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The short- and long-run cyclical variation of the cross-asset nexus: Mixed-frequency evidence on financial and ‘financialised’ assets
No full textJEL classification: C32; D80; E44; G15; Q02; R33.Data availability:
Data will be made available on request.Supplementary data are available online at: https://www.sciencedirect.com/science/article/pii/S2405851325000066#appSB .We study the dynamic interdependence between stocks, a risky and financial ‘by definition’ asset class, and the ‘financialised’ assets from the real estate and commodity markets. We first introduce a new multivariate corrected Dynamic Conditional Correlations Mixed-Data Sampling (cDCC-MIDAS) model through which we analyse short- and long-run time-varying correlation dynamics among stocks, real estate, and five commodity types with direct implications for risk management and portfolio optimisation. The correlation analysis identifies short- and long-run hedging properties and interdependence types and concludes on strong countercyclical cross-asset interlinkages, highly dependent on the state of the economy in most cases (contagion effects) and weak procyclical connectedness for certain safe-haven assets (flight-to-quality). We further investigate the macro-relevance and crisis-vulnerability of the correlations’ evolution by unveiling the macro-determinants of asset co-movements. The economic environment plays a key role as a contagion or flight-to-quality transmitter, outweighing the effects of economic linkages among assets, while the uncertainty channel intensifies the macro impact on the cross-asset nexus
Anxiety-related attentional characteristics and their relation to freezing of gait in people with Parkinson's: Cross-validation of the Adapted Gait Specific Attentional Profile (G-SAP)
Get PDFData availability statement:
The datasets during and/or analyzed during the current study available from the corresponding author on reasonable request.Supplementary Material is available online at: https://journals.sagepub.com/doi/10.1177/1877718X251326266#supplementary-materials .Background:
Anxiety often exacerbates freezing of gait (FOG) in people with Parkinson's (PwP). Anxiety-related attentional processes and associated processing inefficiencies, like conscious movement processing (CMP) and ruminations, can substantially impact movement control. However, their impact on FOG remains largely unexplored.
Objective:
To validate an adapted 10-item (1–5 Likert scale) Gait-Specific Attentional Profile (G-SAP) in PwP and assess if adapted G-SAP-subscales (Physiological Arousal, CMP, Rumination, and Processing Inefficiencies) are associated with self-reported FOG frequency.
Methods:
We recruited 440 PwP (Mage = 65.5 ± 8.7; 5.8 ± 5.0 years since diagnosis) across the UK. Participants completed the adapted G-SAP and questionnaires on demographics, medical background, and FOG frequency. We assessed adapted G-SAP's internal consistency, structural validity, and subscale scores associations with FOG frequency.
Results:
The adapted G-SAP showed acceptable internal consistency (α≥0.66) and acceptable/good model fit (comparative fit index = 0.976). Physiological Arousal and CMP subscale scores presented weaker correlations for PwP with FOG (PwP + FOG, r = 0.52) compared to PwP without FOG (PwP-FOG, r = 0.77; p = 0.006). Higher Rumination (OR: 1.323, 95%CI: [1.214–1.440]) and Physiological Arousal (OR: 1.195, 95%CI:[1.037–1.377]) were significantly associated with higher FOG frequency, controlling for age, time since diagnosis and balance/gait problems.
Conclusions:
The adapted G-SAP is reliable and convenient to measure and identify potentially maladaptive anxiety-related attentional processes that may impact FOG. Results suggest that PwP who experience more worrisome thoughts and greater physiological arousal in daily life are likelier to freeze. Compared to PwP-FOG, for PwP + FOG high physiological arousal was associated with reduced goal-directed focus of attention. Future research will determine if this is a causal risk factor.Plain language summary:
Anxiety can worsen freezing of gait in people with Parkinson's. It often leads to worrisome thoughts and influences how people pay attention to their walking. We think that these changes in attention can substantially influence peoples’ movement – for better or worse. However, there is a lack of research on this topic, and reliable assessment tools are missing.
Therefore, we tested if we could assess changes in the thoughts and attention of people with Parkinson's, using a questionnaire (Gait-Specific Attentional Profile (adapted G-SAP)), previously used in older adults without Parkinson's. This questionnaire aims to measure people's perception of their physiological arousal (how anxious they feel), conscious movement (attention they direct to walking), rumination (self-preoccupation with worries about failure and expectations of negative consequences), and thinking efficiency (the ability to focus on different tasks). We also investigated if people who experience freezing show different attentional characteristics compared to people who do not experience freezing. Four-hundred and forty people with Parkinson's filled the adapted G-SAP questionnaire. We confirmed the questionnaire's reliability and found that people who indicated to have more worrisome thoughts and greater physiological arousal also experienced freezing more often. Our findings suggest that people with Parkinson's who experience higher rumination are more likely to experience freezing of gait. The adapted G-SAP represents a short and convenient tool for identifying potentially negative attentional and thinking processes that may increase freezing frequency. With further research to better understand the causes of freezing of gait and their relation to rumination and physiological arousal the adapted G-SAP could be used to monitor and test treatment effect on these constructs in the context of FOG frequency.The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This project was supported by Parkinson's UK project grants K-1604 and G-2007, an internal award from the lead institution (Brunel Research Initiative and Enterprise Fund Award). This work was also supported by the National Institute for Health and Care Research (NIHR) Exeter Biomedical Research Centre
SOMMD: An R Package for the Analysis of Molecular Dynamics Simulations using Self-Organising Map
Get PDFData availability:
The MD trajectory data required to run the examples in SOMMD are openly available on Figshare under CC-BY licence, and the accompanying R notebooks in the package include the code to automatically download and process these datasets.Supplementary information:
Supplementary data are available at Bioinformatics online at: https://academic.oup.com/bioinformatics/advance-article/doi/10.1093/bioinformatics/btaf308/8132949?searchresult=1#supplementary-data .Accepted manuscripts:
Accepted manuscripts are PDF versions of the author’s final manuscript, as accepted for publication by the journal but prior to copyediting or typesetting. They can be cited using the author(s), article title, journal title, year of online publication, and DOI. They will be replaced by the final typeset articles, which may therefore contain changes. The DOI will remain the same throughout.Motivation:
Molecular Dynamics (MD) simulations provide critical insights into biomolecular processes but they generate complex high-dimensional data that are often difficult to interpret directly. Dimensionality reduction methods like Principal Component Analysis (PCA), Time-Lagged Independent Component Analysis (TICA) and Self-Organising Maps (SOMs) have helped in extracting essential information on functional dynamics. However, there is a growing need for a user-friendly and flexible framework for SOM-based analyses of MD simulations. Such a framework should offer adaptable workflows, customizable options, and direct integration with a widely adopted analysis software.
Results:
We designed and developed SOMMD, an R package to streamline MD analysis workflows. SOMMD facilitates the interpretation of atomistic trajectories through SOMs, providing tools for each stage of the workflow, from importing a wide range of MD trajectories data types to generating enhanced visualizations. The package also includes three example projects that demonstrate how SOM can be applied in real-world scenarios, including cluster analysis, pathways mapping and transition networks reconstruction.
Availability:
SOMMD is available on CRAN (https://CRAN.R-project.org/package=SOMMD) and on GitHub (https://github.com/alepandini/SOMMD).This project made use of time on HPC granted via the UK High-End Computing Consortium for Biomolecular Simulation, HECBioSim (https://www.hecbiosim.ac.uk), supported by EPSRC [EP/X035603/1]
Enhancing fault detection and localization in MT-MVDC networks using advanced singular spectrum analysis
Get PDFThis paper presents a novel methodology for fault detection, classification, and localization in Multi-Terminal Medium Voltage Direct Current (MT-MVDC) networks. The proposed approach utilizes Singular Spectrum Analysis (SSA) to decompose measured positive and negative pole voltages, isolating the seasonal component that represents the traveling wave. Fault detection is based on comparing this component against a predefined threshold, where minimal fluctuations occur under normal conditions, but significant variations emerge after a fault. Fault classification is achieved by analyzing the rate of change of the line-mode current to distinguish between forward and backward faults. For fault localization, the method leverages traveling wave attenuation and dispersion. The first traveling wave is extracted from the voltage seasonal component, and its spreading behavior over distance is analyzed to compute the curvature rate, enabling precise fault location estimation. The methodology is validated through extensive simulations on an MT-MVDC distribution system using PSCAD/EMTDC. MATLAB is employed for signal processing, and the approach is tested under various fault scenarios, including high fault impedance and extreme external faults. Comparative analysis with existing methods highlights the advantages of the proposed technique in terms of accuracy and robustness
Facilitating Recycling of 6xxx Series Aluminum Alloys by Machine Learning-Based Optimization
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The corresponding author can provide the raw or processed data required to reproduce the findings upon request. Dataset for 6xxx series aluminum alloys can be downloaded from Brunel University of London repository: https://doi.org/10.17633/rd.brunel.28471826.Supplementary Information is available online at: https://link.springer.com/article/10.1007/s40831-025-01112-4#Sec14 .Aluminum alloys throughout the last century have experienced extensive development, owing to their unique strength-to-weight ratio. This led to generating multiple alloy grades. However, large number of grades present challenges when it comes to the recycling of aluminum scrap, which is the current and future trend in aluminum alloy production and application. Therefore, there is an urgent need to decrease the number of alloying grades while preserving their performance. In this study, we designed an optimization loop based on Machine Learning (ML) and material science knowledge for the 292 sets of data collected on 42 grades of 6xxx series aluminum alloys, focusing on their mechanical, service, and technological properties under T5, T6, and T7 tempering conditions. K-means clustering and principal component analysis algorithms were applied to form various clusters of alloys and are further re-clustered into fine sub-clusters. An optimal alloy (OA) for each sub-cluster was identified based on optimization criteria. After successive iteration, we were able to reduce 42 grades of the 6xxx series into a set of 10 OA’s each performing optimally. This method not only support the capability of machine learning in selecting OA’s but also introduce a future direction for recycling practices in the aluminum industry.This research was funded by Brunel University of London, UKRI/EPSRC grant EP/V011804/1 and was carried out within the Circular Metals Centre framework. The corresponding author is grateful to Brunel University of London for providing funding for the scholarship
Visible places: Unpacking global and local embeddedness of civil society actors in Bulgaria
No full text........
The impact of fruit and vegetable intake on healthcare costs and preventive care in older adults: evidence from SHARE data
Get PDFData availability:
No datasets were generated or analysed during the current study.Code availability:
(Software application or custom code) Available upon request.Purpose:
This study aims to investigate the association between daily fruit and vegetable consumption and healthcare utilization among older European adults. Our findings inform policies aimed at optimizing healthcare resource allocation and promoting healthy ageing in Europe's growing elderly population.
Methods:
Leveraging data from the 8th wave of the Survey of Health, Ageing and Retirement in Europe (SHARE) conducted in 2019–2020, this cross-sectional analysis examines associations between daily fruit and vegetable intake and hospitalization rates, hospital length of stay, visits to general practitioners, and specialist consultations.
Results:
Our results reveal no significant difference in hospitalization probability between individuals consuming fruits/vegetables daily versus less frequently. However, among hospitalized individuals, daily consumption is associated with fewer hospitalizations and shorter hospital stays. Moreover, daily fruit and vegetable intake is positively associated with increased likelihood of consulting general practitioners and specialists. This association may be indicative of a broader health consciousness and proactive approach to well-being management among individuals who prioritize dietary choices.
Conclusion:
These findings suggest that while fruit and vegetable consumption alone may not prevent hospitalizations in this segment of the population, it is linked to reduced re-hospitalization risk and shorter inpatient durations when hospitalized. Additionally, a diet rich in fruits and vegetables appears to promote greater engagement with preventive primary and speciality care among older European adults. Overall, the study highlights dietary behaviour as a potential factor influencing healthcare utilization and expenditures for ageing populations.No funds, grants, or other support was received
Meso-scale modelling of FRP-to-concrete bond interfaces
Get PDFThe bond behaviour between fiber-reinforced polymer (FRP) and concrete plays a critical role in the performance of FRP-strengthened reinforced concrete (RC) structures. While extensive research has been conducted on debonding failures, existing studies predominantly treat concrete as homogeneous, neglecting its inherent heterogeneity. This paper proposes an effective meso-scale finite element (FE) model incorporating random aggregate distributions to explicitly account for the heterogeneous nature of concrete. As only the compressive strength of concrete is usually reported in bond tests, a set of equations are identified as a guideline for calculating the material properties of mortar and coarse aggregates, as required by the damage plasticity constitutive relations of materials which are employed to model both coarse aggregates and mortar. The proposed model is validated through simulations of uniaxial tensile and compressive tests of concrete and FRP-to-concrete bonded joint experiments. Results demonstrate that the model’s capability to predict the mesoscopic damage and fracture evolution, as well as the macroscopic load-displacement curves and failure patterns. A parametric study reveals that increasing the coarse aggregate fraction from 30% to 50% enhances bond strength and displacement by 7–8%. This meso-scale approach provides a robust tool for developing bond strength and bond-slip models, incorporating concrete’s meso-structural characteristics.The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was partially funded by National Key Research and Development Program of China (2022YFB3706500), the National Natural Science Foundation of China (No. 52173300, 52178218). The work started at Queen’s University Belfast when the first author, supported by the China Scholarship Council (CSC), was a PhD student under the supervision of the last author
Proportional-Integral-Observer-Based Fusion Estimation for Artificial Neural Networks: Implementing a One-Bit Encoding Scheme
Get PDFThis article is concerned with the proportional-integral-observer (PIO)-based fusion estimation problem for a class of artificial neural networks (ANNs) equipped with multiple sensors, which are constrained by bandwidth and subjected to unknown-but-bounded noises (UBBNs). For the purpose of efficient information communication, an approach known as the one-bit encoding mechanism (OBEM) is proposed that enables the encoding of scalar data using merely a single bit. Then, a local PIO-based set-membership estimator is devised for each sensor node, with the aim of achieving the desired estimation task while considering the possible data distortion due to OBEM and the existence of UBBNs. Subsequently, sufficient conditions are established to ensure the existence and effectiveness of the PIO-based set-membership estimator. Moreover, to enhance the global estimation performance, an ellipsoid-based fusion rule is introduced for all local PIO-based set-membership estimators. The performance of fusion estimation is then analyzed using set theory and the optimization method, leading to the determination of relevant parameters. Finally, the effectiveness and advantages of the proposed estimation algorithm are demonstrated through a simulation example.10.13039/501100001809-National Natural Science Foundation of China (Grant Number: 61933007, 62403318, 12471416 and U21A2019);
Shanghai Pujiang Program of China (Grant Number: 22PJ1411700);
10.13039/501100000288-Royal Society of U.K.;
Alexander von Humboldt Foundation of Germany
Enhancing Social Integration and Well-Being of International Students through Social Networking
Get PDFPresented at the 25th Futures Conference: Futures of Technologies – Mutual Shaping of Socio-Technical Transformations, Turku, Finland, 11 June 2025.International students often face social isolation and cultural challenges when they move away from their home
country and go abroad to pursue educational opportunities. Even though universities promote social
integration, put effort into welcoming and integrating international students into the university environment,
often some students struggle to ‘fit-in’, while others feel a sense of isolation in the absence of a like-minded
social group to interact with. This often leading to student drop-outs, lower grades, and mental well-being related issues. ...Brunel University of Londo
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