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Gender Stories
No full textStep into a thought-provoking journey with Gender Stories, an exhibition that sensitively begins to examine the fluid, multifaceted world of gender across cultures, eras, and personal experiences. It asks: What is gender? How do we experience it? Who defines it? What could it’s future look like? Challenging rigid definitions and binary narratives, the exhibition dives deep into the intricate connections between sex, gender, sexuality, and identity. Discover how these ideas have been mythologised, stereotyped, expressed – and sometimes concealed – through art, history, politics, and daily life over time. This compelling display brings together diverse objects and artworks from Brighton & Hove Museums, Bristol Museums, and National Museums Liverpool. By combining community stories with insights from gender theory, Gender Stories highlights both the joys and struggles of gender identity. We don’t have all the answers, but we’re excited to explore these complex questions together. Whether you’re beginning, continuing, or seeking to understand a gender journey – your own or someone else’s – this exhibition offers a meaningful space for reflection and discovery
LLM-Generated Samples for Android Malware Detection
No full textAndroid malware continues to evolve through obfuscation and polymorphism, posing challenges for both signature-based defenses and machine learning models trained on limited and imbalanced datasets. Synthetic data has been proposed as a remedy for scarcity, yet the role of Large Language Models (LLMs) in generating effective malware data for detection tasks remains underexplored. In this study, we fine-tune GPT-4.1-mini to produce structured records for three malware families: BankBot, Locker/SLocker, and Airpush/StopSMS, using the KronoDroid dataset. After addressing generation inconsistencies with prompt engineering and post-processing, we evaluate multiple classifiers under three settings: training with real data only, real-plus-synthetic data, and synthetic data alone. Results show that real-only training achieves near-perfect detection, while augmentation with synthetic data preserves high performance with only minor degradations. In contrast, synthetic-only training produces mixed outcomes, with effectiveness varying across malware families and fine-tuning strategies. These findings suggest that LLM-generated tabular malware feature records can enhance scarce datasets without compromising detection accuracy, but remain insufficient as a standalone training source
Improving Conductivity of Reduced Infill 3D-Printed Electrodes Through Tuning Infill Pattern and Orientation
No full text3D printing has been shown to be a highly effective approach for the reproducible manufacturing of composite carbon electrodes. Various printing parameters have been effectively shown to enhance the electrochemical performance of 3D-printed electrodes through reducing contact resistance; however, most of these studies have been conducted using 100% infill electrodes. Our study explored how the infill pattern and printing orientation can impact the electrochemical performance of reduced infill carbon black/polylactic acid (CB/PLA) electrodes. We printed 30% infill CB/PLA electrodes in linear, grid, triangle, and wiggle infill patterns in both horizontal and vertical orientations and evaluated the performance using cyclic voltammetry, conductivity imaging, and contact angle measurements. CB/PLA electrodes made using a grid infill pattern in horizontal orientation and a linear infill pattern with vertical orientation had the highest current and lowest difference between the anodic and cathodic peak potentials for an inner-sphere redox probe. This study provides vital insight that the choice of infill pattern is important when printing in different orientations. The findings presented have significant implications on effective choice of printing parameters when crafting 3D-printed electrodes and electronic components
The Union Wage Mark-Up for Immigrants in the United States
No full textUsing data from the Current Population Survey (CPS) for 1995–2023, we show that unionized immigrants earn 10.1 log points less than unionized natives, of which 4.8 log points are due to a lower union wage mark-up. Therefore, unionization is beneficial for immigrants but to a lesser extent than for natives in the United States. The difference in the union wage mark-up between natives and immigrants is most pronounced for males and low-skilled blue-collar workers
Experimental and numerical investigation of fire hazard of vertical greenery systems
No full textThis study investigates the fire hazard of vertical greenery systems (VGS) with experiments performed at the bench-scale and medium-scale followed by numerical simulations. Bench-scale tests were conducted in cone-calorimeter while the medium-scale experiments consisted of a test rig with dimensions 100 cm × 30 cm × 3 cm (height × width × depth). 28 cone-calorimeter tests were conducted under four cone heat flux levels, which represented four woodwool moisture content (MC) levels (between 8% to 20%) and four bulk densities (BD) of the fuel bed (between 50 kg/m3 to 100 kg/m3). Cone test results revealed that flammability was increased with the reduction of MC and BD under four flammability parameters, namely, the ignitability, combustibility, flame duration (FD) and consumability. The medium-scale experiments conducted with three different MCs and three different BDs showed that the UFS rate increases with the decrease of MC and BD. Average UFS rate was over 3.48 cm/s while the maximum temperatures along the fuel bed reached values over 700 0C in all scenarios. The medium-scale experiment scenarios were numerically simulated in the fire dynamic simulator (FDS) and the predicted upward fire spread rate showed good agreement with only slight deviations. However, the temperature recordings at different heights were overpredicted
Fostering a sense of community in hyperlocalised retail design for global brands
No full textTo differentiate themselves in a competitive market, global brands are establishing hyperlocalised stores that provide spaces, services, and experiences that are neighbourhood specific, while asserting global brand identity. These enmeshed spaces generate and leverage community attachments to both brand and place. As hyperlocalised retail stores are a convergence between brand and place, their design may contribute to a sense of community that enhances brand connections while serving the needs of people in the district. Branding literature defines brand community as possessing an underlying motivation of conspicuous consumption and explicitly rejects geography as a condition for community definition. Place literature encompasses retail as part of an urban fabric that constitutes place, with a broad perspective on community; however, there is limited focus on the influence of branding on local community. As hyperlocalised stores exist at the intersection of brand and place, there is a gap in the discourse to develop a consolidated understanding of community in physical retail stores. The study asks: How does sense of community influence the design of hyperlocalised retail stores for global brands? Furthermore, the study asks: How can the theoretical attributes of brand and place-based community be developed to inform hyperlocalised retail design practice? Using a constructivist grounded theory protocol, the researcher conducted 18 qualitative interviews with global retail designers. The findings were saturated using a theoretical sample of 20 hyperlocalised retail stores for four global brands. The study develops knowledge on the influence of community attributes on hyperlocalised retail design, resulting in practical design implications
Evaluation of Pressure Based and Density Based Solver to Investigate Supersonic Jet Flow through the Confined Wall
No full textThis study is primarily focused on the assessment of a pressure-based and density CFD solver for the numerical analysis of an under-expanded supersonic jet flow inside a canister tube. The simulation results of both types of solvers in terms of the pressure field and shock structure are compared to experimental measurement. A comparison study indicates that the pressure solvers produce the same key findings as the density-based, and are also closely in agreement with the data reported by Batson and Bertin. The pressure solver using coupled pressure-velocity algorithm showed nearly identical values of the pressure peaks and corresponding positions downstream of the tube wall. However, a pressure-based solver is more robust and computationally efficient. Thus, a pressure solver with coupled algorithm can be considered as an alternative for the study of complex supersonic compressible flows while maintaining accuracy
Data-driven cleaning optimisation strategy for multi-technology PV systems in the higher education sector in arid climate:A case study perspective in MENA region
No full textThe accumulation of dust and other contaminants on photovoltaic (PV) panels is a multifactorial process that significantly affects system performance. While cleaning is vital to maintaining energy output and efficiency, its methods, frequency, and procedures also influence environmental impact, resource use, and operational costs.This study investigates the effects of cleaning protocols on PV energy generation at the Applied Science University (ASU) campus in Amman, Jordan, addressing challenges faced by higher education institutions (HEIs) in the Middle East and North Africa (MENA) region. A controlled intervention was implemented on eight PV arrays with different technologies and installation configurations over a 19-week period. Machine learning techniques were applied for data imputation, and Analysis of Covariance (ANCOVA) was used to assess the significance of cleaning interventions on energy performance.The findings demonstrate that uniform cleaning schedules are suboptimal, as different PV technologies and orientations exhibit varying responses to maintenance interventions. The study underscores the importance of customised cleaning strategies that account for technological type and system configuration to maximise power generation and efficiency. These results provide valuable insights for developing sustainable PV maintenance frameworks for HEIs and other institutions operating in arid climates across the MENA region