bluuebunny/crossref_metadata_2025 huggingface dataset:
Flame Evolution Characteristics for Hydrogen/LPG Co-Combustion in a Counter-Burner
Authors: Ghazal Rabeea M. , Akroot Abdulrazzak , Abdul Wahhab Hasanain A.
Published: February 2025

Industrial development and population growth have significantly escalated worldwide energy demand; in addition, the heightened consumption of primary energy sources such as hydrocarbons has profoundly impacted the atmospheric environment. Among all potential fuels, hydrogen provides the most significant advantages for energy supply and environmental sustainability. Nonetheless, the combustion of pure hydrogen has challenges related to its production, storage, and utilization. A more effective approach to improve combustion is to utilize hydrogen as an addition to fossil fuels. Hydrogen possesses numerous characteristics that render it a compelling fuel alternative. It possesses high energy density, offering triple the energy compared to liquefied petroleum gas. This indicates that hydrogen is able to deliver equal power output with reduced fuel usage, thus decreasing the fuel used and, consequently, greenhouse gasses linked to combustion. In this study, practical experiments and computer simulations were adopted to predict the behavior of some characteristics of the combustion of Iraqi liquefied petroleum gas, such as flame temperature and laminar burning velocity, in addition to the effect of changing the equivalence ratio and hydrogen enrichment at rates ranging between 5 and 20% at a constant atmospheric pressure and temperature. In the practical aspect, a counter-flow burner was developed at the Training and Workshops Center, University of Technology, Iraq, for the purpose of performing practical experiments. In addition, a MATLAB R2023b program code was developed based on flame front image frames to analyze data and measure flame parameters, i.e., laminar burning velocity, flame temperature, and flame front diameter. While the commercial CFD Ansys Fluent version 17.2 program was used to numerically simulate the premixed counter-flame, the steady laminar flame (SLF) was used. Also, in order to implement the continuity of the numerical simulation, the momentum and energy equations of the counter-flow burner were solved. The results showed that increasing the hydrogen percentage caused an increase in the laminar burning velocity as well as the flame temperature; when the hydrogen percentage in the mixture was 20%, the increasing percentages in the practical experiments were about 25% and 19.6%, respectively, and the percentages in the numerical simulation were about 22.6% and 20.5%, respectively. Also, changing the equivalence ratio from 0.4 to 1.4 had an effect on the shape, color, and method of flame spread, where at the higher percentage, the shape changed and the color concentration increased, meaning that the temperature rose and the method of spread changed to an irregular one. Additionally, several recommendations are suggested for future endeavors in this domain.
Influence of Posture and Sleep Duration on Heart Rate Variability in Older Subjects
Authors: Yuda Emi , Yoshida Yutaka
Published: February 2025

Japan is facing challenges associated with its super-aging society, including increased social security burdens and a rise in the elderly workforce due to a declining younger labor force. Extending the healthy life expectancy is one countermeasure, necessitating lifestyle improvements such as frailty prevention and ensuring adequate sleep duration. This study investigated the relationship between heart rate variability (HRV) and sleep duration among older adults (aged ≥ 65) using electrocardiogram (ECG) and three-axis accelerometer data from the Allostatic State Mapping by the Ambulatory ECG Repository (ALLSTAR) database, recorded between January 2019 and March 2021. Inclusion criteria required a sinus rhythm and recording durations ≥80%. Continuous 24 h ECG and accelerometer data were analyzed for 55,154 participants (mean age 76 ± 6). The results consistently showed significant differences in HRV metrics, including MRRI, SDRR, ULF, LF, HF, and LF/HF, across sleep duration groups (G1–G4). Short-sleep groups (G4) exhibited decreased MRRI and SDRR and increased LF/HF, suggesting active lifestyles but reduced HRV. Conversely, long-sleep groups (G1) showed increased MRRI and reduced LF/HF but exhibited age-related declines in SDRR and ULF. These findings indicate that both insufficient and excessive sleep may contribute to HRV reduction in older adults. This study provides critical insights for improving elderly lifestyles through tailored interventions in exercise and sleep management.
PEMFC RUL Prediction for Non-Stationary Time Series Based on Crossformer Model
Authors: Zhou Ning , Zeng He , Zheng Zefei , Wang Ke , Zhou Jianxin
Published: February 2025

Proton-Exchange Membrane Fuel Cells (PEMFCs), as efficient and environmentally friendly energy conversion devices, have wide application potential in areas such as transportation, mobile power, and distributed energy. However, the remaining useful life (RUL) issue of PEMFCs has been one of the main challenges limiting their commercialization. The RUL prediction problem of PEMFCs exhibits characteristics of time series forecasting, but its data possess multidimensional features and non-stationarity, which limits the applicability of classical time series forecasting models like the Transformer in solving the RUL prediction problem. In this paper, we propose a PEMFC RUL prediction model based on the Crossformer for non-stationary time series (De-stationary-Crossformer). Firstly, the overall architecture adopts the Crossformer model to extract dependencies between different features and temporal dependencies. Secondly, adaptive normalization is applied to the data to mitigate the non-stationarity in the original data, thereby increasing their predictability. Subsequently, a non-stationary attention mechanism is introduced in the model to simultaneously utilize the non-stationarity in the original data when extracting deep information. Additionally, manual features are introduced through mathematical statistics to enhance the predictive performance of the model. During the training process, the TILDE-Q loss function is used to focus on the similarity between the predicted sequence and the true sequence. The model proposed in this paper improves the MSE by 31% compared to the Transformer and 23% compared to the Crossformer in the experimental prediction of the RUL of PEMFCs in actual vehicles.
Urban Road Anomaly Monitoring Using Vision–Language Models for Enhanced Safety Management
Authors: Ding Hanyu , Du Yawei , Xia Zhengyu
Published: February 2025

Abnormal phenomena on urban roads, including uneven surfaces, garbage, traffic congestion, floods, fallen trees, fires, and traffic accidents, present significant risks to public safety and infrastructure, necessitating real-time monitoring and early warning systems. This study develops Urban Road Anomaly Visual Large Language Models (URA-VLMs), a generative AI-based framework designed for the monitoring of diverse urban road anomalies. The InternVL was selected as a foundational model due to its adaptability for this monitoring purpose. The URA-VLMs framework features dedicated modules for anomaly detection, flood depth estimation, and safety level assessment, utilizing multi-step prompting and retrieval-augmented generation (RAG) for precise and adaptive analysis. A comprehensive dataset of 3034 annotated images depicting various urban road scenarios was developed to evaluate the models. Experimental results demonstrate the system’s effectiveness, achieving an overall anomaly detection accuracy of 93.20%, outperforming state-of-the-art models such as InternVL2.5 and ResNet34. By facilitating early detection and real-time decision-making, this generative AI approach offers a scalable and robust solution that contributes to a smarter, safer road environment.
Advancements in Nanostructured Functional Constituent Materials for Gas Sensing Applications: A Comprehensive Review
Authors: Panžić Ivana , Bafti Arijeta , Radovanović-Perić Floren , Gašparić Davor , Shi Zhen , Borenstein Arie , Mandić Vilko
Published: February 2025

The unique properties of nanostructures, such as their high surface-to-volume ratio, tunable physical and chemical characteristics, and enhanced sensitivity, are critical for advancing gas detection technologies. Therefore, this comprehensive review explores the recent advancements in nanostructured materials, emphasizing their pivotal role in enhancing gas sensing performance. A key focus of this review is metal oxide-based gas sensors, and the impact of synthesis methods and (micro)structural properties on sensor performance is thoroughly examined. By segmenting the discussion into 1D nanostructured materials, including different metal oxides, the review provides a broad yet detailed perspective on how different functional materials contribute to gas sensing efficiency. From a performance standpoint, this review highlights critical sensing parameters, including gas detection mechanisms, response times, selectivity, stability, and operating conditions. High-end detection values may reach around a few ppb for most gases. Beyond evaluating current advancements, this review also addresses existing challenges and future research directions, particularly in scalability, long-term sensor stability, low-temperature operation, and integration into real-world applications. By providing a comprehensive and up-to-date analysis, this review serves as a valuable resource for researchers and engineers, offering insights that can drive the next generation of high-performance, reliable, and selective gas sensors.
Spatio-Temporal Analysis of Changes in the Iranian Summer Subtropical High-Pressure System from a Climate Change Perspective
Authors: Fatahian Mokhtar , Hejazizadeh Zahra , Karbalaee Ali Reza , Shahidinia Hamed , Wang Junye
Published: February 2025

Climate change plays a significant role in altering the behavior of large-scale atmospheric systems, particularly the subtropical high-pressure systems relevant to the climate of Iran. This study investigates the impact of climate change on the subtropical high-pressure system over Iran by utilizing ERA5 reanalysis data and CORDEX projections. Focusing on future projections (2022–2063) under RCP4.5 and RCP8.5 scenarios, the analysis reveals substantial shifts in the position and intensity of the subtropical high when comparing the high-pressure center between currently observed data and the projected scenarios. The center of the high-pressure system exhibits a northward migration, particularly pronounced in August; a consistent upward trend in geopotential height, analyzed using the Kendall trend method, is observed, indicating a strengthening of the high-pressure system. This intensification leads to a westward and northward expansion of the summer high-pressure cell. Consequently, this study anticipates the emergence of more pronounced cyclonic circulations at higher latitudes (>38° N) in the future. These findings suggest that climate change will substantially alter the behavior of the subtropical high over Iran, impacting regional weather patterns and potentially leading to climate anomalies.
Optimized Conditions for Electrical Tissue Stimulation with Biphasic, Charge-Balanced Impulses
Authors: Sun Zhengwu , Sen Payel , Hamers Jules , Seidel Thomas , Dendorfer Andreas , Kameritsch Petra
Published: February 2025

The cultivation of excitable cells typically profits from continuous electrical stimulation, but electrochemical consequences are mostly harmful and must be minimized. The properties of the electrode materials and stimulation impulses are key. Here, we developed an easy method to analyze the electrochemical impact of biphasic, current-controlled impulses, applied via graphite electrodes, using phenol red as the redox indicator. We also tested the stimulation conditions for the long-term cultivation of myocardial tissue. The colorimetric assay was able to detect ±0.2% deviations in typical positive and negative pulse charges. Phenol red was best preserved (20% degradation over 24 h) by impulses of equivalent positive and negative charges (full charge balance), generated with either manual calibration, capacitive electrode coupling, or feedback regulation of electrode polarization. Feedback regulation established full charge balance at pre-pulse voltages of about 300 mV, but also provided the option to selectively compensate irreversible electrode reactions. Modifications to shape and timing did not affect the electrochemical effects of symmetric impulses. Charge-balanced stimulation maintained more than 80% of the contractility of porcine left ventricular myocardium after 10 days of culture, whereas disbalances of 2–4% provoked weakening and discoloration of the tissues. Active polarization regulation, in contrast to capacitive electrode coupling, reproduced the biological advantages of full charge balance.
Tau Oligomers Resist Phase Separation
Authors: Lucas Lathan , Tsoi Phoebe S. , Ferreon Josephine C. , Ferreon Allan Chris M.
Published: February 2025

Tau is a microtubule-associated protein that undergoes liquid–liquid phase separation (LLPS) to form condensates under physiological conditions, facilitating microtubule stabilization and intracellular transport. LLPS has also been implicated in pathological Tau aggregation, which contributes to tauopathies such as Alzheimer’s disease. While LLPS is known to promote Tau aggregation, the relationship between Tau’s structural states and its phase separation behavior remains poorly defined. Here, we examine how oligomerization modulates Tau LLPS and uncover key distinctions between monomeric, oligomeric, and amyloidogenic Tau species. Using dynamic light scattering and fluorescence microscopy, we monitored oligomer formation over time and assessed oligomeric Tau’s ability to undergo LLPS. We found that Tau monomers readily phase separate and form condensates. As oligomerization progresses, Tau’s propensity to undergo LLPS diminishes, with oligomers still being able to phase separate, albeit with reduced efficiency. Interestingly, oligomeric Tau is recruited into condensates formed with 0-day-aged Tau, with this recruitment depending on the oligomer state of maturation. Early-stage, Thioflavin T (ThT)-negative oligomers co-localize with 0-day-aged Tau condensates, whereas ThT-positive oligomers resist condensate recruitment entirely. This study highlights a dynamic interplay between Tau LLPS and aggregation, providing insight into how Tau’s structural and oligomeric states influence its pathological and functional roles. These findings underscore the need to further explore LLPS as a likely modulator of Tau pathogenesis and distinct pathogenic oligomers as viable therapeutic targets in tauopathies.
Unraveling the Extra Virgin Olive Oil Effect on Inflammation and on Gut and Saliva Microbiota
Authors: Correia Marta , Gomes Ana T. P. C. , Moreira Inês , El Maghariki Jane , Mendes Karina , Correia Maria José , Barros Rui , Barbosa Joana Cristina , Rosa Nuno , Gomes Ana Maria
Published: February 2025

Extra virgin olive oil (EVOO) with a high content of polyphenols has attracted attention due to its proved beneficial effects in decreasing the risk of cardiovascular disease, modulating cholesterol levels (HDL and LDL), modulating inflammatory markers, and decreasing the levels of haemoglobin1Ac, suggesting that EVOO can have an impact in glycemia regulation. This study assessed the impact of the consumption of a northern Portuguese polyphenol-rich EVOO with a high profile of bioactive molecules on several parameters, such as saliva and serum inflammatory biomarkers, and explored EVOO impact on gut and oral microbiota regarding Bacillota and Bacteroidota content. Thus, the impact on glycated haemoglobin (HbA1c), low-density lipoprotein cholesterol (LDL-C), C-reactive protein (CRP), inflammatory biomarkers, and faecal and salivary microbiomes were evaluated before and after the exposure to EVOO. The results showed that EVOO promotes a decrease in the levels of HbA1C and in the pro-inflammatory interleukin IL-1β, associated with inflammatory processes. Moreover, EVOO intake modulated gut and oral microbiota, increasing Bacteroidota in both ecological niches and Bacillota in the oral microbiota, both phyla being associated with health, demonstrating a prebiotic effect.
The Dentin Microbiome: A Metatranscriptomic Evaluation of Caries-Associated Bacteria
Authors: Oliveira Simone G. de , Jardim Rodrigo , Kotowski Nelson , Dávila Alberto M. R. , Sampaio-Filho Hélio R. , Ruiz Karina G. S. , Aguiar Flávio H. B.
Published: February 2025

Background/Objectives: Dental caries remains a prevalent chronic disease globally, driven by complex interactions between the host, diet, and microbial communities. This study employs a metatranscriptomic RNA-Seq analysis to explore the functional dynamics of the dentin microbiome in both healthy and carious teeth. By examining the transcriptional activity of bacterial communities, we aimed to identify key microbial species and molecular functions associated with caries progression. Methods: Samples from six patients (three healthy and three decayed teeth) were analyzed using the Illumina NovaSeq 2000 platform, with data processed through the SAMSA2 pipeline for taxonomic and functional annotation. Results: The differential expression analysis revealed significant upregulation of Streptococcus and Lactobacillus species, including S. mutans, S. sobrinus, and L. salivarius, in carious samples, highlighting their roles in acid production and carbohydrate metabolism. Additionally, Mycobacterium species, known for their biofilm-forming capabilities and acid tolerance, were upregulated in decayed teeth. The Gene Ontology (GO) enrichment analysis identified unique molecular functions and biological processes in carious teeth, such as carbohydrate metabolism, oxidative stress response, and bacterial cell wall biogenesis, which are critical for microbial survival in acidic environments. In contrast, healthy teeth exhibited functions related to homeostasis and nutrient acquisition, reflecting a balanced microbial community. Conclusions: The study underscores the polymicrobial nature of dental caries, with multiple bacterial species contributing to disease progression through diverse metabolic and stress-response mechanisms. These findings provide deeper insights into the ecological shifts within the oral microbiome during caries development, emphasizing the importance of a functional metatranscriptomic analysis in understanding the pathogenesis of dental caries.
Obstacle Avoidance Strategy and Path Planning of Medical Automated Guided Vehicles Based on the Bionic Characteristics of Antelope Migration
Authors: Hu Jing , Niu Junchao , Zhang Bangcheng , Gao Xiang , Zhang Xinming , Huang Sa
Published: February 2025

Automated Guided Vehicles (AGVs) face dynamic and static obstacles in the process of transporting patients in medical environments, and they need to avoid these obstacles in real time. This paper proposes a bionic obstacle avoidance strategy based on the adaptive behavior of antelopes, aiming to address this problem. Firstly, the traditional artificial potential field and dynamic window algorithm are improved by using the bionic characteristics of antelope migration. Secondly, the success rate and prediction range of AGV navigation are improved by adding new potential field force points and increasing the window size. Simulation experiments were carried out on a numerical simulation platform, and the verification results showed that the bionic obstacle avoidance strategy proposed in this paper can avoid dynamic and static obstacles at the same time. In the example, the success rate of path planning is increased by 34%, the running time is reduced by 33%, and the average path length is reduced by 1%. The proposed method can help realize the integration of “dynamic and static” avoidance in the process of transporting patients and effectively save time by using AGVs to transport patients. It provides a theoretical basis for realizing obstacle avoidance and rapidly loading AGVs in medical environments.
Puffed Up Creativity? The Relationship Between Grandiose Narcissism and Creativity: A Study of Chinese High-Tech Companies
Authors: Zheng Wen , Yu Huihui , Gu Yu , Huang Yang
Published: February 2025

Prior research has yielded inconsistent findings regarding the association between narcissism and creativity, possibly due to the neglect of different narcissism subtypes. The present study aimed to elucidate the relationship between narcissism and creativity by introducing two distinct subtypes of narcissism, namely grandiose and vulnerable narcissism. A total of 571 employees (267 males, 304 females) from high-tech enterprises across 26 provinces in China completed measures of narcissism, creative performance, creative states, and self-esteem, following explicit instructions. The results indicated that participants with grandiose narcissism reported significantly higher levels of creativity states and fluency in creativity performance than those with vulnerable narcissism. Self-esteem mediated the relationship between both subtypes of narcissism and creativity. The implications of the revealed differential effects of grandiosity and vulnerability on creativity in the workplace were also discussed.
Psychosocial Predictors of Job Satisfaction in Nursing: Insights from a Spanish Hospital Setting
Authors: Trillo Alejandra , Ortega-Maldonado Alberto , Lopez-Pena Beatriz , Bretones Francisco D.
Published: February 2025

Nurses play a key role in healthcare systems, yet their job satisfaction is often challenged by factors such as emotional exhaustion and organisational dynamics. This study examines the relationship between psychological empowerment, affective commitment, and emotional exhaustion as predictors of job satisfaction in a sample of 150 Spanish nurses. Data were collected using validated questionnaires measuring these constructs, and mediation analyses were conducted using the PROCESS macro. Results indicated that psychological empowerment positively influenced job satisfaction both directly and indirectly through affective commitment. However, emotional exhaustion did not significantly mediate this relationship, suggesting that contextual factors such as workload may override its effects. This research contributes to the understanding of job satisfaction among healthcare professionals and highlights the importance of empowerment and affective engagement. Practical implications for hospital management include fostering psychological empowerment through organisational strategies that promote autonomy, competence, and meaningful involvement, which could improve nurses’ well-being and organisational performance.
Factorial Invariance of the Satisfaction with Life Scale (SWLS) in Mexican and Colombian University Students
Authors: Norambuena-Paredes Ignacio , Polanco-Levicán Karina , Tereucán-Angulo Julio , Sepúlveda-Maldonado José , Gálvez-Nieto José Luis , Tavera-Cuellar Cristina , Pérez-Ramírez Selene , Álvarez-Violante Crisóforo , López-Tarango Roque
Published: February 2025

This study aimed to evaluate the psychometric equivalence of the Satisfaction with Life Scale (SWLS) in university students from Mexico and Colombia. A non-probabilistic convenience sampling was used in five public and private universities in both countries, with a sample of 861 university students (40% men and 60% women), whose average age was 20.55 years (SD = 2.72). A six-point version of the SWLS was employed. Through confirmatory factor analysis, a unidimensional structure of the SWLS was identified in both samples, with adequate fit indices in both countries. Additionally, the factorial invariance analysis confirmed the metric and configural equivalence of the model, indicating that the factorial structure and factor loadings are comparable between both populations. The results support the use of the SWLS to assess life satisfaction in the context of university education in Mexico and Colombia.
Exploring the Dynamic Evolution and Drivers of the Coupled Coordination Relationship of Carbon Emission Efficiency and Economic Benefits in Construction Land Development
Authors: Zhang Peixing , Jin Tianlu , Wang Yuqi , Guo Honglei
Published: February 2025

In the pursuit of sustainable urban development, construction land development (CLD) not only carries the important mission of promoting economic growth but also needs to actively respond to the environmental requirements of reducing carbon emissions. However, there is a tension and balance between these two objectives. This study explores the evolution characteristics and influencing mechanisms of the synergistic relationship between carbon emission efficiency and economic benefits of CLD based on the undesirable slacks-based measurement, coupling coordination degree (CCD) model, Tapio decoupling model, spatial convergence model, and interpretable machine learning techniques. The main conclusions are as follows: (1) The CCR between CEE and economic benefits of CLD in China shows the characteristic of “improvement-stability-local decline”, and it is higher in the eastern region than in the central and western regions. (2) The decoupling of carbon emission efficiency (CEE) and economic benefits of CLD between 2003 and 2023 shows diverse trends in different provinces and time scales in China. (3) China’s eastern region are consistent with σ-convergence and β-convergence, and the gap in the level of inter-regional coupling co-ordination has narrowed. On the contrary, the central and western regions do not pass the σ and β-convergence tests, and the regional equilibrium needs to be improved. (4) In descending order of influence on CCR, they are ownership structure, urban construction land per capita, energy consumption per unit of gross domestic product, energy structure, industrial structure, and foreign trade investment intensity.
Moisture Ingress in Building Envelope Materials: (II) Transport Mechanisms and Practical Mitigation Approaches
Authors: Lopez-Carreon Itzel , Jahan Esrat , Yari Mohammad Hossein , Esmizadeh Elnaz , Riahinezhad Marzieh , Lacasse Michael , Xiao Zhe , Dragomirescu Elena
Published: February 2025

The primary goal of this review is to explore both the fundamental dynamics of moisture ingress and practical strategies for its mitigation. Moisture ingress remains a critical issue due to its impact on the structural integrity of buildings and the health and safety of occupants. This work adopts a systematic approach, focusing on key mechanisms of water transport—capillary action, vapour diffusion, and condensation—and how different parameters influence the process of moisture transport. Moisture ingress, whether through direct leakage, capillary action, air infiltration, or vapour diffusion, poses significant risks to the premature degradation of building envelope materials. In this study, emphasis has been placed on describing the methods for controlling liquid water movement, preventing condensation, and using moisture-resistant materials. Additionally in this study, the advanced design and hygrothermal performance simulation tools are examined; the use of such tools is considered essential for predicting and managing moisture-related issues in building envelopes. Finally, the significance of complying with moisture control standards and guidelines is highlighted, ensuring a comprehensive framework for effective moisture management in building design and maintenance. Beyond this review, key knowledge gaps in moisture control strategies have been identified, particularly in respect to material performance, the accuracy of predictive modeling, and the standardization of mitigation techniques. Addressing these gaps is essential for advancing building design, maintenance practices, and regulatory frameworks that together combine to enhance moisture resilience.
Should Clinically Assisted Hydration and Nutrition Ever Be Withdrawn for a Neonate with a Chronic Non-Progressive Neurological Condition? A Case Study
Authors: Kang Zhi-Lin , Tay Keson , Chong Poh-Heng
Published: February 2025

Background: For infants, withholding or withdrawal of feeding is ethically permissible when the child is imminently dying or chronically and irreversibly comatose. It can also be appropriate in cases of medical futility with a low chance of survival. However, there is much contention in situations where the medical prognosis is uncertain. Case presentation: Annie is a 6-week-old neonate with antenatally acquired cystic encephalomalacia, a chronic non-progressive neurological condition. Her future neurological outcome is uncertain. She is putting on weight in the NICU with stable cardiorespiratory status on room air and tolerates full nasogastric tube feeding but requires frequent oropharyngeal suctioning. Her parents ask to stop tube feeding and allow Annie to die. They deem she has a poor quality of life and is experiencing tremendous suffering. Discussion: Parents’ perceptions of “best interest” and “physical suffering” are explored, alongside those of the healthcare team. Concomitant issues like feeding withdrawal and moral distress are examined in context—that of a newborn where developmental outcomes and disease trajectory are unclear. Conceptual frameworks, empirical evidence and consensus-based ethics guidelines informed a rich and multi-dimensional exposition of a difficult and value-laden decision. Conclusions: While instinctively legitimate, enteral feeding in an infant, in this case with severe neurological impairment, is ultimately still a medical intervention. In contrast to prevailing conventions within adult medicine, the careful and nuanced consideration of benefits and burdens from different stakeholders’ perspectives is critical before any deliberate withdrawal to allow natural death.
The Dual Role of Digital Self-Efficacy in Reading Engagement from a Nonlinear Dynamics Perspective
Authors: Alghamdi Mohammed , Sideridis Georgios
Published: February 2025

Background: The purpose of this study is to elucidate the potentially complex relationship between digital self-efficacy and students’ engagement with reading activities, given that the students are known to enjoy reading. Of particular interest were the roles of digital self-efficacy as potential regulators and/or moderators of students’ engagement with reading activities at school. Methods: The participants were fourth-grade students from the Kingdom of Saudi Arabia. The data came from the Progress in International Reading Literacy Study (PIRLS) in 2021. The main hypothesis put forth was that digital self-efficacy would play a significant role in regulating students’ engagement with reading activities. The prediction of students’ reading engagement at school may take two different directions: linear and nonlinear. Based on the linear model’s prediction, it was expected that increases in digital self-efficacy would be associated with increases in engagement with reading activities. Results: The opposite prediction was supported; that is, heightened self-efficacy led to an unexpected drop and unpredictability in students’ engagement with reading. Conclusions: A potential explanation is that enhanced self-efficacy in digital skills is associated with enhanced interest and activity in digitally related tasks, such as video games, and engagement with internet-type activities and social media platforms, which consume a significant amount of time. Another possible explanation is related to levels of overconfidence in students, and it is suggested that those enhanced ratings are not necessarily associated with enhanced outcomes. It is concluded that enhanced digital self-efficacy may not have the expected positive effects as individuals become complacent and cease their efforts after seeing prior successes in reading achievement.
Investigation of Ultra-Thin Glass Scribing Mechanism
Authors: Li Dawei , Li Jiahao , Kong Huaye , Guo Jinzhu , Huang Liyong , Liu Yao
Published: February 2025

To reveal the scribing mechanism of ultra-thin glass, single-factor scribing tests were carried out. The effects of the scribing wheel angle θ, scribing force F, and scribing speed v on the lateral cracks width w, scribing depth d, median cracks size l, and cross-section deflection angle α were analyzed to present the scribing quality. The results show that w increases with an increase in θ and F. Further, l and d increase with an increase in F. However, d shows an increasing trend with the increase in θ, and l shows a decreasing trend. In the range of 120–140°, α shows a trend of increasing first and then decreasing with an increase in F. The 120° scribing wheel angle, 20 N scribing force, and 100–400 mm/s scribing speed show the best scribing quality, which limits micro-cracks at the initiation stage without any damage or chipping. Under this condition, the breaking surface edges were free of debris and cracks. A smooth and trim Wallner ripple was obtained from the median cracks with a minimum deflection angle.
Design and Preparation of a Novel Double-Modified Cement-Based Protective Coating Material and Its Improved Protection Performance Against Chloride Corrosion
Authors: Hua Quan , Wu Changyun , Zhu Yangshun , Wang Juhang , Zhou Zhou , Wang Xing , Wang Guowei , Zhang Shuguang , Song Dan
Published: February 2025

The service of reinforced concrete structures (RCSs) in harsh coastal environments is often threatened by chloride corrosion. The penetration of chloride ions through concrete pores into the steel/concrete interface will cause the depassivation and corrosion of steel rebars, which will lead to the deterioration and failure of RCSs durability. It is important to repair and protect the corrosion damage of existing concrete structures and ensure their high durability, and the high performance of repairing and protecting materials is crucial. In this paper, a novel cement-based protective coating material with low porosity, high impermeability and chloride-corrosion resistance was designed and prepared by introducing polypropylene fiber and high-performance cement into commercial cement-based protective materials through the double modification strategy of fiber-toughening and substrate-enhancing, in order to provide a reliable corrosion protection solution for the high durability and long life of RCSs under chloride erosion environment. Based on this, the microstructure and pore structure of the double-modified coating material was systematically analyzed by SEM, XRD, X-CT and other characterization methods. The impermeability and chloride corrosion resistance of this material were scientifically evaluated, and the protection mechanism was systematically discussed. The results show that the impermeability of the double-modified coating material is about 2.8 times higher than that of the untreated mortar. At the same time, the corrosion current density was significantly reduced to 8.60 × 10−7 A·cm−2, which was about 86% lower than that of the untreated sample (6.11 × 10−6 A·cm−2). The new cement-based coating material optimized by double-modification effectively inhibits the formation and propagation of microcracks in the protective coating through the bridging effect of fibers. At the same time, the regulation of cement hydration products and the densification of pore structure are realized by adjusting the composition of cement matrix. Based on the above two aspects of microstructure improvement, the chloride-corrosion protection performance of the novel cement-based protective coating material has been greatly improved.
Two Complete Mitochondrial Genomes of Potamanthidae (Ephemeroptera): Genome Features and Phylogenetic Implications
Authors: Li Ran , Xue Chao , Ma Zhenxing , Zhou Changfa
Published: February 2025

The family Potamanthidae is widely distributed across the Holarctic and Oriental regions, with nymphs often utilized as bioindicators for water pollution and human-induced environmental disturbances. However, limited mitochondrial genomes (mitogenomes) have been reported for this family. This study presents the first complete mitochondrial genome sequences of two Potamanthidae species, Potamanthus longitibius and Rhoenanthus youi. The mitogenome sizes were 15,430 bp and 15,232 bp, with A + T contents of 68.79% and 66.75%, respectively. The most abundant amino acids were phenylalanine (Phe), isoleucine (Ile), glycine (Gly), and alanine (Ala), with leucine (Leu2) showing the highest relative synonymous codon usage (RSCU) value. The analysis of tRNA secondary structures revealed high conservation among the tRNAs encoded on the H-strand. Phylogenetic reconstruction, incorporating 40 species from 13 families of Ephemeroptera, confirmed the monophyly of all the families and supported a sister group relationship between Potamanthidae and Ephemeridae. Additionally, the sequence previously identified as Rhoenanthus sp. JZ-2021 was reassigned to the genus Potamanthus. This study provides valuable insights into the evolutionary relationships within Potamanthidae and lays a foundation for future phylogenetic and taxonomic research.
Foraging Resource Partitioning in the California Sea Lion (Zalophus californianus) from the Southwestern Gulf of California
Authors: Elorriaga-Verplancken Fernando R. , Enríquez-García Arturo B. , Cruz-Vallejo Romyna A.
Published: February 2025

California sea lion (CSL, Zalophus californianus) abundance has declined in different localities across this species’ Mexican distribution. However, Los Islotes rookery in the southwestern Gulf of California (GoC) deviates from this pattern. It is vital to gather ecological knowledge of this CSL settlement and its surroundings to better understand its population in the GoC. This study aimed to determine the foraging habits of different CSL sex and age classes. Sixty-five CSL samples were collected in Los Islotes and its surroundings for stable isotope analysis (δ13C and δ15N). The data were analyzed using a hierarchical Bayesian model, and isotopic areas were estimated using the SIBER package in R. Our findings evidenced resource partitioning. Adult females had lower δ15N values than most classes, reflecting the regional 15N-enrichment of the GoC. Conversely, subadult males showed low δ15N values, carrying foraging information from the 15N-depleted Pacific Ocean into the GoC. Adult males presented the highest δ15N values (after pups), suggesting a higher trophic position than adult females and values corresponding to the GoC. Moreover, juveniles had the most negative δ13C values and the largest isotopic areas, indicating offshore foraging habits and a mixed consumption of maternal milk and their first prey. Pups showed the highest mean δ15N value due to maternal milk consumption, reflecting the mother’s δ15N value and their enrichment. Our findings suggest that segregation is explained by unique life history traits and a possible strategy to avoid potential competition
Essential Oil and Phylogenetic Positions of Five Medicinal Litsea Species (Lauraceae)
Authors: Chaisoung Natcha , Balslev Henrik , Suksathan Ratchuporn , Panyadee Prateep , Long Chunlin , Ngernsaengsaruay Chatchai , Chaowasku Tanawat , Inta Angkhana
Published: February 2025

Litsea species have been used for herbal medicine by many ethnic groups. However, defining the morphological characteristics of the species remains difficult, leading to confusion and misuse of Litsea names. We examined Litsea classification, focusing on folk taxonomy. A field survey revealed that Litsea cubeba, L. elliptica, L. mollis, L. glutinosa, and L. martabanica have the highest use values. Using headspace solid-phase microextraction coupled with gas chromatography–mass spectrometry (HS-SPME-GC-MS) analysis and multivariate statistical methods, we examined metabolites from these species to assess consistency across plant parts. Principal coordinate analysis (PCoA) and cluster analysis revealed distinct metabolite patterns, grouping species into four significant clusters: Group I (L. elliptica and L. martabanica), Group II (L. martabanica roots), Group III (L. cubeba and L. mollis bark and roots), and Group IV (L. glutinosa and L. cubeba and L. mollis leaves). Chemical compounds are clustered by species rather than by plant parts. Our study reveals a significant correlation (p < 0.05) between phylogenetic distances and chemical differences among Litsea species, elucidating the evolutionary links through metabolite variations. This predictive approach could help with more efficient selection for traditional medicine discovery and should be the first to be pharmacologically tested for drug development.
Enhancing Typhoid Fever Diagnosis Based on Clinical Data Using a Lightweight Machine Learning Metamodel
Authors: Nishat Fariha Ahmed , Mridha M. F. , Mahmud Istiak , Alfarhood Meshal , Safran Mejdl , Che Dunren
Published: February 2025

Background: Typhoid fever remains a significant public health challenge, especially in developing countries where diagnostic resources are limited. Accurate and timely diagnosis is crucial for effective treatment and disease containment. Traditional diagnostic methods, while effective, can be time-consuming and resource-intensive. This study aims to develop a lightweight machine learning-based diagnostic tool for the early and efficient detection of typhoid fever using clinical data. Methods: A custom dataset comprising 14 clinical and demographic parameters—including age, gender, headache, muscle pain, nausea, diarrhea, cough, fever range (°F), hemoglobin (g/dL), platelet count, urine culture bacteria, calcium (mg/dL), and potassium (mg/dL)—was analyzed. A machine learning metamodel, integrating Support Vector Machine (SVM), Gaussian Naive Bayes (GNB), and Decision Tree classifiers with a Light Gradient Boosting Machine (LGBM), was trained and evaluated using k-fold cross-validation. Performance was assessed using precision, recall, F1-score, and area under the receiver operating characteristic curve (AUC). Results: The proposed metamodel demonstrated superior diagnostic performance, achieving a precision of 99%, recall of 100%, and an AUC of 1.00. It outperformed traditional diagnostic methods and other standalone machine learning algorithms, offering high accuracy and generalizability. Conclusions: The lightweight machine learning metamodel provides a cost-effective, non-invasive, and rapid diagnostic alternative for typhoid fever, particularly suited for resource-limited settings. Its reliance on accessible clinical parameters ensures practical applicability and scalability, potentially improving patient outcomes and aiding in disease control. Future work will focus on broader validation and integration into clinical workflows to further enhance its utility.
Volume Estimation Method for Irregular Object Using RGB-D Deep Learning
Authors: Kim Ji-hwan , Lee Dong-seok , Kwon Soon-kak
Published: February 2025

The demand for non-contact object volume estimation has been increasing across various industries. Although image-based volume estimation methods have been studied, they are generally limited to measuring simple shapes and are not suitable for irregularly shaped objects. We propose a volume estimation method for a single object using color and depth images through a deep learning network. For the color image, the object region is detected using a pre-trained segmentation model. For the depth image, the heights corresponding to pixels in the object region are calculated as differences between the pixel values and a background depth image that has captured a floor without any objects. Then, the heights are divided into multiple 2 × 2 pixel units. The element volumes corresponding to the 2 × 2 pixel units are estimated by a deep learning network which takes heights in a 2 × 2 pixel unit as inputs. This network estimates the corresponding volume to this unit through multiple fully connected layers. All estimated element volumes are summed to obtain the object volume. The simulation results show that the average volume estimation error is about 2.37%.
Strategic Network Attack Prevention System Leveraging Sophisticated Query-Based Network Attention Algorithm (QNAA) and Self-Perpetuating Generative Adversarial Network (SPF-GAN) Techniques for Optimal Detection
Authors: Albalawi Tahani , Ganeshkumar Perumal , Albalwy Faisal
Published: February 2025

Network attack detection is a critical issue in complex networks at present, one which becomes even more challenging as the network complexity grows and new threats emerge. Existing security models may encounter problems such as low accuracy, a high number of false positives, and the inability to learn new attacks, especially jamming attacks, where the attacker floods a communication channel with noise. Hence, an adaptive and resilient approach is required. This study presents two novel approaches—the Query-Based Network Attention Algorithm (QNAA) and the Self-Perpetuating Generative Adversarial Network (SPF-GAN) —to enhance performance and flexibility. The QNAA integrates attention mechanisms that allow the model to focus on features and patterns connected with attacks, while the SPF-GAN applies generative adversarial networks to mimic attack scenarios, improving the model’s predictive capability and robustness. The assessment outcomes indicate that the formulated model yields a higher accuracy, precision, recall, and F1-scores than conventional methods in identifying jammer attacks on different datasets.
SESAME: Automated Security Assessment of Robots and Modern Multi-Robot Systems
Authors: Papoutsakis Manos , Hatzivasilis George , Michalodimitrakis Emmanouil , Ioannidis Sotiris , Michael Maria , Savva Antonis , Nikolaou Panagiota , Stokkou Eftychia , Bozdemir Gizem
Published: February 2025

As robotic systems become more integrated into our daily lives, there is growing concern about cybersecurity. Robots used in areas such as autonomous driving, surveillance, surgery, home assistance, and industrial automation can be vulnerable to cyber-attacks, which could have serious real-world consequences. Modern robotic systems face a unique set of threats due to their evolving characteristics. This paper outlines the SESAME project’s methodology for the automated security analysis of multi-robot systems (MRS) and the production of Executable Digital Dependability Identities (EDDIs). Addressing security challenges in MRS involves overcoming complex factors such as increased connectivity, human–robot interactions, and a lack of risk awareness. The proposed methodology encompasses a detailed process, starting from system description and vulnerability identification and moving to the generation of attack trees and security EDDIs. The SESAME security methodology leverages structured repositories like Common Vulnerabilities and Exposures (CVE), Common Weakness Enumeration (CWE), and Common Attack Pattern Enumeration and Classification (CAPEC) to identify potential vulnerabilities and associated attacks. The introduction of Template Attack Trees facilitates modeling potential attacks, helping security experts develop effective mitigation strategies. This approach not only identifies, but also connects, specific vulnerabilities to possible exploits, thereby generating comprehensive security assessments. By merging safety and security assessments, this methodology ensures the overall dependability of MRS, providing a robust framework to mitigate cyber–physical threats.