Integrating Multiple Point Statistics with Aerial Geophysical Data to assist Groundwater Flow Models

The process of accounting for heterogeneity has made significant advances in statistical research, primarily in the framework of stochastic analysis and the development of multiple-point statistics (MPS). Among MPS techniques, the direct sampling (DS) method is tested to determine its ability to delineate heterogeneity from aerial magnetics data in a regional sandstone aquifer intruded by low-permeability volcanic dykes in Northern Ireland, UK. The use of two two-dimensional bivariate training images aids in creating spatial probability distributions of heterogeneities of hydrogeological interest, despite relatively ‘noisy’ magnetics data (i.e. including hydrogeologically irrelevant urban noise and regional geologic effects). These distributions are incorporated into a hierarchy system where previously published density function and upscaling methods are applied to derive regional distributions of equivalent hydraulic conductivity tensor K. Several K models, as determined by several stochastic realisations of MPS dyke locations, are computed within groundwater flow models and evaluated by comparing modelled heads with field observations. Results show a significant improvement in model calibration when compared to a simplistic homogeneous and isotropic aquifer model that does not account for the dyke occurrence evidenced by airborne magnetic data. The best model is obtained when normal and reverse polarity dykes are computed separately within MPS simulations and when a probability threshold of 0.7 is applied. The presented stochastic approach also provides improvement when compared to a previously published deterministic anisotropic model based on the unprocessed (i.e. noisy) airborne magnetics. This demonstrates the potential of coupling MPS to airborne geophysical data for regional groundwater modelling.

International inter-school competition to encourage children to walk to school: a mixed methods feasibility study.

Background: Active travel to school can be an important contributor to the total physical activity of children but levels have declined and more novel approaches are required to stimulate this as an habitual behaviour. The aim of this mixed methods study was to investigate the feasibility of an international walk to school competition supported by novel swipecard technology to increase children's walking to/from school. Methods: Children aged 9-13 years old participated in an international walk to school competition to win points for themselves, their school and their country over a 4-week period. Walks to and from school were recorded using swipecard technology and a bespoke website. For each point earned by participants, 1 pence (£0.01) was donated to the charity of the school's choice. The primary outcome was number of walks to/from school objectively recorded using the swipecard tracking system over the intervention period. Other measures included attitudes towards walking collected at baseline and week 4 (post-intervention). A qualitative sub-study involving focus groups with children, parents and teachers provided further insight. Results: A total of 3817 children (mean age 11.5±SD 0.7) from 12 schools in three cities (London and Reading, England and Vancouver, Canada) took part in the intervention, representing a 95% intervention participation rate. Results show a gradual decline in the average number of children walking to and from school over the 4-week period (week 1 mean 29%±SD2.5; week 2 mean 18%±SD3.6; week 3 mean 14%±SD4.0; week 4 mean 12%±SD1.1). Post intervention, 97% of children felt that walking to school helped them stay healthy, feel happy (81%) and stay alert in class (76%). These results are supported by qualitative findings from children, parents and teachers. Key areas for improvement include the need to incorporate strategies for maintenance of behaviour change into the intervention and also to adopt novel methods of data collection to increase follow-up rates. Conclusions: This mixed methods study suggests that an international walk to school competition using innovative technology can be feasibly implemented and offers a novel way of engaging schools and motivating children to walk to school.

Plasma properties and Stokes profiles during the lifetime of a photospheric magnetic bright point

Aims: In this paper we aim to investigate the evolution of plasmaproperties and Stokes parameters in photospheric magnetic bright pointsusing 3D magneto-hydrodynamical simulations and radiative diagnostics ofsolar granulation.

Methods: Simulated time-dependent radiationparameters and plasma properties were investigated throughout theevolution of a bright point. Synthetic Stokes profiles for the FeI630.25 nm line were calculated, which also allowed the evolution of theStokes-I line strength and Stokes-V area and amplitude asymmetries to beinvestigated.

Results: Our results are consistent withtheoretical predictions and published observations describing convectivecollapse, and confirm this as the bright point formation process.Through degradation of the simulated data to match the spatialresolution of SOT, we show that high spatial resolution is crucial forthe detection of changing spectro-polarimetric signatures throughout amagnetic bright point's lifetime. We also show that the signaturedownflow associated with the convective collapse process tends towardszero as the radiation intensity in the bright point peaks, because ofthe magnetic forces present restricting the flow of material in the fluxtube.

Computational scheduling methods for integrating plug-in electric vehicles with power systems: a review

Traditional internal combustion engine vehicles are a major contributor to global greenhouse gas emissions and other air pollutants, such as particulate matter and nitrogen oxides. If the tail pipe point emissions could be managed centrally without reducing the commercial and personal user functionalities, then one of the most attractive solutions for achieving a significant reduction of emissions in the transport sector would be the mass deployment of electric vehicles. Though electric vehicle sales are still hindered by battery performance, cost and a few other technological bottlenecks, focused commercialisation and support from government policies are encouraging large scale electric vehicle adoptions. The mass proliferation of plug-in electric vehicles is likely to bring a significant additional electric load onto the grid creating a highly complex operational problem for power system operators. Electric vehicle batteries also have the ability to act as energy storage points on the distribution system. This double charge and storage impact of many uncontrollable small kW loads, as consumers will want maximum flexibility, on a distribution system which was originally not designed for such operations has the potential to be detrimental to grid balancing. Intelligent scheduling methods if established correctly could smoothly integrate electric vehicles onto the grid. Intelligent scheduling methods will help to avoid cycling of large combustion plants, using expensive fossil fuel peaking plant, match renewable generation to electric vehicle charging and not overload the distribution system causing a reduction in power quality. In this paper, a state-of-the-art review of scheduling methods to integrate plug-in electric vehicles are reviewed, examined and categorised based on their computational techniques. Thus, in addition to various existing approaches covering analytical scheduling, conventional optimisation methods (e.g. linear, non-linear mixed integer programming and dynamic programming), and game theory, meta-heuristic algorithms including genetic algorithm and particle swarm optimisation, are all comprehensively surveyed, offering a systematic reference for grid scheduling considering intelligent electric vehicle integration.

High variability in the dosing of commonly used antibiotics revealed by a Europe-wide point prevalence study: implications for research and dissemination

BACKGROUND: Antibiotic dosing in neonates varies between countries and centres, suggesting suboptimal exposures for some neonates. We aimed to describe variations and factors influencing the variability in the dosing of frequently used antibiotics in European NICUs to help define strategies for improvement.

METHODS: A sub-analysis of the European Study of Neonatal Exposure to Excipients point prevalence study was undertaken. Demographic data of neonates receiving any antibiotic on the study day within one of three two-week periods from January to June 2012, the dose, dosing interval and route of administration of each prescription were recorded. The British National Formulary for Children (BNFC) and Neofax were used as reference sources. Risk factors for deviations exceeding ±25% of the relevant BNFC dosage recommendation were identified by multivariate logistic regression analysis.

RESULTS: In 89 NICUs from 21 countries, 586 antibiotic prescriptions for 342 infants were reported. The twelve most frequently used antibiotics - gentamicin, penicillin G, ampicillin, vancomycin, amikacin, cefotaxime, ceftazidime, meropenem, amoxicillin, metronidazole, teicoplanin and flucloxacillin - covered 92% of systemic prescriptions. Glycopeptide class, GA <32 weeks, 5(th) minute Apgar score <5 and geographical region were associated with deviation from the BNFC dosage recommendation. While the doses of penicillins exceeded recommendations, antibiotics with safety concerns followed (gentamicin) or were dosed below (vancomycin) recommendations.

CONCLUSIONS: The current lack of compliance with existing dosing recommendations for neonates needs to be overcome through the conduct of well-designed clinical trials with a limited number of antibiotics to define pharmacokinetics/pharmacodynamics, efficacy and safety in this population and by efficient dissemination of the results.

Autism in the air: using Point of View Video Priming and Natural Environment Teaching to help children with autism travel by plane

This paper describes a study that used video materials and visits to an airport to prepare children on the autism spectrum for travel by plane. Twenty parents and carers took part in the study with children aged from 3 to 16 years. The authors explain that the methods they used were based on Applied Behaviour Analysis (ABA) research; a video modeling technique called Point-Of-View Video-priming and during visits to an airport they used procedures known as Natural Environment Teaching. The findings suggest that using video and preparing children by taking them through what is likely to happen in the real environment when they travel by plane is effective and the authors suggest these strategies could be used to support children with autism with other experiences they need or would like to engage in such as visits to the dentist or hairdressers and access to leisure centres and other public spaces.

Comparative Study of Different Methods for the Prediction of Drug− Polymer Solubility

In this study, a comparison of different methods to predict drug−polymer solubility was carried out on binary systems consisting of five model drugs (paracetamol, chloramphenicol, celecoxib, indomethacin, and felodipine) and polyvinylpyrrolidone/vinyl acetate copolymers (PVP/VA) of different monomer weight ratios. The drug−polymer solubility at 25 °C was predicted using the Flory−Huggins model, from data obtained at elevated temperature using thermal analysis methods based on the recrystallization of a supersaturated amorphous solid dispersion and two variations of the melting point depression method. These predictions were compared with the solubility in the low molecular weight liquid analogues of the PVP/VA copolymer (N-vinylpyrrolidone and vinyl acetate). The predicted solubilities at 25 °C varied considerably depending on the method used. However, the three thermal analysis methods ranked the predicted solubilities in the same order, except for the felodipine−PVP system. Furthermore, the magnitude of the predicted solubilities from the recrystallization method and melting point depression method correlated well with the estimates based on the solubility in the liquid analogues, which suggests that this method can be used as an initial screening tool if a liquid analogue is available. The learnings of this important comparative study provided general guidance for the selection of the most suitable method(s) for the screening of drug−polymer solubility.

Spitzer infrared spectrograph point source classification in the Small Magellanic Cloud

The Magellanic Clouds are uniquely placed to study the stellar contribution to dust emission. Individual stars can be resolved in these systems even in the mid-infrared, and they are close enough to allow detection of infrared excess caused by dust. We have searched the Spitzer Space Telescope data archive for all Infrared Spectrograph (IRS) staring-mode observations of the Small Magellanic Cloud (SMC) and found that 209 Infrared Array Camera (IRAC) point sources within the footprint of the Surveying the Agents of Galaxy Evolution in the Small Magellanic Cloud (SAGE-SMC) Spitzer Legacy programme were targeted, within a total of 311 staring-mode observations. We classify these point sources using a decision tree method of object classification, based on infrared spectral features, continuum and spectral energy distribution shape, bolometric luminosity, cluster membership and variability information. We find 58 asymptotic giant branch (AGB) stars, 51 young stellar objects, 4 post-AGB objects, 22 red supergiants, 27 stars (of which 23 are dusty OB stars), 24 planetary nebulae (PNe), 10 Wolf-Rayet stars, 3 H II regions, 3 R Coronae Borealis stars, 1 Blue Supergiant and 6 other objects, including 2 foreground AGB stars. We use these classifications to evaluate the success of photometric classification methods reported in the literature.

The Antibiotic Resistance and Prescribing in European Children Project: A Neonatal and Pediatric Antimicrobial Web-based Point Prevalence Survey in 73 Hospitals Worldwide

BACKGROUND: The neonatal and pediatric antimicrobial point prevalence survey (PPS) of the Antibiotic Resistance and Prescribing in European Children project (http://www.arpecproject.eu/) aims to standardize a method for surveillance of antimicrobial use in children and neonates admitted to the hospital within Europe. This article describes the audit criteria used and reports overall country-specific proportions of antimicrobial use. An analytical review presents methodologies on antimicrobial use.

METHODS: A 1-day PPS on antimicrobial use in hospitalized children was organized in September 2011, using a previously validated and standardized method. The survey included all inpatient pediatric and neonatal beds and identified all children receiving an antimicrobial treatment on the day of survey. Mandatory data were age, gender, (birth) weight, underlying diagnosis, antimicrobial agent, dose and indication for treatment. Data were entered through a web-based system for data-entry and reporting, based on the WebPPS program developed for the European Surveillance of Antimicrobial Consumption project.

RESULTS: There were 2760 and 1565 pediatric versus 1154 and 589 neonatal inpatients reported among 50 European (n = 14 countries) and 23 non-European hospitals (n = 9 countries), respectively. Overall, antibiotic pediatric and neonatal use was significantly higher in non-European (43.8%; 95% confidence interval [CI]: 41.3-46.3% and 39.4%; 95% CI: 35.5-43.4%) compared with that in European hospitals (35.4; 95% CI: 33.6-37.2% and 21.8%; 95% CI: 19.4-24.2%). Proportions of antibiotic use were highest in hematology/oncology wards (61.3%; 95% CI: 56.2-66.4%) and pediatric intensive care units (55.8%; 95% CI: 50.3-61.3%).

CONCLUSIONS: An Antibiotic Resistance and Prescribing in European Children standardized web-based method for a 1-day PPS was successfully developed and conducted in 73 hospitals worldwide. It offers a simple, feasible and sustainable way of data collection that can be used globally.

An exploration of men’s experiences of undergoing active surveillance for favourable-risk prostate cancer: A mixed methods study protocol

Background
Prostate cancer is one of the most common male cancers worldwide. Active Surveillance (AS) has been developed to allow men with lower risk disease to postpone or avoid the adverse side effects associated with curative treatments until the disease progresses. Despite the medical benefits of AS, it is reported that living with untreated cancer can create a significant emotional burden for patients.

Methods/design
The aim of this study is to gain insight into the experiences of men eligible to undergo AS for favourable-risk PCa.

This study has a mixed-methods sequential explanatory design consisting of two phases: quantitative followed by qualitative. Phase 1 has a multiple point, prospective, longitudinal exploratory design. Ninety men diagnosed with favourable-risk prostate cancer will be assessed immediately post-diagnosis (baseline) and followed over a period of 12 months, in intervals of 3 month. Ninety age-matched men with no cancer diagnosis will also be recruited using peer nomination and followed up in the same 3 month intervals. Following completion of Phase 1, 10–15 AS participants who have reported both the best and worst psychological functioning will be invited to participate in semi-structured qualitative interviews. Phase 2 will facilitate further exploration of the quantitative results and obtain a richer understanding of participants’ personal interpretations of their illness and psychological wellbeing.

Discussion
To our knowledge, this is the first study to utilise early baseline measures; include a healthy comparison group; calculate sample size through power calculations; and use a mixed methods approach to gain a deeper more holistic insight into the experiences of men diagnosed with favourable-risk prostate cancer.