Minimum aberration construction results for nonregular two-level fractional factorial designs

Nonregular two-level fractional factorial designs are designs which cannot be specified in terms of a set of defining contrasts. The aliasing properties of nonregular designs can be compared by using a generalisation of the minimum aberration criterion called minimum G2-aberration.Until now, the only nontrivial designs that are known to have minimum G2-aberration are designs for n runs and m n–5 factors. In this paper, a number of construction results are presented which allow minimum G2-aberration designs to be found for many of the cases with n = 16, 24, 32, 48, 64 and 96 runs and m n/2–2 factors.

Wheat archive links long-term population dynamics of pathogens to air pollution

We used the PCR to study the presence of two plant pathogens in archived wheat samples from a long-term experiment started in 1843. The data were used to construct a unique 160-yr time-series of the abundance of Phaeosphaeria nodorum and Mycosphaerella graminicola, two important pathogens of wheat. During the period since 1970, the relative abundance of DNA of these two pathogens in the samples has reflected the relative importance of the two wheat diseases they cause in U.K. disease surveys. Unexpectedly, changes in the ratio of the pathogens over the 160-yr period were very strongly correlated with changes in atmospheric pollution, as measured by SO2 emissions. This finding suggests that long-term, economically important, changes in pathogen populations can be influenced by anthropogenically induced environmental changes.

Some theory for constructing minimum aberration fractional factorial designs

Minimum aberration is the most established criterion for selecting a regular fractional factorial design of maximum resolution. Minimum aberration designs for n runs and n/2 less than or equal to m < n factors have previously been constructed using the novel idea of complementary designs. In this paper, an alternative method of construction is developed by relating the wordlength pattern of designs to the so-called 'confounding between experimental runs'. This allows minimum aberration designs to be constructed for n runs and 5n/16 less than or equal to m less than or equal to n/2 factors as well as for n/2 less than or equal to m < n.

Nitrogen management is essential to prevent tropical oil palm plantations from causing ground-level ozone pollution

More than half the world's rainforest has been lost to agriculture since the Industrial Revolution. Among the most widespread tropical crops is oil palm (Elaeis guineensis): global production now exceeds 35 million tonnes per year. In Malaysia, for example, 13% of land area is now oil palm plantation, compared with 1% in 1974. There are enormous pressures to increase palm oil production for food, domestic products, and, especially, biofuels. Greater use of palm oil for biofuel production is predicated on the assumption that palm oil is an "environmentally friendly'' fuel feedstock. Here we show, using measurements and models, that oil palm plantations in Malaysia directly emit more oxides of nitrogen and volatile organic compounds than rainforest. These compounds lead to the production of ground-level ozone (O-3), an air pollutant that damages human health, plants, and materials, reduces crop productivity, and has effects on the Earth's climate. Our measurements show that, at present, O-3 concentrations do not differ significantly over rainforest and adjacent oil palm plantation landscapes. However, our model calculations predict that if concentrations of oxides of nitrogen in Borneo are allowed to reach those currently seen over rural North America and Europe, ground-level O-3 concentrations will reach 100 parts per billion (10(9)) volume (ppbv) and exceed levels known to be harmful to human health. Our study provides an early warning of the urgent need to develop policies that manage nitrogen emissions if the detrimental effects of palm oil production on air quality and climate are to be avoided.

Ventilation rates in schools and pupil’s performance using computerized assessment tests

Research shows that poor indoor air quality (IAQ) in school buildings can cause a reduction in the students’ performance assessed by short-term computer-based tests; whereas good air quality in classrooms can enhance children's concentration and also teachers’ productivity. Investigation of air quality in classrooms helps us to characterise pollutant levels and implement corrective measures. Outdoor pollution, ventilation equipment, furnishings, and human activities affect IAQ. In school classrooms, the occupancy density is high (1.8–2.4 m2/person) compared to offices (10 m2/person). Ventilation systems expend energy and there is a trend to save energy by reducing ventilation rates. We need to establish the minimum acceptable level of fresh air required for the health of the occupants. This paper describes a project, which will aim to investigate the effect of IAQ and ventilation rates on pupils’ performance and health using psychological tests. The aim is to recommend suitable ventilation rates for classrooms and examine the suitability of the air quality guidelines for classrooms. The air quality, ventilation rates and pupils’ performance in classrooms will be evaluated in parallel measurements. In addition, Visual Analogue Scales will be used to assess subjective perception of the classroom environment and SBS symptoms. Pupil performance will be measured with Computerised Assessment Tests (CAT), and Pen and Paper Performance Tasks while physical parameters of the classroom environment will be recorded using an advanced data logging system. A total number of 20 primary schools in the Reading area are expected to participate in the present investigation, and the pupils participating in this study will be within the age group of 9–11 years. On completion of the project, based on the overall data recommendations for suitable ventilation rates for schools will be formulated.

Ventilation rates in schools

Research shows that poor indoor air quality in school buildings can cause a reduction in the students' performance assessed by short term computer based tests; whereas good air quality in classrooms can enhance children's concentration and also teachers' productivity. Investigation of air quality in classrooms helps us to characterise pollutant levels and implement corrective measures. Outdoor pollution, ventilation equipment, furnishings, and human activities affect indoor air quality. In school classrooms the occupancy density is high (1.8 to 2.4 m(2)/person) compared to offices (10 m(2) /person). Ventilation systems expend energy and there is a trend to save energy by reducing ventilation rates. We need to establish the minimum acceptable level of fresh air required for the health of the occupants. This paper describes a project which will aim to investigate the effect of indoor air quality and ventilation rates on pupils' performance and health using psychological tests. The aim is to recommend suitable ventilation rates for classrooms and examine the suitability of the air quality guidelines for classrooms.

Description of a "Phoenix" phenomenon in the growth of Campylobacter jejuni at temperatures close to the minimum for growth

When Campylobacter jejuni cultures that had been grown in broth at 39degreesC were subcultured into fresh medium at 30degreesC, there was a transient period of growth followed by a decline in viable-cell numbers before growth resumed once more. We propose that this complex behavior is the net effect of the growth of inoculum cells followed by a loss of viability due to oxidative stress and the subsequent emergence of a spontaneously arising mutant population that takes over the culture.

Ventilation rates in schools

Research shows that poor indoor air quality (IAQ) in school buildings can cause a reduction in the students' performance assessed by short-term computer-based tests: whereas good air quality in classrooms can enhance children's concentration and also teachers' productivity. Investigation of air quality in classrooms helps us to characterise pollutant levels and implement corrective measures. Outdoor pollution, ventilation equipment, furnishings, and human activities affect IAQ. In school classrooms, the occupancy density is high (1.8-2.4m(2)/person) compared to offices (10 m(2)/person). Ventilation systems expend energy and there is a trend to save energy by reducing ventilation rates. We need to establish the minimum acceptable level of fresh air required for the health of the occupants. This paper describes a project, which will aim to investigate the effect of IAQ and ventilation rates on pupils' performance and health using psychological tests. The aim is to recommend suitable ventilation rates for classrooms and examine the suitability of the air quality guidelines for classrooms. The air quality, ventilation rates and pupils' performance in classrooms will be evaluated in parallel measurements. In addition, Visual Analogue Scales will be used to assess subjective perception of the classroom environment and SBS symptoms. Pupil performance will be measured with Computerised Assessment Tests (CAT), and Pen and Paper Performance Tasks while physical parameters of the classroom environment will be recorded using an advanced data logging system. A total number of 20 primary schools in the Reading area are expected to participate in the present investigation, and the pupils participating in this study will be within the age group of 9-11 years. On completion of the project, based oil the overall data recommendations for suitable ventilation rates for schools will be formulated. (C) 2006 Elsevier Ltd. All rights reserved.

A knowledge-based evolution strategy for the multi-objective minimum spanning tree problem

A fast Knowledge-based Evolution Strategy, KES, for the multi-objective minimum spanning tree, is presented. The proposed algorithm is validated, for the bi-objective case, with an exhaustive search for small problems (4-10 nodes), and compared with a deterministic algorithm, EPDA and NSGA-II for larger problems (up to 100 nodes) using benchmark hard instances. Experimental results show that KES finds the true Pareto fronts for small instances of the problem and calculates good approximation Pareto sets for larger instances tested. It is shown that the fronts calculated by YES are superior to NSGA-II fronts and almost as good as those established by EPDA. KES is designed to be scalable to multi-objective problems and fast due to its small complexity.

A hybridised evolutionary algorithm for multi-criterion minimum spanning tree problems

A hybridised and Knowledge-based Evolutionary Algorithm (KEA) is applied to the multi-criterion minimum spanning tree problems. Hybridisation is used across its three phases. In the first phase a deterministic single objective optimization algorithm finds the extreme points of the Pareto front. In the second phase a K-best approach finds the first neighbours of the extreme points, which serve as an elitist parent population to an evolutionary algorithm in the third phase. A knowledge-based mutation operator is applied in each generation to reproduce individuals that are at least as good as the unique parent. The advantages of KEA over previous algorithms include its speed (making it applicable to large real-world problems), its scalability to more than two criteria, and its ability to find both the supported and unsupported optimal solutions.