Dynamic simulation for closed loops in heating systems with decision-making support

Nowadays utilising the proper HVAC system is essential both in extreme weather conditions and dense buildings design. Hydraulic loops are the most common parts in all air conditioning systems. This article aims to investigate the performance of different hydraulic loop arrangements in variable flow systems. Technical, economic and environmental assessments have been considered in this process. A dynamic system simulation is generated to evaluate the system performance and an economic evaluation is conducted by whole life cost assessment. Moreover, environmental impacts have been studied by considering the whole life energy consumption, CO2 emission, the embodied energy and embodied CO2 of the system components. Finally, decision-making in choosing the most suitable hydraulic system among five well-known alternatives has been proposed.

A proposal for a new scenario framework to support research and assessment in different climate research communities

In this paper, we propose a scenario framework that could provide a scenario “thread” through the different climate research communities (climate change – vulnerability, impact, and adaptation (VIA) and mitigation) in order to provide assessment of mitigation and adaptation strategies and other VIA challenges. The scenario framework is organised around a matrix with two main axes: radiative forcing levels and socio-economic conditions. The radiative forcing levels (and the associated climate signal) are described by the new Representative Concentration Pathways. The second axis, socio-economic developments, comprises elements that affect the capacity for mitigation and adaptation, as well as the exposure to climate impacts. The proposed scenarios derived from this framework are limited in number, allow for comparison across various mitigation and adaptation levels, address a range of vulnerability characteristics, provide information across climate forcing and vulnerability states and span a full century time scale. Assessments based on the proposed scenario framework would strengthen cooperation between integrated-assessment modelers, climate modelers and vulnerability, impact and adaptation researchers, and most importantly, facilitate the development of more consistent and comparable research within and across communities.

Secondary structure prediction with support vector machines

Motivation: A new method that uses support vector machines (SVMs) to predict protein secondary structure is described and evaluated. The study is designed to develop a reliable prediction method using an alternative technique and to investigate the applicability of SVMs to this type of bioinformatics problem. Methods: Binary SVMs are trained to discriminate between two structural classes. The binary classifiers are combined in several ways to predict multi-class secondary structure. Results: The average three-state prediction accuracy per protein (Q3) is estimated by cross-validation to be 77.07 ± 0.26% with a segment overlap (Sov) score of 73.32 ± 0.39%. The SVM performs similarly to the 'state-of-the-art' PSIPRED prediction method on a non-homologous test set of 121 proteins despite being trained on substantially fewer examples. A simple consensus of the SVM, PSIPRED and PROFsec achieves significantly higher prediction accuracy than the individual methods. Availability: The SVM classifier is available from the authors. Work is in progress to make the method available on-line and to integrate the SVM predictions into the PSIPRED server.

Modelling of Johne's disease control options in beef cattle: a decision support approach

Johne's disease in cattle is a contagious wasting disease caused by Mycobacterium avium subspecies paratuberculosis (MAP). Johne's infection is characterised by a long subclinical phase and can therefore go undetected for long periods of time during which substantial production losses can occur. The protracted nature of Johne's infection therefore presents a challenge for both veterinarians and farmers when discussing control options due to a paucity of information and limited test performance when screening for the disease. The objectives were to model Johne's control decisions in suckler beef cattle using a decision support approach, thus implying equal focus on ‘end user’ (veterinarian) participation whilst still focusing on the technical disease modelling aspects during the decision support model development. The model shows how Johne's disease is likely to affect a herd over time both in terms of physical and financial impacts. In addition, the model simulates the effect on production from two different Johne's control strategies; herd management measures and test and cull measures. The article also provides and discusses results from a sensitivity analysis to assess the effects on production from improving the currently available test performance. Output from running the model shows that a combination of management improvements to reduce routes of infection and testing and culling to remove infected and infectious animals is likely to be the least-cost control strategy.

Parkinson’s Disease tremor classification – a comparison between Support Vector Machines and neural networks

Deep Brain Stimulation has been used in the study of and for treating Parkinson’s Disease (PD) tremor symptoms since the 1980s. In the research reported here we have carried out a comparative analysis to classify tremor onset based on intraoperative microelectrode recordings of a PD patient’s brain Local Field Potential (LFP) signals. In particular, we compared the performance of a Support Vector Machine (SVM) with two well known artificial neural network classifiers, namely a Multiple Layer Perceptron (MLP) and a Radial Basis Function Network (RBN). The results show that in this study, using specifically PD data, the SVM provided an overall better classification rate achieving an accuracy of 81% recognition.

Children with Special Educational Needs as film makers: Using digital video to support Understandings of Narrative

The literature has identified issues around transitions among phases for all pupils (Cocklin, 1999) including pupils with special educational needs (SEN) (Morgan 1999, Maras and Aveling 2006). These issues include pupils’ uncertainties and worries about building size and spatial orientation, exposure to a range of teaching styles, relationships with peers and older pupils as well as parents’ difficulties in establishing effective communications with prospective secondary schools. Research has also identified that interventions to facilitate these educational transitions should consider managerial support, social and personal familiarisation with the new setting as well as personalised learning strategies (BECTA 2004). However, the role that digital technologies can play in supporting these strategies or facilitating the role of the professionals such as SENCos and heads of departments involved in supporting effective transitions for pupils with SEN has not been widely discussed. Uses of ICT include passing references of student-produced media presentations (Higgins 1993) and use of photographs of activities attached to a timetable to support familiarisation with the secondary curriculum for pupils with autism (Cumine et al. 1998).

Nonlinear set-membership estimation: a support vector machine approach

In this paper a support vector machine (SVM) approach for characterizing the feasible parameter set (FPS) in non-linear set-membership estimation problems is presented. It iteratively solves a regression problem from which an approximation of the boundary of the FPS can be determined. To guarantee convergence to the boundary the procedure includes a no-derivative line search and for an appropriate coverage of points on the FPS boundary it is suggested to start with a sequential box pavement procedure. The SVM approach is illustrated on a simple sine and exponential model with two parameters and an agro-forestry simulation model.

Top down influence on visuo-tactile interaction modulates neural oscillatory responses

Multisensory integration involves bottom-up as well as top-down processes. We investigated the influences of top-down control on the neural responses to multisensory stimulation using EEG recording and time-frequency analyses. Participants were stimulated at the index or thumb of the left hand, using tactile vibrators mounted on a foam cube. Simultaneously they received a visual distractor from a light emitting diode adjacent to the active vibrator (spatially congruent trial) or adjacent to the inactive vibrator (spatially incongruent trial). The task was to respond to the elevation of the tactile stimulus (upper or lower), while ignoring the simultaneous visual distractor. To manipulate top-down control on this multisensory stimulation, the proportion of spatially congruent (vs. incongruent) trials was changed across blocks. Our results reveal that the behavioral cost of responding to incongruent than congruent trials (i.e., the crossmodal congruency effect) was modulated by the proportion of congruent trials. Most importantly, the EEG gamma band response and the gamma-theta coupling were also affected by this modulation of top-down control, whereas the late theta band response related to the congruency effect was not. These findings suggest that gamma band response is more than a marker of multisensory binding, being also sensitive to the correspondence between expected and actual multisensory stimulation. By contrast, theta band response was affected by congruency but appears to be largely immune to stimulation expectancy.

Support for global climate reorganization during the "Medieval Climate Anomaly"

Widely distributed proxy records indicate that the Medieval Climate Anomaly (MCA; *900–1350 AD) was characterized by coherent shifts in large-scale Northern Hemisphere atmospheric circulation patterns. Although cooler sea surface temperatures in the central and eastern equatorial Pacific can explain some aspects of medieval circulation changes, they are not sufficient to account for other notable features, including widespread aridity through the Eurasian sub-tropics, stronger winter westerlies across the North Atlantic and Western Europe, and shifts in monsoon rainfall patterns across Africa and South Asia. We present results from a full-physics coupled climate model showing that a slight warming of the tropical Indian and western Pacific Oceans relative to the other tropical ocean basins can induce a broad range of the medieval circulation and climate changes indicated by proxy data, including many of those not explained by a cooler tropical Pacific alone. Important aspects of the results resemble those from previous simulations examining the climatic response to the rapid Indian Ocean warming during the late twentieth century, and to results from climate warming simulations—especially in indicating an expansion of the Northern Hemisphere Hadley circulation. Notably, the pattern of tropical Indo-Pacific sea surface temperature (SST) change responsible for producing the proxy-model similarity in our results agrees well with MCA-LIA SST differences obtained in a recent proxy-based climate field reconstruction. Though much remains unclear, our results indicate that the MCA was characterized by an enhanced zonal Indo-Pacific SST gradient with resulting changes in Northern Hemisphere tropical and extra-tropical circulation patterns and hydroclimate regimes, linkages that may explain the coherent regional climate shifts indicated by proxy records from across the planet. The findings provide new perspectives on the nature and possible causes of the MCA—a remarkable, yet incompletely understood episode of Late Holocene climatic change.

Developing consensus on hospital prescribing indicators of potential harms amenable to decision support

Aim: To develop a list of prescribing indicators specific for the hospital setting that would facilitate the prospective collection of high severity and/or high frequency prescribing errors, which are also amenable to electronic clinical decision support (CDS). Method: A three-stage consensus technique (electronic Delphi) was carried out with 20 expert pharmacists and physicians across England. Participants were asked to score prescribing errors using a 5-point Likert scale for their likelihood of occurrence and the severity of the most likely outcome. These were combined to produce risk scores, from which median scores were calculated for each indicator across the participants in the study. The degree of consensus between the participants was defined as the proportion that gave a risk score in the same category as the median. Indicators were included if a consensus of 80% or more was achieved. Results: A total of 80 prescribing errors were identified by consensus as being high or extreme risk. The most common drug classes named within the indicators were antibiotics (n=13), antidepressants (n=8), nonsteroidal anti-inflammatory drugs (n=6), and opioid analgesics (n=6).The most frequent error type identified as high or extreme risk were those classified as clinical contraindications (n=29/80). Conclusion: 80 high risk prescribing errors in the hospital setting have been identified by an expert panel. These indicators can serve as the basis for a standardised, validated tool for the collection of data in both paperbased and electronic prescribing processes, as well as to assess the impact of electronic decision support implementation or development.

Ozone database in support of CMIP5 simulations: results and corresponding radiative forcing

A continuous tropospheric and stratospheric vertically resolved ozone time series, from 1850 to 2099, has been generated to be used as forcing in global climate models that do not include interactive chemistry. A multiple linear regression analysis of SAGE I+II satellite observations and polar ozonesonde measurements is used for the stratospheric zonal mean dataset during the well-observed period from 1979 to 2009. In addition to terms describing the mean annual cycle, the regression includes terms representing equivalent effective stratospheric chlorine (EESC) and the 11-yr solar cycle variability. The EESC regression fit coefficients, together with pre-1979 EESC values, are used to extrapolate the stratospheric ozone time series backward to 1850. While a similar procedure could be used to extrapolate into the future, coupled chemistry climate model (CCM) simulations indicate that future stratospheric ozone abundances are likely to be significantly affected by climate change, and capturing such effects through a regression model approach is not feasible. Therefore, the stratospheric ozone dataset is extended into the future (merged in 2009) with multimodel mean projections from 13 CCMs that performed a simulation until 2099 under the SRES (Special Report on Emission Scenarios) A1B greenhouse gas scenario and the A1 adjusted halogen scenario in the second round of the Chemistry-Climate Model Validation (CCMVal-2) Activity. The stratospheric zonal mean ozone time series is merged with a three-dimensional tropospheric data set extracted from simulations of the past by two CCMs (CAM3.5 and GISSPUCCINI)and of the future by one CCM (CAM3.5). The future tropospheric ozone time series continues the historical CAM3.5 simulation until 2099 following the four different Representative Concentration Pathways (RCPs). Generally good agreement is found between the historical segment of the ozone database and satellite observations, although it should be noted that total column ozone is overestimated in the southern polar latitudes during spring and tropospheric column ozone is slightly underestimated. Vertical profiles of tropospheric ozone are broadly consistent with ozonesondes and in-situ measurements, with some deviations in regions of biomass burning. The tropospheric ozone radiative forcing (RF) from the 1850s to the 2000s is 0.23Wm−2, lower than previous results. The lower value is mainly due to (i) a smaller increase in biomass burning emissions; (ii) a larger influence of stratospheric ozone depletion on upper tropospheric ozone at high southern latitudes; and possibly (iii) a larger influence of clouds (which act to reduce the net forcing) compared to previous radiative forcing calculations. Over the same period, decreases in stratospheric ozone, mainly at high latitudes, produce a RF of −0.08Wm−2, which is more negative than the central Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) value of −0.05Wm−2, but which is within the stated range of −0.15 to +0.05Wm−2. The more negative value is explained by the fact that the regression model simulates significant ozone depletion prior to 1979, in line with the increase in EESC and as confirmed by CCMs, while the AR4 assumed no change in stratospheric RF prior to 1979. A negative RF of similar magnitude persists into the future, although its location shifts from high latitudes to the tropics. This shift is due to increases in polar stratospheric ozone, but decreases in tropical lower stratospheric ozone, related to a strengthening of the Brewer-Dobson circulation, particularly through the latter half of the 21st century. Differences in trends in tropospheric ozone among the four RCPs are mainly driven by different methane concentrations, resulting in a range of tropospheric ozone RFs between 0.4 and 0.1Wm−2 by 2100. The ozone dataset described here has been released for the Coupled Model Intercomparison Project (CMIP5) model simulations in netCDF Climate and Forecast (CF) Metadata Convention at the PCMDI website (http://cmip-pcmdi.llnl.gov/).

A study of the microstructure and condition of thin sheets of painting support ivory using SEM and ESEM

This paper outlines a study of the microstructure of thin sheets of ivory used as a painting support for portrait miniatures. Warping of the ivory support is one of the main problems commonly found in portrait miniatures from the late eighteenth century and early nineteenth century. Portrait miniatures from this period are painted on very thin sheets of ivory that are often only 0.2 mm in thickness. Warping can lead to cracking of the ivory and can also accentuate flaking of the paint layer. The problem of warping in ivory has thus been of long-term interest to conservators who deal with portrait miniatures, including those at the Victoria and Albert (V&A) Museum. The causes of warping are complex. However, it should be noted that artists normally stuck the thin ivory sheets onto paper or card before commencing the painting. The possible causes of warping therefore are thought to relate to the differential reactions of the ivory/adhesive/paper or card layers to changes in relative humidity (RH). It is well known that ivory is hygroscopic and anisotropic.1 However, only a few scientific studies have been carried out related to this subject and systematic analyses of the morphological and microstructural changes due to changes in RH or moisture in such thin sheets of ivory have yet to be investigated.