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Multidimensional Benefits of Improved Sanitation: Evaluating 'PEE POWER®' in Kisoro, Uganda (2020)
Journal Article
You, J., Staddon, C., Cook, A., Walker, J., Boulton, J., Powell, W., & Ieropoulos, I. (2020). Multidimensional Benefits of Improved Sanitation: Evaluating 'PEE POWER®' in Kisoro, Uganda. International Journal of Environmental Research and Public Health, 17(7), 2175. https://doi.org/10.3390/ijerph17072175

With 2.3 billion people around the world lacking adequate sanitation services, attention has turned to alternative service provision models. This study suggests an approach for meeting the sanitation challenge, especially as expressed in Sustainable... Read More about Multidimensional Benefits of Improved Sanitation: Evaluating 'PEE POWER®' in Kisoro, Uganda.

Microbial Fuel Cell anodic bacterial community and antibacterial agents: resilience and vulnerability test (2020)
Journal Article
Obata, O., Greenman, J., Ieropoulos, Y., Kurt, H., & Chandran, K. (in press). Microbial Fuel Cell anodic bacterial community and antibacterial agents: resilience and vulnerability test. Bioelectrochemistry,

This study evaluates the fate of certain bactericidal agents introduced into microbial fuel cell (MFC) cascades and the response of the microbial community. We tested the response of functioning urine fed MFC cascades using two very different bacteri... Read More about Microbial Fuel Cell anodic bacterial community and antibacterial agents: resilience and vulnerability test.

A holistic evaluation of the impact of UK renewable strategy on emissions from compression ignition engines (2020)
Journal Article
Van Niekerk, A. S., & Kay, P. J. (in press). A holistic evaluation of the impact of UK renewable strategy on emissions from compression ignition engines. Fuel,

Reduction in fossil fuels, contributing to greenhouse gases, and improvement of air quality from vehicle emissions is of growing concern worldwide. This has led to the introduction of several binding and non-binding agreements, such as the Renewable... Read More about A holistic evaluation of the impact of UK renewable strategy on emissions from compression ignition engines.

Above-ground biomass estimation and yield prediction in potato by using UAV-based RGB and hyperspectral imaging (2020)
Journal Article
Li, B., Xu, X., Zhang, L., Han, J., Bian, C., Li, G., …Jin, L. (2020). Above-ground biomass estimation and yield prediction in potato by using UAV-based RGB and hyperspectral imaging. ISPRS Journal of Photogrammetry and Remote Sensing, 162, 161-172. https://doi.org/10.1016/j.isprsjprs.2020.02.013

© 2020 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS) Rapid and accurate biomass and yield estimation facilitates efficient plant phenotyping and site-specific crop management. A low altitude unmanned aerial vehicle (UAV) w... Read More about Above-ground biomass estimation and yield prediction in potato by using UAV-based RGB and hyperspectral imaging.

Genetic and phenotypic associations between root architecture, arbuscular mycorrhizal fungi colonisation and low phosphate tolerance in strawberry (Fragaria× ananassa) (2020)
Journal Article
Li, B. (in press). Genetic and phenotypic associations between root architecture, arbuscular mycorrhizal fungi colonisation and low phosphate tolerance in strawberry (Fragaria× ananassa). BMC Plant Biology,

Background Phosphate is an essential plant macronutrient required to achieve maximum crop yield. Roots are able to uptake soil phosphate from the immediate root area, thus creating a nutrient depletion zone. Many plants are able to exploit phosphate... Read More about Genetic and phenotypic associations between root architecture, arbuscular mycorrhizal fungi colonisation and low phosphate tolerance in strawberry (Fragaria× ananassa).

Microbial fuel cell stack performance enhancement through carbon veil anode modification with activated carbon powder (2020)
Journal Article
Gajda, I., Greenman, J., & Ieropoulos, I. (2020). Microbial fuel cell stack performance enhancement through carbon veil anode modification with activated carbon powder. Applied Energy, 262, https://doi.org/10.1016/j.apenergy.2019.114475

The chemical energy contained in urine can be efficiently extracted into direct electricity by Microbial Fuel Cell stacks to reach usable power levels for practical implementation and a decentralised power source in remote locations. Herein, a novel... Read More about Microbial fuel cell stack performance enhancement through carbon veil anode modification with activated carbon powder.

A composite feedback approach to stabilize nonholonomic systems with time varying time delays and nonlinear disturbances (2020)
Journal Article
Rasoolinasab, S., Mobayen, S., Fekih, A., Narayan, P., & Yao, Y. (in press). A composite feedback approach to stabilize nonholonomic systems with time varying time delays and nonlinear disturbances. ISA Transactions, https://doi.org/10.1016/j.isatra.2020.02.009

In this work, we propose a robust stabilizer for nonholonomic systems with time varying time delays and nonlinear disturbances. The proposed approach implements a composite nonlinear feedback structure in which a linear controller is designed to yiel... Read More about A composite feedback approach to stabilize nonholonomic systems with time varying time delays and nonlinear disturbances.

Optimisation of the internal structure of ceramic membranes for electricity production in urine-fed microbial fuel cells (2020)
Journal Article
Salar-García, M. J., & Ieropoulos, I. (2020). Optimisation of the internal structure of ceramic membranes for electricity production in urine-fed microbial fuel cells. Journal of Power Sources, 451, https://doi.org/10.1016/j.jpowsour.2020.227741

The need to find a feasible alternative to commercial membranes for microbial fuel cells (MFCs) poses an important challenge for the practical implementation of this technology. This work aims to analyse the influence of the internal structure of low... Read More about Optimisation of the internal structure of ceramic membranes for electricity production in urine-fed microbial fuel cells.

The Pre-BRA (pre-pectoral Breast Reconstruction EvAluation) feasibility study: protocol for a mixed-methods IDEAL 2a/2b prospective cohort study to determine the safety and effectiveness of prepectoral implant-based breast reconstruction (2020)
Journal Article
Harvey, K. L., Mills, N., White, P., Holcombe, C., Potter, S., & The Pre-BRA Feasibility Study Steering Group, . (2020). The Pre-BRA (pre-pectoral Breast Reconstruction EvAluation) feasibility study: protocol for a mixed-methods IDEAL 2a/2b prospective cohort study to determine the safety and effectiveness of prepectoral implant-based breast reconstruction. BMJ Open, 10(1), e033641. https://doi.org/10.1136/bmjopen-2019-033641

© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY. Published by BMJ. INTRODUCTION: Implant-based breast reconstruction is the most commonly performed reconstructive technique worldwide. Subpectoral reconstruction with mesh is the... Read More about The Pre-BRA (pre-pectoral Breast Reconstruction EvAluation) feasibility study: protocol for a mixed-methods IDEAL 2a/2b prospective cohort study to determine the safety and effectiveness of prepectoral implant-based breast reconstruction.

Designing ethical social robots - A longitudinal field study with older adults (2020)
Journal Article
van Maris, A., Zook, N., Caleb-Solly, P., Studley, M., Winfield, A., & Dogramadzi, S. (2020). Designing ethical social robots - A longitudinal field study with older adults. Frontiers in Robotics and AI, 7, https://doi.org/10.3389/frobt.2020.00001

Emotional deception and emotional attachment are regarded as ethical concerns in human robot interaction. Considering these concerns is essential, particularly as little is known about longitudinal effects of interactions with social robots. We ran a... Read More about Designing ethical social robots - A longitudinal field study with older adults.

Neural learning enhanced variable admittance control for human-robot collaboration (2020)
Journal Article
Chen, X., Wang, N., Cheng, H., & Yang, C. (2020). Neural learning enhanced variable admittance control for human-robot collaboration. IEEE Access, 8, 25727-25737. https://doi.org/10.1109/access.2020.2969085

© 2013 IEEE. In this paper, we propose a novel strategy for human-robot impedance mapping to realize an effective execution of human-robot collaboration. The endpoint stiffness of the human arm impedance is estimated according to the configurations o... Read More about Neural learning enhanced variable admittance control for human-robot collaboration.

Long-term bio-power of ceramic microbial fuel cells in individual and stacked configurations (2020)
Journal Article
Gajda, I., Obata, O., Jose Salar-Garcia, M., Greenman, J., & Ieropoulos, I. A. (2020). Long-term bio-power of ceramic microbial fuel cells in individual and stacked configurations. Bioelectrochemistry, 133, https://doi.org/10.1016/j.bioelechem.2020.107459

© 2020 The Authors In order to improve the potential of Microbial Fuel Cells (MFCs) as an applicable technology, the main challenge is to engineer practical systems for bioenergy production at larger scales and to test how the prototypes withstand th... Read More about Long-term bio-power of ceramic microbial fuel cells in individual and stacked configurations.

A non-contact impedimetric biosensing system for classification of toxins associated with cytotoxicity testing (2020)
Journal Article
Gasser, A., Eveness, J., Kiely, J., Attwood, D., & Luxton, R. (2020). A non-contact impedimetric biosensing system for classification of toxins associated with cytotoxicity testing. Bioelectrochemistry, 133, 107448. https://doi.org/10.1016/j.bioelechem.2019.107448

© 2019 We report on a novel impedance spectroscopy measurement and data analysis technique for cytotoxicity testing. The technique combines non-contact measurement with real-time impedance data analysis based on the toxin dose dependency of the outpu... Read More about A non-contact impedimetric biosensing system for classification of toxins associated with cytotoxicity testing.

Development of efficient electroactive biofilm in urine-fed microbial fuel cell cascades for bioelectricity generation (2020)
Journal Article
Obata, O., Salar-Garcia, M. J., Greenman, J., Kurt, H., Chandran, K., & Ieropoulos, I. (2020). Development of efficient electroactive biofilm in urine-fed microbial fuel cell cascades for bioelectricity generation. Journal of Environmental Management, 258, https://doi.org/10.1016/j.jenvman.2019.109992

The Microbial fuel cell (MFC) technology harnesses the potential of some naturally occurring bacteria for electricity generation. Digested sludge is commonly used as the inoculum to initiate the process. There are, however, health hazards and practic... Read More about Development of efficient electroactive biofilm in urine-fed microbial fuel cell cascades for bioelectricity generation.

U -Model-Based Finite-Time Control for Nonlinear Valve-Controlled Hydraulic Servosystem (2020)
Journal Article
Yan, H., Li, J., Nouri, H., & Xu, L. (2020). U -Model-Based Finite-Time Control for Nonlinear Valve-Controlled Hydraulic Servosystem. Mathematical Problems in Engineering, 2020, 1-12. https://doi.org/10.1155/2020/7083639

© 2020 Hao Yan et al. Valve-controlled servosystems are widely used in dynamic tracking, but, not properly studied, nonlinearity, perturbation of internal parameters, and external disturbance have significant impacts on the control performance and ch... Read More about U -Model-Based Finite-Time Control for Nonlinear Valve-Controlled Hydraulic Servosystem.

Tracking changes in user activity from unlabelled smart home sensor data using unsupervised learning methods (2020)
Journal Article
Caleb-Solly, P., Gupta, P., & McClatchey, R. (2020). Tracking changes in user activity from unlabelled smart home sensor data using unsupervised learning methods. Neural Computing and Applications, https://doi.org/10.1007/s00521-020-04737-6

© 2020, The Author(s). This paper investigates the utility of unsupervised machine learning and data visualisation for tracking changes in user activity over time. This is done through analysing unlabelled data generated from passive and ambient smar... Read More about Tracking changes in user activity from unlabelled smart home sensor data using unsupervised learning methods.


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