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Automated Design of Antennas Using AI Techniques: A Review of Contemporary Methods and Applications
Get PDFThe automated design of antennas made possible through the use of artificial intelligence (AI) techniques is attracting much attention. This development can be mainly attributed to the reduced design time and the higher quality of design solutions that AI-driven antenna optimization methods provide in comparison to their more traditional counterparts. Due to the growing need to fulfill more stringent design specifications and functional requirements for both present-day and future wireless communication systems, the design and development of antennas and antenna systems have increased both in scope and complexity, such that conventional methodologies are often not fit for an efficient practical implementation. In this paper, a brief overview of some of the latest AI-based techniques for the design and optimization of contemporary antennas is provided with the goal of providing information on recent research to researchers in this growing area of interest
Pracademia—Role Modelling HyFlex Digital Pedagogies in Youth Work Education
Get PDFThis research evaluates the experience of educators and students engaging in HyFlex learning experiences on a university Youth Work programme during the Covid-19 pandemic. Adopting a mixed methods approach, the research identifies challenges, opportunities, and possibilities of HyFlex learning. The research explores how digital skills gained in the classroom supported students to be more confident in role modelling these to deliver Digital Youth Work and support them in a post-Covid-19 environment. HyFlex pedagogies supported the development of pracademics, creating opportunities for learning in the classroom and translating this into real-world practice. Themes of time, technology, accessibility, and communities of practice (COP) are also discussed. Recommendations are made for future Higher Education practice which can be applied beyond Youth Work programmes
Exploring demand for, and perceptions of, Residential Rehabilitation amongst people who experience problems with drugs across Scotland
No full textIntroduction
The level of harms from drugs in Scotland is high in comparison to the rest of the UK and Europe, and causes avoidable damage to people's lives, families and communities.
Tackling the high level of drug related deaths in Scotland is a stated priority for the Scottish Government.
Public Health Scotland [PHS] have been asked by the Scottish Government to evaluate the Residential Rehabilitation [RR] programme element of its National Mission to reduce
drug deaths, covering the period until March 2026.
This is the final report of a two-part study and explores (1) ‘demand for’, and (2) ‘perceptions of’ RR amongst people who experience problems with drugs across Scotland.
Study aim and objectives The overall study aim was to better understand demand for, and perceptions of, RR services amongst people who experience problems with drugs across Scotland.
The research objectives of the study were to explore, amongst people who experience problems with drugs: awareness of RR services; experience of trying to access RR
services; perceptions of RR; levels of interest in RR; and interest in RR relative to other treatment options (treatment preferences)
A word to the wise (gair i gall): university teacher educators’ experiences of emergency response pedagogy in Wales
No full textThis study investigates the impact of COVID-19 on Initial Teacher Education (ITE) in Wales by examining university teacher educators’ experiences during lockdown. The pandemic significantly disrupted teacher-education partnerships, prompting rapid adaptation and changing delivery modes. Data were collected from semi-structured interviews with university teachers from eight HEIs offering teacher education in Wales in early 2022 to understand these rapid pedagogical adjustments and the transition to online teaching. Thirteen educators with varying expertise in online learning provided insights into institutional emergency pedagogy approaches. The transcribed interviews underwent a hybrid thematic analysis, initially guided by the Community of Inquiry framework and later using an open coding approach. Seven themes were identified: digital equity, assurance of professional learning, online etiquette, online teaching philosophy, design principles, meeting teaching standards, and belonging and making online connections. While the shift to online learning was transformative for Welsh academia, it highlighted a lack of digital preparedness. Cultural, linguistic and geographical factors, usually associated with fostering belonging, became obstacles during lockdown. The findings suggest that the Welsh ITE sector should adopt an outward-looking approach, leveraging existing research and proven pedagogical models to enhance professional development for university teachers and reimagining digital pedagogies to prepare for classroom realities effectively
Machine Learning-Assisted Microstrip Antenna Design Featuring Extraordinary Polarization Purity
No full textA high degree of polarization purity for microstrip antennas has been successfully explored. This, to the best of our knowledge, is the first of its kind and claims a twofold novelty: a stepwise development of complex multiunit defected ground geometry (DGG) based on a thorough scientific analysis and use of a machine learning-assisted global antenna optimization method, particularly, the parallel surrogate model-assisted hybrid differential evolution for antenna synthesis (PSADEA) algorithm, which is often more than ten times faster than popular global optimization techniques, while obtaining superior results. They result in highly optimal solutions considering multiple performances, i.e., reduction in cross-polarization (XP) radiations simultaneously over orthogonal (H-) and diagonal (D-) planes maintaining the primary gain unaffected. The proposed DGG has been satisfactorily tested with different patches and arrays fabricated in C band. Typically, 7.5 dBi to 8.0 dBi peak gain has been ensured along with 13 dB to 18 dB improvement in XP level over entire radiation planes. A 4-element array on an identical DGG promises over 40 dB co-to-XP isolation over the entire azimuth planes
Creating a Framework for Treating Autoimmune Gastritis – The Case for Replacing Lost Acid
Get PDFAutoimmune gastritis (AIG) is characterized by the destruction of gastric parietal cells, resulting in hypochlorhydria and eventual achlorhydria, as oxyntic glands in the corpus are destroyed and become atrophic. The permanent loss of gastric acid has many impacts—both theoretical and documented. The most concerning of these are hypergastrinemia and increased N-nitroso compounds, both of which increase the risk of gastric cancers. While known deficiencies of B12 and iron are often replaced in AIG, acid is not. Moreover, patients with AIG are often prescribed acid suppression for a stomach that is decidedly no longer acidic, worsening the sequelae of gastric atrophy. Betaine hydrochloride (BHCL) is a short-acting acidifying agent, available over the counter in capsule form. Mealtime acid supplementation has an historic basis and could ameliorate many AIG-related gastrointestinal symptoms. Theoretically, acidification could also reduce the potential for hypergastrinemia and the production of N-nitroso compounds, consequently reducing the risk of gastric cancers. Supplemental vitamin C may also help in preventing gastric N-nitroso formation, regardless of the gastric pH. This narrative review describes the functions of gastric acid in gastrointestinal and immune health, documents the effects of hypochlorhydria in AIG, and proposes potential options for safely re-establishing the acid milieu of the stomach for patients with AIG
Influence of stacking sequence on flexural properties of hybrid carbon fibre reinforced polymer laminates
No full textThis paper presents a numerical investigation of the influence of the stacking sequence and fibre variation of the plies on the flexural properties of carbon fibre-reinforced polymer laminates. The numerical approach utilised a three-point flexural test to evaluate different quasi-isotropic stacking sequences. It also analysed attempts to reinforce failure-prone plies only using a stronger prepreg material to reduce the cost of the laminate. The results were validated by conducting a cantilever bending test and compared with calculations based on classical lamination theory. The beam deflection, normal stress per ply, and the Puck failure criterion inverse reverse factor per ply were used for evaluation and result comparison. The results showed that the quasi-isotropic stacking sequence [0/90/+45/−45]s is the most suitable for beam applications. Replacement of the outer plies of the composite laminate by a stronger ply material made the hybrid laminate performance almost identical to a pure composite laminate consisting of stronger material only
Optimal design of a microgrid for carbon-free in-use housing developments: A UK-based case study
No full textThe UK Government’s plan to be net-zero by 2050 means that decarbonising the national grid whilst continuing to provide steady and reliable electricity is paramount. The mi-crogrids, formed by a combination of renewable energies, energy storage systems and a connection to the grid can pave the way to changing the UK energy landscape. Microgrids have been providing power to small communities on UK shores for over 20 years. The rationale of this work is to present the optimal microgrid design for new housing devel-opments in various UK locations. The power sources for each case study comprised of wind turbines, photovoltaic panels, hydro turbines, battery energy storage systems and a connection to the grid. Environmental impact, load performance and economic feasibility were key performance indicators when selecting the optimal microgrid design for each lo-cation. The objective is to find optimal combinations of wind turbines, hydro turbines, and a connection to the grid for case studies and to demonstrate that microgrids can provide consumers with free, carbon-reduced electricity throughout their 25-year project lifetime, and be funded entirely by consumers alone. Based on this research findings the optimal configuration of the microgrid is determined and analysed; the recommendations for the stakeholders are developed
Closing remarks on “The integration and implications of artificial intelligence in forensic science”
Get PDFThis commentary examines the use of artificial intelligence (AI) in forensic science, highlighting its benefits in enhancing accuracy and efficiency across a number of forensic disciplines, including medicine, anthropology, forensics, and taphonomy. However its use, also raises concerns about privacy, data protection, bias, fairness, and the reliability of AI systems. The commentary emphasises the importance of scrutiny, standardized procedures, and ongoing dialogue to ensure AI is responsibly advanced in forensic science
A Hybrid Swarm Intelligence Algorithm for Compute Cluster Selection Using Bee Colony Optimization with Random Sampling
No full textIn this paper a new hybrid swarm intelligence algorithm is proposed that blends traditional swarm intelligence (SI) framework with random sampling to have an improved search through large amounts of compute cluster data (associated with computing resource allocation and utilization) for optimum cluster selection. The proposed method is called Bee Colony Optimization with Random Sampling (BCORS) and its parallel variant is called Parallel BCORS (PBCORS). Both BCORS and PBCORS are tested using High Performance Computer (HPC) cluster specification data, and their convergence speeds in finding the optimum cluster to select are compared with alternative methods. Experimental results show that BCORS and PBCORS can sort cluster data and provide optimum computing resource allocation and selection faster than current alternatives and with less memory usage. Specifically, an average speed improvement of 68% and an average reduced memory usage of 120% are observed in comparison to parallel random sampling. The scalability of PBCORS to large amounts of data is also demonstrated by using test files with up to 70,000 entries