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Superpixel semantics representation and pre-training for vision-language tasks
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Data will be made available on request.A Preprint version submitted to Neurocomputing, October 2, 2024, is available at: arXiv.2310.13447 [v3] (https://arxiv.org/abs/2310.13447). It has not been certified by peer review.The key to integrating visual language tasks is to establish a good alignment strategy. Recently, visual semantic representation has achieved fine-grained visual understanding by dividing grids or image patches. However, the coarse-grained semantic interactions in image space should not be ignored, which hinders the extraction of complex contextual semantic relations at the scene boundaries. This paper proposes superpixels as comprehensive and robust visual primitives, which mine coarse-grained semantic interactions by clustering perceptually similar pixels, speeding up the subsequent processing of primitives. To capture superpixel-level semantic features, we propose a Multiscale Difference Graph Convolutional Network (MDGCN). It allows parsing the entire image as a fine-to-coarse visual hierarchy. To reason actual semantic relations, we reduce potential noise interference by aggregating difference information between adjacent graph nodes. Finally, we propose a multi-level fusion rule in a bottom-up manner to avoid understanding deviation by mining complementary spatial information at different levels. Experiments show that the proposed method can effectively promote the learning of multiple downstream tasks. Encouragingly, our method outperforms previous methods on all metrics.This work was supported by the National Natural Science Foundation of China (91748122)
Bidirectional Alpha Power EEG Neurofeedback During a Focused Attention Meditation Practice in Novices
Get PDFData Availability Statement: The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.Background:. Neurofeedback and meditation practices are techniques aimed at enhancing awareness and self-regulation. Training of alpha power has been found to increase mindfulness outcomes, and increases in alpha power seem relatively consistent during focused attention meditation practices. Considering the commonalities between these self-regulation techniques, we here examined the trainability of alpha power while engaging in a focused attention meditation, allowing novice practitioners to attain self-regulation with an integrated training. In a within-subject design, 31 participants (25 women, 6 men, aged 23.16, range 18–30) engaged in two types of alpha neurofeedback training conditions, one aimed at upregulating alpha, the other aimed at downregulating global alpha absolute power. Results: Linear mixed-effect analyses showed a differential effect of the two neurofeedback training conditions, indicating that alpha power was overall higher during upregulation compared to downregulation training. While differential alpha power was evident “online” during training, there appeared to be no “offline” transfer, as measured during a resting-state recording posttraining. Conclusion: These results provide relevant insights into the applicability of alpha neurofeedback combined with focused attention meditation instructions that may guide future work into the application of neurofeedback approaches for supporting meditation practice.The authors declare no conflict of interest. This work was supported by grants from the Flanders Fund for Scientific Research (FWO projects G079017N and G046321N), an interdisciplinary network project of the KU Leuven (IDN21022) and the Branco Weiss fellowship of the Society in Science–ETH Zurich granted to Kaat Alaerts and the European Varela Awards (Mind & Life Europe) granted to Julio Rodriguez-Larios
Effect of Vestibular Stimulation on Balance and Gait in Parkinson’s Disease: A Systematic Review
Get PDFBackground/Objectives: Parkinson’s Disease (PD) can be associated with balance and gait impairments leading to increased risk of falls. Several studies have reported positive effects of various forms of vestibular stimulation (VS) for improving balance and stability in people with PD (PwP). The purpose of present study was to synthesise the current evidence on the effectiveness of VS, highlighting its potential benefits in improving postural stability and reducing gait impairments in people with Parkinson’s Disease. Method: A systematic search was conducted across databases Cochrane, Medline, PEDro, PubMed, Web of Science, and Google Scholar. Studies were included if they involved PwP at stages 3 or 4 of the Hoehn and Yahr scale, aged 60 years or older. The Risk of Bias (RoB) was assessed using the ROBINS-I tool. The review followed the PRISMA guidelines and the protocol was registered with PROSPERO (CRD42022283898). Results: demonstrated that various forms of VS have shown promise in mitigating symptoms of vestibular dysfunction and improving gait and balance in PwP. However, the overall RoB ranged from moderate to critical, with variations across different domains. Conclusions: While VS appears to offer potential benefits in improving balance and gait in PwP, the presence of biases in the reviewed studies necessitate caution in interpreting the results. Further research should focus on addressing these biases to confirm the therapeutic potential of VS in PD.This research received no external funding
Engineering biology approaches to modulate bacterial biofilms
Get PDFDeclaration of interests:
Brunel University London and R.R.M. have patent applications covering the manipulation of biofilm levels to enhance plastic degradation. The remaining authors have no interests to declare.Building on a productive two decades of advancements in synthetic biology, engineering biology now promises to enable the implementation and scale-up of novel biological systems tailored to tackle urgent global challenges. Here we explore the latest engineering biology approaches for the control and modification of bacterial biofilms with exciting new functionalities.All authors acknowledge support from a Biological Sciences Research Council (BBSRC), UK grant (BB/Y008332/1). R.R.M. is supported by BBSRC grant BB/V007823/1, Natural Environment Research Council grant NE/X010902/1, Medical Research Council grant MR/Y001354/1, and the Academy of Medical Sciences/the Wellcome Trust/the Government Department of Business, Energy and Industrial Strategy/the British Heart Foundation/Diabetes UK Springboard Award [SBF006\1040]
Simulation Exploration Experience (SEE) Introductory Tutorial
Get PDFThis paper presents an introductory tutorial based on the Simulation Exploration Experience (SEE) 2024, highlighting a collaborative effort by NASA, SISO and international academic partners to model lunar facilities and habitats through the High-Level Architecture (HLA) for distributed simulations. Focused on federating simulations of lunar infrastructure, this paper outlines methodical steps for creating and executing models that incorporate communication systems and 3D visualizations to support educational and research initiatives in space exploration. Reflecting on SEE 2024’s advancements, the tutorial emphasizes significant progress in using simulation technology to promote innovation and collaboration across various scientific disciplines. This contribution, intended for discussion at the Winter Simulation Conference (WSC) 2024, showcases the role of HLA runtime infrastructure (RTI) in enabling realistic and interoperable simulation environments, enriching the discourse on simulation education
From Microalgae to Biofuels: Investigating Valorization Pathways Towards Biorefinery Integration
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The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding authors.The rapid growth of the world population led to an exponential growth in industrial activity all around the world. Consequently, CO2 emissions have risen almost 400% since 1950 due to human activities. In this context, microalgae biomass has emerged as a renewable and sustainable feedstock for producing third-generation biofuels. This study explores the laboratory-scale production of bioethanol and biomethane from dried algal biomass. The first step was to evaluate and optimize the production of glucose from the biomass. Thus, three different techniques with three different solvents were tested to identify the most effective and efficient in terms of saccharification yield. With the assistance of an autoclave or a high-temperature water bath and 0.2 M NaOH as a solvent, yields of 79.16 ± 3.03% and 85.73 ± 3.23% were achieved which correspond to 9.24 and 9.80 g/L of glucose, respectively. Furthermore, the most efficient method from the pretreatment step was chosen to carry out a factorial design to produce bioethanol. The experiments showed that the loading of cellulase was of crucial importance to the optimization of the process. Optimized ethanolic fermentation yielded ethanol concentrations up to 4.40 ± 0.28 g/L (76.12 ± 4.90%) (0.3 Μ NaOH, 750 μL/gcellulose and 65 μL/gstarch), demonstrating the critical role of cellulase loading. Biomethane potential (BMP) assays on fermentation residues showed increased yields compared to untreated feedstock, with a maximum methane yield of 217.88 ± 10.40 mL/gVS. Combined energy production from bioethanol and biomethane was calculated at up to 1044.48 kWh/tn of algae feedstock, with biomethane contributing 75.26% to the total output. These findings highlight the potential of integrated algae-based biorefineries to provide scalable and sustainable biofuel solutions, aligning with circular economy principles.This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No. 101084405 (CRONUS)
Overview of Effects of Motor Learning Strategies in Neurologic and Geriatric Populations: A Systematic Mapping Review
Get PDFSupplementary materials are available online at: https://www.sciencedirect.com/science/article/pii/S2590109524000922?via%3Dihub#sec0027 .Objective:
To provide a broad overview of the current state of research regarding the effects of 7 commonly used motor learning strategies to improve functional tasks within older neurologic and geriatric populations.
Data Sources:
PubMed, CINAHL, and Embase were searched.
Study Selection:
A systematic mapping review of randomized controlled trials was conducted regarding the effectiveness of 7 motor learning strategies—errorless learning, analogy learning, observational learning, trial-and-error learning, dual-task learning, discovery learning, and movement imagery—within the geriatric and neurologic population.
Data Extraction:
Two thousand and ninety-nine articles were identified. After screening, 87 articles were included for further analysis. Two reviewers extracted descriptive data regarding the population, type of motor learning strategy/intervention, frequency and total duration intervention, task trained, movement performance measures, assessment time points, and between-group effects of the included studies. The risk of bias 2 tool was used to assess bias; additionally, papers underwent screening for sample size justification.
Data Synthesis:
Identified articles regarding the effects of the targeted motor learning strategies started around the year 2000 and mainly emerged in 2010. Eight populations were included, for example, Parkinson's and stroke. Included studies were not equally balanced: analogy learning (n=2), errorless learning and trial-and-error learning (n=5), mental practice (n=19), observational learning (n=11), discovery learning (n=0), and dual-tasking (n=50). Overall studies showed a moderate-to-high risk of bias. Four studies were deemed sufficiently reliable to interpret effects. Positive trends regarding the effects were observed for dual-tasking, observational learning, and movement imagery.
Conclusions:
Findings show a skewed distribution of studies across motor learning interventions, especially toward dual-tasking. Methodological shortcomings make it difficult to draw firm conclusions regarding the effectiveness of motor learning strategies to improve functional studies. Future researchers are strongly advised to follow guidelines that aid in maintaining methodological quality. Moreover, alternative designs fitting the complex practice situation should be considered.This study was funded by Regieorgaan SIA (Dutch Organization for Scientific Research Applied Research Fund) under grant number RAAK.PUB09.001
Acceptability of a remotely delivered sedentary behaviour intervention to improve sarcopenia and maintain independent living in older adults with frailty: A mixed-methods study
No full textAvailability of data and materials: The datasets supporting the conclusions of this article are available in Figshare, https://doi.org/10.17633/rd.brunel.26028892.v1. The raw qualitative data (transcripts) are not publicly available due to privacy restrictions. Further detail on the qualitative data and analysis that supports the findings of this study are available upon request to the corresponding author....Abbeyfield Research Foundation
The role of emotions in individual and team creativity: A case study of UK fashion designers
No full textThis thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonThe principal objective of this research is to investigate the role of emotions in enhancing creative performance at the micro, meso and macro levels, while also unpacking the relationship between creativity and negative emotions. Negative emotions usually emanate from feelings of failure or inadequacy in the creative process, and as a result, they can be harmful for the creative confidence and self-efficacy of an individual working within a creative team. Nevertheless, experiences of failure can boost individual creativity if an individual can move away from the ‘vicious cycle’ of negative emotions into deep reflection on the reasons for failure. Pivoting from the mere experience of negative emotion to learning from a negative experience can improve the intrinsic motivation of individuals and their creativity.
The contribution of this thesis to existing theory of creativity is a framework which will allow the management of fashion firms to fully comprehend the concept of positive emotions and creativity, as well as emotional numbness and the resulting impact on creative individuals. This could be when they are working individually, or within a team framework, and also considers broader cultural and environmental influences which stem from a macro-level of analysis.
The sample will include creative students who are yet to graduate, alumni and creative individuals who are working as entrepreneurs or in a creative industry. The primary empirical contributions of this thesis reveal the underlying causes of the emergence of emotional numbness in UK fashion firms. These include the rejection of creative ideas, social exclusion, precarity and a communication barrier between creative individuals and management, all of which lead to an overall lack of emotional support for creativity within these firms. Secondly, this research further enriches the concept of emotional numbness by critically addressing the lack of mutual ground between early-stage international fashion designers and international students who are preparing to enter fashion firms and creative leaders who are unable to understand, communicate and provide adequate support. This triggers a need to devise coping mechanisms, not only in fashion or other creative organisations but also in the UK fashion education system
On Bayesian Filtering for Markov Regime Switching Models
Get PDFImportant: e-prints posted on arXiv are not peer-reviewed by arXiv; they should not be relied upon without context to guide clinical practice or health-related behavior and should not be reported in news media as established information without consulting multiple experts in the field.This paper presents a framework for empirical analysis of dynamic macroeconomic models using Bayesian filtering, with a specific focus on the state-space formulation of Dynamic Stochastic General Equilibrium (DSGE) models with multiple regimes. We outline the theoretical foundations of model estimation, provide the details of two families of powerful multiple-regime filters, IMM and GPB, and construct corresponding multiple-regime smoothers. A simulation exercise, based on a prototypical New Keynesian DSGE model, is used to demonstrate the computational robustness of the proposed filters and smoothers and evaluate their accuracy and speed for a selection of filters from each family. We show that the canonical IMM filter is faster and is no less, and often more, accurate than its competitors within IMM and GPB families, the latter including the commonly used Kim and Nelson (1999) filter. Using it with the matching smoother improves the precision in recovering unobserved variables by about 25 percent. Furthermore, applying it to the U.S. 1947-2023 macroeconomic time series, we successfully identify significant past policy shifts including those related to the post-Covid-19 period. Our results demonstrate the practical applicability and potential of the proposed routines in macroeconomic analysis
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