109 research outputs found

    PFG NMR and Bayesian analysis to characterise non-Newtonian fluids

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    Many industrial flow processes are sensitive to changes in the rheological behaviour of process fluids, and there therefore exists a need for methods that provide online, or inline, rheological characterisation necessary for process control and optimisation over timescales of minutes or less. Nuclear magnetic resonance (NMR) offers a non-invasive technique for this application, without limitation on optical opacity. We present a Bayesian analysis approach using pulsed field gradient (PFG) NMR to enable estimation of the rheological parameters of Herschel-Bulkley fluids in a pipe flow geometry, characterised by a flow behaviour index n, yield stress τ0_{0}, and consistency factor k, by analysis of the signal in q-space. This approach eliminates the need for velocity image acquisition and expensive gradient hardware. We investigate the robustness of the proposed Bayesian NMR approach to noisy data and reduced sampling using simulated NMR data and show that even with a signal-to-noise ratio (SNR) of 100, only 16 points are required to be sampled to provide rheological parameters accurate to within 2% of the ground truth. Experimental validation is provided through an experimental case study on Carbopol 940 solutions (model Herschel-Bulkley fluids) using PFG NMR at a 1^{1}H resonance frequency of 85.2MHz; for SNR>1000, only 8 points are required to be sampled. This corresponds to a total acquisition time of <60s and represents an 88% reduction in acquisition time when compared to MR flow imaging. Comparison of the shear stress-shear rate relationship, quantified using Bayesian NMR, with non-Bayesian NMR methods demonstrates that the Bayesian NMR approach is in agreement with MR flow imaging to within the accuracy of the measurement. Furthermore, as we increase the concentration of Carbopol 940 we observe a change in rheological characteristics, probably due to shear history-dependent behaviour and the different geometries used. This behaviour highlights the need for online, or inline, rheological characterisation in industrial process applications.AJS and LFG wish to thank the EPSRC (Grant numbers EP/F047991/1 and EP/K039318/1) and TWB wishes to thank the EPSRC and Johnson Matthey plc for financial support

    Characterising the rheology of non-Newtonian fluids using PFG-NMR and cumulant analysis.

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    Conventional rheological characterisation using nuclear magnetic resonance (NMR) typically utilises spatially-resolved measurements of velocity. We propose a new approach to rheometry using pulsed field gradient (PFG) NMR which readily extends the application of MR rheometry to single-axis gradient hardware. The quantitative use of flow propagators in this application is challenging because of the introduction of artefacts during Fourier transform, which arise when realistic sampling strategies are limited by experimental and hardware constraints and when particular spatial and temporal resolution are required. The method outlined in this paper involves the cumulant analysis of the acquisition data directly, thereby preventing the introduction of artefacts and reducing data acquisition times. A model-dependent approach is developed to enable the pipe-flow characterisation of fluids demonstrating non-Newtonian power-law rheology, involving the use of an analytical expression describing the flow propagator in terms of the flow behaviour index. The sensitivity of this approach was investigated and found to be robust to the signal-to-noise ratio (SNR) and number of acquired data points, enabling an increase in temporal resolution defined by the SNR. Validation of the simulated results was provided by an experimental case study on shear-thinning aqueous xanthan gum solutions, whose rheology could be accurately characterised using a power-law model across the experimental shear rate range of 1-100 s(-1). The flow behaviour indices calculated using this approach were observed to be within 8% of those obtained using spatially-resolved velocity imaging and within 5% of conventional rheometry. Furthermore, it was shown that the number of points sampled could be reduced by a factor of 32, when compared to the acquisition of a volume-averaged flow propagator with 128 gradient increments, without negatively influencing the accuracy of the characterisation, reducing the acquisition time to only 3% of its original value.AJS wishes to thank the EPSRC (grant numbers EP/F047991/1 and EP/K039318/1) and TB wishes to thank the EPSRC and Johnson Matthey plc for financial support.This is the final published version. It first appeared at http://www.sciencedirect.com/science/article/pii/S1090780715000798#

    Validation of a low field Rheo-NMR instrument and application to shear-induced migration of suspended non-colloidal particles in Couette flow.

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    Nuclear magnetic resonance rheology (Rheo-NMR) is a valuable tool for studying the transport of suspended non-colloidal particles, important in many commercial processes. The Rheo-NMR imaging technique directly and quantitatively measures fluid displacement as a function of radial position. However, the high field magnets typically used in these experiments are unsuitable for the industrial environment and significantly hinder the measurement of shear stress. We introduce a low field Rheo-NMR instrument (1H resonance frequency of 10.7MHz), which is portable and suitable as a process monitoring tool. This system is applied to the measurement of steady-state velocity profiles of a Newtonian carrier fluid suspending neutrally-buoyant non-colloidal particles at a range of concentrations. The large particle size (diameter >200μm) in the system studied requires a wide-gap Couette geometry and the local rheology was expected to be controlled by shear-induced particle migration. The low-field results are validated against high field Rheo-NMR measurements of consistent samples at matched shear rates. Additionally, it is demonstrated that existing models for particle migration fail to adequately describe the solid volume fractions measured in these systems, highlighting the need for improvement. The low field implementation of Rheo-NMR is complementary to shear stress rheology, such that the two techniques could be combined in a single instrument

    Equine Protozoal Myeloencephalitis: An Updated Consensus Statement with a Focus on Parasite Biology, Diagnosis, Treatment, and Prevention

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    Equine protozoal myeloencephalitis (EPM) remains an important neurologic disease of horses. There are no pathognomonic clinical signs for the disease. Affected horses can have focal or multifocal central nervous system (CNS) disease. EPM can be difficult to diagnose antemortem. It is caused by either of 2 parasites, Sarcocystis neurona and Neospora hughesi, with much less known about N. hughesi. Although risk factors such as transport stress and breed and age correlations have been identified, biologic factors such as genetic predispositions of individual animals, and parasite-specific factors such as strain differences in virulence, remain largely undetermined. This consensus statement update presents current published knowledge of the parasite biology, host immune response, disease pathogenesis, epidemiology, and risk factors. Importantly, the statement provides recommendations for EPM diagnosis, treatment, and prevention

    Predicting Peptide Binding Affinities to MHC Molecules Using a Modified Semi-Empirical Scoring Function

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    The Major Histocompatibility Complex (MHC) plays an important role in the human immune system. The MHC is involved in the antigen presentation system assisting T cells to identify foreign or pathogenic proteins. However, an MHC molecule binding a self-peptide may incorrectly trigger an immune response and cause an autoimmune disease, such as multiple sclerosis. Understanding the molecular mechanism of this process will greatly assist in determining the aetiology of various diseases and in the design of effective drugs. In the present study, we have used the Fresno semi-empirical scoring function and modify the approach to the prediction of peptide-MHC binding by using open-source and public domain software. We apply the method to HLA class II alleles DR15, DR1, and DR4, and the HLA class I allele HLA A2. Our analysis shows that using a large set of binding data and multiple crystal structures improves the predictive capability of the method. The performance of the method is also shown to be correlated to the structural similarity of the crystal structures used. We have exposed some of the obstacles faced by structure-based prediction methods and proposed possible solutions to those obstacles. It is envisaged that these obstacles need to be addressed before the performance of structure-based methods can be on par with the sequence-based methods

    A Meta-Analysis of the Existing Knowledge of Immunoreactivity against Hepatitis C Virus (HCV)

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    Approximately 3% of the world population is infected by HCV, which represents a major global health challenge. Almost 400 different scientific reports present immunological data related to T cell and antibody epitopes derived from HCV literature. Analysis of all HCV-related epitope hosted in the Immune Epitope Database (IEDB), a repository of freely accessible immune epitope data, revealed more than 1500 and 1900 distinct T cell and antibody epitopes, respectively. The inventory of all data revealed specific trends in terms of the host and the HCV genotypes from which sequences were derived. Upon further analysis we found that this large number of epitopes reflects overlapping structures, and homologous sequences derived from different HCV isolates. To access and visualize this information we developed a novel strategy that assembles large sets of epitope data, maps them onto reference genomes and displays the frequency of positive responses. Compilation of the HCV immune reactivity from hundreds of different studies, revealed a complex and thorough picture of HCV immune epitope data to date. The results pinpoint areas of more intense reactivity or research activities at the level of antibody, CD4 and CD8 responses for each of the individual HCV proteins. In general, the areas targeted by the different effector immune functions were distinct and antibody reactivity was positively correlated with hydrophilicity, while T cell reactivity correlated with hydrophobicity. At the sequence level, epitopes frequently recognized by both T cell and B cell correlated with low variability, and our analysis thus highlighted areas of potential interest for practical applications. The human reactivity was further analyzed to pinpoint differential patterns of reactivity associated with acute versus chronic infection, to reveal the apparent impact of glycosylation on T cell, but not antibody responses, and to highlight a paucity of studies involved antibody epitopes associated with virus neutralization

    Assessment of personal care and medical robots from older adults' perspective

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    Demographic reports indicate that population of older adults is growing significantly over the world and in particular in developed nations. Consequently, there are a noticeable number of demands for certain services such as health-care systems and assistive medical robots and devices. In today's world, different types of robots play substantial roles specifically in medical sector to facilitate human life, especially older adults. Assistive medical robots and devices are created in various designs to fulfill specific needs of older adults. Though medical robots are utilized widely by senior citizens, it is dramatic to find out into what extent assistive robots satisfy their needs and expectations. This paper reviews various assessments of assistive medical robots from older adults' perspectives with the purpose of identifying senior citizen's needs, expectations, and preferences. On the other hand, these kinds of assessments inform robot designers, developers, and programmers to come up with robots fulfilling elderly's needs while improving their life quality

    An evidence-based decision assistance model for predicting training outcome in juvenile guide dogs

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    Working dog organisations, such as Guide Dogs, need to regularly assess the behaviour of the dogs they train. In this study we developed a questionnaire-style behaviour assessment completed by training supervisors of juvenile guide dogs aged 5, 8 and 12 months old (n = 1,401), and evaluated aspects of its reliability and validity. Specifically, internal reliability, temporal consistency, construct validity, predictive criterion validity (comparing against later training outcome) and concurrent criterion validity (comparing against a standardised behaviour test) were evaluated. Thirty-nine questions were sourced either from previously published literature or created to meet requirements identified via Guide Dogs staff surveys and staff feedback. Internal reliability analyses revealed seven reliable and interpretable trait scales named according to the questions within them as: Adaptability; Body Sensitivity; Distractibility; Excitability; General Anxiety; Trainability and Stair Anxiety. Intra-individual temporal consistency of the scale scores between 5±8, 8±12 and 5±12 months was high. All scales excepting Body Sensitivity showed some degree of concurrent criterion validity. Predictive criterion validity was supported for all seven scales, since associations were found with training outcome, at at-least one age. Thresholds of z-scores on the scales were identified that were able to distinguish later training outcome by identifying 8.4% of all dogs withdrawn for behaviour and 8.5% of all qualified dogs, with 84% and 85% specificity. The questionnaire assessment was reliable and could detect traits that are consistent within individuals over time, despite juvenile dogs undergoing development during the study period. By applying thresholds to scores produced from the questionnaire this assessment could prove to be a highly valuable decision-making tool for Guide Dogs. This is the first questionnaire-style assessment of juvenile dogs that has shown value in predicting the training outcome of individual working dogs

    In Search of Cellular Immunophenotypes in the Blood of Children with Autism

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    Autism is a neurodevelopmental disorder characterized by impairments in social behavior, communication difficulties and the occurrence of repetitive or stereotyped behaviors. There has been substantial evidence for dysregulation of the immune system in autism.We evaluated differences in the number and phenotype of circulating blood cells in young children with autism (n = 70) compared with age-matched controls (n = 35). Children with a confirmed diagnosis of autism (4-6 years of age) were further subdivided into low (IQ<68, n = 35) or high functioning (IQ ≥ 68, n = 35) groups. Age- and gender-matched typically developing children constituted the control group. Six hundred and forty four primary and secondary variables, including cell counts and the abundance of cell surface antigens, were assessed using microvolume laser scanning cytometry.There were multiple differences in immune cell populations between the autism and control groups. The absolute number of B cells per volume of blood was over 20% higher for children with autism and the absolute number of NK cells was about 40% higher. Neither of these variables showed significant difference between the low and high functioning autism groups. While the absolute number of T cells was not different across groups, a number of cellular activation markers, including HLA-DR and CD26 on T cells, and CD38 on B cells, were significantly higher in the autism group compared to controls.These results support previous findings that immune dysfunction may occur in some children with autism. Further evaluation of the nature of the dysfunction and how it may play a role in the etiology of autism or in facets of autism neuropathology and/or behavior are needed
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