bluuebunny/crossref_metadata_2025 huggingface dataset:
Logistics Transportation Vehicle Supply Forecasting Based on Improved Informer Modeling
Authors: Guo Dudu , Jiang Peifan , Qin Yin , Zhang Xue , Zhang Jinquan
Published: September 2024

This study focuses on the problem of the supply prediction of logistics transportation vehicles in road transportation. Aiming at the problem that the supply data of logistics transportation has the characteristics of long sequential data, numerous influencing factors, and a significant spatiotemporal evolution law, which leads to the lack of accuracy of supply predictions, this paper proposes a supply prediction method for logistics transportation based on an improved Informer model. Firstly, multidimensional feature engineering is applied to historical supply data to enhance the interpretability of labeled data. Secondly, a spatiotemporal convolutional network is designed to extract the spatiotemporal features of the supply volume. Lastly, a long short-term memory (LSTM) model is introduced to capture the supply volume’s long- and short-term dependencies, and the predicted value is derived through a multilayer perceptron. The experimental results show that mean square error (MSE) is reduced by 73.8%, 79.36%, 82.24%, 78.58%, 77.02%, 53.96%, and 40.38%, and mean absolute error (MAE) is reduced by 52%, 59.5%, 60.36%, 57.52%, 53.9%, 31.21%, and 36.58%, respectively, when compared to the auto-regressive integrated moving average (ARIMA), support vector regression (SVR), LSTM, gated recurrent units (GRUs), a back propagation neural network (BPNN), and Informer and InformerStack single models; compared with the ARIMA + BPNN, ARIMA + GRU and ARIMA + LSTM integrated models, the MSE is reduced by 74.88%, 71.56%, and 74.07%, respectively, and the MAE is reduced by 51.31%, 50%, and 52.02%; it effectively reduces the supply prediction error and improves the prediction accuracy.
Sustainable School Lunches: A Comparative Analysis of Lunch Quality in Primary Schools in Warsaw and Zagreb
Authors: Górnicka Magdalena , Keser Irena , Kaleta Agnieszka , Jeruszka-Bielak Marta
Published: September 2024

The School Meal Index-Lunch Evaluation (SMI-LE) has been developed to assess school lunch quality. The aim of this study was to use the SMI-LE index for a comparative analysis of the quality of school meals planned in primary schools in Warsaw and Zagreb. The SMI-LE index was used to assess 4-week school meals in both cities. The collected menus were analyzed both in terms of overall quality as an average of points over 4 weeks and in terms of individual categories. According to the SMI-LE index, 4-week school lunches were rated on average 64 and 62 points out of a total of 140 points, in Warsaw and Zagreb, respectively. The majority of school lunches in Zagreb were classified as medium quality, while in Warsaw, over 50% were classified as good quality. Aspects that could be improved include an increase in vegetable availability and variety, limiting the meat dishes, and providing alternatives for children on vegetarian diets, as well as the ability to choose portion sizes. Polish schools need to change their approach to school meals. Following the example of schools in Zagreb, these could be one-course hot meals but with a wider range of raw vegetables and fruits. The current findings also highlight the importance of future research to develop standards for school food policies and investigate whether such a school food program could improve the eating habits and nutritional status of primary school children in the long term. Using the SMI-LE index to design new school meals could be a good solution to improve the quality of school meals.
Fast Joint Optimization of Well Placement and Control Strategy Based on Prior Experience and Quasi-Affine Transformation
Authors: Wang Haochen , Zhang Kai , Liu Chengcheng , Zhang Liming
Published: September 2024

Well placement optimization is one of the most important means to control the decline of oilfields and improve the recovery rate in the development process of deep and heterogeneous reservoirs, such as deep buried carbonate oil reservoirs. However, the mapping relationship from deployed well positions to actual profits is non-linear and multi-modal. At the same time, the injection and production relationship of new wells also affects the contribution of well positions to final profits. Currently, common algorithms include gradient-based and heuristic non-gradient algorithms, which have advantages, but face problems of high computational complexity, slow optimization speed, and difficulty in convergence. We propose an evolutionary algorithm for well placement optimization in carbonate reservoirs. This algorithm improves well placement optimization and computational speed by constraining the sampling process to effective sampling spaces, integrating prior knowledge to enhance sampling efficiency, strengthening local optima exploration, and utilizing parallel computing. Additionally, it refines the optimized variable content based on actual control factors, enhancing the algorithm’s robustness in practical applications. A case study from a carbonate reservoir in northwestern China demonstrated that this algorithm not only improved the performance by 50% compared to the classic DE algorithm but also achieved 15% higher optimization effectiveness than the current state-of-the-art algorithms.
Stress Analysis on the Ankle Joint during Incline and Decline Standing
Authors: Yamin Noor Arifah Azwani Abdul , Basaruddin Khairul Salleh , Ijaz Muhammad Farzik , Mat Som Mohd Hanafi , Shahrol Aman Muhammad Nazrin Shah , Takemura Hiroshi
Published: September 2024

In daily routine movement, the ankle joint plays a crucial role in stability and mobility, especially when different types of terrain are involved. However, the simple task of standing can become a biomechanical difficulty when performed on a slope since demands that have to be accommodated are made on the complex structure of the ankle joint. The purpose of this study is to develop finite element (FE) models of the ankle joint with different inclined foot postures and to analyse the stress distributions on the ankle joint while standing on an inclined or declined surface. In this study, the FE model of the foot was developed, and von Mises stress distribution at the ankle joint was explored. The results show that the bone, cartilage, and ligament of the ankle experienced a different von Mises stress distribution pattern during flat standing in comparison with slope standing. In addition, this study found that the maximum von Mises stress distribution at the component of the ankle joint is higher during slope standing than flat standing. Taken together, these results suggest that slope standing, both inclined and declined, with more than 10° inclination, might contribute to a higher risk of injury as a higher maximum stress was observed. Therefore, to maintain proper body posture, it is suggested that weight be evenly distributed at both feet, since this can reduce stress at the ankle.
Evaluating the Resilience of the Cocoa Agroecosystem in the Offinso Municipal and Adansi North Districts of Ghana
Authors: Asante Richard , Pedersen Søren Marcus , Berg Torsten Rodel , Agbenyega Olivia , Amisah Steve , Barnes Victor Rex , Ayesu Samuel , Opoku Stephen Yaw , Afele John Tennyson , Anokye Joseph
Published: September 2024

The application of the resilience concept within socioecological systems has recently received much attention. Assessing the characteristics of cocoa agroecosystems in the dry and moist semi-deciduous ecological zones has become critical for resilience analysis in this era of climate change and the constant shrinking of cocoa suitability areas. Previous studies have used one of the dimensions of resilience to analyse complex adaptive systems, excluding critical factors and variables. This study applied a multi-criteria decision-making process, the Analytic Hierarchy Process (AHP) that accommodates the three dimensions of resilience, i.e., buffer capacity, adaptive capacity and self-organisation. The AHP is a multi-criteria decision-making tool that proceeds with the design of a hierarchy system for the goal, criteria, attributes and variables. Selected cocoa farmers were assigned weights related to criteria, attributes and variables in a comparison matrix. The resilience of the cocoa agroecosystems in Offinso Municipal and Adansi North Districts was 2.75 ± 0.06 (mean ± SD) and 3.23 ± 0.10 (mean ± SD), respectively. Buffer capacity contributed the highest proportion (44.3%) in the Offinso Municipal District, followed by adaptive capacity (38.7%) and self-organisation (17%). A similar trend was recorded for the Adansi North District: buffer capacity (42.9%), adaptive capacity (42.9%) and self-organisation (14.3%). Across the two study areas, shade trees, crop diversification, soil quality, cocoa variety, farm size, farm age, alternative livelihood, annual income and co-operative membership contributed prominently to the construction of cocoa agroecosystem resilience. The assessment of agroecosystem resilience is location-specific, and the study provides a simplified methodology for evaluating resilience. The paper aims to understand the importance of the components of the cocoa agroecosystem, and a simplified methodology for evaluating its resilience to perturbations. It presents a conceptual and methodological framework for the analysis and measurement of agroecosystem resilience in a participatory manner.
Three-Dimensional Analysis of the Impact of Different Concentrations of Glyphosate on the Growth of Cocoa (Theobroma cacao)
Authors: Valenzuela-Cobos Juan , Guevara-Viejó Fabricio , Galindo-Villardón Purificación , Vicente-Galindo Purificación
Published: September 2024

Ecuadorian cocoa possesses important organoleptic characteristics such as aroma and flavor, called fine and aromatic cocoa. The objective of this study was to evaluate the initial growth responses of young cocoa seedlings to glyphosate in a dose progression in 45 cocoa plants (5 months old), which were transplanted into pots with substrate adjusted to pH 6.0–6.5. Glyphosate doses (0 to 904 g e.e. ha−1) were applied every two weeks, evaluating the impact at 30 and 60 days post-application. Data on shikimate accumulation parameters, chlorophyll content and PSII quantum efficiency were subjected to multivariate analysis using a three-dimensional scatter plot. The results indicated that high concentrations of glyphosate contributed to higher shikimate concentration and lower PSII quantum efficiency. The findings for the variables crop damage, stem height and stem diameter were evaluated by ANOVA. Similarities were reported between the results of the variables height and diameter, and significant differences (p < 0.05) in the variable crop damage for all treatments were also reported. In terms of phytotoxic reaction and growth parameters, the most efficient treatment was DO4, since the seedlings with this dosage showed a low percentage of damage (10%) and the best indices in terms of height and diameter. The least efficient treatment was D15. The control plants (DO1) showed a crop damage of >50% because the absence of control favored weed proliferation. These indications highlight the need to adjust glyphosate doses according to the specific needs of each crop and the development stage of the plant in order to reduce negative effects and maximize potential benefits.
Research on Multimodal Prediction of E-Commerce Customer Satisfaction Driven by Big Data
Authors: Zhang Xiaodong , Guo Chunrong
Published: September 2024

This study deeply integrates multimodal data analysis and big data technology, proposing a multimodal learning framework that consolidates various information sources, such as user geographic location, behavior data, and product attributes, to achieve a more comprehensive understanding and prediction of consumer behavior. By comparing the performance of unimodal and multimodal approaches in handling complex cross-border e-commerce data, it was found that multimodal learning models using the Adam optimizer significantly outperformed traditional unimodal learning models in terms of prediction accuracy and loss rate. The improvements were particularly notable in training loss and testing accuracy. This demonstrates the efficiency and superiority of multimodal methods in capturing and analyzing heterogeneous data. Furthermore, the study explores and validates the potential of big data and multimodal learning methods to enhance customer satisfaction in the cross-border e-commerce environment. Based on the core findings, specific applications of big data technology in cross-border e-commerce operations were further explored. A series of innovative strategies aimed at improving operational efficiency, enhancing consumer satisfaction, and increasing global market competitiveness were proposed.
Solving Time-Dependent Schödinger Equation for Some PT-Symmetric Quantum Mechanical Problems
Authors: Jiang Tsin-Fu
Published: September 2024

Using a high-precision code, we generate the eigenstates of a PT-symmetric Hamiltonian. We solve the time-dependent Schrödinger equation (TDSE) of the non-Hermitian system based on the eigenset. Since the formulation is relatively new and the observables are calculated differently than conventional quantum mechanics, we justify it with a paradigmatic case in Hermitian quantum mechanics. We present the harmonic generation spectra on some model PT-Hamiltonians driven by an electric pulse. We discuss the physical differences with the harmonic spectra of a pulse-driven atom.
Connections between Some Extremization Problems and Associated Inequalities
Authors: Xu Wei , Treanţă Savin
Published: September 2024

In this paper, we investigate and characterize a family of optimization problems introduced by interval-valued functionals that are determined by curvilinear integrals. To this end, we first state the path independence and (strictly) LU convexity properties of the considered functionals. Thereafter, we formulate the corresponding controlled variational inequalities. The main results of this paper provide some connections for the above-mentioned variational models. Since the objective functionals have a physical importance, an illustrative application is considered and studied by using the theoretical elements obtained in this study.
Round-Off Error Suppression by Statistical Averaging
Authors: Liptaj Andrej
Published: September 2024

Regarding round-off errors as random is often a necessary simplification to describe their behavior. Assuming, in addition, the symmetry of their distributions, we show that one can, in unstable (ill-conditioned) computer calculations, suppress their effect by statistical averaging. For this, one slightly perturbs the argument of fx0 many times and averages the resulting function values. In this text, we forward arguments to support the assumed properties of round-off errors and critically evaluate the validity of the averaging approach in several numerical experiments.
Research on New Interval-Valued Fractional Integrals with Exponential Kernel and Their Applications
Authors: Aljohani Abdulrahman F. , Althobaiti Ali , Althobaiti Saad
Published: September 2024

This paper aims to introduce a new fractional extension of the interval Hermite–Hadamard (HH), HH–Fejér, and Pachpatte-type inequalities for left- and right-interval-valued harmonically convex mappings (LRIVH convex mappings) with an exponential function in the kernel. We use fractional operators to develop several generalizations, capturing unique outcomes that are currently under investigation, while also introducing a new operator. Generally, we propose two methods that, in conjunction with more generalized fractional integral operators with an exponential function in the kernel, can address certain novel generalizations of increasing mappings under the assumption of LRIV convexity, yielding some noteworthy results. The results produced by applying the suggested scheme show that the computational effects are extremely accurate, flexible, efficient, and simple to implement in order to explore the path of upcoming intricate waveform and circuit theory research.
Multi-Attribute Decision-Making Based on Consistent Bidirectional Projection Measures of Triangular Dual Hesitant Fuzzy Set
Authors: Wang Juan , Cui Baoyu , Ren Zhiliang
Published: September 2024

To solve complex multi-attribute decision-making (MADM) problems within a triangular dual hesitant fuzzy (TDHF) environment where the attribute weights (Aws) are either fully or partially known, a novel bidirectional projection method is proposed, named multi-attribute decision-making and based on the consistent bidirectional projection measures of triangular dual hesitant fuzzy sets (TDHFSs). First, some notions are developed, such as the operation laws, score and accuracy functions, negative ideal points (NIPs), and positive ideal points (PIPs) of TDHFSs. The correlation coefficients and the cosine of the angle between the vectors of each alternative and the triangular dual hesitant fuzzy (TDHF) points are introduced. Then, the consistent bidirectional projection decision-making method based on the TDHFSs’ correlation coefficients is proposed. Additionally, an optimization model is established via maximizing the consistent coefficient to determine the Aws. Furthermore, some approaches are investigated based on the proposed approaches concerning the MADM issues with attribute values represented by triangular dual hesitant fuzzy elements (TDHFEs). Finally, a supply chain management (SCM) problem is illustrated, and comparative analyses are implemented to demonstrate the presented approach’s feasibility and efficiency.
Effects of Crystalline Diamond Nanoparticles on Silicon Thin Films as an Anode for a Lithium-Ion Battery
Authors: Tzeng Yonhua , Jhan Cheng-Ying , Sung Shi-Hong , Chiou Yu-Yang
Published: September 2024

Crystalline diamond nanoparticles which are 3.6 nm in size adhering to thin-film silicon results in a hydrophilic silicon surface for uniform wetting by electrolytes and serves as a current spreader for the prevention of a local high-lithium-ion current density. The excellent physical integrity of an anode made of diamond on silicon and the long-life and high-capacity-retention cycling performance are thus achieved for lithium-ion batteries. A specific capacity of 1860 mAh/g(si) was retained after 200 cycles of discharge/charge at an areal current density of 0.2 mA/cm2. This is compared to 1626 mAh/g(si) for a thin-film-silicon anode without the additive of diamond nanoparticles.
NMGrad: Advancing Histopathological Bladder Cancer Grading with Weakly Supervised Deep Learning
Authors: Fuster Saul , Kiraz Umay , Eftestøl Trygve , Janssen Emiel A. M. , Engan Kjersti
Published: September 2024

The most prevalent form of bladder cancer is urothelial carcinoma, characterized by a high recurrence rate and substantial lifetime treatment costs for patients. Grading is a prime factor for patient risk stratification, although it suffers from inconsistencies and variations among pathologists. Moreover, absence of annotations in medical imaging renders it difficult to train deep learning models. To address these challenges, we introduce a pipeline designed for bladder cancer grading using histological slides. First, it extracts urothelium tissue tiles at different magnification levels, employing a convolutional neural network for processing for feature extraction. Then, it engages in the slide-level prediction process. It employs a nested multiple-instance learning approach with attention to predict the grade. To distinguish different levels of malignancy within specific regions of the slide, we include the origins of the tiles in our analysis. The attention scores at region level are shown to correlate with verified high-grade regions, giving some explainability to the model. Clinical evaluations demonstrate that our model consistently outperforms previous state-of-the-art methods, achieving an F1 score of 0.85.
Mechanisms Underlying the Therapeutic Effects of JianPiYiFei II Granules in Treating COPD Based on GEO Datasets, Network Pharmacology, Molecular Docking, and Molecular Dynamics Simulations
Authors: Pang Liyuan , Zhao Yongjuan , Xu Yang , Gao Chencheng , Wang Chao , Yu Xiao , Wang Fang , He Kan
Published: September 2024

Background: JianPiYiFei (JPYF) II granules are a Chinese medicine for the treatment of chronic obstructive pulmonary disease (COPD). However, the main components and underlying mechanisms of JPYF II granules are not well understood. This study aimed to elucidate the potential mechanism of JPYF II granules in the treatment of COPD using network pharmacology, molecular docking, and molecular dynamics simulation techniques. Methods: The active compounds and corresponding protein targets of the JPYF II granules were found using the TCMSP, ETCM, and Uniport databases, and a compound–target network was constructed using Cytoscape3.9.1. The COPD targets were searched for in GEO datasets and the OMIM and GeneCards databases. The intersection between the effective compound-related targets and disease-related targets was obtained, PPI networks were constructed, and GO and KEGG enrichment analyses were performed. Then, molecular docking analysis verified the results obtained using network pharmacology. Finally, the protein–compound complexes obtained from the molecular docking analysis were simulated using molecular dynamics (MD) simulations. Results: The network pharmacological results showed that quercetin, kaempferol, and stigmasterol are the main active compounds in JPYF II granules, and AKT1, IL-6, and TNF are key target proteins. The PI3K/AKT signaling pathway is a potential pathway through which the JPYF II granules affect COPD. The results of the molecular docking analysis suggested that quercetin, kaempferol, and stigmasterol have a good binding affinity with AKT1, IL-6, and TNF. The MD simulation results showed that TNF has a good binding affinity with the compounds. Conclusions: This study identified the effective compounds, targets, and related underlying molecular mechanisms of JPYF II granules in the treatment of COPD through network pharmacology, molecular docking, and MD simulation techniques, which provides a reference for subsequent research on the treatment of COPD.
scVGATAE: A Variational Graph Attentional Autoencoder Model for Clustering Single-Cell RNA-seq Data
Authors: Liu Lijun , Wu Xiaoyang , Yu Jun , Zhang Yuduo , Niu Kaixing , Yu Anli
Published: September 2024

Single-cell RNA sequencing (scRNA-seq) is now a successful technology for identifying cell heterogeneity, revealing new cell subpopulations, and predicting developmental trajectories. A crucial component in scRNA-seq is the precise identification of cell subsets. Although many unsupervised clustering methods have been developed for clustering cell subpopulations, the performance of these methods is prone to be affected by dropout, high dimensionality, and technical noise. Additionally, most existing methods are time-consuming and fail to fully consider the potential correlations between cells. In this paper, we propose a novel unsupervised clustering method called scVGATAE (Single-cell Variational Graph Attention Autoencoder) for scRNA-seq data. This method constructs a reliable cell graph through network denoising, utilizes a novel variational graph autoencoder model integrated with graph attention networks to aggregate neighbor information and learn the distribution of the low-dimensional representations of cells, and adaptively determines the model training iterations for various datasets. Finally, the obtained low-dimensional representations of cells are clustered using kmeans. Experiments on nine public datasets show that scVGATAE outperforms classical and state-of-the-art clustering methods.
The Effects of Kynurenic Acid in Zebrafish Embryos and Adult Rainbow Trout
Authors: Marszalek-Grabska Marta , Turska-Kozlowska Monika , Kaczorek-Lukowska Edyta , Wicha-Komsta Katarzyna , Turski Waldemar A. , Siwicki Andrzej K. , Gawel Kinga
Published: September 2024

Kynurenic acid (KYNA) is a metabolite of tryptophan formed on the kynurenine pathway. Its pharmacological effects are relatively well characterized in mammals, whereas its role in fish is poorly understood. Therefore, the aim of the study was to expand the knowledge of KYNA’s presence inside a fish’s body and its impact on fish development and function. The study was performed on zebrafish larvae and adult rainbow trout. We provide evidence that KYNA is present in the embryo, larva and mature fish and that its distribution in organs varies considerably. A study of KYNA’s effect on early larval development suggests that it can accelerate larval maturation, especially under conditions that are suboptimal for fish growth. Moreover, KYNA in concentrations over 1 mM caused morphological impairment and death of larvae. However, long-lasting exposure of larvae to subtoxic concentrations of KYNA does not affect the behavior of 5-day-old larvae kept under standard optimal conditions. We also show that ingestion of KYNA-supplemented feed can lead to KYNA accumulation, particularly in the pyloric caeca of mature trout. These results shed new light on the relevance of KYNA and provide new impulse for further research on the importance of the kynurenine pathway in fish.
Daytime Dysfunction: Symptoms Associated with Nervous System Disorders Mediated by SIRT1
Authors: Huang Tianke , Zhang Xianxie , Qi Ling , Li Fang , Liu Zuoxu , Wang Zhixing , Ru Yi , Li Maoxing , Xiao Chengrong , Wang Yuguang , Ma Zengchun , Gao Yue
Published: September 2024

Daytime dysfunction, including symptoms like sleepiness, poor memory, and reduced responsiveness, is not well researched. It is crucial to develop animal models and study the biological mechanisms involved. We simulated sleep disorders through sleep deprivation, and stressful stimuli were used to establish daytime functional animal models. We used tests like the sodium pentobarbital sleep synergy test and the DSI telemetry system to measure sleep duration and structure. We also used tests like the Morris water maze, open field test, grip test, and baton twirling test to assess mental and physical fatigue. To assess the intrinsic biological mechanisms, we measured sleep–wake-related neurotransmitters and related receptor proteins, circadian rhythm-related proteins and cognition-related proteins in hypothalamus tissue, and oxidative stress, inflammatory factors, S100β, and HPA axis-related indexes in serum. Multi-factor sleep deprivation resulted in the disruption of sleep–wakefulness structure, memory–cognitive function degradation, decreased grip coordination, and other manifestations of decreased energetic and physical strength. The intrinsic biological mechanisms were related to the disturbed expression of sleep–wake, circadian rhythm, memory–cognition-related proteins, as well as the significant elevation of inflammatory factors, oxidative stress, the HPA axis, and other related indicators. Intrinsically related biological mechanisms and reduced sirt1 expression can lead to disruption of circadian rhythms; resulting in disruption of their sleep–wake-related neurotransmitter content and receptor expression. Meanwhile, the reduced expression of sirt1 also resulted in reduced expression of synapse-associated proteins. This study prepared an animal model of daytime dysfunction by means of multi-factor sleep deprivation. With sirt1 as a core target, the relevant biological mechanisms of neurological disorders were modulated.
The Impact of Home Medication Management Practices on Medication Adherence
Authors: Gualtieri Lisa , Steinfeldt Meredith , Shaveet Eden , Estime Brandon , Singhal Meera
Published: September 2024

Medication adherence is a vexing challenge, with over 50% of US adults not adhering to their prescribed medication regimen. Most medications are self-administered by patients at home, requiring them to independently develop and manage their own medication routines. By understanding these home-based practices, such as where patients store their medications and how different storage locations impact adherence, we can develop targeted interventions to improve adherence rates. Our goal was to identify and categorize self-reported home medication management practices and determine which practices are associated with self-reported medication adherence. From the 1673 total survey respondents we learned that the most common places people store their medications at home are nightstand drawers (28%), on top of nightstands (27%), kitchen cabinets (22%), and bathroom medicine cabinets (20%). Kitchen cabinets and bathroom vanities were significantly associated with increased odds of having ever forgotten to take a medication. On the other hand, desks, dining room tables, and the inside of nightstand drawers were associated with the greatest statistically significant decrease in odds of having ever forgotten to take a medication. Almost all (96%) respondents were receptive to receiving guidance from healthcare providers on how to store medications. Patients are largely responsible for creating their own home medication management practices, including deciding where to store their medication at home. Understanding which home storage locations are associated with medication adherence can lead to innovative approaches to improve adherence, including personalized guidance to patients from their healthcare providers for patients.
Do Attitudes towards Gender Equality Influence the Internalization of Ambivalent Sexism in Adolescence?
Authors: Bonilla-Algovia Enrique , Carrasco Carpio Concepción , García-Pérez Rafael
Published: September 2024

Sexism during adolescence may hinder the attainment of gender equality and the eradication of violence against women. The aim of this research was to analyze the relationship between an individual’s view on gender equality and the internalization of ambivalent sexism, as well as to study the impact of different types of egalitarian attitudes (sociocultural, relational, and personal) on the levels of hostile and benevolent sexism among the adolescent population. A quantitative approach with a cross-sectional design was employed in this research. The sample group consisted of 1840 students (50.1% female and 49.9% male) in Compulsory Secondary Education in Castilla-La Mancha, Spain. The results show that adolescents who endorse pro-gender-inequality attitudes exhibit greater levels of hostile and benevolent sexism than their counterparts. Conversely, adolescents adopting pro-equality attitudes leads to lower levels of ambivalent sexism. In both male and female adolescents, egalitarian attitudes at the sociocultural, relational, and individual levels have a negative impact on the internalization of sexism. It is therefore crucial for both schools and families to prioritize the instruction of egalitarian values from early childhood, as this will aid in advancing a fairer and more equal society whilst eradicating sexist biases and violence against women.
Concept Maps to Assess System Understanding: Are Graphical Explanations More Accurate than Verbal Ones?
Authors: Schmidt Judith , Wollermann Lilli , Abele Stephan , Müller Romy
Published: September 2024

Solving problems in a technical system usually requires people to understand its functioning on different levels of abstraction (i.e., goals, functions, components, characteristics) that are connected via means–ends links. We combined this abstraction hierarchy with concept mapping to assess people’s understanding of system functioning. The present study examines the benefits and drawbacks of the proposed method by comparing it to a viable alternative, namely verbal explanation. Using a set of pre-defined concepts, twenty-four participants explained the functioning of two everyday systems: one graphically by constructing a concept map and one verbally. The verbal explanations were subsequently transformed into concept maps by the authors. Compared to verbal explanations, participant-constructed concept maps contained a higher proportion of functional propositions, and lower proportions of structural, temporal, general, and other propositions. Contrary to our expectations, there was no difference regarding the accuracy of functional propositions. Even though participants needed far less time to explain system functioning verbally, our results indicate that concept mapping is better suited to assess functional system understanding. We discuss how this benefit relates to the cognitive processes during concept mapping, and how the method needs to be adapted to assess functional understanding of more complex systems.
Comparative Review of Lift Maintenance Regulations in Beijing, Hong Kong, and London
Authors: Lai Savannah Y. T. , Lai Joseph H. K. , Wong Philip Y. L. , Hu Ben X. Y. , Zhang Leona J. , Edwards David
Published: September 2024

Lifts, or elevators, are transportation facilities that are indispensable for countless end users in high-rise buildings. They require proper maintenance to ensure safe operation. In addition to technological applications, effective management and legislative controls play a crucial role in ensuring lift safety. Given the limited understanding of an optimal regulatory model for governing lift maintenance, a cross-discipline comparative study was conducted to examine lift maintenance regulations in regions with different legal systems. Following a systematic and comparative review approach, this study focused on regulatory controls across civil and common law jurisdictions, specifically Beijing, Hong Kong, and London. Relevant statutes and publications were searched from engineering, law and management databases, which included Scopus, JSTOR, Lexis+, Lexis China, Lexis Advance Hong Kong, and Westlaw Asia. Through scrutinizing the retrieved documents, key features of the regulations were identified and compared in terms of lift classifications, types and frequencies of mandatory maintenance works, qualifications for authorized parties, and legal liabilities for non-compliance. Validated by industry experts, the results reveal both similarities and differences in the regulations among the three jurisdictions. While these findings serve as valuable references for policymakers in formulating optimal legislative controls to enhance lift safety in the future, further research could expand the scope of this study to examine the regulations in other regions and investigate the effectiveness of existing statutory controls on lift maintenance.
Preparation and Performance Study of Flame-Retardant Composite Filling Materials for Tunnel Surrounding Rock
Authors: Dong Sihui , Li Wanjing , Yang Qinde , Xun Wuju
Published: September 2024

Rigid polyurethane foam (RPUF) is a common filling material for tunnels surrounding rock in China. The Chinese national standard explicitly stipulates that RPUF, utilized as a tunnel filling material, must adhere to the following criteria: a thermal conductivity of ≤0.1 W/(m·K), a compressive strength of ≥150 kPa, a limiting oxygen index of ≥26%, and a flame-retardant grade of B2. However, the flame-retardant grade B2 is still possible to burn in the special environment of the tunnel. In view of the strict requirements of national standards for thermal conductivity, compressive strength, and flame-retardant performance of RPUF, this study focuses on optimizing the comprehensive performance of RPUF through scientific matching of flame retardants. The aim is to prepare RPUF that not only meets the national standard but also can reach B1 level. Three flame retardants, melamine polyphosphate (MPP), expandable graphite (EG), and low melting point glass powder (LGP), were selected for the ratio test. Measurement correlation coefficient. A comprehensive analysis of these test results was conducted. The results show that: When the overall proportion of EG-MPP-LGP is 41% and EG:MPP:LGP = 26:13:2. Its thermal conductivity is 0.0555 W/(m·K), compressive strength is 216.72 kPa, and the limiting oxygen index is 32.2%, which increases by 74% compared with pure RPUF. The flame-retardant grade achieved is B1, categorizing it as a flame-retardant material. Additionally, all other properties measured align with national standards. This innovative preparation method provides material support for tunnel safety engineering and has practical value.
Stakeholder Mapping and Analysis of Off-Site Construction Projects: Utilizing a Power–Interest Matrix and the Fuzzy Logic Theory
Authors: Zhu Qing , Xi Jiade , Hu Xin , Chong Heap-Yih , Zhou Yijun , Lyu Sainan
Published: September 2024

Stakeholder management is a crucial component in the implementation of off-site construction (OSC) projects, while stakeholder mapping serves as a practical technique to facilitate an in-depth understanding of different project stakeholders. Various topics have been explored in the OSC stakeholder management field, but research on OSC stakeholder analysis based on stakeholder mapping is still lacking. This study addresses this gap by developing two-dimensional (2D) and three-dimensional (3D) stakeholder mapping models. Data were collected from 167 stakeholders involved in OSC projects. The 2D model utilizes a power–interest matrix to classify 12 identified OSC stakeholder groups, while the 3D model further explores these groups by incorporating an additional dimension of stakeholder salience across different stages of project implementation. The results show that OSC stakeholders predominantly fall into the “key players” or “minimal effort” categories across various project stages. Key players include the client, modular manufacturer, main contractor, government, and designer, while the public and industry organizations generally require minimal effort. Additionally, stakeholders such as the supervision company, supplier, and subcontractor play key roles at specific stages, with varying levels of salience throughout the project lifecycle, reflecting shifts in their influence and involvement. The findings contribute to stakeholder management knowledge by providing an in-depth understanding of OSC stakeholders’ interrelationships during project implementation, especially through uncovered stakeholder mapping in the OSC field.
Technique and Tectonic Concepts as Theoretical Tools in Object and Space Production: An Experimental Approach to Building Technologies I and II Courses
Authors: Sönmez Murat
Published: September 2024

By focusing on technical content, this study presents ‘two experimental building technologies courses’ connecting the conceptual and practical aspects of architectural object production. Built on the fundamental ‘concept of making’, these courses encourage students to explore their creative abilities by uniting material, form, and purpose. In the Building Technologies I course, exploration starts with the concept of ‘technique’, which involves the practical and theoretical knowledge necessary to shape architectural objects. This technique allows the production of architectural objects that encapsulate spaces carrying action and time, making a mere explanation of space creation insufficient. Thus, in the Building Technologies II course, the focus shifts to the ‘tectonic’ concept, which involves creating coherent spatial entities within a single structural system. The two courses aim to equip students with the ability to develop their unique knowledge and methods for construction before advancing to more theorised Building Technologies courses. Students are encouraged to engage with materials to uncover their potential, experiment with forms to achieve design goals, and personalise construction processes. This proposal advocates for foundational construction courses built on intuitive knowledge to replace traditional rational knowledge courses. Our study presents the methodologies and outputs of the proposed Building Technologies courses as a basis for ongoing construction courses.
A Dynamic Impact Evaluation of the High-Quality Development of China’s Construction Industry Using the Panel Vector Autoregressive Model
Authors: Li Hui , Yang Xin , Meng Fanyu , Hou Yu , Zhang Jinshuai , Zhang Lingyao , Yang Ge , Liu Jiyu
Published: September 2024

Based on the theory of new structural economics, this research aims to explore the dynamic correlation among high-quality development, environmental regulation structures, and property rights structures in China’s construction industry. A panel vector autoregressive model (PVAR) is employed to conduct an empirical study of 30 provinces from 2008 to 2022. To further explore regional heterogeneity, K-means clustering is utilized to categorize the country into three types of regions. The results indicate that strict environmental regulation structures have a beneficial effect on the high-quality growth of the construction sector, which is most pronounced in Region III with a lower degree of construction development. Conversely, state-owned ownership structures are an impediment, and their influence is the greatest in Region I with a higher degree of construction development. Additionally, environmental regulation structures and property rights structures demonstrate a certain interactional effect. The dynamic correlation between these indicators varies in distinct regions. Various regions in China should combine their development characteristics and advantages to reasonably adjust environmental regulation structures and property rights structures. This research provides a direction for structural adjustments for the high-quality development of the construction industry.
Future Climate Projections and Uncertainty Evaluations for Frost Decay Exposure Index in Norway
Authors: Gaarder Jørn Emil , Tajet Helga Therese Tilley , Dobler Andreas , Hygen Hans Olav , Kvande Tore
Published: September 2024

To implement the geographical and future climate adaptation of building moisture design for building projects, practitioners need efficient tools, such as precalculated climate indices to assess climate loads. Among them, the Frost Decay Exposure Index (FDEI) describes the risk of freezing damage for clay bricks in facades. Previously, the FDEI has been calculated for 12 locations in Norway using 1961–1990 measurements. The purpose of this study is both updating the FDEI values with new climate data and future scenarios and assessing how such indices may be suitable as a climate adaptation tool in building moisture safety design. The validity of FDEI as an expression of frost decay potential is outside the scope of this study. Historical data from the last normal period as well as future estimated climate data based on 10 different climate models forced by two emission scenarios (representative concentration pathways 4.5 and 8.5) have been analyzed. The results indicate an overall decline in FDEI values on average, due to increased winter temperatures leading to fewer freezing events. Further, the variability between climate models and scenarios necessitates explicit uncertainty evaluations, as single climate model calculations may result in misleading conclusions due to high variability between models.
Investigation of Synergistic Influence of Ultrasound and Co-Doping to Degrade Toluene from Polluted Air in Construction Sites—An Experimental Approach
Authors: Akbarzadeh Omid , Rasoulzadeh Yahya , Haghighi Mohammad , Talati Azadeh , Golzad Hamed
Published: September 2024

Background: Toluene exposure in construction workers can lead to several health problems, primarily affecting the nervous system, respiratory system, and skin. Utilizing advanced photocatalytic materials to degrade gaseous toluene aims to significantly mitigate its negative impact. Methods: In this research, photocatalysts based on pure TiO2 and modified TiO2 were synthesized to evaluate their efficacy in degrading gaseous toluene, a prevalent air pollutant in construction settings. Two synthesis methods were employed. Sonoprecipitation was used to create Fe-N co-doped TiO2 nanoparticles in the first method, while the second method utilized co-precipitation and hydrothermal techniques without ultrasonic assistance to achieve Fe-N co-doping. Seven types of nanophotocatalysts were synthesized, including TiO2-U (with ultrasonic assistance), NTiO2-U, FeNTiO2 (2.5)-U, FeNTiO2 (5)-U, FeNTiO2 (7.5)-U, FeNTiO2 (10)-U, and FeNTiO2 (5) without ultrasonic assistance. Characterization of the synthesized photocatalysts involved various analyses, including XRD, SEM, EDX, UV–VIS DRS, FT–IR, BET, and N2 adsorption-desorption isotherm. Results: Ultrasonic assistance notably improved particle dispersion and prevented agglomeration on the photocatalyst surface. UV–VIS DRS analysis indicated a reduction in band gap energy due to Fe and N doping of TiO2. The study also investigated the influence of Fe doping, initial toluene concentration, light source, and residence time on the degradation rate of gaseous toluene. Experimental findings showed that FeNTiO2 (5)-U exhibited a higher degradation rate of toluene (63.5%) compared to FeNTiO2 (5) (50%) under visible light irradiation over 15 s. Conclusions: The study underscores the significant enhancement in photocatalytic activity for toluene degradation achieved through the combined effects of ultrasound and co-doping methods.
Dermatofibrosarcoma Protuberans: An Updated Review of the Literature
Authors: Jozwik Marcin , Bednarczuk Katarzyna , Osierda Zofia
Published: September 2024

Dermatofibrosarcoma protuberans (DFSP) is a rare proliferative condition representing skin sarcomas which is known to locally recur yet very rarely metastasizes. Its genetic background is a reciprocal translocation t(17;22)(q22;q13) that produces COL1A1-PDGFB gene fusion. Complete resection is the primary treatment. The aim of this review is to outline the pathogenesis, diagnosis, and management of DFSP. A clear-cut distinction between low-to-moderate-grade DFSP with excellent prognosis and high-grade fibrosarcomatous DFSP with a much worse prognosis is underlined. Malignant transformation within DFSP (or high histologic grade), older age, being female, large primary tumor size (≥10 cm), narrow surgical margins of excision (<3 cm), surgical margin positivity for tumor cells, short time to recurrence, numerous recurrences, tumor that was recently rapidly enlarging, and presence of pain in the tumor have all been proposed as clinicopathological risk factors for recurrence and metastasis. A tendency for local growth and local relapses of well- and moderately differentiated DFSPs is an argument for their surgical excision, possibly combined with reconstructive surgery, even in patients of advanced age. Another main point of this review is that cases of DFSP with fibrosarcomatous transformation are a challenge and require careful medical attention. Both anatomopathological evaluation of the presence of lymphovascular space invasion and sentinel lymph node biopsy at DFSP surgery merit further study.
The Role of ctDNA and Liquid Biopsy in the Diagnosis and Monitoring of Head and Neck Cancer: Towards Precision Medicine
Authors: Nassar Sami I. , Suk Amber , Nguyen Shaun A. , Adilbay Dauren , Pang John , Nathan Cherie-Ann O.
Published: September 2024

Recent data have shown a continued rise in the worldwide annual incidence and mortality rates of head and neck cancers. The present standard for diagnosis and monitoring for disease recurrence or progression involves clinical examination, imaging, and invasive biopsy techniques of lesions suspected of being malignant. In addition to limitations relating to cost, time, and patient discomfort, these methodologies have inherent inaccuracies for detecting recurrence. In view of these limitations, the analysis of patient bodily fluid samples via liquid biopsy proposes a cost-effective and convenient alternative, which provides insight on the biogenetic and biomolecular underpinnings of oncologic disease processes. The monitoring of biomarkers for head and neck cancer via liquid biopsy, including circulating tumor DNA, circulating tumor cells, and circulating cell-free RNA, has shown clinical utility in the screening, diagnosis, prognostication, and monitoring of patients with various forms of head and neck cancer. The present review will provide an update on the current literature examining the use of liquid biopsy in head and neck cancer care and the clinical applicability of potential biomarkers, with a focus on viral and non-viral circulating tumor DNA. Possible future avenues for research to address specific shortcomings of liquid biopsy will be discussed.