bluuebunny/crossref_metadata_2025 huggingface dataset:
An Enhanced Deep Q Network Algorithm for Localized Obstacle Avoidance in Indoor Robot Path Planning
Authors: Chen Cheng , Yu Jiantao , Qian Songrong
Published: December 2024

Path planning is a key task in mobile robots, and the application of Deep Q Network (DQN) algorithm for mobile robot path planning has become a hotspot and challenge in current research. In order to solve the obstacle avoidance limitations faced by the DQN algorithm in indoor robot path planning, this paper proposes a solution based on an improved DQN algorithm. In view of the low learning efficiency of the DQN algorithm, the Duel DQN structure is introduced to enhance the performance and combined with a Prioritized Experience Replay (PER) mechanism to ensure the stability of the robot during the learning process. In addition, the idea of Munchausen Deep Q Network (M-DQN) is incorporated to guide the robot to learn the optimal policy more effectively. Based on the above improvements, the PER-D2MQN algorithm is proposed in this paper. In order to validate the effectiveness of the proposed algorithm, we conducted multidimensional simulation comparison experiments of the PER-D2MQN algorithm with DQN, Duel DQN, and the existing methodology PMR-DQN in the Gazebo simulation environment and examined the cumulative and average rewards for reaching the goal point, the number of convergent execution steps, and the time consumed by the robot in reaching the goal point. The simulation results show that the PER-D2MQN algorithm obtains the highest reward in both static and complex environments, exhibits the best convergence, and finds the goal point with the lowest average number of steps and the shortest elapsed time.
Multimodal Explainability Using Class Activation Maps and Canonical Correlation for MI-EEG Deep Learning Classification
Authors: Loaiza-Arias Marcos , Álvarez-Meza Andrés Marino , Cárdenas-Peña David , Orozco-Gutierrez Álvaro Ángel , Castellanos-Dominguez German
Published: December 2024

Brain–computer interfaces (BCIs) are essential in advancing medical diagnosis and treatment by providing non-invasive tools to assess neurological states. Among these, motor imagery (MI), in which patients mentally simulate motor tasks without physical movement, has proven to be an effective paradigm for diagnosing and monitoring neurological conditions. Electroencephalography (EEG) is widely used for MI data collection due to its high temporal resolution, cost-effectiveness, and portability. However, EEG signals can be noisy from a number of sources, including physiological artifacts and electromagnetic interference. They can also vary from person to person, which makes it harder to extract features and understand the signals. Additionally, this variability, influenced by genetic and cognitive factors, presents challenges for developing subject-independent solutions. To address these limitations, this paper presents a Multimodal and Explainable Deep Learning (MEDL) approach for MI-EEG classification and physiological interpretability. Our approach involves the following: (i) evaluating different deep learning (DL) models for subject-dependent MI-EEG discrimination; (ii) employing class activation mapping (CAM) to visualize relevant MI-EEG features; and (iii) utilizing a questionnaire–MI performance canonical correlation analysis (QMIP-CCA) to provide multidomain interpretability. On the GIGAScience MI dataset, experiments show that shallow neural networks are good at classifying MI-EEG data, while the CAM-based method finds spatio-frequency patterns. Moreover, the QMIP-CCA framework successfully correlates physiological data with MI-EEG performance, offering an enhanced, interpretable solution for BCIs.
Optimization of High-Performance Computing Job Scheduling Based on Offline Reinforcement Learning
Authors: Li Shihao , Dai Wei , Chen Yongyan , Liang Bo
Published: December 2024

In large-scale, distributed high-performance computing systems, the increasing complexity of job scheduling has expanded along with the growth of computational resources and job diversity. While heuristic scheduling strategies with various optimization objectives have shown promising results, their effectiveness is often limited in real-world applications due to the dynamic nature of workloads and system configurations. Deep reinforcement learning (DRL) methods offer the potential to address scheduling challenges. However, their trial-and-error learning approach can lead to suboptimal performance or resource wastage in the early stages. To mitigate these risks, this paper introduces an offline reinforcement learning-based job scheduling method. By training on historical data, the method avoids the pitfalls of deploying immature strategies in live environments. We constructed an offline dataset by combining expert scheduling trajectories with early-stage trial data from online reinforcement learning. This enables the development of more robust scheduling policies. Experimental results demonstrate that, compared to heuristic and online DRL algorithms, the proposed approach achieves more efficient scheduling performance across various workloads and optimization goals, showcasing its practicality and broad applicability.
Optimization of an Asymmetric-Rotor Permanent Magnet-Assisted Synchronous Reluctance Motor for Improved Anti-Demagnetization Performance
Authors: Xing Feng , Zhang Jiajia , Zuo Feng , Gao Yuge
Published: December 2024

Permanent magnet-assisted synchronous reluctance motors (PMA-SynRMs) are widely used in various fields due to their significant advantages, including strong torque output, high efficiency, excellent speed regulation, and low cost. The PMA-SynRM with asymmetric-rotor structure has a weaker anti-demagnetization performance than the conventional PMA-SynRM due to its multi-layer and thin permanent magnets construction. According to the finite element (FEM) simulation analysis, the anti-demagnetization performance of the asymmetric-rotor PMA-SynRM can be improved by adding bypass magnetic bridges on the ribs of the flux barriers and by changing the positions of the permanent magnets. The rotor structure of the proposed model is globally optimized by combining the two methods. Anti-demagnetization performance is improved as much as possible under the premise of ensuring the torque performance of the basic model. After multi-objective optimization, there is almost no difference between the optimized model and the basic model in terms of no-load air-gap flux density, no-load Back-electromotive force (EMF), and average torque. The maximum demagnetization rate of the optimized model is reduced by 81.44% compared with the basic model, and the anti-demagnetization performance is significantly improved. At the same time, the torque ripple is also reduced by 44.14%, which is obviously reduced. Compared with the basic model, the optimized model has better stability and reliability.
Evaluation of Aeolian Sand Collapsibility Based on Physical Indicators in the Mu Us Desert, China
Authors: Li Zhixu , Deng Yahong , Mu Huandong , Song Yanxun
Published: December 2024

The collapsibility of aeolian sand has hindered the development of oil and gas resources and the construction of oil and gas stations in the Mu Us Desert. This study considered aeolian sand on the southern edge of the Mu Us Desert as the research object. Based on a water immersion load test, standard penetration test, and indoor geotechnical test, four evaluation indicators were selected, the water content, dry density, void ratio, and saturation. Combined with the support vector machine method, we established a method for evaluating the collapsibility of aeolian sand based on basic physical indicators. The results showed the following: (1) The degree of collapsibility was slight, with a small portion showing no collapsibility. And the load-settlement curve (P-s) was divided into three stages: the linear elastic deformation stage, the elastic–plastic deformation stage, and the collapsible deformation stage. (2) There was a strong relationship between the collapsibility coefficient and the four evaluation indicators for aeolian sand. Based on these indicators, we could accurately predict and evaluate the collapsibility coefficient. (3) Machine learning methods, such as the support vector machine, can effectively solve prediction and evaluation problems between variables when there is no clear mathematical relationship between multiple independent variables and a single dependent variable.
A Review on Head-Related Transfer Function Generation for Spatial Audio
Authors: Bruschi Valeria , Grossi Loris , Dourou Nefeli A. , Quattrini Andrea , Vancheri Alberto , Leidi Tiziano , Cecchi Stefania
Published: December 2024

A head-related transfer function (HRTF) is a mathematical model that describes the acoustic path between a sound source and a listener’s ear. Using binaural synthesis techniques, HRTFs play a crucial role in creating immersive audio experiences through headphones or loudspeakers, using binaural synthesis techniques. HRTF measurements can be conducted either with standardised mannequins or with in-ear microphones on real subjects. However, various challenges arise in, for example, individual differences in head shape, pinnae geometry, and torso dimensions, as well as in the extensive number of measurements required for optimal audio immersion. To address these issues, numerous methods have been developed to generate new HRTFs from existing data or through computer simulations. This review paper provides an overview of the current approaches and technologies for generating, adapting, and optimising HRTFs, with a focus on physical modelling, anthropometric techniques, machine learning methods, interpolation strategies, and their practical applications.
NMR Evaluation of Shale Oil Mobility: Combined Pyrolysis and CO2 Huff-N-Puff
Authors: Sun Jianmeng , Yao Yibo , Sun Fujing , Su Junlei , Lu Jing , Liu Kun , Chi Peng
Published: December 2024

The occurrence and mobility of shale oil are critical issues in exploration and development. Shale reservoirs exhibit a complex fluid state, with oil and water present in various forms. The presence of organic matter and clay minerals within the reservoir framework further complicates the fluid’s occurrence and mobility. Utilizing two-dimensional nuclear magnetic resonance (NMR) experiments, in this study, core samples from the Shengli Oilfield’s shale oil reservoirs were analyzed. We conducted pyrolysis-NMR and CO2 huff-n-puff-NMR joint measurement experiments to assess the shale oil mobility. The results indicated that CO2 huff-n-puff was the most effective in the initial cycle, with diminishing returns in subsequent cycles, and NMR signal changes were predominantly observed in the movable oil fraction. The selected samples showed an average recovery rate of 26.9%, suggesting good mobility of shale oil in the study area. Based on the experimental results, a fluid component identification template for the study region was established, which mainly consists of the following five parts: movable oil, adsorbed oil, asphaltene, clay-bound water, structural water, and kerogen. This research provides valuable insights for the efficient development of shale oil reservoirs.
A Critical Review on the Experimental Setups Used to Assess the Efficiency of Respirators Against Ambient Particulate Matter
Authors: Faridi Sasan , Yousefian Fatemeh , Niazi Sadegh , Ghalhari Mohammad Rezvani , Rafiee Ata , Harrison Roy M. , Brook Robert D. , Contini Daniele , Kumar Prashant , Naddafi Kazem , Hassanvand Mohammad Sadegh , Carlsten Christopher
Published: December 2024

Fine particulate matter (PM2.5) poses significant health risks, prompting public health organizations to recommend the use of respirators and facemasks (RFMs) to mitigate exposure. Consequently, interest in their usage has increased, leading to several studies assessing the efficiency of these personal-level interventions against various fractions of ambient particulate matter (PM). We conducted a comprehensive literature search across PubMed, Web of Science, and Scopus to identify relevant studies and address the following objectives: (1) explore the efficiency of RFMs in reducing ambient PM; (2) discuss discrepancies in efficiencies reported; (3) critique the experimental setups used to evaluate the efficiency of RFMs; and (4) propose recommendations for future research. Five relevant studies we reviewed reported significantly lower RFM effectiveness against ambient PM, with a size-dependent efficiency that decreases for smaller PM fractions. Variations in the reported efficiencies were primarily attributed to design-related factors, resulting in poor facial fit. Therefore, it is crucial to consider standardizing and properly designing these products. These studies overlooked essential factors, such as using dummy heads with flexible textures that mimic human skin. The use of rigid-textured dummy heads, as seen in previous studies, may fail to accurately represent real-world conditions. We recommend researchers take into account diverse facial profiles in their experiments. Moreover, it is essential to consider facial characteristics in the design of RFMs. We believe the evidence supports the increasing need for the adoption of appropriate guidelines and regulations to govern RFM suppliers at both national and international levels.
Temporal Variations, Air Quality, Heavy Metal Concentrations, and Environmental and Health Impacts of Atmospheric PM2.5 and PM10 in Riyadh City, Saudi Arabia
Authors: Alharbi Hattan A. , Rushdi Ahmed I. , Bazeyad Abdulqader , Al-Mutlaq Khalid F.
Published: December 2024

Atmospheric particulate matter (PM) samples were collected in Riyadh, Saudi Arabia, to assess air quality, quantify, heavy metal concentrations, and evaluate related ecological and health risks. This study’s uniqueness stems from its focused and detailed analysis of PM pollution in Riyadh, including an extensive assessment of heavy metal concentrations across different PM sizes by applying diverse pollution and health indices. This brings to light critical health and ecological issues and provides foundation for targeted pollution control efforts in the region. The study focused on two PM size fractions, PM2.5 and PM10 and analyzed the presence of heavy metals, including iron (Fe), nickel (Ni), chromium (Cr), zinc (Zn), cobalt (Co), copper (Cu), silver (Ag), arsenic (As), cadmium (Cd), and lead (Pb), using inductively coupled plasma emission spectrometry. Results showed significantly higher levels of PM10 (223.12 ± 66.12 µg/m3) compared to PM2.5 (35.49 ± 9.63 µg/m3), suggesting that local dust is likely a primary source. Air quality varied from moderate to unhealthy, with PM10 posing substantial risks. Heavy metal concentrations in PM2.5 followed the order Fe (13.14 ± 11.66 ng/m3) > As (2.87 ± 2.08 ng/m3) > Cu (0.71 ± 0.51 ng/m3) > Zn (0.66 ± 0.46 ng/m3) > Cr 0.50 ± 0.23 ng/m3) > Pb (0.14 ± 0.10 ng/m3) > Ni (0.03 ± 0.04 ng/m3) > Cd (0.004 ± 0.002 ng/m3) > Ag (0.003 ± 0.003 ng/m3) > Co (0.002 ± 0.004 ng/m3). In PM10, they followed the order Fe (743.18 ± 593.91 ng/m3) > As (20.12 ± 13.03 ng/m3) > Cu (10.97 ± 4.66 ng/m3) > Zn (9.06 ± 5.50 ng/m3) > Cr (37.5 ± 2.70 ng/m3) > Ni (1.72 ± 01.54 ng/m3) > Pb (1.11 ± 0.64 ng/m3) > Co (0.25 ± 0.28 ng/m3) > Ag (0.10 ± 0.26 ng/m3) > Cd (0.04 ± 0.02 ng/m3). Enrichment factor analysis revealed elevated levels for the metals Cu, Zn, As, Ag, Cd, and Pb. Pollution indices indicated various contamination levels, with Ag and As showing particularly high contamination and ecological risks. The study highlighted significant health concerns, especially from As, which poses a substantial long-term carcinogenic threat. The findings emphasize the urgent need to reduce hazardous metal levels in Riyadh’s air, especially with high child exposure.
The Role of Pleiotropy and Epistasis on Evolvability and Robustness in a Two-Peak Fitness Landscape
Authors: Mehra Priyanka , Hintze Arend
Published: December 2024

Understanding the balance between robustness and evolvability is crucial in evolutionary dynamics. This study aims to determine how varying mutation rates and valley depths affect this interplay during adaptation. Using a two-peak fitness landscape model requiring populations to cross a fitness valley to reach a higher peak, we investigate how mutation rates and valley depths influence both evolvability—the capacity to generate beneficial mutations—and mutational robustness, which stabilizes populations at the highest peak. Our experiments reveal that at low mutation rates, populations struggle to cross fitness valleys, reducing the occurrence of pioneers. As mutation rates increase, valley crossing becomes more frequent, but organisms forming a majority at the highest peak are less common and tend to arise at intermediate mutation rates. Although pioneers reach the highest peak, they are often replaced by more mutationally robust organisms that later form a majority. This suggests that while evolvability aids in valley crossing, long-term stability at the highest peak requires greater mutational robustness. Our findings highlight that adaptations in epistasis and pleiotropy facilitate the trade-off between evolvability and robustness, providing insights into how organisms navigate complex fitness landscapes. These results can also inform the design of genetic algorithms that balance evolvability with robustness to optimize outcomes.
UV Sensitivities of Two Littoral and Two Deep-Freshwater Amphipods (Amphipoda, Crustacea) Reflect Their Preferred Depths in the Ancient Lake Baikal
Authors: Kondrateva Elizaveta , Gurkov Anton , Rzhechitskiy Yaroslav , Saranchina Alexandra , Diagileva Anastasiia , Drozdova Polina , Vereshchagina Kseniya , Shatilina Zhanna , Sokolova Inna , Timofeyev Maxim
Published: December 2024

Solar ultraviolet (UV) is among the most important ecological factors shaping the composition of biota on the planet’s surface, including the upper layers of waterbodies. Inhabitants of dark environments recently evolving from surface organisms provide natural opportunities to study the evolutionary losses of UV adaptation mechanisms and better understand how those mechanisms function at the biochemical level. The ancient Lake Baikal is the only freshwater reservoir where deep-water fauna emerged, and its diverse endemic amphipods (Amphipoda, Crustacea) now inhabit the whole range from highly transparent littoral to dark depths of over 1600 m, which makes them a convenient model to study UV adaptation. With 10-day-long laboratory exposures, we show that adults of deep-water Baikal amphipods Ommatogammarus flavus and O. albinus indeed have high sensitivity to environmentally relevant UV levels in contrast to littoral species Eulimnogammarus cyaneus and E. verrucosus. The UV intolerance was more pronounced in deeper-dwelling O. albinus and was partially explainable by lower levels of carotenoids and carotenoid-binding proteins. Signs of oxidative stress were not found but UV-B specifically seemingly led to the accumulation of toxic compounds. Overall, the obtained results demonstrate that UV is an important factor limiting the distribution of deep-water amphipods into the littoral zone of Lake Baikal.
Mitochondrial Dysfunction in Cardiac Disease: The Fort Fell
Authors: Paraskevaidis Ioannis , Kourek Christos , Farmakis Dimitrios , Tsougos Elias
Published: December 2024

Myocardial cells and the extracellular matrix achieve their functions through the availability of energy. In fact, the mechanical and electrical properties of the heart are heavily dependent on the balance between energy production and consumption. The energy produced is utilized in various forms, including kinetic, dynamic, and thermal energy. Although total energy remains nearly constant, the contribution of each form changes over time. Thermal energy increases, while dynamic and kinetic energy decrease, ultimately becoming insufficient to adequately support cardiac function. As a result, toxic byproducts, unfolded or misfolded proteins, free radicals, and other harmful substances accumulate within the myocardium. This leads to the failure of crucial processes such as myocardial contraction–relaxation coupling, ion exchange, cell growth, and regulation of apoptosis and necrosis. Consequently, both the micro- and macro-architecture of the heart are altered. Energy production and consumption depend on the heart’s metabolic resources and the functional state of the cardiac structure, including cardiomyocytes, non-cardiomyocyte cells, and their metabolic and energetic behavior. Mitochondria, which are intracellular organelles that produce more than 95% of ATP, play a critical role in fulfilling all these requirements. Therefore, it is essential to gain a deeper understanding of their anatomy, function, and homeostatic properties.
Affinity Tag-Free Purification of SARS-CoV-2 N Protein and Its Crystal Structure in Complex with ssDNA
Authors: Maiti Atanu , Matsuo Hiroshi
Published: December 2024

The nucleocapsid (N) protein is one of the four structural proteins in SARS-CoV-2, playing key roles in viral assembly, immune evasion, and stability. One of its primary functions is to protect viral RNA by forming the nucleocapsid. However, the precise mechanisms by which the N protein interacts with viral RNA and assembles into a nucleocapsid remain unclear. Compared to other SARS-CoV-2 components, targeting the N protein has several advantages: it exhibits higher sequence conservation, lower mutation rates, and stronger immunogenicity, making it an attractive target for antiviral drug development and diagnostics. Therefore, a detailed understanding of the N protein’s structure is essential for deciphering its role in viral assembly and developing effective therapeutics. In this study, we report the expression and purification of a soluble recombinant N protein, along with a 1.55 Å resolution crystal structure of its nucleic acid-binding domain (N-NTD) in complex with ssDNA. Our structure revealed new insights into the conformation and interaction of the flexible N-arm, which could aid in understanding nucleocapsid assembly. Additionally, we identified residues that are critical for ssDNA interaction.
Identification of Six Novel Proteins Containing a ZP Module from Nemertean Species
Authors: Ikenaga Jumpei , Yoshida Kaoru , Yoshida Manabu
Published: December 2024

During fertilization, a series of reactions between the eggs and spermatozoa proceed predominantly in a species-specific manner. The molecules mediating these species-specific reactions remain unknown except in a few organisms. In this study, we focused on two species belonging to the phylum Nemertea, Kulikovia alborostrata and K. fulva, and explored molecules involved in species-specific interactions between gametes. Orthologs of molecules known to be involved in species-specific reactions were not expressed in the ovaries of these two species. In contrast, we identified six novel proteins, named NeZPL1–NeZPL6, containing a ZP module. Among these, we found that NeZPL6 is located on the surface of an unfertilized egg and is suggested to be involved in its interaction with spermatozoa. Furthermore, we found an indel of three amino acids in the EGF-like domain of NeZPL6, which possibly confers species specificity to this interaction. Our results suggested the existence of a novel system for species recognition in animal gametes.
Sex Differences in Processing Emotional Speech Prosody: Preliminary Findings from a Multi-Feature Oddball Study
Authors: Kao Chieh , Zhang Yang
Published: December 2024

Background/Objectives: Emotional prosody, the intonation and rhythm of speech that conveys emotions, is vital for speech communication as it provides essential context and nuance to the words being spoken. This study explored how listeners automatically process emotional prosody in speech, focusing on different neural responses for the prosodic categories and potential sex differences. Methods: The pilot data here involved 11 male and 11 female adult participants (age range: 18–28). A multi-feature oddball paradigm was used, in which participants were exposed to sequences of non-repeating English words with emotional (angry, happy, sad) or neutral prosody while watching a silent movie. Results: Both mismatch negativity (MMN) and P3a components were observed, indicating automatic perceptual grouping and neural sensitivity to emotional variations in speech. Women showed stronger MMN to angry than sad prosody, while men showed stronger MMN to angry than happy prosody. Happy prosody elicited the strongest P3a, but only in men. Conclusions: The findings challenge the notion that all facets of emotion processing are biased toward female superiority. However, these results from 22 young adult native English speakers should be interpreted with caution, as data from a more adequate sample size are needed to test the generalizability of the findings. Combined with results from studies on children and elderly adults, these preliminary data underscore the need to explore the complexities of emotional speech processing mechanisms to account for category and sex differences across the lifespan in a longitudinal perspective.
Subjective Perception Types of Older Adults Living Alone as Farmers in Korea: A Q Methodology Study
Authors: Ha Oh Sun , Lee Song Yi
Published: December 2024

This study explores the psychological characteristics of older adults living alone as farmers in South Korea, categorising their subjective experiences. Using Q methodology, interviews were conducted with participants from Seosan, Chungcheong Province, South Korea, on 19 and 22 June 2023. A total of 25 participants conducted Q sorting with 33 finalized Q sample items in three locations: Chungju, Chungcheong Province, on 14 July 2023; Ildong, Gyeonggi Province, on 28 July 2023; and Seosan, Chungcheong Province, on 14 August 2023. The Q sorting results were analysed using the QUANAL program and categorised into four types. Type 1, Balanced Life Pursuit, reflects satisfaction across various aspects of life, such as relationships, health, economy, and psychological wellbeing. Type 2, Independent Life and Improvement-Seeking, pursues independence but experiences loneliness due to the absence of a spouse, while still seeking to improve their life. Type 3, Relationship and Care Needed, highlights a need for relationships and care. Finally, Type 4, Family and Work-Focused, prioritises family and farming work. These findings provide a foundation for developing customised support programs to address the specific needs of different types of older adults living alone as farmers in South Korea.
Exploring Attachment Differences Across the Contexts of Sports and Academics: A Qualitative Exploration of Child and Parent Experiences
Authors: Chang Sheng-I , Lai Ya-Hsin
Published: December 2024

This study aimed to explore the nature of contextual differences in child–parent attachment relationships and examine how these experiences relate to children’s psychological outcomes. A theoretically informed qualitative study was conducted using semi-structured interviews with 15 participants across four groups of Taiwanese youths and parents, representing different contextual attachment combinations. Data were analyzed using a hybrid thematic analysis approach, integrating both inductive and deductive methods. The findings revealed two key characteristics of secure attachment across contexts: (1) parental timely and sensitive responsiveness enhances children’s openness to share personal thoughts, and (2) parental empathic and genuine concern fosters children’s empathy. Conversely, insecure attachment across contexts was marked by (1) inappropriate parental responses reducing children’s willingness to share their inner feelings, and (2) parental lack of empathy frustrating children and discouraging communication. In addition, parental beliefs about children’s achievement behaviors (e.g., expectation primarily centered on academic achievement and viewing athletic achievement as an alternative pathway to higher education) and parenting practices (e.g., performance- vs. mastery-oriented achievement goals, conditional negative regard, and psychological control through invalidating feelings and demeaning the child) significantly influenced children’s psychological outcomes, particularly in terms of basic psychological needs satisfaction and frustration (autonomy and competence) across academic and sports domains. These findings advance our theoretical understanding of contextual attachment dynamics and provide practical insights for fostering optimal parenting strategies, particularly in academic and sport-related contexts.
The Moderating Effect of Cultural Orientation on the Relationship Between Growth Mindset and Learning Self-Efficacy: A Dimension-Specific Pattern
Authors: He Wu-Jing , Zhang Kai
Published: December 2024

Building on the theoretical perspectives of mindset theory and cultural orientation framework, this study explores the moderating role of cultural orientation in the relationship between individuals’ growth mindset and learning self-efficacy, addressing the contextual dependency of mindset theory. A total of 307 Chinese undergraduates (61% female; age range = 18–22 years) from a university in Hong Kong were recruited for this cross-sectional study. Cultural orientation, growth mindset, and learning self-efficacy were assessed via the Chinese version of the Cultural Values Scale (CVScale), Growth Mindset Inventory (GMI), and Learning Self-Efficacy Scale (LSES), respectively. Linear multiple regression analysis was conducted to examine the hypothesized moderation effects. The results revealed an interesting dimension-specific pattern among the five dimensions of cultural orientation. While one dimension (i.e., long-term orientation) had a positive moderating effect on the relationship between growth mindset and learning self-efficacy, two dimensions (i.e., power distance and uncertainty avoidance) had negative moderating effects on that relationship. The two remaining cultural dimensions (i.e., individualism/collectivism and motivation towards achievement and success) did not exhibit any significant moderating effects. These findings underscore the interplay between a growth mindset, cultural orientation, and learning self-efficacy, emphasizing the influence of cultural factors on the outcomes of mindset interventions. This study highlights the need for culturally tailored educational practices and interventions to maximize the effectiveness of growth mindset theories in diverse contexts.
The Impact of Coverage Forms of Exterior Vertical Greening Walls on the Thermal Environmental Benefits of Buildings in Hot and Humid Regions
Authors: Li Li , Cheng Junfeng , Liu Zhichao , Li Qingliang , Yu Lan , Zhou Xiaoqing , Pang Yue
Published: December 2024

Architectural vertical green walls can mitigate the urban heat island effect, provide shade and cooling, reduce energy consumption, improve a microclimate, and increase indoor comfort. However, an excessive pursuit of high coverage may diminish the benefit ratio and adversely affect ventilation and lighting. Field measurements were conducted in the hot and humid Guangzhou area to investigate the thermal benefits of external vertical green walls with varying green coverage and diverse layouts, encompassing effects such as shading, insulation, cooling, and humidification. Analyses were conducted using ENVI-met, orthogonal experiments, and SPSS to quantify the moderating effects of planted green coverage (PGC), leaf area density (LAD), and air interstitial layers on the environmental thermal benefits. The results indicated that the cooling and humidifying effects of 100% PGC and 75% PGC were comparable and superior to those of 50% PGC, yet 75% PGC outperformed 100% PGC in terms of indoor humidification. Among the layout modes, the horizontal layout was the most effective for cooling and humidification, followed by the point layout, with the vertical layout being the least effective. A global sensitivity analysis revealed that PGC had the greatest impact on wall cooling and outdoor humidification, LAD significantly influenced humidification, the width of air interstitial layers had a minor impact, and the two architectural vertical greening design ratios of 75% PGC × 4.60 LAD and 75% PGC × 2.70 LAD were particularly effective for cooling and humidification. Incorporating horizontal or point-like layouts can enhance façade design diversity while preserving the desired environmental thermal benefits, thereby contributing to the overall aesthetics of a building.
Experimental Study of Alkali-Excited Steel Slag–Granulated Blast Furnace Slag–Cement-Based Grouting Material Based on Response Surface Methodology
Authors: Fang Fang , Wang Zhenhua , Zhang Fuqing , Li Dongwei , Jia Zhiwen , Wang Zecheng , Jiang Tiantian , Lan Wei
Published: December 2024

This study aims to refine the ratio of alkali-activated steel slag (SS) to granulated blast furnace slag (GBFS)–cement-based grouting materials, with the dual objectives of cost reduction and performance enhancement. By employing single-factor experiments and response surface methodology (RSM), we have pinpointed the critical factors that influence the slurry’s performance and developed a regression model to assess the impact of these factors and their interplay. Our findings indicate that the compressive strength initially increases with higher SS content but subsequently declines. Additionally, an increase in alkali content and activator modulus is beneficial for strength improvement. However, beyond an alkali content of 8%, the 28-day strength is observed to decrease. Through meticulous model analysis, we have determined the optimal ratio to be 7.07% SS content, 7.82% alkali content, and an activator modulus of 1.8. The material’s performance at this ratio satisfies construction specifications. This research not only offers a cost-effective and high-performance grouting solution for geotechnical applications but also pioneers a novel approach to the resourceful utilization of solid waste materials, such as SS.
Experimental Comparison of the Performance of Shear Frame with TLD and TLCD Under Harmonic Ground Motion
Authors: Kebeli Yunus Emre , Aydın Ersin , Öztürk Baki , Çetin Hüseyin
Published: December 2024

Today, various systems are used to reduce vibrations in civil engineering structures. Among these systems, tuned liquid dampers are the preferred passive systems due to their ability to be designed in different geometries, their low cost, their ease of installation, and their low maintenance costs. This study examines the effectiveness of tuned liquid dampers (TLD) and tuned liquid column dampers (TLCD) under identical geometric conditions and harmonic ground motion to assess which is more efficient in controlling the behavior of a three-storey steel shear frame model equipped with these systems. A small-scale, three-storey shear frame model placed on a uniaxial shaking table was subjected to harmonic motion with a 5 mm amplitude, 1.4 Hz frequency, and 10 cycles. The chosen frequency aligns with the resonance frequency of the undamped building model’s first mode. Both TLD and TLCD tanks, positioned atop the structure, share a geometry of 30 cm in length and 10 cm in width, with variable liquid heights of 5, 10, 15, and 20 cm. Mounting TLD and TLCD models with four different liquid heights on the undamped model resulted in nine distinct setups. In this designed scenario, the TLDs and TLCDs on the undamped shear frame were compared according to liquid heights at rest. To identify the best-performing system based on liquid height, response displacement–frequency graphs were generated for all models within a frequency range of 0.5–2.5 Hz, and damping ratios were calculated using the half-power bandwidth method. Additionally, harmonic ground motion experiments at the resonance frequency compared both acceleration and displacement values over time for damped and undamped models. Peak acceleration and displacement values on each floor were also analyzed. The results highlight which system proves more effective based on damping ratio, acceleration, and displacement values under equivalent conditions.
Influence of Fly Ash Content on Macroscopic Properties and Microstructure of High-Performance Concrete
Authors: Kang Mengxin , Jia Yabo , Guo Peng , Ju Yanzhong , Zhang Hongji
Published: December 2024

To investigate the influence of the fly ash (FA) content on the performance of high-performance concrete (HPC), seven groups of tests were conducted, aiming to evaluate both the macroscopic properties (workability and compressive strength) and microscopic pore structure. Low-field nuclear magnetic resonance (NMR) technology and SEM images were employed to analyze the changes in the internal pore structure of the concrete. The results showed that the workability of HPC initially increased and then decreased with the increase in the FA content. When the FA content was 15%, the slump of HPC reached a maximum of 264 mm, and the 28-day compressive strength exhibited a 23.2% increase compared to the 7-day compressive strength. The pore size distribution of the concrete varied with different fly ash content. At 15% FA content, secondary hydration of the FA was sufficient, refining the pores to between 0 and 0.1 µm. Excessive FA substitution deteriorated the internal structure of the HPC matrix and reduced the workability and mechanical properties of the HPC. When the content of FA was 35%, the slump of HPC decreased to 176 mm, while the macropores within the matrix significantly increased, resulting in porosity of 6.81%.
A Comprehensive Study on the Estimation of Concrete Compressive Strength Using Machine Learning Models
Authors: Altuncı Yusuf Tahir
Published: December 2024

Conducting comprehensive analyses to predict concrete compressive strength is crucial for enhancing safety in field applications and optimizing work processes. There is an extensive body of research in the literature focusing on predicting the mechanical properties of concrete, such as compressive strength. Summarizing the key contributions of these studies will serve as a guide for future research. To this end, this study aims to conduct a scientometric analysis of contributions that utilize machine learning (ML) models for predicting concrete compressive strength, assess these models, and provide insights for developing optimal solutions. Additionally, it seeks to offer researchers comprehensive information on prominent research themes, trends, and gaps in the literature regarding concrete compressive strength prediction. For this purpose, 2319 articles addressing the prediction of concrete compressive strength, published between 2000 and 19 August 2024, were identified through the Scopus Database. Scientometric analyses were conducted using VOSviewer software. The evaluation of relevant studies demonstrates that ML models are frequently used to predict concrete compressive strength. The advantages and limitations of these models are examined, with a particular emphasis on key considerations when working with complex datasets. A comprehensive analysis of ML models and their practical contributions to field applications distinguishes this study from existing research. This study contributes significantly to the literature by examining leading institutions, countries, authors, and sources in the field, synthesizing data, and identifying research areas, gaps, and trends in concrete compressive strength prediction. It establishes a strong foundation for the design of ML-supported, reliable, sustainable, and optimized structural systems in civil engineering, building materials, and the concrete industry.
Identifying Critical Criteria on Assessment of Sustainable Materials for Construction Projects in New Zealand Through the Analytic Hierarchy Process (AHP) Approach
Authors: Qian Jiachen , Siriwardana Chandana , Shahzad Wajiha
Published: December 2024

New Zealand’s goal of achieving net-zero greenhouse gas emissions (GHG) by 2050 highlights the urgent need for integrating sustainable practices into the construction industry. Since the construction industry makes a major contribution to GHG emissions, this study aims to address this need by identifying and prioritizing the critical criteria relevant to the effective selection of sustainable construction materials for New Zealand’s construction industry. The research employs a multi-stage approach, including a comprehensive literature review, expert interviews, and industry surveys. Initially, 80 criteria were identified through the literature review. Subsequently, expert interviews and industry surveys led to the identification of 30 critical criteria, which were categorized into environmental, technical, economic, and social impacts, and were ranked based on their importance. This study utilizes a 5-point importance index and Analytic Hierarchy Process (AHP) to rank these criteria. This study notably integrates technical impacts with the three traditional sustainability pillars—environmental, economic, and social—providing a nuanced evaluation of construction material selection. The results indicate that environmental and technical criteria received the highest priority weights (32% each), followed by economic (19%) and social impacts (17%). The findings offer valuable insights for industry stakeholders, assisting them in applying these critical criteria to improve material selection practices in alignment with New Zealand’s sustainability objectives.
Experimental and Numerical Investigation on Behavior of Rectangular Closed Section Steel Truss Beams with Concrete-Filled Joints
Authors: He Junlong , Kong Fanlei , Huang Pingming , Mei Kuihua
Published: December 2024

This study investigates the flexural performance of steel trusses with concrete infill and gradient stiffeners at the joints. Three specimens were fabricated and subjected to flexural tests. A finite element model was developed and validated based on experimental results. This model was used to study the stiffness to evaluate the effects of concrete infill and gradient stiffeners at joints on the steel truss. The results demonstrated that all three specimens were subjected to joint tensile–compression failure. The ultimate bearing capacity of specimens with concrete infill and stiffening ribs increased by 29.7% and 35.6%, respectively. The displacement deformation of joints decreased by 21.6% and 18.9%, respectively, and the initial stiffness increased by 31.3% and 39.1%, respectively. Therefore, the concrete infill significantly enhanced the ultimate bearing capacity and flexural stiffness of the steel truss while reducing slip deformation at the joints. The concrete infill improved the deformation resistance of the joints and increased the overall stiffness of the structure. Gradient stiffeners had a limited effect on enhancing the ultimate bearing capacity and flexural stiffness but contributed to a smoother stress transition between filled and unfilled sections. This could also reduce stress distortion at the joints.
The Time-Dependent Method for Probabilistic Fault Displacement Hazard Analysis (PFDHA-td)
Authors: Zhou Qingyun , Yuan Xiaoxiang
Published: December 2024

Coseismic surface displacement can cause major damage to buildings located on faults. Therefore, it is important to quantitatively evaluate the future surface displacement of active faults. The commonly used deterministic evaluation methods often tend to overestimate surface displacement values, so researchers are working toward probabilistic fault displacement hazard analysis (PFDHA). However, the PFDHA assumes that earthquakes occur equally in time, which is not consistent with the physical mechanism of earthquake occurrence. Elastic rebound theory and paleoseismic research results show that the accumulation and release of energy in the crustal medium have cyclical characteristics. In this study, using two parameters, the strong earthquake recurrence period (TRP) and strong earthquake elapsed time (tet), of active faults, the displacements of active faults with different TRP and tet under different exceedance probabilities are obtained. The calculation results indicate that the surface displacement hazard of the weakly active and extremely weakly active faults in the Holocene does not need to be considered; for the moderately and strongly active faults in the Holocene, the surface displacement result is lower than that provided by the deterministic method. According to the importance of the project, the calculation results of the PFDHA-td method under different exceedance probabilities are selected.
New Instant Digital Pathology for EUS/EBUS Samples: The Last Advance in Bedside Diagnostics for Lung Carcinoma
Authors: Di Matteo Francesco Maria , Stigliano Serena , Frasca Luca , Biasutto Dario , Maricchiolo Giulia , Morano Vittoria , Taffon Chiara , Crescenzi Anna
Published: December 2024

Background: Ex vivo fluorescence laser scanning microscopes (FCMs) allow digital tissue imaging directly from fresh, unfixed specimens without the need for conventional histological slide preparation. To date, no data have been reported on the use of FCMs in the endoscopy suite for immediate evaluation of endoscopic ultrasound (EUS)/endobronchial ultrasound (EBUS) fine needle aspiration/biopsy (FNA-B) specimens of lung lesions and/or mediastinal lymph nodes. Objectives: The aim of this study was to evaluate the performance of the FCM Vivascope 2500 (Vivascope, Munich, Germany) in providing real-time adequacy assessment and diagnostic information on the digital images of fresh unprocessed EUS/EBUS FNA-B specimens and to compare it with the corresponding final histological sections of formalin-fixed and paraffin-embedded cell blocks. Methods and Results: Thirty-two patients (50% male; 71 ± 8 years old) were enrolled between May 2023 and June 2024. In 28/32 (87.5%) patients, samples were defined as adequate at Vivascope evaluation, and in 20/28 (71.4%) patients, samples were classified as malignant. At final cytohistological evaluation, 87.5% of specimens were defined as adequate and 20/28 (71.4%) were diagnosed as malignant. There was perfect agreement between the Vivascope assessment of adequacy and the final cytohistological assessment on the same specimen (k Cohen 1). From a diagnostic point of view, perfect agreement was found between the two techniques in the identification of malignant neoplasms (k Cohen 1). Conclusions: The use of FCM could provide rapid information on both the adequacy and malignancy of the sample obtained during EBUS tissue acquisition (EBUS-TA), with minimal or no preparation and without destroying or losing the tissue. This technique allows for obtaining representative material in EBUS/EUS for lung cancer staging and is expected to change the turnaround time from biopsy sampling to diagnostic characterization of the tumor, ultimately improving patient management both at diagnosis and at restaging in follow up.