Yes / In the pharmaceutical industry, enhanced process understanding resulting in superior control of product attributes, has the potential to save up to 20% of process engineering and product development costs during drug development. With the aim of achieving enhanced process understating, a novel approach for granulation of fine powders is presented. First, a mould with the desired particle shape and size is created using 3D printing followed by casting using elastomeric material. The formulation is prepared through wet massing and tested as a thin film on flat elastomeric membranes. The thin film itself can be a product but it also gives a good indication of coating performance before coating the patterned elastic membrane with the formulation i.e., 3D printed elastic mould granulation. Results show that following granulation and drying, granules of controlled size and shape (e.g. cubic and 500 μm), strength, friability and flowability can be formed. The method presented may allow for more robust process development in particle engineering. / Research Development Fund Publication Prize Award winner, December 2018.

Yes / This paper presents the development of a new chatter model using measured cutting forces instead of a mathematical model with empirical nature that describes them. The utilisation of measured cutting forces enables the prediction of real-time chatter conditions and stable machining. The chatter model is validated using fast Fourier transform (FFT) analyses for detection of chatter. The key contribution of the developed chatter model is that it can be incorporated in digital twins for process monitoring and control in order to achieve greater material removal rates and improved surface quality in future industrial applications involving machining processes. / Research Development Fund Publication Prize Award winner, Sep 2020.

Yes / Industry 4.0 promotes highly automated mechanisms for setting up and operating flexible manufacturing systems, using distributed control and data-driven machine intelligence. This paper presents an approach to reconfiguring distributed production systems based on complex product requirements, combining the capabilities of the available production resources. A method for both checking the “realisability” of a product by matching required operations and capabilities, and adapting resources is introduced. The reconfiguration is handled by a multi-agent system, which reflects the distributed nature of the production system and provides an intelligent interface to the user. This is all integrated with a self-adaptation technique for learning how to improve the performance of the production system as part of a reconfiguration. This technique is based on a machine learning algorithm that generalises from past experience on adjustments. The mechanisms of the proposed approach have been evaluated on a distributed robotic manufacturing system, demonstrating their efficacy. Nevertheless, the approach is general and it can be applied to other scenarios. / This work was supported by the SURE Research Projects Fund of the University of Bradford and the European Commission (grant agreement no. 314762). / Research Development Fund Publication Prize Award winner, Nov 2022

Yes / A set of shallow-water equations (SWEs) based on a k-epsilon Reynold stress model is established to simulate the turbulent flows over a complex roughness bed. The fundamental equations are discretized by the second-order finite-difference method (FDM), in which spatial and temporal discretization are conducted by staggered-grid and leap-frog schemes, respectively. The turbulent model in this study stems from the standard k-epsilon model, but is enhanced by replacing the conventional vertical production with a more rigorous and precise generation derived from the energy spectrum and turbulence scales. To verify its effectiveness, the model is applied to compute the turbulence in complex flow surroundings (including a rough bed) in an abrupt bend and in a natural waterway. The comparison of the model results against experimental data and other numerical results shows the robustness and accuracy of the present model in describing hydrodynamic characteristics, especially turbulence features on the complex roughness bottom. / National Key Research and Development Program of China (Grant No: 2016YFE0122500, 2013CB036401 and 2013CB036402), China Postdoctoral Science Foundation (Grant No: 2016M591184) and Programme of Introducing Talents of Discipline to Universities (Grant No: BC2018038) / Research Development Fund Publication Prize Award winner, June 2019.

Yes / Surgical smoke removal algorithms can improve the quality of intra-operative imaging and reduce hazards in image-guided surgery, a highly desirable post-process for many clinical applications. These algorithms also enable effective computer vision tasks for future robotic surgery. In this paper, we present a new unsupervised learning framework for high-quality pixel-wise smoke detection and removal. One of the well recognized grand challenges in using convolutional neural networks (CNNs) for medical image processing is to obtain intra-operative medical imaging datasets for network training and validation, but availability and quality of these datasets are scarce. Our novel training framework does not require ground-truth image pairs. Instead, it learns purely from computer-generated simulation images. This approach opens up new avenues and bridges a substantial gap between conventional non-learning based methods and which requiring prior knowledge gained from extensive training datasets. Inspired by the Generative Adversarial Network (GAN), we have developed a novel generative-collaborative learning scheme that decomposes the de-smoke process into two separate tasks: smoke detection and smoke removal. The detection network is used as prior knowledge, and also as a loss function to maximize its support for training of the smoke removal network. Quantitative and qualitative studies show that the proposed training framework outperforms the state-of-the-art de-smoking approaches including the latest GAN framework (such as PIX2PIX). Although trained on synthetic images, experimental results on clinical images have proved the effectiveness of the proposed network for detecting and removing surgical smoke on both simulated and real-world laparoscopic images. / Research Development Fund Publication Prize Award winner, November 2019.

Yes / Prediction of engine-out emissions with high fidelity from in-cylinder combustion simulations is still a significant challenge early in the engine development process. This paper contributes to this fast evolving body of knowledge by focusing on the evaluation of NOx emissions predictions capability of a Probability Density Function (PDF) based Stochastic Reactor Engine Models (SRM), for a Diesel engine. The research implements a systematic approach to the study of the SRM engine model performance, based on a detailed space-filling design of experiments based sensitivity analysis of both external and internal parameters, evaluating their effects on the accuracy in matching physical measurements of in-cylinder conditions, and NOx emissions output. The approach proposed in this paper introduces an automatic SRM model calibration methodology across the engine operating envelope, based on a multi-objective optimization approach. This aims to exploit opportunities for internal SRM parameters tuning to achieve good overall modelling performance as a trade-off between physical in-cylinder measurements accuracy and the output NOx emissions predictions error. The results from the case study provide a valuable insight into the effectiveness of the SRM model, showing good capability for NOx emissions prediction and trends, while pointing out the critical sensitivity to the external input parameters and modelling conditions. / 41043/R00836 Jaguar Land Rover funded research “MULTI-PHYSICS ENGINE SIMULATION FRAMEWORK: RESEARCH INTO ADVANCED CAE CAPABILITY FOR MULTI-PHYSICS SIMULATION FRAMEWORK TO GENERATE HIGH FIDELITY PREDICTION OF ENGINE-OUT EMISSIONS”, 2016 – 2019. / Research Development Fund Publication Prize Award winner, March 2019.

Yes / Studies of nanosized forms of bismuth (Bi)-containing materials have recently expanded from optical, chemical, electronic, and engineering fields towards biomedicine, as a result of their safety, cost-effective fabrication processes, large surface area, high stability, and high versatility in terms of shape, size, and porosity. Bi, as a nontoxic and inexpensive diamagnetic heavy metal, has been used for the fabrication of various nanoparticles (NPs) with unique structural, physicochemical, and compositional features to combine various properties, such as a favourably high X-ray attenuation coefficient and near-infrared (NIR) absorbance, excellent light-to-heat conversion efficiency, and a long circulation half-life. These features have rendered bismuth-containing nanoparticles (BiNPs) with desirable performance for combined cancer therapy, photothermal and radiation therapy (RT), multimodal imaging, theranostics, drug delivery, biosensing, and tissue engineering. Bismuth oxyhalides (BiOx, where X is Cl, Br or I) and bismuth chalcogenides, including bismuth oxide, bismuth sulfide, bismuth selenide, and bismuth telluride, have been heavily investigated for therapeutic purposes. The pharmacokinetics of these BiNPs can be easily improved via the facile modification of their surfaces with biocompatible polymers and proteins, resulting in enhanced colloidal stability, extended blood circulation, and reduced toxicity. Desirable antibacterial effects, bone regeneration potential, and tumor growth suppression under NIR laser radiation are the main biomedical research areas involving BiNPs that have opened up a new paradigm for their future clinical translation. This review emphasizes the synthesis and state-of-the-art progress related to the biomedical applications of BiNPs with different structures, sizes, and compositions. Furthermore, a comprehensive discussion focusing on challenges and future opportunities is presented. / M.-A. Shahbazi acknowledges financial support from the Academy of Finland (grant no. 317316). P. Figueiredo acknowledges the Finnish Cultural Foundation for its financial support (decision no. 00190246). H. A. Santos acknowledges financial support from the HiLIFE Research Funds, the Sigrid Juse´lius Foundation, and the Academy of Finland (grant no. 317042). / Research Development Fund Publication Prize Award winner, Jan 2020.

Yes / The advent of Internet of Things (IoT) has escalated the information sharing among various smart devices by many folds, irrespective of their geographical locations. Recently, applications like e-healthcare monitoring has attracted wide attention from the research community, where both the security and the effectiveness of the system are greatly imperative. However, to the best of our knowledge none of the existing literature can accomplish both these objectives (e.g., existing systems are not secure against physical attacks). This paper addresses the shortcomings in existing IoT-based healthcare system. We propose an enhanced system by introducing a Physical Unclonable Function (PUF)-based authentication scheme and a data driven fault-tolerant decision-making scheme for designing an IoT-based modern healthcare system. Analyses show that our proposed scheme is more secure and efficient than existing systems. Hence, it will be useful in designing an advanced IoT-based healthcare system. / Supported in part by Singapore Ministry of Education Academic Research Fund Tier 1 (R-263-000- D63-114). / Research Development Fund Publication Prize Award winner, July 2020.

Yes / This paper examines arms trade regulation in the late 19th century and contributes to the literature on norms, arms regulation, humanitarian arms control and arms control as governmentality. I begin by examining the 1890 Brussels Act as an example of the first ‘Matryoshka doll’ of arms trade governance, a specific humanitarian initiative focused on regulating a particular class of weapons in a specified area. I suggest the Act represented an attempt to graft a regulatory arms trade norm onto an established anti-slavery norm and that it was more extensively implemented than has been recognised. I then locate the Act within the second Matryoshka doll of arms trade governance, the broader approach to prohibition operating in the era. In contrast to representations of the period as one of free trade in arms I demonstrate the extensive efforts to restrict the transfer of firearms to colonial subjects. Finally, I demonstrate how mechanisms of prohibition and permission constituted the practices of arms control as governmentality – the third matryoshka doll - where the concern was to define and manage which gradations of people could legitimately own, trade and use which gradations of weapons in what contexts. Overall, the paper challenges the optimistic assumptions in much of the literature on humanitarian arms control and arms trade norms. Instead, I suggest the merger of humanitarianism and arms control can reflect the influence of both good and bad norms; is not necessarily incompatible with colonialism, racism or imperial violence and can be congruent with liberal militarism. / Research Development Fund Publication Prize Award winner.

Yes / Drawing upon concepts of expressive equipment and body image, the aim of this study is to explore how men diagnosed and treated for penile cancer construct their penis and its surgical disfigurement (penectomy). Using maximum variation sampling with the intention to acquire the broadest range of experiences of stage of disease and treatment, 27 cisgender men (aged 48-83, x=63) who had surgical treatment consented for their data to be archived for analysis. From a dramaturgical perspective, the constructionist thematic analysis explored direct and indirect talk about the penis after surgery. The analysis showed that through graphic and sequential narratives of dismemberment revealed, participants constructed a post-surgery period in which they both wanted and did-not-want to see their penis. Additionally, participants constructed themselves managing difficult emotions through others and seeing themselves being rejected by a potentially desiring (female) Other. The findings extend research on male genitals by showing how the post-surgery penis can function as something hidden but visceral and traumatic when revealed. Importantly, this paper illustrates body image as expressive equipment where body and identity are formed in the image of manhood, which is an intersubjective (sexual) object between self and other. / This paper presents independent research commissioned by the National Institute for Health Research (NIHR) under its Research for Patient Benefit (RfPB) Programme (Grant Reference Number PB-PG-0808-17158). / Research Development Fund Publication Prize Award winner, October 2019.