Outputs (1249)

A qualitative, theory-based exploration of facilitators and barriers for implementation of pharmacist prescribing in chronic kidney disease. (2024)
Journal Article
AL RAIISI, F., CUNNINGHAM, S. and STEWART, D. 2024. A qualitative, theory-based exploration of facilitators and barriers for implementation of pharmacist prescribing in chronic kidney disease. International journal of clinical pharmacy [online], Latest Article. Available from: https://doi.org/10.1007/s11096-024-01794-y

While there is an accumulation of evidence that pharmacist prescribing is safe and effective, there is a lack of research on processes of implementation into practice, particularly for patients with complex clinical conditions such as chronic kidney... Read More about A qualitative, theory-based exploration of facilitators and barriers for implementation of pharmacist prescribing in chronic kidney disease..

Improved K-means clustering-genetic backpropagation modeling for online state-of-charge estimation of lithium-ion batteries adaptive to low-temperature conditions. (2024)
Journal Article
HAI, N., WANG, S., HUANG, Q., XIE, Y. and FERNANDEZ, C. 2024. Improved K-means clustering-genetic backpropagation modeling for online state-of-charge estimation of lithium-ion batteries adaptive to low-temperature conditions. Journal of energy storage [online], 99(B), article number 113399. Available from: https://doi.org/10.1016/j.est.2024.113399

Accurate state-of-charge (SOC) estimation of lithium-ion batteries (LIBs) in low temperatures is significant to maximize their performance and application. An improved K-means clustering-genetic backpropagation (KMC-GBP) algorithm consisting of five... Read More about Improved K-means clustering-genetic backpropagation modeling for online state-of-charge estimation of lithium-ion batteries adaptive to low-temperature conditions..

Acoustic emission wave propagation in pipeline sections and analysis of the effect of coating and sensor location. (2024)
Journal Article
RAJENDRAN, V., PRATHURU, A., FERNANDEZ, C. and FAISAL, N. [2024]. Acoustic emission wave propagation in pipeline sections and analysis of the effect of coating and sensor location. Nondestructive testing and evaluation [online], Latest Articles. Available from: https://doi.org/10.1080/10589759.2024.2390996

This paper presents an experimental investigation in which acoustic emission (AE) wave was generated through a pencil lead break (PLB) as a point source on two pipeline sections made of mild steel and titanium. The pipelines (bare, epoxy phenolic coa... Read More about Acoustic emission wave propagation in pipeline sections and analysis of the effect of coating and sensor location..

Exploring structures and processes supporting interprofessional education during experiential learning placements for student pharmacists. (2024)
Journal Article
DEPASQUALE, C., ARNOLD, A., CUNNINGHAM, S., JACOB, S.A., BOYTER, A., PORTLOCK, J., POWER, A. and ADDISON, B. [2024]. Exploring structures and processes supporting interprofessional education during experiential learning placements for student pharmacists. American journal of pharmaceutical education [online], Articles in Press. Available from: https://doi.org/10.1016/j.ajpe.2024.101267

The objective of this study was to explore stakeholder views on structures and processes supporting planned and unplanned interprofessional education (IPE) during experiential learning (EL) placements for student pharmacists in Scotland. Online semi-... Read More about Exploring structures and processes supporting interprofessional education during experiential learning placements for student pharmacists..

Battery asynchronous fractional-order thermoelectric coupling modeling and state of charge estimation based on frequency characteristic separation at low temperatures. (2024)
Journal Article
ZENG, J., WANG, S., CAO, W., ZHOU, Y., FERNANDEZ, C. and GUERRERO, J.M. 2024. Battery asynchronous fractional-order thermoelectric coupling modeling and state of charge estimation based on frequency characteristic separation at low temperatures. Energy [online], 307, article number 132730. Available from: https://doi.org/10.1016/j.energy.2024.132730

Due to the widespread application of lithium-ion batteries in new energy vehicles and energy storage fields, fractional-order theory and coupling modeling methods have developed rapidly in battery modeling. This paper proposes an asynchronous fractio... Read More about Battery asynchronous fractional-order thermoelectric coupling modeling and state of charge estimation based on frequency characteristic separation at low temperatures..

An optimized quantum particle swarm optimization–extended Kalman filter algorithm for the online state of charge estimation of high-capacity lithium-ion batteries under varying temperature conditions. (2024)
Journal Article
WU, W., WANG, S., LIU, D., FAN, Y., MO, D. and FERNANDEZ, C. 2024. An optimized quantum particle swarm optimization–extended Kalman filter algorithm for the online state of charge estimation of high-capacity lithium-ion batteries under varying temperature conditions. Ionics [online], Latest Articles. Available from: https://doi.org/10.1007/s11581-024-05749-1

The core focus of the battery management system (BMS) is accurate state of charge (SOC) estimation of the lithium-ion batteries. To solve the problem of improper selection of the noise covariance matrix in the extended Kalman filter (EKF) algorithm,... Read More about An optimized quantum particle swarm optimization–extended Kalman filter algorithm for the online state of charge estimation of high-capacity lithium-ion batteries under varying temperature conditions..

Enhanced multi-constraint dung beetle optimization-kernel extreme learning machine for lithium-ion battery state of health estimation with adaptive enhancement ability. (2024)
Journal Article
MO, D., WANG, S., FAN, Y., TAKYI-ANINAKWA, P., ZHANG, M., WANG, Y. and FERNANDEZ, C. 2024. Enhanced multi-constraint dung beetle optimization-kernel extreme learning machine for lithium-ion battery state of health estimation with adaptive enhancement ability. Energy [online], 307, article number 132723. Available from: https://doi.org/10.1016/j.energy.2024.132723

Accurately estimating the state of health (SOH) of lithium batteries is a critical and challenging task in battery management systems. Data-driven models are widely used for SOH estimation but still suffer from the difficulty of balancing speed, accu... Read More about Enhanced multi-constraint dung beetle optimization-kernel extreme learning machine for lithium-ion battery state of health estimation with adaptive enhancement ability..

A hybrid algorithm for the state of energy estimation of lithium-ion batteries based on improved adaptive-forgotten-factor recursive least squares and particle swarm optimized unscented particle filtering. (2024)
Journal Article
SHEN, X., WANG, S., YU, C., LI, Z. and FERNANDEZ, C. [2024]. A hybrid algorithm for the state of energy estimation of lithium-ion batteries based on improved adaptive-forgotten-factor recursive least squares and particle swarm optimized unscented particle filtering. Ionics [online], Latest Articles. Available from: https://doi.org/10.1007/s11581-024-05716-w

State of energy (SOE) estimation of lithium-ion batteries is the basis of electric vehicle driving range prediction. To improve the estimation accuracy of SOE under complex dynamic working conditions, this paper takes the ternary lithium-ion battery... Read More about A hybrid algorithm for the state of energy estimation of lithium-ion batteries based on improved adaptive-forgotten-factor recursive least squares and particle swarm optimized unscented particle filtering..

An improved forgetting factor recursive least square and extended particle filtering algorithm for accurate lithium-ion battery state of energy estimation. (2024)
Journal Article
SHEN, X., WANG, S., YU, C., LI, Z. and FERNANDEZ, C. [2024]. An improved forgetting factor recursive least square and extended particle filtering algorithm for accurate lithium-ion battery state of energy estimation. Ionics [online], Latest Articles. Available from: https://doi.org/10.1007/s11581-024-05698-9

State of energy (SOE) estimation of lithium-ion batteries is the basis for electric vehicle range prediction. To improve the estimation accuracy of SOE under complex dynamic operating conditions. In this paper, ternary lithium-ion batteries are used... Read More about An improved forgetting factor recursive least square and extended particle filtering algorithm for accurate lithium-ion battery state of energy estimation..

An improved dung beetle optimizer- hybrid kernel least square support vector regression algorithm for state of health estimation of lithium-ion batteries based on variational model decomposition. (2024)
Journal Article
ZHU, T., WANG, S., FAN, Y., HAI, N., HUANG, Q. and FERNANDEZ, C. 2024. An improved dung beetle optimizer- hybrid kernel least square support vector regression algorithm for state of health estimation of lithium-ion batteries based on variational model decomposition. Energy, [online], 306, article 132464. Available from: https://doi.org/10.1016/j.energy.2024.132464

Accurate prediction of the state of health (SOH) of lithium-ion batteries is important for real-time monitoring and safety control of lithium-ion batteries. In this paper, a hybrid kernel least square support vector regression (HKLSSVR) prediction mo... Read More about An improved dung beetle optimizer- hybrid kernel least square support vector regression algorithm for state of health estimation of lithium-ion batteries based on variational model decomposition..