19684 research outputs found
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Multi-defect reconstruction in nondestructive testing:an interpretable neural network approach
No full textGuided wave tomography (GWT) methods for precise multi-defect reconstruction are crucial for structural health monitoring. In this work, an improved physics-informed wave tomography framework (PIWT) is proposed for the quantitative reconstruction of multiple defects in plates. A trunk-branch network is employed to reconstruct the wave travel time and velocity field by synergizing the waveguide governing equations and the real travel time data from sensors. This approach speeds up the network convergence of loss function which includes the travel time data, its first-order derivatives, and the physical principle of wave equations to constrain the space of parameters for accurate defect reconstruction. Based on simulation data, the results demonstrate that PIWT achieves the highly accurate defect with the errors of 4.25% in position and 5.5% in depth. Also, experimental validations are conducted to demonstrate the feasibility of PIWT with a defect position error of less than 1.7% and depth location error under 15%. Furthermore, uniform manifold approximation and projection is applied to enable a clear visualization of trajectories representing the defect reconstruction convergence, thereby revealing how incremental sensor data enhance the model’s capability to approximate the true solution. This interpretation provides useful insights into the latent dynamics to bridge the gap between the black-box nature of deep neural networks and the need for transparent and explainable AI, ultimately reinforcing confidence in the model's applicability for broader engineering applications.</p
Bi-stability of two coupled functionally graded plate-type MEMS under opposing differential pressure
No full textSnap-through instability, normally observable in initially curved micro-plates, can be utilized as a sensing mechanism. Given the higher stiffness of curved structures in comparison to flat ones, this mechanism faces a serious limitation of low sensitivity. It has recently been shown that pressurized flat micro-plates are able to face snap-through instability and benefit from high sensitivity. Therefore, the present paper aims to investigate the bi-stability of two pressurized electrostatically coupled flat micro-plates for the first time. The micro-plates are both made of functionally graded materials, and the influences of small scales are accounted for based on the modified couple stress theory. Adopting a Galerkin-based two-degree-of-freedom reduced order model containing thirty-eight approximating functions, equilibrium, stability and free vibrations of the system are assessed. The convergence of the generated ROM is studied and its outcomes are validated by those simulated in COMSOL Multiphysics as well as the results available in the literature. Aside from the expectable simultaneous pull-in instability, where the electrodes stick to each other at the pull-in state, the results also illustrate a new and interesting unstable behavior where the micro-plates with different thicknesses experience snapping behavior simultaneously.</p
The economic and welfare impact of investment in transport infrastructure in Africa:a dynamic computable general equilibrium model analysis
No full textThis study investigates the effects of public investment in transport infrastructure in six African countries using a dynamic computable general equilibrium model. The analysis calculates externality coefficients for each period to assess the impact on sectoral output and other economic variables. The findings suggest that the effectiveness of infrastructure investment depends on initial infrastructure levels and national production structure. Notably, transport investment funded through value-added tax generates the highest externalities, leading to increased output, private investment, household income, and welfare. However, the overall growth rate decreases over time. The study also highlights a potential risk of Dutch Disease when relying on external debt for transport infrastructure development in certain countries, emphasizing the importance of domestic financing. The findings suggest that governments should prioritize VAT financing for transport infrastructure, focus on productive infrastructure, and carefully assess potential crowding-out effects
A novel multi-source sensor correlation adaptive fusion framework with uncertainty quantification for intelligent fault diagnosis
No full textIntelligent fault diagnosis using multi-source sensor fusion holds significant promise but faces challenges related to reliability due to variations in signal quality across sensors and inconsistencies in fault features. To tackle these issues, a multi-source sensor correlation adaptive fusion (MSCAF) framework with uncertainty quantification is proposed to enhance identification trustworthiness for intelligent fault diagnosis. The proposed MSCAF integrates Dempster–Shafer theory with Dirichlet distribution to model sensor uncertainty and split multi-source sensors into high-confidence and low-confidence sensors based on the consistency of cross-sensor fault information. High-confidence sensors are given greater weight, ensuring more reliable fusion. Then, the reward and penalty functions are introduced to assess their correlation weights. Meanwhile, Convolutional and graph neural networks are employed to enhance feature extraction and output category probabilities, which can ensure robust fusion across varying diagnostic scenarios. This approach allows adaptive weighting, optimizes fusion reliability, and enables manual intervention for low-confidence sensors. Experimental results demonstrate that the proposed MSCAF achieves superior diagnostic performance compared to state-of-the-art methods, confirming its efficacy in extracting reliable features with uncertainty quantification for intelligent fault diagnosis.</p
Contemporary Approaches to Metal Music Mixing and Production:Heavy Metal, Death Metal, and Metalcore
No full textWith a focus on traditional heavy metal, death metal, and metalcore, this chapter examines contemporary metal music production and explores overarching concepts and approaches specific to individual subgenres or producers. Guided by mixing walkthrough videos from the educational provider “Nail the Mix,” three productions per subgenre are analyzed. The analysis demonstrates how producers take typical metal features such as heaviness, hyperreal precision, and perceived brutality and aggression, and blend these qualities with additional sonic attributes, including atmosphere, excitement, and groove. The findings suggest that contemporary productions achieve maximum impact through hyperreal elements—inhumanly precise performances, with larger-than-life drum sounds and particularly dense walls of guitars—but carefully balance these with natural elements that preserve the performers’ authenticity and human qualities, which aid the listener’s ability to ‘connect’ with the music. The wealth of aesthetic and technical considerations, discussions, and decisions that have led to the result heard on the final record tends to be of no great concern to the casual or non-technical listener. Nevertheless, all listeners benefit from the high standard common and expected in contemporary metal music production
Evaluating the combustion characteristics of Prosopis Juliflora biodiesel with diethyl ether additives in diesel engines
No full textFossil fuels contribute heavily to global greenhouse gas emissions and their fast depletion necessitates sustainable alternatives. Biodiesel produced from non-edible oils like those of invasive plant species can provide renewable options without concerns of food security or land-use changes. This study experimentally investigates the combustion characteristics of biodiesel derived from Prosopis Juliflora (PJ), an invasive shrub in Ethiopia, when blended with diesel and diethyl ether (DEE) additive. The primary objective is to optimize the combustion of PJ biodiesel in a diesel engine by identifying the optimal DEE concentration and analyzing its impact on combustion parameters. Biodiesel was produced from PJ seeds through transesterification and blended in a 20 % ratio with diesel fuel. DEE was added to this mixture in varying concentrations (5 %, 10 %, 15 %, and 20 %). The combustion characteristics, including cylinder pressure and heat release rate (HRR), were evaluated on a single-cylinder diesel engine at a constant speed of 2600 rpm under different engine loads. The results demonstrate that a 10 % DEE blend yields the most significant improvement, with a 6.5 % increase in peak cylinder pressure and a 4.7 % rise in heat release rate, compared to baseline diesel. Furthermore, engine brake power output showed maximum enhancement at this DEE concentration. The improved combustion is attributed to the synergistic effects of PJ biodiesel's high cetane number and DEE's low viscosity and high volatility, which reduce ignition delay and enhance fuel atomization. This study provides the first comprehensive investigation into the combustion optimization of PJ biodiesel with DEE additives, demonstrating its potential as a sustainable, renewable alternative to petrodiesel without requiring engine modifications. Such non-edible biodiesel-ether blends provide feasible renewable substitutes to petrodiesel.</p
Incorporating the principles of Spiritually Competent Practice in mental healthcare:A qualitative exploration with service users
No full textThough service users may view them as an important aspect of care, spiritual issues are often neglected by mental health professionals. This study explored the experiences and perceptions of mental health service users in the United Kingdom around the integration of spirituality in their care. Two new concepts which support the implementation of spirituality into clinical practice; “Spiritually Competent Practice” and “Availability and Vulnerability”, were also examined. Qualitative data were obtained via a web-based survey (n=170) and semi-structured interviews (n=6) carried out during 2021. The data were analysed thematically and organised into four overarching themes: Spirituality and mental health care, Perceptions of spirituality, Spiritually Competent Practice and Availability and Vulnerability. Findings in this study showed that service users valued the integration of spirituality into mental healthcare and saw the recognition of individuals’ spiritual needs as important, but reported this was lacking in their experience. Participants provided rich and nuanced reflections on the concepts of “Spiritually Competent Practice” and “Availability and Vulnerability” as a means to address this gap. Findings pointed to the need for adequate training to ensure the implementation of these concepts into practice is both evidence-informed and resonant with the service user.<br/
Adaptive multi-domain capacity estimation for battery energy storage system based on multi-scale random sequence feature fusion
No full textMonitoring battery capacity degradation in lithium-ion battery energy storage systems (BESSs) is crucial for ensuring safe and reliable operations. However, conventional data-driven methods primarily focus on single-domain estimation and feature engineering from fixed charging/discharging stages, limiting their adaptability in real-world scenarios. Therefore, this paper proposes an adaptive multi-domain capacity estimation method for BESSs based on multi-scale random sequence feature fusion. Firstly, this paper proposes the adaptive multi-domain capacity estimation theory, which utilizes the Pearson correlation coefficient (PCC) for health feature screening and maximum mean discrepancy (MMD) for domain discrepancy identification and domain classification. Secondly, an optimal random sequence feature is proposed based on short-duration raw voltage and incremental capacity, considering the effects of both sampling interval and duration. Subsequently, a multi-scale convolutional neural network (MSCNN) is developed to fuse ageing information from the random sequence feature and enable accurate adaptive multi-domain capacity estimation. Finally, the validation is conducted using 130 batteries operating under various working conditions, and it shows the proposed method is more robust compared to the single-domain estimation. The overall RMSE and MAE are reduced to within 1.53 % and 1.18 %, with the overall R2 value up to 99 %. This demonstrates the superiority of the proposed method for real-world applications.</p
A novel approach for sun gear fault localization using on-rotor sensing and tidal periods effect
No full textDue to the complex structure of planetary gearboxes, fault localization through vibration analysis presents certain challenges. Existing methods rely on absolute phase references provided by external laser tachometers, which are challenging to implement in complex industrial settings. To overcome these limitations, this study introduces a novel method for fault localization in planetary gearboxes utilizing a single On-Rotor Sensing (ORS) sensor. This method utilizes ORS technology to capture high signal-to-noise ratio vibration signals and employs position information derived from changes in gravitational acceleration sensed by the sensor as the absolute phase reference for locating faulty sun gear teeth. Subsequently, the phase relationships between the extracted and enhanced fault impulse signals from the vibration signals and the absolute phase reference were analyzed. By integrating the effects of tidal periods effect, encodings for the number of single-tooth meshings lagging behind the absolute phase reference at different positions of the faulty sun gear tooth are derived. Finally, two indicators, mean Spearman coefficient (MSC) and mean encoding value (MEV), are employed to locate the faulty sun gear tooth. The proposed method is validated on a planetary gearbox test rig with the sun gear fault exhibiting in different gear tooth, showing the proposed method can effectively identify the potential faulty sun gear tooth.</p
Adolescents’ and Young Adults’ Adherence to Medication During the Transition to Adult Healthcare:A Developmentally Appropriate Framework for Optimising Adherence-Promoting Interventions
No full textFor adolescents and young adults (AYA) with any health condition, it is important that they learn to manage their condition and healthcare as they transition into adulthood. For AYA with childhood-onset long-term conditions, this is also fundamental for a successful transition from child- to adult-centred services, as this period is associated with a decline in important health behaviours, such as medication adherence, which in turn are associated with poorer clinical outcomes and increased mortality. Current evidence suggests that, even though AYA are at higher risk for non-adherence than other age groups, existing interventions are less likely to be effective, or may bring about more modest benefits, for AYA compared with younger children and older adults. There is still a need for novel, innovative approaches to medication adherence that can help better meet the unique needs of AYA groups. We suggest that developmentally informed and developmentally tailored approaches may offer a promising avenue to achieve this. The most widely reported AYA adherence issues are deeply intertwined with the different stages of AYA biopsychosocial development and, therefore, AYA development can be understood as a common thread underlying AYA adherence issues. Ensuring that AYA adherence-promoting interventions are relative to an ongoing developmental assessment is crucial, not only to better meet AYA needs as they gradually prepare for their transfer to adult care, but also to continue to do so in the often forgotten third phase of transitional care (i.e. following transfer) well into their late adolescence and young adulthood.</p
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