bluuebunny/crossref_metadata_2025_split huggingface dataset:
Psychotic experiences and disorders in adolescents and young adults with intellectual disabilities: Evidence from a population-based birth cohort in the United Kingdom
Authors: Dardani Christina , Underwood Jack F G , Jones Hannah J. , Rammos Alexandros , Sullivan Sarah , Hull Laura , Khandaker Golam M. , Zammit Stan , Rai Dheeraj , Madley-Dowd Paul 
Published: July 2024

SummaryBackgroundEvidence suggests that individuals with intellectual disabilities may be at increased risk of affective and non-affective psychotic disorders. However, studies so far have been limited by small and selected samples. Moreover, the role of early life trauma, a key environmental risk factor for psychosis, in the potential associations is unknown.MethodsUsing data from Avon Longitudinal Study of Parents and Children (ALSPAC) birth cohort, we investigated the associations between ID, psychotic disorders, and psychotic experiences in adulthood, and assessed the potential mediating role of trauma in childhood. Individuals with intellectual disabilities were identified using a multisource measure utilising cognitive, functional, and diagnostic indicators from ALSPAC combined with health and administrative records. Psychotic disorder clinical diagnoses were extracted through linkage to primary care records. Psychotic experiences were assessed at ages 18 and 24 using the semi-structured Psychosis-Like Symptoms interview (PLIKSi). Traumatic experiences between ages 5 and 11 were assessed with questionnaires and interviews administered to children and parents at multiple ages. Multiple imputation was performed across all analyses to mitigate potential bias due to missing data.FindingsThe maximum sample after multiple imputation was 9,407. We found evidence of associations between intellectual disabilities and psychotic disorders (OR= 4.57; 95%CI: 1.56-13.39). Evidence was weaker in the case of psychotic experiences (OR=1.63; 95%CI: 0.93-2.84). There was some evidence suggesting a potential mediating role of traumatic experiences in the associations between ID and psychotic experiences (OR= 1.09; 95%CI: 1.03-1.15). Evidence was less consistent in the case of psychotic disorders. Complete records analyses yielded comparable estimates.InterpretationIntellectual disabilities are associated with psychotic disorders and experiences in young adulthood. Further research into the contribution of trauma could shape current intervention strategies for psychotic disorders in this population.FundingThe Baily Thomas Charitable Fund
Healthcare visits of the population 50+ in Europe from 2004 to 2022
Authors: Nguyen Van Kinh , Reuter Anna , Abd El Aziz Mirna , Bärnighausen Till 
Published: July 2024

BackgroundThe COVID-19 pandemic brought major reductions in healthcare visits in Europe. The long-run consequences for healthcare systems depend on the paths to post-pandemic levels, especially among the groups in highest need of sustained care.MethodsWe used individual longitudinal data from 27 European countries from the Survey of Health, Ageing and Retirement in Europe, divided in three phases: pre-pandemic (2004-2019), pandemic (2021), and post-pandemic (2022). We analysed the number of healthcare visits by gender over time and their correlation with age and chronic conditions using a Bayesian spatio-temporal model.ResultsBefore COVID-19, the nominal rate of healthcare visits varied among countries from two to six visits per year and increased over time. The COVID-19 pandemic severely affected the number of healthcare visits, with an estimated reduction from 65% to 95% across countries. During COVID-19, older individuals and those with chronic conditions had a more than proportional reduction in the number of healthcare visits. After COVID-19, the pattern of healthcare visits mostly returned to pre-pandemic levels, with an over-shooting for people with cancer and a lag for people with cardiovascular diseases.ConclusionThe quick recovery in the number of healthcare visits for most European countries indicate that access to care stabilised again. Yet, the different trends for vulnerable groups show that these groups require timely action to prevent long-term consequences of missed care.
Large Language Models Diagnose Facial Deformity
Authors: Lee Jungwook , Xu Xuanang , Kim Daeseung , Deng Hannah H. , Kuang Tianshu , Lampen Nathan , Fang Xi , Gateno Jaime , Yan Pingkun 
Published: July 2024

AbstractPurposeThis study examines the application of Large Language Models (LLMs) in diagnosing jaw deformities, aiming to overcome the limitations of various diagnostic methods by harnessing the advanced capabilities of LLMs for enhanced data interpretation. The goal is to provide tools that simplify complex data analysis and make diagnostic processes more accessible and intuitive for clinical practitioners.MethodsAn experiment involving patients with jaw deformities was conducted, where cephalometric measurements (SNB Angle, Facial Angle, Mandibular Unit Length) were converted into text for LLM analysis. Multiple LLMs, including LLAMA-2 variants, GPT models, and the Gemini-Pro model, were evaluated against various methods (Threshold-based, Machine Learning Models) using balanced accuracy and F1-score.ResultsOur research demonstrates that larger LLMs efficiently adapt to diagnostic tasks, showing rapid performance saturation with minimal training examples and reducing ambiguous classification, which highlights their robust in-context learning abilities. The conversion of complex cephalometric measurements into intuitive text formats not only broadens the accessibility of the information but also enhances the interpretability, providing clinicians with clear and actionable insights.ConclusionIntegrating LLMs into the diagnosis of jaw deformities marks a significant advancement in making diagnostic processes more accessible and reducing reliance on specialized training. These models serve as valuable auxiliary tools, offering clear, understandable outputs that facilitate easier decision-making for clinicians, particularly those with less experience or in settings with limited access to specialized expertise. Future refinements and adaptations to include more comprehensive and medically specific datasets are expected to enhance the precision and utility of LLMs, potentially transforming the landscape of medical diagnostics.
Life cycle cost analysis at scale: a reference architecture-based approach
Authors: Shaw Conor , de Andrade Pereira Flávia , Farghaly Karim , Hoare Cathal , Hartmann Timo , O'Donnell James 
Published: July 2024

PurposeThis research demonstrates the theoretical merit of a reference architecture-based approach to life cycle cost (LCC) analysis system provision in the built environment. LCC insight is considered fundamental to sustainable decision making by asset managers; however, the current capabilities in practice do not align with the political ambition and the scale of competencies required to realise sectoral emissions–reduction targets.Design/methodology/approachIn pursuing practical outcomes, the study employs a custom design science research-inspired methodology. Domain requirements are gathered via literature research as an initial top-down software reference architecture which is refined, bottom-up, through testing and implementation in a representative case study. A prototype IT system and reference architecture artefact are developed and used to evaluate the concept qualitatively through broad practitioner focus groups.FindingsSentiment analysis of the expert opinions is broadly positive and helps to substantiate the proposal’s theoretical suitability in addressing the scalability challenge. Additionally, constructive feedback provides guidance towards this trajectory, highlighting the importance of aligning with existing communities and standards, broadening future research scope to consider further scenarios and prioritisation of efforts to build trust around contracts and data quality.Originality/valueThe novelty of the work is the provision of the reusable LCC reference architecture development methodology.Practical implicationsThe concept has the potential to provide LCC capabilities to industry at scale while the artefacts developed herein can be appended to existing LCC standards as implementation guidance to support IT system developers. Furthermore, the developed methodology can be employed in harmonisation efforts between policy and practice.
Non-Fourier computations of heat and mass transport in nanoscale solid-fluid interactions using the Galerkin finite element method
Authors: Alsenafi Abdulaziz , Alazemi Fares , Nawaz M. 
Published: July 2024

Purpose
To improve the thermal performance of base fluid, nanoparticles of three types are dispersed in the base fluid. A novel theory of non-Fourier heat transfer is used for design and development of models. The thermal performance of sample fluids is compared to determine which types of combination of nanoparticles are the best for an optimized enhancement in thermal performance of fluids. This article aims to: (i) investigate the impact of nanoparticles on thermal performance; and (ii) implement the Galerkin finite element method (GFEM) to thermal problems.

Design/methodology/approach
The mathematical models are developed using novel non-Fourier heat flux theory, conservation laws of computational fluid dynamics (CFD) and no-slip thermal boundary conditions. The models are approximated using thermal boundary layer approximations, and transformed models are solved numerically using GFEM. A grid-sensitivity test is performed. The accuracy, correction and stability of solutions is ensured. The numerical method adopted for the calculations is validated with published data. Quantities of engineering interest, i.e. wall shear stress, wall mass flow rate and wall heat flux, are calculated and examined versus emerging rheological parameters and thermal relaxation time.

Findings
The thermal relaxation time measures the ability of a fluid to restore its original thermal state, called thermal equilibrium and therefore, simulations have shown that the thermal relaxation time associated with a mono nanofluid has the most substantial effect on the temperature of fluid, whereas a ternary nanofluid has the smallest thermal relaxation time. A ternary nanofluid has a wider thermal boundary thickness in comparison with base and di- and mono nanofluids. The wall heat flux (in the case of the ternary nanofluids) has the most significant value compared with the wall shear stresses for the mono and hybrid nanofluids. The wall heat and mass fluxes have the highest values for the case of non-Fourier heat and mass diffusion compared to the case of Fourier heat and mass transfer.

Originality/value
An extensive literature review reveals that no study has considered thermal and concentration memory effects on transport mechanisms in fluids of cross-rheological liquid using novel theory of heat and mass [presented by Cattaneo (Cattaneo, 1958) and Christov (Christov, 2009)] so far. Moreover, the finite element method for coupled and nonlinear CFD problems has not been implemented so far. To the best of the authors’ knowledge for the first time, the dynamics of wall heat flow rate and mass flow rate under simultaneous effects of thermal and solute relaxation times, Ohmic dissipation and first-order chemical reactions are studied.
Power to the she: early-stage female entrepreneurs and innovation
Authors: Brownell Katrina , Kickul Jill , Hechavarria Diana 
Published: July 2024

PurposeOur study draws on gender role congruity theory to theorize and test an integrative conceptual model outlining how motives for entrepreneurial action explain the relationship between female entrepreneurship and innovation in nascent ventures.Design/methodology/approachTo test our hypotheses, we employed structural equation modeling (SEM) in a sample of early-stage entrepreneurs (N = 533).FindingsWe found a positive relationship between nascent female entrepreneurs and innovation, and that this relationship is mediated by motives for recognition, respect, and autonomy.Originality/valueBy revealing a positive relationship between female entrepreneurship and innovation, our work provides a complementary perspective to the literature, which suggests that there are limits to innovation potential for female entrepreneurs. Further, we find that this relationship is explained by motives for recognition, respect, and autonomy, but not financial security. Finally, most empirical research focuses on the innovative outputs of established new ventures, while our work leverages a sample of early-stage entrepreneurs.
Web-aided data set expansion in deep learning: evaluating trainable activation functions in ResNet for improved image classification
Authors: Zhang Zhiqiang , Li Xiaoming , Xu Xinyi , Lu Chengjie , Yang Yihe , Shi Zhiyong 
Published: July 2024

Purpose
The purpose of this study is to explore the potential of trainable activation functions to enhance the performance of deep neural networks, specifically ResNet architectures, in the task of image classification. By introducing activation functions that adapt during training, the authors aim to determine whether such flexibility can lead to improved learning outcomes and generalization capabilities compared to static activation functions like ReLU. This research seeks to provide insights into how dynamic nonlinearities might influence deep learning models' efficiency and accuracy in handling complex image data sets.

Design/methodology/approach
This research integrates three novel trainable activation functions – CosLU, DELU and ReLUN – into various ResNet-n architectures, where “n” denotes the number of convolutional layers. Using CIFAR-10 and CIFAR-100 data sets, the authors conducted a comparative study to assess the impact of these functions on image classification accuracy. The approach included modifying the traditional ResNet models by replacing their static activation functions with the trainable variants, allowing for dynamic adaptation during training. The performance was evaluated based on accuracy metrics and loss profiles across different network depths.

Findings
The findings indicate that trainable activation functions, particularly CosLU, can significantly enhance the performance of deep learning models, outperforming the traditional ReLU in deeper network configurations on the CIFAR-10 data set. CosLU showed the highest improvement in accuracy, whereas DELU and ReLUN offered varying levels of performance enhancements. These functions also demonstrated potential in reducing overfitting and improving model generalization across more complex data sets like CIFAR-100, suggesting that the adaptability of activation functions plays a crucial role in the training dynamics of deep neural networks.

Originality/value
This study contributes to the field of deep learning by introducing and evaluating the impact of three novel trainable activation functions within widely used ResNet architectures. Unlike previous works that primarily focused on static activation functions, this research demonstrates that incorporating trainable nonlinearities can lead to significant improvements in model performance and adaptability. The introduction of CosLU, DELU and ReLUN provides a new pathway for enhancing the flexibility and efficiency of neural networks, potentially setting a new standard for future deep learning applications in image classification and beyond.
Community-engaged co-design of a quality improvement capacity building program within an integrated health system in Ontario, Canada
Authors: Rotteau Leahora , Magaz Mercedes , Wong Brian M. , Shearkhani Sara , Shabani Mohammad , Pradhan Rishma , Auguste Bourne , Bourne Laurie , Powis Jeff , Smith Kelly Michelle 
Published: July 2024

PurposeAn integrated care system identified quality improvement (QI) capacity as a gap in advancing their integrated quality care priorities and improvement efforts. Here we describe the design and implementation of a QI capacity building program that aimed to (1) build QI capacity amongst diverse integrated care system members and (2) apply QI principles to advance integrated quality care priorities.Design/methodology/approachThe integrated care system leaders, including community members, partnered with the University of Toronto Centre for Quality Improvement and Patient Safety to co-design and deliver the QI capacity building program focused on improving cancer screening rates. An existing acute care capacity building program was adapted. Content included QI tools, data to identify and monitor QI priorities, equity considerations, and empowering participants as change agents.FindingsParticipants were satisfied with the content and delivery of the program. Some described using QI tools and strategies in practice following the workshop. Challenges to using the tools included the current pressures facing primary care and the health system, resources, and data availability.Practical implicationsThis QI capacity building program was challenging but feasible. Clarifying the target audience, being attentive to co-design, acknowledging post-pandemic system challenges and proactively addressing variable knowledge and barriers to QI work in practice will inform future iterations of this program.Originality/valueWhile many examples of QI education programs exist, the majority target a single healthcare sector. We describe a novel QI capacity building model that bridges healthcare sectors and includes patient partners and community members as teachers and participants.
Exploring the inter-sectoral and inter-regional effect of tourism industry in Indonesia based on input-output framework
Authors: Li Fanglin , Sastri Ray , Edziah Bless Kofi , Setiyawan Arbi 
Published: July 2024

PurposeTourism is an essential industry in Indonesia, and understanding its inter-sectoral and inter-regional connections is critical for policy development. This study examines the economic impact of regional tourism in Indonesia and the connections between different tourism-related regions and industries.Design/methodology/approachThis study uses a non-survey method to estimate the inter-regional input-output table (IRIOT) in 2019, backward and forward linkage to identify the role of tourism in the economy, and the structural path analysis (SPA) to identify the inter-sectoral and inter-regional flow of tourism effect. The benchmark IRIOT 2016 published by Badan Pusat Statistik (BPS) serves as the primary data source.FindingsThe findings indicate that tourism has a relatively high impact on the overall national economy and plays an essential role in nine provinces. However, this study uses four provinces to represent Indonesian tourism: Jakarta, Jawa Timur, Bali, and Kepulauan Riau. The SPA result captures that Kepulauan Riau Province has the highest tourism multiplier effect and Jawa Timur has the highest coverage value. Moreover, the manufacturing sector receives the most benefit from the tourism effect, followed by trade, construction, agriculture, transportation, and electricity-gas. From a spatial perspective, tourism connections are not solely based on geographical proximity. Instead, they are established through an intricate supply chain network of manufactured goods. This emphasizes the significance of considering supply chain dynamics when investigating inter-regional relationships in the tourism sector.Originality/valueThis research contributes to the literature by estimating the IRIOT in 2019, disaggregating tourism activities from related economic sectors, constructing tourism-extended IRIOT, and identifying the critical path of tourism effect in numerous provinces with different economic structures. This novel approach offers valuable insights into the full spectrum of tourism’s economic impact, which has not been previously explored in this depth. This study is useful for policymaking, investment insight, and disaster mitigation.
Study of liquid photopolymer 3D printing resins exposed to accelerated aging for cultural heritage purposes
Authors: Higueras María , Carrasco-Huertas Ana , Calero-Castillo Ana Isabel , Moreno Alcaide Manuel , Collado Montero Francisco José 
Published: July 2024

Purpose
This paper aims to study the suitability of a selection of 3D printing liquid photopolymer resins for their application in the cultural heritage context.

Design/methodology/approach
The main concerns regarding the conservation and restoration of cultural assets are the chemical composition and long-term behavior of the new materials that will be in contact with the original object. Because of this, four different LED curing resins were exposed to an accelerated aging procedure and tested to identify the materials which demonstrated a better result. Some specific properties of the material (color, glossiness, pH and volatile organic compound emissions) were measured before and after the exposure.

Findings
Some of the properties measured reported good results demonstrating a decent stability against the selected aging conditions. The main changes were produced in the colorimetric aspect, probably indicating other chemical reactions in the material. Likewise, a case study could be also executed to demonstrate the usefulness of these materials in the cultural field.

Research limitations/implications
It is necessary to study in more detail the long-lasting behavior of the materials employed with these technologies. Further analysis should be carried out highlighting the chemical composition and degradation process of the materials proposed.

Originality/value
This paper contributes to the introduction of curing 3D printing resins in the restoration methodologies of cultural assets. For this, the study of a selection of properties represents the first stage to suggest or reject their use.
Interviewing students with special needs: Developing ethical considerations and interviewing protocols
Authors: Amjad Amjad Islam , Malik Muhammad Abid 
Published: July 2024

AbstractInterviewing students with special needs (SSNs) comes with a unique set of ethical and practical challenges that require highly specialised skills and interviewing protocols. Our objectives were to identify the most appropriate tools for collecting data from SSNs, key differences in interviewing students with and without special needs, and ethical and practical challenges during it. The ultimate goal was to develop ethical considerations and interviewing protocols for SSNs (ECIP4SSN). It was done through a two‐step Delphi method, collecting data from 11 special education experts from 11 different countries. The experts believed the tools should be selected based on the study's nature; however, many of them preferred the interviews. They believed that interviewing special students is challenging due to their special needs. Challenges pertaining to consent, hyperactivity, emotional distress, and wrong and irrelevant answers were among the top challenges mentioned by them. Final ECIP4SSN consisted of the key ethical considerations and interviewing protocols i.e. obtaining the background information and support, training and preparations, consent, data collection, building rapport, emotional support, confidentiality, and anonymity, using supporting tools, language, methods of asking questions and validating responses. The ECIP4SSN will guide the university teachers, students and researchers in interviewing special students.