bluuebunny/crossref_metadata_2025 huggingface dataset:
Applications and Prospects of Smooth Particle Hydrodynamics in Tunnel and Underground Engineering
Authors: Fan Rong , Chen Tielin , Li Man , Wang Shunyu
Published: September 2024

Smoothed particle hydrodynamics (SPH) is a state-of-the-art numerical simulation method in fluid mechanics. It is a novel approach for modeling and comprehending complex fluid behaviors. In contrast to traditional grid-dependent techniques like finite element and finite difference methods, SPH utilizes a meshless, purely Lagrangian approach, offering significant advantages in fluid simulations. By leveraging a set of arbitrarily distributed particles to represent the continuous fluid medium, SPH enables the precise estimation of partial differential equations. This grid-free methodology effectively addresses many challenges associated with conventional methods, providing a more adaptable and efficient solution framework. SPH’s versatility is evident across a broad spectrum of applications, ranging from advanced computational fluid dynamics (CFD) to complex computational solid mechanics (CSM), and proves effective across various scales—from micro to macro and even astronomical phenomena. Although SPH excels in tackling problems involving multiple degrees of freedom, complex boundaries, and large discontinuous deformations, it is still in its developmental phase and has not yet been widely adopted. As such, a thorough understanding and systematic analysis of SPH’s foundational theories are critical. This paper offers a comprehensive review of the defining characteristics and theoretical foundations of the SPH method, supported by practical examples derived from the Navier–Stokes (N-S) equations. It also provides a critical examination of successful SPH applications across various fields. Additionally, the paper presents case studies of SPH’s application in tunnel and underground engineering based on practical engineering experiences and long-term on-site monitoring, highlighting SPH’s alignment with real-world conditions. The theory and application of SPH have thus emerged as highly dynamic and rapidly evolving research areas. The detailed theoretical analysis and case studies presented in this paper offer valuable insights and practical guidance for scholars and practitioners alike.
Seismic Design and Ductility Evaluation of Thin-Walled Stiffened Steel Square Box Columns
Authors: Njiru Mwaura , Mamaghani Iraj H. P.
Published: September 2024

This paper investigates the seismic performance of thin-walled stiffened steel square box columns, modeling bridge piers subjected to unidirectional cyclic lateral loading with a constant axial load, focusing on local, global, and local-global interactive buckling phenomena. Initially, the finite element model was validated against existing experimental results. The study further explored the degradation in strength and ductility of both thin-walled and compact columns under cyclic loading. Thin-walled, stiffened steel square box columns exhibited buckling near the base, forming a half-sine wave shape. The research also addresses discrepancies from different material models used to analyze steel tubular bridge piers. Analysis using a modified two-surface plasticity model (2SM) yielded results closer to experimental data than a multi-linear kinematic hardening model, particularly for compact sections. The 2SM, which accounts for cycling within the yield plateau and strain hardening regime, demonstrated enhanced accuracy over the multi-linear kinematic hardening model. Additionally, a parametric study was conducted to assess the impact of key design parameters—such as width-to-thickness ratio (Rf), column slenderness ratio (λ), and magnitude of axial load (P/Py)—on the performance of thin-walled stiffened steel square box columns. Design equations were then developed to predict the strength and ductility of bridge piers. These equations closely matched experimental results, achieving an accuracy of 95% for ultimate strength and 97% for ductility.
People Detection Using Artificial Intelligence with Panchromatic Satellite Images
Authors: Golej Peter , Kukuliač Pavel , Horák Jiří , Orlíková Lucie , Partila Pavol
Published: September 2024

The detection of people in urban environments from satellite imagery can be employed in a variety of applications, such as urban planning, business management, crisis management, military operations, and security. A WorldView-3 satellite image of Prague was processed. Several variants of feature-extracting networks, referred to as backbone networks, were tested alongside the Faster R–CNN model. This model combines region proposal networks with object detection, offering a balance between speed and accuracy that is well suited for dense and varied urban environments. Data augmentation was used to increase the robustness of the models, which contributed to the improvement of classification results. Achieving a high level of accuracy is an ongoing challenge due to the low spatial resolution of available imagery. An F1 score of 54% was achieved using data augmentation, a 15 cm buffer, and a maximum distance limit of 60 cm.
Comprehensive Characterization and Metamorphic Control Analysis of Full Apertures in Different Coal Ranks within Deep Coal Seams
Authors: Li Qi , Wu Yong , Qiao Lei
Published: September 2024

The pore fracture structure of deep coal reservoirs is crucial for evaluating the potential of deep coalbed methane resources, conducting exploration and development, and controlling coal mine gas disasters. Mercury intrusion porosimetry, the liquid nitrogen method, and the low-temperature carbon dioxide adsorption method were used to study the full pore size structure and pore fractal characteristics of different coal grades in deep coal and comprehensively characterize the pore structure of kilometer-level coal mining. The sponge, Frenkel–Halsey–Hill (FHH), and density function models were applied to comprehensively analyze the pore complexity of coal, and the influence of metamorphic degree on pore size structure was evaluated. The distribution relationship of pore volume in different stages of coal samples was macropore→mesopore→micropore, and macropores had the best connectivity. Micropores and mesopores had the largest specific surface area, and the development of micropores and microcracks controlled the deep gas adsorption performance. The micropore volume and specific surface area both revealed a nonlinear decreasing trend with the increase in volatile matter, and coal metamorphism promoted the development of micropores. The pore volume and specific surface area of mesopores and macropores decreased first and then increased in a “U” shape with increasing volatile matter. In contrast, the fractal dimension D1 revealed an inverted U shape with increasing volatile matter, followed by a decrease. The D2 value decreased nonlinearly with increasing volatile matter, whereas the D3 value increased nonlinearly with increasing volatile matter. The degree of metamorphism increased, and the microporous structure became more regular.
Influence of Dentin Sealing Technique on the Shear Bond Strength between Lithium Disilicate Ceramics and Try-In-Paste-Contaminated Dentin
Authors: Ciftci Gozde , Ekren Orhun , Soygun Koray , Ciftci Volkan
Published: September 2024

This study aimed to evaluate the effect of try-in paste contamination on the bond strength of lithium disilicate glass–ceramic to dentin treated with immediate (IDS) or delayed (DDS) dentin sealing techniques. Occlusal halves of 33 molars were decapitated and divided into three groups (n = 10). Lithium disilicate discs (3 × 5 mm) were prepared. For Group A, the provisional crown was applied over dentin and was soaked in distilled water. Lithium disilicate discs were cemented following dentin conditioning with a three-step etch and rinse adhesive. In Group B (IDS), the three-step adhesive was applied to dentin. The dentin surfaces were conditioned only in the final cementation for Group C (DDS). The intaglio surfaces of test groups were contaminated with try-in paste. All specimens were thermally cycled 3000 times at 5–55 °C and were subjected to shear tests. An additional three specimens for each group were contaminated with try-in paste and subjected to the same surface cleaning as the test specimens were examined with SEM/EDS. The adhesive surfaces were also examined with SEM/EDS for try-in paste remnants. Group C showed a significant decrease in bond strength values compared to Group B and Group A (5.84 ±1.4 MPa, 11.45 ±2.4 MPa, and 10.29 ±2.5 MPa, respectively). No statistically significant difference was detected between Group B and Group A (p ≥ 0.05). The SEM-EDS analyses revealed obstructions of the dentinal tubules in the try-in-paste-contaminated specimens. Immediate dentin sealing application enhanced the bonding strength of lithium disilicate to the try-in-paste-contaminated dentin. Try-in paste contamination over dentin negatively influenced the bonding process.
Fatigue Characteristics Analysis of Carbon Fiber Laminates with Multiple Initial Cracks
Authors: Liu Zheng , Zhang Yuhao , Liu Haodong , Liu Xin , Liang Jinlong , Shao Zhenjiang
Published: September 2024

In the entire wind turbine system, the blade acts as the central load-bearing element, with its stability and reliability being essential for the safe and effective operation of the wind power unit. Carbon fiber, known for its high strength-to-weight ratio, high modulus, and lightweight characteristics, is extensively utilized in blade manufacturing due to its superior attributes. Despite these advantages, carbon fiber composites are frequently subjected to cyclic loading, which often results in fatigue issues. The presence of internal manufacturing defects further intensifies these fatigue challenges. Considering this, the current study focuses on carbon fiber composites with multiple pre-existing cracks, conducting both static and fatigue experiments by varying the crack length, the angle between cracks, and the distance among them to understand their influence on the fatigue life under various conditions. Furthermore, this study leverages the advantages of Paris theory combined with the Extended Finite Element Method (XFEM) to simulate cracks of arbitrary shapes, introducing a fatigue simulation method for carbon fiber composite laminates with multiple cracks to analyze their fatigue characteristics. Concurrently, the Particle Swarm Optimization (PSO) algorithm is employed to determine the optimal weight configuration, and the Backpropagation neural network (BP) is used to train and adjust the weights and thresholds to minimize network errors. Building on this foundation, a surrogate model for predicting the fatigue life of carbon fiber composite laminates with multiple cracks under conditions of physical parameter uncertainty has been constructed, achieving modeling and assessment of fatigue reliability. This research offers theoretical insights and methodological guidance for the utilization of carbon fiber-reinforced composites in wind turbine blade applications.
Depth-Optimized Quantum Circuit of Gauss–Jordan Elimination
Authors: Jang Kyungbae , Oh Yujin , Seo Hwajeong
Published: September 2024

Quantum computers have the capacity to solve certain complex problems more efficiently than classical computers. To fully leverage these quantum advantages, adapting classical arithmetic for quantum systems in a circuit level is essential. In this paper, we introduce a depth-optimized quantum circuit of Gauss–Jordan elimination for matrices in binary. This quantum circuit is a crucial module for accelerating Information Set Decoding (ISD) using Grover’s algorithm. ISD is a cryptographic technique used in analyzing code-based cryptographic algorithms. When combined with Grover’s search, it achieves a square root reduction in complexity. The proposed method emphasizes the potential for parallelization in the quantum circuit implementation of Gauss–Jordan elimination. We allocate additional ancilla qubits to enable parallel operations within the target matrix and further reuse these ancilla qubits to minimize overhead from our additional allocation. The proposed quantum circuit for Gauss–Jordan elimination achieves the lowest Toffoli depth compared to the-state-of-art previous works.
Effects of Organic Acid Coagulants on the Textural and Physical–Chemical Properties of Tofu
Authors: Paz-Yépez Carolina , Gavilanes-Tomalá Mariana , Palmay-Paredes Julio , Medina-Galarza Grace , Guerrero-Luzuriaga Sebastián , Velázquez Martí Borja
Published: September 2024

Tofu is obtained by heating soymilk, to which a coagulant, such as calcium sulfate or magnesium chloride, is added to make it curdle. This study aimed to parameterize the effects of the following three alternative organic coagulant types: apple, rice, and white vinegars, used in different proportions. Six treatments were established with three concentrations (1%, 3%, and 5%), evaluating the coagulation time and curd yield. The treatments with the lowest coagulation time were analyzed for texture by TPA, color through the CIEL*a*b scale, protein content, and moisture. The results showed that the rice vinegar + 3% white vinegar (T6C3) treatment showed the lowest coagulation time (0.78 min). The 5% apple vinegar (T1C5) treatment provided the highest curd yield, averaging 23.73%. This treatment’s protein and moisture contents were 3.93% protein and 69.73% moisture, confirming that better texture characteristics are recorded in tofu at lower pH values. The TPA results showed that using apple and rice vinegars as coagulants provided a challenging, less cohesive, more adhesive, and less elastic tofu. White vinegar provided a soft, more cohesive, less adhesive, and more elastic tofu. In the color analysis, it was observed that tofu coagulated with apple vinegar showed a tendency toward a yellow color, and tofu coagulated with rice and white vinegars showed a tendency toward a white color. These findings parameterize the effects of using each type of vinegar as a coagulant. These organic coagulants provide faster coagulation times and desirable texture characteristics, thus offering a practical alternative to traditional coagulants in tofu manufacturing.
Simultaneous Determination of Glyphosate and 13 Multiclass Pesticides in Agricultural Soil by Direct-Immersion SPME Followed by Solid–Liquid Extraction
Authors: Brinco João , Guedes Paula , da Silva Marco Gomes , Mateus Eduardo P. , Ribeiro Alexandra B.
Published: September 2024

A new method is presented for the simultaneous determination of 13 multiclass pesticides along with glyphosate. The multiclass pesticides were extracted by creating a soil slurry with 2% ethanol in water (v/v), and then, applying direct-immersion solid-phase microextraction (DI-SPME) with a new type of semi-disposable SPME fiber configuration called LC-Tips. The fibers were then retroextracted to ethanol, and aqueous ammonia was added to the slurry to extract glyphosate. Derivatization of the glyphosate extract was accomplished with a mixture of trifluoroacetic anhydride and trifluoroethanol, after which the reaction mixture was dried and resuspended with the SPME ethanol extract. To this, a mixture of analyte protectants was added, and it was analyzed by GC-MS/MS in multiple-reaction-monitoring mode. All analytes showed a coefficient of determination greater than 0.95 in the 0.1–100 µg/kg calibrated range, and the limits of detection were between 0.1 and 1 µg/kg, except for glyphosate, which was 0.01 µg/kg. The method shows relatively high replicate relative standard deviation (as much as 37% for five extractions at 20 µg/kg), but the isotopically labeled internal standard was effective at mitigating this effect for some analytes.
Application of PolyJet 3D Printing in Production of Flexographic Printing Plates
Authors: Izdebska-Podsiadły Joanna , Lasecki Adam
Published: September 2024

The aim of this study was to investigate whether PolyJet technology, which uses rubber-like materials for printing and is known for its high resolution and performance, could be suitable for producing flexographic printing plates. In our research, we designed test plates that were printed using PolyJet technology with TangoBlackPlus FLX9870-DM resin. These 3D-printed plates were evaluated for their resistance to various flexographic inks and solvents, and their contact angles were measured. Subsequently, the prints were made on a Flexiproof device using water-based ink with both the test plates and traditional photopolymer plates across six different substrates. The print quality was assessed using densitometry and spectrophotometry. Our findings indicate that the 3D-printed plates are suitable for printing solid areas and lines with water-based inks. However, the print quality of the 3D-printed plates is slightly lower than that of the photopolymer plates, with the optical density values for the high-quality prints on coated papers being approximately 10% lower. Additionally, the plates printed with TangoBlack Plus resin appear to be suitable for UV inks due to their high resistance, but they are not resistant to the solvents used in solvent-based inks.
Research on the Cable-to-Terminal Connection Recognition Based on the YOLOv8-Pose Estimation Model
Authors: Qu Xu , Long Yanping , Wang Xing , Hu Ge , Tao Xiongfei
Published: September 2024

Substations, as critical nodes for power transmission and distribution, play a pivotal role in ensuring the stability and security of the entire power grid. With the ever-increasing demand for electricity and the growing complexity of grid structures, traditional manual inspection methods for substations can no longer meet the requirements for efficient and safe operation and maintenance. The advent of automated inspection systems has brought revolutionary changes to the power industry. These systems utilize advanced sensor technology, image processing techniques, and artificial intelligence algorithms to achieve real-time monitoring and fault diagnosis of substation equipment. Among these, the recognition of cable-to-terminal connection relationships is a key task for automated inspection systems, and its accuracy directly impacts the system’s diagnostic capabilities and fault prevention levels. However, traditional methods face numerous limitations when dealing with complex power environments, such as inadequate recognition performance under conditions of significant perspective angles and geometric distortions. This paper proposes a cable-to-terminal connection relationship recognition method based on the YOLOv8-pose model. The YOLOv8-pose model combines object detection and pose estimation techniques, significantly improving detection accuracy and real-time performance in environments with small targets and dense occlusions through optimized feature extraction algorithms and enhanced receptive fields. The model achieves an average inference time of 74 milliseconds on the test set, with an accuracy of 92.8%, a recall rate of 91.5%, and an average precision mean of 90.2%. Experimental results demonstrate that the YOLOv8-pose model performs excellently under different angles and complex backgrounds, accurately identifying the connection relationships between terminals and cables, providing reliable technical support for automated substation inspection systems. This research offers an innovative solution for automated substation inspection systems, with significant application prospects.
Research on Automatic Recharging Technology for Automated Guided Vehicles Based on Multi-Sensor Fusion
Authors: Xue Yuquan , Wang Liming , Li Longmei
Published: September 2024

Automated guided vehicles (AGVs) play a critical role in indoor environments, where battery endurance and reliable recharging are essential. This study proposes a multi-sensor fusion approach that integrates LiDAR, depth cameras, and infrared sensors to address challenges in autonomous navigation and automatic recharging. The proposed system overcomes the limitations of LiDAR’s blind spots in near-field detection and the restricted range of vision-based navigation. By combining LiDAR for precise long-distance measurements, depth cameras for enhanced close-range visual positioning, and infrared sensors for accurate docking, the AGV’s ability to locate and autonomously connect to charging stations is significantly improved. Experimental results show a 25% increase in docking success rate (from 70% with LiDAR-only to 95%) and a 70% decrease in docking error (from 10 cm to 3 cm). These improvements demonstrate the effectiveness of the proposed sensor fusion method, ensuring more reliable, efficient, and precise operations for AGVs in complex indoor environments.
Plant-Derived Flavonoids as AMPK Activators: Unveiling Their Potential in Type 2 Diabetes Management through Mechanistic Insights, Docking Studies, and Pharmacokinetics
Authors: Moon Dong Oh
Published: September 2024

Type 2 diabetes mellitus (T2DM) remains a significant global health issue, marked by insulin resistance and disrupted glucose metabolism. AMP-activated protein kinase (AMPK) serves as a key regulator of cellular energy balance, playing a crucial role in enhancing insulin sensitivity, promoting glucose uptake, and reducing glucose production in the liver. Recently, there has been growing interest in plant-derived flavonoids as natural activators of AMPK, offering a promising complementary approach to conventional diabetes treatments. This review delves into ten flavonoids identified as AMPK activators, including baicalein, dihydromyricetin, bavachin, 7-O-MA, derrone, and alpinumisoflavone. Their activation mechanisms are explored, which include both direct binding to the AMPK complex and indirect pathways involving upstream signaling. Through molecular docking studies, the binding affinities and interaction profiles of these flavonoids with AMPK are assessed, revealing varying levels of activation potential. Notably, baicalein and dihydromyricetin showed strong binding to the α1 subunit of AMPK, indicating high potential for robust activation. Additionally, this review provides a thorough analysis of the pharmacokinetic properties and drug-likeness of these flavonoids using the SwissADME tool, focusing on aspects such as ADME (Absorption, Distribution, Metabolism, and Excretion). While the overall profiles of these compounds are promising, issues like solubility and possible drug–drug interactions are areas that need further refinement. In summary, plant-derived flavonoids emerge as a promising avenue for developing new natural therapies for T2DM. Moving forward, research should aim at optimizing these compounds for clinical application, elucidating their specific mechanisms of AMPK activation, and confirming their efficacy in T2DM treatment. This review highlights the potential of flavonoids as safer and more holistic alternatives or adjuncts to current diabetes therapies.
Automatic Optimal Robotic Base Placement for Collaborative Industrial Robotic Car Painting
Authors: Zbiss Khalil , Kacem Amal , Santillo Mario , Mohammadi Alireza
Published: September 2024

This paper investigates the problem of optimal base placement in collaborative robotic car painting. The objective of this problem is to find the optimal fixed base positions of a collection of given articulated robotic arms on the factory floor/ceiling such that the possibility of vehicle paint coverage is maximized while the possibility of robot collision avoidance is minimized. Leveraging the inherent two-dimensional geometric features of robotic car painting, we construct two types of cost functions that formally capture the notions of paint coverage maximization and collision avoidance minimization. Using these cost functions, we formulate a multi-objective optimization problem, which can be readily solved using any standard multi-objective optimizer. Our resulting optimal base placement algorithm decouples base placement from motion/trajectory planning. In particular, our computationally efficient algorithm does not require any information from motion/trajectory planners a priori or during base placement computations. Rather, it offers a hierarchical solution in the sense that its generated results can be utilized within already available robotic painting motion/trajectory planners. Our proposed solution’s effectiveness is demonstrated through simulation results of multiple industrial robotic arms collaboratively painting a Ford F-150 truck.
Designing a Novel THz Band 2-D Wide-Angle Scanning Phased-Array Antenna Based on a Decoupling Surface
Authors: Xiong Bao , Xie Wenxuan , Zhu Yongzhong
Published: September 2024

This paper proposes a novel THz band 2-D wide-angle scanning phased-array antenna (PAA) based on a decoupling surface. The simulated S11 bandwidth under periodic boundary conditions is 106–119 GHz, with stable gain within the bandwidth. The designed decoupling surface effectively reduces the coupling between elements, and the simulated active VSWR performance and ground surface current distribution under periodic boundary conditions confirm this. An 8 × 8 (64-element) planar PAA is modeled and simulated in CST2022 to verify the beam-scanning performance of the PAA. According to the simulation results, a 2-D wide-angle scanning of ±48° is achieved in the 106–114 GHz range, while in the 115–119 GHz range, a wide-angle scanning of ±48° is achieved on the E-plane, and the beam-scanning range on the H-plane reaches ±40°. Moreover, the normal peak gain is stably maintained at 21.9–22.8 dBi, with a normalized radiation efficiency as high as 95%, and the scanning radiation efficiency is higher than 81%. Due to its stable gain and 2-D wide-angle scanning performance, the proposed PAA has a broad application prospect in terahertz wireless communication equipment.
Exploration of the Characteristics of Elderly-Driver-Involved Single-Vehicle Hit-Fixed-Object Crashes in Pennsylvania, USA
Authors: Hou Xuerui , Zhang Zihao , Su Xue , Liu Chenhui
Published: September 2024

With the acceleration of population aging, the elderly driving safety issue is increasingly prominent. Method: With the crash data of Pennsylvania from 2010 to 2019, this study exclusively discusses features of single-vehicle hit-fixed-object crashes (SVHFOCs), one of the most common and deadliest crash types for elderly drivers. Results: Firstly, we demonstrate that elderly drivers are much more likely to be injured and killed than young drivers in SVHFOCs by checking crash consequences. The descriptive analysis indicates that elderly drivers have very different crash features from young drivers. They are found to drive with more caution in many aspects, such as more low-speed local travels, fewer illegal behaviors, fewer nighttime travels, etc. Then, a logistic regression model is built to find the factors significantly influencing the severity of SVHFOCs from driver, vehicle, roadway, and environment. The estimation results indicate that female sex, not wearing a seatbelt, DUI, rural area, and SUV involvement tend to be associated with more severe SVHFOCs. Additionally, illumination, weather, and road type could also significantly affect crash severity. Especially, SVHFOCs in adverse weather, in dark conditions, and at intersections are found to be less severe, which implies that elderly drivers might drive more carefully in complex environments. Practical Applications: These findings are expected to provide new insights for agencies in formulating customized measures to prevent elderly drivers from being involved in SVHFOCs.
Preprocessing for Multi-Dimensional Enhancement and Reconstruction in Neural Video Compression
Authors: Wang Jiajia , Zhang Qi , Zhao Haiwu , Wang Guozhong , Shang Xiwu
Published: September 2024

The surge in ultra-high-definition video content has intensified the demand for advanced video compression techniques. Video encoding preprocessing can improve coding efficiency while ensuring a high degree of compatibility with existing codecs. Existing video encoding preprocessing methods are limited in their ability to fully exploit redundant features in video data and recover high-frequency details, and their network architectures often lack compatibility with neural video encoders. To addressing these challenges, we propose a Multi-Dimensional Enhancement and Reconstruction (MDER) preprocessing method to improve the efficiency of deep learning-based neural video encoders. Firstly, our approach integrates a degradation compensation module to mitigate encoding noise and boost feature extraction efficiency. Secondly, a lightweight fully convolutional neural network is employed, which utilizes residual learning and knowledge distillation to refine and suppress irrelevant features across spatial and channel dimensions. Furthermore, to maximize the use of redundant information, we incorporate Dense Blocks, which can enhance and reconstruct important features in the video data during preprocessing. Finally, the preprocessed frames are then mapped from pixel space to feature space through the Dense Feature-Enhanced Video Compression (DFVC) module, which improves motion estimation and compensation accuracy. The experimental results demonstrate that, compared to neural video encoders, the MDER method can reduce bits per pixel (Bpp) by 0.0714 and 0.0536 under equivalent PSNR and MS-SSIM conditions, respectively. These results demonstrate significant improvements in compression efficiency and reconstruction quality, highlighting the effectiveness of the MDER preprocessing method and its compatibility with neural video codec workflows.
Application of a Quantitative Risk-Based Decision Tool for Local Railway Level Crossing Management
Authors: Di Graziano Alessandro , Marchetta Vincenzo
Published: September 2024

Railway level crossings pose risks to both train passengers and road users, worsened by the complex interaction between rail and road traffic, particularly on local railways. This study introduces a Risk Management (RM) framework designed to enhance safety at level crossings on local railways by providing a decision-support tool. By individually assessing risk factors, the framework allows for a precise evaluation of the current risk levels in terms of both Cumulated and Individual Risk levels, Individual Risk, and the impacts of potential modifications. The framework allows the quantitative assessment of risk and resource optimization, enabling infrastructure managers to identify high-risk crossings and select the most effective safety interventions. The framework was applied to 96 level crossings on an Italian local railway line, demonstrating its ability to support decision-making for targeted interventions as well as broader network-level actions, significantly improving system safety.
Calibrating and Visualizing Some Bootstrap Confidence Regions
Authors: Welagedara Welagedara Arachchilage Dhanushka M. , Olive David J.
Published: September 2024

When the bootstrap sample size is moderate, bootstrap confidence regions tend to have undercoverage. Improving the coverage is known as calibrating the confidence region. Consider testing H0:θ=θ0 versus H1:θ≠θ0. We reject H0 only if θ0 is not contained in a large-sample 95% confidence region. If the confidence region has 3% undercoverage for the data set sample size, then the type I error is 8% instead of the nominal 5%. Hence, calibrating confidence regions is also useful for testing hypotheses. Several bootstrap confidence regions are also prediction regions for a future value of a bootstrap statistic. A new bootstrap confidence region uses a simple prediction region calibration technique to improve the coverage. The DD plot for visualizing prediction regions can also be used to visualize some bootstrap confidence regions.
Oxidative Stress Markers and Na,K-ATPase Enzyme Kinetics Are Altered in the Cerebellum of Zucker Diabetic Fatty fa/fa Rats: A Comparison with Lean fa/+ and Wistar Rats
Authors: Radosinska Dominika , Gaal Kovalcikova Alexandra , Gardlik Roman , Chomova Maria , Snurikova Denisa , Radosinska Jana , Vrbjar Norbert
Published: September 2024

Type 2 diabetes mellitus has been referred to as being closely related to oxidative stress, which may affect brain functions and brain glucose metabolism due to its high metabolic activity and lipid-rich content. Na,K-ATPase is an essential enzyme maintaining intracellular homeostasis, with properties that can sensitively mirror various pathophysiological conditions such as diabetes. The goal of this study was to determine oxidative stress markers as well as Na,K-ATPase activities in the cerebellum of Zucker diabetic fatty (ZDF) rats depending on diabetes severity. The following groups of male rats were used: Wistar, ZDF Lean (fa/+), and ZDF (fa/fa) rats, arbitrarily divided according to glycemia into ZDF obese (ZO, less severe diabetes) and ZDF diabetic (ZOD, advanced diabetes) groups. In addition to basic biometry and biochemistry, oxidative stress markers were assessed in plasma and cerebellar tissues. The Na, K-ATPase enzyme activity was measured at varying ATP substrate concentrations. The results indicate significant differences in basic biometric and biochemical parameters within all the studied groups. Furthermore, oxidative damage was greater in the cerebellum of both ZDF (fa/fa) groups compared with the controls. Interestingly, Na,K-ATPase enzyme activity was highest to lowest in the following order: ZOD > ZO > Wistar > ZDF lean rats. In conclusion, an increase in systemic oxidative stress resulting from diabetic conditions has a significant impact on the cerebellar tissue independently of diabetes severity. The increased cerebellar Na,K-ATPase activity may reflect compensatory mechanisms in aged ZDF (fa/fa) animals, rather than indicating cerebellar neurodegeneration: a phenomenon that warrants further investigation.
Beneficial Effects of Tyrosol and Oleocanthal from Extra Virgin Olive Oil on Liver Health: Insights into Their Mechanisms of Action
Authors: Gabbia Daniela
Published: September 2024

The Mediterranean diet and consumption of EVOO are associated with multiple beneficial effects for human health, e.g. reduction in cardiovascular risk and mortality, improvement in the lipid profile, and the prevention of chronic diseases, such as cancers and neurodegenerative diseases. In EVOO, more than 30 different phenolic-derived compounds have been identified, representing one of the most promising bioactive classes in olive oil. This review explores the hepatoprotective properties of two of these compounds, tyrosol and oleocanthal, focusing on their mechanisms of action. Recent studies have shown that these compounds, which share a similar chemical structure with a hydroxyl group attached to an aromatic hydrocarbon ring, can potentially mitigate chronic liver diseases, such as MASLD and liver fibrosis, as well as their progression to liver cancer. Consequently, they deserve attention for future pharmacological drug development. In vitro and in vivo studies have suggested that these compounds exert these effects through the regulation of cellular pathways involved in antioxidant response, lipid metabolism, transcription factor activity, and NF-κB signaling. Understanding the mechanisms underlying the hepatoprotective properties of tyrosol and oleocanthal may provide valuable information for the development of therapeutic agents based on their chemical structures capable of targeting chronic liver diseases.
Somatostatin Receptor Type 2 as a Potential Marker of Local Myocardial Inflammation in Myocardial Infarction: Morphologic Data on Distribution in Infarcted and Normal Human Myocardium
Authors: Ryabov Vyacheslav V. , Trusov Andrey A. , Kercheva Maria A. , Gombozhapova Aleksandra E. , Ilyushenkova Julia N. , Stepanov Ivan V. , Fadeev Mikhail V. , Syrkina Anna G. , Sazonova Svetlana I.
Published: September 2024

Nuclear imaging modalities can detect somatostatin receptor type 2 (SSTR2) in vivo as a potential marker of local post-MI inflammation. SSTR2+ macrophages are thought to be the main substrate for SSTR-targeted radioimaging. However, the distribution of SSTR2+ cells in the MI patients’ myocardium is unknown. Using immunohistochemistry, we investigated the distribution of SSTR2+ cells in the myocardium of patients who died during the MI inflammatory phase (n = 7) compared to the control group of individuals with fatal trauma (n = 3). Inflammatory cellular landscapes evolve in a wave front-like pattern, so we divided the myocardium into histological zones: the infarct core (IC), the border zone (BZ), the remote zone (RZ), and the peri-scar zone (PSZ). The number of SSTR2+ neutrophils (NPs), SSTR2+ monocytes/macrophages (Mos/MPs), and SSTR2+ vessels were counted. In the myocardium of the control group, SSTR2+ NPs and SSTR2+ Mos/MPs were occasional, SSTR2+ vessels were absent. In the RZ, the picture was similar to the control group, but there was a lower number of SSTR2+ Mos/MPs in the RZ. In the PSZ, SSTR2+ vessel numbers were highest in the myocardium. In the IC, the median number of SSTR2+ NPs was 200 times higher compared to the RZ or control group myocardium, which may explain the selective uptake of SSTR-targeted radiotracers in the MI area during the inflammatory phase of MI.
A Multi-Center Observation Study on Medication-Related Osteonecrosis of the Jaw (MRONJ) in Patients with Osteoporosis, and Other Non-Malignant Bone Diseases, in Northwestern Italy over 16 Years
Authors: Karimi Dora , Arduino Paolo Giacomo , Gambino Alessio , Erovigni Francesco , Dell’Acqua Alessandro , Pera Francesco , Carossa Massimo , Pentenero Monica , Appendino Paolo , Della Ferrera Francesco , Fasciolo Antonella , Caka Majlinda , Migliario Mario , Brucoli Matteo , Franchi Stefano , Pezzimenti Alessandro , Fusco Vittorio
Published: September 2024

Objectives: To assess the number of new cases of Medication-Related Osteonecrosis of the Jaw (MRONJ) among patients with osteoporosis and other non-malignant bone diseases in Northwestern Italy between 2007 and 2022. Methods: MRONJ cases were collected from referral centers in a population of 4.5 million. We analysed the number of new MRONJ cases per year, type of disease, administered drugs, duration of therapy (when available), and onset time of disease. Results: We analysed 198 cases (out of 1071 total MRONJ cases); diseases included osteoporosis (87%), rheumatoid arthritis (5%), their association (4%), Paget’s disease, and other various diseases (4%). Patients received bisphosphonates alone (74%), or denosumab alone (6%), or a sequence of different drugs (20%). The number of new cases increased over five years from 2 (2003–2007) to 51 (2008–2012), 65 (2013–2017), and 79 (2018–2022), and the percentage increased from 1% to 14%, 20%, and 29% of the total cases. Conclusions: The number of new MRONJ cases per year among patients with non-malignant diseases is rapidly increasing all around the world, though underestimation cannot be excluded. In this study, we describe epidemiological and clinical characteristics of patients, and the drug most frequently involved in MRONJ cases in our region over a long period, allowing a comprehensive view of the progression of the disease. Greater collaboration among specialists is needed for correct and early diagnosis to improve measures potentially reducing disease incidence and to limit quality of life deterioration in patients with osteoporosis and other non-malignant diseases.
MNAzyme-Assisted Nucleic Acid Lateral Flow Assay for Cost-Effective, On-Site Mercury Detection
Authors: Kim Seok Hyeon , Kim Yujun , Kim Seokjoon , Lee Eun Sung , Cha Byung Seok , Park Ki Soo
Published: September 2024

Mercury ions (Hg2+) are toxic heavy metals present in the environment that pose significant health risks. An advanced detection system could allow for a prompt response and alleviate serious damage to humans. In this study, we developed a cost-effective, on-site detection method for Hg2+ using a multicomponent nucleic acid enzyme (MNAzyme)-assisted nucleic acid lateral flow assay (NALFA). The MNAzyme, which was engineered to contain thymine–thymine mismatches, is responsive only to the presence of Hg2+ and exerts efficient cleavage activity on substrates that can be captured by the NALFA strip, and thus the proposed system enables the visual detection of Hg2+ in the NALFA strip. Our assay demonstrated sufficient detection sensitivity and specificity to meet the WHO standards, offering a good practical alternative for rapid environmental and public health monitoring.
Punishment after Life: How Attitudes about Longer-than-Life Sentences Expose the Rules of Retribution
Authors: Aharoni Eyal , Nahmias Eddy , Hoffman Morris B. , Fernandes Sharlene
Published: September 2024

Prison sentences that exceed the natural lifespan present a puzzle because they have no more power to deter or incapacitate than a single life sentence. In three survey experiments, we tested the extent to which participants support these longer-than-life sentences under different decision contexts. In Experiment 1, 130 undergraduates made hypothetical prison sentence-length recommendations for a serious criminal offender, warranting two sentences to be served either concurrently or consecutively. Using a nationally representative sample (N = 182) and an undergraduate pilot sample (N = 260), participants in Experiments 2 and 3 voted on a hypothetical ballot measure to either allow or prohibit the use of consecutive life sentences. Results from all experiments revealed that, compared to concurrent life sentences participants supported the use of consecutive life sentences for serious offenders. In addition, they adjusted these posthumous years in response to mitigating factors in a manner that was indistinguishable from ordinary sentences (Experiment 1), and their support for consecutive life sentencing policies persisted, regardless of the default choice and whether the policy was costly to implement (Experiments 2 and 3). These judgment patterns were most consistent with retributive punishment heuristics and have implications for sentencing policy and for theories of punishment behavior.
Night Lighting Fault Detection Based on Improved YOLOv5
Authors: Zhang Feng , Dai Congqi , Zhang Wanlu , Liu Shu , Guo Ruiqian
Published: September 2024

Night lighting is essential for urban life, and the occurrence of faults can significantly affect the presentation of lighting effects. Many reasons can cause lighting faults, including the damage of lamps and circuits, and the typical manifestation of the faults is that the lights do not light up. The current troubleshooting mainly relies on artificial visual inspection, making detecting faults difficult and time-consuming. Therefore, it is necessary to introduce technical means to detect lighting faults. However, current research on lighting fault detection mainly focuses on using non-visual methods such as sensor data analysis, which has the disadvantages of having a high cost and difficulty adapting to large-scale fault detection. Therefore, this study mainly focuses on solving the problem of the automatic detection of night lighting faults using machine vision methods, especially object detection methods. Based on the YOLOv5 model, two data fusion models have been developed based on the characteristics of lighting fault detection inverse problems: YOLOv5 Channel Concatenation and YOLOv5 Image Fusion. Based on the dataset obtained from the developed automatic image collection and annotation system, the training and evaluation of these three models, including the original YOLOv5, YOLOv5 Channel Concatenation, and YOLOv5 Image Fusion, have been completed. Research has found that applying complete lighting images is essential for the problem of lighting fault detection. The developed Image Fusion model can effectively fuse information and accurately detect the occurrence and area of faults, with a mAP value of 0.984. This study is expected to play an essential role in the intelligent development of urban night lighting.
Photocatalytic Luminous Textiles for the Treatment of Wastewater Issued from Petroleum Activity: Photocatalytic Process Extrapolation
Authors: Assadi Achraf Amir , Zeghioud Hicham , Belkessa Nacer , Rabahi Amina , Jery Atef EL , Aldrdery Moutaz , Assadi Aymen Amine
Published: September 2024

In this study, the degradation of naphthalene in water was performed via photocatalysis with two different configurations: UV-irradiated TiO2 deposited on cellulosic tissue and photocatalytic luminous textiles. The photocatalytic performance of these configurations was evaluated in terms of pollutant removal and mineralization yield. Moreover, the influence of key operating parameters, such as the initial pollutant concentration, solution turbidity, the number of tissues, and the type of irradiation, was investigated. The results showed a complete removal of 8 mg/L of naphthalene with photocatalytic luminous textiles after 4 h of UV irradiation, with a mineralization yield of 80%. The impact of the turbidity shows that at 90 NTU, reductions in photocatalytic activity of 30% and 10% were recorded for the UV-irradiated TiO2 deposed on cellulosic tissue and photocatalytic luminous textiles, respectively. The reactive oxygen species (ROS) concentrations were monitored during photocatalysis to better understand the contribution of each active species in the mechanism reaction of naphthalene oxidation. The results show that the hydroxyl radical (•OH) is responsible for 70% of pollutant oxidation. A scaling up of the water treatment with photocatalytic luminous textiles was performed. The extrapolation confirmed the same trends observed at the laboratory scale in terms of degradation and mineralization.
A Novel Bioluminescent Biosensor Quantifying Intramolecular Interaction and Levels of Pyroptosis Effector GSDMD
Authors: Kelly Tynan , Bhandari Simran , Carew Madeleine , Rubino Rachel , Nicol Christopher , Yang Xiaolong
Published: September 2024

Gasdermin D (GSDMD) is a key executor of pyroptosis, a form of inflammation-induced programmed cell death. Recently, GSDMD has been shown to play important roles in the development of various inflammatory-related human diseases including heart failure and cancer, suggesting that it is a promising therapeutic target for these diseases. While extensive studies on GSDMD’s role in pyroptosis have been reported, it is challenging to study its function due to the lack of enzymatic activity of GSDMD. In this study, we used the NanoBiT technology to develop a novel GSDMD bioluminescent biosensor (GSDMD-BS) that detects the amount of non-cleaved GSDMD. This sensor allows us to quantify GSDMD’s intramolecular interactions, the amounts of uncleaved GSDMD after caspase-1 cleavage, and expression levels in living cells. In vitro experiments using purified GSDMD-BS also confirmed the sensor’s accuracy in reporting GSDMD levels and cleavage. Moreover, the potential for in vivo application was demonstrated in a xenograft mouse model. In conclusion, we have developed a GSDMD biosensor that is a valuable tool for real-time monitoring of GSDMD dynamics and pyroptosis. This biosensor will significantly expedite pyroptosis research and can be used for high-throughput screening for drugs targeting GSDMD for the therapy of many inflammation-related diseases.