individual-based models of butterfly movement thus allowing analysis of their effects. Methods: We constructed a mechanistic movement model and calibrated it with high precision movement data on a widely studied species of butterfly, the meadow brown (Maniola jurtina), collected over a 21-week period at four sites in southern England. Day time temperatures during the study ranged from 14.5 to 31.5⁰C and solar radiation from heavy cloud to bright sunshine. The effects of weather are integrated into the individual-based model through weather-dependent scaling of parametric distributions representing key behaviours: the durations of flight and periods of inactivity. Results: Flight speed was unaffected by weather, time between successive flights increased as solar radiation decreased, and flight duration showed a unimodal response to air temperature that peaked between approximately 23⁰C and 26⁰C. After validation, the model demonstrated that weather alone can produce a more than two-fold difference in predicted weekly displacement. Conclusions: Individual Based models provide a useful framework for integrating the effect of weather into movement models. By including weather effects we are able to explain a two-fold difference in movement rate of M. jurtina consistent with inter-annual variation in dispersal measured in population studies. Climate change for the studied populations is expected to decrease activity and dispersal rates since these butterflies already operate close to their thermal optimum

The genome sequence of the brown trout, Salmo trutta Linnaeus 1758

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Diagnosis and misdiagnosis of adult neuronal ceroid lipofuscinosis (Kufs disease)

OBJECTIVE: To critically re-evaluate cases diagnosed as adult neuronal ceroid lipofuscinosis (ANCL) in order to aid clinicopathologic diagnosis as a route to further gene discovery. METHODS: Through establishment of an international consortium we pooled 47 unsolved cases regarded by referring centers as ANCL. Clinical and neuropathologic experts within the Consortium established diagnostic criteria for ANCL based on the literature to assess each case. A panel of 3 neuropathologists independently reviewed source pathologic data. Cases were given a final clinicopathologic classification of definite ANCL, probable ANCL, possible ANCL, or not ANCL. RESULTS: Of the 47 cases, only 16 fulfilled the Consortium's criteria of ANCL (5 definite, 2 probable, 9 possible). Definitive alternate diagnoses were made in 10, including Huntington disease, early-onset Alzheimer disease, Niemann-Pick disease, neuroserpinopathy, prion disease, and neurodegeneration with brain iron accumulation. Six cases had features suggesting an alternate diagnosis, but no specific condition was identified; in 15, the data were inadequate for classification. Misinterpretation of normal lipofuscin as abnormal storage material was the commonest cause of misdiagnosis. CONCLUSIONS: Diagnosis of ANCL remains challenging; expert pathologic analysis and recent molecular genetic advances revealed misdiagnoses in >1/3 of cases. We now have a refined group of cases that will facilitate identification of new causative genes