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Characterisation of pressure-concentration-temperature profiles for metal hydride hydrogen storage alloys with model development
Get PDFMetal hydride (MH) alloys have been applied to hydrogen storage and various energy conversion systems such as refrigeration, heat pump and heat transformer. However, to facilitate and efficiently investigate efficiently a particular application, an MH alloy must firstly be characterised with a purposely built test facility to measure profiles of pressure, MH hydrogen concentration and temperature (PCT). Obtaining detailed PCT profiles or curves could be an arduous and expensive task as each isothermal hydrogen absorption or desorption line requires hundreds of measurement points. It is thus desirable to develop an accurate correlative model for the PCT profiles with limited measurements of thermophysical property data for the purpose of characterisation of each MH alloy. This correlative model or characterisation process has been developed and is described in detail in this article. The correlative PCT MH alloy profiles can cover all applicable hydrogen storage phase regions of α, α + β and β as well as the phase transition dome curve and critical point such that a PCT phase diagram for a particular MH alloy can be depicted and characterised. As an application example, the correlative model is applied to predict an MH alloy's hydrogen storage capacity and hysteresis at a specific MH temperature. It has been discovered that each of these two parameters shows comparative trends in variation with reduced temperature. Correspondingly, for each parameter, a correlative function with reduced temperature has been produced. The MH alloy characterisation process is an essential step towards a detailed dynamic MH energy system modelling, simulation and optimisation as well as experimental investigation
Smart Energy Management System for Minimizing Electricity Cost and Peak to Average Ratio in Residential Areas with Hybrid Genetic Flower Pollination Algorithm
Get PDFDemand Side Management (DSM) plays a significant role in the smart grid to minimize Electricity Cost (EC). Home Energy Management Systems (HEMSs) have recently been studied and proposed explicitly for HEM. In this paper, we propose a novel nature-inspired hybrid Genetic Flower Pollination Algorithm (GFPA) to minimize cost with an affordable delay in appliance scheduling. Our proposed GFPA algorithm combines elements of the Genetic Algorithm (GA) and Flower Pollination Algorithm (FPA) to create a hybrid approach. To assess the effectiveness of the proposed algorithm, we consider a scalable town consisting of 1, 10, 30, and 50 homes, respectively. The proposed solution finds an optimal scheduling pattern that simultaneously minimizes EC and Peak to Average Ratio (PAR) while maximizing User Comfort (UC). We assume that all homes are homogeneous regarding appliances and power consumption patterns. Simulation results show that our proposed scheme GFPA performs better when applying Critical Peak Pricing (CPP) signal using different Operational Time Intervals (OTIs) and compared with unscheduled, GA, and FPA-based solutions in terms of reducing cost since they achieve on average 98%, 36%, 23%, and 22%, respectively. Similarly, PAR averages 98%, 36%, 59%, and 55%, respectively. While, UC comparing to GA and FPA, are around 88%, 48%, and 63%, respectively. Our proposed scheme achieves better results by applying Real Time Pricing (RTP) signals and different OTIs. As these schemes, i.e., unscheduled, GA, FPA, and GFPA, achieve cost on average 92%, 50%, 29%, and 28%, respectively. While PAR on average 94%, 39%, 62%, and 56%, and UC for GA, FPA, and GFPA on average 98%, 52%, and 49%, respectively. Overall, ourproposed GFPA algorithm offers a more effective solution for minimizing EC with an affordable delay in appliance scheduling while considering PAR and UC
Superhydrophobic Hexadecyltrimethoxysilane-Modified Fumed Silica Nanostructure/Poly(butyl methacrylate) Composite Thin Films via Aerosol-Assisted Deposition: Implications for Self-Cleaning Surfaces
Get PDFSuperhydrophobic coatings with their unique nanostructured surface properties have application in many industrially important technologies but are currently dominated by environmentally problematic fluorinated compounds. Here, we demonstrate the fabrication of fluorocarbon-free superhydrophobic coatings consisting of poly(butyl methacrylate) (PBMA) and nanostructured hexadecyltrimethoxysilane (HDTMS)-functionalized fumed SiO2/PBMA as self-cleaning surfaces via a facile ambient pressure aerosol deposition route. X-ray photoelectron and infrared spectroscopy measurements showed successful composite formation. The deposition temperature and HDTMS-SiO2:PBMA ratio was optimized to give films that had a water contact angle as high as 161 ± 1° and a sliding angle of 1°, owing to a hierarchical surface nano- and microstructure and a root-mean-square surface roughness of 592 nm. This work shows a high-throughput single-step route to environmentally friendly PBMA-based superhydrophobic coatings
Parliamentary insight: domestic abuse and C-19, a year into the pandemic
Get PDFInsight into domestic abuse a year into lockdow
Analysis of Brain Imaging Data for the Detection of Early Age Autism Spectrum Disorder Using Transfer Learning Approaches for Internet of Things
Get PDFIn recent years, advanced magnetic resonance imaging (MRI) methods including functional magnetic resonance imaging (fMRI) and structural magnetic resonance imaging (sMRI) have indicated an increase in the prevalence of neuropsychiatric disorders such as autism spectrum disorder (ASD), effects one out of six children worldwide. Data driven techniques along with medical image analysis techniques, such as computer-assisted diagnosis (CAD), benefiting from deep learning. With the use of artificial intelligence (AI) and IoT-based intelligent approaches, it would be convenient to support autistic children to adopt the new atmospheres. In this paper, we classify and represent learning tasks of the most powerful deep learning network such as convolution neural network (CNN) and transfer learning algorithm on a combination of data from autism brain imaging data exchange (ABIDE I and ABIDE II) datasets. Due to their four-dimensional nature (three spatial dimensions and one temporal dimension), the resting state-fMRI (rs-fMRI) data can be used to develop diagnostic biomarkers for brain dysfunction. ABIDE is a collaboration of global scientists, where ABIDE-I and ABIDE-II consists of 1112 rs-fMRI datasets from 573 typical control (TC) and 539 autism individuals, and 1114 rs-fMRI from 521 autism and 593 typical control individuals respectively, which were collected from 17 different sites. Our proposed optimized version of CNN achieved 81.56% accuracy. This outperforms prior conventional approaches presented only on the ABIDE I datasets
Hand, foot and mouth disease
Get PDFHand, foot and mouth disease is a viral illness characterised by vesicular eruptions in the mouth, and lesions of the hands and feet. Amy Noakes provides a brief guide to the condition in childre
Drug Breakdown: Fosfomycin
Get PDFIn this column, Sharon Rees aims to refresh knowledge and interest in some of the commonly used drugs in a series of tweets. This month she is talking about #fosfomyci
Lightweight Privacy-Preserving Remote User Authentication and Key Agreement Protocol for Next-Generation IoT-Based Smart Healthcare
Get PDFThe advancement and innovations in wireless communication technologies including the Internet of Things have massively changed the paradigms of health-based services. In particular, during the COVID-19 pandemic, the trends of working from home have been promoted. Wireless body area network technology frameworks help sufferers in remotely obtaining scientific remedies from physicians through the Internet without paying a visit to the clinics. IoT sensor nodes are incorporated into the clinical device to allow health workers to consult the patients' fitness conditions in real time. Insecure wireless communication channels make unauthorized access to fitness-related records and manipulation of IoT sensor nodes attached to the patient's bodies possible, as a result of security flaws. As a result, IoT-enabled devices are threatened by a number of well-known attacks, including impersonation, replay, man-in-the-middle, and denial-of-service assaults. Modern authentication schemes do solve these issues, but they frequently involve challenging mathematical concepts that raise processing and transmission costs. In this paper, we propose a lightweight, secure, and efficient symmetric key exchange algorithm and remote user authentication scheme. Our research proposal presents a successful privacy-protecting method for remote users and provides protection against known attacks. When compared to conventional options, this technique significantly reduces calculation costs by up to 37.68% and transmission costs by up to 32.55%
EFFECTS OF CONTINUUM VERSUS BINARY BELIEFS ABOUT ALCOHOL PROBLEMS ON PROBLEM RECOGNITION, DEFENSIVE PROCESSING AND STIGMA AMONG HARMFUL DRINKERS
Get PDFThis programme of research reports a series of studies aimed at examining IBA interventions in university settings, among those delivering and receiving interventions. Three studies utilising both quantitative and qualitative methods investigated a) the motivations for alcohol use amongst students in two university settings, b) the views, opinions and reflections of interventionists and recipients of IBA, and c) the feasibility of implementing an IBA intervention and its effect on alcohol consumption amongst prepartiers and drinking gamers. The first study used quantitative e-questionnaires to examine alcohol motivations using a cross-sectional design. The main findings demonstrated that motivations for prepartying and drinking games differed from general drinking motivations, with pre-partiers and drinking gamers reporting increased AUDIT-C measures. Using a series of focus groups comprised of students, recipients of IBA and IBA interventionists, the second study provided a qualitative exploration of views, opinions, and reflections on IBA interventions. Recipients of IBA interventions reported more problematic usage compared to students and IBA interventionists. Thematic analysis highlighted two common themes across all focus groups. The first theme, Intervention Approach / Reflection, included evaluations on how interventions were constructed, developed, and implemented. The second theme, Social Convention of drinking included reflections on how alcohol experiences differ in social settings and the need to tailor interventions to groups specifically with the use of opportunistic methods. The third study was a feasibility study implementing an IBA intervention with students. Findings demonstrated that IBA interventions were associated with lower AUDIT-C scores at a 2-month follow up. Overall, the original contributions from this programme of research have been the sequence of research studies that have identified, evaluated, and feasibly implemented IBA initiatives. The evidence provided by the research has illustrated the need for intervention with pre-partiers and drinking gamers given the differing motivations and increased AUDIT-C measures. The research conducted in this thesis contributes to the alcohol motivations and IBA intervention implementation literature
Fabrication of monodisperse droplets and microcapsules using microfluidic chips: a review of methodologies and applications
Get PDFMicrofluidics has been applied in the preparation of monodisperse droplets and microcapsules due to its high encapsulation efficiency, its ability to create uniform particle sizes, and its capacity to control core-shell ratio and structure. To bring to the fore methodologies for the fabrication and application of monodisperse microcapsules using microfluidics, we present a review of the design, structure, materials, and surface modification techniques of various microfluidic chips. The review also covers fabrication methods, operating parameters and regulation methods of single and multiple monodisperse emulsion droplets fabricated from various microfluidic devices. Our findings show that particle size of monodisperse droplets depend mainly on microchannel characteristic size and flow rate, with particle size increasing with larger microchannel but decreasing with higher continuous phase flow rate. We additionally reviewed and compared various fabrication methods for monodisperse microcapsules, such as interfacial polymerization, free-radical polymerization, ionic cross-linking, and solvent evaporation. We further reviewed and examined the application of monodisperse microcapsules in biology applications, food engineering, composite materials development and pharmaceutical industry. We found that high-throughput microfluidics for scale-up monodisperse microcapsule preparation towards uniform degradation and targeted release properties of monodisperse microcapsules would be key innovative direction for future applications