Robust parameter settings of evolutionary algorithms for the optimisation of agricultural systems models

Numerical optimisation methods are being more commonly applied to agricultural systems models, to identify the most profitable management strategies. The available optimisation algorithms are reviewed and compared, with literature and our studies identifying evolutionary algorithms (including genetic algorithms) as superior in this regard to simulated annealing, tabu search, hill-climbing, and direct-search methods. Results of a complex beef property optimisation, using a real-value genetic algorithm, are presented. The relative contributions of the range of operational options and parameters of this method are discussed, and general recommendations listed to assist practitioners applying evolutionary algorithms to the solution of agricultural systems. (C) 2001 Elsevier Science Ltd. All rights reserved.

Dengue virus binding to human leukocyte cell lines: receptor usage differs between cell types and virus strains

Monocyte macrophages (M phi) are thought to be the principal target cells for the dengue viruses (DV), the cause of dengue fever and hemorrhagic fever. Cell attachment is mediated by the virus envelope (E) protein, but the host-cell receptors remain elusive. Currently, candidate receptor molecules include proteins, Fc receptors, glycosaminoglycans (GAGs) and lipopolysaccharide binding CD14-associated molecules. Here, we show that in addition to M phi, cells of the T- and B-cell lineages, and including cells lacking GAGs, can bind and become infected with DV. The level of virus binding varied widely between cell lines and, notably, between virus strains within a DV serotype. The latter difference may be ascribable to one or more amino acid differences in domain II of the E protein. Heparin had no significant effect on DV binding, while heparinase treatment of cells in all cases increased DV binding, further supporting the contention that GAGs are not required for DV binding and infection of human cells. In contrast to a recent report, we found that lipopolysaccharide (LPS) had either no effect or enhanced DV binding to, and infection of various human leukocyte cell lines, while in all virus-cell combinations, depletion of Ca2+/Mg2+ enhanced DV binding. This argues against involvement of beta (2) integrins in virus-host cell interactions, a conclusion in accord with the demonstration of three virus binding membrane proteins of < 75 kDa. Collectively, the results of this study question the purported exclusive importance of the E protein domain III in DV binding to host cells and point to a far more complex interaction between various target cells and, notably, individual DV strains. (C) 2001 Elsevier Science B.V. All rights reserved.

Sludge population optimisation: a new dimension for the control of biological wastewater treatment systems

The activated sludge comprises a complex microbiological community. The structure (what types of microorganisms are present) and function (what can the organisms do and at what rates) of this community are determined by external physico -chemical features and by the influent to the sewage treatment plant. The external features we can manipulate but rarely the influent. Conventional control and operational strategies optimise activated sludge processes more as a chemical system than as a biological one. While optimising the process in a short time period, these strategies may deteriorate the long-term performance of the process due to their potentially adverse impact on the microbial properties. Through briefly reviewing the evidence available in the literature that plant design and operation affect both the structure and function of the microbial community in activated sludge, we propose to add sludge population optimisation as a new dimension to the control of biological wastewater treatment systems. We stress that optimising the microbial community structure and property should be an explicit aim for the design and operation of a treatment plant. The major limitations to sludge population optimisation revolve around inadequate microbiological data, specifically community structure, function and kinetic data. However, molecular microbiological methods that strive to provide that data are being developed rapidly. The combination of these methods with the conventional approaches for kinetic study is briefly discussed. The most pressing research questions pertaining to sludge population optimisation are outlined. (C) 2002 Elsevier Science Ltd. All rights reserved.

Control of nitrate recirculation flow in predenitrification systems

The control of the nitrate recirculation flow in a predenitrification system is addressed. An elementary mass balance analysis on the utilisation efficiency of the influent biodegradable COD (bCOD) for nitrate removal indicates that the control problem can be broken down into two parts: maintaining the anoxic zone anoxic (i.e. nitrate is present throughout the anoxic zone) and maximising the usage of influent soluble bCOD for denitrification. Simulation studies using the Simulation Benchmark developed in the European COST program show that both objectives can be achieved by maintaining the nitrate concentration at the outlet of the anoxic zone at around 2 mgN/L. This setpoint appears to be robust towards variations in the influent characteristics and sludge kinetics.

Codon usage bias and A+T content variation in human papillomavirus genomes

We analyzed the codon usage bias of eight open reading frames (ORFs) across up to 79 human papillomavirus (HPV) genotypes from three distinct phylogenetic groups. All eight ORFs across HPV genotypes show a strong codon usage bias, amongst degenerately encoded amino acids, toward 18 codons mainly with T at the 3rd position. For all 18 degenerately encoded amino acids, codon preferences amongst human and animal PV ORFs are significantly different from those averaged across mammalian genes. Across the HPV types, the L2 ORFs show the highest codon usage bias (73.2 +/- 1.6% and the E4 ORFs the lowest (51.1 +/- 0.5%), reflecting as similar bias in codon 3rd position A + T content (L2: 76.1 +/- 4.2%; E4: 58.6 +/- 4.5%). The E4 ORF, uniquely amongst the HPV ORFs, is G + C rich, while the other ORFs are A + T rich. Codon usage bias correlates positively with A + T content at the codon 3rd position in the E2, E6, L1 and L2 ORFs, but negatively in the E4 ORFs. A general conservation of preferred codon usage across human and non-human PV genotypes whether they originate from a same supergroup or not, together with observed difference between the preferred codon usage for HPV ORFs and for genes of the cells they infect, suggests that specific codon usage bias and A + T content variation may somehow increase the replicational fitness of HPVs in mammalian epithelial cells, and have practical implications for gene therapy of HPV infection. (C) 2003 Elsevier B.V. All rights reserved.

Learning management systems usage on higher education institutions

Learning Management Systems (LMS) are used all over Higher Education Institutions (HEI) and the need to know and understand its adoption and usage arises. However, there is a lack of information about how LMSs are being used, which are the most adopted, whether there is a country adoption standard and which countries use more LMSs. A research team is developing a project that tries to fill this lack of information and provide the needed answers. With this purpose, on a first phase, it a survey was taken place. The results of this survey are presented in this paper. Another purpose of this paper is to disseminate the ongoing project.

An architecture for an effective usage of data mining in business intelligence systems

Business Intelligence (BI) is one emergent area of the Decision Support Systems (DSS) discipline. Over the last years, the evolution in this area has been considerable. Similarly, in the last years, there has been a huge growth and consolidation of the Data Mining (DM) field. DM is being used with success in BI systems, but a truly DM integration with BI is lacking. Therefore, a lack of an effective usage of DM in BI can be found in some BI systems. An architecture that pretends to conduct to an effective usage of DM in BI is presented.

Probabilistic linkage in household survey on hospital care usage

OBJECTIVE: To evaluate the potential advantages and limitations of the use of the Brazilian hospital admission authorization forms database and the probabilistic record linkage methodology for the validation of reported utilization of hospital care services in household surveys. METHODS: A total of 2,288 households interviews were conducted in the county of Duque de Caxias, Brazil. Information on the occurrence of at least one hospital admission in the year preceding the interview was obtained from a total of 10,733 household members. The 130 records of household members who reported at least one hospital admission in a public hospital were linked to a hospital database with 801,587 records, using an automatic probabilistic approach combined with an extensive clerical review. RESULTS: Seventy-four (57%) of the 130 household members were identified in the hospital database. Yet only 60 subjects (46%) showed a record of hospitalization in the hospital database in the study period. Hospital admissions due to a surgery procedure were significantly more likely to have been identified in the hospital database. The low level of concordance seen in the study can be explained by the following factors: errors in the linkage process; a telescoping effect; and an incomplete record in the hospital database. CONCLUSIONS: The use of hospital administrative databases and probabilistic linkage methodology may represent a methodological alternative for the validation of reported utilization of health care services, but some strategies should be employed in order to minimize the problems related to the use of this methodology in non-ideal conditions. Ideally, a single identifier, such as a personal health insurance number, and the universal coverage of the database would be desirable.

Analysis of polycyclic aromatic hydrocarbons in fish: optimisation and validation of microwave-assisted extraction

An accurate and sensitive method for determination of 18 polycyclic aromatic hydrocarbons (PAHs) (16 PAHs considered by USEPA as priority pollutants, dibenzo[a,l]pyrene and benzo[j]fluoranthene) in fish samples was validated. Analysis was performed by microwave-assisted extraction and liquid chromatography with photodiode array and fluorescence detection. Response surface methodology was used to find the optimal extraction parameters. Validation of the overall methodology was performed by spiking assays at four levels and using SRM 2977. Quantification limits ranging from 0.15–27.16 ng/g wet weight were obtained. The established method was applied in edible tissues of three commonly consumed and commercially valuable fish species (sardine, chub mackerel and horse mackerel) originated from Atlantic Ocean. Variable levels of naphthalene (1.03–2.95 ng/g wet weight), fluorene (0.34–1.09 ng/g wet weight) and phenanthrene (0.34–3.54 ng/g wet weight) were detected in the analysed samples. None of the samples contained detectable amounts of benzo[a]pyrene, the marker used for evaluating the occurrence and carcinogenic effects of PAHs in food.

Constraint solving over multi-valued logics - application to digital circuits

Due to usage conditions, hazardous environments or intentional causes, physical and virtual systems are subject to faults in their components, which may affect their overall behaviour. In a ‘black-box’ agent modelled by a set of propositional logic rules, in which just a subset of components is externally visible, such faults may only be recognised by examining some output function of the agent. A (fault-free) model of the agent’s system provides the expected output given some input. If the real output differs from that predicted output, then the system is faulty. However, some faults may only become apparent in the system output when appropriate inputs are given. A number of problems regarding both testing and diagnosis thus arise, such as testing a fault, testing the whole system, finding possible faults and differentiating them to locate the correct one. The corresponding optimisation problems of finding solutions that require minimum resources are also very relevant in industry, as is minimal diagnosis. In this dissertation we use a well established set of benchmark circuits to address such diagnostic related problems and propose and develop models with different logics that we formalise and generalise as much as possible. We also prove that all techniques generalise to agents and to multiple faults. The developed multi-valued logics extend the usual Boolean logic (suitable for faultfree models) by encoding values with some dependency (usually on faults). Such logics thus allow modelling an arbitrary number of diagnostic theories. Each problem is subsequently solved with CLP solvers that we implement and discuss, together with a new efficient search technique that we present. We compare our results with other approaches such as SAT (that require substantial duplication of circuits), showing the effectiveness of constraints over multi-valued logics, and also the adequacy of a general set constraint solver (with special inferences over set functions such as cardinality) on other problems. In addition, for an optimisation problem, we integrate local search with a constructive approach (branch-and-bound) using a variety of logics to improve an existing efficient tool based on SAT and ILP.

OPTIMAX 2014 - Radiation dose and image quality optimisation in medical imaging

Medical imaging is a powerful diagnostic tool. Consequently, the number of medical images taken has increased vastly over the past few decades. The most common medical imaging techniques use X-radiation as the primary investigative tool. The main limitation of using X-radiation is associated with the risk of developing cancers. Alongside this, technology has advanced and more centres now use CT scanners; these can incur significant radiation burdens compared with traditional X-ray imaging systems. The net effect is that the population radiation burden is rising steadily. Risk arising from X-radiation for diagnostic medical purposes needs minimising and one way to achieve this is through reducing radiation dose whilst optimising image quality. All ages are affected by risk from X-radiation however the increasing population age highlights the elderly as a new group that may require consideration. Of greatest concern are paediatric patients: firstly they are more sensitive to radiation; secondly their younger age means that the potential detriment to this group is greater. Containment of radiation exposure falls to a number of professionals within medical fields, from those who request imaging to those who produce the image. These staff are supported in their radiation protection role by engineers, physicists and technicians. It is important to realise that radiation protection is currently a major European focus of interest and minimum competence levels in radiation protection for radiographers have been defined through the integrated activities of the EU consortium called MEDRAPET. The outcomes of this project have been used by the European Federation of Radiographer Societies to describe the European Qualifications Framework levels for radiographers in radiation protection. Though variations exist between European countries radiographers and nuclear medicine technologists are normally the professional groups who are responsible for exposing screening populations and patients to X-radiation. As part of their training they learn fundamental principles of radiation protection and theoretical and practical approaches to dose minimisation. However dose minimisation is complex – it is not simply about reducing X-radiation without taking into account major contextual factors. These factors relate to the real world of clinical imaging and include the need to measure clinical image quality and lesion visibility when applying X-radiation dose reduction strategies. This requires the use of validated psychological and physics techniques to measure clinical image quality and lesion perceptibility.