bluuebunny/crossref_metadata_2025_split huggingface dataset:
Designing and evaluation of a mixed reality system for crime scene investigation training: a hybrid approach
Authors: Albeedan Meshal , Kolivanda Hoshang , Hammady Ramy 
Published: June 2024

AbstractPolice investigation in real-life crime scenes is an essential aspect of forensic science education. However, the practicality of bringing young investigators to actual crime scenes is often hindered by the costs and challenges involved. In order to overcome these obstacles, new technologies such as mixed reality (MR) are being explored as potential solutions. MR technology offers an interactive and cost-effective way to simulate real-life crime scenes, providing a valuable training experience for young investigators. This paper presents a novel design of a MR system using Microsoft HoloLens 2.0, which is tailored to work in a spatial 3D scanned and reconstructed crime scene using FARO point cloud 3D scanner X130 blended with photogrammetry techniques. The system was developed through the lens of Experiential Learning Theory and designed using a participatory approach, providing a cost-effective solution to help trained Kuwaiti police officers enhance their investigative skills. In order to evaluate the system’s user experience and user interaction, the Questionnaire of User Interaction Satisfaction and User Experience Questionnaire were utilised. Forty-four young police officers evaluated the system. Police students showed positive levels of satisfaction with user interaction and overall user experience with minimal negative feedback. Female students showed higher satisfaction with the overall impression compared to male students. Based on the positive feedback regarding the system expansion, the system will be taken into the commercialisation stage in the future to be provided as an essential tool for crime scene education and investigation practices.
Structures of Laminar Lean Premixed H2/CH4/Air Polyhedral Flames: Effects of Flow Velocity, H2 Content and Equivalence Ratio
Authors: Shi Shuguo , Breicher Adrian , Schultheis Robin , Hartl Sandra , Barlow Robert S. , Geyer Dirk , Dreizler Andreas 
Published: June 2024

AbstractPolyhedral Bunsen flames, induced by hydrodynamic and thermo-diffusive instabilities, are characterized by periodic trough and cusp cellular structures along the conical flame front. In this study, the effects of flow velocity, hydrogen content, and equivalence ratio on the internal cellular structure of premixed fuel-lean hydrogen/methane/air polyhedral flames are experimentally investigated. A high-spatial-resolution one-dimensional Raman/Rayleigh scattering system is employed to measure the internal scalar structures of polyhedral flames in troughs and cusps. Planar laser-induced fluorescence of hydroxyl radicals and chemiluminescence imaging measurements are used to quantify the flame front morphology. In the experiments, stationary polyhedral flames with varying flow velocities from 1.65 to 2.50 m/s, hydrogen contents from 50 to 83%, and equivalence ratios from 0.53 to 0.64 are selected and measured. The results indicate that the positively curved troughs exhibit significantly higher hydrogen mole fractions and local equivalence ratios compared to the negatively curved cusps, due to the respective focusing/defocusing effect of trough/cusp structure on highly diffusive hydrogen. The hydrogen mole fraction and local equivalence ratio differences between troughs and cusps are first increased and then decreased with increasing measurement height from 5 to 13 mm, due to the three-dimensional effect of the flame front. With increasing flow velocity from 1.65 to 2.50 m/s, the hydrogen mole fraction and local equivalence ratio differences between troughs and cusps decrease, which is attributed to the overall decreasing curvatures in troughs and cusps due to the decreased residence time and increased velocity-induced strain. With increasing hydrogen content from 50 to 83%, the hydrogen mole fraction and local equivalence ratio differences between troughs and cusps are amplified, due to the enhanced effects of the flame front curvature and the differential diffusion of hydrogen. With increasing equivalence ratio from 0.53 to 0.64, a clear increasing trend in hydrogen mole fraction and equivalence ratio differences between troughs and cusps is observed at constant flow velocity condition, which is a trade-off result between increasing effective Lewis number and increasing curvatures in troughs and cusps.
The “IAS Management Attitude” scale: a tool for measuring consensus between experts and practitioners in invasion biology
Authors: Cerri Jacopo , Serra Elisa , Stefanuto Alberto , Mori Emiliano 
Published: June 2024

AbstractQuantifying attitudes towards invasive alien species (IAS) is fundamental to understanding the extent to which conservation scientists agree and can collaborate in their management. We tested the IAS Management Attitude scale (IMA), a shortened version of the Pest Management Attitude Scale, originally invented to quantify attitudes towards pests in New Zealand, as a tool to quantify broader attitudes towards IAS among bioinvasion experts in Italy. We administered an online questionnaire to a sample of experts working on biological invasions in Italy. We collected 316 answers, both from conservation practitioners (26.6%) and researchers (73.4%), and we used structural equation modeling to test for the psychometric properties of the scale and compare attitude scores between groups. The scale showed both a good reliability (Cronbach’s alpha = 0.7), validity (CFI = 0.99, TLI = 0.99, SRMR = 0.03, RMSE = 0.02) and measurement invariance, when comparing researchers and practitioners, as well as when comparing respondents working on different invasive taxa. Both researchers and practitioners, as well as respondents of a different age, had similar attitudes about IAS and their management. Our study shows that this shortened version of PMA scale, a simple scale originally conceived to measure attitudes towards invasive alien mammals, could indeed be used to quantify the attitudes of experts towards IAS, even in countries where the public debate about biological invasions is much more recent than in New Zealand. The scale could potentially be used both for large-scale and long-term research about the attitudes of experts about IAS.
Feasibility of risk assessment for breast cancer molecular subtypes
Authors: McCarthy Anne Marie , Ehsan Sarah , Hughes Kevin S. , Lehman Constance D. , Conant Emily F. , Kontos Despina , Armstrong Katrina , Chen Jinbo 
Published: June 2024

Abstract
Purpose
Few breast cancer risk assessment models account for the risk profiles of different tumor subtypes. This study evaluated whether a subtype-specific approach improves discrimination.

Methods
Among 3389 women who had a screening mammogram and were later diagnosed with invasive breast cancer we performed multinomial logistic regression with tumor subtype as the outcome and known breast cancer risk factors as predictors. Tumor subtypes were defined by expression of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) based on immunohistochemistry. Discrimination was assessed with the area under the receiver operating curve (AUC). Absolute risk of each subtype was estimated by proportioning Gail absolute risk estimates by the predicted probabilities for each subtype. We then compared risk factor distributions for women in the highest deciles of risk for each subtype.

Results
There were 3,073 ER/PR+ HER2 − , 340 ER/PR +HER2 + , 126 ER/PR−ER2+, and 300 triple-negative breast cancers (TNBC). Discrimination differed by subtype; ER/PR−HER2+ (AUC: 0.64, 95% CI 0.59, 0.69) and TNBC (AUC: 0.64, 95% CI 0.61, 0.68) had better discrimination than ER/PR+HER2+ (AUC: 0.61, 95% CI 0.58, 0.64). Compared to other subtypes, patients at high absolute risk of TNBC were younger, mostly Black, had no family history of breast cancer, and higher BMI. Those at high absolute risk of HER2+ cancers were younger and had lower BMI.

Conclusion
Our study provides proof of concept that stratifying risk prediction for breast cancer subtypes may enable identification of patients with unique profiles conferring increased risk for tumor subtypes.
Depression Literacy and Self-Reported Help-Giving Behaviour in Adolescents in Ireland
Authors: Byrne Sadhbh J. , Swords Lorraine , Nixon Elizabeth 
Published: June 2024

AbstractThis questionnaire-based study aimed to explore depression literacy (DL) and help-giving experiences in 12–18-year-old adolescents (N = 535, Mage = 14.9 years, 51.8% male) in Ireland. In response to a vignette depicting a character displaying symptoms of depression, 46.7% labelled these symptoms ‘depression’, with increasing age and empathy associated with increased likelihood of labelling as such. Almost all (92.1%) believed the character needed help, but the perceived helpfulness of potential responses varied. Over one-third (38.2%) indicated they knew someone who had displayed similar symptoms in the past year, with 85.2% of these reporting having helped this person. Reported help-giving responses included comforting the person, encouraging professional help-seeking, and informing an adult. The findings suggest adolescent DL can be best supported by developmentally-sensitive interventions that encourage empathy and the importance of engaging adults’ assistance.
A framework for physically consistent storylines of UK future mean sea level rise
Authors: Palmer Matthew D. , Harrison Benjamin J. , Gregory Jonathan M. , Hewitt Helene T. , Lowe Jason A. , Weeks Jennifer H. 
Published: June 2024

AbstractWe present a framework for developing storylines of UK sea level rise to aid risk communication and coastal adaptation planning. Our approach builds on the UK national climate projections (UKCP18) and maintains the same physically consistent methods that preserve component correlations and traceability between global mean sea level (GMSL) and local relative sea level (RSL). Five example storylines are presented that represent singular trajectories of future sea level rise drawn from the underlying large Monte Carlo simulations. The first three storylines span the total range of the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6) likely range GMSL projections across the SSP1-2.6 and SSP5-8.5 scenarios. The final two storylines are based upon recent high-end storylines of GMSL presented in AR6 and the recent literature. Our results suggest that even the most optimistic sea level rise outcomes for the UK will require adaptation of up to 1 m of sea level rise for large sections of coastline by 2300. For the storyline most consistent with current international greenhouse gas emissions pledges and a moderate sea level rise response, UK capital cities will experience between about 1 and 2 m of sea level rise by 2300, with continued rise beyond 2300. The storyline based on the upper end of the AR6 likely range sea level projections yields much larger values for UK capital cities that range between about 3 and 4 m at 2300. The two high-end scenarios, which are based on a recent study that showed accelerated sea level rise associated with ice sheet instability feedbacks, lead to sea level rise for UK capital cities at 2300 that range between about 8 m and 17 m. These magnitudes of rise would pose enormous challenges for UK coastal communities and are likely to be beyond the limits of adaptation at some locations.
Depth-dependent warming of the Gulf of Eilat (Aqaba)
Authors: Sengupta Sounav , Gildor Hezi , Ashkenazy Yosef 
Published: June 2024

AbstractThe Gulf of Eilat (Gulf of Aqaba) is a semi-enclosed basin situated at the northern end of the Red Sea, renowned for its exceptional marine ecosystem. To evaluate the response of the Gulf to climate variations, we analyzed various factors including temperature down to 700 m, surface air temperature, and heat fluxes. We find that the sea temperature is rising at all depths despite inconclusive trends in local atmospheric variables, including the surface air temperature. The Gulf’s sea surface temperature (SST) warms at a rate of a few hundredths of a degree Celsius per year, which is comparable to the warming of the global SST and the Mediterranean Sea. The increase in sea warming is linked to fewer winter deep mixing events that used to occur more frequently in the past. Based on the analysis of the ocean-atmosphere heat fluxes, we conclude that the lateral advection of heat from the southern part of the Gulf likely leads to an increase in water temperature in the northern part of the Gulf. Our findings suggest that local ocean warming is not necessarily associated with local processes, but rather with the warming of other remote locations.
Robust Picture Fuzzy Regression Functions Approach Based on M-Estimators for the Forecasting Problem
Authors: Bas Eren , Egrioglu Erol 
Published: June 2024

AbstractA picture fuzzy regression function approach is a fuzzy inference system method that uses as input the lagged variables of a time series and the positive, negative and neutral membership values obtained by picture fuzzy clustering method. In a picture fuzzy regression functions method, the parameter estimation is also obtained by ordinary least squares method. Since the picture fuzzy regression functions approach is based on the ordinary least squares method, the forecasting performance decreases when there are outliers in the time series. In this study, a picture fuzzy regression function approach that can be used even in the presence of outliers in a time series is proposed. In the proposed method, the parameter estimation for the picture fuzzy regression function approach is performed based on robust regression with Bisquare, Cauchy, Fair, Huber, Logistic, Talwar and Welsch functions. The forecasting performance of the proposed method is evaluated on the time series of the Spanish and the London stock exchange time series. The forecasting performance of these time series are evaluated separately for both the original and outlier cases. Besides, the proposed method is compared with several different fuzzy regression function approaches and a neural network method. Based on the results of the analysis, it is concluded that the proposed method outperforms the other methods even when the time series contains both original and outliers.
Beware of the Woozle effect and belief perseverance in the PLS-SEM literature!
Authors: Henseler Jörg , Lee Nick , Roemer Ellen , Kemény Ildikó , Dirsehan Taşkın , Cadogan John W. 
Published: June 2024

AbstractPartial least squares structural equation modeling (PLS-SEM) is a popular method of data analysis in marketing, information systems research, and related fields. Unfortunately, the literature on PLS-SEM contains a number of misstatements that ascribe characteristics to PLS-SEM that it does not possess. In our study, we consider why these misstatements continue to be made and reinforced. We show how inaccuracies, omissions, repetitions of past misconceptions, and the introduction of additional misconceptions lead to the so-called Woozle effect. As an example, we use perhaps the most serious misconception about PLS-SEM namely its alleged suitability for estimating the parameters of reflective measurement models. The Woozle effect is a cumulative process by which falsehoods become established as fact, and the self-correcting mechanisms of science are suspended. Through a literature review, we identify a number of factors that are likely to have contributed to the Woozle effect in the PLS-SEM literature. For the Woozle effect to disappear, researchers need to acknowledge that PLS-SEM, in its current incarnation, is not suitable for scientific work with reflective measurement models.
Mapping the landscape of ethical considerations in explainable AI research
Authors: Nannini Luca , Marchiori Manerba Marta , Beretta Isacco 
Published: June 2024

AbstractWith its potential to contribute to the ethical governance of AI, eXplainable AI (XAI) research frequently asserts its relevance to ethical considerations. Yet, the substantiation of these claims with rigorous ethical analysis and reflection remains largely unexamined. This contribution endeavors to scrutinize the relationship between XAI and ethical considerations. By systematically reviewing research papers mentioning ethical terms in XAI frameworks and tools, we investigate the extent and depth of ethical discussions in scholarly research. We observe a limited and often superficial engagement with ethical theories, with a tendency to acknowledge the importance of ethics, yet treating it as a monolithic and not contextualized concept. Our findings suggest a pressing need for a more nuanced and comprehensive integration of ethics in XAI research and practice. To support this, we propose to critically reconsider transparency and explainability in regards to ethical considerations during XAI systems design while accounting for ethical complexity in practice. As future research directions, we point to the promotion of interdisciplinary collaborations and education, also for underrepresented ethical perspectives. Such ethical grounding can guide the design of ethically robust XAI systems, aligning technical advancements with ethical considerations.
Dissecting bias of ChatGPT in college major recommendations
Authors: Zheng Alex 
Published: June 2024

AbstractLarge language models (LLMs) such as ChatGPT play a crucial role in guiding critical decisions nowadays, such as in choosing a college major. Therefore, it is essential to assess the limitations of these models’ recommendations and understand any potential biases that may mislead human decisions. In this study, I investigate bias in terms of GPT-3.5 Turbo’s college major recommendations for students with various profiles, looking at demographic disparities in factors such as race, gender, and socioeconomic status, as well as educational disparities such as score percentiles. To conduct this analysis, I sourced public data for California seniors who have taken standardized tests like the California Standard Test (CAST) in 2023. By constructing prompts for the ChatGPT API, allowing the model to recommend majors based on high school student profiles, I evaluate bias using various metrics, including the Jaccard Coefficient, Wasserstein Metric, and STEM Disparity Score. The results of this study reveal a significant disparity in the set of recommended college majors, irrespective of the bias metric applied. Notably, the most pronounced disparities are observed for students who fall into minority categories, such as LGBTQ + , Hispanic, or the socioeconomically disadvantaged. Within these groups, ChatGPT demonstrates a lower likelihood of recommending STEM majors compared to a baseline scenario where these criteria are unspecified. For example, when employing the STEM Disparity Score metric, an LGBTQ + student scoring at the 50th percentile faces a 50% reduced chance of receiving a STEM major recommendation in comparison to a male student, with all other factors held constant. Additionally, an average Asian student is three times more likely to receive a STEM major recommendation than an African-American student. Meanwhile, students facing socioeconomic disadvantages have a 30% lower chance of being recommended a STEM major compared to their more privileged counterparts. These findings highlight the pressing need to acknowledge and rectify biases within language models, especially when they play a critical role in shaping personalized decisions. Addressing these disparities is essential to foster a more equitable educational and career environment for all students.
Transcriptomic Analysis of Pubertal and Adult Virgin Mouse Mammary Epithelial and Stromal Cell Populations
Authors: Heijmans Nika , Wiese Katrin E. , Jonkers Jos , van Amerongen Renée 
Published: June 2024

AbstractConflicting data exist as to how mammary epithelial cell proliferation changes during the reproductive cycle. To study the effect of endogenous hormone fluctuations on gene expression in the mouse mammary gland, we performed bulk RNAseq analyses of epithelial and stromal cell populations that were isolated either during puberty or at different stages of the adult virgin estrous cycle. Our data confirm prior findings that proliferative changes do not occur in every mouse in every cycle. We also show that during the estrous cycle the main gene expression changes occur in adipocytes and fibroblasts. Finally, we present a comprehensive overview of the Wnt gene expression landscape in different mammary gland cell types in pubertal and adult mice. This work contributes to understanding the effects of physiological hormone fluctuations and locally produced signaling molecules on gene expression changes in the mammary gland during the reproductive cycle and should be a useful resource for future studies investigating gene expression patterns in different cell types across different developmental timepoints.
Thermoeconomic analysis and environmental impact assessment of the Akkuyu nuclear power plant
Authors: Saylan Elvin , Aygün Cemalettin 
Published: June 2024

AbstractWithin the scope of this study, a thermoeconomic analysis was carried out for Akkuyu Nuclear Power Plant (ANPP), the first nuclear power plant of Türkiye. As a result of the analysis, it is aimed to reduce the cost of energy production and prevent thermal pollution at the same time by converting the heat discharged into the environment into useful heat due to the working principle of NPP. Thermodynamic analysis was performed in the Engineering Equation Solver (EES) program using equipment values equivalent to ANPP. Cost analysis was performed using the specific exergy costing (SPECO) method, which is based on the second law of thermodynamics and is the most widely used cost analysis method. The study concludes that the energy efficiency is 35%, while the economic analysis shows that the best case has an exergy efficiency of 68% with a payback period of 7–8 years, and an electricity cost of $0.0196 per kWh. It is possible to use the heat discharged from the plant indirectly in district heating (heating, hot water needs of the lodgings, guesthouses in the facility), greenhouse heating, agricultural drying and heating, considering the geographical conditions and livelihood of the region. Thus, 68% of the waste heat was utilized, the unit cost of the energy produced was reduced and at the same time thermal pollution was reduced at the same rate. The results of the study can contribute to the efforts preventing energy waste, thermal environmental pollution, and reducing greenhouse gas emissions. Additionally, it could aid in the development of more energy-efficient and environmentally friendly power generation systems, including pioneering nuclear power plants in developing countries.