Multiprocessor task scheduling in multistage hyrid flowshops: a genetic algorithm approach

This paper considers multiprocessor task scheduling in a multistage hybrid flow-shop environment. The objective is to minimize the make-span, that is, the completion time of all the tasks in the last stage. This problem is of practical interest in the textile and process industries. A genetic algorithm (GA) is developed to solve the problem. The GA is tested against a lower bound from the literature as well as against heuristic rules on a test bed comprising 400 problems with up to 100 jobs, 10 stages, and with up to five processors on each stage. For small problems, solutions found by the GA are compared to optimal solutions, which are obtained by total enumeration. For larger problems, optimum solutions are estimated by a statistical prediction technique. Computational results show that the GA is both effective and efficient for the current problem. Test problems are provided in a web site at www.benchmark.ibu.edu.tr/mpt-h; fsp

Pruritus is a common feature in sheep infected with the BSE agent.

BACKGROUND: The variability in the clinical or pathological presentation of transmissible spongiform encephalopathies (TSEs) in sheep, such as scrapie and bovine spongiform encephalopathy (BSE), has been attributed to prion protein genotype, strain, breed, clinical duration, dose, route and type of inoculum and the age at infection. The study aimed to describe the clinical signs in sheep infected with the BSE agent throughout its clinical course to determine whether the clinical signs were as variable as described for classical scrapie in sheep. The clinical signs were compared to BSE-negative sheep to assess if disease-specific clinical markers exist. RESULTS: Forty-seven (34%) of 139 sheep, which comprised 123 challenged sheep and 16 undosed controls, were positive for BSE. Affected sheep belonged to five different breeds and three different genotypes (ARQ/ARQ, VRQ/VRQ and AHQ/AHQ). None of the controls or BSE exposed sheep with ARR alleles were positive. Pruritus was present in 41 (87%) BSE positive sheep; the remaining six were judged to be pre-clinically infected. Testing of the response to scratching along the dorsum of a sheep proved to be a good indicator of clinical disease with a test sensitivity of 85% and specificity of 98% and usually coincided with weight loss. Clinical signs that were displayed significantly earlier in BSE positive cases compared to negative cases were behavioural changes, pruritic behaviour, a positive scratch test, alopecia, skin lesions, teeth grinding, tremor, ataxia, loss of weight and loss of body condition. The frequency and severity of each specific clinical sign usually increased with the progression of disease over a period of 16-20 weeks. CONCLUSION: Our results suggest that BSE in sheep presents with relatively uniform clinical signs, with pruritus of increased severity and abnormalities in behaviour or movement as the disease progressed. Based on the studied sheep, these clinical features appear to be independent of breed, affected genotype, dose, route of inoculation and whether BSE was passed into sheep from cattle or from other sheep, suggesting that the clinical phenotype of BSE is influenced by the TSE strain more than by other factors. The clinical phenotype of BSE in the genotypes and breed studied was indistinguishable from that described for classical scrapie cases

Impact of inactivated poliovirus vaccine on mucosal immunity: implications for the polio eradication endgame.

The polio eradication endgame aims to bring transmission of all polioviruses to a halt. To achieve this aim, it is essential to block viral replication in individuals via induction of a robust mucosal immune response. Although it has long been recognized that inactivated poliovirus vaccine (IPV) is incapable of inducing a strong mucosal response on its own, it has recently become clear that IPV may boost immunity in the intestinal mucosa among individuals previously immunized with oral poliovirus vaccine. Indeed, mucosal protection appears to be stronger following a booster dose of IPV than oral poliovirus vaccine, especially in older children. Here, we review the available evidence regarding the impact of IPV on mucosal immunity, and consider the implications of this evidence for the polio eradication endgame. We conclude that the implementation of IPV in both routine and supplementary immunization activities has the potential to play a key role in halting poliovirus transmission, and thereby hasten the eradication of polio

Identifying component modules

A computer-based system for modelling component dependencies and identifying component modules is presented. A variation of the Dependency Structure Matrix (DSM) representation was used to model component dependencies. The system utilises a two-stage approach towards facilitating the identification of a hierarchical modular structure. The first stage calculates a value for a clustering criterion that may be used to group component dependencies together. A Genetic Algorithm is described to optimise the order of the components within the DSM with the focus of minimising the value of the clustering criterion to identify the most significant component groupings (modules) within the product structure. The second stage utilises a 'Module Strength Indicator' (MSI) function to determine a value representative of the degree of modularity of the component groupings. The application of this function to the DSM produces a 'Module Structure Matrix' (MSM) depicting the relative modularity of available component groupings within it. The approach enabled the identification of hierarchical modularity in the product structure without the requirement for any additional domain specific knowledge within the system. The system supports design by providing mechanisms to explicitly represent and utilise component and dependency knowledge to facilitate the nontrivial task of determining near-optimal component modules and representing product modularity

The cultural capitalists: notes on the ongoing reconfiguration of trafficking culture in Asia

Most analysis of the international flows of the illicit art market has described a global situation in which a postcolonial legacy of acquisition and collection exploits cultural heritage by pulling it westwards towards major international trade nodes in the USA and Europe. As the locus of consumptive global economic power shifts, however, these traditional flows are pulled in other directions: notably for the present commentary, towards and within Asia

A pentapeptide as minimal antigenic determinant for MHC class I-restricted T lymphocytes

Peptides that are antigenic for T lymphocytes are ligands for two receptors, the class I or II glycoproteins that are encoded by genes in the major histocompatibility complex, and the idiotypic / chain T-cell antigen receptor1–9. That a peptide must bind to an MHC molecule to interact with a T-cell antigen receptor is the molecular basis of the MHC restriction of antigen-recognition by T lymphocytes10,11. In such a trimolecular interaction the amino-acid sequence of the peptide must specify the contact with both receptors: agretope residues bind to the MHC receptor and epitope residues bind to the T-cell antigen receptor12,13. From a compilation of known antigenic peptides, two algorithms have been proposed to predict antigenic sites in proteins. One algorithm uses linear motifs in the sequence14, whereas the other considers peptide conformation and predicts antigenicity for amphipathic -helices15,16. We report here that a systematic delimitation of an antigenic site precisely identifies a predicted pentapeptide motif as the minimal antigenic determinant presented by a class I MHC molecule and recognized by a cytolytic T lymphocyte clone

Patient perspectives of managing fatigue in ankylosing spondylitis, and views on potential interventions: a qualitative study

<p>Background: Fatigue is a major component of living with ankylosing spondylitis (AS), though it has been largely over-looked, and currently there are no specific agreed management strategies.</p> <p>Methods: This qualitative exploratory study involved participants who are members of an existing population-based ankylosing spondylitis (PAS) cohort. Participants residing in South West Wales were invited to participate in a focus group to discuss; (1) effects of fatigue, (2) self-management strategies and (3) potential future interventions. The focus groups were audio-recorded and the transcripts were analysed using thematic analysis.</p> <p>Results: Participants consisted of 3 males/4 females (group 1) and 4 males/3 females (group 2), aged between 35 and 73 years (mean age 53 years). Three main themes were identified: (1) The effects of fatigue were multi-dimensional with participants expressing feelings of being ‘drained’ (physical), ‘upset’ (emotional) and experiencing ‘low-mood’ (psychological); (2) The most commonly reported self-management strategy for fatigue was a balanced combination of activity (exercise) and rest. Medication was reluctantly taken due to side-effects and worries over dependency; (3) Participants expressed a preference for psychological therapies rather than pharmacological for managing fatigue. Information on Mindfulness-Based Stress Reduction (MBSR) was received with interest, with recommendations for delivery in a group format with the option of distance-based delivery for people who were not able to attend a group course.</p> <p>Conclusions: Patients frequently try and manage their fatigue without any formal guidance or support. Our research indicates there is a need for future research to focus on psychological interventions to address the multi-faceted aspects of fatigue in AS.</p&gt

Mining and analysis of audiology data to find significant factors associated with tinnitus masker

Objectives: The objective of this research is to find the factors associated with tinnitus masker from the literature, and by using the large amount of audiology data available from a large NHS (National Health Services, UK) hearing aid clinic. The factors evaluated were hearing impairment, age, gender, hearing aid type, mould and clinical comments. Design: The research includes literature survey for factors associated with tinnitus masker, and performs the analysis of audiology data using statistical and data mining techniques. Setting: This research uses a large audiology data but it also faced the problem of limited data for tinnitus. Participants: It uses 1,316 records for tinnitus and other diagnoses, and 10,437 records of clinical comments from a hearing aid clinic. Primary and secondary outcome measures: The research is looking for variables associated with tinnitus masker, and in future, these variables can be combined into a single model to develop a decision support system to predict about tinnitus masker for a patient. Results: The results demonstrated that tinnitus maskers are more likely to be fit to individuals with milder forms of hearing loss, and the factors age, gender, type of hearing aid and mould were all found significantly associated with tinnitus masker. In particular, those patients having Age<=55 years were more likely to wear a tinnitus masker, as well as those with milder forms of hearing loss. ITE (in the ear) hearing aids were also found associated with tinnitus masker. A feedback on the results of association of mould with tinnitus masker from a professional audiologist of a large NHS (National Health Services, UK) was also taken to better understand them. The results were obtained with different accuracy for different techniques. For example, the chi-squared test results were obtained with 95% accuracy, for Support and Confidence only those results were retained which had more than 1% Support and 80% Confidence. Conclusions: The variables audiograms, age, gender, hearing aid type and mould were found associated with the choice of tinnitus masker in the literature and by using statistical and data mining techniques. The further work in this research would lead to the development of a decision support system for tinnitus masker with an explanation that how that decision was obtained

B-spline collocation simulation of non-linear transient magnetic nanobio-tribological squeeze-film flow

A mathematical model is presented for magnetized nanofluid bio-tribological squeeze film flow between two approaching disks. The nanofluid comprises a suspension of metal oxide nanoparticles with an electrically-conducting base fluid, making the nano-suspension responsive to applied magnetic field. The governing viscous momentum, heat and species (nano-particle) conservation equations are normalized with appropriate transformations which renders the original coupled, nonlinear partial differential equation system into a more amenable ordinary differential boundary value problem. The emerging model is shown to be controlled by a number of parameters, viz nanoparticle volume fraction, squeeze number, Hartmann magnetic body force number, disk surface transpiration parameter, Brownian motion parameter, thermophoretic parameter, Prandtl number and Lewis number. Computations are conducted with a B-spline collocation numerical method. Validation with previous homotopy solutions is included. The numerical spline algorithm is shown to achieve excellent convergence and stability in nonlinear bio-tribological boundary value problems. The interaction of heat and mass transfer with nanofluid velocity characteristics is explored. In particular smaller nanoparticle (high Brownian motion parameter) suspensions are studied. The study is relevant to enhanced lubrication performance in novel bio-sensors and intelligent knee joint (orthopaedic) systems

Missing Value Imputation Using Stratified Supervised Learning for Cardiovascular Data

Legacy (and current) medical datasets are rich source of information and knowledge. However, the use of most legacy medical datasets is beset with problems. One of the most often faced is the problem of missing data, often due to oversights in data capture or data entry procedures. Algorithms commonly used in the analysis of data often depend on a complete data set. Missing value imputation offers a solution to this problem. This may result in the generation of synthetic data, with artificially induced missing values, but simply removing the incomplete data records often produces the best classifier results. With legacy data, simply removing the records from the original datasets can significantly reduce the data volume and often affect the class balance of the dataset. A suitable method for missing value imputation is very much needed to produce good quality datasets for better analysing data resulting from clinical trials. This paper proposes a framework for missing value imputation using stratified machine learning methods. We explore machine learning technique to predict missing value for incomplete clinical (cardiovascular) data, with experiments comparing this with other standard methods. Two machine learning (classifier) algorithms, fuzzy unordered rule induction algorithm and decision tree, plus other machine learning algorithms (for comparison purposes) are used to train on complete data and subsequently predict missing values for incomplete data. The complete datasets are classified using decision tree, neural network, K-NN and K-Mean clustering. The classification performances are evaluated using sensitivity, specificity, accuracy, positive predictive value and negative predictive value. The results show that final classifier performance can be significantly improved for all class labels when stratification was used with fuzzy unordered rule induction algorithm to predict missing attribute values