bluuebunny/crossref_metadata_2025 huggingface dataset:
Identification of Plasma Metabolites Responding to Oxycodone Exposure in Rats
Authors: Vu Thao , Godbole Suneeta , Carrette Lieselot L. G. , Maturin Lisa , George Olivier , Saba Laura M. , Kechris Katerina
Published: February 2025

Background: Oxycodone has an elevated abuse liability profile compared to other prescription opioid medications. However, many human and rodent metabolomics studies have not been specifically focused on oxycodone. Objectives: Investigating metabolomics changes associated with oxycodone exposure can provide insights into biochemical mechanisms of the addiction cycle and prognosis prediction. Methods: Plasma samples from 16 rats at pre-exposure and intoxication time points were profiled on the Metabolon platform. A total of 941 metabolites were characterized. We employed a k-Nearest Neighbor imputation to impute metabolites with low levels of missingness and binarized metabolites with moderate levels of missingness, respectively. Results: Of the 136 binarized metabolites, 6 showed differential abundance (FDR < 0.05), including 5 that were present at pre-exposure but absent at intoxication (e.g., adenine), while linoleamide (18:2n6) exhibited the opposite behavior. Among the 798 metabolites with low levels of missingness, 364 showed significant changes between pre-exposure and intoxication (FDR < 0.01), including succinate, oleamide, and sarcosine. We identified four pathways, including tryptophan metabolism, that were nominally enriched among the metabolites that change with oxycodone exposure (p < 0.05). Furthermore, we identified several metabolites that showed nominal correlations with the Addiction Index (composite of oxycodone behaviors): 17 at pre-exposure and 8 at intoxication. In addition, the changes in abundance between pre-exposure and intoxication time points of 9 metabolites were nominally correlated with the Addiction Index, including sphingomyelins, methylhistidines, and glycerols. Conclusions: In summary, not only were we able to capture oxy-induced changes in metabolic pathways using easily accessible blood samples, but we also demonstrated the potential of blood metabolomics to better understand addiction liability.
Imaging Techniques for 3-Dimensional, Non-Line-of-Sight Structures Fabricated in Silicon Carbide
Authors: Payne Jared E. , Eddy Joseph , Stevenson Hunter , Nielson Gregory N. , Schultz Stephen
Published: February 2025

Advances in silicon carbide fabrication techniques enable the fabrication of high aspect ratio non-line-of-sight structures. The further development of non-line-of-sight fabrication tools and the use of the non-line-of-sight structures requires a set of measurement techniques. The goals of the measurement techniques are to (1) quickly detect the success of the fabrication and determine when a failure occurs, (2) accurately measure the shape of the subsurface structure, and (3) accurately characterize the structure. The first goal is attained using subsurface optical microscopy and single point confocal microscopy with a demonstrated resolution of 3 μm. The second goal is attained using X-ray computer tomography with a resolution of 500 nm. The third goal requires the accuracy of scanning electron microscopy. The substructures are brought to the surface through focused ion beam milling if the structures are less than 30 μm deep and through ablation cleaving and polishing for deeper substructures.
Purification, Characterization, and Potential Immune-Regulation Mechanism of Polysaccharides from Artemisia odosica Krasch.
Authors: Xing Yuanyuan , Zheng Yankai , Zhang Jing , Chen Lu , Xu Yuanqing , Jin Xiao , Hong Lei , Yan Sumei , Shi Binlin
Published: February 2025

Artemisia ordosica Krasch. represents a medicinal species traditionally and extensively employed in traditional medicine for treating ailments such as rheumatic arthritis, sore throat, and inflammation. This study initially focuses on the extraction, purification, and characterization of Artemisia ordosica Krasch. polysaccharides (AOP). The purified AOP exhibits a molecular mass corresponding to 9.00 kDa and consists of multiple monosaccharide units, with glucose (54.08%) as the predominant component, followed by arabinose (13.75%), mannose (13.43%), galactose (12.79%), xylose (3.15%), glucuronic acid (0.93%), galacturonic acid (0.67%), ribose (0.63%), and fucose (0.56%), respectively. Furthermore, to explore the immune-regulatory mechanisms of AOP, peripheral blood lymphocytes (PBLs) were cultured and exposed to inhibitors targeting receptors and signaling molecules. The results indicated that TLR4 serves as a potential target through which AOP exerts its immunomodulatory functions. AOP mitigates immune stress in PBLs triggered by LPS by disrupting the interaction between LPS and TLR and downregulating the over-activation of the nuclear factor kappa B (NF-κB) signaling pathway. In summary, AOP shows promise as a feed additive to protect animals from immune stress.
An Exploratory Investigation of Representations of Herpes Zoster and Adjuvanted Recombinant Herpes Zoster Vaccination in a Sample of Fragile Adults in Italy
Authors: De Caro Francesco , Pecoraro Nadia , Capunzo Mario , Caruccio Simona , Caggiano Filippo , Cersosimo Giuseppina , Costantino Maria , Longanella Walter , Malatesta Francesca , Tomeo Matteo , Savarese Giulia , Sinopoli Pio , Vozzella Emilia Anna , Moccia Giuseppina
Published: February 2025

In the context of the Italian National Herpes Zoster Vaccine program, an exploratory survey was conducted on a sample of fragile adult patients to investigate the representations of the disease and its prevention to build future local vaccination campaigns. An ad hoc questionnaire was administered to 271 fragile adult patients who had adjuvanted recombinant Herpes Zoster vaccination to detect the following: knowledge and perception of the disease and its risks; information sources and confidence in the information sources used; and perception of the Herpes Zoster vaccination. Fragile adult patients have the representation of Herpes Zoster as a serious disease (86.5%), and they consider themselves informed concerning symptoms and health effects. Women are more fearful of the impact of the disease (Chi-square = 10.03; DF = 3; p-value = 0.018), while those with a higher average age consider themselves less informed (R = −158; p-value = 0.039). The sources of information that contributed to the construction of illness representation are health personnel (73.5%), followed by the web and social web (14.7%), and media such as radio and TV (10.0%). Regarding the vaccine representation, fragile patients are confident about the vaccine and the science behind it and believe everyone should receive it. However, a high percentage (62.9%) fear side effects. Our analysis highlights that vaccination campaigns must be planned based on the target audience, individual and contextual needs, and representations of the disease, particularly when dealing with frail patients, to implement effective preventive interventions.
Intravenously Administered Nonsteroidal Anti-Inflammatory Drugs in Clinical Practice: A Narrative Review
Authors: Maurice-Szamburski Axel , Quemeneur Cyril , Rozier Romain , Cuvillon Philippe , Ecoffey Claude
Published: February 2025

Intravenously administered nonsteroidal anti-inflammatory drugs (NSAIDs) constitute a crucial component of multimodal analgesia strategies in surgical settings. This narrative review aims to provide an up-to-date evaluation of the efficacy, safety, and clinical use of intravenous (IV) NSAIDs for perioperative pain management in adults and children. The NSAIDs and selective COX-2 inhibitors (coxibs) approved in Europe for the short-term symptomatic treatment of acute, moderate perioperative pain via IV infusion in adults and/or children have been influenced by US and global guidelines and practice: the drugs primarily reviewed here are ibuprofen, ketorolac, ketoprofen, naproxen, paracetamol, and acetylsalicylic acid. Furthermore, intravenous ibuprofen is authorized for the short-term symptomatic treatment of fever. In contrast to intravenous ketoprofen, intravenous ibuprofen is authorized for administration to children over 6 years of age or weighing more than 20 kg. Overall, IV ibuprofen had a more favorable profile with regard to peri- and postoperative opioid sparing and pain relief. Oral ibuprofen and IV ibuprofen have similar levels of efficacy, although IV ibuprofen has a shorter onset of action and is required in patients who are unable to take oral medications. The frequency of significant adverse events appears to be similar for ibuprofen and paracetamol. Systematic reviews and meta-analyses report that intravenous NSAIDs reduce postoperative opioid consumption by approximately 20–60%, improving pain management with fewer opioid-related side effects. In indications in infants, the choice of medication is limited, and the oral route is not always feasible; IV formulations of ibuprofen are preferred in this setting. Topics for further research should include head-to-head trials of IV NSAIDs.
Inulin as a Biopolymer; Chemical Structure, Anticancer Effects, Nutraceutical Potential and Industrial Applications: A Comprehensive Review
Authors: Karimi Isaac , Ghowsi Mahnaz , Mohammed Layth Jasim , Haidari Zohreh , Nazari Kosar , Schiöth Helgi B.
Published: February 2025

Inulin is a versatile biopolymer that is non-digestible in the upper alimentary tract and acts as a bifidogenic prebiotic which selectively promotes gut health and modulates gut–organ axes through short-chain fatty acids and possibly yet-to-be-known interactions. Inulin usage as a fiber ingredient in food has been approved by the FDA since June 2018 and it is predicted that the universal inulin market demand will skyrocket in the near future because of its novel applications in health and diseases. This comprehensive review outlines the known applications of inulin in various disciplines ranging from medicine to industry, covering its benefits in gut health and diseases, metabolism, drug delivery, therapeutic pharmacology, nutrition, and the prebiotics industry. Furthermore, this review acknowledges the attention of researchers to knowledge gaps regarding the usages of inulin as a key modulator in the gut–organ axes.
Sustainable Bio-Preservation of Concentrated Yogurt (Labneh) Using Syzygium aromaticum L.
Authors: El-ssayad Mohamed F. , Assem Fayza M. , El-Gawad Mona A. M. Abd , Mohamed Sahar H. S. , Kassem Jihan M. , Alsaleem Khalid A.
Published: February 2025

Bio-preservation strategies for sustainable food and dairy products are some of the most in-demand techniques that expand shelf life and meet consumer requirements. The purpose of this study is to produce high quality, sensory-acceptable labneh cheese with a prolonged shelf life and sustainable preservation. Ethanolic extract of clove flower buds was applied during the manufacturing of labneh as a bio-preserving agent. The effect of the sprayed-clove extract on the chemical composition, microbiological composition, texture profile, antioxidant capabilities, aromatic compounds, and sensory properties of the labneh cheese were determined. Phytochemical profiling showed chaulmoogric acid, trans-cinnamic acid, propyl gallate, and sinapine as major constituents in clove extract. Antimicrobial inhibitory potential was estimated against both foodborne pathogens and food spoilage microorganisms. Clove extract showed a promising inhibitory effect against fungi recording 1 mg/mL maximally. Labneh samples with clove extract contained the highest records of antioxidant activity in addition to having no record of any fungal growth after 60 days. It is also distinguished by its eugenol, β-Caryophyllene, and acetyleugeno as aroma compound content. All spray-treated samples achieved the highest scores in sensory properties during the storage period. It can be concluded that clove extract, when sprayed on the surface of labneh cheese, produced an antifungal effect in a smart and economic way which boosted the shelf life, quality, enhanced nutritional value, and the antioxidant capacity of labneh cheese.
Recycling Water Hyacinth as Supplementary Cementitious Material, Admixture, and Fiber in Mortar and Concrete: Current Trends and Research Gaps
Authors: García Gilberto , Cabrera René , Rolón Julio , Pichardo Roberto
Published: February 2025

This review explores the potential of water hyacinth (WH) as a sustainable material in cement-based applications, focusing on its use as an addition, admixture, and fiber reinforcement. WH’s unique physical and chemical properties, such as high cellulose content and pozzolanic potential, make it suitable for bio-composites and eco-friendly concrete formulations. The present study highlights several promising findings, including the enhancement of the resulting mechanical properties and the reduction in their environmental impact when the WH is incorporated in controlled quantities. Challenges such as workability and durability issues at higher dosages are discussed. This review aims to bridge knowledge gaps and support WH’s adoption in sustainable construction practices.
Assessing Hydrocyclone System’s Efficiency in Water-Borne Microplastics Capture Using Online Microscopy Sensors
Authors: Pajuro Kacper , Yang Zhenyu , Jespersen Stefan , Hansen Dennis Severin
Published: February 2025

Plastic pollution has been a global concern. Microplastics are often referred to as plastic particulates whose sizes are within the range of 1 μm to 5 mm. To cost-effectively capture these tiny microplastics from open environments, such as from the air or aquatic/marine systems, is far from trivial. Not only is some innovative capturing technology demanded, but some online monitoring solutions are often requested as well to assess the capturing effectiveness and efficiency, as well as provide some feedback information to the control system to adapt to varying operating conditions. Inspired by the de-oiling treatment of the produced water in offshore oil & gas production, this paper explores the potential to apply the hydrocyclone technology to cost-effectively handle the water-borne microplastics, and its effectiveness is demonstrated based on reliably calibrated online microscopy measurements subject to artificial polyethylene particulates added to the water stream. The experimental work is carried out using a commercial de-oiling hydrocyclone system and a set of commercial optical microscopy sensors. A statistic-based calibration method is firstly proposed for the deployed microscopy sensors to select the best calibration parameters. Afterwards these sensors are installed at the inlet and water-outlet of the hydrocyclone system via a side-stream sampling mechanism to assess this system’s (microplastics) separation efficiency subject to dynamical operating conditions, which are mimicked by manipulating its underflow and overflow control valves via PI-controlled loops. The separation efficiencies are calculated based on these volume concentration measurements and compared between the case with (statistically) optimal calibration parameters and the case with a set of non-optimal parameters. The best separation efficiency of 87.76% under the optimal calibration parameters is observed under a specific operating condition. The obtained result shows a promising potential to use these separation and sensing systems to cost-effectively handle aquatic microplastics collection, though it also indicates that a further higher efficiency could be achieved by some (microplastics) dedicated cyclone design combined with a dedicated process control system, and this is one part of our ongoing research work.
Simulation and Analysis of Imaging Process of Phosphor Screens for X-Ray Imaging of Streak Tube Using Geant4-Based Monte Carlo Method
Authors: Wang Zichen , Lin Riyi , Liao Yuxiang , Tang Lin , Wu Zhenhua , Liu Diwei , Zhong Renbin , Zhang Kaichun
Published: February 2025

Ultrafast diagnostic technology has caused breakthroughs in fields such as inertial confinement fusion, particle accelerator research, and laser-induced phenomena. As the most widely used tool for ultrafast diagnostic technology, investigating the characteristics of streak cameras in the imaging process and streak tubes’ complex physical processes is significant for its overall development. In this work, the imaging process of a streak camera is modeled and simulated using Geant4-based Monte Carlo simulations. Based on the selected phosphor screen P43 (Gd2O2S: Tb) and charged coupled device (CCD) sensor parameters, Monte Carlo simulation models of phosphor screens and CCD sensors (We refer to the sensor parameters of the US company onsemi’s KAF-50100 sensor, but some adjustments are made during the simulation), implemented with the toolkit Geant4, are used to study the electron beam to generate fluorescence on phosphor and photoelectrons on CCD sensors. The physical process of a high-energy electron beam hitting a phosphor screen and imaging on the CCD camera is studied. Meanwhile, merits such as the luminous efficiency of the selected phosphor, spatial resolution of the phosphor screen, and spatial resolution of the selected CCD sensor are analyzed. The simulation results show that the phosphor screen and CCD sensor simulation models can accurately simulate the selected components’ performance parameters with the imaging process’ simulation results precisely reflecting the distribution of output electrons in the streak image tube. References for simulation and device selection in the subsequent research on streak cameras can be provided.
Research on Blood Cell Image Detection Method Based on Fourier Ptychographic Microscopy
Authors: Li Mingjing , Yang Le , Fang Shu , Liu Xinyang , Yun Haijiao , Wang Xiaoli , Du Qingyu , Han Ziqing , Wang Junshuai
Published: February 2025

Autonomous Fourier Ptychographic Microscopy (FPM) is a technology widely used in the field of pathology. It is compatible with high resolution and large field-of-view imaging and can observe more image details. Red blood cells play an indispensable role in assessing the oxygen-carrying capacity of the human body and in screening for clinical diagnosis and treatment needs. In this paper, the blood cell data set is constructed based on the FPM system experimental platform. Before training, four enhancement strategies are adopted for the blood cell image data to improve the generalization and robustness of the model. A blood cell detection algorithm based on SCD-YOLOv7 is proposed. Firstly, the C-MP (Convolutional Max Pooling) module and DELAN (Deep Efficient Learning Automotive Network) module are used in the feature extraction network to optimize the feature extraction process and improve the extraction ability of overlapping cell features by considering the characteristics of channels and spatial dimensions. Secondly, through the Sim-Head detection head, the global information of the deep feature map (mean average precision) and the local details of the shallow feature map are fully utilized to improve the performance of the algorithm for small target detection. MAP is a comprehensive indicator for evaluating the performance of object detection algorithms, which measures the accuracy and robustness of a model by calculating the average precision (AP) under different categories or thresholds. Finally, the Focal-EIoU (Focal Extended Intersection over Union) loss function is introduced, which not only improves the convergence speed of the model but also significantly improves the accuracy of blood cell detection. Through quantitative and qualitative analysis of ablation experiments and comparative experimental results, the detection accuracy of the SCD-YOLOv7 algorithm on the blood cell data set reached 92.4%, increased by 7.2%, and the calculation amount was reduced by 14.6 G.
Wearable and Thermal Drift-Compensated Monitoring System Based on Fiber Bragg Grating Sensors for a 3D-Printed Foot Prosthesis
Authors: Del Chicca Sara , Rollo Gennaro , Sorrentino Andrea , Gruppioni Emanuele , Tarabini Marco , Saccomandi Paola
Published: February 2025

Monitoring foot prostheses is essential, as their performance impacts users’ daily lives. Fiber Bragg Grating (FBG) sensors represent a gold standard in monitoring applications, but traditional optoelectronic units are too cumbersome for wearable applications. This research addresses this issue by using a lightweight and compact optoelectronic unit and developing a compensation algorithm to overcome the signal drift phenomena caused by the light source instability. The proposed method uses an FBG as a reference to provide the algorithm with information on the signals drift. The developed algorithm is based on the assumptions of linearity among drift in different detection channels and the absence of drift at the initial time instant. The compensation variable was experimentally identified and validated. Experimental validation through temperature tests showed the algorithm reduces the drift error by 60%. Finally, mechanical tests were conducted on a foot prosthesis equipped with two FBGs: one used as a reference and the other for strain sensing. An electrical strain gauge was used to validate the FBG-based sensing system. The results of the mechanical tests indicate the possiblity to monitor a foot prosthesis using FBGs. The FBG and strain gauge measurements comparison aligns with previous studies where high-performance optoelectronic units were used.
Towards Digital-Twin Assisted Software-Defined Quantum Satellite Networks
Authors: Chiti Francesco , Pecorella Tommaso , Picchi Roberto , Pierucci Laura
Published: February 2025

The Quantum Internet (QI) necessitates a complete revision of the classical protocol stack and the technologies used, whereas its operating principles depend on the physical laws governing quantum mechanics. Recent experiments demonstrate that Optical Fibers (OFs) allow connections only in urban areas. Therefore, a novel Quantum Satellite Backbone (QSB) composed of a considerable number of Quantum Satellite Repeaters (QSRs) deployed in Low Earth Orbit (LEO) would allow for the overcoming of typical OFs’ attenuation problems. Nevertheless, the dynamic nature of the scenario represents a challenge for novel satellite networks, making their design and management complicated. Therefore, we have designed an ad hoc QSB considering the interaction between Digital Twin (DT) and Software-Defined Networking (SDN). In addition to defining the system architecture, we present a DT monitoring protocol that allows efficient status recovery for the creation of multiple End-to-End (E2E) entanglement states. Moreover, we have evaluated the system performance by assessing the path monitoring and configuration time, the time required to establish the E2E entanglement, and the fidelity between a couple of Ground Stations (GSs) interconnected through the QSB, also conducting a deep analysis of the created temporal paths.
Time-Interval-Based Collision Detection for 4WIS Mobile Robots in Human-Shared Indoor Environments
Authors: Kim Seungmin , Jang Hyunseo , Ha Jiseung , Lee Daekug , Ha Yeongho , Song Youngeun
Published: February 2025

The recent growth in e-commerce has significantly increased the demand for indoor delivery solutions, highlighting challenges in last-mile delivery. This study presents a time-interval-based collision detection method for Four-Wheel Independent Steering (4WIS) mobile robots operating in human-shared indoor environments, where traditional path following algorithms often create unpredictable movements. By integrating kinematic-based robot trajectory calculation with LiDAR-based human detection and Kalman filter-based prediction, our system enables more natural robot–human interactions. Experimental results demonstrate that our parallel driving mode achieves superior human detection performance compared to conventional Ackermann steering, particularly during cornering and high-speed operations. The proposed method’s effectiveness is validated through comprehensive experiments in realistic indoor scenarios, showing its potential for improving the efficiency and safety of indoor autonomous navigation systems.
CLEAR: Multimodal Human Activity Recognition via Contrastive Learning Based Feature Extraction Refinement
Authors: Cao Mingming , Wan Jie , Gu Xiang
Published: February 2025

Human activity recognition (HAR) has become a crucial research area for many applications, such as Healthcare, surveillance, etc. With the development of artificial intelligence (AI) and Internet of Things (IoT), sensor-based HAR has gained increasing attention and presents great advantages to existing work. Relying solely on existing labeled data may not adequately address the challenge of ensuring the model’s generalization ability to new data. The ’CLEAR’ method is designed to improve the accuracy of multimodal human activity recognition. This approach employs data augmentation, multimodal feature fusion, and contrastive learning techniques. These strategies are utilized to refine and extract highly discriminative features from various data sources, thereby significantly enhancing the model’s capacity to identify and classify diverse human activities accurately. CLEAR achieves high generalization performance on unknown datasets using only training data. Furthermore, CLEAR can be directly applied to various target domains without retraining or fine-tuning. Specifically, CLEAR consists of two parts. First, it employs data augmentation techniques in both the time and frequency domains to enrich the training data. Second, it optimizes feature extraction using attention-based multimodal fusion techniques and employs supervised contrastive learning to improve feature discriminability. We achieved accuracy rates of 81.09%, 90.45%, and 82.75% on three public datasets USC-HAD, DSADS, and PAMAP2, respectively. Additionally, when the training data are reduced from 100% to 20%, the model’s accuracy on the three datasets decreases by only about 5%, demonstrating that our model possesses strong generalization capabilities. Additionally, when the training data are reduced from 100% to 20%, the model’s accuracy on the three datasets decreases by only about 5%, demonstrating that our model possesses strong generalization capabilities.
Long-Term Energy Consumption Minimization Based on UAV Joint Content Fetching and Trajectory Design
Authors: Diallo Elhadj Moustapha , Chai Rong , Adam Abuzar B. M. , Bayessa Gezahegn Abdissa , Liang Chengchao , Chen Qianbin
Published: February 2025

Caching the contents of unmanned aerial vehicles (UAVs) could significantly improve the content fetching performance of request users (RUs). In this paper, we study UAV trajectory design, content fetching, power allocation, and content placement problems in multi-UAV-aided networks, where multiple UAVs can transmit contents to the assigned RUs. To minimize the energy consumption of the system, we develop a constrained optimization problem that simultaneously designs UAV trajectory, power allocation, content fetching, and content placement. Since the original minimization problem is a mixed-integer nonlinear programming (MINLP) problem that is difficult to solve, the optimization problem was first transformed into a semi-Markov decision process (SMDP). Next, we developed a new technique to solve the joint optimization problem: option-based hierarchical deep reinforcement learning (OHDRL). We define UAV trajectory planning and power allocation as the low-level action space and content placement and content fetching as the high-level option space. Stochastic optimization can be handled using this strategy, where the agent makes high-level option selections, and the action is carried out at a low level based on the chosen option’s policy. When comparing the proposed approach to the current technique, the numerical results show that it can produce more consistent learning performance and reduced energy consumption.
Design and Tracking Control Experimental Study of a Hybrid Reluctance-Actuated Fast Steering Mirror with an Integrated Sensing Unit
Authors: Zhou Jian , Fan Yudong , Li Liang , Zhang Feng , Feng Bo , Xu Minglong
Published: February 2025

This study proposes the design of a hybrid reluctance-actuated fast steering mirror (HRAFSM) using Maxwell’s electromagnetic normal stress principle. Strain gauges were attached to the flexible supports as sensors for measuring the rotation angles. According to Maxwell’s stress tensor theory and the theory of vibration mechanics, we obtained the dynamic equation of the HRAFSM in the uniaxial direction to investigate the relationship between the input current and the output angle of the entire system. Further, we propose a control algorithm combining proportional-integral-derivative (PID) and adaptive inverse control (AIC) to achieve high-precision control. We established an experimental system for testing and validation of the control method. The experimental results showed that the designed HRAFSM can achieve the expected rotation angle of ±1.5 mrad, and revealed a linear relationship between the rotation angle of the two axes and their corresponding strain voltages. The effectiveness of the designed controller was verified, and the amplitude tracking errors of the x- and y-axes were 0.1% and 0.14%, respectively.
FLDQN: Cooperative Multi-Agent Federated Reinforcement Learning for Solving Travel Time Minimization Problems in Dynamic Environments Using SUMO Simulation
Authors: Mamond Abdul Wahab , Kundroo Majid , Yoo Seong-eun , Kim Seonghoon , Kim Taehong
Published: February 2025

The increasing volume of traffic has led to severe challenges, including traffic congestion, heightened energy consumption, increased air pollution, and prolonged travel times. Addressing these issues requires innovative approaches for optimizing road network utilization. While Deep Reinforcement Learning (DRL)-based methods have shown remarkable effectiveness in dynamic scenarios like traffic management, their primary focus has been on single-agent setups, limiting their applicability to real-world multi-agent systems. Managing agents and fostering collaboration in a multi-agent reinforcement learning scenario remains a challenging task. This paper introduces a cooperative multi-agent federated reinforcement learning algorithm named FLDQN to address the challenge of agent cooperation by solving travel time minimization challenges in dynamic multi-agent reinforcement learning (MARL) scenarios. FLDQN leverages federated learning to facilitate collaboration and knowledge sharing among intelligent agents, optimizing vehicle routing and reducing congestion in dynamic traffic environments. Using the SUMO simulator, multiple agents equipped with deep Q-learning models interact with their local environments, share model updates via a federated server, and collectively enhance their policies using unique local observations while benefiting from the collective experiences of other agents. Experimental evaluations demonstrate that FLDQN achieves a significant average reduction of over 34.6% in travel time compared to non-cooperative methods while simultaneously lowering the computational overhead through distributed learning. FLDQN underscores the vital impact of agent cooperation and provides an innovative solution for enabling agent cooperation in a multi-agent environment.
Compound Fault Diagnosis of Wind Turbine Gearbox via Modified Signal Quality Coefficient and Versatile Residual Shrinkage Network
Authors: Jiang Weixiong , Zhao Guanhui , Gao Zhan , Wang Yuanhang , Wu Jun
Published: February 2025

Wind turbine gearbox fault diagnosis is critical to guarantee working efficiency and operational safety. However, the current diagnostic methods face enormous restrictions in handling nonlinear noise signals and intricate compound fault patterns. Herein, a compound fault diagnosis method based on modified signal quality coefficient (MSQC) and versatile residual shrinkage network (VRSN) is proposed to resolve these issues. In detail, the MSQC is designed to remove the noise components irrelevant to wind turbine operation status, and it has the ability to balance the denoised effect and signal fidelity. The VRSN is constructed for compound fault diagnosis, and it consists of two heterogeneous residual shrinkage networks. The former is designed to count the number of faults, and the latter is adopted to identify the single or compound fault pattern. Finally, a self-built wind turbine gearbox compound fault test rig is adopted to verify the proposed method’s effectiveness. The results demonstrate that the proposed method is competitive in terms of compound fault diagnosis accuracy.
A Large Voltage Responsivity Pyroelectric Sensor Based on Hot-Pressed Lead Zirconate Titanate Ceramic
Authors: Guo Yanhao , Guo Shaobo , Yao Chunhua , Pan Zhiwei , Wang Genshui
Published: February 2025

In this article, hot-pressed PZT ceramics were used as a sensitive element material and made into a pyroelectric chip. Three current mode sensors were fabricated using a pyroelectric chip of different thicknesses (80 μm, 40 μm, and 30 μm). The voltage responsivity of sensors reached the order of magnitude of 105. The size effect resulting from varying the thickness was studied. The results indicate that as the thickness decreases, the performance significantly increases. When the modulation frequency is 10 Hz, the specific detectivity of the sensor with a 30 μm PZT ceramic pyroelectric chip reaches 5.3 × 108 cm·Hz1/2/W.
Prediction of Member Forces of Steel Tubes on the Basis of a Sensor System with the Use of AI
Authors: Li Haiyu , Chung Heungjin
Published: February 2025

The rapid development of AI (artificial intelligence), sensor technology, high-speed Internet, and cloud computing has demonstrated the potential of data-driven approaches in structural health monitoring (SHM) within the field of structural engineering. Algorithms based on machine learning (ML) models are capable of discerning intricate structural behavioral patterns from real-time data gathered by sensors, thereby offering solutions to engineering quandaries in structural mechanics and SHM. This study presents an innovative approach based on AI and a fiber-reinforced polymer (FRP) double-helix sensor system for the prediction of forces acting on steel tube members in offshore wind turbine support systems; this enables structural health monitoring of the support system. The steel tube as the transitional member and the FRP double helix-sensor system were initially modeled in three dimensions using ABAQUS finite element software. Subsequently, the data obtained from the finite element analysis (FEA) were inputted into a fully connected neural network (FCNN) model, with the objective of establishing a nonlinear mapping relationship between the inputs (strain) and the outputs (reaction force). In the FCNN model, the impact of the number of input variables on the model’s predictive performance is examined through cross-comparison of different combinations and positions of the six sets of input variables. And based on an evaluation of engineering costs and the number of strain sensors, a series of potential combinations of variables are identified for further optimization. Furthermore, the potential variable combinations were optimized using a convolutional neural network (CNN) model, resulting in optimal input variable combinations that achieved the accuracy level of more input variable combinations with fewer sensors. This not only improves the prediction performance of the model but also effectively controls the engineering cost. The model performance was evaluated using several metrics, including R2, MSE, MAE, and SMAPE. The results demonstrated that the CNN model exhibited notable advantages in terms of fitting accuracy and computational efficiency when confronted with a limited data set. To provide further support for practical applications, an interactive graphical user interface (GUI)-based sensor-coupled mechanical prediction system for steel tubes was developed. This system enables engineers to predict the member forces of steel tubes in real time, thereby enhancing the efficiency and accuracy of SHM for offshore wind turbine support systems.
Assessing Safety Concerns in Omeprazole Use: An Observational Study of Potentially Inappropriate Prescriptions and Patient Adherence in a Spanish Community Pharmacy
Authors: Capdevila Finestres Franc , Alberto Armas Daida , Miró Manzano Antoni , Hernández García Verónica , Sosa Alonso Yeray , Hardisson de la Torre Arturo , Rubio Armendáriz Carmen
Published: February 2025

Introduction: Omeprazole is commonly prescribed for conditions associated with excess gastric acid, including gastroesophageal reflux and Helicobacter pylori infection. Spain ranks highest among Organization for Economic Co-operation and Development (OECD) countries in omeprazole consumption (measured in doses per 1000 inhabitants per day, DHD), indicating potential overuse and misuse. Community pharmacists are pivotal in collaborating with healthcare professionals to address safety risks and improve patient outcomes. Objective: This study aims to profile omeprazole users to inform pharmaceutical care (PC) strategies that address patient-specific needs and improve treatment safety. Methods: We conducted an observational, cross-sectional study (CEIm Code FCF-OME-2023-01) involving 100 omeprazole users at a community pharmacy in Barcelona from November 2023 to May 2024. Data were collected via clinical interviews using a Data Collection Questionnaire. Results: Among the omeprazole users, 49% were male, 51% female, and 56% were over the age of 65. A significant proportion (71%) exhibited long-term omeprazole use, and 30% were polymedicated (taking five or more medications). Notably, 52% of patients reported no history of gastric symptoms. Additionally, 22% reported using omeprazole occasionally, following short-term, on-demand treatment regimens, while 78% adhered to a chronic daily dosing schedule. Among these patients, 29.5% demonstrated poor treatment adherence. The analysis of medication-related problems (MRPs) among the 78 patients using omeprazole daily and chronically revealed that the most prevalent MRPs were “unnecessary medication”, “lack of adherence”, “wrong administration”, “drug interactions”, and “lack of knowledge regarding medication use”. Based on STOPP criteria, 45% of users were candidates for deprescribing or dose adjustment. Conclusions: The high incidence of MRPs among omeprazole users highlights the need for enhanced pharmaceutical care (PC). Proactive pharmacist interventions, including deprescribing, dose adjustments, and prescriber collaboration, can reduce adverse medication outcomes and promote safer omeprazole use.
Systematic Isolation and Characterization of Regenerated Hemicellulose and Lignin from Soybean Feedstocks Using Ionic Liquids
Authors: Essel Victor , Raynie Douglas E.
Published: February 2025

The use of ionic liquids in biomass pretreatment for ethanol production has seen increased attention in recent years. In this work, 1-butyl-3-methylimidazolium chloride ([Bmim]Cl), 1-allyl-3-methylimidazolium chloride ([Amim]Cl), and 1-ethyl-3-methylimidazolium acetate ([Emim]Ac) were used to regenerate and recover significant amount of hemicellulose and lignin from soybean meal, flakes, and hulls. The regenerated lignin and hemicellulose were characterized using Fourier-transform infrared (FTIR) spectroscopy and pyrolysis-gas chromatography/mass spectrometry (Py-GC/MS). For all three ionic liquids, the amount of regenerated hemicellulose and lignin ranged from approximately 6 to 12% and 8 to 19%, respectively. Lignin characteristic bands 1738.8, 1652.6, 1516.4, 1455.2, and 1174.9 cm−1 were identified in the FTIR spectrum. The regenerated hemicellulose showed the characteristic bands 1658.31, 1434.14, 1167.98, and 865.20 cm−1. The Py-GC/MS analysis of the regenerated lignin showed the characteristic grass lignin pyrolyzates phenol, 2-methoxyphenol, 4-methylphenol, 2-benzaldehyde, 2-methoxy-4-vinylphenol, phenol-2,6-dimethoxy, and ethylvanillin.
Has It Never Been a Better Time to Play? Opportunity, Empowerment and Contested Terrains of Women’s Grassroots Football in Australia
Authors: Richardson Alana , McLachlan Fiona , McDonald Brent
Published: February 2025

The introduction of the semi-professional Australian Rules Football League for Women (AFLW) in 2017 was indicative of a broader ‘boom’ for women and girls’ sport in Australia. The ‘boom’ promised not only newly created, or enhanced, professional pathways for elite women athletes but also a commensurate change in the community sport landscape, backed by a gender equality framework, that would offer women and girls new, and supported, opportunities to play sport. This paper investigates what happens when these opportunities are taken up by examining the experiences of a senior women’s football team in a community-level Australian Rules football club in Melbourne, Australia. Drawing on 11 semi-structured interviews with players, we consider the transformative potential, for these individuals and for gendered power relations, that might be generated from women’s participation in traditionally masculine sporting spaces. The findings reveal contradictory moments of both emancipation and empowerment on one hand with ambivalence and disempowerment on the other. Women’s participation in Australian Rules Football is a contested terrain that is simultaneously embodied, cultural, and social, and we note the experiences and strategies that women utilize to negotiate their engagement with football. We argue that increasing “opportunities” for women to play football is not enough for the transformative promise of the AFLW to be met, and as such, further highlight the ongoing contested terrain of women’s sport.
Does Low-Carbon City Transition Empower Tourism Economy? Evidence from China
Authors: Yue Qi , Zhang Yang , Liao Yinchao , Liao Lei , Yu Juntai
Published: February 2025

The tourism economy is inseparably linked to the ecological environment, serving as a “green engine” in the promotion of the low-carbon transition of cities and the realization of high-quality economic development. Taking the implementation of a low-carbon city pilot (LCCP) policy as a quasinatural experiment, we assess the impact of a low-carbon transition on the urban tourism economy using a time-varying difference-in-differences identification strategy based on the panel data of 279 Chinese cities covering the period from 2007 to 2019. The results indicate that LCCPs have a favorable effect on the development of the tourism economy. Compared to non-pilot cities, the implementation of LCCPs has led to an average increase of approximately CNY 1918 in tourism receipts per inhabitant in pilot cities. The mechanism analysis reveals that the implementation of LCCPs promotes the tourism economy by energizing the tourism market and accumulating ecological wealth. Specifically, LCCPs have not only optimized the supply of tourism products and related services but have also improved the competitiveness of regional tourism by energizing the tourism market. Meanwhile, LCCPs have improved the ecological environment and enriched natural resources through the accumulation of urban ecological wealth, thereby enhancing urban tourism attractiveness and environmental carrying capacity. The heterogeneity results show that the impact of LCCPs on the tourism economy varies significantly by tourism resource endowment, border-crossing status, and ecological landscape division. Our findings provide empirical evidence that can be used to promote the tourism economy in other countries and facilitate the industrial transformation during the process of a low-carbon transition.
Customer Environmental Performance and Supplier Green Innovation: A Sustainable Supply Chain Perspective
Authors: Yang Mingnan , Hou Aoyu , Wang Pingping , Chai Li
Published: February 2025

With the growing emphasis on sustainable development, the impact of customer environmental performance on innovation activities has attracted more attention. Using a dataset of Chinese A-share listed companies from 2009 to 2022, this study empirically investigates the relationship between customer environmental performance and supplier green innovation. The results show that customer environmental performance has a significant positive effect on supplier green innovation. Mechanism analysis reveals that customer environmental performance promotes supplier green innovation through four pathways: supply chain transmission, market investment expectations, institutional policies, and financial constraints. The impact of customer environmental performance on supplier green innovation is more pronounced when the customer enterprise is state-owned, the supplier enterprise is state-owned, or the supplier enterprise holds ISO14001 certification. This study contributes to the literature on supply chain sustainability and provides valuable insights for enterprises on enhancing competitiveness and promoting sustainable supply chain transformation through improved environmental performance.
An Automated Method to Assess the Suitability of Existing Boreholes for Solar-Based Pumping Systems: An Application to Southern Madagascar
Authors: Fussi Fabio , Gómez-Escalonilla Víctor , Rahobisoa Jean-Jacques , Ramanantsoa Hariliva Omena Anahy , Martinez-Santos Pedro
Published: February 2025

Groundwater provides a strategic resource in the face of uncertain climate conditions in arid and semi-arid regions. Solar-based groundwater pumping is quickly gaining ground across rural sub-Saharan Africa, promoted by national and international organizations as the new technology of choice for water supply and irrigation. A crucial question in large-scale developments is whether pre-existing boreholes can be fitted with solar pumps. Based on data from southern Madagascar, this paper provides an automated method to deal with this. Our approach relies on a combination of hydrogeological criteria, including well screen depth, drawdown in relation to the static water column, and pumping efficiency. The results show that 60% of the existing boreholes in the study region are potentially suitable for the installation of solar pumps. Out of these, 54% would be able to supply water to large rural communities (>1000 people), whereas the remaining 46% present the potential to provide water to medium communities (500 to 1000 people). There are, however, concerns as to whether the information contained in the dataset is fully representative of current borehole conditions. Furthermore, the potential for installation of solar-based supplies must be placed in the context of the available resources and local capacities in order to ensure future sustainability.
Tidal Current Modeling Using Shallow Water Equations Based on the Finite Element Method: Case Studies in the Qiongzhou Strait and Around Naozhou Island
Authors: Peng Dawei , Mao Jia , Li Jianhua , Zhao Lanhao
Published: February 2025

Tidal currents are a crucial oceanic process with significant implications for marine engineering and the sustainable use of coastal and marine resources. This paper presents the development of a finite element numerical model to simulate tidal currents. The model was mathematically formulated using the shallow water equations, which are applicable to fluid dynamics where the horizontal scale is significantly larger than the vertical scale. The finite element method was employed to discretize and solve the equations, with the bottom slope source term incorporated into the pressure equation to ensure numerical consistency. Furthermore, characteristic line theory was applied to derive the relationship between boundary tidal levels and current velocities to satisfy boundary compatibility conditions. The model was initially applied to the Qiongzhou Strait, and the results demonstrated good agreement with observed data. Subsequently, the model was implemented at Naozhou Island and its adjacent waters. The results revealed that the tidal currents around Naozhou Island exhibit oscillatory flow patterns, with the flow direction near Donghai Island oriented northeast–southwest (NE-SW) and the flow direction near Leizhou Bay oriented northwest–southeast (NW-SE). This study provides a hydrodynamic basis for marine engineering projects and the sustainable utilization of marine resources in the Naozhou Island area.