Current Developments in Computer Assisted Cartography at the UK Hydrographic Department

Since the introduction of Computer Assisted Cartography (CAC) techniques into the chart production process at the UK Hydrographic Department in the early 1970s, automation has come to play an increasingly important role. Current policy is to make use of such techniques wherever they offer benefits in terms of cost-effectiveness or production efficiency. This policy has been pursued since combination of the separate CAC production and development units in 1981. The aim of this paper is to summarise the development of the digital production flowline since 1981, to outline the current objectives for further development of the flowline, and to review the progress that is being made towards achieving those objectives. The paper deals specifically with the use of CAC to support production of the conventional paper chart. Expertise gained in the use of CAC is now being applied to experimental work related to the ‘electronic chart’ concept, but those developments fall outside the scope of this paper

The circulatory impact of dust from dust profile assimilation

We present results from a reanalysis of temperatures, dust columns and dust vertical profiles focussing on the assimilation, distribution and transport of dust in the martian atmosphere. The assimilation of dust vertical information in particular is a valuable technique which has been shown to be of vital importance to a successful assimilation of the martian atmosphere, with the vertical representation of the dust distribution having a critical effect on assimilation results generally. Atmospheric dust is a key driver of the martian circulation. Dust-induced heating and cooling is a potential feedback mechanism for dust lifting, for example, and can modify the circulation to either enhance or suppress dust storm activity. Accurately representing its complex spatial and temporal distribution is therefore crucial for understanding Mars’ atmospheric dynamics and transport

Local environmental quality positively predicts breastfeeding in the UK’s Millennium Cohort Study

Background and Objectives: Breastfeeding is an important form of parental investment with clear health benefits. Despite this, rates remain low in the UK; understanding variation can therefore help improve interventions. Life history theory suggests that environmental quality may pattern maternal investment, including breastfeeding. We analyse a nationally representative dataset to test two predictions: (i) higher local environmental quality predicts higher likelihood of breastfeeding initiation and longer duration; (ii) higher socioeconomic status (SES) provides a buffer against the adverse influences of low local environmental quality.Methodology: We ran factor analysis on a wide range of local-level environmental variables. Two summary measures of local environmental quality were generated by this analysis—one ‘objective’ (based on an independent assessor’s neighbourhood scores) and one ‘subjective’ (based on respondent’s scores). We used mixed-effects regression techniques to test our hypotheses.Results: Higher objective, but not subjective, local environmental quality predicts higher likelihood of starting and maintaining breastfeeding over and above individual SES and area-level measures of environmental quality. Higher individual SES is protective, with women from high-income households having relatively high breastfeeding initiation rates and those with high status jobs being more likely to maintain breastfeeding, even in poor environmental conditions.Conclusions and Implications: Environmental quality is often vaguely measured; here we present a thorough investigation of environmental quality at the local level, controlling for individual- and area-level measures. Our findings support a shift in focus away from individual factors and towards altering the landscape of women’s decision making contexts when considering behaviours relevant to public health

Numerical comparison of pipe-column-separation models

Results comparing six column-separation numerical models for simulating localized vapor cavities and distributed vaporous cavitation in pipelines are presented. The discrete vapor-cavity model (DVCM) is shown to be quite sensitive to selected input parameters. For short pipeline systems, the maximum pressure rise following column separation can vary markedly for small changes in wave speed, friction factor, diameter, initial velocity, length of pipe, or pipe slope. Of the six numerical models, three perform consistently over a broad number of reaches. One of them, the discrete gas-cavity model, is recommended for general use as it is least sensitive to input parameters or to the selected discretization of the pipeline. Three models provide inconsistent estimates of the maximum pressure rise as the number of reaches is increased; however, these models do give consistent results provided the ratio of maximum cavity size to reach volume is kept below 10%.Angus R. Simpson and Anton Bergan

Discovering Valuable Items from Massive Data

Suppose there is a large collection of items, each with an associated cost and an inherent utility that is revealed only once we commit to selecting it. Given a budget on the cumulative cost of the selected items, how can we pick a subset of maximal value? This task generalizes several important problems such as multi-arm bandits, active search and the knapsack problem. We present an algorithm, GP-Select, which utilizes prior knowledge about similarity be- tween items, expressed as a kernel function. GP-Select uses Gaussian process prediction to balance exploration (estimating the unknown value of items) and exploitation (selecting items of high value). We extend GP-Select to be able to discover sets that simultaneously have high utility and are diverse. Our preference for diversity can be specified as an arbitrary monotone submodular function that quantifies the diminishing returns obtained when selecting similar items. Furthermore, we exploit the structure of the model updates to achieve an order of magnitude (up to 40X) speedup in our experiments without resorting to approximations. We provide strong guarantees on the performance of GP-Select and apply it to three real-world case studies of industrial relevance: (1) Refreshing a repository of prices in a Global Distribution System for the travel industry, (2) Identifying diverse, binding-affine peptides in a vaccine de- sign task and (3) Maximizing clicks in a web-scale recommender system by recommending items to users

Planetary wave reanalysis using satellite data

A key motivation to use data assimilation for plane-tary science is in order to recover information about day-to-day atmospheric variability, or ‘weather’. Whilst there is no immediate need for a regular weather forecast in most planetary science, data assimilation offers the prospect of a systematic rea-nalysis of past and present spacecraft data. This is especially valuable when, as is often the case, a planet is being observed from only one or two orbital platforms at any one time and synoptic-scale weather system may translate and change signifi-cantly between satellite passes. Observations are often sparse and incomplete. This leads to problems of aliasing and potential ambiguity in a convention-al data analysis

Investigating the Role of Advection Processes in Improved Martian Dust Assimilation Techniques for ExoMars

Mineral dust is a key component in the atmosphere of Mars, and understanding its properties and behaviour is therefore key for planning and performing future activity on the planet. Data assimilation is a technique for combining observations with an atmospheric model, in this case the LMD-UK Mars General Circulation Model (MGCM). We describe its benefits and previous work in Martian data assimilation, and demonstrate its utility by examining a regional dust event in Mars Year 26 using Thermal Emission Spectrometer (TES) dust optical depth observations. We set out aims to improve upon current dust assimilation techniques, specifically regarding the advection of dust within the assimilation, in preparation for forthcoming high-resolution dust observations from the ExoMars Trace Gas Orbiter (TGO) and its NOMAD spectrometer

A research program to reduce interior noise in general aviation airplanes. Influence of depressurization and damping material on the noise reduction characteristics of flat and curved stiffened panels

Some 20 x 20 aluminum panels were studied in a frequency range from 20 Hz to 5000 Hz. The noise sources used were a swept sine wave generator and a random noise generator. The effect of noise source was found to be negligible. Increasing the pressure differential across the panel gave better noise reduction below the fundamental resonance frequency due to an increase in stiffness. The largest increase occurred in the first 1 psi pressure differential. The curved, stiffened panel exhibited similar behavior, but with a lower increase of low frequency noise reduction. Depressurization on these panels resulted in decreased noise reduction at higher frequencies. The effect of damping tapes on the overall noise reduction values of the test specimens was small away from the resonance frequency. In the mass-law region, a slight and proportional improvement in noise reduction was observed by adding damping material. Adding sound absorbtion material to a panel with damping material beneficially increased noise reduction at high frequencies