Plug Force Monitoring for the Control and Optimisation of the Thermoforming Process

Thermoforming processes generally employ sheet temperature monitoring as the primary means of process control. In this paper the development of an alternative system that monitors plug force is described. Tests using a prototype device have shown that the force record over a forming cycle creates a unique map of the process operation. Key process features such as the sheet modulus, sheet sag and the timing of the process stages may be readily observed, and the effects of changes in all of the major processing parameters are easily distinguished. Continuous, cycle-to-cycle tests show that the output is consistent and repeatable over a longer time frame, providing the opportunity for development of an on-line process control system. Further testing of the system is proposed.

‘Transforming justice’: challenges for restorative justice in an era of punishment-based corrections

Scholars of restorative justice have long debated its theoretical relationship with formal criminal justice. This analysis critically examines the range of sociostructural conditions in contemporary society that have halted the spread of restorative policies in practice and prevented them from realizing their transformative potential as an alternative system of justice. These factors are attributed largely to a punitive penal culture that is characterized by policy-making based on penal populism, the governance of risk and a managerialist criminal justice agenda; and the widespread co-optation of restorative programs by the state. This broad argument is explored in the context of two particular case studies – recent developments in youth justice and in sexual offending respectively in England and Wales and elsewhere. This examination ultimately highlights challenges for restorative justice in the current risk-driven penal climate and advocates a need to re-evaluate its relationship with formal state justice.

Computerised Diagnostic Decision Support System for the Classification of Pre-Invasive Cervical Squamous Lesions.

Previous studies have revealed considerable interobserver and intraobserver variation in the histological classification of preinvasive cervical squamous lesions. The aim of the present study was to develop a decision support system (DSS) for the histological interpretation of these lesions. Knowledge and uncertainty were represented in the form of a Bayesian belief network that permitted the storage of diagnostic knowledge and, for a given case, the collection of evidence in a cumulative manner that provided a final probability for the possible diagnostic outcomes. The network comprised 8 diagnostic histological features (evidence nodes) that were each independently linked to the diagnosis (decision node) by a conditional probability matrix. Diagnostic outcomes comprised normal; koilocytosis; and cervical intraepithelial neoplasia (CIN) 1, CIN II, and CIN M. For each evidence feature, a set of images was recorded that represented the full spectrum of change for that feature. The system was designed to be interactive in that the histopathologist was prompted to enter evidence into the network via a specifically designed graphical user interface (i-Path Diagnostics, Belfast, Northern Ireland). Membership functions were used to derive the relative likelihoods for the alternative feature outcomes, the likelihood vector was entered into the network, and the updated diagnostic belief was computed for the diagnostic outcomes and displayed. A cumulative probability graph was generated throughout the diagnostic process and presented on screen. The network was tested on 50 cervical colposcopic biopsy specimens, comprising 10 cases each of normal, koilocytosis, CIN 1, CIN H, and CIN III. These had been preselected by a consultant gynecological pathologist. Using conventional morphological assessment, the cases were classified on 2 separate occasions by 2 consultant and 2 junior pathologists. The cases were also then classified using the DSS on 2 occasions by the 4 pathologists and by 2 medical students with no experience in cervical histology. Interobserver and intraobserver agreement using morphology and using the DSS was calculated with K statistics. Intraobserver reproducibility using conventional unaided diagnosis was reasonably good (kappa range, 0.688 to 0.861), but interobserver agreement was poor (kappa range, 0.347 to 0.747). Using the DSS improved overall reproducibility between individuals. Using the DSS, however, did not enhance the diagnostic performance of junior pathologists when comparing their DSS-based diagnosis against an experienced consultant. However, the generation of a cumulative probability graph also allowed a comparison of individual performance, how individual features were assessed in the same case, and how this contributed to diagnostic disagreement between individuals. Diagnostic features such as nuclear pleomorphism were shown to be particularly problematic and poorly reproducible. DSSs such as this therefore not only have a role to play in enhancing decision making but also in the study of diagnostic protocol, education, self-assessment, and quality control. (C) 2003 Elsevier Inc. All rights reserved.

Comparison of a centralised and distributed approach for a generic scheduling system

PEGS (Production and Environmental Generic Scheduler) is a generic production scheduler that produces good schedules over a wide range of problems. It is centralised, using search strategies with the Shifting Bottleneck algorithm. We have also developed an alternative distributed approach using software agents. In some cases this reduces run times by a factor of 10 or more. In most cases, the agent-based program also produces good solutions for published benchmark data, and the short run times make our program useful for a large range of problems. Test results show that the agents can produce schedules comparable to the best found so far for some benchmark datasets and actually better schedules than PEGS on our own random datasets. The flexibility that agents can provide for today's dynamic scheduling is also appealing. We suggest that in this sort of generic or commercial system, the agent-based approach is a good alternative.

'Like waking up in a Franz Kafka novel': Service users' experiences of the child protection system when domestic violence and acrimonious separations are involved

The challenges that arise in respect of child abuse reports made in the context of domestic violence and/or acrimonious separation have been the subject of recent academic discussion. This paper adds a service user perspective to the debate and reports on the findings from a study conducted in the Republic of Ireland. In addition to the previously established evidence about such cases, it demonstrates the level of powerlessness and frustration experienced by families who found it difficult to have their needs heard or met. It also illustrates the very detrimental emotional impact on children and parents who frequently encountered indifference as well as insensitive and gendered responses from child protection staff. The findings indicate that mainstream statutory child protection services do not have the capacity to deal with these complex cases, and advocates the adoption of alternative approaches. Importantly, the study demonstrates the necessity to pay attention to the views of service users in developing an appropriate response.

The appraisal of an automated multi-immunoaffinity chromatography system to detect anabolic agents in bile and urine

Screening for residues of anabolic steroids frequently requires extraction from tissues and fluids before analysis. Chemical procedures for these extractions can be complicated, expensive to perform and not ideal for the simultaneous extraction of analytes with different solubilities. Extraction by multi-immunoaffinity chromatography (MIAC) may be used as an alternative. Samples are passed through a column containing a range of antibodies immobilized on an inert support. The desired analytes are bound to their respective antibodies, washed and then eluted by a suitable solvent. The purified extracts can then be incorporated into the analytical tests, The analytes that can be extracted presently are alpha-nortestosterone, zeranol, trenbolone, diethylstilboestrol, boldenone and dexamethasone. Manually, the MIAC procedure is limited to about six columns per operator but bq automating the process using a robotic sample processor (RSP), 48 columns can be run simultaneously during the day or night. The RSP has also been adapted to transfer extracts and reagents on to ELISA plates. The automated system has proved to be a robust and reliable means of screening large numbers of samples for anabolic agents with minimal manual input

Spatial Allocation of Material Flow Analysis: A Geographic Information System Application of Material Flow Analysis in Ireland

This study concerns the spatial allocation of material flows, with emphasis on construction material in the Irish housing sector. It addresses some of the key issues concerning anthropogenic impact on the environment through spatial temporal visualisation of the flow of materials, wastes and emissions at different spatial levels. This is presented in the form of a spatial model, Spatial Allocation of Material Flow Analysis (SAMFA), which enables the simulation of construction material flows and associated energy use. SAMFA parallels the Island Limits project (EPA funded under 2004-SD-MS-22-M2), which aimed to create a material flow analysis of the Irish economy classified by industrial sector. SAMFA further develops this by attempting to establish the material flows at the subnational geographical scale that could be used in the development of local authority (LA) sustainability strategies and spatial planning frameworks by highlighting the cumulative environmental impacts of the development of the built environment. By drawing on the idea of planning support systems, SAMFA also aims to provide a cross-disciplinary, integrative medium for involving stakeholders in strategies for a sustainable built environment and, as such, would help illustrate the sustainability consequences of alternative The pilot run of the model in Kildare has shown that the model can be successfully calibrated and applied to develop alternative material flows and energy-use scenarios at the ED level. This has been demonstrated through the development of an integrated and a business-as-usual scenario, with the former integrating a range of potential material efficiency and energysaving policy options and the latter replicating conditions that best describe the current trend. Their comparison shows that the former is better than the latter in terms of both material and energy use. This report also identifies a number of potential areas of future research and areas of broader application. This includes improving the accuracy of the SAMFA model (e.g. by establishing actual life expectancy of buildings in the Irish context through field surveys) and the extension of the model to other Irish counties. This would establish SAMFA as a valuable predicting and monitoring tool that is capable of integrating national and local spatial planning objectives with actual environmental impacts. Furthermore, should the model prove successful at this level, it then has the potential to transfer the modelling approach to other areas of the built environment, such as commercial development and other key contributors of greenhouse emissions. The ultimate aim is to develop a meta-model for predicting the consequences of consumption patterns at the local scale. This therefore offers the possibility of creating critical links between socio technical systems with the most important challenge of all the limitations of the biophysical environment.

The rebirth of dependence– offering an alternative understanding of the financial crisis

Purpose – This article aims to contribute to the re-evaluation of the global market system using a Marxist inspired theory of development, dependency.

Design/methodology/approach – This article draws on dependency theory as an alternative means of understanding global relationships. Building on existing literature, it modifies dependency to encapsulate technological developments and trends in the global market.

Findings – Re-evaluating the global market and the relationships that underpin it, through an alternative theory, highlights the fragility of markets and associated relationships. Increasingly, nation states are becoming irrelevant. This presents a problem as the main actors in the global market today are “above” inter-state relations, yet the organs that regulate their behaviour still are grounded in inter-state rhetoric. The relationship between development and underdevelopment remains.

Research limitations/implications – The financial crisis has propagated a wealth of interest in the relationships between states, between multi-national corporations (MNCs) and between MNCs and state. Using this broad theory of modified dependency, it can be applied to a range of different relationships. In the wake of financial crisis, there is the opportunity to raise awareness of these ingrained issues and initiate discussions at national, regional and international levels to alleviate some of the conditions of dependence.

Practical implications – Regardless of the work of national governments and NGOs to instigate development in lesser-developed regions through policy and regulations, unless there is a conscientious commitment from MNCs operating in that region to contribute to development, the result will be the development of underdevelopment and the underdevelopment of development. CSR can help alleviate the conditions of the dependence on capital generated by MNCs, but this is not a solution to an ingrained problem, capitalism.

Originality/value – This article introduces a modified theory of dependency for the first time. It applies the theory to the financial crisis and to the continent of Africa. It considers the role that CSR can play in alleviating the conditions of dependence.

Inverse planned constant dose rate volumetric modulated arc therapy (VMAT) as an efficient alternative to five-field intensity modulated radiation therapy (IMRT) for prostate

Purpose: The aim of this work was to determine if volumetric modulated arc therapy (VMAT) plans, created for constant dose-rate (cdrVMAT) delivery are a viable alternative to step and shoot five-field intensity modulated radiation therapy (IMRT). Materials and methods: The cdrVMAT plans, inverse planned on a treatment planning system with no solution to account for couch top or rails, were created for delivery on a linear accelerator with no variable dose rate control system. A series of five-field IMRT and cdrVMAT plans were created using dual partial arcs (gantry rotating between 260° and 100°) with 4° control points for ten prostate patients with the average rectal constraint incrementally increased. Pareto fronts were compared for the planning target volume homogeneity and average rectal dose between the two techniques for each patient. Also investigated were tumour control probability and normal tissue complication probability values for each technique. The delivery parameters [monitor units (MU) and time] and delivery accuracy of the IMRT and VMAT plans were also compared. Results: Pareto fronts showed that the dual partial arc plans were superior to the five-field IMRT plans, particularly for the clinically acceptable plans where average rectal doses were less for rotational plans (p = 0·009) with no statistical difference in target homogeneity. The cdrVMAT plans had significantly more MU (p = 0·005) but the average delivery time was significantly less than the IMRT plans by 42%. All clinically acceptable cdrVMAT plans were accurate in their delivery (gamma 99·2 ± 1·1%, 3%3 mm criteria). Conclusions Accurate delivery of dual partial arc cdrVMAT avoiding the couch top and rails has been demonstrated.

The use of a dynamic truck-trailer drive-by system to monitor bridge damping

Bridge structures are continuously subject to degradation due to the environment, ageing and excess loading. Periodic monitoring of bridges is therefore a key part of any maintenance strategy as it can give early warning if a bridge becomes unsafe. This article investigates an alternative method for the monitoring of bridge dynamic behaviour: a truck-trailer vehicle system, with accelerometers fitted to the axles of the trailer. The method aims to detect changes in the damping of a bridge, which may indicate the existence of damage. A simplified vehicle-bridge interaction model is used in theoretical simulations to assess the effectiveness of the method in detecting those changes. The influence of road profile roughness on the vehicle vibration is overcome by recording accelerations from both axles of a trailer and then analysing the spectra of the difference in the accelerations between the two axles. The effectiveness of the approach in detecting damage simulated as a loss in stiffness is also investigated. In addition, the sensitivity of the approach to the vehicle speed, road roughness class, bridge span length, changes in the equal axle properties and noise is investigated.

Experimental investigation of a wavelet based drive-by bridge inspection system incorporating pattern recognition

This paper presents the results of an experimental investigation, carried out in order to verify the feasibility of a ‘drive-by’ approach which uses a vehicle instrumented with accelerometers to detect and locate damage in a bridge. In theoretical simulations, a simplified vehicle-bridge interaction model is used to investigate the effectiveness of the approach in detecting damage in a bridge from vehicle accelerations. For this purpose, the accelerations are processed using a continuous wavelet transform and damage indicators are evaluated and compared. Alternative statistical pattern recognition techniques are incorporated to allow for repeated vehicle passes. Parameters such as vehicle speed, damage level, location and road roughness are varied in simulations to investigate the effect. A scaled laboratory experiment is carried out to assess the effectiveness of the approach in a more realistic environment, considering a number of bridge damage scenarios.

Deliberative Democracy in Northern Ireland: Opportunities and challenges for consensus in a consociational system

The 1998 Multiparty Agreement established a consociational system that contains within it an explicit dualism: unionist/nationalist, north and south of Ireland, and British and Irish. But although this formula has facilitated relatively stable and devolved governance, it is based on a distorted representation of a society in which there are much more complex divisions and, indeed, many common problems. Citizen-led efforts towards deliberative democracy since the 1980s have demonstrated both the will and the capacity for alternative, consensual political expressions. This chapter examines the challenges and opportunities facing these citizen-led initiatives in a political environment which, despite the significant decline in violence and terror, seems stubbornly resistant to the idea of broadening the various means of democratic participation.

Phytoremediation assessment of Gomphrena globosa and Zinnia elegans grown in arsenic-contaminated hydroponic conditions as a safe and feasible alternative to be applied in arsenic-contaminated soils of the Bengal Delta

Several agricultural fields show high contents of arsenic because of irrigation with arsenic- contaminated groundwater. Vegetables accumulate arse- nic in their edible parts when grown in contaminated soils. Polluted vegetables are one of the main sources of arsenic in the food chain, especially for people living in rural arsenic endemic villages of India and Bangladesh. The aim of this study was to assess the feasibility of floriculture in the crop rotation system of arsenic en- demic areas of the Bengal Delta. The effects of different arsenic concentrations (0, 0.5, 1.0, and 2.0 mg As L−1) and types of flowering plant (Gomphrena globosa and Zinnia elegans) on plant growth and arsenic accumula- tion were studied under hydroponic conditions. Total arsenic was quantified using atomic absorption spec- trometer with hydride generation (HG-AAS). Arsenic was mainly accumulated in the roots (72 %), followed by leaves (12 %), stems (10 %), and flowers (<1 %). The flowering plants studied did not show as high phytoremediation capacities as other wild species, suchas ferns. However, they behaved as arsenic tolerant plants and grew and bloomed well, without showing any phytotoxic signs. This study proves that floriculture could be included within the crop rotation system in arsenic-contaminated agricultural soils, in order to im- prove food safety and also food security by increasing farmer’s revenue.

An Efficient LS-SVM-Based Method for Fuzzy System Construction

This paper proposes an efficient learning mechanism to build fuzzy rule-based systems through the construction of sparse least-squares support vector machines (LS-SVMs). In addition to the significantly reduced computational complexity in model training, the resultant LS-SVM-based fuzzy system is sparser while offers satisfactory generalization capability over unseen data. It is well known that the LS-SVMs have their computational advantage over conventional SVMs in the model training process; however, the model sparseness is lost, which is the main drawback of LS-SVMs. This is an open problem for the LS-SVMs. To tackle the nonsparseness issue, a new regression alternative to the Lagrangian solution for the LS-SVM is first presented. A novel efficient learning mechanism is then proposed in this paper to extract a sparse set of support vectors for generating fuzzy IF-THEN rules. This novel mechanism works in a stepwise subset selection manner, including a forward expansion phase and a backward exclusion phase in each selection step. The implementation of the algorithm is computationally very efficient due to the introduction of a few key techniques to avoid the matrix inverse operations to accelerate the training process. The computational efficiency is also confirmed by detailed computational complexity analysis. As a result, the proposed approach is not only able to achieve the sparseness of the resultant LS-SVM-based fuzzy systems but significantly reduces the amount of computational effort in model training as well. Three experimental examples are presented to demonstrate the effectiveness and efficiency of the proposed learning mechanism and the sparseness of the obtained LS-SVM-based fuzzy systems, in comparison with other SVM-based learning techniques.