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The frail-LESS (LEss sitting and sarcopenia in frail older adults) remote intervention to improve sarcopenia and maintain independent living via reductions in sedentary behaviour: findings from a randomised controlled feasibility trial
Get PDFThe 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.Electronic supplementary material is available online at: https://bmcgeriatr.biomedcentral.com/articles/10.1186/s12877-024-05310-9#Sec40 .Background:
Sarcopenia leads to functional disability, dependence in activities of daily living (ADL), and is a key contributor to frailty. Reducing and breaking up sedentary time is associated with improved sarcopenia and frailty-related outcomes. The aim of this study was to determine the feasibility of delivering and evaluating a remote sedentary behaviour intervention to improve sarcopenia and independent living in older adults with frailty.
Methods:
A two-arm randomised controlled feasibility trial was conducted with a target of 60 older adults (mean age 74 ± 6 years) with very mild or mild frailty. Participants were randomised to the Frail-LESS (LEss Sitting and Sarcopenia in Frail older adults) intervention or usual care control group for six months. The intervention included tailored feedback on sitting, standing and stepping; an education workbook that included goal setting and action planning; one-to-one health coaching; peer support; and a wearable device to self-monitor sedentary behaviour. Participant recruitment (percentage of eligible individuals recruited), retention and data completion rates were used to assess trial feasibility. Acceptability of the trial was explored through interviews and safety was evaluated via unplanned healthcare utilisation and number of falls. Sitting, standing, stepping and sarcopenia were measured to evaluate potential intervention effects.
Results:
Sixty participants were recruited. Recruitment and retention rates were 72% and 83%, respectively. Completion rates for outcome measures ranged from 70 to 100%. The trial was safe (< 1 fall per participant on average at each timepoint) and trial procedures were acceptable. Descriptive analysis (mean ± SD) showed that daily sitting was 25.1 ± 82.1 min/day lower in the intervention group, and 6.4 ± 60.5 min/day higher in the control group, at 6 months compared with baseline. Hand grip strength and sit-to-stand score were improved by 1.3 ± 2.4 kg and 0.7 ± 1.0, respectively, in the intervention group.
Conclusions:
This study demonstrates the feasibility and safety of delivering and evaluating a remote intervention to reduce and break up sitting in older adults with frailty. The intervention showed evidence towards reducing daily sitting and improving sarcopenia, supporting its evaluation in a definitive randomised controlled trial.
Trial registration:
ISRCTN registry (registration number: ISRCTN17158017). Registered 6th August 2021.Abbeyfield Research Foundatio
Gait event detection accuracy: Effects of amputee gait pattern, terrain and algorithm
Get PDFSupplementary materials are available online at: https://www.sciencedirect.com/science/article/pii/S0021929024004627?via%3Dihub#s0045 .Several kinematic-based algorithms have shown accuracy for gait event detection in unimpaired and pathological gait. However, their validation in subjects with lower limb amputation while walking on different terrains is still limited. The aim of this study was to evaluate the accuracy of three kinematic-based algorithms: Coordinate-Based Algorithm (CBA), Velocity-Based Algorithm (VBA) and High-Pass Filtered Algorithms (HPA) for detection of gait events in subjects with unilateral transtibial amputation walking on different terrains. Twelve subjects with unilateral transtibial amputation, using a hydraulic ankle prosthesis, walked at self-selected walking speed, on level ground and up and down a slope. Detection of Initial Contact (IC) and Foot Off (FO) by the three algorithms for intact and prosthetic limbs was compared with detection by force platforms using the True Error (TE) (time difference in detection). Mean TE found for over 100 events analysed per condition were smaller than 40 ms for both events in all conditions (approximately 6 % of stance phase). Significant interactions (p < 0.01) were found between terrain and algorithm, limb and algorithm, and also a main effect for the algorithm. Post-hoc analyses indicate that the algorithm, the limb and the terrain had an effect on the accuracy in detection. If an accuracy of 40 ms is acceptable for the particular application, then all three algorithms can be used for event detection in amputee gait. However, if accuracy in detection of events is crucial for the intended application, an evaluation of the algorithms in pathological gait walking on the terrain of interest is recommended.This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors
A novel local feature fusion architecture for wind turbine pitch fault diagnosis with redundant feature screening
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The data that support the findings of this study are available from the corresponding author, C. Wen, upon reasonable request.The safe and reliable operation of the pitch system is essential for the stable and efficient operation of a wind turbine (WT). The pitch fault data collected by supervisory control and data acquisition systems (SCADA) often contain a wide variety of variables, leading to redundant features that interfere with the accuracy of final diagnosis results, making it difficult to meet requirements. Also, the problem of extracting only local features while ignoring global information is present in the feature extraction process using the deep Convolutional Neural Network (CNN) model. To address these issues, the global average correlation coefficient is proposed in this article to measure the correlation between multiple variables in SCADA data. By considering the correlation among multiple variables comprehensively, redundant features are effectively eliminated, enhancing the accuracy of fault diagnosis. Furthermore, a new local amplification fusion architecture network (LAFA-Net) based on multi-head attention (MHA) is introduced. An efficient local feature extraction module, designed to enhance the model’s perception of detailed features while maintaining global context information, is first introduced. LAFA-Net integrates the advantages of CNN and MHA, efficiently extracting and fusing valuable features from filtered data for both local and global aspects. Experiments on real pitch fault data demonstrate that the global average correlation coefficient effectively screens out redundant features in the dataset that negatively impact fault diagnosis results, thereby improving diagnosis efficiency and accuracy. The LAFA-Net model, capable of accurately diagnosing multiple types of pitch faults, shows a superior classification effect and accuracy compared to several advanced models, along with a faster convergence speed.This work was supported in part by the European Union’s Horizon 2020 Research and Innovation Programme under Grant 820776 (INTEGRADDE), the Royal Society of the UK, the Alexander von Humboldt Foundation of Germany, the BRIEF Award of Brunel University London in theUK, and the Capacity Building Project of Shanghai Local Colleges and Universities of China under Grant 22010501100
Text Indexing for Long Patterns using Locally Consistent Anchors
Get PDFThe article is available as a preprint, arXiv:2407.11819v1 [cs.DS], available online at https://arxiv.org/abs/2407.11819 , It has not been certified by peer review. Comments: Extended version of a PVLDB 2023 paper. Abstract abridged to satisfy arXiv requirements.In many real-world database systems, a large fraction of the data is represented by strings: sequences of letters over some alphabet. This is because strings can easily encode data arising from different sources. It is often crucial to represent such string datasets in a compact form but also to simultaneously enable fast pattern matching queries. This is the classic text indexing problem. The four absolute measures anyone should pay attention to when designing or implementing a text index are: (i) index space; (ii) query time; (iii) construction space; and (iv) construction time. Unfortunately, however, most (if not all) widely-used indexes (e.g., suffix tree, suffix array, or their compressed counterparts) are not optimized for all four measures simultaneously, as it is difficult to have the best of all four worlds. Here, we take an important step in this direction by showing that text indexing with sampling based on locally consistent anchors (lc-anchors) offers remarkably good performance in all four measures, when we have at hand a lower bound ℓ on the length of the queried patterns -- which is arguably a quite reasonable assumption in practical applications. Our index offers average-case guarantees. In our experiments using real benchmark datasets, we show that it compares favorably based on the four measures to all classic indexes: (compressed) suffix tree; (compressed) suffix array; and the FM-index. Notably, we also present a counterpart of our index with worst-case guarantees based on the lc-anchors notion of partitioning sets. To the best of our knowledge, this is the first index achieving the best of all worlds in the regime where we have at hand a lower bound ℓ on the length of the queried patterns...
A novel neural network architecture utilizing parametric-logarithmic-modulus-based activation function: Theory, algorithm, and applications
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Data will be made available on request.This paper introduces a novel parametric-logarithmic-modulus-based activation function (PLM-AF) designed to significantly enhance the nonlinear expression capabilities of high-dimensional spectroscopy data. A one-dimensional CNN-LSTM (1D-CNN-BiLSTM) model is subsequently developed to capture long-term dependencies within glucose Raman spectroscopy. To the best of our knowledge, this is the first work to simultaneously optimize the predictive performance of the model from the perspectives of both network architecture and activation functions. The effectiveness of the model is comprehensively evaluated against state-of-the-art methods using a public Raman spectroscopy dataset. Compared to the sub-optimal glucose prediction models, the proposed model improves the training root mean square error (RMSE) by 41.89%. The improved prediction accuracy demonstrates that the proposed regression model with the novel PLM-AF can significantly facilitate non-invasive glucose concentration prediction, thereby advancing the auxiliary diagnosis and healthcare industry.This work was supported in part by the National Natural Science Foundation of China under Grant 62073180 and Nantong Natural Science Foundation of China under Grant JC2023073
Study on the energy evolution process and damage constitutive model of concrete-granite composite specimens under uniaxial compression load
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The data underpinning this publication can be accessed from Brunel University London's data repository (Brunelfigshare) under a CC BY license using the DOI of 10.17633/rd.brunel.27939117.The interaction between concrete structures and rock foundations is a crucial research topic for assessing safety and stability in geotechnical and underground engineering. The uniaxial compression tests were conducted on different combination modes (concrete component heights (Hc), interface inclination angle (β), and coarse aggregate contents) to investigate their impact on the mechanical and energy response of concrete–granite composite specimens (CGCSs). This study categorized three failure modes: only concrete component failure (Hc = 80 mm), shear failure along the interface (β = 30°), and simultaneous failure of both components (other combination modes). The fractal dimension (Df) of surface cracks positively correlates with Hc, while the compressive strength (σCGCS) and stiffness (ECGCS) exhibit an inverse trend. The value of Df and σCGCS both exhibit a ''U-shaped'' trend when β ranges from 0° to 90°, whereas the value of ECGCS decreases linearly. Moreover, The value of Df and ECGCS positively correlate with coarse aggregate contents, while the value of σCGCS trends vary non-monotonically increases. The coarse aggregate contents have few effects on energy conversion. Typical brittle failure (β = 0°, β = 30°, and Hc = 20 mm) and ductile failure (other combination modes) are observed. Energy evolution characteristics offer quantitative insight into the damage evolution processes of CGCSs. The piecewise damage constitutive model based on dissipation energy can accurately describe the mechanical response of CGCSs. This study enhances understanding of the mechanical properties, failure characteristics, and energy evolution process of CGCSs under complex combination modes.This work was funded by the National Natural Science Foundation of China (No. 52104084), the Henan Provincial Science and Technology Research Project (No. 232102321128), and the Program for Innovative Research Team (in Science and Technology) in University of Henan Province (No. 22IRTSTHN005)
Comparison of transformation behavior of the peritectic steels with different carbon content and its correlation to the slab quality during solidification
Get PDFIn order to investigate the phase transformation behavior of peritectic steels, we devise an integrated facility for X-ray transmission imaging combined with Laue diffraction analysis and precise temperature control. This integrated facility can measure the temperature at which the delta phase transforms into the gamma phase during solidification with continuous cooling. The investigation of four alloys with different carbon content reveals the dependence of carbon content on the minimum undercooling required for gamma phase formation. As carbon content increases, the amount of undercooling for the peritectic transformation decreases, and the gamma phase onset temperature necessarily increases. X-ray transmission images, which present the growing dendrites and moving delta-to-gamma interface, confirm that the peritectic reaction is likely to occur with high carbon content, leading to the gamma phase formation before the end of solidification.
On the contrary, the low carbon content suppresses the gamma phase formation, and the solid delta and liquid phase exist under equilibrium peritectic temperature. Once after the gamma phase nucleation, the phase change occurs rapidly with increasing undercooling. The delay in gamma phase formation results in massive phase transition and rapid change of interface velocity with a slight variation of undercooling. The fast kinetic of solid phase transformation is associated with a corresponding increase of internal stress, leading to the degradation of slab quality.This research is supported by POSCO steelmaking company in South Korea (Project number: 4.0026102.01)
Local Design of Distributed State Estimators for Linear Discrete Time-Varying Systems Over Binary Sensor Networks: A Set-Membership Approach
Get PDFThis article is concerned with the distributed set-membership estimation problem for a class of discrete time-varying systems over binary sensor networks. For the binary sensors, the cases of fixed and time-varying thresholds are considered. In both the cases, the information useful for state estimation purposes is extracted by utilizing the crossings of binary measurements at two adjacent time instants, and then distributed estimators are constructed for each sensor node with the aid of the available measurements, where a set of vector saturation functions is introduced to resist the adverse effect of outliers during signal transmission. A novel distributed set-membership performance index is provided by averaging over the ellipsoidal constraints of all the sensor nodes, and the local performance analysis method is employed to establish sufficient criteria that guarantee the existence of desired estimators whose parameters are then derived for every node by recursively optimizing certain ellipsoids in the sense of matrix trace. The applicability and feasibility of the distributed set-membership schemes developed in this article are verified by two illustrative examples.10.13039/501100001809-National Natural Science Foundation of China (Grant Number: 62073070, U21A2019, 61933007 and 62273005);
Hainan Province Science and Technology Special Fund of China (Grant Number: ZDYF2022SHFZ105);
Alexander Von Humboldt Foundation of Germany
JSCAN is now IJCC: First issue explores AI and metaverse from the perspective of contracting
Get PDFEditorial.The Journal of Strategic Contracting and Negotiation (JSCAN) was launched in 2015. It was conceived as ‘an international peer-reviewed journal for research and theory about practices that challenge the status quo in strategic contracting and negotiations and the commercial implementation of business strategy or policy’. Fast-forward to 2024, after 22 issues and numerous high-quality scholarly articles and practitioner essays, JSCAN shall carry a new name: International Journal of Commerce and Contracting (IJCC).The authors received no financial support for the research, authorship, and/or publication of this article
MSD-EMA: Multiscale Decoupled Expectation–Maximization Attention for Polyp Segmentation
Get PDFAutomatic polyp segmentation is a crucial technique of computer-aided clinical diagnosis. However, some current polyp segmentation methods cannot accurately extract polyps from colonoscopy images due to the diversity of polyp shapes and sizes, as well as the blurry boundaries caused by the adhesion between polyps and surrounding tissues. To address this issue, we propose a multiscale decoupled expectation-maximization (EM) attention, namely MSD-EMA. There are two advantages of MSD-EMA. First, we design the decoupled EM attention, which decouples attention weights into the sum of pairwise term representing interregional features and unary term representing salient boundary features, thereby extracting boundary features between polyps and surrounding tissues while reducing computational complexity. Second, we propose the parallel collaborative strategy (PCS), which enables MSD-EMA to simultaneously extract sparse and dense feature maps using lower computational complexity. Sparse features are suitable for segmenting small polyps due to filtering out noise interference. Dense features are suitable for capturing large polyps that contain more location information. Comparative experiments are conducted with currently excellent polyp segmentation networks on five publicly available datasets, and the experimental results demonstrate that MSD-EMA can effectively improve polyp segmentation performance. Moreover, MSD-EMA is a plug-and-play module that can be applied to other types of segmentation tasks. The source code is available at https://github.com/EmarkZOU/MSD-EMA.10.13039/501100001809-National Natural Science Foundation of China (Grant Number: 61861024, 62271296 and 62201334);
Scientific Research Program funded by the Education Department of Shaanxi Provincial Government (Grant Number: 23JP022 and 23JP014);
10.13039/501100015401-Key Research and Development Projects of Shaanxi Province (Grant Number: 2021ZDLGY08-07);
10.13039/501100015401-General Project of Key Research and Development Programs in Shaanxi Province, China, Social Development (Grant Number: 2022SF-105)
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