bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Influence of Sex and Gender, Gender Ontological Beliefs, and Sexism on Pain Sensitivity Judgments: Implications for Health Care Settings and Beyond
Authors: Vetterlein Annabel , Reuter Martin , von Häfen Lina , Dressler Sara , Plieger Thomas 
Published: June 2024

AbstractChronic pain affects at least one in five individuals. Hence, adequate pain judgement is a vital interpersonal skill. Nonetheless, women often face treatment disparities due to biased assessments. Priorly, sex and gender (i.e., biological category vs. cultural representation) have not been investigated separately. Our study was thus designed to disentangle their distinct influence on pain judgments. In an online study, N = 679 participants (73.8% female) were presented with a novel vignettes paradigm including descriptions of fictional gender-stereotypical and counter-stereotypical women and men. Participants were instructed to rate the characters’ pain sensitivity before completing inventories measuring gender ontological beliefs and ambivalent sexism. We found significant interaction effects of observer and character sex, in that higher pain sensitivity was attributed to opposite-sex characters. Men showed a higher sex bias, which was partially mediated by lower social constructionism and higher hostile sexism. We further uncovered a gender bias across observers, in that feminine characters were assumed to be more pain sensitive, irrespective of their sex. Our research underscores the presence of sex and gender biases in pain judgments, even in scenarios with minimal contextual cues. Despite limitations, the findings offer insights for the development of intervention strategies, which might reduce treatment disparities.
Testing driver warning systems for off-road industrial vehicles using a cyber-physical simulator
Authors: Garcia-Carrillo Dan , Garcia Roberto , Pañeda Xabiel G. , Mourao Filipa , Melendi David , Corcoba Victor , Paiva Sara 
Published: June 2024

AbstractADAS (Advanced Driver Assistance Systems) are becoming increasingly popular in on-road vehicles due to their safety, productivity, and cost savings. In the same way, off-road vehicles can benefit from ADAS systems to improve the security of drivers and workers in industrial settings. In this work, we study, design, and develop a novel security system to be integrated into industrial vehicles. This system is built to provide one-way Human Computer Interaction, from the computer to the human, so providing, through the interaction with the ADAS system, feedback to drivers about their surroundings, such as nearby workers, and thus helping to avoid collisions and prevent incidents. The study evaluates the quality of different feedback mechanisms, with the goal of designing the ADAS that produces the best User eXperience (UX). These feedback mechanisms are generated by LEDs in different display formats and colors, as well as with haptic feedback. We created a hybrid testbed using a realistic ADAS and a forklift simulator, integrating the system into a physical structure that resembles an industrial vehicle (a forklift) and used a computer-based simulation of a warehouse to gather the information from users. We performed a study with 36 people for the evaluation of the different feedback mechanisms tested, evaluating the results both from an objective point of view based on the results of the simulation, and a subjective point of view through a questionnaire and the stress of the users in each test.
Children with obesity have poorer circadian health as assessed by a global circadian health score
Authors: Rodríguez-Martín María , Martínez-Lozano Nuria , Santaclara-Maneiro Vicente , Gris-Peñas Antonio , Salmerón Diego , Ríos Rafael , Tvarijonaviciute Asta , Garaulet Marta 
Published: June 2024

Abstract
Background
Circadian health refers to individuals’ well-being and balance in terms of their circadian rhythm. It is influenced by external cues. In adults, a close relationship between circadian-related alterations and obesity has been described. However, studies in children are scarce, and circadian health and its association with obesity have not been evaluated globally. We aimed to assess whether circadian health differed between children with and without obesity as determined by a global circadian score (GCS) in a school-age population.

Methods
Four hundred and thirty-two children (7–12 years) were recruited in Spain. Non-invasive tools were used to calculate the GCS: (1) 7-day rhythm of wrist temperature (T), activity (A), position (P), an integrative variable that combines T, A, and P (TAP); (2) cortisol; and (3) 7-day food and sleep records. Body mass index, body fat percentage, waist circumference (WC), melatonin concentration, and cardiometabolic marker levels were determined.

Results
Circadian health, as assessed by the GCS, differed among children with obesity, overweight, and normal weight, with poorer circadian health among children with obesity. Children with obesity and abdominal obesity had 3.54 and 2.39 greater odds of having poor circadian health, respectively, than did those with normal weight or low WC. The percentage of rhythmicity, a marker of the robustness of the TAP rhythm, and the amplitude, both components of the GCS, decreased with increasing obesity. Different lifestyle behaviors were involved in the association between circadian health and obesity, particularly protein intake (P = 0.024), physical activity level (P = 0.076) and chronotype (P = 0.029).

Conclusions
The GCS can capture the relationship between circadian health and obesity in school-age children. Protein intake, physical activity level, and chronotype were involved in this association. Early intervention based on improving circadian health may help to prevent childhood obesity.
Food expensiveness in remote areas of Scotland: a natural experiment measuring the out-shopping effect
Authors: Russo Carlo , Revoredo-Giha Cesar 
Published: June 2024

AbstractThis paper investigates the effect of out-shopping (i.e., buying food outside local area) on food expensiveness in remote areas in Scotland, contributing to the literature on social factors affecting food security and food affordability in remote rural areas worldwide. It identifies out-shopping as a factor explaining why existing studies observing food prices at local stores in remote areas find much higher prices than at urban stores, while studies observing actual purchases of household in remote areas find small differences in food expensiveness with urban households. To investigate this difference, a food expensiveness index was constructed using home scanner data measuring households’ actual purchases. Data from the 2020 COVID-19 lockdown, when travel restriction limited out-shopping, were compared with the same period in 2019 when such restrictions were not in place. The results find that the premium paid in remote rural areas was small overall, but a statistically significant increase during lockdown was found for those households that lost access to discount stores because of movement restrictions. This result indicates that out-shopping is an important factor limiting food expensiveness in remote areas of Scotland and thus ensuring food affordability. Data suggest that approximately 42 percent of households in Scotland remote areas rely on out-shopping for obtaining affordable food.
How are We Doing Today? Using Natural Speech Analysis to Assess Older Adults’ Subjective Well-Being
Authors: Finze Nikola , Jechle Deinera , Faußer Stefan , Gewald Heiko 
Published: June 2024

AbstractThe research presents the development and test of a machine learning (ML) model to assess the subjective well-being of older adults based solely on natural speech. The use of such technologies can have a positive impact on healthcare delivery: the proposed ML model is patient-centric and securely uses user-generated data to provide sustainable value not only in the healthcare context but also to address the global challenge of demographic change, especially with respect to healthy aging. The developed model unobtrusively analyzes the vocal characteristics of older adults by utilizing natural language processing but without using speech recognition capabilities and adhering to the highest privacy standards. It is based on theories of subjective well-being, acoustic phonetics, and prosodic theories. The ML models were trained with voice data from volunteer participants and calibrated through the World Health Organization Quality of Life Questionnaire (WHOQOL), a widely accepted tool for assessing the subjective well-being of human beings. Using WHOQOL scores as a proxy, the developed model provides accurate numerical estimates of individuals’ subjective well-being.Different models were tested and compared. The regression model proves beneficial for detecting unexpected shifts in subjective well-being, whereas the support vector regression model performed best and achieved a mean absolute error of 10.90 with a standard deviation of 2.17. The results enhance the understanding of the subconscious information conveyed through natural speech. This offers multiple applications in healthcare and aging, as well as new ways to collect, analyze, and interpret self-reported user data. Practitioners can use these insights to develop a wealth of innovative products and services to help seniors maintain their independence longer, and physicians can gain much greater insight into changes in their patients’ subjective well-being.
Efficacy of disinfectants and heat treatments against green mould in casing soil and button mushroom (Agaricus bisporus) yield
Authors: Aydoğdu Mehmet 
Published: June 2024

AbstractButton mushroom (Agaricus bisporus) is the predominant mushroom species cultivated around the world. In the button mushroom cultivation, casing soil is one of the main substrate inducing emergence of mushrooms but presence of Trichoderma aggressivum f. aggressivum (causal agent of green mould disease) in casing soil causes devastating yield losses. However, little is known about management of the green mould in button mushroom cultivation. The aim of this study was to examine efficacy of several disinfectants and heat treatments against T. aggressivum f. aggressivum in casing soil and mushroom yield. In this respect, by considering yield (total amount of sporophores) values, in vivo experiments were separately set up according to randomized block design with three replications. As a result, compared to controls, disinfectants [hydrogen peroxide (H202), formaldehyde (CH2O), sodium hypochlorite (NaOCl) and hypochlorous acid (HOCl)] and heat treatments (60, 90 and 120 °C) significantly (P˂0.01) increased mushroom yields up to 18.74 and 24.06% in the treated plots, respectively. Biological efficiency values ranged from 87.16 to 105.72% in the disinfectant treatments, while they varied from 93.15 to 95.68% in the heat treatments. However, applications of the disinfectants at high doses had negative influence on growth of A. bisporus. The overall results suggest that the tested disinfectants and heat treatments may significantly increase button mushroom yield by suppressing development of T. aggressivum f. aggressivum in casing soil. The present study not only reveals management practices that can be used against the green mould in the in vivo but also presents new knowledge for mushroom industry.
‘Off–On’ determination of lead (Pb2+) and fluoride (F−) ion in fish and wastewater samples using N, S co-doped carbon quantum dots (N, S-CQDs)
Authors: Aladesuyi Olanrewaju Aladesanmi , Oluwafemi Oluwatobi Samuel 
Published: June 2024

AbstractLead is a global priority pollutant. Its presence in aquatic systems is harmful to the human health. Fluoride is essential to the human body, especially in dental health. However, excess fluoride in the body can lead to serious health concerns. Therefore, a simple approach to monitoring lead and fluoride in environmental samples is paramount. In this study, we synthesized N and S co-doped carbon quantum dots under the hydrothermal method by employing citric acid, glutamine, and sodium sulphide (Na2S) as precursors. Characterization of the developed nanosensor was carried out using Fourier transform infrared spectroscopy (FTIR), high-resolution transmission electron microscopy (HRTEM), photoluminescence (PL) spectrophotometer, ultraviolet–visible spectroscopy (UV–Vis), and X-ray diffraction (XRD). The as-prepared nanosensor is spherical with an average particle diameter of 3.45 ± 0.86 nm and emits light in the green region of the spectrum. This material was employed as an ‘on–off’ and ‘off–on’ fluorescent sensor to determine Pb2+ and F− rapidly and selectively. The fluorescence was quenched (turned off) in the presence of Pb2+ because of the strong interaction between Pb2+ ions and the surface functional groups of the as-synthesized material. Subsequently, the quenched fluorescence of the N, S-CQDs + Pb2+ system was restored (turned on) upon the introduction of F− ions, owing to the formation of ionic bonds between Pb2+ and F−. The N S-CQDs were selective towards Pb2+. At the same time, the N, S-CQDs + Pb2+ system exhibited selectivity towards F− ions amidst other ions with low detection limits (LODs) of 13.35 nM and 43.17 nM for Pb2+ and F−, respectively. The dynamic quenching mechanism was suggested based on the absorption spectra and lifetime results. Satisfied recoveries of 89.30–116.40% for Pb2+ and 90.22–115.05% for F- (RSD < 5) were obtained in practical samples of wastewater and fish. We believe that the as-synthesized N S-CQDs can effectively serve as reliable, accurate, and swift nanosensor for detecting Pb2+ and F− in environmental samples.
Use of gene expression programming to predict reference evapotranspiration in different climatic conditions
Authors: Raza Ali , Vishwakarma Dinesh Kumar , Acharki Siham , Al-Ansari Nadhir , Alshehri Fahad , Elbeltagi Ahmed 
Published: June 2024

AbstractEvapotranspiration plays a pivotal role in the hydrological cycle. It is essential to develop an accurate computational model for predicting reference evapotranspiration (RET) for agricultural and hydrological applications, especially for the management of irrigation systems, allocation of water resources, assessments of utilization and demand and water use allocations in rural and urban areas. The limitation of climatic data to estimate RET restricted the use of standard Penman–Monteith method recommended by food and agriculture organization (FAO-PM56). Therefore, the current study used climatic data such as minimum, maximum and mean air temperature (Tmax, Tmin, Tmean), mean relative humidity (RHmean), wind speed (U) and sunshine hours (N) to predict RET using gene expression programming (GEP) technique. In this study, a total of 17 different input meteorological combinations were used to develop RET models. The obtained results of each GEP model are compared with FAO-PM56 to evaluate its performance in both training and testing periods. The GEP-13 model (Tmax, Tmin, RHmean, U) showed the lowest errors (RMSE, MAE) and highest efficiencies (R2, NSE) in semi-arid (Faisalabad and Peshawar) and humid (Skardu) conditions while GEP-11 and GEP-12 perform best in arid (Multan, Jacobabad) conditions during training period. However, GEP-11 in Multan and Jacobabad, GEP-7 in Faisalabad, GEP-1 in Peshawar, GEP-13 in Islamabad and Skardu outperformed in testing period. In testing phase, the GEP models R2 values reach 0.99, RMSE values ranged from 0.27 to 2.65, MAE values from 0.21 to 1.85 and NSE values from 0.18 to 0.99. The study findings indicate that GEP is effective in predicting RET when there are minimal climatic data. Additionally, the mean relative humidity was identified as the most relevant factor across all climatic conditions. The findings of this study may be used to the planning and management of water resources in practical situations, as they demonstrate the impact of input variables on the RET associated with different climatic conditions.
No Agent in the Machine: Being Trustworthy and Responsible about AI
Authors: Conradie Niël Henk , Nagel Saskia K. 
Published: June 2024

AbstractMany recent AI policies have been structured under labels that follow a particular trend: national or international guidelines, policies or regulations, such as the EU’s and USA’s ‘Trustworthy AI’ and China’s and India’s adoption of ‘Responsible AI’, use a label that follows the recipe of [agentially loaded notion + ‘AI’]. A result of this branding, even if implicit, is to encourage the application by laypeople of these agentially loaded notions to the AI technologies themselves. Yet, these notions are appropriate only when applied to agents, which current AI technologies are not; and the concern is that this misapplication creates an incentive to inappropriately attribute trustworthiness or responsibility to AI technologies. We endeavour to show that we have good reason to avoid any general AI policy that uses agentially loaded labelling. We suggest labelling these policies not in terms of some qualification of AI, but rather in terms of our approach to the technology and its wider development and use context – focusing on being trustworthy and responsible about AI, rather than on trustworthy or responsible AI.
Effect of Number of Channels on Performance of PEM Fuel Cells for Serpentine Type Channel Configuration
Authors: Işıklı Fırat , Işıklı Hazal , Sürmen Ali 
Published: June 2024

Abstract
The number of gas flow channels in a serpentine-type channel configuration for Polymer Electrolyte Membrane Fuel Cells (PEMFC) is a critical design parameter. It influences mass transport, pressure drop, and water management, all of which contribute to the overall performance and efficiency of the fuel cell. In this study, different channel number configurations for small active area fuel cell and their role in contributing to a more sustainable energy environment are discussed. The influence of the number of multiple channels on the operational performance was examined in a fuel cell with 25 cm2 of active area. Six different flow channel configurations belonging to the traditional serpentine-designed flow channel were utilized, with multiple inlet–outlet structures. Numerical calculations for pressure, velocity, distribution of reactants (oxygen and hydrogen), membrane water content, and changes in water saturation concentration were conducted using the ANSYS Fluent program. The highest power density of 0.657 W/cm2 was achieved in the single-channel design, resulting in a 14% performance increase compared to the eight-channel design, which exhibited the lowest performance. However, the highest pumping loss due to pressure drop was observed in the serpentine one-channel design at 0.016573 W/cm2. While the pressure drop enhances performance in the same channel design, when constructing a fuel cell stack with a large number of cells, significant difficulties may arise in procuring a compressor capable of providing the desired pressure and flow rate. Therefore, alternative designs with reduced pressure drop need to be considered.
Comparison Analysis of Seepage Through Homogenous Embankment Dams Using Physical, Mathematical and Numerical Models
Authors: Al-Janabi Ahmed Mohammed Sami , Dibs Hayder , Sammen Saad Sh. , Yusuf Badronnisa , Ikram Rana Muhammad Adnan , Alzuhairy Sabih Hashim , Kisi Ozgur 
Published: June 2024

AbstractEmbankment dams have many advantages; however, they frequently develop seepage problems which may cause dams’ failure. In this study, comparison analysis of seepage through embankment dams was conducted using three different methods, namely experimental tests, mathematical calculations and numerical modeling. Three homogeneous embankment dam models with different downstream drainage filters were considered. Results revealed that SEEP/W model is inappropriate to compute the water flow volume if there is an intersection between the seepage flow line and the downstream slope of the embankment dam due to the appearance of pipes. Numerical modeling based on SEEP/W software was found to be compatible to the rest physical models. The findings also demonstrated that for all scenarios, both the Casagrande equations and the SEEP/W model produced seepage lines that closely matched the observed seepage lines. These results highlight the significance of managing the seepage line’s location to ensure the stability of embankment dams through the implementation of horizontal drains.
Urban Flood Mitigation Strategies with Coupled Gray–Green Measures: A Case Study in Guangzhou City, China
Authors: Li Jiayue , Zeng Jiajun , Huang Guoru , Chen Wenjie 
Published: June 2024

AbstractThe integration of gray and green infrastructure has proven to be a feasible approach for managing stormwater in established urban areas. However, evaluating the specific contributions of such coupled strategies is challenging. This study introduced a novel integrated hydrological-hydrodynamic model that takes into account the layout of low-impact development (LID) facilities along with pipeline alignment and rehabilitation. Reliable results from modeling were used to assess the individual contribution of LID and improved drainage facilities to urban flooding mitigation. We selected a natural island in Guangzhou City, China, as the study site. The results indicate that combining three LID measures, namely green roofs, sunken green spaces, and permeable pavements, can reduce total runoff by 41.7% to 25.89% for rainfall recurrence periods ranging from 1 year to 100 years, and decrease the volume of nodal overflow by nearly half during rainfall events of less than 10-year return period. By integrating LID measures with the upgraded gray infrastructure, the regional pipeline overloading condition is substantially alleviated, resulting in a significant improvement in pipeline system resilience. For urban flooding control, it is recommended to integrate sufficient green space and avoid pipe-laying structural issues during urban planning and construction. The findings may assist stakeholders in developing strategies to best utilize gray and green infrastructure in mitigating the negative effects of urban flooding.
Correlated high throughput nanoindentation mapping and microstructural characterization of wire and arc additively manufactured 2205 duplex stainless steel
Authors: Queguineur Antoine , Cherukuri Rahul , Lambai Aloshious , Dalal Manasi Sameer , Peura Pasi , Mohanty Gaurav , Hascoët Jean-Yves , Ituarte Iñigo Flores 
Published: June 2024

AbstractDuplex stainless steels (DSS) in wire and arc additive manufacturing (WAAM) have attracted significant research attention due to their mechanical properties and corrosion resistance. This study uses conventional and nanomechanical testing methods to compare the mechanical and microstructural behaviors at macroscopic and microscopic length scales. Macro hardness (HV10) testing yielded 259 and 249 in low and high heat input (HI) samples, respectively, while ferrite content averaged 52.7 and 48.5%. However, these results fail to provide conclusive insight into the potential influence of microstructural variations at the macroscopic level, likely due to the composite response of the material. To overcome this limitation, the mechanical response of the DSS samples is assessed at the grain level via high throughput nanoindentation mapping with image processing to track the location of each indent. This approach enabled differentiating the indents landing on ferrite and austenite phases as well as those landing on the interfaces. The results showed that the austenite phase had higher hardness (4.30 and 4.35 GPa) than the ferrite phase (3.89 GPa and 4.03 GPa) for high and low HI samples, respectively. The observed differences in hardness between the phases can be attributed to higher nitrogen content in the austenitic phase.