bluuebunny/crossref_metadata_2025 huggingface dataset:
Building a Speech Dataset and Recognition Model for the Minority Tu Language
Authors: Kong Shasha , Li Chunmei , Fang Chengwu , Yang Peng
Published: August 2024

Speech recognition technology has many applications in our daily life. However, for many low-resource languages without written forms, acquiring sufficient training data remains a significant challenge for building accurate ASR models. The Tu language, spoken by an ethnic minority group in Qinghai Province in China, is one such example. Due to the lack of written records and the great diversity in regional pronunciations, there has been little previous research on Tu-language speech recognition. This work seeks to address this research gap by creating the first speech dataset for the Tu language spoken in Huzhu County, Qinghai. We first formulated the relevant pronunciation rules for the Tu language based on linguistic analysis. Then, we constructed a new speech corpus, named HZ-TuDs, through targeted data collection and annotation. Based on the HZ-TuDs dataset, we designed several baseline sequence-to-sequence deep neural models for end-to-end Tu-language speech recognition. Additionally, we proposed a novel SA-conformer model, which combines convolutional and channel attention modules to better extract speech features. Experiments showed that our proposed SA-conformer model can significantly reduce the character error rate from 23% to 12%, effectively improving the accuracy of Tu language recognition compared to previous approaches. This demonstrates the effectiveness of our dataset construction and model design efforts in advancing speech recognition technology for this low-resource minority language.
Preparation and Performance Characterization of Low-Density 3D-Printed Expanded Perlite–Foam Concrete
Authors: Jiang Shangjin , Wang Yuntao , Hua Sudong , Yue Hongfei , Zhang Yanan
Published: August 2024

Traditional lightweight foam concrete typically introduces a large number of voids into the concrete using surfactants to reduce density. However, in 3D printing, the instability of lightweight foam concrete can affect the workability of the slurry. Additionally, the lower strength of foam with more pores also reduces its mechanical performance. This study found that by replacing sand with expanded perlite in 3D-printed foam concrete, the stability of the foam is improved, enhancing the workability of the mixture and increasing the constructability of printed concrete. Furthermore, analyses of mechanical properties, porosity, and pore size distribution showed that at the same dry density, foam concrete with a higher expanded perlite replacement ratio exhibited higher compressive strength, with a maximum strength increase of up to 39%. Moreover, the introduction of expanded perlite optimized the pore distribution of the foam concrete, resulting in a more uniform material structure. The 3D-printed expanded perlite–foam concrete (3DPFC) prepared in this study provides new insights for the preparation of lightweight 3D-printed concrete, which is of significant importance for the sustainable development of the construction industry.
Meat Color, Marbling, and the Evaluation of Defects in Beef and Pork at the Point of Purchase
Authors: Simunović Sara , Tomasevic Igor , Djordjevic Vesna Ž. , Baltić Tatjana , Simunovic Stefan , Ćirić Jelena , Djekic Ilija
Published: August 2024

Intentions to purchase meat and repeat purchasing patterns will depend on the consumer’s perception of intrinsic and extrinsic quality cues. In order to discover consumers’ insights into the quality of pork and beef, the main objective of this study was to investigate meat color, marbling, and types of fresh meat defects. A total of 50 samples of meat were analyzed for three quality characteristics on different levels. This study applied a statistical calculation of a loss function invented by Taguchi. The results showed the values of variations in meat color and marbling that present the limits of consumers’ tolerance. Based on the obtained results, it was determined that the tolerable level of color variations of beef is 3.61, while for pork, this limit is 2.00. The most preferred marbling percentages were 21% and 5.74% for beef and pork, respectively. On the other hand, the negative effect of defects was the strongest for “dark cutting” for beef and “blood spotting” for pork loins.
Contributions of the Communication and Management of Bad News in Nursing to the Readaptation Process in Palliative Care: A Scoping Review
Authors: Moura Teresa , Ramos Ana , Sá Eunice , Pinho Lara , Fonseca César
Published: August 2024

Background: Delivering bad news is a sensitive and challenging aspect of nursing healthcare, requiring a holistic approach that respects patients’ preferences, cultural values, and religious beliefs to promote adaptation to the person’s state of health. Aim: We aim to map the evidence of the dimensions present in the communication and management of bad news by nurses to a person in a palliative situation, their caregivers, and their family members. Methods: Based on the Joanna Briggs Institute methodology, the search was conducted through MEDLINE Complete (EBSCOhost), CINAHL Complete (EBSCOhost), SciELO, and the Open Access Scientific Repository in Portugal. From a total of 756 articles, 14 were included, published between 2018 and 2023. Results: Structure components in bad news are influenced by the characteristics of the palliative patients, their caregivers, their family members, the nurses, and the organizational environment. Promoting the quality of the communication process is desirable through continuous and advanced training in end-of-life care, training in bad news, religiously and culturally sensitive nursing interventions centered on hope and maintaining faith, emotional management, and the utilization of a checklist protocol. Conclusions: Honest communication allows people to actively participate in the decision-making process and in the trajectory of the care plan that is focused on themselves and their preferences, which has outcomes in functional capacities and readaptation.
Fusing Ground-Penetrating Radar Images for Improving Image Characteristics Fidelity
Authors: Tassiopoulou Styliani , Koukiou Georgia
Published: August 2024

The analysis of ground-penetrating radar (GPR) data is of vital importance for detecting various subsurface features that might manifest as hyperbolic peaks, which are indicators of a buried object or grayscale variation in the case of contrast in the soil texture. This method focuses on identifying exaggerated patterns through a series of image-processing steps. Two GPR images are initially read and preprocessed by extracting channels, flipping, and resizing. Then, specific regions of interest (ROIs) are cropped, and the Fourier transform is further applied to turn them into the frequency domain. With the help of their frequency signatures, these patterns are extracted from the images, and binary masks are constructed to obtain features of interest. These masked images were reconstructed and merged to make hyperbolic features visible. Finally, Local Binary Pattern (LBP) analysis is used to emphasize these hyperbolic peaks, thereby facilitating their recognition across the whole image. The proposed approach improves the detection of performance subsurface features in GPR data; hence, it is an important tool for geophysical surveys and other related applications. The results prove the high performance of the proposed procedure in improving GPR image characteristics.
Health State Prediction Method Based on Multi-Featured Parameter Information Fusion
Authors: Yin Xiaojing , Rong Yao , Li Lei , He Weidong , Lv Ming , Sun Shiqi
Published: August 2024

The prediction of the health status of critical components is an important influence in making accurate maintenance decisions for rotating equipment. Since vibration signals contain a large amount of fault information, they can more accurately describe the health status of critical components. Therefore, it is widely used in the field of rotating equipment health state prediction. However, there are two major problems in predicting the health status of key components based on vibration signals: (1) The working environment of rotating equipment is harsh, and if only one feature in the time or frequency domain is selected for fault analysis, it will be susceptible to harsh operating environments and cannot completely reflect the fault information. (2) The vibration signals are unlabeled time series data, which are difficult to accurately convert into the health status of key components. In order to solve the above problems, this paper proposes a combined prediction model combining a bidirectional long- and short-term memory network (BiLSTM), a self-organizing neural network (SOM) and particle swarm optimization (PSO). Firstly, the SOM is utilized to fuse the fault characteristics of multiple vibration signals of key components to obtain an indicator (HI) that can reflect the health status of rotating equipment and to also compensate for the vulnerability of single signal characteristics in the time or frequency domain to environmental influences. Secondly, the K-means clustering method is employed to cluster the health indicators and determine the health state, which solves the problem of determining the health of a component from unsupervised vibration signal data which is quite difficult. Finally, the particle swarm optimized BiLSTM model is used to predict the health state of key components and the bearing dataset from the IEEE PHM 2012 Data Challenge verifies the method’s effectiveness and validity.
A User-Centered Framework for Data Privacy Protection Using Large Language Models and Attention Mechanisms
Authors: Zhou Shutian , Zhou Zizhe , Wang Chenxi , Liang Yuzhe , Wang Liangyu , Zhang Jiahe , Zhang Jinming , Lv Chunli
Published: August 2024

This paper introduces a user-centered data privacy protection framework utilizing large language models (LLMs) and user attention mechanisms, which are tailored to address urgent privacy concerns in sensitive data processing domains like financial computing and facial recognition. The innovation lies in a novel user attention mechanism that dynamically adjusts attention weights based on data characteristics and user privacy needs, enhancing the ability to identify and protect sensitive information effectively. Significant methodological advancements differentiate our approach from existing techniques by incorporating user-specific attention into traditional LLMs, ensuring both data accuracy and privacy. We succinctly highlight the enhanced performance of this framework through a selective presentation of experimental results across various applications. Notably, in computer vision, the application of our user attention mechanism led to improved metrics over traditional multi-head and self-attention methods: FasterRCNN models achieved precision, recall, and accuracy rates of 0.82, 0.79, and 0.80, respectively. Similar enhancements were observed with SSD, YOLO, and EfficientDet models with notable increases in all performance metrics. In natural language processing tasks, our framework significantly boosted the performance of models like Transformer, BERT, CLIP, BLIP, and BLIP2, demonstrating the framework’s adaptability and effectiveness. These streamlined results underscore the practical impact and the technological advancement of our proposed framework, confirming its superiority in enhancing privacy protection without compromising on data processing efficacy.
Effect of Bedding Angle on Energy and Failure Characteristics of Soft–Hard Interbedded Rock-like Specimen under Uniaxial Compression
Authors: Wang Zheng , Guo Jiaqi , Chen Fan
Published: August 2024

To investigate how bedding planes affect the energy evolution and failure characteristics of transversely isotropic rock, uniaxial compression tests were conducted on soft–hard interbedded rock-like specimens with varying bedding angles (α) using the RMT-150B rock mechanics loading system. The test results indicate that throughout the loading process, the energy evolution shows obvious stage characteristics, and the change of α mainly affects the accelerating energy dissipation stage and the full energy release stage. With the increase of α, the ability of rock to resist deformation under the action of energy shows the characteristics of “strong–weak–strong”. The energy dissipation process is accelerated by medium angle bedding planes (α = 45°~60°). The precursor points of the ratios of dissipation energy to total energy (RDT) and elastic energy to dissipation energy (RED) can be used to effectively predict early failure. With the gradual increase of α, the difficulty of crack development is gradually reduced. The changes of energy storage limitation and release rate of releasable elastic energy are the immanent cause of different macroscopic failure modes of specimens with varying α.
Self-Adaptable Software for Pre-Programmed Internet Tasks: Enhancing Reliability and Efficiency
Authors: Martínez García Mario , Martínez Rodríguez Luis Carlos G. , Pérez Zúñiga Ricardo
Published: August 2024

In the current digital landscape, artificial intelligence-driven automation has revolutionized efficiency in various areas, enabling significant time and resource savings. However, the reliability and efficiency of software systems remain crucial challenges. To address this issue, a generation of self-adaptive software has emerged with the ability to rectify errors and autonomously optimize performance. This study focuses on the development of self-adaptive software designed for pre-programmed tasks on the Internet. The software stands out for its self-adaptation, automation, fault tolerance, efficiency, and robustness. Various technologies such as Python, MySQL, Firebase, and others were employed to enhance the adaptability of the software. The results demonstrate the effectiveness of the software, with a continuously growing self-adaptation rate and improvements in response times. Probability models were applied to analyze the software’s effectiveness in fault situations. The implementation of virtual cables and multiprocessing significantly improved performance, achieving higher execution speed and scalability. In summary, this study presents self-adaptive software that rectifies errors, optimizes performance, and maintains functionality in the presence of faults, contributing to efficiency in Internet task automation.
Synthetic Medical Imaging Generation with Generative Adversarial Networks for Plain Radiographs
Authors: McNulty John R. , Kho Lee , Case Alexandria L. , Slater David , Abzug Joshua M. , Russell Sybil A.
Published: August 2024

In medical imaging, access to data is commonly limited due to patient privacy restrictions, and it can be difficult to acquire enough data in the case of rare diseases. The purpose of this investigation was to develop a reusable open-source synthetic image-generation pipeline, the GAN Image Synthesis Tool (GIST), that is easy to use as well as easy to deploy. The pipeline helps to improve and standardize AI algorithms in the digital health space by generating high quality synthetic image data that is not linked to specific patients. Its image generation capabilities include the ability to generate imaging of pathologies or injuries with low incidence rates. This improvement of digital health AI algorithms could improve diagnostic accuracy, aid in patient care, decrease medicolegal claims, and ultimately decrease the overall cost of healthcare. The pipeline builds on existing Generative Adversarial Networks (GANs) algorithms, and preprocessing and evaluation steps were included for completeness. For this work, we focused on ensuring the pipeline supports radiography, with a focus on synthetic knee and elbow X-ray images. In designing the pipeline, we evaluated the performance of current GAN architectures, studying the performance on available X-ray data. We show that the pipeline is capable of generating high-quality and clinically relevant images based on a lay person’s evaluation and the Fréchet Inception Distance (FID) metric.
A Meshless Method of Radial Basis Function-Finite Difference Approach to 3-Dimensional Numerical Simulation on Selective Laser Melting Process
Authors: Chen Chieh-Li , Wu Cheng-Hsuan , Chen Cha’o-Kuang
Published: August 2024

Selective laser melting (SLM) is a rapidly evolving technology that requires extensive knowledge and management for broader industrial adoption due to the complexity of phenomena involved. The selection of parameters and numerical analysis for the SLM process are both costly and time-consuming. In this paper, a three-dimensional radial basis function-finite difference (RBF-FD) meshless model is introduced to accurately and efficiently simulate the molten pool size and temperature distribution during the SLM process for austenitic stainless steel (AISI 316L). Two different volumetric moving heat source models were presented, namely the ray-tracing method heat source model and the double-ellipsoidal shape heat source model. The temperature-dependent material properties and phase change process were also considered, based on experiments and effective models. Results of the model for the molten pool size were validated with those of the literature. The proposed approach can be used to predict the effect of different laser power and scan speed on the molten pool size and temperature gradient along the depth direction. The result reveals that the depth of the molten pool is more sensitive to laser power than scan speed. Under the same scan speed, a 22% change in laser power (45 ± 10 W) affects the maximum temperature proportionally by about 9%. The developed algorithm is computationally efficient and suitable for industrial applications.
Can Stiff Matter Solve the Hubble Tension?
Authors: Grøn Øyvind G.
Published: August 2024

A new form of the mathematical expression for the co-moving volume element of a flat universe with cosmological constant, cold matter, and stiff matter is presented. It is used to determine the constraints from the Planck measurements of the Hubble parameter on the amount of stiff matter in the universe. These constraints are used to investigate whether the presence of stiff matter can solve the Hubble tension. It is found that the Planck measurements lead to an upper bound on the present value of the density parameter of stiff matter ΩS0<5⋅10−23, and that this is too small to solve the Hubble tension. Report. The main objective of this article is to introduce a novel mathematical expression for the co-moving volume element in a flat universe that includes a cosmological constant, cold matter, and stiff matter. This expression is utilized to derive constraints on the amount of stiff matter in the universe based on the Planck measurements of the Hubble parameter. These constraints are then examined to assess whether stiff matter could potentially resolve the Hubble tension. The findings indicate that the Planck measurements impose an upper limit on the current value of the density parameter of stiff matter, ΩS0<5⋅10−23, which is insufficient to resolve the Hubble tension.
Numerical Analysis of the Cylindrical Shell Pipe with Preformed Holes Subjected to a Compressive Load Using Non-Uniform Rational B-Splines and T-Splines for an Isogeometric Analysis Approach
Authors: EL Fakkoussi Said , Koubaiti Ouadie , Elkhalfi Ahmed , Vlase Sorin , Marin Marin
Published: August 2024

In this paper, we implement the finite detail technique primarily based on T-Splines for approximating solutions to the linear elasticity equations in the connected and bounded Lipschitz domain. Both theoretical and numerical analyses of the Dirichlet and Neumann boundary problems are presented. The Reissner–Mindlin (RM) hypothesis is considered for the investigation of the mechanical performance of a 3D cylindrical shell pipe without and with preformed hole problems under concentrated and compression loading in the linear elastic behavior for trimmed and untrimmed surfaces in structural engineering problems. Bézier extraction from T-Splines is integrated for an isogeometric analysis (IGA) approach. The numerical results obtained, particularly for the displacement and von Mises stress, are compared with and validated against the literature results, particularly with those for Non-Uniform Rational B-Spline (NURBS) IGA and the finite element method (FEM) Abaqus methods. The obtained results show that the computation time of the IGA based on the T-Spline method is shorter than that of the IGA NURBS and FEM Abaqus/CAE (computer-aided engineering) methods. Furthermore, the highlighted results confirm that the IGA approach based on the T-Spline method shows more success than numerical reference methods. We observed that the NURBS IGA method is very limited for studying trimmed surfaces. The T-Spline method shows its power and capability in computing trimmed and untrimmed surfaces.
Three New Species and a New Record of the Lichen Genus Peltula (Peltulaceae) from Helan Mountain in China
Authors: Wang Siying , Zhao Gege , Niu Dongling , Wang Liang , Ren Xia , Wu Jinai , Qu Hongbin
Published: August 2024

In this study, a systematic taxonomic analysis was carried out on the lichen genus Peltula, collected from Helan Mountain in China; three new species (Peltula helanense, P. overlappine, and P. reticulata) and a new record (P. crispatula (Nyl.) Egea) for China were identified. Four species were identified by morph-anatomical, chemical, and phylogenetic analyses by combining two gene loci (ITS and LSU). Peltula helanense is with tiny individual thalli up to 1mm, attached by creamy-white cylindrical rhizoids and apothecia filling the whole squamule. Peltula overlappine is characterized by thallus squamulose forming rosette-shaped patches and squamules with distinctive thickened margins. Peltula reticulata is characterized by brownish brown thallus and squamules with densely reticulate upper surface. P. crispatula is characterized by irregular squamules attached to a tuft of hyphae. The four species are described in detail, compared, and discussed with similar species, and images of morpho-anatomical structures of the four species are also provided. Moreover, a key to the species of Peltula from Helan Mountain is provided. The results enrich the data of the genus Peltula and also indicate that the rich diversity of lichen species in Helan Mountain is worthy of in-depth study.
Establishment and Evaluation of a Mouse Model of Experimental Ulcerative Colitis Induced by the Gavage Administration of Dextran Sulfate Sodium
Authors: Wang Dan , Chen Wei , Cao Jie , Si Luqin , Chen Zehong
Published: August 2024

Given the critical role of dextran sulfate sodium (DSS)-induced ulcerative colitis (UC) mouse models in the appraisal of associated therapeutic drugs, the optimization of the administration method and dosages is of paramount importance. Therefore, UC was induced in mice through the gavage administration of a DSS solution instead of free drinking water. The effects of varying daily dosages (2, 4, 6, and 8 g/kg) and frequencies (once or twice) of administration on the body weight and survival rate of the model mice were evaluated. Concurrently, the inflammatory indicators and tissue sections of the model mice were thoroughly evaluated. The results revealed that when the daily dosage reached 8 g/kg, the dosage exhibited a high level of toxicity, resulting in a high mortality rate among the mice. The DSS administration of 6 g/kg*2 not only elicited conspicuous symptoms, significant weight loss, substantial shortening of the colon, and significant changes in various inflammatory indicators, such as myeloperoxidase (MPO), nitric oxide (NO), reactive oxygen species (ROS), and glutathione (GSH), but it also maintained a high survival rate in the UC mice. The findings from this experiment lay a solid experimental foundation for future research on drugs intended for the treatment of UC.
Quantifying Plant Signaling Pathways by Integrating Luminescence-Based Biosensors and Mathematical Modeling
Authors: Ahmed Shakeel , Naqvi Syed Muhammad Zaigham Abbas , Hussain Fida , Awais Muhammad , Ren Yongzhe , Wu Junfeng , Zhang Hao , Zang Yiheng , Hu Jiandong
Published: August 2024

Plants have evolved intricate signaling pathways, which operate as networks governed by feedback to deal with stressors. Nevertheless, the sophisticated molecular mechanisms underlying these routes still need to be comprehended, and experimental validation poses significant challenges and expenses. Consequently, computational hypothesis evaluation gains prominence in understanding plant signaling dynamics. Biosensors are genetically modified to emit light when exposed to a particular hormone, such as abscisic acid (ABA), enabling quantification. We developed computational models to simulate the relationship between ABA concentrations and bioluminescent sensors utilizing the Hill equation and ordinary differential equations (ODEs), aiding better hypothesis development regarding plant signaling. Based on simulation results, the luminescence intensity was recorded for a concentration of 47.646 RLUs for 1.5 μmol, given the specified parameters and model assumptions. This method enhances our understanding of plant signaling pathways at the cellular level, offering significant benefits to the scientific community in a cost-effective manner. The alignment of these computational predictions with experimental results emphasizes the robustness of our approach, providing a cost-effective means to validate mathematical models empirically. The research intended to correlate the bioluminescence of biosensors with plant signaling and its mathematical models for quantified detection of specific plant hormone ABA.
Psychopathic Traits in Adult versus Adolescent Males: Measurement Invariance across the PCL-R and PCL:YV
Authors: Ngo Darlene A. , Neumann Craig S. , Maurer J. Michael , Harenski Carla , Kiehl Kent A.
Published: August 2024

Both the Psychopathy Checklist–Revised (PCL-R) and the Psychopathy Checklist: Youth Version (PCL:YV), respectively, are established instruments for assessment of psychopathy and development of psychopathic propensity. To reliably compare scores from both instruments, measurement invariance must be established. The current study involved a combined sample of 1091 male participants (adults = 813; adolescents = 278) from correctional facilities in New Mexico. An exploratory structural equation modeling (ESEM) framework was used to test for measurement invariance. The four-factor ESEM model demonstrated good fit for the combined and individual samples. Results from the multiple group ESEM provide evidence for generally strong invariance, with equivalent factor loadings and thresholds. Adolescents exhibited decreased latent interpersonal traits but increased latent features on other PCL factors (affective, lifestyle, and antisocial) compared to adults. Findings suggest that the four-factor model and the measurement of psychopathic traits remain consistent across age groups. Implications of the findings within research and clinical contexts are discussed.
Relationships between Resilience and Self-Efficacy in the Prosocial Behavior of Chilean Elementary School Teachers
Authors: Salvo-Garrido Sonia , Polanco-Levicán Karina , Dominguez-Lara Sergio , Mieres-Chacaltana Manuel , Gálvez-Nieto José Luis
Published: August 2024

Teachers’ actions go beyond instruction, as their personal traits influence their teaching methods, problem-solving skills, and the quality of their relationships with students. Among these attributes, their prosocial competencies stand out for contributing to school, community, and social coexistence. Furthermore, the connection they have to resilience and self-efficacy promotes increased effectiveness in meeting the demands of an ever-more challenging work environment. This research aimed to analyze the effect of the relationship between self-efficacy and resilience on the prosocial behavior of Chilean elementary school teachers. The sample consisted of 1426 teachers (77.2% women) working in public and subsidized Chilean schools. Structural equation modeling (SEM) explored the relationships between self-efficacy, resilience, and prosocial behavior. The findings indicate that self-efficacy and resilience directly and positively affect the prosocial behavior of elementary school teachers. It is suggested that resilience, self-efficacy, and prosociality among teachers are promoted due to their synergistic effects and, consequently, the benefits for school children, especially those from vulnerable social contexts.
Revitalizing Rural Landscapes: Applying Cultural Landscape Gene Theory for Sustainable Spatial Planning in Linpu Village
Authors: Liu Shuhu , Wu Lin , Xiang Chenlu , Dai Wenyuan
Published: August 2024

In the context of rapid urbanization, it is imperative to address the preservation and sustainable development of rural landscapes. This study introduces a novel framework using cultural landscape gene theory to enhance the landscape spatial pattern of Linpu Village, China. Employing a multi-method approach, including data collection and historical data analysis, GIS analysis, and field surveys, we analyze the village’s landscape features and identify a well-preserved “one core, two wings” spatial configuration with diminishing accessibility from the center to the periphery. The study uncovers significant challenges to landscape coherence and legibility, including landscape element discontinuity, inadequate maintenance, and fragmented information. To address these issues, we propose optimization strategies aimed at revitalizing weakened cultural landscape genes, repairing disrupted elements, ensuring corridor integrity, and improving spatial organization. The extraction–construction–analysis–preservation model established in this research not only delivers a comprehensive analysis of Linpu’s cultural landscape but also offers a scalable framework for preserving the ecological and cultural integrity of traditional villages. This study contributes to the practical implementation of sustainable landscape strategies, enhancing the ecological adaptability and resilience of rural environments in the face of urban encroachment.
Analyzing Critical Factors Influencing the Quality Management in Smart Construction Site: A DEMATEL-ISM-MICMAC Based Approach
Authors: Zhang Shuolin , Liu Jianzhao , Li Zirui , Xiahou Xiaer , Li Qiming
Published: August 2024

The swift integration of advanced technologies in the construction sector has significantly propelled the adoption of smart construction sites (SCSs). Quality management (QM), a critical endeavor within the construction domain, is central to the operational success of construction projects. The establishment of quality management in smart construction sites (SCS-QM) specifically seeks to delineate the principal factors influencing quality management in the context of SCS, with the objective of enhancing overall project quality. This study has identified 19 pivotal factors impacting SCS-QM by drawing upon the 4M1E quality management framework and an extensive review of the literature. Utilizing the hybrid DEMATEL-ISM-MICMAC analytical framework, the research evaluates these factors in terms of significance, hierarchical structure, and interdependencies, thereby formulating targeted strategies for the advancement of SCS-QM. Through a systematic evaluation by nine experts, this study categorizes the influencing factors into nine levels, three layers, and four areas, further classifying them into four distinct impact typologies. The results underscore that those technologies, such as automation and intelligence, along with regulatory frameworks, comprehensive quality management standards, transparency of critical technologies, training of construction personnel, and effective process management, constitute the foundational elements crucial for enhancing SCS-QM.
Utilizing Marble Wastewater in Cement Pastes and Mortars for Enhanced Physico-Mechanical and Microstructural Properties
Authors: Alrowais Raid , Shakeel Khalid , Bashir Muhammad Tariq , Sikandar Muhammad Ali , Khan Md. Munir Hayet , Ounais Wassef
Published: August 2024

This research explored the potential of marble wastewater (MWW) in cement paste and mortar production, addressing water scarcity, sustainable growth, and resource management. It investigated the physico-mechanical properties and microstructure of cement materials incorporated with varying amounts of MWW. In this study, we utilized tap water and MWW for mortar quality testing, focusing on parameters including setting times, water absorption, and mechanical strength. The viability of MWW in concrete formulations was confirmed by its acceptable total dissolved solids and alkalinity levels. A comprehensive experimental program determined that using marble wastewater in place of tap water reduced the quantity of water required for cement consistency and generated slightly higher compressive strengths (2, 3, 4, and 6%) after 28 days of curing. Analytical techniques, including Fourier-transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), energy-dispersive X-ray analysis, and X-ray diffraction (XRD), were employed for molecular and microstructural analyses, which revealed that MWW had a significant influence on portlandite development and CSH formation at higher replacement levels. In short, this research highlights the feasibility of using MWW in cement products, contributing to sustainable water resources, and industrial waste management and utilization.
Social Cluster and Heritage Memory: A Study on the Space Perception of Zhaozhou Basin Horse Caravan Vernacular Architecture
Authors: Chen Hongyu , Yang Yi , Zhao Difei , Zhang Lanxi , Tang Zhenjie , Tian Jinhuan , Shen Ting , Yin Yinghao
Published: August 2024

Located in Dali, Yunnan, the Zhaozhou basin is home to many precious architectural heritages, particularly the historical horse caravan architecture. These buildings face the challenge of renewal and transformation. It is of great significance to explore the local population’s awareness of the architectural heritage of the horse caravan in order to protect the architectural heritage and facilitate rural revitalization. This study reviews the related research on “space perception”, establishes a theoretical framework of space perception under the architectural dimension, and develops hypotheses. The social cluster of typical settlements in the Zhaozhou basin is selected as the research object, and empirical analyses are carried out using SPSS and AMOS software. An analytical framework model of empirical research is constructed to evaluate the space perception of the current social population. The results of the reliability and validity tests of the questionnaire show that the CR is greater than 0.7 and that the AVE is greater than 0.5. The value of the structural equation model fitting index χ2/df is 1.863, which is less than 3. The model test results show that research hypotheses H1–H5 are supported; that is, space perception has a significant positive impact on cognition and local identity, cognition has a significant positive impact on local identity and space function, and place identity has a significant positive impact on space appeal. This study demonstrates the relationship between space perception and the architectural remains of the horse caravan, and it analyzes the human psychological perception behind the material space. The findings support the need for further conservation of the horse caravan architecture. This study further deepens the theory of space perception and its application in the study of vernacular architecture, which can provide a research path for the protection and development of vernacular architectural heritage.
Sand Mining Tailings as Supplementary Cementitious Material
Authors: Figueiredo Aline Santana , Bezerra Augusto Cesar da Silva , Costa Laís Cristina Barbosa , Resende Douglas Mol , Kuster Luana Drago , Peixoto Ricardo André Fiorotti
Published: August 2024

Sand mining tailing (ST) is a byproduct of the sand extraction of submerged pits, a process which is carried out to obtain aggregates for civil construction. This tailing consists of fine particles from the pulp washing process, usually disposed of in decantation ponds. The present study proposes ST as a supplementary cementitious material (SCM) for Portland cement concrete, thereby reintegrating this tailing into the production chain. In this sense, ST was characterized, and concretes containing 2% to 14% of cement replacement (%vol) by ST were produced and evaluated. STs showed natural fineness, particles with angular morphology, a significant amount of kaolinite, and 36% amorphous content. ST concretes exhibited a compressive strength of up to 57.9 MPa at 28 days under 7.0% of cement replacement, 38.8% higher than the reference. Consequently, only 5.6 kg/m3 of Portland cement was required to attain 1.0 MPa, representing a 33.6% reduction compared to the reference. The ultrasonic pulse velocities measured in ST concrete with 2.0%, 4.0%, 7.0%, and 14.0% cement replacement were 3.0%, 6.1%, 9.3%, and 6.6% higher than the reference, respectively. These results indicate enhanced mechanical properties, improved matrix uniformity, and superior environmental performance across all SCM levels compared to the reference, with optimal efficiency observed at 7.0% ST content.
A Reliability-Based Design Approach for the Flexural Resistance of Compression Yielded Fibre-Reinforced Polymer (FRP)-Reinforced Concrete Beams
Authors: Ramamoorthy Dharinee , Guo Bingcheng , Kazmi Syed Minhaj Saleem , Wu Yufei
Published: August 2024

Fibre-reinforced polymer (FRP) reinforcement has been employed as an alternative to conventional steel reinforcement in concrete structures, which is attributed to its excellent strength and corrosion resistance. However, one drawback is that FRP reinforcements are brittle and affect the ductility of concrete structures. One of the recent effective techniques proposed to overcome ductility issues is the compression yielding (CY) concept. The CY mechanism allows the structure to fail differently than the conventional FRP-reinforced concrete structure. Thus, the existing design recommendations as per the current codes for FRP-reinforced concrete structures are not appropriate. Hence, reliability studies are crucial for the development of a functional CY beam design in order to emphasise the structure’s lifetime performance and to guarantee safety requirements. In this study, a reliability-based design approach is developed for a compression-yielded FRP-reinforced concrete beam (CY beam) using load and resistance factor design (LRFD). Firstly, the flexural failure modes of CY beams are discussed. The uncertainties involved in the development of the probabilistic model for the CY beam are defined. A case study is consequently conducted for a CY beam with random variables that are associated with the statistical characteristics of material properties and load. The reliability analysis method employed in this research is the Hasofer–Lind method. The results suggest the importance of choosing appropriate design variables and stochastic parameters for CY blocks that contribute to a higher level of reliability. The reliability index and resistance factors of a CY beam are then evaluated using the Monte Carlo Simulation computational method. The reliability index value of 3.336 is obtained from the simulation, which indicates that the CY beam demonstrates ductile behaviour. The results not only demonstrate ductile behaviour but also contribute to a possible reduction in material costs and a substantial safety margin. When compared to conventional FRP-reinforced concrete beams, for different load ratios, CY beams showed higher resistance and better reliability levels.
A Simplified Evaluation Framework for Adaptation Measures to Urban Heat Islands
Authors: Takebayashi Hideki
Published: August 2024

Adaptation measures to urban heat islands are classified into the following three categories: measures to reduce solar radiation incident on the human body, measures to control and cool ground and wall surface temperature, and measures to control and cool the air and human body temperature. Case studies are conducted to evaluate the effects of the implementation of a cool water circulation sunshade and to examine the adverse effects of cool pavements on the human thermal environment, in addition to the effects of mist sprays on the human body. The effect of the sunshade, watering road, and mist spray, which are typical adaptation measures to urban heat islands, on the human thermal environment was estimated using Wet Bulb Globe Temperature (WBGT) as an indicator for heat stroke prevention and Standard New Effective Temperature (SET*) as an indicator for thermal comfort assessment. The effect of solar radiation shielding on improving the human thermal environment was the most significant, with a large decrease in the amount of solar radiation absorbed by the human body, resulting in a large decrease in SET* and WBGT of 2.7 °C and 1.0 °C, respectively, on fine summer days.
Ultrasound Combination to Improve the Efficacy of Current Boron Neutron Capture Therapy for Head and Neck Cancer
Authors: Yura Yoshiaki , Fujita Yusei , Hamada Masakazu
Published: August 2024

Boron neutron capture therapy (BNCT) is radiotherapy in which a nuclear reaction between boron-10 (10B) in tumor cells and neutrons produces alpha particles and recoiling 7Li nuclei with an extremely short range, leading to the destruction of the tumor cells. Although the neutron source has traditionally been a nuclear reactor, accelerators to generate neutron beams have been developed and commercialized. Therefore, this treatment will become more widespread. Recurrent head and neck cancer (HNC) close to the body surface is considered a candidate for BNCT using the boron compound boronophenylalanine (BPA) and has been found to be highly responsive to this treatment. However, some cases recur early after the completion of the treatment, which needs to be addressed. Ultrasound is a highly safe diagnostic method. Ultrasound with microbubbles is expected to promote the uptake of BPA into tumor cells. Ultrasound also has the ability to improve the sensitivity of tumor cells to radiotherapy. In addition, high-intensity focused ultrasound may improve the efficacy of BNCT via its thermal and mechanical effects. This review is not systematic but outlines the current status of BPA-based BNCT and proposes plans to reduce the recurrence rate of HNC after BNCT in combination with ultrasound.
Effect of Abiotic Factors on Nectar Quality and Secretion of Two Early Spring Species, Galanthus nivalis L. and Helleborus niger L.
Authors: Malovrh Katja , Bavcon Jože , Križman Mitja , Ravnjak Blanka
Published: August 2024

Floral nectar is mainly a reward in the form of food for pollinators. In early spring, when snow can still be present, pollinators have trouble finding food. The composition and productivity of nectar in flowers play an important role in a pollinator’s life. It is known that low temperatures and lower humidity cause lower nectar secretion. Some studies have also shown that the quality of nectar can differ because of lower temperatures. In our research, we analysed whether abiotic factors affect nectar secretion, as well as the nectar composition of the early spring plant species Galanthus nivalis L. and Helleborus niger L. in February 2024. The study was conducted in two locations in nature. Nectar from H. niger was sampled in Tomišelj, Slovenia, whereas nectar from G. nivalis was sampled in Ljubljana, Slovenia. On four different days at three different times of day, we sampled nectar from flowers using microcapillaries. In total, we sampled 48 nectar samples from one species. We analysed soil humidity and temperature, air temperature and humidity, and UVB radiation. Our results show that nectar productivity is highest in the morning for both species. H. niger has sucrose-dominant nectar, while G. nivalis has hexose-dominant nectar. Proline, which is an important amino acid for bees, has the highest level in both species, as does the phenolic compound rutin. Environmental factors do affect nectar secretion. Soil and air temperature affect G. nivalis nectar secretion, while soil humidity affects H. niger nectar secretion. Soil and air temperature also have an effect on higher levels of sugars in both researched nectars. UVB, air humidity, and air and soil temperature seem to have an effect on phenolic compounds, but abiotic factors do not affect amino acids.
Prediction of Bone Marrow Metastases Using Computed Tomography (CT) Radiomics in Patients with Gastric Cancer: Uncovering Invisible Metastases
Authors: Park Jiwoo , Jung Minkyu , Kim Sang Kyum , Lee Young Han
Published: August 2024

We investigated whether radiomics of computed tomography (CT) image data enables the differentiation of bone metastases not visible on CT from unaffected bone, using pathologically confirmed bone metastasis as the reference standard, in patients with gastric cancer. In this retrospective study, 96 patients (mean age, 58.4 ± 13.3 years; range, 28–85 years) with pathologically confirmed bone metastasis in iliac bones were included. The dataset was categorized into three feature sets: (1) mean and standard deviation values of attenuation in the region of interest (ROI), (2) radiomic features extracted from the same ROI, and (3) combined features of (1) and (2). Five machine learning models were developed and evaluated using these feature sets, and their predictive performance was assessed. The predictive performance of the best-performing model in the test set (based on the area under the curve [AUC] value) was validated in the external validation group. A Random Forest classifier applied to the combined radiomics and attenuation dataset achieved the highest performance in predicting bone marrow metastasis in patients with gastric cancer (AUC, 0.96), outperforming models using only radiomics or attenuation datasets. Even in the pathology-positive CT-negative group, the model demonstrated the best performance (AUC, 0.93). The model’s performance was validated both internally and with an external validation cohort, consistently demonstrating excellent predictive accuracy. Radiomic features derived from CT images can serve as effective imaging biomarkers for predicting bone marrow metastasis in patients with gastric cancer. These findings indicate promising potential for their clinical utility in diagnosing and predicting bone marrow metastasis through routine evaluation of abdominopelvic CT images during follow-up.