bluuebunny/crossref_metadata_2025 huggingface dataset:
Real-Time Optimization of Heliostat Field Aiming Strategy via an Improved Swarm Intelligence Algorithm
Authors: Wang Yi’an , Wu Zhe , Ni Dong
Published: January 2024

Optimizing the heliostat field aiming strategy is crucial for maximizing thermal power production in solar power tower (SPT) plants while adhering to operational constraints. Although existing approaches can yield highly optimal solutions, their considerable computational cost makes them unsuitable for real-time optimization in large-scale scenes. This study introduces an efficient, intelligent, real-time optimization method based on a meta-heuristic algorithm to effectively and reliably manage SPT plant operations under varying solar conditions, such as cloud shadowing variations. To minimize redundant calculations, the real-time optimization problem is framed in a way that captures the operational continuity of the heliostat, which can be utilized to streamline the solution process. The proposed method is tested in a simulation environment that includes a heliostat field, cylindrical receiver, and cloud movement model. The results demonstrate that the algorithm presented in this paper offers higher intercept efficiency, improved robustness, and reduced optimization time in more complex scenes.
Enhancing Fingerprint Forensics: A Comprehensive Study of Gender Classification Based on Advanced Data-Centric AI Approaches and Multi-Database Analysis
Authors: Spanier Assaf B. , Steiner Dor , Sahalo Navon , Abecassis Yoel , Ziv Dan , Hefetz Ido , Kimchi Shimon
Published: January 2024

Fingerprint analysis has long been a cornerstone in criminal investigations for suspect identification. Beyond this conventional role, recent efforts have aimed to extract additional demographic information from fingerprints, such as gender, age, and nationality. While studies have demonstrated promising accuracy in gender classification based on fingerprints, practical implementation faces challenges, including the often low quality of crime scene fingerprints. This study presents a pioneering comparison of gender classification across diverse datasets, considering variations in fingerprint image quality. We examine the results from four databases, encompassing both public and private sources, employing state-of-the-art Data-Centric AI (DCAI) approaches for enhanced classification. Our findings reveal that a conservative Convolutional Neural Network (CNN)—specifically VGG—proves effective, achieving an accuracy ranging from 70% to 95% based on fingerprint quality. DCAI methods contribute a noteworthy 1–4% improvement. Notably, for partial or low-quality fingerprints, the periphery emerges as a critical determinant of gender classification. This study contributes insights into practical gender classification from fingerprints, emphasizing the significance of the fingerprint periphery. Furthermore, we provide the source code for future research and accessibility in real-world applications.
Life at the Landau Pole
Authors: Romatschke Paul
Published: January 2024

If a quantum field theory has a Landau pole, the theory is usually called ‘sick’ and dismissed as a candidate for an interacting UV-complete theory. In a recent study on the interacting 4d O(N) model at large N, it was shown that at the Landau pole, observables remain well-defined and finite. In this work, I investigate both relevant and irrelevant deformations of the said model at the Landau pole, finding that physical observables remain unaffected. Apparently, the Landau pole in this theory is benign. As a phenomenological application, I compare the O(N) model to QCD by identifying ΛMS¯ with the Landau pole in the O(N) model.
Dynamics of the Isotropic Star Differential System from the Mathematical and Physical Point of Views
Authors: Artés Joan-Carles , Llibre Jaume , Vulpe Nicolae
Published: January 2024

The following differential quadratic polynomial differential system  dxdt=y−x, dydt=2y−yγ−12−γy−5γ−4γ−1x, when the parameter γ∈(1,2] models the structure equations of an isotropic star having a linear barotropic equation of state, being x=m(r)/r where m(r)≥0 is the mass inside the sphere of radius r of the star, y=4πr2ρ where ρ is the density of the star, and t=ln(r/R) where R is the radius of the star. First, we classify all the topologically non-equivalent phase portraits in the Poincaré disc of these quadratic polynomial differential systems for all values of the parameter γ∈R∖{1}. Second, using the information of the different phase portraits obtained we classify the possible limit values of m(r)/r and 4πr2ρ of an isotropic star when r decreases.
A New Criterion for Improving Convergence of Fuzzy C-Means Clustering
Authors: Pérez-Ortega Joaquín , Moreno-Calderón Carlos Fernando , Roblero-Aguilar Sandra Silvia , Almanza-Ortega Nelva Nely , Frausto-Solís Juan , Pazos-Rangel Rodolfo , Rodríguez-Lelis José María
Published: January 2024

One of the most used algorithms to solve the fuzzy clustering problem is Fuzzy C-Means; however, one of its main limitations is its high computational complexity. It is known that the efficiency of an algorithm depends, among other factors, on the strategies for its initialization and convergence. In this research, a new convergence strategy is proposed, which is based on the difference of the objective function values, in two consecutive iterations, expressed as a percentage of its value in the next to the last one. Additionally, a new method is proposed to optimize the selection of values of the convergence or stop threshold of the algorithm, which is based on the Pareto principle. To validate our approach, a collection of real datasets was solved, and a significant reduction in the number of iterations was observed, without affecting significantly the solution quality. Based on the proposed method and the experiments carried out, we found it is convenient to use threshold values equal to 0.73 and 0.35 if a decrease in the number of iterations of approximately 75.2% and 64.56%, respectively, is wanted, at the expense of a reduction in solution quality of 2% and 1%, respectively. It is worth mentioning that, as the size of the datasets is increased, the proposed approach tends to obtain better results, and therefore, its use is suggested for datasets found in Big Data and Data Science.
Unveiling Sentiments: A Comprehensive Analysis of Arabic Hajj-Related Tweets from 2017–2022 Utilizing Advanced AI Models
Authors: Alghamdi Hanan M.
Published: January 2024

Sentiment analysis plays a crucial role in understanding public opinion and social media trends. It involves analyzing the emotional tone and polarity of a given text. When applied to Arabic text, this task becomes particularly challenging due to the language’s complex morphology, right-to-left script, and intricate nuances in expressing emotions. Social media has emerged as a powerful platform for individuals to express their sentiments, especially regarding religious and cultural events. Consequently, studying sentiment analysis in the context of Hajj has become a captivating subject. This research paper presents a comprehensive sentiment analysis of tweets discussing the annual Hajj pilgrimage over a six-year period. By employing a combination of machine learning and deep learning models, this study successfully conducted sentiment analysis on a sizable dataset consisting of Arabic tweets. The process involves pre-processing, feature extraction, and sentiment classification. The objective was to uncover the prevailing sentiments associated with Hajj over different years, before, during, and after each Hajj event. Importantly, the results presented in this study highlight that BERT, an advanced transformer-based model, outperformed other models in accurately classifying sentiment. This underscores its effectiveness in capturing the complexities inherent in Arabic text.
Advancing Barrett’s Esophagus Segmentation: A Deep-Learning Ensemble Approach with Data Augmentation and Model Collaboration
Authors: Lee Jiann-Der , Tsai Chih Mao
Published: January 2024

This approach provides a thorough investigation of Barrett’s esophagus segmentation using deep-learning methods. This study explores various U-Net model variants with different backbone architectures, focusing on how the choice of backbone influences segmentation accuracy. By employing rigorous data augmentation techniques and ensemble strategies, the goal is to achieve precise and robust segmentation results. Key findings include the superiority of DenseNet backbones, the importance of tailored data augmentation, and the adaptability of training U-Net models from scratch. Ensemble methods are shown to enhance segmentation accuracy, and a grid search is used to fine-tune ensemble weights. A comprehensive comparison with the popular Deeplabv3+ architecture emphasizes the role of dataset characteristics. Insights into training saturation help optimize resource utilization, and efficient ensembles consistently achieve high mean intersection over union (IoU) scores, approaching 0.94. This research marks a significant advancement in Barrett’s esophagus segmentation.
Simultaneous Dual-Wavelength Laser Irradiation against Implant-Adherent Biofilms of Staphylococcus aureus, Escherichia coli, and Candida albicans for Improved Antimicrobial Photodynamic Therapy
Authors: Afrasiabi Shima , Benedicenti Stefano , Signore Antonio , Arshad Mahnaz , Chiniforush Nasim
Published: January 2024

The efficiency of antimicrobial photodynamic therapy (PDT) might be improved by using multiple wavelengths. This study investigates the sensitivity of implant-adherent biofilms of Staphylococcus aureus, Escherichia coli, and Candida albicans to indocyanine green (ICG)-808 nm diode laser, toluidine blue O (TBO)-635 nm diode laser, and hydrogen peroxide (HP)-980 nm diode laser and their combination when irradiated with dual-wavelength laser irradiation (simultaneously 980–635 nm or 980–808 nm). After an incubation period of 72 h, the infected implants were randomly divided into seven different treatment modalities: Control, HP, HP-PDT, TBO-PDT, HP-TBO-PDT, ICG-PDT, and HP-ICG-PDT. After the treatments, the colony-forming units (CFUs)/mL and reactive oxygen species (ROS) generation were determined. All evaluated disinfection methods were significantly effective against the three investigated bacteria compared to the control. The combined treatment of HP-ICG-PDT or HP-TBO-PDT had the greatest antibacterial effect compared to each treatment alone. There were statistical differences between HP-ICG-PDT and ICG-PDT or HP-TBO-PDT and TBO-PDT for all three bacteria studied. PDT with simultaneous dual-wavelength laser irradiation is an efficient strategy to improve the therapeutic effect of PDT.
Automatic Osteoporosis Screening System Using Radiomics and Deep Learning from Low-Dose Chest CT Images
Authors: Tong Xiaoyu , Wang Shigeng , Zhang Jingyi , Fan Yong , Liu Yijun , Wei Wei
Published: January 2024

Objective: Develop two fully automatic osteoporosis screening systems using deep learning (DL) and radiomics (Rad) techniques based on low-dose chest CT (LDCT) images and evaluate their diagnostic effectiveness. Methods: In total, 434 patients who underwent LDCT and bone mineral density (BMD) examination were retrospectively enrolled and divided into the development set (n = 333) and temporal validation set (n = 101). An automatic thoracic vertebra cancellous bone (TVCB) segmentation model was developed. The Dice similarity coefficient (DSC) was used to evaluate the segmentation performance. Furthermore, the three-class Rad and DL models were developed to distinguish osteoporosis, osteopenia, and normal bone mass. The diagnostic performance of these models was evaluated using the receiver operating characteristic (ROC) curve and decision curve analysis (DCA). Results: The automatic segmentation model achieved excellent segmentation performance, with a mean DSC of 0.96 ± 0.02 in the temporal validation set. The Rad model was used to identify osteoporosis, osteopenia, and normal BMD in the temporal validation set, with respective area under the receiver operating characteristic curve (AUC) values of 0.943, 0.801, and 0.932. The DL model achieved higher AUC values of 0.983, 0.906, and 0.969 for the same categories in the same validation set. The Delong test affirmed that both models performed similarly in BMD assessment. However, the accuracy of the DL model is 81.2%, which is better than the 73.3% accuracy of the Rad model in the temporal validation set. Additionally, DCA indicated that the DL model provided a greater net benefit compared to the Rad model across the majority of the reasonable threshold probabilities Conclusions: The automated segmentation framework we developed can accurately segment cancellous bone on low-dose chest CT images. These predictive models, which are based on deep learning and radiomics, provided comparable diagnostic performance in automatic BMD assessment. Nevertheless, it is important to highlight that the DL model demonstrates higher accuracy and precision than the Rad model.
Regulation of Angiogenesis by Non-Coding RNAs in Cancer
Authors: Su Zhiyue , Li Wenshu , Lei Zhe , Hu Lin , Wang Shengjie , Guo Lingchuan
Published: January 2024

Non-coding RNAs, including microRNAs, long non-coding RNAs, and circular RNAs, have been identified as crucial regulators of various biological processes through epigenetic regulation, transcriptional regulation, and post-transcriptional regulation. Growing evidence suggests that dysregulation and activation of non-coding RNAs are closely associated with tumor angiogenesis, a process essential for tumor growth and metastasis and a major contributor to cancer-related mortality. Therefore, understanding the molecular mechanisms underlying tumor angiogenesis is of utmost importance. Numerous studies have documented the involvement of different types of non-coding RNAs in the regulation of angiogenesis. This review provides an overview of how non-coding RNAs regulate tumor angiogenesis. Additionally, we discuss emerging strategies that exploit non-coding RNAs for anti-angiogenic therapy in cancer treatment. Ultimately, this review underscores the crucial role played by non-coding RNAs in tumor angiogenesis and highlights their potential as therapeutic targets for anti-angiogenic interventions against cancer.
Predictive Modeling of Proteins Encoded by a Plant Virus Sheds a New Light on Their Structure and Inherent Multifunctionality
Authors: Roy Brandon G. , Choi Jiyeong , Fuchs Marc F.
Published: January 2024

Plant virus genomes encode proteins that are involved in replication, encapsidation, cell-to-cell, and long-distance movement, avoidance of host detection, counter-defense, and transmission from host to host, among other functions. Even though the multifunctionality of plant viral proteins is well documented, contemporary functional repertoires of individual proteins are incomplete. However, these can be enhanced by modeling tools. Here, predictive modeling of proteins encoded by the two genomic RNAs, i.e., RNA1 and RNA2, of grapevine fanleaf virus (GFLV) and their satellite RNAs by a suite of protein prediction software confirmed not only previously validated functions (suppressor of RNA silencing [VSR], viral genome-linked protein [VPg], protease [Pro], symptom determinant [Sd], homing protein [HP], movement protein [MP], coat protein [CP], and transmission determinant [Td]) and previously identified putative functions (helicase [Hel] and RNA-dependent RNA polymerase [Pol]), but also predicted novel functions with varying levels of confidence. These include a T3/T7-like RNA polymerase domain for protein 1AVSR, a short-chain reductase for protein 1BHel/VSR, a parathyroid hormone family domain for protein 1EPol/Sd, overlapping domains of unknown function and an ABC transporter domain for protein 2BMP, and DNA topoisomerase domains, transcription factor FBXO25 domain, or DNA Pol subunit cdc27 domain for the satellite RNA protein. Structural predictions for proteins 2AHP/Sd, 2BMP, and 3A? had low confidence, while predictions for proteins 1AVSR, 1BHel*/VSR, 1CVPg, 1DPro, 1EPol*/Sd, and 2CCP/Td retained higher confidence in at least one prediction. This research provided new insights into the structure and functions of GFLV proteins and their satellite protein. Future work is needed to validate these findings.
Comparative Feasibility and Environmental Life Cycle Assessment of Cotton Stalks Gasification and Pyrolysis
Authors: Vaskalis Ioannis , Zabaniotou Anastasia
Published: January 2024

In a circular economy, significant emphasis is given to the energetic valorization of agricultural byproducts. Cotton stalks are suitable as a feedstock for the production of bioenergy due to their high energy content. This study’s main focal areas are the economic viability and environmental implications of a system that can gasify or pyrolyze 25,500 tons of cotton stalk annually. To learn more about how gasification and pyrolysis affect the environment, a life cycle assessment (LCA) was conducted. This analysis evaluates the whole value chain and covers all stages of the cotton supply chain from cradle to gate, including production, harvest, transportation, and utilization. According to the findings, both systems exhibit economic viability, generating sizable profits and having quick payback times. However, despite its larger initial expenditure of EUR 2.74 million, the pyrolysis unit ends up being the better option because it has a payback period of 1.58 years, a return on investment (ROI) of 58% and a net present value (NPV) of EUR 21.5 million. Gasification is still an economically attractive alternative with a lower initial investment (EUR 1.81 million), despite having a lower ROI (36%) and NPV (EUR 10.52 million), as well as a longer payback period (2.41 years). However, the environmental implications of the gasification option are generally higher than those of pyrolysis. The impacts of gasification on fossil depletion (FDP) were estimated to be 5.7 million kg oil eq., compared to 5.3 million kg oil eq. for pyrolysis. Similarly, gasification resulted in 41.55 million kg U235 eq. and pyrolysis in 41.5 million kg U235 eq. related to impacts on ionizing radiation (IRP_HE). Other impact categories that emerge as the most important are freshwater eutrophication (FEP) and marine eutrophication (MEP).
A Closer Look at the Perivascular Unit in the Development of Enlarged Perivascular Spaces in Obesity, Metabolic Syndrome, and Type 2 Diabetes Mellitus
Authors: Hayden Melvin R.
Published: January 2024

The recently described perivascular unit (PVU) resides immediately adjacent to the true capillary neurovascular unit (NVU) in the postcapillary venule and contains the normal-benign perivascular spaces (PVS) and pathological enlarged perivascular spaces (EPVS). The PVS are important in that they have recently been identified to be the construct and the conduit responsible for the delivery of metabolic waste from the interstitial fluid to the ventricular cerebrospinal fluid for disposal into the systemic circulation, termed the glymphatic system. Importantly, the outermost boundary of the PVS is lined by protoplasmic perivascular astrocyte endfeet (pvACef) that communicate with regional neurons. As compared to the well-recognized and described neurovascular unit (NVU) and NVU coupling, the PVU is less well understood and remains an emerging concept. The primary focus of this narrative review is to compare the similarities and differences between these two units and discuss each of their structural and functional relationships and how they relate not only to brain homeostasis but also how they may relate to the development of multiple clinical neurological disease states and specifically how they may relate to obesity, metabolic syndrome, and type 2 diabetes mellitus. Additionally, the concept and importance of a perisynaptic astrocyte coupling to the neuronal synapses with pre- and postsynaptic neurons will also be considered as a perisynaptic unit to provide for the creation of the information transfer in the brain via synaptic transmission and brain homeostasis. Multiple electron microscopic images and illustrations will be utilized in order to help explain these complex units.
Artificial Hair Cell Sensor Based on Nanofiber-Reinforced Thin Metal Films
Authors: A. Moshizi Sajad , Pastras Christopher J. , Peng Shuhua , Wu Shuying , Asadnia Mohsen
Published: January 2024

Engineering artificial mechanosensory hair cells offers a promising avenue for developing diverse biosensors spanning applications from biomedicine to underwater sensing. Unfortunately, current artificial sensory hair cells do not have the ability to simultaneously achieve ultrahigh sensitivity with low-frequency threshold detection (e.g., 0.1 Hz). This work aimed to solve this gap by developing an artificial sensory hair cell inspired by the vestibular sensory apparatus, which has such functional capabilities. For device characterization and response testing, the sensory unit was inserted in a 3D printed lateral semicircular canal (LSCC) mimicking the environment of the labyrinth. The sensor was fabricated based on platinum (Pt) thin film which was reinforced by carbon nanofibers (CNFs). A Pi-shaped hair cell sensor was created as the sensing element which was tested under various conditions of simulated head motion. Results reveal the hair cell sensor displayed markedly higher sensitivity compared to other reported artificial hair cell sensors (e.g., 21.47 mV Hz−1 at 60°) and low frequency detection capability, 0.1 Hz < f < 1.5 Hz. Moreover, like the LSCC hair cells in biology, the fabricated sensor was most sensitive in a given plane of rotational motion, demonstrating features of directional sensitivity.
Design and Analysis of a Novel Bionic Tensegrity Robotic Fish with a Continuum Body
Authors: Chen Di , Wang Bo , Xiong Yan , Zhang Jie , Tong Ru , Meng Yan , Yu Junzhi
Published: January 2024

Biological fish exhibit remarkable adaptability and exceptional swimming performance through their powerful and flexible bodies. Therefore, designing a continuum flexible body is significantly important for the development of a robotic fish. However, it is still challenging to replicate these functions of a biological body due to the limitations of actuation and material. In this paper, based on a tensegrity structure, we propose a bionic design scheme for a continuum robotic fish body with a property of stiffness variation. Its detailed structures and actuation principles are also presented. A mathematical model was established to analyze the bending characteristics of the tensegrity structure, which demonstrates the feasibility of mimicking the fish-like oscillation propulsion. Additionally, the stiffness variation mechanism is also exhibited experimentally to validate the effectiveness of the designed tensegrity fish body. Finally, a novel bionic robotic fish design scheme is proposed, integrating an electronic module-equipped fish head, a tensegrity body, and a flexible tail with a caudal fin. Subsequently, a prototype was developed. Extensive experiments were conducted to explore how control parameters and stiffness variation influence swimming velocity and turning performance. The obtained results reveal that the oscillation amplitude, frequency, and stiffness variation of the tensegrity robotic fish play crucial roles in swimming motions. With the stiffness variation, the developed tensegrity robotic fish achieves a maximum swimming velocity of 295 mm/s (0.84 body length per second, BL/s). Moreover, the bionic tensegrity robotic fish also performs a steering motion with a minimum turning radius of 230 mm (0.68 BL) and an angular velocity of 46.6°/s. The conducted studies will shed light on the novel design of a continuum robotic fish equipped with stiffness variation mechanisms.
Bidirectional Relationship between Adolescent Gender Egalitarianism and Prosocial Behavior
Authors: Fu Xinyuan , Fu Ruoran , Chang Yanping , Yang Zhixu
Published: January 2024

This study investigates the bidirectional associations between gender egalitarianism and prosocial behavior in adolescents, and the moderating effect of gender in the associations, as well as gender differences and longitudinal changes in both. We recruited 543 Chinese adolescents (284 girls, 259 boys; mean age at Time 1 = 11.27 years) and collected three waves of data measuring gender egalitarianism and prosocial behavior at one-year intervals. According to the results, girls expressed greater gender egalitarianism than boys did; girls reported more prosocial behavior than boys in the sixth grade, but there were no significant gender differences in the seventh and eighth grades. Adolescents’ gender egalitarianism stayed stable from the sixth to the seventh grade then increased from the seventh to the eighth grade, and there was a decrease in prosocial behavior from the sixth to the seventh grade. More importantly, the results of the multi-group cross-lagged panel model revealed that adolescents’ gender egalitarianism in the previous year positively predicted prosocial behavior in the next year, and vice versa; such bidirectional associations equally applied to boys and girls. These findings add to the knowledge of adolescent gender egalitarianism and prosocial behavior, and the dynamic interplay between the two.
Optimizing Rural Pavements with SBS-Modified Asphalt Binders and Petroleum Resin
Authors: Kim Je-won , Kim Kyungnam , Le Tri Ho Minh
Published: January 2024

This study addresses the imperative for enhancing asphalt mixtures tailored for rural pavements, focusing on optimizing RAP mixtures with styrene–butadiene–styrene (SBS)-modified asphalt binders incorporating petroleum resin and oil. Through systematic investigation, the study examines the impact of varying RAP content (25% and 50%) and two SBS-modified asphalt binder types (Type 1 and Type 2) on mechanical properties and sustainability. Laboratory tests reveal that the mix of 25% RAP + 75% Type 1 exhibits exceptional flexibility, evidenced by a high ductility value of 880 mm at 25 °C, enhancing pavement resilience. Conversely, the 50% RAP + 50% Type 2 mixture displays vulnerability to fatigue cracking, while 25% RAP + 75% Type 1 demonstrates superior resistance, with a fatigue vulnerability value of 1524 kPa. The Hamburg Wheel Tracking test highlights the influence of RAP content on rut depth, with the mix of 50% RAP + 50% Type 1 achieving the lowest rutting at 3.9 mm. Overlay test results show the mix of 25% RAP + 75% Type 2’s resilience, with the lowest load reduction at 64.5%, while the mix of 50% RAP + 50% Type 1 exhibits substantial load reduction at 82.1%. Field tests unveil differences in pavement bearing capacities, with the mix of 25% RAP + 75% Type 2 demonstrating a remarkable elastic modulus of 58.5 MPa, indicating heightened bearing capacity. The investigation underscores the significant role of SBS-modified asphalt binders with incorporated petroleum resin and oil in enhancing fatigue resistance for sustainable rural pavements.
Configurational Path to Collaborative Innovation in Large and Complex Construction Projects
Authors: Chen Xiaoyan , Wang Ting , Liu Yan , Dou Zixin
Published: January 2024

Collaborative innovation contributes to sustainable development in many industries. Although there is a growing literature on collaborative innovation, it is still unclear whether and how configurations of drivers affect collaborative innovation in large and complex construction projects (hereafter megaprojects). This research adopts fuzzy-set qualitative comparative analysis (fsQCA) to explore multiple conjunctural causations of collaborative innovation in megaprojects. The findings show that four equifinal solutions can influence collaborative innovation in megaprojects, i.e.: “system innovation-oriented” (configuration 1), “radical innovation-oriented” (configuration 2), “second-tier supplier oriented” (configuration 3), and “modular or architectural innovation-oriented” (configuration 4). This study contributes to explaining the mechanisms regarding how configurations of drivers contribute to collaborative innovation in megaprojects. It also contributes to the development of collaborative innovation research in a construction project context. The research findings provide construction project managers with four useful suggestions for promoting collaborative innovation in megaprojects.
Seismic Performance of Steel Buildings with Eccentrically Braced Frame Systems with Different Configurations
Authors: Acosta Juan , Bojórquez Edén , Bojórquez Juan , Reyes-Salazar Alfredo , Ruiz-García Jorge , Ruiz Sonia E. , Iovinella Ivano
Published: January 2024

Although eccentrically braced frames (EBFs) can be used with different configurations according to architectural requirements, it has not yet been indicated which configuration has a better seismic performance; therefore, this paper presents an analytical study focused on evaluating the seismic behavior of various steel buildings with EBF systems, factoring in different configurations. Furthermore, the objective is to compare the performances of EBF systems with one another, to learn more about their structural efficiency. The results obtained indicate that seismic response, in terms of peak interstory drifts, depends on the structural period and hysteretic behavior of the links, because high levels of plastic rotation increase lateral displacement. In addition, it was observed that maximum drift demands are concentrated in the lower floors where the links exhibit inelastic behavior, while the level of interstory drift decreases as height increases.
Dewatering Characteristics and Drawdown Prediction of Suspended Waterproof Curtain Foundation Pit in Soft Soil Areas
Authors: Chu Yuhan , Shi Junfeng , Ye Zhaoyi , Liu Dingdan
Published: January 2024

Suspended waterproof curtains combined with pumping wells are the primary method for controlling groundwater levels in foundation pits within soft soil areas. However, there is still a lack of a systematic approach to predict the groundwater drawdown within the foundation pit caused by the influence of these suspended curtains. In order to investigate the variation of groundwater level within the excavation during dewatering processes, the finite difference method is employed to analyze the seepage characteristics of foundation pits with suspended waterproof curtains. Basing on the concept of equivalent well, this study examines the coupled effects of aquifer anisotropy (ki), aquifer thickness (Mi), well screen length (li), and the depth of waterproof curtain embedment on the seepage field distortion. A characteristic curve is established for standard conditions, which exposes the blocking effect of the curtain on the amount of groundwater drawdown in the pit. Additionally, correction coefficients are proposed for non-standard conditions, which, in turn, results in a prediction formula with a wider range of applicability. Comparative analysis between the calculated predictions and the field observation data from an actual foundation pit project in Zhuhai City validates the feasibility of the quantitative prediction method proposed in this research, which also provides a 21% safety margin.
Research on Leased Space of Urban Villages in Large Cities Based on Fuzzy Kano Model Evaluation and Building Performance Simulation: A Case Study of Laojuntang Village, Chaoyang District, Beijing
Authors: Wei Liuchao , Duan Wei , Dong Siqiao
Published: January 2024

China is in the transition period of urbanization, and the imbalance of land use generated during the original rapid development of megacities still exists, resulting in the preservation of a large number of urban villages in the peripheral areas of cities. Unlike formal housing, these villages are heavily influenced by the confrontation and interweaving between top-down policies of local governments and bottom-up spontaneous construction by local villagers, resulting in a diverse and complex status quo. At the same time, self-built housing in urban villages has become a gathering place for a large number of low-income migrants due to its relatively low rental prices. In terms of the research of urban villages on the current situation of housing, the real needs of users and housing performance are mostly subjective judgments and conclusions. Therefore, the entry point of this paper is the leased space and the leasers, taking Laojuntang Village in Chaoyang District of Beijing as the research object and analyzing its current problems and the real needs of users. This paper adopts an integrated approach of fuzzy Kano model evaluation and building performance simulation. After analyzing the data and discussing the influencing factors, this paper identifies the specific problems and user needs that exist in leased spaces in Laojuntang Village: (1) The architectural performance of leased space is a Must-be Quality, which is the bottom-line requirement and must be improved. (2) The quality of the basic facilities and equipment of the leased space is mostly a One-dimensional Quality, Attractive Quality, and the degree of importance is lower than that of the building performance. (3) The external activity facilities of the leased space are mostly undifferentiated needs, for which the local users are not particularly prominent. (4) The scale and plot ratio of local housing is relatively high, and users are dissatisfied and complaining, which falls under the category of Reverse Quality.
A Study on the Spatiotemporal Aggregation and Corridor Distribution Characteristics of Cultural Heritage: The Case of Fuzhou, China
Authors: Zhang Jiahao , Jiang Lan , Wang Xuqian , Chen Zhihong , Xu Subin
Published: January 2024

Fuzhou is an important city on the southeast coast of China with rich cultural heritage resources, and it is a national historical and cultural city in China. The main purposes of this study are the following: 1. To study the current situation and spatial distribution of cultural heritage; 2. To study the construction of cultural heritage corridors; 3. To utilize the holistic characteristics of heritage corridors to integrate the cultural heritage elements along the corridors and achieve the optimal allocation of resources. This study collects data from 605 cultural heritage sites in Fuzhou City and establishes a GIS database. The spatial distribution characteristics of cultural heritage in Fuzhou City are studied using aggregation analysis, nearest neighbor analysis, and buffer analysis in GIS technology. The following results were obtained: there is a cultural heritage corridor in Fuzhou City with the Minjiang River serving as the main land and water transportation line, and the closer one is to the water transportation line, the more intensive the distribution of cultural heritage points; and there are three cultural heritage node areas and one special cultural heritage node area. The study of Fuzhou’s heritage corridor system has important reference significance for the protection of cultural heritage in coastal historical cities in China and even in East Asia and has exploratory value for the holistic protection of cultural heritage and for the planning and development of tourism.
Numerical Simulation of Mechanical Characteristics and Safety Performance for Pre-Cracked Tunnel Lining with the Extended Finite Element Method
Authors: Lu Xin , Liu Yong , Hou Xiaolong , Chen Cai , Gao Ruidan
Published: January 2024

The service performance of tunnel lining is affected by crack properties and development states. In this paper, numerical simulation models were established to investigate the mechanics characteristics and safety performance for lining structures under different cracks based on the extended finite element method (XFEM). Analyze multiple quantitative factors in simulation, including changes in crack location, crack length, and crack distribution range in the lining structure. The axial force and bending moment of the preset cracks in the lining structures were first studied. The maximum safety factor attenuation rate (Dkmax) was proposed to analyze the impact of longitudinal and annular cracks on the safety performance. The axial force at the vault of the lining arch is the most significantly affected by the combined longitudinal cracks at multiple locations. When the length of a longitudinal crack increases from 1 m to 6 m, the axial force value at the crack point decreases by 33.77%, 36.15%, and 11.32%. However, the bending moment value increases by 4.47 times, 2.50 times, and 1.69 times. Under the influence of longitudinal cracks in an “arch crown + arch shoulder”, “arch crown + arch waist”, and “arch crown + arch shoulder + arch waist”, the axial force in the arch vault increased by 21.55%, decreased by 17.52%, and decreased by 13.45%. The distribution pattern of the bending moment under the influence of circumferential cracks shows convexity at the arch shoulder and arch foot, and concavity at the arch waist and side walls. The safety factor scatter curve with longitudinal cracks shows a gradual transition from a “W” shape to a “U” shape. The safety factor curve with circumferential cracks presents an approximately symmetrical wave-shaped distribution.
Modified (Spherical and Cylindrical) Permeation Diffusion Model Considering Deep Bed Filtration Effect
Authors: Song Liang , Li Jun , Zhang Rongtang , Qin Shipeng , Dong Yiqie , Wu Jie
Published: January 2024

The study of the slurry reinforcement mechanism is mainly focused on the interaction between slurry and soil. The seepage effect of the slurry always exists no matter what way the slurry interacts with the soil around the pile. In the process of slurry diffusion, the porosity of the soil, the permeability of the slurry, and the slurry pressure vary due to some cement particles being blocked by the soil particle skeleton. Therefore, the study of the slurry filtration effect is of great significance for predicting the permeation and diffusion law of slurry. In this paper, a macroscopic linear filtration model was introduced and the changes of slurry properties in the permeation diffusion process were considered. Firstly, a spherical (cylindrical) permeation diffusion model, which takes the linear filtration effect and the variation of slurry viscosity into account, was derived based on the conservation of mass. Furthermore, in order to more accurately reflect the influence of the filtration effect on the slurry permeation diffusion model, a polynomial nonlinear filtration model was proposed, and the numerical solution for the permeation diffusion model was derived using finite difference and finite element methods. Finally, the numerically simulated values, the measured values, and the values from the spherical permeation diffusion model that does not consider slurry viscosity variations were compared. The results indicate that the grout pressure is inconsistent with the measured value without considering the effect of the filtration. The initial grouting pressure calculated by the model in this paper is slightly larger, and the required grouting pressure over time is greater than that without considering the filtration effect, regardless of whether the grout diffuses in a spherical or cylindrical manner. The results of this study can contribute to a better understanding of grouting engineering and provide some theoretical guidance for actual grouting.
Community Governance in Age-Friendly Community Regeneration—A Case Study on Installing Elevators in Old Residential Buildings
Authors: Fang Kailun , Wu Yifei , Jiao Lu
Published: January 2024

The rise in aging world populations poses enormous concerns, among which is the critical topic of how to promote active aging by improving the health and well-being of the elderly. Accordingly, installing elevators in old residential buildings has become a main issue in age-friendly community regeneration to make it easier for the elderly to go outside. There is limited evidence on stakeholder involvement in age-friendly community regeneration. Some studies have overlooked the fact that fostering age-friendly communities in developing countries requires innovative governance for inclusive physical and social features despite the low awareness of citizen engagement. With reference to community governance as a structure and process, a theoretical framework is proposed to understand the practice of elevator installation in age-friendly community regeneration in Guangzhou, China. This study adopted the questionnaire survey method and collected 455 valid samples (150 valid samples with installed elevators; 305 valid samples did not install elevators). The findings led to the following conclusions: (1) shared common interests lead to effective community governance and smooth elevator installation; (2) some communities failed to install elevators due to opposition from people whose interests were hindered; and (3) it is important to set up self-governing organizations and find key people in community governance for interest-based negotiation. This paper’s contribution is that it makes up for the deficiency in the previous research that has neglected the elderly’s participation in public affairs via age-friendly community regeneration. Finally, this study suggests further research on the dynamic processes of different types of age-friendly community regeneration affairs.
Imaging Delay Following Liver-Directed Therapy Increases Progression Risk in Early- to Intermediate-Stage Hepatocellular Carcinoma
Authors: Stanneart Jordin , Nunez Kelley G. , Sandow Tyler , Gimenez Juan , Fort Daniel , Hibino Mina , Cohen Ari J. , Thevenot Paul T.
Published: January 2024

Hepatocellular carcinoma (HCC) remains one of the leading causes of cancer-related deaths in the world. Patients with early-stage HCC are treated with liver-directed therapies to bridge or downstage for liver transplantation (LT). In this study, the impact of HCC care delay on HCC progression among early-stage patients was investigated. Early-stage HCC patients undergoing their first cycle of liver-directed therapy (LDT) for bridge/downstaging to LT between 04/2016 and 04/2022 were retrospectively analyzed. Baseline variables were analyzed for risk of disease progression and time to progression (TTP). HCC care delay was determined by the number of rescheduled appointments related to HCC care. The study cohort consisted of 316 patients who received first-cycle LDT. The HCC care no-show rate was associated with TTP (p = 0.004), while the overall no-show rate was not (p = 0.242). The HCC care no-show rate and HCC care delay were further expanded as no-show rates and rescheduled appointments for imaging, laboratory, and office visits, respectively. More than 60% of patients experienced HCC care delay for imaging and laboratory appointments compared to just 8% for office visits. Multivariate analysis revealed that HCC-specific no-show rates and HCC care delay for imaging (p < 0.001) were both independently associated with TTP, highlighting the importance of minimizing delays in early-stage HCC imaging surveillance to reduce disease progression risk.
Evaluation of Three Imaging Methods to Quantify Key Events in Pelvic Bone Metastasis
Authors: Lee Haejun , Ahn Tae Ran , Hwang Kyung Hoon , Lee Sheen-Woo
Published: January 2024

Background: The purpose of this study is to compare turbo spin echo diffusion-weighted images in radial trajectory (BLADE DWI) with multi-shot echoplanar imaging (RESOLVE DWI) for imaging the metastatic lesion in the pelvic bone to find a correlation between ADC values and standardized uptake values (SUVs) of FDG uptake in PET/CT. The study also seeks to compare the values of metastatic lesions with those of benign bone lesions, specifically red marrow hyperplasia. Methods: The retrospective IRB-approved study included patients with bone metastasis and red marrow hyperplasia in the pelvic bone who underwent 3.0 T MRI with BLADE/RESOLVE DWI sequences and F-18 FDG PET/CT within one month. BVC (best value comparator) was used in determining the nature of bone lesions. Apparent diffusion coefficient (ADC) and standardized uptake value (SUV) were measured by a radiologist and a nuclear medicine physician. MRI image quality was graded with a Likert scale regarding the visualization of the sacroiliac joint, sacral neural foramen, hamstring tendon at ischial tuberosity, and tumor border. Signal-to-noise ratio (SNR) and imaging time were compared between the two DWIs. Mean, peak, and maximum SUVs between metastatic and benign red marrow lesions were compared. SUVs and ADC values were compared. AUROC analyses and cut-off values were obtained for each parameter. Mann–Whitney U, Spearman’s rho, and Kolmogorov–Smirnov tests were applied using SPSS. Results: The final study group included 58 bone lesions (19 patients (male: female = 6:13, age 52.5 ± 9.6, forty-four (75.9%) bone metastasis, fourteen (24.1%) benign red marrow hyperplasia). ADCs from BLADE and RESOLVE were significantly higher in bone metastasis than red marrow hyperplasia. BLADE showed higher ADC values, higher anatomical scores, and higher SNR than RESOLVE DWI (p < 0.05). Imaging times were longer for BLADE than RESOLVE (6 min 3 s vs. 3 min 47 s, p < 0.05). There was a poor correlation between ADC values and SUVs (correlation coefficient from 0.04 to 0.31). The AUROC values of BLADE and RESOLVE MRI ranged from 0.892~0.995. Those of PET ranged from 0.877~0.895. The cut-off ADC values between the bone metastasis and red marrow hyperplasia were 355.0, 686.5, 531.0 for BLADE min, max, and average, respectively, and 112.5, 737.0, 273.0 for RESOLVE min, max, and average, respectively. The cut-off SUV values were 1.84, 5.01, and 3.81 for mean, peak, and max values, respectively (p < 0.05). Conclusions: Compared with RESOLVE DWI, BLADE DWI showed improved image quality of pelvic bone MRI in the aspect of anatomical depiction and SNR, higher ADC values, albeit longer imaging time. BLADE and RESOLVE could differentiate bone metastasis and red marrow hyperplasia with quantifiable cut-off values. Further study is necessary to evaluate the discrepancy between the quantifiers between PET and MRI.
Identification of Skin Lesions by Snapshot Hyperspectral Imaging
Authors: Huang Hung-Yi , Nguyen Hong-Thai , Lin Teng-Li , Saenprasarn Penchun , Liu Ping-Hung , Wang Hsiang-Chen
Published: January 2024

This study pioneers the application of artificial intelligence (AI) and hyperspectral imaging (HSI) in the diagnosis of skin cancer lesions, particularly focusing on Mycosis fungoides (MF) and its differentiation from psoriasis (PsO) and atopic dermatitis (AD). By utilizing a comprehensive dataset of 1659 skin images, including cases of MF, PsO, AD, and normal skin, a novel multi-frame AI algorithm was used for computer-aided diagnosis. The automatic segmentation and classification of skin lesions were further explored using advanced techniques, such as U-Net Attention models and XGBoost algorithms, transforming images from the color space to the spectral domain. The potential of AI and HSI in dermatological diagnostics was underscored, offering a noninvasive, efficient, and accurate alternative to traditional methods. The findings are particularly crucial for early-stage invasive lesion detection in MF, showcasing the model’s robust performance in segmenting and classifying lesions and its superior predictive accuracy validated through k-fold cross-validation. The model attained its optimal performance with a k-fold cross-validation value of 7, achieving a sensitivity of 90.72%, a specificity of 96.76%, an F1-score of 90.08%, and an ROC-AUC of 0.9351. This study marks a substantial advancement in dermatological diagnostics, thereby contributing significantly to the early and precise identification of skin malignancies and inflammatory conditions.