Carbon reduction in buildings (CaRB) - Understanding the social and technical factors that influence energy use in UK buildings

Attempts to reduce the energy consumed in UK homes have met with limited success. One reason for this is a lack of understanding of how people interact with domestic technology – heating systems, lights, electrical equipment and so forth. Attaining such an understanding is hampered by a chronic shortage of detailed energy use data matched to descriptions of the house, the occupants, the internal conditions and the installed services and appliances. Without such information it is impossible to produce transparent and valid models for understanding and predicting energy use. The Carbon Reduction in Buildings (CaRB) consortium of five UK universities plans to develop socio-technical models of energy use, underpinned by a flow of data from a longitudinal monitoring campaign involving several hundred UK homes. This paper outlines the models proposed, the preliminary monitoring work and the structure of the proposed longitudinal study.

A cluster-based implementation of a fault-tolerant parallel reduction algorithm using swarm-array computing

Recent research in multi-agent systems incorporate fault tolerance concepts. However, the research does not explore the extension and implementation of such ideas for large scale parallel computing systems. The work reported in this paper investigates a swarm array computing approach, namely ‘Intelligent Agents’. In the approach considered a task to be executed on a parallel computing system is decomposed to sub-tasks and mapped onto agents that traverse an abstracted hardware layer. The agents intercommunicate across processors to share information during the event of a predicted core/processor failure and for successfully completing the task. The agents hence contribute towards fault tolerance and towards building reliable systems. The feasibility of the approach is validated by simulations on an FPGA using a multi-agent simulator and implementation of a parallel reduction algorithm on a computer cluster using the Message Passing Interface.

Intrusions in trauma and psychosis: information processing and phenomenology

Background: Intrusions are common symptoms of both posttraumatic stress disorder (PTSD) and schizophrenia. Steel et al (2005) suggest that an information processing style characterized by weak trait contextual integration renders psychotic individuals vulnerable to intrusive experiences. This ‘contextual integration hypothesis’ was tested in individuals reporting anomalous experiences in the absence of a need-for-care. Methods: Twenty-six low schizotypes and twenty-three individuals reporting anomalous experiences were shown a traumatic film with and without a concurrent visuo-spatial task. Participants rated post-traumatic intrusions for frequency and form, and completed self-report measures of information processing style. It was predicted that, due to their weaker trait contextual integration, the anomalous experiences group would (1) exhibit more intrusions following exposure to the trauma-film; (2) display intrusions characterised by more PTSD qualities and (3) show a greater reduction of intrusions with the concurrent visuo-spatial task. Results: As predicted, the anomalous experiences group reported a lower level of trait contextual integration and more intrusions than the low schizotypes, both immediately after watching the film, and during the following seven days. Their post-traumatic intrusive memories were more PTSD-like (more intrusive, vivid and associated with emotion). The visuo-spatial task had no effect on number of intrusions in either group. Conclusions: These findings provide some support for the proposal that weak trait contextual integration underlies the development of intrusions within both PTSD and psychosis.

A comparative review of dimension reduction methods in approximate Bayesian computation

Approximate Bayesian computation (ABC) methods make use of comparisons between simulated and observed summary statistics to overcome the problem of computationally intractable likelihood functions. As the practical implementation of ABC requires computations based on vectors of summary statistics, rather than full data sets, a central question is how to derive low-dimensional summary statistics from the observed data with minimal loss of information. In this article we provide a comprehensive review and comparison of the performance of the principal methods of dimension reduction proposed in the ABC literature. The methods are split into three nonmutually exclusive classes consisting of best subset selection methods, projection techniques and regularization. In addition, we introduce two new methods of dimension reduction. The first is a best subset selection method based on Akaike and Bayesian information criteria, and the second uses ridge regression as a regularization procedure. We illustrate the performance of these dimension reduction techniques through the analysis of three challenging models and data sets.

J-measure based hybrid pruning for complexity reduction in classification rules

Prism is a modular classification rule generation method based on the ‘separate and conquer’ approach that is alternative to the rule induction approach using decision trees also known as ‘divide and conquer’. Prism often achieves a similar level of classification accuracy compared with decision trees, but tends to produce a more compact noise tolerant set of classification rules. As with other classification rule generation methods, a principle problem arising with Prism is that of overfitting due to over-specialised rules. In addition, over-specialised rules increase the associated computational complexity. These problems can be solved by pruning methods. For the Prism method, two pruning algorithms have been introduced recently for reducing overfitting of classification rules - J-pruning and Jmax-pruning. Both algorithms are based on the J-measure, an information theoretic means for quantifying the theoretical information content of a rule. Jmax-pruning attempts to exploit the J-measure to its full potential because J-pruning does not actually achieve this and may even lead to underfitting. A series of experiments have proved that Jmax-pruning may outperform J-pruning in reducing overfitting. However, Jmax-pruning is computationally relatively expensive and may also lead to underfitting. This paper reviews the Prism method and the two existing pruning algorithms above. It also proposes a novel pruning algorithm called Jmid-pruning. The latter is based on the J-measure and it reduces overfitting to a similar level as the other two algorithms but is better in avoiding underfitting and unnecessary computational effort. The authors conduct an experimental study on the performance of the Jmid-pruning algorithm in terms of classification accuracy and computational efficiency. The algorithm is also evaluated comparatively with the J-pruning and Jmax-pruning algorithms.

Protocol for a feasibility study of a self help cognitive behavioural therapy resource for the reduction of dental anxiety in young people

Background Childhood dental anxiety is very common, with 10–20 % of children and young people reporting high levels of dental anxiety. It is distressing and has a negative impact on the quality of life of young people and their parents as well as being associated with poor oral health. Affected individuals may develop a lifelong reliance on general anaesthetic or sedation for necessary dental treatment thus requiring the support of specialist dental services. Children and young people with dental anxiety therefore require additional clinical time and can be costly to treat in the long term. The reduction of dental anxiety through the use of effective psychological techniques is, therefore, of high importance. However, there is a lack of high-quality research investigating the impact of cognitive behavioural therapy (CBT) approaches when applied to young people’s dental anxiety. Methods/design The first part of the study will develop a profile of dentally anxious young people using a prospective questionnaire sent to a consecutive sample of 100 young people referred to the Paediatric Dentistry Department, Charles Clifford Dental Hospital, in Sheffield. The second part will involve interviewing a purposive sample of 15–20 dental team members on their perceptions of a CBT self-help resource for dental anxiety, their opinions on whether they might use such a resource with patients, and their willingness to recruit participants to a future randomised controlled trial (RCT) to evaluate the resource. The third part of the study will investigate the most appropriate outcome measures to include in a trial, the acceptability of the resource, and retention and completion rates of treatment with a sample of 60 dentally anxious young people using the CBT resource. Discussion This study will provide information on the profile of dentally anxious young people who could potentially be helped by a guided self-help CBT resource. It will gain the perceptions of dental care team members of guided self-help CBT for dental anxiety in young people and their willingness to recruit participants to a trial. Acceptability of the resource to participants and retention and completion rates will also be investigated to inform a future RCT.

Outcome Analysis of Immediate and Delayed Conservative Breast Surgery Reconstruction With Mastopexy and Reduction Mammaplasty Techniques

Background: Bilateral mammaplasty or mastopexy is frequently used for oncoplastic objectives. However, little information has been available regarding outcome following immediate and delayed reconstruction. Method: Patients were divided into Group I (immediate reconstruction) and Group II (delayed reconstruction). Retrospective review was performed to compare complications, length of hospital stay, revision surgeries, and satisfaction. The associations between the complications with potential risk factors (timing, age, body mass index, smoking, and comorbid medical conditions) were analyzed. Results: There were a total of 144 patients with a mean follow-up of 47 months. Of the 106 patients in Group I, complications occurred in 24 (22.6%), skin necrosis was observed in 7.5%, fat necrosis in 5.6%, and 6.6% patients developed local recurrence. Mean period of hospitalization was 1.89 days. Of the 38 patients of the Group II, complications occurred in 12 (31.5%), skin necrosis was observed in 7 (18.4%), fat necrosis in 4 (10.5%), and 5.2% patients developed local recurrence. Mean period of hospitalization was 1.35 days. Increased length of hospital stay greater than 1 day (P < 0.001) and the number of revision surgeries (P = 0.043) were associated with the timing of the reconstruction. In univariate analysis, no difference between groups was found with respect to complication incidence (P = 0.275); however, after adjusting for other risk factors, the probability of complications tend to be higher for Group II (OR = 2.65; 95% confidence interval - 1.01-7.00; P = 0.049). Conclusions: On the basis of the results of our study, the probability of complications tends to be higher for delayed reconstructions, and it is demonstrated that obesity and smoking are risk factors for complications. Ultimately, these data may facilitate the provision of individualized risk information for shared medical decision-making.

A Learning Function for Parameter Reduction in Spiking Neural Networks with Radial Basis Function

Spiking neural networks - networks that encode information in the timing of spikes - are arising as a new approach in the artificial neural networks paradigm, emergent from cognitive science. One of these new models is the pulsed neural network with radial basis function, a network able to store information in the axonal propagation delay of neurons. Learning algorithms have been proposed to this model looking for mapping input pulses into output pulses. Recently, a new method was proposed to encode constant data into a temporal sequence of spikes, stimulating deeper studies in order to establish abilities and frontiers of this new approach. However, a well known problem of this kind of network is the high number of free parameters - more that 15 - to be properly configured or tuned in order to allow network convergence. This work presents for the first time a new learning function for this network training that allow the automatic configuration of one of the key network parameters: the synaptic weight decreasing factor.

Temporal analysis of the reduction in gas emission in areas of mechanically-harvested sugarcane using satellite imagery

The primary objective of this study was to estimate the amount of gas not emitted into the air in areas cultivated with sugarcane (Saccharum officinarum) that were mechanically harvested. Satellite images CBERS-2/CCD, from 08-13-2004, 08-14-2005, 08-15-2006 and 08-16-2007, of northwestern São Paulo State were processed using the Geographic Information System (GIS)-IDRISI 15.0. Areas of interest (the mechanically-harvested sugarcane fields) were identified and quantified based on the spectral response of the bands studied. Based on these data, the amount of gas that was not emitted was evaluated, according to the estimate equation proposed by the Intergovernmental Panel on Climate Change (IPCC). The results of 396.65 km(2) (5.91% for 2004); 447.56 km(2) (6.67% for 2005); 511.54 km(2) (7.62% in 2006); and 474.60 km(2) (7.07% for 2007), calculated from a total area of 6,710.89 km(2) with sugarcane, showed a significant increase of mechanical harvesting in the study area and a reduction of gas emissions of more than 300,000 t yr(-1).

Dimensional reduction of the ABJM model

We dimensionally reduce the ABJM model, obtaining a two-dimensional theory that can be thought of as a 'master action'. This encodes information about both T- and S-duality, i.e. describes fundamental (F1) and D-strings (D1) in 9 and 10 dimensions. The Higgsed theory at large VEV, (v) over tilde, and large k yields D1-brane actions in 9d and 10d, depending on which auxiliary fields are integrated out. For N = 1 there is a map to a Green-Schwarz string wrapping a nontrivial circle in C(4)/Z(k).

Information technology for development of small and medium-sized exporters in Latin America and East Asia

Includes bibliography

Corn yield with reduction of insecticidal sprayings against fall armyworm Spodoptera frugiperda (Lepidoptera: Noctuidae)

The ideal time is more important than amount of insecticidal spraying to adequate the control of Spodoptera frugiperda J.E. Smith (Lepidoptera: Noctuidae) in corn. This study aimed to evaluate lufenuron sequential sprayings effect and its rotation with other active ingredients on the population, damage caused by S. frugiperda and the impact on corn yield. The experiment was carried out in the field with six treatments: (1) one lufenuron spraying, (2) two lufenuron sprayings, (3) three lufenuron sprayings (4) four lufenuron sprayings, (5) sprayings with spinosad, lufenuron, thiamethoxam+lambdacyhalothrin and deltamethrin (in sequence, at ten days intervals) (6) control treatment. Sprayings started twenty days after the seedling had emerged and then every ten days for a maximum of four sprays. Both caterpillar population (20.9-21.7 larvae/plot) and index of damage (1.2-1.7) observed in corn plants were significantly lower in treated plots compared to control (untreated) (31.7 larvae/plot and index of damage 2.7), regardless of spraying amount. The results showed that multiple insecticide applications to control S. frugiperda do not guarantee higher yields in corn, ranging from 6375.2 to 7650.1 kg ha -1. Only one spraying of lufenuron was enough to prevent significant reduction in corn yield (6749.9 kg ha -1). © 2012 Asian Network for Scientific Information.

Reduction of infant mortality in Latin America and the Caribbean: uneven progress requiring a variety of responses

Infant mortality has unquestionably declined throughout Latin America over the last decade, even under conditions of low and unstable economic growth and a meagre overall reduction of poverty in the region. The declines in infant mortality vary from one country to another. The persistence of high infant mortality rates is related to low income, teenage pregnancy and lack of access to basic services, as well as to the lack of appropriate health care infrastructure. At the same time, both the rural population as a whole, and the indigenous and Afro-descendent population in particular, has fallen markedly behind, with overall infant mortality rates much higher than among the rest of the population. Moreover, the cause and incidence of death in this age group have been changing according with the changes in neonatal and post-neonatal deaths. Our editorial line-up has created space for opinions from adolescents and youth, as well as from policy experts on the problem, its causes, and approaches to dealing with infant mortality. We also offer succinct information on a broad range of programmes—utilizing various interventions—in different countries of the region regarding maternal and infant care, in an attempt to bring about a reduction in mortality.

Development strategies for the information and communications technology sector in the Caribbean: A global perspective

This occasional paper examines the experiences of three leading global centres of the ICT industry – India, Silicon Valley, and Estonia – to reflect on how the lessons of these models can be applied to the context of countries in the Caribbean region.Several sectors of the technology industry are considered in relation to the suitability for their establishment in the Caribbean. Animation is an area that is showing encouraging signs of development in several countries, and which offers some promise to provide a significant source of employment in the region. However, the global market for animation production is likely to become increasingly competitive, as improved technology has reduced barriers to entry into the industry not only in the Caribbean, but around the world. The region’s animation industry will need to move swiftly up the value chain if it is to avoid the downsides of being caught in an increasingly commoditized market. Mobile applications development has also been widely a heralded industry for the Caribbean. However, the market for consumer-oriented smartphone applications has matured very quickly, and is now a very difficult sector in which to compete. Caribbean mobile developers would be better served to focus on creating applications to suit the needs of regional industries and governments, rather than attempting to gain notice in over-saturated consumer marketplaces such as the iTunes App Store and Google Play. Another sector considered for the Caribbean is “big data” analysis. This area holds significant potential for growth in coming years, but the Caribbean, which is generally considered to be a datapoor region, currently lacks a sufficient base of local customers to form a competitive foundation for such an industry. While a Caribbean big data industry could plausibly be oriented toward outsourcing, that orientation would limit positive externalities from the sector, and benefits from its establishment would largely accrue only to a relatively small number of direct participants in the industry. Instead, development in the big data sector should be twinned with the development of products to build a regional customer base for the industry. The region has pressing needs in areas such as disaster risk reduction, water resource management, and support for agricultural production. Development of big data solutions – and other technology products – to address areas such as these could help to establish niche industries that both support the needs of local populations, and provide viable opportunities for the export of higher-value products and services to regions of the world with similar needs.

EVALUATION OF EUCALYPTUS KRAFT PULP LIGNIN THROUGH THE NITROBENZENE OXIDATION, COPPER OXIDE REDUCTION AND ACIDOLYSIS TECHNIQUES

This study aimed to evaluate the sensitiveness of the information obtained for the residual lignin from Eucalyptus grandis kraft pulps analyzed through the nitrobenzene oxidation, copper oxide (CuO) reduction and acidolysis techniques. The chips were cooked, resulting pulps of kappa number 14,5 and 16,9, respectively. Both lignins' pulps were evaluated through three methods (nitrobenzene oxidation, copper oxide oxidation and acidolysis). Then, they were subjected to an oxygen delignification stage. The 16,9 kappa number pulp resulted in higher levels of non-condensed lignin structures by the acidolysis method, higher syringyl/vanillin ratios (S/V) by the nitrobenzene and copper oxide methods and better performance in the oxygen delignification stage. The different methods allowed to differ the residual lignin pulps with kappa number 14,5 and 16,9, and the nitrobenzene oxidation method showed the highest sensitiveness in this study results.