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A multi-site, multi-modal travelling-heads resource for brain MRI harmonisation
Get PDFDespite its great potential for studying the living brain, magnetic resonance imaging (MRI) can be often limited by nuisance non-biological factors, such as hardware/software differences between scanners, which can interfere with biological variability. This lack of standardisation or harmonisation between scanners hinders reproducibility and quantifiability of MRI. Towards addressing this challenge, we present one of the most comprehensive MRI harmonisation resources, based on a travelling heads paradigm; healthy volunteers scanned repeatedly across different scanners. The Oxford-Nottingham Harmonisation (ON-Harmony) resource offers data from participants each scanned on six different 3T MRI scanners from three major vendors (GE/Philips/Siemens) across five imaging sites. Each scanning session includes five imaging modalities (T1w/T2w/dMRI/rfMRI/SWI) with protocols aligned to UK Biobank, while for about half of the participants five within-scanner repeats are additionally acquired. The 165 multi-modal scanning sessions allow mapping of different pools of variability (biological, between-scanner, within-scanner) for hundreds of MRI-derived measures. We describe the breadth of information contained in the publicly-available data and showcase their reuse potential for evaluating efficacy of harmonisation approaches
Simplified model for the tool-part interaction in spring-in of L-shape composite laminates
No full textManufacturing of fibre-reinforced composites is often accompanied by process-induced distortions, primarily due to the anisotropy of the composites constituents (fibres and matrix), their thermo-chemical interactions, and the interaction between the composite and the tooling. Numerical models that account for these factors require extensive experimental material and process characterisation programmes before the models can be effectively used at the design stage. This paper presents experimental measurements of spring-in angles of L-shape IM7/8552 laminates cured on an aluminium mould. The curing process for L-shape laminates was simulated using the Cure Hardening Instantaneously Linear Elastic model. Tool-part interaction was characterised by fitting an analytical model to experimental measurements of warpage of flat laminates and modelled using boundary conditions designed to avoid the need for explicit modelling of the tooling. The spring-in angles predicted by the proposed simulation framework were within 0.5∘ of the experimental results for the range of geometries considered. The simulations provided insights into the effects of specimen design (corner radius, flange length, and lay-up) as well as tool-part interaction on the total spring-in angle. It was shown that tool-part interaction significantly contributes to the spring-in angle, particularly in specimens with larger flange lengths
Dog-assisted interventions for children and adults with mental health or neurodevelopmental conditions: systematic review
Get PDFBackground Dog-assisted interventions (DAIs) to improve health-related outcomes for people with mental health or neurodevelopmental conditions are becoming increasingly popular. However, DAIs are not based on robust scientific evidence. Aims To determine the effectiveness of DAIs for children and adults with mental health or neurodevelopmental conditions, assess how well randomised controlled trials (RCTs) are reported, and examine the use of terminology to classify DAIs. Methods A systematic search was conducted in Embase, PsycINFO, PubMed, CINAHL, Web of Science and the Cochrane Library. RCTs were grouped by commonly reported outcomes and described narratively with forest plots reporting standardised mean differences and 95% confidence intervals without a pooled estimate. The quality of reporting of RCTs and DAIs was evaluated by assessing adherence to CONSORT and the Template for Intervention Description and Replication (TIDieR) guidelines. Suitability of use of terminology was assessed by mapping terms to the intervention content described. Results Thirty-three papers were included, reporting 29 RCTs (with five assessed as overall high quality); a positive impact of DAIs was found by 57% (8/14) for social skills and/or behaviour, 50% (5/10) for symptom frequency and/or severity, 43% (6/14) for depression and 33% (2/6) for agitation. The mean proportion of adherence to the CONSORT statement was 48.6%. The TIDieR checklist also indicated considerable variability in intervention reporting. Most DAIs were assessed as having clear alignment for terminology, but improvement in reporting information is still required. Conclusions DAIs may show promise for improving mental health and behavioural outcomes for those with mental health or neurodevelopmental conditions, particularly for conditions requiring social skill support. However, the quality of reporting requires improvement
Stepping on the Gas: Pathways to Reduce Venting in Household-Scale Kenyan Biogas Digesters
No full textOne method of producing bioenergy is through Anaerobic Digestion (AD) of plant, animal, and human waste in a biodigester. AD is a cost-effective method of simultaneously managing harmful waste, creating biogas for cooking, and producing nitrogen-rich liquid fertiliser for agriculture. However, there is minimal exploration around how these household-scale biogas digesters, in Kenya and beyond, contribute to global bioenergy methane emissions - this paper directly addresses this gap.We employ a two-phase approach which establishes the scale of the challenge through a rapid review of available literature on loss, leaking and venting, then contextualise this data with the lived experience of 33 biogas-users across 5 counties in Kenya.The results highlight three critical dimensions - the demand, supply, and systemic from the users' perspectives - all linked to the venting phenomenon. The demand side showed a lack of understanding of venting and its causes, these included; pre-processing feedstock, feeding regime, seasonal influence, pressure, cookstove stacking, lack of maintenance and market access. On the supply side, our critical learning highlighted that biogas units are typically sold based upon the available feedstock, rather than the potential gas need. Next, we identify the systemic drivers; household-scale digesters do not pose a climate threat, a lack of technical solutions, and the overwhelming Pandora's Box of impacts. For each driver - the supply, demand, and systemic - we highlight a series of mitigating actions that small-scale, locally-led biogas stakeholders can take to minimise venting, this is summarised in our practical “venting framework”
Relationship Between Neutrophil Count and 90-Day Outcomes and Effect of Dual Antiplatelet Therapy in Patients with Acute Ischemic Stroke or Transient Ischemic Attack: A Post Hoc Analysis of the INSPIRES Trial
Get PDFBackground: Inflammation is an important mechanism in ischemic stroke and high-risk transient ischemic attack (TIA), but clinical inflammatory markers on antiplatelet therapy remains to be studied. To compare the neutrophil count (NC) on the efficacy and safety of clopidogrel–aspirin with that of aspirin in patients with ischemic stroke or high-risk TIA caused by intracranial or extracranial atherosclerosis.Methods: The study was a post hoc analysis of the multicenter, randomized, double-blind, placebo-controlled, two-by-two factorial trial. The primary efficacy and safety outcomes were the 90-day stroke and moderate-to-severe bleeding. The differences in the efficacy outcome were calculated with cox proportional hazards model, and the generalized linear model as well as logistic regression.Results: The study included 5929 patients of median age 65 years (interquartile range 57 to 71 years), 3800 (64.09%) of whom were men; 1983 (33.28%) had a low NC (≤3.65 × 109/L), 1973 (33.28%) had an intermediate NC (3.65 4.97 × 109/L). Patients with ischemic stroke or TIA with a higher NC benefited more from clopidogrel–aspirin than from aspirin alone. There was no significant difference in the primary safety outcome of moderate-to-severe bleeding according to antiplatelet therapy or NC.Conclusions: The post hoc analysis suggested patients with a higher NC obtained greater benefit from clopidogrel–aspirin than from aspirin without an increase in bleeding risk. The findings may serve as a reference indicator for future anti-inflammatory therapy. However, further research is needed to explore the mechanism
Inflammation-related microRNA alterations in epilepsy: a systematic review of human and animal studies
No full textEpilepsy is a neurological condition that affects around 50 million people globally. While the underlying mechanism of epilepsy is not fully understood, emerging evidence demonstrates that inflammation is a key player in the pathogenesis of epilepsy. MicroRNAs are involved in the pathogenesis of epilepsy, particularly through regulating oxidative stress, apoptosis, and inflammation. In this systematic review, we analyzed and summarized data from the literature regarding the role of inflammatory miRNAs in the pathophysiology of epilepsy, through human and animal studies. Twenty one reports on humans and 44 reports on animals were included in the current analysis. Kainic acid (KA) and pilocarpine were broadly used approaches in inducing epilepsy in animal models. Among upregulated microRNAs, miR-146a, miR-155, and miR-132 were more emphasized for their inflammatory role involved in epilepsy. MiR-221, miR-222, and miR-29a were downregulated and were associated with anti-inflammatory effects. Notably, microRNAs demonstrated tissue-specific expression patterns in different samples, including brain cortex, hippocampus, and body fluids, which is considerable in further investigations in the pathophysiologic and diagnostic roles of inflammatory microRNAs in epilepsy. Furthermore, inflammatory miRNAs regulate critical signaling pathways like TLR4/NF-κB, PI3K/Akt, and IL-1β-mediated neuroinflammation. Conclusively, these findings highlight the possibility of using inflammatory miRNAs as diagnostic biomarkers and therapeutic targets of epilepsies
A Proposed Standard for the Reporting of Structural Equation Models With Ordinal Variables: Why Ordinal Data Should be Treated With Extra Care?
Get PDFEducational researchers, as well as researchers in other disciplines, often work with ordinal data, such as Likert item responses and test item scores. Critical questions arise when researchers attempt to implement statistical models to analyse ordinal data, given that many statistical techniques assume the data analysed to be continuous. Could ordinal data be treated as continuous data, that is, assuming the ordinal data to be continuous and then applying statistical techniques as if analysing continuous data? Why and why not? Focusing on structural equation models (SEMs), particularly confirmatory factor analysis (CFA), this article discusses an ongoing debate on the treatment of ordinal data and reports a short review on the practices of conducting and reporting SEMs, in the context of mathematics education research. The author reviewed 70 publications in mathematics education research that reported a study involving SEMs to analyse ordinal data, but less than half discussed how data were treated or guided readers through the analysis; it is therefore harder to repeat such an analysis and evaluate the results. This article invites methodological discussions on SEMs with ordinal variables in the practices of educational research. Subsequently, a standard for reporting SEMs with ordinal data is proposed, followed by an example. This standard contributes to educational research by enabling researchers (self and others) to evaluate SEMs reported. The example demonstrates, using real-life research data, how two different approaches for analysing ordinal data (as continuous or as a product of discretisation from some continuous distributions) can lead to results that disagree. Introduction Educational researchers often work with observations (e.g., surveys, tests) related to unobserved characteristics (e.g., anxiety, beliefs). Those observations are often measured as ordinal data. Ordinal data indicate ordered categories, such as 'always' to 'never'. For example, Johnny asks his participants to rate 15 items with statements related to their attitudes towards mathematics; each item has five options: 'strongly agree', 'agree', 'neutral', 'disagree', and 'strongly disagree'. He thinks that the items can be grouped into confidence, enjoyment, and motivation. To test this hypothesis, he records his participants' responses as 0-4 and fits the numeric data into a statistical model. In which the items are treated as individual variables and are grouped into three clusters. He uses available computing software with default options to assess his model, and then writes a report of his analysis, including item means and variances. How valid and reliable is Johnny's analysis? What questions arise from the analysis steps? What does an item's mean score of 3.5 mean? Later, Johnny realises that the software has an option for ordered-categorical variables, so he chooses this option and reruns the analysis. This time, the results show that the items can still be grouped into three clusters, but the grouping is different. However, a warning message appears in the software outputs-how does this message impact the validity of the analysis? How should the different results be interpreted
Gaussian mixture model clustering allows accurate semantic image segmentation of wheat kernels from near-infrared hyperspectral images
Get PDFIn this study, an ad-hoc image processing pipeline has been developed and proposed for the purpose of semantically segmenting wheat kernel data acquired through near-infrared hyperspectral imaging (HSI). The Gaussian Mixture Model (GMM), characterized as a soft clustering method, has been employed for this task, yielding noteworthy results in both kernel and germ segmentation. A comparative analysis was conducted, wherein GMM was compared with two hard clustering methods, hierarchical clustering and k-means, as well as other common clustering algorithms prevalent in food HSI applications. Notably, GMM exhibited the highest accuracy, with a Jaccard index of 0.745, surpassing hierarchical clustering at 0.698 and k-means at 0.652. Furthermore, the spectral variations observed in wheat kernel topology can be used for semantic image segmentation, especially in the context of selecting the germ portion within the wheat kernels. These findings carry practical significance for professionals in the fields of hyperspectral imaging (HSI) and machine vision, particularly for food product quality assessment and real-time inspection
Sampling and Estimation on Manifolds using the Langevin Diffusion
Get PDFError bounds are derived for sampling and estimation using a discretization of an intrin-sically defined Langevin diffusion with invariant measure dµ ϕ ∝ e −ϕ dvol g on a compact Riemannian manifold. Two estimators of linear functionals of µ ϕ based on the discretized Markov process are considered: a time-averaging estimator based on a single trajectory and an ensemble-averaging estimator based on multiple independent trajectories. Imposing no restrictions beyond a nominal level of smoothness on ϕ, first-order error bounds, in discretization step size, on the bias and variance/mean-square error of both estimators are derived. The order of error matches the optimal rate in Euclidean and flat spaces, and leads to a first-order bound on distance between the invariant measure µ ϕ and a stationary measure of the discretized Markov process. This order is preserved even upon using retractions when exponential maps are unavailable in closed form, thus enhancing practi-cality of the proposed algorithms. Generality of the proof techniques, which exploit links between two partial differential equations and the semigroup of operators corresponding to the Langevin diffusion, renders them amenable for the study of a more general class of sampling algorithms related to the Langevin diffusion. Conditions for extending analysis to the case of non-compact manifolds are discussed. Numerical illustrations with distributions, log-concave and otherwise, on the manifolds of positive and negative curvature elucidate on the derived bounds and demonstrate practical utility of the sampling algorithm
Deep-eutectic solvents enable tunable control of the micro-mechanical response through electrical actuation
Get PDFActive interactions at liquid-to-solid interfaces can significantly impact the mechanical response of solid substrates. Traditionally, these have been regulated through surface-active media, such as ionic liquids, used in a static (time-invariant) manner that relies on chemical tuning to induce specific mechanochemical responses. This study introduces a novel and sustainable class of Deep Eutectic Solvents (DESs) to demonstrate a dynamic (time-variant) mechanochemical effect, achieved through molecular electro-actuation at the fluid-to-solid interface. The dynamic micro-mechanochemical effect was demonstrated using a DES mixture consisting of citric acid and choline chloride in a 1:1 M ratio, applied to a nickel single-crystal micro-cantilever substrate. The findings show how the DES coating alone induced compressive surface stress, resulting in a 34 % increase in principal stress. More notably, when the substrate surface was polarized with a ±5 V potential, electro-actuation amplified this mechanochemical effect by up to 51 %, confirming a clear dynamic response. Further validation was presented at the macroscale in a polycrystalline material setting, where a similar response was observed. These findings give insight into the possible development of smart surfaces coated with DESs, where a single chemical system can dynamically alter materials’ mechanical response through simple electro-actuation, offering versatile applications across micro and macro scales
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