Applications of Metric Coinduction

Metric coinduction is a form of coinduction that can be used to establish properties of objects constructed as a limit of finite approximations. One can prove a coinduction step showing that some property is preserved by one step of the approximation process, then automatically infer by the coinduction principle that the property holds of the limit object. This can often be used to avoid complicated analytic arguments involving limits and convergence, replacing them with simpler algebraic arguments. This paper examines the application of this principle in a variety of areas, including infinite streams, Markov chains, Markov decision processes, and non-well-founded sets. These results point to the usefulness of coinduction as a general proof technique

CLTS reinvigorates a water and sanitation project

A conventional water and sanitation project in northern Mozambique was mostly focused on water provision by default as sanitation got bogged down in providing incentives, such as cement slab provision for the construction of “improved” latrines. Coverage lagged behind as adoption and the expected technology transfer did not take place. Following introduction of the participatory CLTS strategy, sanitation has become the core of the project, reinvigorating it and giving the project staff a renewed sense of purpose. Sanitation is now leading the way, coverage exceeds that of water, communities and government partners are enthused and neighbouring communities are being seen to imitate the example of this infectious strategy. Handwashing has also been added to the CLTS methodology to make it more “complete”

The Behaviour of Feral Pigs in North-West New South Wales and its Implications for the Epidemiology of Foot and Mouth Disease

A population of feral pigs was monitored by radio-telemetry at at Nocoleche Nature Reserve, in the semi-arid rangelands of north-west New South Wales, Australia to see how high temperature and spatio-temporal variability in food supply influenced habitat utilisation, home-range size, hourly distance moved and adult body weight. Radio-telemetry data was collected during seven intensive tracking sessions between November 1991 and July 1993. This period covered a period of drought and subsequent good seasons following heavy rains in late 1992. Food supply was indexed by estimating pasture biomass in four distinct habitats. These habitats were shrubland, riverine woodland, woodland and ephemeral swamp. Shelter from high temperatures was indexed by the amount of cover estimated from Daubenmire Cover Scale estimates for each habitat. Riverine woodland had the most cover ephemeral swamps the least cover and shrubland and woodland intermediate cover. Habitat utilisation was significantly influenced by pasture biomass in the shrubland and high temperature. Use of shrubland increased with increasing pasture biomass in shrubland and decreasing temperature. Use of riverine woodland increased with decreasing pasture biomass in woodland and increasing temperature. Use of woodland increased with decreasing pasture biomass in shrubland. Use of ephemeral swamps increased with decreasing temperature. Habitat utilisation by feral pigs therefore responds to changes in pasture biomass in shrubland while also responding to temperature with habitats with more cover used more during hot weather

Canonical explorations of 'Tel' environments for computer programming

This paper applies a novel technique of canonical gradient analysis, pioneered in ecological sciences, with the aim of exploring student performance and behaviours (such as communication and collaboration) while undertaking formative and summative tasks in technology enhanced learning (TEL) environments for computer programming. The research emphasis is, therefore, on revealing complex patterns, trends, tacit communications and technology interactions associated with a particular type of learning environment, rather than the testing of discrete hypotheses. The study is based on observations of first year programming modules in BSc Computing and closely related joint-honours with software engineering, web and game development courses. This research extends earlier work, and evaluates the suitability of canonical approaches for exploring complex dimensional gradients represented by multivariate and technology-enhanced learning environments. The advancements represented here are: (1) an extended context, beyond the use of the ‘Ceebot’ learning platform, to include learning-achievement following advanced instruction using an industrystandard integrated development environment, or IDE, for engineering software; and (2) longitudinal comparison of consistency of findings across cohort years. Direct findings (from analyses based on code tests, module assessment and questionnaire surveys) reveal overall engagement with and high acceptance of collaborative working and of the TEL environments used, but an inconsistent relationship between deeply learned programming skills and module performance. The paper also discusses research findings in the contexts of established and emerging teaching practices for computer programming, as well as government policies and commercial requirements for improved capacity in computer-science related industries

Evaluasi Program Pembelajaran Bahasa Inggris

The aims of this research were to evaluate English learning in context, input, process, product. This research was an evaluation research. The sources of the research were students of English for Children class at English Smart Bandar Jaya. The data was collected through observation, test, and documentation which was analyzed descriptive quantitative. The conclusions in this research were : 1) the of context value of sub component at the pre-condition is fair, the input value of component sub component infrastructure,human resources and curriculum is poor, the result of process component sub component of planning and english learning implementation is fair, and the product component value in the learning result of the students is fair, and 2) the recommendation of this research,the general manager needs to observe and change the curriculum for a better future, then provide laboratory room for listening, the teachers should make a lesson plan based on the syllabus for each competency.Penelitian ini bertujuan untuk mengevaluasi pembelajaran Bahasa Inggris pada komponen context, input, process, product. Penelitian ini merupakan penelitian evaluasi. Sumber penelitian adalah pembelajar kelas English for Children di English Smart Bandar Jaya. Data dikumpulkan dengan observasi, tes dan dokumentasi kemudian dianalisis secara deskriptif kuantitatif. Kesimpulan dalam penelitian ini : 1) nilai context sub komponen kondisi awal lembaga cukup, nilai input sub komponen fasilitas sarana prasarana, tenaga pendidik dan kurikulum cukup, nilai process sub komponen perencanaan dan pelaksanaan pembelajaran bahasa Inggris kurang, dan nilai komponen product pada hasil belajar pembelajar cukup, dan 2) rekomendasi penelitian ini, kepala lembaga perlu meninjau atau mengubah kurikulum lembaga untuk pembaruan ke arah yang lebih baik, disediakan ruang laboratorium untuk menunjang pembelajaran listening, tentor harus membuat lesson plan yang disusun berdasarkan silabus unit kompetensi

Characterisation of Polymesoda bengalensis Shell Powder

Seafood shell is abundant and has no eminent use and thus, commonly regarded as waste.Reusing and converting it into a useful material can decrease the amount of waste.Therefore, a study of the crystalline structure should be performed before identifying the potential use of the material. Theaim of this study istoidentifythe element and polymorph of Polymesoda bengalensis shell. The characterisations involved the usage of X-ray powder diffraction (XRD), scanning electron microscope (SEM)andenergy-dispersive X-ray spectroscopy (EDX). The XRD study revealed that theshellpowder mostly consisted of aragonite. The analysis from SEM also revealed that the aragonite was in the form of rod-like crystal. The morphology of sectional, inner and outer surfaces of the shell was s foundthat the aragonite was arranged in the form of a cross-lamellar structure of various sizes. The elemental content of the shell showed that CaCO3in this shell contained large amounts of calcium and carbon

The qualification of an enrichment biomarker for clinical trials targeting early stages of Parkinson’s disease

As therapeutic trials target early stages of Parkinson’s disease (PD), appropriate patient selection based purely on clinical criteria poses significant challenges. Members of the Critical Path for Parkinson’s Consortium formally submitted documentation to the European Medicines Agency (EMA) supporting the use of Dopamine Transporter (DAT) neuroimaging in early PD. Regulatory documents included a comprehensive literature review, a proposed analysis plan of both observational and clinical trial data, and an assessment of biomarker reproducibility and reliability. The research plan included longitudinal analysis of the Parkinson Research Examination of CEP-1347 Trial (PRECEPT) and the Parkinson’s Progression Markers Initiative (PPMI) study to estimate the degree of enrichment achieved and impact on future trials in subjects with early motor PD. The presence of reduced striatal DAT binding based on visual reads of single photon emission tomography (SPECT) scans in early motor PD subjects was an independent predictor of faster decline in UPDRS Parts II and III as compared to subjects with scans without evidence of dopaminergic deficit (SWEDD) over 24 months. The EMA issued in 2018 a full Qualification Opinion for the use of DAT as an enrichment biomarker in PD trials targeting subjects with early motor symptoms. Exclusion of SWEDD subjects in future clinical trials targeting early motor PD subjects aims to enrich clinical trial populations with idiopathic PD patients, improve statistical power, and exclude subjects who are unlikely to progress clinically from being exposed to novel test therapeutics

Optimizing Sparse RFI Prediction using Deep Learning

Radio Frequency Interference (RFI) is an ever-present limiting factor among radio telescopes even in the most remote observing locations. When looking to retain the maximum amount of sensitivity and reduce contamination for Epoch of Reionization studies, the identification and removal of RFI is especially important. In addition to improved RFI identification, we must also take into account computational efficiency of the RFI-Identification algorithm as radio interferometer arrays such as the Hydrogen Epoch of Reionization Array grow larger in number of receivers. To address this, we present a Deep Fully Convolutional Neural Network (DFCN) that is comprehensive in its use of interferometric data, where both amplitude and phase information are used jointly for identifying RFI. We train the network using simulated HERA visibilities containing mock RFI, yielding a known "ground truth" dataset for evaluating the accuracy of various RFI algorithms. Evaluation of the DFCN model is performed on observations from the 67 dish build-out, HERA-67, and achieves a data throughput of 1.6$\times 10^{5}$ HERA time-ordered 1024 channeled visibilities per hour per GPU. We determine that relative to an amplitude only network including visibility phase adds important adjacent time-frequency context which increases discrimination between RFI and Non-RFI. The inclusion of phase when predicting achieves a Recall of 0.81, Precision of 0.58, and $F_{2}$ score of 0.75 as applied to our HERA-67 observations.Comment: 11 pages, 7 figure