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Patients as qualitative data analysts: Developing a method for a process evaluation of the 'Improving the Safety and Continuity of Medicines management at care Transitions' (ISCOMAT) cluster randomised control trial
Get PDFYesHow to meaningfully partner with patients as data analysts remains obscure. A process evaluation of the ‘Improving the Safety and Continuity Of Medicines management at care Transitions’ (ISCOMAT) cluster randomised control trial of an intervention for improving medicines use for people living with heart failure is being conducted. The intervention includes patient held information on heart medicines and care, enhanced communication between hospital and community pharmacists, and increased engagement of community pharmacists with patient care post-hospital discharge. ISCOMAT patients living with heart failure were interviewed about experiences with the intervention. We sought to gain insights from patients on data collected to enhance our understanding of experiences with the intervention.
To develop a method for involving patients as analysts of qualitative data in a process evaluation.
Design:
Patients and researchers co-analysed qualitative data. A framework method was applied involving; familiarisation, coding, developing an analytical framework and interpretation. The process was facilitated through home working and a workshop with a training component.
Results:
The co-designed framework enabled researchers to map all further patient interview data. Patients' specialist knowledge enhanced understanding of how the ISCOMAT intervention can be best implemented.
Conclusions:
Patients’ unique experiences can enhance validity and rigour in data analysis through sharing their interpretations of qualitative data. The involvement process is crucial in elucidating knowledge and avoiding tokenism. As analysts, patients gain an appreciation of research processes, building trust between researchers and patients. Group dynamics and involving patients throughout the whole research process are important considerations.NIHR Grant RP-PG-0514-20009. NIHR Yorkshire and Humber Patient Safety Translational Research Centre
A planar dual-polarized phased array with broad bandwidth and quasi end-fire radiation for 5G mobile handsets
Get PDFYesA planar dual-polarized phased array is proposed for 5G cellular communications. The array has the properties of dual-polarization, wideband and quasi end-fire radiation, which is printed on one side of a single-layer substrate. The design contains two 8-element sub-arrays including horizontally polarized end-fire dipole antennas and vertically polarized end-fire periodic slot antennas, employed on the PCB ground plane of the 5G mobile platform. Both sub-arrays provide wide bandwidth to cover 28 and 38 GHz (promising 5G candidate bands). The -10 dB impedance bandwidth of the proposed CPW-fed dipole and slot antennas are 26.5-39.5 GHz and 27.1-45.5 GHz, respectively. Moreover, for -6 dB impedance bandwidth, these values could be more than 20 GHz (24.4-46.4 GHz for the dipole antenna) and 70 GHz (22.3-95 GHz for the slot antenna). The fundamental characteristics of the proposed dual-polarized 5G antenna array in terms of the impedance bandwidth, realized gain, polarization, radiation pattern, and beam steering are investigated and good results are obtained. The clearance of the proposed dual-polarized 5G antenna array is less than 4.5 mm which is sufficient for cellular applications.This work is partially supported by the InnovationsFonden project of Reconfigurable Arrays for Next Generation Efficiency (RANGE), AAU Young Talent Program, and European Union's Horizon 2020 research and innovation programme under grant agreement H2020-MSCA-ITN-2016SECRET-722424
Lattice-Boltzmann coupled models for advection-diffusion flow on a wide range of Péclet numbers
Get PDFYesTraditional Lattice-Boltzmann modelling of advection-diffusion flow is affected by numerical instability if the advective term becomes dominant over the diffusive (i.e., high-Péclet flow). To overcome the problem, two 3D one-way coupled models are proposed. In a traditional model, a Lattice-Boltzmann Navier-Stokes solver is coupled to a Lattice-Boltzmann advection-diffusion model. In a novel model, the Lattice-Boltzmann Navier-Stokes solver is coupled to an explicit finite-difference algorithm for advection-diffusion. The finite-difference algorithm also includes a novel approach to mitigate the numerical diffusivity connected with the upwind differentiation scheme
A Proposed IoT Architecture for Effective Energy Management in Smart Microgrids
Get PDFyesThe current electricity grid suffers from numerous challenges due to the lack of an effective energy management strategy that is able to match the generated power to the load demand. This problem becomes more pronounced with microgrids, where the variability of the load is obvious and the generation is mostly coming from renewables, as it depends on the usage of distributed energy sources. Building a smart microgrid would be much more economically feasible than converting the large electricity grid into a smart grid, as it would require huge investments in replacing legacy equipment with smart equipment. In this paper, application of Internet of Things (IoT) technology in different parts of the microgrid is carried out to achieve an effective IoT architecture in addition to proposing the Internet-of-Asset (IoA) concept that will be able to convert any legacy asset into a smart IoT-ready one. This will allow the effective connection of all assets to a cloud-based IoT. The role of which is to perform computations and big data analysis on the collected data from across the smart microgrid to send effective energy management and control commands to different controllers. Then the IoT cloud will send control actions to solve microgrid's technical issues such as solving energy mismatch problem by setting prediction models, increasing power quality by the effective commitment of DERs and eliminating load shedding by turning off only unnecessary loads so consumers won't suffer from power outages. The benefits of using IoT on various parts within the microgrid are also addressed
Legal capacity and decision making: The ethical implications of lack of legal capacity on the lives of people with dementia
Get PDFYesThe report entitled “Legal capacity and decision making: The ethical implications of lack of legal capacity on the lives of people with dementia” received funding under an operating grant from the European Union’s Health Programme (2014–2020)
A comparative study between sand- and gravel-bed open channel flows in the wake region of a bed-mounted horizontal cylinder
Get PDFYesIn nature, environmental and geophysical flows frequently encounter submerged cylindrical bodies on a rough bed. The flows around the cylindrical bodies on the rough bed are very complicated as the flow field in these cases will be a function of bed roughness apart from the diameter of the cylinder and the flow velocity. In addition, the sand-bed roughness has different effects on the flow compared to the gravel-bed roughness due to differences in the roughness heights. Therefore, the main objective of this article is to compare the mean velocities and turbulent flow properties in the wake region of a horizontal bed-mounted cylinder over the sand-bed with that over the gravel-bed. Three experimental runs, two for the sand-bed and one for the gravel-bed with similar physical and hydraulic conditions, were recorded to fulfil this purpose. The Acoustic Doppler Velocimetry (ADV) probe was used for measuring the three-dimensional (3D) instantaneous velocity data. This comparative study shows that the magnitude of mean streamwise flow velocity, streamwise Reynolds normal stress, and Reynolds shear stress are reduced on the gravel-bed compared to the sand-bed. Conversely, the vertical velocities and vertical Reynolds normal stress are higher on the gravel-bed than the sand-bed.The Author Ram Balachandar acknowledges the grant support from Natural Sciences and Engineering Research Council of Canada the author Jaan H. Pu acknowledges the grant support from the Hidden Histories of Environmental Science Project (at Seedgrant Stage) by the Natural Environment Research Council (NERC) and Arts and Humanities Research Council (AHRC), part of UK Research and Innovation (UKRI)
Reusable rainwater quality at Ikorodu area of Lagos, Nigeria: Impact of first-flush and household treatment techniques
Get PDFYesWater scarcity is a huge problem in Africa, and hence rainwater becomes a crucial water source for fulfilling basic human needs. However, less attention has been given by African countries to the effectiveness of common rainwater treatments to ensure the population's health. This study investigates the impact of different household treatment techniques (HHTTs), i.e. treatments by chlorine, boiling, alum, and a combination of alum and chlorine, on its storage system using a case study at the Ikorodu area of Lagos state, which is a rural area in Nigeria. The first-flush quality has been particularly studied here, where the microbial reduction through its practice has been examined from five different roofs. One of the investigated roofs was from a residential building, and four were constructed for the purpose of this study. In this study, the physical parameters (i.e. total suspended solids and turbidity) and the microbial parameters (i.e. total coliform and Escherichia coli) of the collected rainwater have been investigated. From the results, it has been observed that: (1) the water quality at the free phase zone is better than that at the tank's bottom; (2) the combination of chlorine and alum gives the best rainwater quality after comparing the application of different HHTTs; and (3) a reduction of about 40% from the original contaminant load occurs in every 1 mm diversion.Hidden Histories of Environmental Science Grant Project (at Seed-grant Stage), funded by the Natural Environment Research Council (NERC) and Arts and Humanities Research Council (AHRC), part of UK Research and Innovation (UKRI
Ethanol amine functionalized electrospun nanofibers membrane for the treatment of dyes polluted wastewater
Get PDFYesThis study investigated adsorption kinetics, adsorption equilibrium, and adsorption isotherm of three dyes [i.e., methylene blue (MB), rhodamine-B (RB), and safranin T (ST)] onto polyacrylonitrile (PAN) and ethanolamine (EA) grafted PAN nanofibers (NFs) membranes (EA-g-PAN). The membranes were characterized by field emission scanning electron microscopy (FE-SEM), Fourier-transform infrared spectroscopy (FT-IR) spectroscopy, and Brunauer-Emmet-Teller (BET). FE-SEM showed a smooth morphology for the NFs before and after grafting, while FT-IR confirmed EA grafting into the nitrile group of PAN. The grafting percentage with no change in the physical nature of the membrane was 12.18%. The nitrogen adsorption-desorption isotherms for PAN and EA-g-PAN NFs membranes were similar and classified as a Type IV according to the International Union of Pure and Applied Chemistry. The surface area, pore-volume, and pore size of the EA-g-PAN increased to 21.36 m2 g−1, 0.16 cm3 g−1, and 304.93 Å, respectively. The pores were cylindrical mesopores with bimodal openings, which means that pores were open at both ends. The adsorption of the MB, RB, and ST dyes onto the PAN and EA-g-PAN NFs membranes leveled off at ~ 60 min. The adsorption kinetics showed good fitting to pseudo-second-order kinetic model and multi-step diffusion process. The order of the dye adsorption was PANthe Deanship of Scientific Research, King Saud University [RG-1440-060
Learning Transferable Features for Diagnosis of Breast Cancer from Histopathological Images
No full textNoNowadays, there is no argument that deep learning algorithms provide impressive results in many applications of medical image analysis. However, data scarcity problem and its consequences are challenges in implementation of deep learning for the digital histopathology domain. Deep transfer learning is one of the possible solutions for these challenges. The method of off-the-shelf features extraction from pre-trained convolutional neural networks (CNNs) is one of the common deep transfer learning approaches. The architecture of deep CNNs has a significant role in the choice of the optimal learning transferable features to adopt for classifying the cancerous histopathological image. In this study, we have investigated three pre-trained CNNs on ImageNet dataset; ResNet-50, DenseNet-201 and ShuffleNet models for classifying the Breast Cancer Histopathology (BACH) Challenge 2018 dataset. The extracted deep features from these three models were utilised to train two machine learning classifiers; namely, the K-Nearest Neighbour (KNN) and Support Vector Machine (SVM) to classify the breast cancer grades. Four grades of breast cancer were presented in the BACH challenge dataset; these grades namely normal tissue, benign tumour, in-situ carcinoma and invasive carcinoma. The performance of the target classifiers was evaluated. Our experimental results showed that the extracted off-the-shelf features from DenseNet-201 model provide the best predictive accuracy using both SVM and KNN classifiers. They yielded the image-wise classification accuracy of 93.75% and 88.75% for SVM and KNN classifiers, respectively. These results indicate the high robustness of our proposed framework
Dynamic simulation of once-through multistage flash (MSF-OT) desalination process: Effect of seawater temperature on the fouling mechanism in the heat exchangers
Get PDFYesScale formation of carbonates and sulphates is one of the most well-known types of crystallization fouling in heat exchangers. Tackling crystallization fouling in Once-Through Multistage Flash Desalination (MSF-OT) is one of the most challenging tasks in the desalination industry. In this paper, a fouling model is developed and then incorporated into a MSF model to investigate the fouling behaviour under variable seawater temperature. The proposed dynamic model investigates the crystallization of calcium carbonate and magnesium hydroxide at the inside tube surface areas by considering the attachment and removal mechanisms. The results show that the fouling rate is higher at high constant seawater temperature. Overall, the fouling rate is lower at the seasonal variation of the seawater temperature, resulting in a higher performance ratio (PR). The results also show that although the brine heater duty increases in winter due to low seawater temperature, the drop of fouling rate in cold months may save some energy