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Working memory capacity is related to eyewitness identification accuracy, but selective attention and need for cognition are not
No full textIndividual differences in working memory capacity, selective attention, and need for cognition were investigated as postdictors—variables indicating the likelihood that an identification is accurate—using same-race and cross-race lineups. We also explored whether these variables improve predictions of identification accuracy when considering confidence and response time. White participants (N = 274) completed individual differences measures, watched four mock-crime videos (2 Asian targets, 2 White targets), made lineup decisions, and rated their confidence. Working memory capacity predicted identification accuracy and target-present accuracy but not target-absent accuracy. A regression model with confidence, response time, and working memory capacity explained more variance than a model with confidence and response time alone, indicating that working memory capacity tells us more about identification accuracy than extant reflector variables about identification accuracy
Access to services for mental ill-health and substance use among people released from prison in Scotland (RELEASE): Retrospective observational cohort study protocol
No full textIntroductionMental health and substance use (MH/SU) problems are highly prevalent among the prison population. However, early and preventative post-imprisonment care appears to be insufficient to meet the MH/SU needs of people released. This is demonstrated by elevated rates of MH/SU-related emergency care and deaths attributable to alcohol, drugs and suicide. Studies examining post-imprisonment healthcare contacts across community, outpatient, inpatient and emergency services for MH/SU are required to address this issue. This protocol paper describes the outcome of data linkage and details our plans for data cleaning and analysis.MethodsThe RELEASE study will follow a retrospective observational cohort design. This is the first study using national individual-level linked administrative health and prison data from Scotland. We report the results of creating the cohort, and outline proposed methods for data preparation and analysis. Within the cohort, the exposed group comprises everyone released from prison in 2015, and the unexposed group consists of a random sample of the general population matched (1:5 ratio) on age, sex, postcode and postcode-derived index of multiple deprivation, and with no prison exposure in the preceding 5 years. Health data (community prescribing, outpatient visits, specialist substance use, psychiatric inpatient, general inpatient, out-of-hours general practice, 24-hour National Health Service [NHS] helpline, ambulance, and emergency services), deaths data, and prison data (admissions, releases, demographic data) were linked to the cohort using unique identifiers. Service contacts associated with MH/SU will be quantified and compared across the two groups using regression modelling, controlling for potential confounding variables, reimprisonment and deaths.ConclusionRELEASE is a comprehensive study with potential to inform post-imprisonment MH/SU service delivery, whilst the dataset holds significant potential for exploring other health conditions and outcomes. This research will allow for an unprecedented understanding of post-imprisonment service use patterns in Scotland, and RELEASE will make a significant public health contribution given the overrepresentation of people released in costly emergency care contact and death rates
Encapsulated U-shape lossy mode resonance optical fibre sensor for temperature quantification of lithium-ion batteries
Get PDFAccurate measurement of essential operational parameters in electrochemical energy storage devices is vital for ensuring reliable and long-lasting performance in a circular economy. This study presents the first use of a Lossy Mode Resonance (LMR) optical fibre sensor to measure the temperature of lithium-ion batteries, which is a highly influential aspect of their degradation. This technique enables an effective and simple application of optical fibre sensors for energy storage devices. The design involves using a U-shaped fibre to accurately detect changes in absorption, rather than changes in wavelength. Additionally, it incorporates a thin-film of graphene oxide and polyethyleneimine to induce the LMR which is enclosed within polydimethylsiloxane which alters refractive index with temperature. The total sensitivity reached is −0.0072 A.U./°C and −0.39 nm/°C, with excellent linearity values of R² 0.98 and R² 0.99 for the 2 C and 2.5 C discharge rates, respectively. This work emphasises the affordable, accurate, and innovative use of LMR sensors, which encourages the advancement and utilisation of these sensors in electrochemical energy storage systems
UK Built Environment postgraduate programme provision: sectoral context, viability and educational implications
Get PDFPostgraduate (PG) Built Environment education provides higher level skills, yet, concerns of losing such provision exist, as UK universities are experiencing financial challenges from systemic governmental underfunding. This article presents survey findings evaluating three areas in PG Built Environment provision: (i) Institutional context and programmes offerings; (ii) Programme viability and institutional decision making; and (iii) Implications of change in programme offerings. Collectively, these support an understanding of ‘What is offered?’ ‘Whatis viable?’ and ‘What is the result of change in provision?’ Participants included Senior academics from a range of UK universities and disciplines. Results suggest more PG programmes are being opened (72%) than closed (35%), reflecting institutional aspirations to grow numbers via new offerings. No consensus exists regarding numbers for financial viability, although 10 to 30 students was commonly noted. Decisions to open and close programmes are largely ‘top-down’, from University Executive or Head of School, whilst arguments for retaining programmes with low student numbers typically come from staff at programme level. Regarding implications of change, policy makers are encouraged to engage with universities, employers and professional bodies, as findings point towards more online PG degrees, Continuing Professional Development activities and inhouse specialist training
An Investigation of Affect Transfer of Social Responsibility in Ski Events Among Tourists and Employees
Get PDFThis research investigates the integration of social responsibility into Iranian ski tourism events and its positive affect transfer among employees and sport tourists. Study 1 comprised interviews with 30 employees of ski resorts and found that workers' understanding and expectation of social responsibility of the ski resorts extended beyond benefits to local communities. Study 2 comprised a survey with 710 sport tourists of ski events and found that when the event includes social responsibility that benefits local communities, it positively moderates the relationship between satisfaction and ongoing loyalty and emotional investment of sport tourists in these events. These results suggest the incorporation of social responsibility practices into ski events can transfer positive affects into desirable loyalty and emotional outcomes among sport tourists, yet employees seek more ambitious social responsibility efforts
Cleaning methods for solar PV systems in Sri Lanka: Economic and environmental evaluations
Get PDFSolar energy holds significant potential in Sri Lanka, but the performance of photovoltaic (PV) systems is often compromised by soiling from dust and pollution. This study evaluates the economic and environmental feasibility of manual and robotic PV cleaning methods across Sri Lanka's diverse climatic zones. Using PVsyst simulations with localised economic data, the research models energy generation and performs financial analyses using Levelized Cost of Electricity (LCOE) and Net Present Value (NPV). Environmental assessments further examine soiling effects and cleaning efficiency. Simulations conducted in wet, dry, and intermediate zones reveal that manual cleaning is generally more cost-effective, with a payback period of 3–4 years. Robotic cleaning, while operationally advantageous due to reduced labour dependency and consistent efficiency, requires a longer payback period of 5–7 years without financing and 7–9 years with loans. These findings highlight the importance of climate-specific cleaning schedules and suggest that while manual cleaning is currently more viable, advancements in technology and rising labour costs may render robotic cleaning a competitive option in the future
Exploring the black box: analysing explainable AI challenges and best practices through stack exchange discussions
No full textExplainable Artificial Intelligence (XAI) is a crucial domain within research and industry, aiming to develop AI models that provide human-understandable explanations for their decisions. While the challenges in AI, deep learning, and big data have been extensively explored, the specific concerns of XAI developers have received limited attention. To address this gap, we analysed discussions on Stack Exchange websites to delve into these issues. Through a combination of automated and Manual analysis, we identified 6 overarching categories, 10 distinct topics, and 40 sub-topics commonly discussed by developers. Our examination revealed a steady rise in discussions on XAI since late 2015, initially focusing on conceptualisation and practical applications, with a notable surge in activity across all topic categories since 2019. Notably, Concepts and Applications, Tools Troubleshooting, and Neural Networks Interpretation emerged as the most popular topics. Troubleshooting challenges were commonly encountered with tools like SHAP, ELI5, and AIF360, while visualisation issues were prevalent with Yellowbrick and SHAP. Furthermore, our analysis suggests that addressing questions related to XAI poses greater difficulty compared to other machine-learning questions
2025 ESC Clinical Consensus Statement on mental health and cardiovascular disease: developed under the auspices of the ESC Clinical Practice Guidelines Committee
No full textHigh-Isolation Array Antenna Design for 5G mm-Wave MIMO Applications
Get PDFA low form-factor design of an eight-element antenna array is presented for 5G mm-wave MIMO applications. The design features modified circular patch radiators that achieve an impedance bandwidth of 2.6 GHz, covering frequencies from 37.7 to 40.3 GHz. The radiating elements are strategically arranged on opposite sides of a common substrate and interleaved to significantly reduce mutual coupling between adjacent elements. This innovative technique effectively minimizes coupling between the array’s radiators without the need of a decoupling structure. The MIMO antenna is fabricated on a low-loss Rogers-5880 substrate, with a thickness of 0.8 mm, a dielectric constant of 2.2, and a loss tangent of 0.0009, ensuring minimal signal loss and confirming the accuracy of simulation results. The inter-element isolation exceeds 25 dB, and the array provides a gain greater than 6 dBi, with a peak gain of 7.5 dBi at 39 GHz. This high gain enhances the antenna’s ability to mitigate atmospheric attenuation at higher frequencies, making it highly suitable for 5G mm-wave applications
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