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Growing Up and Out of Crime: Desistance, Maturation and Emerging Adulthood
Get PDFGrowing Up and Out of Crime explores how justice-involved youth desist from crime during a transition to adulthood. It challenges and situates conventional turning points amidst contemporary socio-structural shifts. Building upon theoretical frameworks, empirical evidence, and incorporating justice-involved narratives, Nader dissects the psychological and social concepts which contribute to identity, maturation and desistance during the emerging adulthood stage of the life course. From the outset Nader considers how emerging adults, particularly justice-involved, explore who they are and builds a case for thoughtful reconsideration of desistance and maturation processes. The book develops emerging adulthood theory to offer a rightful contribution to life-course criminology and desistance studies
Analytical solution for buckling analysis of FGM axisymmetric cylindrical shell under axial load using shear deformation theory and perturbation technique
Get PDFThis paper provides an analytical approach to determining the buckling load of an axisymmetric cylindrical shell made of functionally graded material (FGM) using utilizing the first-order shear deformation theory (FSDT) and von Karman relations. Nonlinear equilibrium equations are derived using the virtual work principle and solved with the perturbation technique. The stability equations are then obtained using the adjacent criterion method, resulting in a system of coupled linear differential equations with variable coefficients, which are solved analytically for the buckling load. A parametric study examines how various geometric and material properties influence the results. It is found that transitioning from homogeneous materials to FGMs increases the buckling load by 4–11%, depending on the shell dimensions. Additionally, finite element method (FEM) results are used to validate the analytical findings and are compared with existing literature.<br/
Future Island-Island Impact Cards:The Story of Rathlin Wool
Get PDFThe Story of Rathlin WoolChallengeThis Design Fellowship, The Story of Rathlin Wool, uses storytelling to highlight the regenerative potential of wool, rooted in Rathlin Island’s unique cultural and ecological landscape. Through an illustrated book, it explores vital connections between people, land, and sustainability - inviting reflections on waste, identity, and the need for community-led ecological renewal.ApproachThe project features a partnership between a Rathlin islander and local artist and centres on deep collaboration with the island and its wool. The illustrations have a gentle, earthy style that create an illustrated book through iterative stages - sketching, pacing, final artwork, and print preparation - integrating feedback throughout to ensure authenticity, educational value, and emotional resonance.OutcomesThe project has created a short, illustrated book telling the story of Rathlin wool, as it moves through the landscape from farmer, shearer, tractor, ferry driver, trailer, fleece grader, seaweed gatherer and dyer, knitter, and shopkeeper. Linked to the wider Rathlin Wool project, the book connects story, craft, farming, commerce and place. By weaving together heritage, craft, and environmental consciousness, the book inspires both local and global audiences to reimagine resilience and regeneration through the lens ofplace-based storytelling.LearningsThe project fosters education on sustainability and island life, celebrates Rathlin’s farming and wool heritage, and showcases the work of FII and local residents. It highlights the challenges and beauty of island livelihoods, honours often unseen contributions, and demonstrates how storytelling can preserve culture and practice, linking people, land, and tradition through low-carbon, regenerative, and circular approaches.ImpactThrough the co-creation of a new cultural artefact, The Story of Rathlin Wool fosters intergenerational understanding of sustainability, waste, and regeneration. It preserves Rathlin’s heritage, amplifies local voices, and offers an accessible entry point into circular practice and ecological thinking, stimulating cultural tourism, community pride, and deeper environmental engagement
“Time‐Tripping” and Memory‐Making: A Grounded Theory of Grounded Theory
Get PDFThis paper explores the development of grounded theory methodology through the lens of memory studies, introducing the concept of “time‐tripping” as a key generic social process. The paper identifies several sub‐processes of time‐tripping, including “reclaiming,” “resisting,” “retro‐casting,” and “landscaping,” which shape the methodological “imaginary.” Through a “grounded theory of grounded theory” approach, the authors analyze how these processes, influenced by individual and collective memory, authorship, and power dynamics, have contributed to the pluralism of the method. The paper concludes by suggesting that time‐tripping offers a valuable framework for understanding the social processes of memory and forgetting in science
Channel Estimation for Reconfigurable Intelligent Surface-aided 6G NOMA Systems: A Quantum Machine Learning Approach
Get PDFThe integration of reconfigurable intelligent surfaces (RISs) and non-orthogonal multiple access (NOMA) is considered a promising technique to enhance spectral efficiency and connectivity in future 6G networks. Accurate channel estimation remains a critical challenge in RIS-NOMA systems due to the increased complexity introduced by the combination of RIS and NOMA technologies. While quantum machine learning (QML) has demonstrated potential in wireless communications, its application in channel estimation remains underexplored. This paper investigates the effectiveness of a hybrid quantum-classical machine learning (ML) model for channel estimation in RIS-NOMA systems. We propose a hybrid architecture that integrates convolutional neural networks (CNNs) with quantum long short-term memory (QLSTM) networks, where CNNs perform spatial feature extraction while QLSTMs capture temporal dependencies in the time-varying channel. Extensive simulations are conducted to evaluate the performance of the model under various network configurations, considering different power allocation factors, the number of RIS elements, and signal-to-noise ratios (SNRs). The performance of the proposed model is benchmarked against both pure quantum and classical ML models, including a quantum neural network (QNN), a CNN, a long short-term memory (LSTM) model, a bidirectional LSTM (BiLSTM) model, and a CNN-LSTM model. The results demonstrate that the proposed CNN-QLSTM model outperforms all baseline methods in terms of root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE). These findings highlight the potential of quantum-enhanced ML for channel estimation in next-generation communication networks
A digital recipe for enhancing clinical reasoning: the role of e-learning by concordance (E-LbC): a quasi-experimental study
Get PDFBackground: Clinical reasoning (CR) is a critical competency in medical education, essential for effective decision-making in clinical practice. This study aimed to enhance CR skills among undergraduate medical students by comparing two instructional strategies: the E-learning by Concordance (e-LbC) approach and an interactive lecture-based method. Methods: A quasi-experimental comparative study was conducted at the Faculty of Medicine, Suez Canal University, Egypt, during the 2021–2022 academic year. The study involved 60 fifth-year medical students through comprehensive sampling and was implemented over one academic term. It consisted of three phases. In the first phase, an online Script Concordance Test (SCT) was used via the Wooclap platform to assess students’ baseline CR skills. The second phase included the educational intervention, in which the e-LbC method was used to teach the topic of painless vision loss, while the interactive lecture method was used for painful vision loss. In the final phase, a researcher-developed questionnaire assessed students’ perceptions regarding the impact of each instructional method on CR development, difficulty level, and satisfaction. The questionnaire’s validity was established by medical education experts, and reliability was confirmed using Cronbach’s alpha. Results: Statistical analysis using paired t-tests revealed no significant difference in the pre-SCT scores between groups. However, post-SCT scores showed a statistically significant improvement in both groups, with the e-LbC, painless vision loss theme, demonstrating a greater effect size (Cohen’s d) and overall higher performance (p < 0.001). Additionally, 62% of students expressed satisfaction with the e-LbC method. Conclusion: the e-LbC approach positively influenced students’ clinical reasoning skills and engagement. Its integration with real-time assessment tools like Wooclap, combined with its cost-effectiveness, flexibility, and user-friendliness, positions it as a valuable tool for enhancing medical education in diverse learning environments.</p
Experimental Verification of Broadband mmWave RIS-Aided Communications: Codebook-Based Beam Steering and Indoor Channel Measurements
Get PDFThis paper summarises the design and channel measurements of a wide band Reconfigurable Intelligent Surface RIS operating within the millimeter wave spectrum for 5G and beyond communication. RIS elements are controlled by a p-i-n diode and biased via RF chokes operating within the n257 millimeter wave 5G band. The RIS operates in both vertical and horizontal polarizations. Experiments have been performed to validate the performance of the RIS in both near-field and far-field regions. It has been experimentally demonstrated that the proposed RIS can reflect incident beams towards desired locations with channel gain enhancement of up to 16.3 dB when appropriate phase profiles are applied
Deep Learning-Based Secure Tag Selection in BackCom Network With RIS-Induced Interference
Get PDFThis article investigates the secrecy performance of a non-linear energy-harvesting backscatter communication (BackCom) network in the presence of direct link and reconfigurable intelligent surface (RIS) interference. The network comprises a source, multiple passive tags, an RIS, and a legitimate reader, with an eavesdropper attempting to intercept the communication. We analyze a tag selection scheme based on long-short-term memory (LSTM) to address the challenge of selecting tags under the influence of direct link and the RIS interference. The nonideal behavior of the RIS is exploited to enhance secrecy performance by modeling RIS phase errors using Von Mises and uniform distributions. Because of interference from the direct link and the RIS being common to all tags, the secrecy rates of different tags are correlated. The LSTM-based scheme effectively captures this correlation and perfectly matches the conventional selection scheme on low and high tag counts. The secrecy outage probability (SOP) achieved using the LSTM outperforms other machine learning techniques, such as k -nearest neighbors ( k -NN), decision trees (DT), and support vector machines (SVM). We also demonstrate the impact of RIS elements, phase error parameters, and the number of tags on the SOP in the considered RIS-aided BackCom network
Persuading Chronically Ill Patients to Subscribe to Medical Services in Physician-Driven Online Health Communities
Get PDFWhile patient-driven online health communities (OHCs) have long been a fixture of the online healthcare landscape, physician-driven OHCs are becoming increasingly popular. Drawing on the persuasive communication literature, this study takes a physician’s perspective to examine how physicians signal their professional expertise and caring demeanor through online responses and influence patient medical service subscription decisions. By analyzing textual and image data collected from a leading physician-driven OHC, we found that regarding message framing, caring messages (emotional appeals) significantly boosted subscriptions among chronically ill patients, while technical messages (rational appeals) did not. The results were found to be the opposite for source framing: authoritative reputation (rational appeals) had a significant effect but smiling images (emotional appeals) did not. The results also punctuate the importance of congruence between message and source and between text and image in both rational and emotional appeals. Our findings make significant theoretical contributions and offer guidance for physicians seeking to optimize their OHC participation to enhance chronic disease care.</p
Practical Implications of Generative AI on Assessment:Snapshot of Early Reactions to Assessment Redesign in an HRM and a Psychology Course
Get PDFThe advent of Generative AI (GAI) tools such as ChatGPT, Google Gemini, and Microsoft Copilot has significantly impacted higher education. This exploratory study investigates the current perspectives of lecturers in Human Resource Management (HRM) and Psychology on adapting assessment strategies in response to GAI developments. Through an online survey, qualitative data was collected from 12 academics, revealing a shift towards more authentic and process-oriented assessments. The findings highlight the dual role of GAI: while it poses risks to academic integrity, contrary to the common perception, it also offers opportunities to enhance assessment authenticity and student engagement. Participating educators reported various adaptations, including the integration of GAI into assessment tasks, increased use of group-based projects, and the implementation of time-limited and context-specific assignments. The study emphasises the need for continuous evolution in assessment practices to maintain academic integrity and effectively measure student learning outcomes in the GAI era. Further research should focus on longitudinal studies to track the impact of these changes over time, to identify the merits and any shortcomings of these new assessment approaches.</p