bluuebunny/crossref_metadata_2025 huggingface dataset:
Changes in Non-Driving-Related Activities from Conditional to Full Automation and Their Implications for Interior Design: A Systematic Review and Meta-Analysis
Authors: Cai Yujing , Anjani Shabila , Withey Dave , Vledder Gerbera , Song Yu , Vink Peter
Published: October 2024

Automated driving frees users from the task of driving, allowing them to engage in new activities. Using keywords related to Non-Driving-Related Activities (NDRAs) and automated vehicles (and their variants), with reference to the Society of Automotive Engineers (SAE) levels 3, 4, and 5, the authors identified 2430 studies from various databases and sources. Of these, 47 were included in this study, with 39 included in the meta-analysis. The meta-analysis of the included studies shows a positive correlation between automation levels and the diversity of NDRAs. Communication and interaction with passengers are the most common activities, followed by media consumption, rest, and relaxation. Food and drink consumption slightly surpasses working and productivity, while personal habits and hygiene are less prioritized. Although some users still value vehicle monitoring, this need decreases with higher automation levels. Key activities such as communication, laptop use, and sleeping are highlighted as significant benefits of automation, as users transition away from situational awareness and are able to perform cognitively intensive tasks. The review also addresses potential design implications to support these NDRAs and discusses related regulatory challenges.
Modeling Multi-Factor Coupled Pressure Fluctuations in EMU Trains under Extreme Tunnel Conditions
Authors: Zou Miao , Chen Chunjun , Yang Lu
Published: October 2024

As an electric multiple unit (EMU) train passes through an extreme tunnel characterized by high altitude, steep gradient, and extended lengths, the pressure waves generated by the train–tunnel aerodynamic coupling combine with the baseline pressure variations within the tunnel. This interaction results in rapid fluctuations and extreme external pressure with higher amplitudes, which are transmitted into the carriage, causing pressure fluctuations that can adversely affect passenger comfort. These waves interact with multiple factors within the carriage, such as air ducts, airtight gaps, carbody deformation, oxygen supply systems, and temperature, creating a highly nonlinear internal pressure transmission system. This study first establishes a single-factor internal pressure fluctuation model. Subsequently, a multi-factor coupled internal pressure fluctuation model is constructed based on the ideal gas polytropic process assumption and the law of mass conservation. The model parameters are corrected and the model’s effectiveness and accuracy are validated using experimental data to predict and summarize the internal pressure variation patterns of the EMU train during dynamic operation in such tunnels, ensuring safe train operation and meeting the pressure comfort requirements of passengers. Finally, to address the challenges of maintaining and regulating multi-physical variable comfort under extreme tunnel conditions, this study investigates the impact of partial oxygen pressure and temperature on pressure fluctuations and comfort. The study finds that higher oxygen pressure and temperature significantly increase internal pressure fluctuation amplitude, with the oxygen supply system contributing 18.11% and temperature 5.74% of total variation. Thus, setting appropriate standards for oxygen supply, temperature, and valve operation is crucial for mitigating internal pressure fluctuations and enhancing safety and comfort. This research provides a theoretical foundation for developing a comprehensive comfort evaluation and regulation system under harsh environments.
Conservative Analysis of Transient Heat Transfer in Thermal Protection Systems with Interval Parameters
Authors: Feng Xuelei , Shi Zhiyu , Yang Zheng
Published: October 2024

There are many uncertainties in the actual use of thermal protection systems (TPSs). In this paper, an interval finite element model of a TPS under transient heat transfer is established by taking the uncertainties of TPSs as interval parameters. An affine interval finite element method (AIFEM) is proposed to study the temperature response bounds of uncertain TPSs under transient heat transfer conditions. Two numerical examples are given to verify the effectiveness and accuracy of the proposed AIFEM by comparison with the Monte Carlo method. The results show that the AIFEM can provide conservative and efficient calculation results in TPS transient heat transfer design with interval parameters.
Occurrence Type Classification for Establishing Prevention Plans Based on Industrial Accident Cases Using the KoBERT Model
Authors: Song Ju-Han , Shin Seung-Hyeon , Kang Sung-Yong , Won Jeong-Hun , Yoo Kwan-Hee
Published: October 2024

With increasing industrial sophistication and complexity, workplaces are increasingly prone to occupational accidents, causing negative impacts on workers and employers, including economic losses and decreased productivity. South Korea occupational safety and health has implemented new policies addressing potential risks to overcome stagnation in industrial accident reduction and predict site accidents from past cases. Cases are human-classified according to rules, including occurrence type or original causal materials. However, human errors, subjective judgments, synonyms, and terms incorrectly used by classifiers reduce original data quality and impede developments or applications of policies, technologies, and methods preventing accidents based on past accidents. This study proposes three artificial intelligence models to objectively classify the occurrence type of accident cases. Models are developed based on a natural language processing model (KoBERT), which considers Korean language characteristics. Each model is tested by sequentially performing sentence preprocessing, keyword replacement, and morphological analysis. The proposed Model 3 exhibits 93.1% accuracy, which was the highest among tested models. Up to three classification categories for occurrence type are allowed to assist objective classification. The accident case-based occurrence type classification model is effective for industrial accident prevention, aiding in strategy development and reducing social costs.
Assessment of Micropropagation Possibilities for Japanese Hascap (Lonicera caerulea var. emphyllocalyx L.)
Authors: Basara Oskar , Litwińczuk Wojciech , Gorzelany Józef
Published: October 2024

In recent years, interest in Lonicera caerulea production has grown significantly because of its nutritional and pharmaceutical benefits, leading to rapid expansion in its cultivation. L caerulea var. emphyllocalyx is a lesser-known botanical variety. Due to differences between plants of the Lonicera genus and the lack of scientific reports on micropropagation, it is necessary to determine the possibilities of in vitro propagation. The aim of this study was to elaborate a micropropagation protocol of two new breeding clones of Lonicera caerulea var. emphyllocalyx: ‘21–17’ and ‘139–24’. The experiments were carried out on in vitro cultures grown on MS medium supplemented with 1 mg·dm−3 BA or 1 mg·dm−3 mT. Two types of explants were used during the experiment: nodal fragments (NFs) and shoot-tips (STs). Before acclimatisation, some rooted microshoots were subjected to cooling at 4 °C for 4 weeks. Significantly more ST explants than NF explants started to grow at the proliferation stage. The application of BA resulted in much better proliferation and health of cultures. Cold storage of micropropagated ‘139–24’ plantlets significantly increased their survival in acclimatisation in contrast to ‘21–17’ plantlets but weakened further growth of the plants. In future in vitro studies on L. caerulea var. emphyllocalyx, BA can be used as the primary growth regulator due to its effectiveness and low cost. Nodal fragments should be considered as the main propagation material since they promote better growth rates. Additionally, further research is required to explore the effects of low-temperature storage on the growth and physiology of these plants. The results obtained in this research may contribute to the development of micropropagation technology in the future for L. caerulea var. emphyllocalyx.
A Coal Mine Excavation Tunnels Modeling Method Based on Point Clouds
Authors: Zhang Haoyuan , Mao Shanjun , Li Mei
Published: October 2024

The excavation tunnel model is an important reference for mine equipment control and tunnel deformation monitoring. Currently, tunnel models are mainly created manually, and point cloud reconstruction algorithms are difficult to directly apply to tunnel point clouds. To address these issues, this paper proposes a point cloud-based excavation tunnel modeling method. First, preprocessing algorithms such as point cloud coordinate transformation, tunnel point cloud extraction, and tunnel point cloud completion are used to filter out equipment point clouds inside the tunnel and repair occluded holes. Then, the tunnel centerline is extracted, and consistency optimization is performed on the point cloud normal vectors. Finally, a tunnel model is established based on the Poisson modeling algorithm, enabling high-precision tunnel modeling. The proposed algorithm’s accuracy and effectiveness are demonstrated through experiments on four different coal mine tunnels.
Signal Extension Method for Improved Range Resolution of Frequency-Modulated Continuous Wave Radar in Indoor Environments
Authors: Lee Seonyul , Kim Minsu , Jung Yunho , Lee Seongjoo
Published: October 2024

The range resolution of FMCW radar is critical for accurately distinguishing between multiple objects. Higher range resolution allows for better object separation and more precise location determination. While increasing the bandwidth can improve range resolution, it also raises costs and may be subject to regulatory constraints on the available frequency spectrum. This paper proposes an approach to enhance range resolution by increasing the effective bandwidth through signal processing, specifically by introducing the Estimated Signal Padding (ESP) method. ESP extends the bandwidth by lengthening the signal in the time domain, creating a synthesized signal for each target. The proposed algorithm can improve range resolution by a factor of at least 2.25. Unlike existing methods such as Zero Padding and Neural Network Padding, the proposed algorithm can distinguish targets of varying sizes rather than only targets of the same size. The performance of the algorithm has been validated through MATLAB simulations and FMCW radar experiments.
Citrus Seed Waste and Circular Bioeconomy: Insights on Nutritional Profile, Health Benefits, and Application as Food Ingredient
Authors: Seyyedi-Mansour S. , Carpena M. , Donn P. , Barciela P. , Perez-Vazquez A. , Echave J. , Pereira A. G. , Prieto M. A.
Published: October 2024

Citrus fruits are widely grown, processed, and distributed in more than 140 countries, with annual global production exceeding 124.3 million metric tons. This substantial consumption generates significant organic waste, accounting for approximately 50–60% of the total fruit mass, primarily in the form of peel, pulp, and seeds. Often discarded or reused as animal feed, these wastes contribute to significant environmental pollution and economic losses. Therefore, the valorization of these by-products represents an important opportunity to mitigate these challenges and improve the sustainability of the Citrus-related industry. This review highlights Citrus seed waste concerning its invaluable bioactive compounds, including fatty acids, phenolic compounds, limonoids, dietary fibers, vitamins, and carotenoids. Chemical compositions of Citrus seed biowaste differ depending on a variety of factors, such as Citrus variety, fruit maturity, environmental conditions, waste storage conditions, and extraction methods. The extraction and purification of phytochemicals from Citrus seed biowaste are one of the major procedures for valorizing waste. The two types of effective extraction methods are traditional (conventional extraction) and innovative (green extraction). Furthermore, Citrus seeds have been demonstrated to exhibit several biological activities and health-promoting properties including antioxidative, anti-inflammatory, and anti-cancer activities. Therefore, these wastes are safe and beneficial compounds used in the production of functional foods, nutraceuticals, pharmaceuticals, and cosmetics. A conclusion can be reached by emphasizing the abundance of bioactive compounds in Citrus seed wastes, which makes them an excellent opportunity for increased environmental and economic utilization.
Inhibition Performance and Mechanism of Poly(Citric Acid–Glutamic Acid) on Carbon Steel Corrosion in Simulated Seawater
Authors: Chang Nanxin , Liu Kuaiying , Zhao Yuzeng , Deng Yining , Ge Honghua
Published: October 2024

In this investigation, the efficacy of PCA-GLU, a polymer obtained by copolymerizing citric acid and glutamic acid, as a corrosion inhibitor for carbon steel was investigated in a 3.5wt% NaCl solution. Electrochemical impedance spectroscopy (EIS) techniques and potentiodynamic polarization (PDP) measurements were used to evaluate the corrosion inhibition. The findings demonstrate that PCA-GLU has a 96.73% corrosion inhibition efficiency. Additionally, when the inhibitor concentration rises, the corrosion inhibition efficiency rises as well, reaching an ideal concentration of 400 mg/L. Furthermore, PCA-GLU can create an adsorption layer on the surface of Q235. This paper verifies the adsorption mechanism of PCA-GLU through molecular dynamics simulations of the system and quantum chemical calculations of corrosion inhibitors in solution. Ultimately, our research findings validate that PCA-GLU is an efficient corrosion inhibitor in safeguarding carbon steel against corrosion in marine environments.
Finite-Time Pinning Event-Triggered Control for Bipartite Consensus of Hybrid-Order Heterogeneous Multi-Agent Systems with Antagonistic Links
Authors: Yu Xiangfeng , Yang Yongqing , Qing Nengneng
Published: October 2024

Finite-time consensus problem of hybrid-order heterogeneous multi-agent systems under a signed digraph topology is investigated in this paper. For heterogeneous multi-agent systems composed of first-order and second-order agents, a novel pinning event-triggered control protocol is devised to facilitate the attainment of the desired consensus state within a finite time. This control method overcomes communication barriers between first-order and second-order multi-agent systems, achieving effective control performance while reducing controller update frequency and communication costs. Based on graph theory and the Lyapunov stability method, several novel matrices are defined to address the finite-time consensus problem in hybrid-order multi-agent systems, and these matrices also facilitate the theoretical derivation process. Furthermore, it is demonstrated that the control protocol designed for hybrid-order systems is devoid of Zeno behavior. Finally, a detailed numerical example is supplied to illustrate the validity of the theoretical analysis.
Absorption Measurement in Ultrapure Crystalline Quartz with the Eliminated Influence of Ambient Air Absorption in the Time-Resolved Photothermal Common-Path Interferometry Scheme
Authors: Vlasova Ksenia , Makarov Alexandre , Andreev Nikolai
Published: October 2024

We demonstrate measurements of the absorption coefficient α ≈ 2.5 × 10−7 cm−1 in synthetic crystalline quartz at a wavelength of 1071 nm with a signal-to-noise ratio of 10/1 using the Time-resolved photothermal common-path interferometry (TPCI) scheme. It utilized cells filled with flowing argon and eliminated the influence of ambient air absorption. The scheme elements limiting the sensitivity of measurements at the level of ≈7.8 × 10−8 cm−1 were revealed. When these elements are replaced by better ones in terms of their thermal influence, the sensitivity of absorption coefficient measurements in crystalline quartz is ~10−8 cm−1. The calculation of the correction due to these optical elements of the values of the measured absorption coefficients is also described, which makes it possible to achieve the same sensitivity without replacing the elements. The improved scheme confirms the presence of the spatial inhomogeneity of absorption with a minimum coefficient of 2.5 × 10−7 cm−1 in synthetic crystalline quartz. The discrepancy of the absorption coefficient values in different regions of the crystal in the presented series of experiments was 2.5 × 10−7 cm−1 to 4 × 10−6 cm−1. Taking into account the ratio of thermo-optical parameters and the heat diffusion effect, the calculation shows that for quartz glasses the corresponding sensitivity of the absorption coefficient measurements equals ≈1.5 × 10−9 cm−1.
Multiple-Access Time and Frequency Transfer over Fiber and Free-Space Link Based on Optical Frequency Comb
Authors: Huang Wantao , Zhang Peng , Hou Dong
Published: October 2024

We have demonstrated a multiple-access transfer of time and frequency signal over a fiber and free-space link based on an optical frequency comb (OFC). With this transfer technique, two time–frequency signals were disseminated separately from a master site to two slave sites over a 3.9 km fiber and 100 m free-space link for 10,000 s. The timing fluctuations and instabilities of the time and frequency transfer were measured, estimated, and discussed. The experimental results show that the total root-mean-square (RMS) timing fluctuation of the transfer from site A to B is about 119 ps, with a fractional frequency instability on the order of 3.3 × 10−11 at 1 s and 2.8 × 10−14 at 2000 s. The RMS timing fluctuation of the transfer from site A to C is about 59.5 ps, with a fractional frequency instability on the order of 3.0 × 10−11 at 1 s and 2.6 × 10−14 at 2000 s. These results indicate that the multiple-access transfer technique proposed in this paper can provide important support for the application of a large-scale time–frequency synchronization network.
Evaluation of the Antecedent Saturation and Rainfall Conditions on the Slope Failure Mechanism Triggered by Rainfalls
Authors: Durukan Seda
Published: October 2024

The stability analysis of rainfall-induced slope failures considers a number of factors including the characteristics of the rainfall, vegetation, geometry of the slope, unsaturated soil characteristics, infiltration capacity, and saturation degree variations. Amongst all these factors, this study aims to investigate the effects of the antecedent rainfall and saturation conditions. A numerical modeling study was conducted using finite difference code software on a representative slope geometry with two different soil types. Two scenarios were followed: The first involved the application of three different rainfall intensities for varying initial saturation levels between 40% and 60%, representing the antecedent saturation conditions. The second scenario involved modeling successive rainfalls for a typical initial saturation degree of 50%. The impact of antecedent rainfall was assessed by determining the time required for failure during the application of a main extreme rainfall after a preceding rainfall of varying durations. Consequently, a zone of susceptible time for failure was suggested for use as a criterion in hazard management, allowing for the tracking of rainfall and its duration through the proposed chart for potential failures. Once the anticipated critical rainfall intensities have been determined through a meteorological analysis, a risk assessment for a specific slope can be conducted using the proposed practical procedure. Accordingly, a control mechanism may be established to detect the potential for a natural hazard. Furthermore, the proposed procedure was applied to a case study, whose modeling insights were in harmony with the real conditions of the slope failure. Thus, this demonstrated the significance of the antecedent conditions in modeling landslides triggered by rainfalls.
Shear Mechanical Behaviours and Size Effect of Band–Bedrock Interface: Discrete Element Method Simulation Insights
Authors: Wang Hao , Guo Xueyan , Liu Xinrong , Zhou Xiaohan , Xu Bin
Published: October 2024

The shear band is a prominent feature within the Banbiyan hazardous rock mass located in the Wushan section of the Three Gorges Reservoir area. This band constitutes a latent risk, as the potential for the rock mass to slide along the region threatens the safety of lives and property. Presently, the understanding of the shear mechanisms and the impact of shear band size on the band–bedrock interface is incomplete. In this study, based on band–bedrock shear laboratory tests, DEM simulation is used to investigate the shear-induced coalescence mechanism, stress evolution, and crack-type characteristics of the band–bedrock interface. In addition, the shear mechanical properties of samples considering specimen size, rock step height, and step width are further studied. The results show that the crack initiation and failure crack types observed in the first rock step are predominantly tensile. In contrast, the failure cracks in the remaining rock slabs and steps are primarily characterised by shear mode in addition to other mixed modes. The stress condition experienced by the first step is very near to the position of the applied point load, whereas the stress distribution across the remaining steps shows a more complex state of compressive–tensile stress. The relationship between shear parameters and sample size is best described by a negative exponential function. The representative elementary volume (REV) for shear parameters is suggested to be a sample with a geometric size of 350 mm. Notably, the peak shear strength and shear elastic modulus demonstrate a progressive increase with the rise in rock step height, with the amplifications reaching 91.37% and 115.83%, respectively. However, the residual strength exhibits an initial decline followed by a gradual ascent with increasing rock step height, with the amplitude of reduction and subsequent amplification being 23.73% and 116.94%, respectively. Additionally, a narrower rock step width is found to diminish the shear parameter values, which then tend to stabilise within a certain range as the step width increases.
Optimizing Assembly in Wiring Boxes Using API Technology for Digital Twin
Authors: Cazacu Carmen-Cristiana , Iorga Ioana , Parpală Radu Constantin , Popa Cicerone Laurențiu , Coteț Costel Emil
Published: October 2024

This study explores the automation enhancement in the assembly process of wiring harnesses for automotive applications, focusing on manually inserting fuses and relays into boxes—a task known for quality and efficiency challenges. This research aimed to address these challenges by implementing a robotic arm integrated with API technology for digital twin. The methods used included the development of a digital twin model to simulate and monitor the assembly process, supported by real-time adjustments and optimizations. The results showed that the robotic system significantly improved the accuracy and speed of fuse insertion, reducing the insertion errors typically seen in manual operations. The conclusions drawn from the research confirm the feasibility of using robotic automation supported by digital twin technology to enhance assembly processes in automotive manufacturing, promising substantial improvements in production efficiency and quality control.
Stratigraphic Division Method Based on the Improved YOLOv8
Authors: Tang Lu , Li Tingting , Xu Chengwu
Published: October 2024

With the deepening of oilfield development, logging data proliferate, and their complexity makes manual stratigraphic division both difficult and time-consuming. Aimed at the current network model widely used to solve the problem of stratigraphic delineation, which has problems such as not considering the multi-scale features of logging curves and insufficient accuracy, the YOLOv8x target detection algorithm in deep learning is utilized to detect the target strata, which has the ability to characterize the multi-scale features and can improve the efficiency and accuracy of the division. In order to better localize and identify targets, this paper proposes a new stratigraphic automatic division method, YOLOv8x-CAMDP, which introduces a CA (Coordinate Attention) mechanism module into the original YOLOv8x model to improve the model’s ability to identify stratigraphic interval boundaries. In addition, the CIOU loss function in the original YOLOv8x network model was replaced using the MDPIOU loss function to effectively improve the accuracy and efficiency of bounding box regression. Based on the logging data from the Xing 10 area pure oil zone, a thorough comparison of the YOLOv8x-CAMDP and YOLOv8x models’ training results is presented. The YOLOv8x-CAMDP model achieves a mean Average Precision (mAP) value of 98.7%, outperforming the YOLOv8x model by one percentage point. Moreover, the YOLOv8x-CAMDP model demonstrates greater precision in boundary division for each stratigraphic interval. The application of the YOLOv8x-CAMDP model to project implementation achieved significant results in stratigraphic division, reduced workload, and optimized manual division. These results not only confirm the practical value of the YOLOv8x-CAMDP model but also demonstrate the prospect and potential of its wide application.
Fault Diagnosis and Prognosis of Satellites and Unmanned Aerial Vehicles: A Review
Authors: Hedayati MohammadSaleh , Barzegar Ailin , Rahimi Afshin
Published: October 2024

This paper comprehensively analyzes advanced Fault Diagnosis and Prognosis (FDP) techniques employed in aerial and space agents such as satellites, spacecraft, and Unmanned Aerial Vehicles (UAVs). The critical engineering functions of fault diagnostics and prognosis, particularly the emerging field of fault prognosis, emphasize the necessity for further advancement. Integrating these methodologies enriches the system’s capacity to diagnose faults in their early stages. Additionally, it enables the prediction of fault propagation and facilitates proactive maintenance to mitigate the risk of severe failure. This paper aims to introduce diverse FDP methods, followed by a discussion on their application and evolution within single and multisatellite/UAV systems. Throughout this review, eighty-five relevant works are analyzed and discussed and their evaluation metrics are expanded upon as well. Within the works analyzed in this review, it was found that data-driven methods constitute 54% and 7% of the methodologies utilized in single- and multiagent FDP, respectively, which underscores the rise of these methods in the field of single-agent FDP and their unexplored potential in multiagent condition monitoring. Finally, this review is brought to a close with a suggested classification scheme of the utilized methodologies in the field, a quantitative analysis of their contributions to the field, and remarks and mentions of the potential gaps in the area.
BAT-Transformer: Prediction of Bus Arrival Time with Transformer Encoder for Smart Public Transportation System
Authors: Jeong Suhyun , Oh Changsong , Jeong Jongpil
Published: October 2024

In urban public transportation systems, the accuracy of bus arrival time prediction is crucial to reduce passenger waiting time, increase satisfaction, and ensure efficient transportation operations. However, traditional bus information systems (BISs) rely on neural network models, which have limited prediction accuracy, and some public transportation systems have non-fixed or irregular arrival times, making it difficult to directly apply traditional prediction models. Therefore, we used a Transformer Encoder model to effectively learn the long-term dependencies of time series data, and a multi-headed attentional mechanism to reduce the root mean square error (RMSE) and lower the mean absolute percentage error (MAPE) compared to other models to improve prediction performance. The model was trained on real bus-operation data collected from a public data portal covering the Gangnam-gu area of Seoul, Korea, and data preprocessing included missing value handling, normalization and one-hot encoding, and resampling techniques. A linear projection process, learnable location-encoding technique, and a fully connected layer were applied to the transformer-encoder model to capture the time series data more precisely. Therefore, we propose BAT-Transformer, a method that applies a linear projection process, learnable location-encoding technique, and a fully connected layer using bus data. It is expected to help optimize public transportation systems and show its applicability in various urban environments.
The Functional Resonance Analysis Method (FRAM) Application in the Healthcare Sector: Lessons Learned from Two Case Studies on Medical Device Management
Authors: Fargnoli Mario , Murgianu Luca , Tronci Massimo
Published: October 2024

In the recent literature, numerous tools have been found that have been used to evaluate and improve the resilience of socio-technical systems such as hospitals. The Functional Resonance Analysis Method (FRAM) is certainly one of the most diffused, as it can provide information on the system structure and its components through a systemic analysis approach. FRAM has been successfully applied in different contexts. However, in the healthcare sector, only a few studies propose practical analyses that can support practitioners in systematically observing and analyzing events, both when things go right and when they go wrong. To reduce such a research gap, the current study focuses on the application of FRAM to two different case studies: (1) an accident that occurred in a hyperbaric oxygen therapy unit, and (2) the risk assessment of a magnetic resonance imaging unit. The results show the effectiveness of FRAM in detecting discrepancies and vulnerabilities in the practical management of these devices, providing valuable insights not only regarding the analysis of adverse events (i.e., retrospectively) but also concerning the improvement of safety procedures (i.e., prospectively).
Applying Molecular Modeling to Predict Novel FmlH-Binding Glycomimetics with Improved Pharmacokinetic Properties for the Prevention of Urinary Tract Infections
Authors: Samanta Priyanka , Doerksen Robert J.
Published: October 2024

Urinary tract infections (UTIs) affect nearly 50% of women in their lifetime. Uropathogenic Escherichia coli (UPEC) expresses F9/Fml pili tipped with the protein FmlH that specifically bind to terminal galactoside and galactosaminoside units in glycoproteins on kidney and bladder cells and colonize host tissues. The traditional UTI treatment using excessive antibiotics has led to the rise in various UPEC antibiotic-resistant strains. An alternative therapeutic approach prevents the initial bacterial attachment on the host cells using competitive FmlH-binding inhibitors. In this study, we used computer-aided drug design techniques to identify novel glycomimetics that are predicted to bind strongly to and inhibit the UPEC FmlH. We performed in silico receptor-based and ligand-based scaffold hopping, and molecular docking to predict novel FmlH-binding glycomimetics with high chemical synthesizability. We replaced the two major scaffolds of the most potent known FmlH-binding ligand to obtain novel compounds. Additionally, we applied global machine-learning models to predict the ADMET properties of the molecules. Compounds with low ADMET risks were subjected to molecular dynamics simulations and a detailed investigation of the FmlH–glycomimetic interactions was performed. We have prepared and supplied a library of 58 novel glycomimetics that can be subjected to further biological activity studies.
Dynamic Analysis of Tethered Satellites with a Payload Moving Along a Flexible Tether
Authors: Ahn Yohan , Jang Woojae , Lee Jeonga , Chung Jintai
Published: October 2024

This study investigates the dynamic behavior of a three-body tethered satellite system with a flexible tether, focusing on a scenario in which a payload is transported along the tether connecting two satellites. Traditional models use rigid tethers, limiting the analysis of complex dynamics such as tether deformation, slack, and rebound. To address these limitations, we employed the absolute nodal coordinate formulation (ANCF) to model the flexibility of the tether. We derived nonlinear equations of motion using Lagrange’s equation and solved them using the Newmark time integration method to obtain the dynamic responses of the satellite system. Our findings revealed that the Coriolis effect caused significant deviations in the payload trajectory as its mass and speed increased, leading to greater tether deformation and slack, and potential system destabilization. Additionally, axial force fluctuations in the tether varied notably as the payload moved, transitioning between tensile and compressive states. This study provides a more accurate representation of three-body tethered satellite systems by incorporating tether flexibility, offering valuable insights into the dynamic behavior and stability of the system.
On the Use of Machine Learning and Key Performance Indicators for Urban Planning and Design
Authors: Ammouriova Majsa , Tsertsvadze Veronika , Juan Angel A. , Fernandez Trinidad , Kapetas Leon
Published: October 2024

Global efforts to achieve climate neutrality increasingly rely on innovative urban planning and design strategies. This study focuses on the identification and application of key performance indicators (KPIs) to support policymakers and local authorities in driving sustainable urban transitions. Using a real-life case study of European cities and countries, this research leverages data analytics and machine learning to inform decision-making processes. Specifically, the k-means clustering algorithm was employed to group countries based on socioeconomic and environmental KPIs, while principal component analysis was used to rank the most influential indicators in shaping these clusters. The analysis highlighted GDP per capita, corruption perception, and climate-related expenditure as key drivers of clustering. Additionally, time series analysis of KPI trends demonstrated the impact of policy decisions over time. This study showcases how machine learning and data-driven approaches can provide valuable insights for urban planners, offering a robust framework for evaluating and improving climate-neutrality strategies at both city and country levels.
WRF-ROMS-SWAN Coupled Model Simulation Study: Effect of Atmosphere–Ocean Coupling on Sea Level Predictions Under Tropical Cyclone and Northeast Monsoon Conditions in Hong Kong
Authors: Leung Ngo-Ching , Chow Chi-Kin , Lau Dick-Shum , Lam Ching-Chi , Chan Pak-Wai
Published: October 2024

The Hong Kong Observatory has been using a parametric storm surge model to forecast the rise of sea level due to the passage of tropical cyclones. This model includes an offset parameter to account for the rise in sea level due to other meteorological factors. By adding the sea level rise forecast to the astronomical tide prediction using the harmonic analysis method, coastal sea level prediction can be produced for the sites with tidal observations, which supports the high water level forecast operation and alert service for risk assessment of sea flooding in Hong Kong. The Coupled Ocean-Atmosphere-Wave-Sediment Transport (COAWST) Modelling System, which comprises the Weather Research and Forecasting (WRF) Model and Regional Ocean Modelling System (ROMS), which in itself is coupled with wave model WaveWatch III and nearshore wave model SWAN, was tested with tropical cyclone cases where there was significant water level rise in Hong Kong. This case study includes two super typhoons, namely Hato in 2017 and Mangkhut in 2018, three cases of the combined effect of tropical cyclone and northeast monsoon, including Typhoon Kompasu in 2021, Typhoon Nesat and Severe Tropical Storm Nalgae in 2022, as well as two cases of monsoon-induced sea level anomalies in February 2022 and February 2023. This study aims to evaluate the ability of the WRF-ROMS-SWAN model to downscale the meteorological fields and the performance of the coupled models in capturing the maximum sea levels under the influence of significant weather events. The results suggested that both configurations could reproduce the sea level variations with a high coefficient of determination (R2) of around 0.9. However, the WRF-ROMS-SWAN model gave better results with a reduced RMSE in the surface wind and sea level anomaly predictions. Except for some cases where the atmospheric model has introduced errors during the downscaling of the ERA5 dataset, bias in the peak sea levels could be reduced by the WRF-ROMS-SWAN coupled model. The study result serves as one of the bases for the implementation of the three-way coupled atmosphere–ocean–wave modelling system for producing an integrated forecast of storm surge or sea level anomalies due to meteorological factors, as well as meteorological and oceanographic parameters as an upgrade to the two-way coupled Operational Marine Forecasting System in the Hong Kong Observatory.
Self-Perceived Stress and the Personality of Mothers of Children with Central Auditory Processing Disorder, as Well as in Mothers of Typically Developing Children, Before and Late in the COVID-19 Pandemic
Authors: Kobosko Joanna , Śliwa Lech , Ganc Malgorzata , Jedrzejczak W. Wiktor , Skarzynski Henryk
Published: October 2024

Objectives: This study aims to measure, at two time points, the relationship between self-perceived global stress and the personality traits of the mothers of children who have central auditory processing disorder (APD) and compare it with the results from mothers of typically developing (TD) children. The comparisons were made before the COVID-19 pandemic, as well as late in the pandemic. Methods: The level of stress was assessed using the Perceived Stress Scale (PSS-10), while the Short Big Five Markers (IPIP-BFM-20) were used to assess Big Five personality traits. The study used two independent samples: one evaluated before the COVID-19 pandemic and the other late in the pandemic. Each sample consisted of 108 mothers of children with APD and 79 mothers whose children did not have APD (TD children) as controls. Results: The average global stress levels were similar in mothers of children with APD and in mothers of TD children, both before and in the late stage of the COVID-19 pandemic. During the late stage, both sets of mothers scored similarly on all personality dimensions, but significantly, mothers of TD children exhibited lower emotional stability compared to during the pre-pandemic period. In both groups, emotional stability predicted global stress level at both time points; however, during the pandemic, conscientiousness also became a predictor of global stress level but only in the group of mothers of TD children. Conclusions: Mothers of APD children might be more resistant to additional stressors. It would be prudent to watch mothers of APD and TD children for signs of needing psychological intervention.
State-of-the-Art on the Impact of Bimodal Acoustic Stimulation on Speech Perception in Noise in Adults: A Systematic Review
Authors: Casarella Antonio , Notaro Anna , Laria Carla , Serra Nicola , Genovese Elisabetta , Malesci Rita , Auletta Gennaro , Fetoni Anna Rita
Published: October 2024

Background/Objectives: Bimodal stimulation (BS), which combines the use of a cochlear implant (CI) in one ear and a hearing aid (HA) in the opposite ear, is an established strategy to treat hearing loss by exploiting the unique capabilities of each device. CIs stimulate the auditory nerve by bypassing damaged hair cells, while HAs amplify sounds by requiring a functional hearing residual. The aim of this systematic review is to investigate the advantages and disadvantages of BS such as speech perception in noise. Methods: We examined clinical studies published from October 2020 to July 2024, following the PRISMA guidelines, focusing on the advantages and disadvantages of BS on speech perception in noise in adulthood. Results: BS in adult patients significantly improves speech perception in quiet and noisy environments, especially for those with increased residual hearing. Unilateral CIs and BS perform similarly in quiet conditions, but BS significantly improves speech discrimination in noisy environments if loudness between the two devices is appropriately balanced. Conclusions: Directional microphones and programming software are new technologies that succeed in reducing environmental noise and improving verbal perception outcomes, although their features in the literature are controversial. In addition, the individuals using BS may face temporal mismatches mainly due to differing device latencies, affecting sound localization. Compensating for these mismatches can enhance localization accuracy. However, modulated noise remains a significant obstacle to verbal perception in noise. Valuable assessment tools such as music tests provide further information on hearing performance and quality of life. More research is needed to define certain selection criteria.
A Penalty Method for Elliptic Variational–Hemivariational Inequalities
Authors: Sofonea Mircea , Tarzia Domingo A.
Published: October 2024

We consider an elliptic variational–hemivariational inequality P in a real reflexive Banach space, governed by a set of constraints K. Under appropriate assumptions of the data, this inequality has a unique solution u∈K. We associate inequality P to a sequence of elliptic variational–hemivariational inequalities {Pn}, governed by a set of constraints K˜⊃K, a sequence of parameters {λn}⊂R+, and a function ψ. We prove that if, for each n∈N, the element un∈K˜ represents a solution to Problem Pn, then the sequence {un} converges to u as λn→0. Based on this general result, we recover convergence results for various associated penalty methods previously obtained in the literature. These convergence results are obtained by considering particular choices of the set K˜ and the function ψ. The corresponding penalty methods can be applied in the study of various inequality problems. To provide an example, we consider a purely hemivariational inequality that describes the equilibrium of an elastic membrane in contact with an obstacle, the so-called foundation.
Tackling Microbial Contamination: Safesink Solution with Silver-Coated Microspheres
Authors: Zumaquero Eulalia , Terrado David , de Llanos Rosa , Puerta Marina , Cejudo Rocío , Gómez-Tena María Pilar
Published: October 2024

Ceramic and vitreous materials can be functionalized to exhibit biocidal activity. This research evaluates the biocidal properties of silver-modified vitreous microspheres designed to be included in water endpoints and siphons to prevent nosocomial diseases produced in hospital environments. The microspheres obtained from a coating and heat treatment process at 650 °C have been chemically and microstructurally characterized using Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES), Wavelength Dispersive X-ray Fluorescence (WD-XRF), Scanning Electron Microscopy (FEG-SEM) and Energy-dispersive X-ray Microanalysis (EDS) to determine how silver particles are distributed in the glassy matrix and to relate their bactericidal capacity by means of leaching tests. Microbiological tests have been performed against microorganisms such as Staphylococcus aureus, Pseudomonas aeruginosa, Escherichia coli, and Candida auris. The results revealed that these silver-coated microspheres had significant bactericidal activity, with a significant reduction in the population of E. coli, C. auris, and P. aeruginosa, with no cytotoxic effect of these microspheres.
Automatic Generation of Medical Case-Based Multiple-Choice Questions (MCQs): A Review of Methodologies, Applications, Evaluation, and Future Directions
Authors: Al Shuraiqi Somaiya , Aal Abdulsalam Abdulrahman , Masters Ken , Zidoum Hamza , AlZaabi Adhari
Published: October 2024

This paper offers an in-depth review of the latest advancements in the automatic generation of medical case-based multiple-choice questions (MCQs). The automatic creation of educational materials, particularly MCQs, is pivotal in enhancing teaching effectiveness and student engagement in medical education. In this review, we explore various algorithms and techniques that have been developed for generating MCQs from medical case studies. Recent innovations in natural language processing (NLP) and machine learning (ML) for automatic language generation have garnered considerable attention. Our analysis evaluates and categorizes the leading approaches, highlighting their generation capabilities and practical applications. Additionally, this paper synthesizes the existing evidence, detailing the strengths, limitations, and gaps in current practices. By contributing to the broader conversation on how technology can support medical education, this review not only assesses the present state but also suggests future directions for improvement. We advocate for the development of more advanced and adaptable mechanisms to enhance the automatic generation of MCQs, thereby supporting more effective learning experiences in medical education.
Appropriate Prescription of Non-Steroidal Anti-Inflammatory Drugs in Geriatric Patients—A Systematic Review
Authors: Costa Carolina , Soares Diana , Borges Ana , Gonçalves Ana , Andrade José Paulo , Ribeiro Hugo
Published: October 2024

The elderly population is growing worldwide. Non-steroidal anti-inflammatory drugs (NSAIDs) are commonly prescribed, but their adverse events can pose significant risks. Different NSAID molecules can exhibit varying risk profiles. This study aims to evaluate the cardiovascular, gastrointestinal, and renal safety profiles of ibuprofen, naproxen, acemetacin, diclofenac, celecoxib, and etoricoxib in elderly patients. A comprehensive literature search was conducted in PubMed and Cochrane Library. For the selection of articles, we used Medical Subject Headings (MeSH) terms “aged” sequentially and together with “ibuprofen”, “diclofenac”, “naproxen”, “acemetacin”, “celecoxib”, and “etoricoxib”. To assess the quality and interest of the articles, four independent reviewers screened titles and abstracts to identify potentially eligible studies. Strength of Recommendation Taxonomy (SORT) was used to rate the quality of individual studies and to establish recommendation strengths (RS). From 2086 articles identified, 39 studies met the inclusion criteria. Twenty studies analyzed cardiovascular safety, fourteen gastrointestinal safety, and four renal safety. When CV risk is the main concern celecoxib or naproxen are a good first choice (RS B). In high GI risk addition of PPI to naproxen or celecoxib use should be recommended (RS A). When renal function is on focus, celecoxib remains as first line of therapy (RS A). Diclofenac in the geriatric population should be avoided (RS B). Celecoxib is a good choice for elderly patients for whom it is difficult to direct pain treatment based on a single known risk factor (RS B).