Analytical Framework Research Articles

On the comparison of regression coefficients across multiple logistic models with binary predictors

AbstractIn many applied contexts, it is of interest to identify the extent to which a given association measure changes its value as different sets of variables are included in the analysis. We consider logistic regression models where the interest is for the effect of a focal binary explanatory variable on a specific response, and a further collection of binary covariates is available. We provide a methodological framework for the joint analysis of the full set of coefficients of the focal variable computed across all the models obtained by adding or removing predictors from the set of covariates. The result is obtained by applying a specific log-hybrid linear expansion of the joint distribution of the variables that implicitly comprises all the regression coefficients of interest. In this way, we obtain a method that allows one to verify, in a flexible way, a wide range of scientific hypotheses involving the comparison of multiple logistic regression coefficients both in nested and in non-nested models. The proposed methodology is illustrated through a test bed example and an empirical application.

A strategic evaluation of BIM-driven information management in the context of ISO 19650-2 standard

PurposeThis paper presents an in-depth evaluation of BIM-driven information management in the context of ISO 19650-2. The study aimed to understand and evaluate the existing mechanisms and the recommended activities and tasks of collaborative information management, particularly as the Turkish AEC organizations are currently implementing ISO 19650-2.Design/methodology/approachThe study employed a qualitative research design based on information management stages of ISO 19650-2. Semi-structured interviews were conducted with purposefully selected professionals. The framework analyses were made with MAXQDA through conceptual coding to identify current drivers, challenges and incentives for BIM-driven information management. The frequencies of common themes, required tasks and semantic relationships were reported systematically and interpreted to provide a conceptual implementation map, practical insights and actionable recommendations.FindingsThe study results encompass strategies for establishing new tasks and implementation procedures to uphold business value by aligning information management standards with evolving project requirements, providing detailed and responsive EIRs, early use of CDEs, compliant production methods, clarity of roles and responsibilities, increased organizational capacity and capabilities, sustained planning and production quality and leveraging lessons learned.Originality/valueThe study provides evidence-based arguments and strategic insights for BIM-driven information management, focusing on the current implementation compatibilities with ISO 19650-2. Findings and discussions highlight the necessity of industry-wide transformations, reengineered activities/tasks and compliant information flows, which are crucial for adopting ISO 19650-2 and the formulation of national annex documents.

Lexical field theory: Key concepts and contemporary approaches

ABSTRACT The article aims to discuss the ideas and principles of Trier’s theory of lexical field and to demonstrate how the concept of field can be fruitfully employed outside of the domain of lexicology. The first part of the article deals with Trier’s main idea that no lexical-semantic element can be considered outside of its systemic relations: a given element (word) can be ascribed a certain significance only depending on the place it occupies in some system called a lexical field (Wortfeld). The second part of the article demonstrates how the field principle can be applied to the analysis of grammatical categories using the ‘functional-semantic field’ approach and the analysis of communicative behaviour using the ‘communicative-pragmatic field’ approach. The former helps to reveal and systematize sets of language elements of a specific language with respect to the coding of a certain categorial function. The latter makes it possible to summarize different possibilities for the realization of speech behaviour patterns and to rank them according to the degree of their usage frequency. These two cases prove that the field concept can be used to solve issues that are deemed unsolvable if one applies the framework of the traditional level-oriented linguistic analysis.

Why “free maternal healthcare” is not entirely free in Ghana: a qualitative exploration of the role of street-level bureaucratic power

BackgroundGhana introduced a free maternal healthcare policy within its National Health Insurance Scheme (NHIS) in 2008 to remove financial barriers to accessing maternal health services. Despite this policy, evidence suggests that women incur substantial out-of-pocket (OOP) payments for maternal health care. This study explores the underlying reasons for these persistent out-of-pocket payments within the context of Ghana’s free maternal healthcare policy.MethodsCross-sectional qualitative data were collected through interviews with a purposive sample of 14 mothers and 8 healthcare providers/administrators in two regions of Ghana between May and September 2022. All interviews were audio-recorded, transcribed and imported into the NVivo 14.0 software for analysis. An iteratively developed codebook guided the coding process. Our thematic data analysis followed the Attride-Sterling framework for network analysis, identifying basic, organising themes and global themes.ResultsWe found that health systems and demand-side factors are responsible for the persistence of OOP payments despite the existence of the free maternal healthcare policy in Ghana. Reasons for these payments arose from health systems factors, particularly, NHIS structural issues – delayed and insufficient reimbursements, inadequate NHIS benefit coverage, stockouts and supply chain challenges and demand-side factors – mothers’ lack of education about the NHIS benefit package, and passing of cost onto patients. Due to structural and system level challenges, healthcare providers, exercising their street-level bureaucratic power, have partly repackaged the policy, enabling the persistence of out-of-pocket payments for maternal healthcare.ConclusionsUrgent measures are required to address the structural and administrative issues confronting Ghana’s free maternal health policy; otherwise, Ghana may not achieve the sustainable development goals targets on maternal and child health.

A Study on Metallurgical Artifacts Excavated from Luojiaba Site H235 in the Eastern Sichuan Region during the Eastern Han Dynasty

Currently, research remains limited on ironworking workshops in China and even throughout East Asia. The discovery of Luojiaba Site H235 in 2021 provides significant new material on this issue. This paper comprehensively organized the metallurgical artifacts and employed technological methods such as XRF and SEM-EDS to analyze the slag and hammerscale excavated from Luojiaba Site H235. First, the chemical composition and microstructural phases of the slag were analyzed, with an examination of the hammerscale. Second, the processes leading to the formation of slag and hammerscale are discussed. Third, based on the scale of the site, the chemical composition, and the characteristic shapes of the slag, combined with Serneels’ theoretical framework for quantitative analysis of forging slag, the slag unearthed from Luojiaba Site H235 was tentatively categorized as forging slag. This suggests that the workshop primarily produced or repaired iron objects through forging. Finally, considering the furnace shapes observed at contemporary sites and discussions on the potential sources of iron materials at the Luojiaba site, speculations are made regarding the furnace structure at the Luojiaba site and the possible origin of its iron materials. Unlike ironworking workshops at other contemporary sites, the location of the forging workshop at Luojiaba Site H235 presents a distinctly different choice, situated within a village or town during the Eastern Han Dynasty. This choice of location may reflect a phenomenon closer to consumer proximity. Therefore, analyzing metallurgical artifacts unearthed from Luojiaba contributes to understanding the operation of ironworking workshops and the distribution of resources in village-level settlements in the eastern Sichuan region during the Eastern Han Dynasty.

The news values of fake news

Fake news poses a significant threat to society by undermining public trust and consensus on critical issues. Although there is a considerable amount of research on the linguistic features of fake news texts, a comprehensive understanding of how language is used to persuade and promote specific ideologies within them is still lacking. This study addresses this gap by analyzing fake news discourse through the lens of news values. We apply the Discursive News Values Analysis (DNVA) framework and key semantic domain analysis to a corpus of fake news stories on vaccination, climate change, and COVID-19. We identify a set of news values that differentiate fake from mainstream news discourse. Our findings reveal that fake news emphasizes negativity, unexpectedness, consonance, and facticity, while also relying on the previously undocumented news values of subversiveness, causality, religiosity, and historicity. These values form a powerful discursive toolkit exploited by fake news writers to craft compelling false narratives.

Whether higher risk indicates severe loss in the flood disaster assessment: A comparative analysis in the Hubei province of central China

Study regionHubei province, Yangtze River Basin, Central China Study focusRisk and loss analysis constitutes a critical element of flood disaster management. Nevertheless, the relationship between risk and loss has been infrequently examined in the literature. Here we developed a comparative analysis framework for assessing flood risk and loss in Hubei Province. The risk model incorporates 22 indicators in terms of hazard, exposure, vulnerability and emergency response & recovery capability. Indicator weights were determined through a combination of objective and subjective weighting methods based on the game theory. Flood risk and loss levels were classified using fuzzy comprehensive evaluation and grey correlation analysis respectively. New hydrological insightsAnnual risk and loss maps exhibit a spatial pattern of higher levels in the eastern regions and lower levels in the western regions. However, the relationship between risk and loss was not as well as expected during designated flood periods. While regions impacted by disasters typically demonstrated higher risk levels, the risk in the regions unaffected by flood disasters appeared to be overestimated. By analyzing flood risk and loss across various temporal scales, this research contributes a novel perspective for the evaluation of flood risk models.

Integrating deep phenotyping with genetic analysis: a comprehensive workflow for diagnosis and management of rare bone diseases.

Phenotypes play a fundamental role in medical genetics, serving as external manifestations of underlying genotypes. Deep phenotyping, a cornerstone of precision medicine, involves precise multi-system phenotype assessments, facilitating disease subtyping and genetic understanding. Despite their significance, the field lacks standardized protocols for accurate phenotype evaluation, hindering clinical comprehension and research comparability. We present a comprehensive workflow of deep phenotyping for rare bone diseases from the Genetics Clinic of Skeletal Deformity at Peking Union Medical College Hospital. Our workflow integrates referral, informed consent, and detailed phenotype evaluation through HPO standards, capturing nuanced phenotypic characteristics using clinical examinations, questionnaires, and multimedia documentation. Genetic testing and counseling follow, based on deep phenotyping results, ensuring personalized interventions. Multidisciplinary team consultations facilitate comprehensive patient care and clinical guideline development. Regular follow-up visits emphasize dynamic phenotype reassessment, ensuring treatment strategies remain responsive to evolving patient needs. In conclusion, this study highlights the importance of deep phenotyping in rare bone diseases, offering a standardized framework for phenotype evaluation, genetic analysis, and multidisciplinary intervention. By enhancing clinical care and research outcomes, this approach contributes to the advancement of precision medicine in the field of medical genetics.

Accelerating Neural Network Inference in Handwritten Digit Recognition — Comparative Study

In deep learning, one of the popular subclasses of multilayer perceptron is the Convolutional Neural Networks (CNNs), optimized for image and semantic segmentation tasks. With a large number of floating-point operations and relatively less data transfer in the training phase, CNNs are well suited to be handled by parallel architectures. The high accuracy of CNNs comes at the cost of consequential compute and memory demands. In this article, we present a comparative analysis of a pre-trained CNN framework for recognizing a handwritten digit on different processing platforms. The performance of the neural network as the function of the parallel processing platforms offers parametric insights and factors that influence the inference on state-of-the-art Graphics Processing Units (GPUs) and systolic arrays such as Eyeriss and Tensor Processing Unit (TPU). Through inference time analysis, we observed that the systolic arrays can outperform upto 58.7 times better than a Turing architecture powered GPU. We show that while the efficiency with which the available resources are utilized is higher in the existing GPUs (upto 32%) than the TPUs, the efficiency of application-specific systolic arrays can be on par with that of GPUs. We present the results obtained from three different customized systolic array-based platforms which can be adopted by the designers to decide the hardware optimization goal.

MEA2: A Lightweight Field-Sensitive Escape Analysis with Points-to Calculation for Golang

Escape analysis plays a crucial role in garbage-collected languages as it enables the allocation of non-escaping variables on the stack by identifying the dynamic lifetimes of objects and pointers. This helps in reducing heap allocations and alleviating garbage collection pressure. However, Go, as a garbage-collected language, employs a fast yet conservative escape analysis, which is field-insensitive and omits point-to-set calculation to expedite compilation. This results in more variables being allocated on the heap. Empirical statistics reveal that field access and indirect memory access are prevalent in real-world Go programs, suggesting potential opportunities for escape analysis to enhance program performance. In this paper, we propose MEA 2 , an escape analysis framework atop GoLLVM (an LLVM-based Go compiler), which combines field sensitivity and points-to analysis. Moreover, a novel generic function summary representation is designed to facilitate fast inter-procedural analysis. We evaluated it by using MEA 2 to perform stack allocation in 12 wildly-use open-source projects. The results show that, compared to Go’s escape analysis, MEA 2 can reduce heap allocation sites by 7.9

New experience of implementing patient e-referral in the Iranian health system: a qualitative study.

Implementing an electronic system of service categorization and a referral system in healthcare is a strategic approach to improving overall health outcomes and optimizing resource use. This study aimed to investigate challenges experienced with the electronic patient referral system in Mashhad University of Medical Sciences (MUMS). In this qualitative research, data were collected using semi-structured interviews. Participants included physicians, experts, and stakeholders working in the Family Physician Program and the referral system, selected through purposive sampling. The data were analyzed using a thematic analysis framework, in which a thematic framework was developed, and key themes were identified. Data analysis was performed using Atlas.ti8 software. According to the interviewees, the challenges of digitizing the referral system can be categorized into three main themes: structure, process, and outcomes. These themes include ten sub-themes, such as challenges related to Internet Infrastructure and the Sina System, Patients' Choice of Desired Specialists, Receiving Payment for Services, Appointment Scheduling, Interdepartmental Coordination, Recording Definitive Diagnosis Codes Before Referral, False Referrals, Dissatisfaction, Feedbacks, and Health Indicators. To improve the e-referral in Iran's health system, several strategies can be implemented. These include sustainable resource allocation, designing consequence mechanisms within the referral system to motivate collaboration and improving appointment scheduling systems. Furthermore, addressing these challenges requires a collaborative approach involving healthcare providers, IT professionals, and patient representatives to ensure that the system is efficient, user-friendly, and effectively meets the needs of all parties involved. Not paying enough attention to these issues cause reform failure while solving them requires multi-dimensional, systematic and coordinated interventions with a deep understanding of the obstacles and challenges. Disregarding these factors may result in apathy over time, ultimately impacting both the quantity and, more importantly, the quality of services.

On the Utilization of Emoji Encoding and Data Preprocessing with a Combined CNN-LSTM Framework for Arabic Sentiment Analysis

Social media users often express their emotions through text in posts and tweets, and these can be used for sentiment analysis, identifying text as positive or negative. Sentiment analysis is critical for different fields such as politics, tourism, e-commerce, education, and health. However, sentiment analysis approaches that perform well on English text encounter challenges with Arabic text due to its morphological complexity. Effective data preprocessing and machine learning techniques are essential to overcome these challenges and provide insightful sentiment predictions for Arabic text. This paper evaluates a combined CNN-LSTM framework with emoji encoding for Arabic Sentiment Analysis, using the Arabic Sentiment Twitter Corpus (ASTC) dataset. Three experiments were conducted with eight-parameter fusion approaches to evaluate the effect of data preprocessing, namely the effect of emoji encoding on their real and emotional meaning. Emoji meanings were collected from four websites specialized in finding the meaning of emojis in social media. Furthermore, the Keras tuner optimized the CNN-LSTM parameters during the 5-fold cross-validation process. The highest accuracy rate (91.85%) was achieved by keeping non-Arabic words and removing punctuation, using the Snowball stemmer after encoding emojis into Arabic text, and applying Keras embedding. This approach is competitive with other state-of-the-art approaches, showing that emoji encoding enriches text by accurately reflecting emotions, and enabling investigation of the effect of data preprocessing, allowing the hybrid model to achieve comparable results to the study using the same ASTC dataset, thereby improving sentiment analysis accuracy.

An exploration of teacher and school-based nurse perceptions of current HPV education offered to students 15-16 years old in post-primary schools in Northern Ireland, UK.

Human papillomavirus virus (HPV) is highest among young adults 15-24 years old. High-risk strains are responsible for the development of cancers including cervical, vaginal, vulvar, anal, oropharyngeal and penile. Despite HPV school-based vaccination programmes in the UK, HPV vaccination uptake rates continue to fluctuate due to misinformation and vaccine hesitancy post COVID-19. The aim of this study is to explore perceptions of post-primary school teachers and nurses regarding the current HPV education provision and the need to provide HPV education to students 15-17 years old when they are most likely to be becoming sexually active. A qualitative study was conducted using online semi-structured interviews between February-August 2022 with post-primary teachers and nurses in Northern Ireland, UK. Stratified random sampling was used to contact schools to recruit participants. Recruitment continued until data saturation was reached. Braun & Clarke's six-phase framework for reflexive thematic analysis was used to analyse the data. Twelve teachers and six nurses participated in the study. Four themes arose based on the analysis including 1) the importance of HPV education 2) self-consent to the HPV vaccine 3) design of the HPV education and 4) delivery of the HPV education. Identified barriers to implementation of HPV education included lack of parental education, religion and the conservative culture of Northern Ireland. Participants perceived HPV education to be poor or non-existent in their schools but placed high importance on this education. They indicated that a non-judgemental health professional would be the ideal person to deliver interactive HPV education as part of a mandated spiral curriculum. HPV education at 15-17 years old provides students with an opportunity to learn about their HPV risk, their HPV vaccination status and an opportunity to self-consent to the HPV vaccine. The Education Authority and Department of Health should support health professionals to deliver consistent robust HPV health information to students of this age.

Immunosuppressive medication adherence and affecting factors in solid organ transplantation patients: a mixed-methods study

Objectives: Transplantation is a form of treatment that requires long-term pharmacotherapy. After transplantation, patients may have difficulty adapting to medication use for various reasons, and this may result in rejection. The aim of this study is to determine participants’ medication compliance and the factors affecting it. Methods: The research was conducted with a sequential explanatory mixed method. In the study, quantitative data were collected using the Turkish Immunosuppressive Medication Adherence Scale, and qualitative data were collected using the In-Depth Individual Interview Guide. Quantitative data were analyzed using statistical methods, and qualitative data were examined according to Braun and Clarke's thematic analysis framework. Results: In this study, 62.3% of the participants were male, 37.0% were 50 years old and over, 71.3% lived with their spouse, 54.0% had primary and secondary school education, and 42.0% could not work due to their current health condition. From a clinical perspective, it was determined that 78% of the transplants were kidney transplants, and 41.3% were more than 4 years after transplantation. 74.3% of the transplants were from living donors. The mean score of the immunosuppressive medication compliance scale was determined to be 40.91±4.09. In the qualitative data analysis of the study, factors affecting medication adherence were examined and the themes of "individual factors", "complexity of the regimen" and "social support resources" were obtained. The sub-themes of the individual factors theme are reluctance, hopelessness and addiction; Sub-themes of the complexity of the regimen theme are drug side effects and polypharmacy; The sub-themes of the social support resources theme are loneliness and family pressure. Conclusions: The factors influencing medication adherence among organ transplant recipients have been investigated, revealing that adherence levels vary significantly depending on various factors. These findings underscore the importance of tailored care strategies and individualized support approaches.

An agile city? Tactical urbanism and responses to protracted displacement in the City of Amman, Jordan

This study seeks to understand the working dynamics through which Greater Amman Municipality (GAM) responds to the challenges of protracted displacement in the city, focusing particularly on the concept of “tactical urbanism” (TU) as a tool and framework. This could be broadly useful to key actors in reconsidering response strategies, strengthening the role of local administrations. The research adopted a qualitative data collection and analysis framework via participatory forums and key informant interviews, steered by guiding research questions. Findings reveal the presence of interconnected multi-scale limitations, opportunities and roles that determine GAM’s response towards displacement and constrain its ability to act within a comprehensive planning rationale. Instead, GAM is driven towards TU as an alternative approach that mitigates these determinants and offers a means for more responsive, constructive action. It is argued that TU affords a more agile response towards displacement, enhancing community engagement, innovation, resilience and identity.

Efficient Random Field Generation With Rotational Anisotropy for Probabilistic SPH Analysis of Slope Failure

ABSTRACTDue to geological processes such as sedimentation, tectonic movement, and backfilling, natural soil often exhibits characteristics of rotated anisotropy. Recent studies have shown the significant impact of rotated anisotropy on slope stability. However, little research has explored how this rotated anisotropy affects the large deformations occurring after slope failure. Therefore, this study integrates rotated random field theory with smoothed particle hydrodynamics (SPH) to investigate its influence on post‐failure slope behavior. Focusing on a typical slope scenario, this research utilizes graphics processing unit (GPU)–accelerated covariance matrix decomposition (CMD) method to create rotated anisotropy random fields and applies the SPH framework for analysis. It examines the influence of rotated anisotropy angles and the cross‐correlation between cohesion and internal friction angle on landslides. The results indicate that the rotational anisotropy of the slope significantly influences post‐failure behavior. When the rotation angle is close to the slope surface, it tends to amplify both the magnitude and variability of slope failure. Furthermore, the study evaluates the efficiency of generating these random fields and emphasizes the substantial computational speed improvements achieved with GPU acceleration. These findings offer a robust approach for probabilistic analysis of slope large deformations considering rotated anisotropy. They provide a theoretical foundation for accurately assessing the risk of slope collapse, holding significant practical implications for geotechnical engineering.

ADDRESSING INFRASTRUCTURE GAPS IN MUMBAI’S 2-WHEELER EV CHARGING NETWORK: A FOCUS ON ACCESSIBILITY, USABILITY, AND USER FEEDBACK

Electric vehicles (EVs) are transforming transportation in Mumbai, with 2-wheeler EVs gaining significant traction among commuters. However, the insufficient availability and accessibility of charging infrastructure remain critical challenges. This study investigates the experiences of 2- wheeler EV users in Mumbai, focusing on the barriers they encounter when charging their vehicles. Given Mumbai’s dense traffic and urban complexities, limited charging points, long waiting times, and infrastructural constraints can hinder the user experience and discourage further adoption of EVs. The findings provide key insights into optimal charging station locations based on a comprehensive analysis of population density, traffic flow, and urban planning frameworks. Additionally, the study addresses the need for standardized charging protocols, advanced technologies, and user-friendly interfaces to enhance the usability of charging stations. The study emphasizes that addressing these challenges is crucial not only for the user experience but also for policymakers, urban planners, and stakeholders aiming to expand Mumbai’s EV infrastructure. Moreover, the environmental benefits of 2-wheeler EV adoption are examined, including reductions in energy consumption, carbon emissions, and overall environmental impact. By analyzing these factors, the research highlights the positive environmental outcomes of investing in robust charging infrastructure. Key challenges, such as high costs, feasibility concerns, and policy limitations, are also explored, offering a holistic understanding of the practical barriers to improving the EV charging network. The study concludes with actionable recommendations aimed at overcoming these challenges, fostering sustainable growth, and ensuring the efficient deployment of 2-wheeler EV charging infrastructure across Mumbai.

5120 Contribution Of Proximal Femur Geometry And Bone Density Distribution To Hip Fragility In Adults ≥ 50yrs With Longstanding Type 1 Diabetes

Abstract Disclosure: F. Johannesdottir: None. C. D’Mello: None. A.B. Murthy: None. B. Zahedi: None. K. Engelke: None. M.L. Bouxsein: None. E.W. Yu: Grant Recipient; Self; Amgen Inc. Introduction: Adults with type 1 diabetes (T1D) have a 6-fold increased risk of hip fracture, which is explained only in part by lower areal bone mineral density (aBMD) by DXA. We hypothesize that femoral geometry and regional bone deficits at the proximal femur contribute to higher hip fracture risk in older adults with T1D. Further, we determine the influence of age at T1D diagnosis on femoral bone density and structure. Methods: We enrolled 97 individuals with T1D and 53 non-diabetic controls (CON) as part of the T1D Bone Health Connection (BEACON) Study, an ongoing prospective study of adults aged ≥50 years. We obtained computed tomography (CT) scans of the proximal femur (in-plane pixel size 0.98x0.98 mm, 1.25 mm slice thickness) to measure total (Tt), trabecular (Tb) and cortical (Ct) volumetric BMD (vBMD); and volume (Vol) and Ct thickness (Th) in several regions, including total hip, femoral neck (FN), trochanter (TR) and intertrochanter (IT) (Medical Image Analysis Framework, University of Erlangen, Germany). We also assessed total hip and FN aBMD by DXA. We employed ANCOVA models to compare bone outcomes between T1D and controls with adjustment for age, height, and weight, stratified by sex. When comparing bone outcomes within T1D, we adjusted for age, height, weight, and sex. Differences are reported as % difference between the least-square means for the groups. Results: The average age of participants was 64±7 yrs, and similar between T1D and CON (p=0.21). Male T1D were shorter than male CON (173 cm vs 176 cm, p=0.05), but with similar weight (p=0.73). Female T1D were heavier than female CON (71 kg vs 64 kg, p=0.03). The T1D cohort included 50 men and 47 women with mean diabetes duration of 46±10 yrs, mean A1c 7.1±1.0%, and median age at onset 17 yrs (IQR:10-25). Among T1D, 31 (52% female) were diagnosed ≤ age 12. Among men, total hip and FN aBMD did not differ by group, but T1D had smaller FN Tt.Vol (9%) and FN width (8%) (p<0.05 for all). In contrast, there were no differences between T1D and CON in the female cohort, neither by DXA nor CT (p≥0.13). Of note, T1D men appeared to have more poorly controlled diabetes than women (29% of men vs 11% women had A1c ≥8%, p=0.03). Within T1D, those who were diagnosed ≤ age 12 had lower Tb.vBMD (16-18%) at the total hip, TR and IT regions (p<0.05) and tended to have lower Tb.vBMD (16%, p=0.06) at the neck compared to those diagnosed at a later age, but no differences in DXA aBMD (p>0.31). Conclusion: In sum, older men, but not women, with T1D showed some deficits in bone structure at the proximal femur. Adults with T1D who were diagnosed ≤ age 12 had trabecular bone deficits within the proximal femur. Additional studies are needed to identify mechanisms underlying the high hip fracture risk in T1D. Presentation: 6/1/2024

MAGPIE: a web-based, open-source framework for plate vibration analysis

The analysis and simulation of plate vibrations are central to many branches of science and engineering, specifically acoustics and musical acoustics. Well-developed plate theories exist, along with numerous simulation software packages, but they are seldom available in open-source form and are not easily accessible to a greater audience. MAGPIE is a framework for interacting with a novel finite difference scheme for plates under general elastic boundary conditions. Free, clamped, and simply supported boundary conditions are obtainable by setting stiffness coefficients to very small or large values. Boundary conditions are parameterised which allow for intermediate possibilities. A web browser based implementation of the framework includes interactive elements. Users begin by providing parameters for an isotropic plate. These parameters are then used to generate visualisations of the mode shapes from the finite difference scheme simulation. Elastic boundary conditions can then be changed on a continuous scale to see their effect on mode shapes. Results are then available for export in common image and data formats. MAGPIE aims to make it easier to explain concepts such as mode shapes to a wider audience and also provide a tool for research that is accessible to students, scientists and musical instrument builders.

Unified framework for stochastic dynamic responses and system reliability analysis of long-span cable-stayed bridges under near-fault ground motions

Long-span cable-stayed bridges are complex systems with numerous components, and prone to failures of multiple components under near-fault ground motions with long-period velocity pulses. The evaluation of dynamic system reliability of cable-stayed bridges is an important challenging issue. In this work, a unified framework for simultaneously determining both the stochastic dynamic responses and system reliabilities of long-span cable-stayed bridges under near-fault stochastic ground motions is proposed based on direct probability integral method (DPIM) with adaptive strategy. Firstly, the 3-dimensional finite element model of typical cable-stayed bridge and the stochastic synthesis model of near-fault ground motions are established. Based on probability density integral equation, new formulas in input probability space of time-variant moments of response are derived. Then, DPIM with adaptive strategy is suggested to calculate the mean value and standard deviation of response via new formulas. Dynamic system reliability of cable-stayed bridge under near-fault stochastic ground motions is evaluated by establishing failure criteria of extreme value mappings of multiple performance functions. Finally, numerical results indicate that the long-period velocity pulse of near-fault motions imposes an important effect, resulting in large mean responses and failure of cables. Failure probability of cables is significantly increased with the occurrence of velocity pulses, which causes the decrease of system reliability of cable-stayed bridge. Thus, the randomness and velocity pulse effect of near-fault ground motions should be seriously considered for reliability-based design and safety assessment of cable-stayed bridges.