bluuebunny/crossref_metadata_2025 huggingface dataset:
NAS-CRE: Neural Architecture Search for Context-Based Relation Extraction
Authors: Yan Rongen , Li Dongmei , Wu Yan , Dang Depeng , Tao Ye , Wang Shaofei
Published: November 2024

Relation extraction, a crucial task in natural language processing (NLP) for constructing knowledge graphs, entails extracting relational semantics between pairs of entities within a sentence. Given the intricacy of language, a single sentence often encompasses multiple entities that mutually influence one another. Recently, various iterations of recurrent neural networks (RNNs) have been introduced into relation extraction tasks, where the efficacy of neural network structures directly influences task performance. However, many neural networks necessitate manual determination of optimal parameters and network architectures, resulting in limited generalization capabilities for specific tasks. In this paper, we formally define the context-based relation extraction problem and propose a solution utilizing neural architecture search (NAS) to optimize RNN. Specifically, NAS employs an RNN controller to delineate an RNN cell, yielding an optimal structure to represent all relationships, thereby aiding in extracting relationships between target entities. Additionally, to enhance relation extraction performance, we leverage the XLNet pretrained model to comprehensively capture the semantic features of the sentence. Extensive experiments conducted on a real-world dataset containing words with multiple relationships demonstrate that our proposed method significantly enhances micro-F1 scores compared to state-of-the-art baselines.
Integrating BIM and GIS for an Existing Infrastructure
Authors: Cepa J. J. , Alberti M. G. , Pavón R. M. , Calvo Juan A.
Published: November 2024

Data-driven digital transformation is becoming increasingly relevant. Building information modelling (BIM) and geographic information systems (GIS) are two technologies specific to the construction industry. The two approaches are different, but complementary. In this article, BIM–GIS integration is approached from some of the most relevant aspects, such as standardization or level of detail, and a comparison between both approaches is presented with the aim of improving the operation and maintenance of urban infrastructure. By means of the Madrid Calle 30 ring road as a case study, the integration of the BIM model of the road in a GIS scenario using the IFC and SLPK formats is shown. The information is stored in an external database, which allows updates without modifying the 3D model and facilitates the inclusion of real-time data. The study highlights the challenges of interoperability between BIM and GIS, as well as the need for open standards and software tools that enable a wider implementation in the FM of this type of infrastructure.
Predicting Crash-Related Incident Clearance Time on Louisiana’s Rural Interstate Using Ensemble Tree-Based Learning Methods
Authors: Khan Waseem Akhtar , Moomen Milhan , Rahman M. Ashifur , Terkper Kelvin Asamoah , Codjoe Julius , Gopu Vijaya
Published: November 2024

Traffic crashes contribute significantly to non-recurrent congestion, thereby increasing delays, congestion pollution, and other challenges. It is important to have tools that enable accurate prediction of incident duration to reduce delays. It is also necessary to understand factors that affect the duration of traffic crashes. This study developed three machine learning models, namely extreme gradient boosting (XGBoost), categorical boosting (CatBoost), and a light gradient-boosting machine (LightGBM), to predict crash-related incident clearance time in Louisiana rural interstates and utilized Shapley additive explanations (SHAP) analysis to determine the influence of factors impacting it. Four ICT levels were defined based on 30 min intervals: short (0–30), medium (31–60), intermediate (61–90), and long (greater than 90). The results suggest that XGBoost outperforms CatBoost and LightGBM in the collective model’s predictive performance. It was found that different features significantly affect different ICT levels. The results indicate that crashes involving injuries, fatalities, heavy trucks, head-on collisions, roadway departure, and older drivers are the significant factors that influence ICT. The results of this study may be used to develop and implement strategies that lead to reduced incident duration and related challenges with long clearance times, providing actionable insights for traffic managers, transportation planners, and incident response agencies to enhance decision-making and mitigate the associated increases in congestion and secondary crashes.
Adaptive Control Parameter Optimization of Permanent Magnet Synchronous Motors Based on Super-Helical Sliding Mode Control
Authors: Kong Lingtao , Zhang Hongxin , Zhang Tiezhu , Wang Junyi , Yang Chaohui , Zhang Zhen
Published: November 2024

Optimizing control rate parameters is one of the key technologies in motor control systems. To address the issues of weak robustness and slow response speed in traditional adaptive control strategies, an adaptive control system based on sliding mode control is proposed to enhance the overall performance of permanent magnet synchronous motors. The Non-dominated Sorting Genetic Algorithm II and Multi-objective Particle Swarm Optimization are employed to effectively optimize control parameters, thereby mitigating motor torque and speed overshoot. A Partial Sample Shannon Entropy Evaluation method, leveraging entropy theory in conjunction with the Z-score method, is introduced to facilitate the feedback regulation of the optimization process by assessing motor output torque. Simulation results confirm that the proposed control strategy, in combination with the optimized control rate parameters, leads to substantial improvements in motor performance. Compared to traditional adaptive control strategies, the proposed approach improves the motor’s steady-state response speed by 42% and reduces rotor error during system fluctuations by 23%, significantly enhancing the motor’s response speed and robustness. Following parameter optimization, speed and torque overshoot are reduced by 38% and 10%, respectively, resulting in a significant improvement in the stability and precision of the motor control system.
Optimal Routing of Gas Pipelines in Seismic Regions Using an Efficient Decision-Support Tool: A Case Study in Northern Greece
Authors: Makrakis Nikolaos , Psarropoulos Prodromos N. , Tsompanakis Yiannis
Published: November 2024

High-pressure gas pipelines are significantly vulnerable to earthquake-related geohazards (tectonic faulting, slope instabilities, and/or soil liquefaction phenomena). Avoiding geohazardous areas is not always techno-economically feasible, as it would increase the length and cost of the infrastructure. Conversely, crossing these areas may adversely affect the structural performance of the pipeline, leading to unfeasible mitigation measures. Thus, selecting cost-effective, safe, and resilient routing is crucial. This study presents a GIS-based decision-support tool for optimal routing, taking into account, among other criteria, earthquake-related geohazards. The proposed tool considers not only the aforementioned but also more complex earthquake-related geohazards, such as secondary fault ruptures that are non-parallel or even perpendicular to the main fault, which might have been overlooked during the design of existing pipelines. To validate its effectiveness, the present tool is applied in a real case study in northern Greece, where the aforementioned earthquake-related geohazards coexist. Through a GIS-based multi-criteria decision method, various scenarios are examined by assigning different weights to the adopted criteria, and several cost-minimized routes are derived. This tool could be highly beneficial for the pipeline industry since it can assist operators and stakeholders in selecting the optimal pipeline route in geohazardous areas.
Recycled Carbonyl Iron-Biodegradable PLA Auxetic Composites: Investigating Mechanical Properties of 3D-Printed Parts Under Quasi-Static Loading
Authors: Bozorgnia Tabary Seyed Amir Ali , Karimi Naeim , Fayazfar Haniyeh (Ramona)
Published: November 2024

Auxetic structures showcase notable properties such as high indentation resistance, shear stiffness, fracture toughness, and acoustic energy absorption. Recent advancements in additive manufacturing have facilitated the creation of complex auxetic designs, but there has been less emphasis on developing new materials. This study focuses on using recycled iron powders mixed with biodegradable polymers by using the solution casting method to create sustainable, 3D-printable materials for energy absorption applications. This research involved examining a 2D re-entrant structure, evaluating the effects of varying iron powder concentrations in the polymer. The analyses included thermogravimetric analyses, differential scanning calorimetry, and microstructural examination, alongside compression tests to assess strength and absorption capabilities. The most effective 3D-printed composite, containing 10% iron powders, demonstrated a substantial improvement in specific energy absorption (SEA of 2.051 kJ/kg compared to neat PLA with an SEA of 0.160 kJ/kg) and exhibited favorable mechanical and thermal properties. The TGA showed that adding iron powder reduced PLA’s onset degradation temperature from 340 °C to 310 °C, 295 °C, and 270 °C for 5%, 10%, and 15% iron, respectively, confirming iron’s catalytic effect on PLA degradation. The DSC analysis showed that adding iron powder increased the degree of crystallinity from 5.63% for pure PLA to 5.77%, 6.79%, and 6.91% for 5%, 10%, and 15% iron, respectively, indicating iron’s role as a nucleation agent. These results highlight the potential of novel iron/PLA 2D re-entrant composites for energy-absorbent applications, emphasizing sustainability and cost-effectiveness.
Deep Learning Forecasting Model for Market Demand of Electric Vehicles
Authors: Simsek Ahmed Ihsan , Koç Erdinç , Desticioglu Tasdemir Beste , Aksöz Ahmet , Turkoglu Muammer , Sengur Abdulkadir
Published: November 2024

The increasing demand for electric vehicles (EVs) requires accurate forecasting to support strategic decisions by manufacturers, policymakers, investors, and infrastructure developers. As EV adoption accelerates due to environmental concerns and technological advances, understanding and predicting this demand becomes critical. In light of these considerations, this study presents an innovative methodology for forecasting EV demand. This model, called EVs-PredNet, is developed using deep learning methods such as LSTM (Long Short-Term Memory) and CNNs (Convolutional Neural Networks). The model comprises convolutional, activation function, max pooling, LSTM, and dense layers. Experimental research has investigated four different categories of electric vehicles: battery electric vehicles (BEV), hybrid electric vehicles (HEV), plug-in hybrid electric vehicles (PHEV), and all electric vehicles (ALL). Performance measures were calculated after conducting experimental studies to assess the model’s ability to predict electric vehicle demand. When the performance measures (mean absolute error, root mean square error, mean squared error, R-Squared) of EVs-PredNet and machine learning regression methods are compared, the proposed model is more effective than the other forecasting methods. The experimental results demonstrate the effectiveness of the proposed approach in forecasting the electric vehicle demand. This model is considered to have significant application potential in assessing the adoption and demand of electric vehicles. This study aims to improve the reliability of forecasting future demand in the electric vehicle market and to develop relevant approaches.
Observation and Numerical Simulation of a Windshear Case at an Airport in the Qinghai-Tibet Plateau
Authors: Chan Pak Wai , Lai Kai Kwong , Zheng Jiafeng , Zhang Yu , Chen Haoming , Shi Xiaoming
Published: November 2024

This paper documents a windshear case for an airport in the Qinghai-Tibet Plateau and explores, for the first time, the capability for high-resolution numerical weather simulation of the wind shear features. The windshear appears to be associated with pulses of the wind speed in a low-level easterly jet. The features are basically reproduced quite well with the high-resolution numerical model, though some discrepancies are identified, such as the maximum wind speed of the easterly jet and the magnitude of the eddy dissipation rate as compared with the actual Doppler LIDAR observations. Statistical analysis has been performed between the observation and the simulation results. The sensitivity of the modeling result to the choice of turbulence parameterization scheme has also been studied. The study result shows that it is possible to forecast the windshear feature using a high-resolution numerical weather prediction model for an airport in the complex terrain of the Plateau.
Evaluation of Horizontal Shear Performance of Composite Girders Using Separable Shear Connectors
Authors: Jung Dae-Sung , Park Se-Hyun , Han Jong-Wook , Kim Chul-Young
Published: November 2024

The increased volume of heavy vehicles and use of de-icing agents on concrete bridge decks accelerates the deterioration of these structures. Therefore, the rapid replacement of these structures has attracted considerable attention, with prefabricated bridges being the preferred option. Conventionally, horizontal shear connections between girders and precast decks have incorporated rebar stirrup shear connectors. Although effective for initial construction, this method renders dismantling of aged decks complex, because rebar connectors are fully embedded within girders. This study introduced an embedded separable shear connector that minimizes deck-breaking and facilitates easy reinstallation by the simple separation of the deck from the girder. Horizontal shear and flexural tests on composite girders and comparisons with various design codes were conducted to evaluate this connector. The results of horizontal shear tests confirmed that securing sufficient embedment depth is necessary to prevent the pull-out failure of shear connectors. Additionally, prestressed concrete composite girder flexural tests with improved design verified that the detachable shear connectors exhibited an approximately 60% improvement in flexural performance compared with conventional reinforcement shear connectors.
Toxic Metals Migration from Plastic Food Contact Materials in Romania: A Health Risk Assessment
Authors: Mustatea Gabriel , Mocanu Andreea L. , Stroe Corina A. , Ungureanu Elena L.
Published: November 2024

Food packaging plays an essential role in preserving food quality. However, heavy metals found in packaging materials—whether intentionally incorporated or not—can migrate into food. This study aims to evaluate the migration of specific heavy metals (Ba, Co, Cu, Zn, Al, Ni, Li, Fe, Pb, Cd, Cr, Sb) from plastic food packages (films and bags) obtained from various materials (PE, PP, PVC, composite materials) into food simulant B (3% acetic acid) using inductively coupled plasma mass spectrometry (ICP-MS). Migration tests was conducted according to EU regulations, using OM2 conditions (10 days at 40 °C). The obtained results were lower than the specific migration limits set by EU Regulation no. 10/2011 (Annex II). Both carcinogenic and non-carcinogenic risk assessments were carried out based on the specific migration data, estimating the exposure, average daily dose (ADD), hazard quotient (HQ), hazard index (HI), cancer risk (CR), and total cancer risk (TCR). The exposure values were found to be below the recommended tolerable daily intake (TDI) levels for each metal tested. Both HQ and HI values were under the limit value of 1. The average total cancer risk was 1.73 × 10−4, indicating that approximately 1.73 consumers out of 10,000 may develop a type of cancer due to chronic exposure to the tested metals. These results highlight the importance of continuous monitoring of chemical migrants from food contact materials.
Characteristics of Pervious Concrete with Activated-Sludge Biological Fermentation
Authors: Zhang Yongsheng , Jia Xuechen , Li Bingqi , Zhao Weilong , Pan Wenyan , Liu Jianfei , Yuan Pengfei
Published: November 2024

This study investigates the performance of sludge-added pervious concrete (SPC) at different curing temperatures by replacing some of the cement with activated sludge (AS). The results reveal that the incorporation of AS into pervious concrete had a favorable impact. At a curing temperature of 30 °C, the 28-day compressive strength and specific surface area reached 20.8 MPa and 9.14 m2/g, respectively, representing a 60% and 98.7% increase, in comparison to conventional concrete. Furthermore, the addition of AS to the concrete results in a notable reduction in the concentration of chemical oxygen demand (COD) in surface runoff water. The maximum rate of COD removal observed was 55.6%. A mechanism study revealed that the strength of concrete increased due to the reaction between reactive SiO2 in AS and CaO in the aggregate. At a temperature of 30 °C, the microorganisms in the activated sludge fermentation process exhibit a higher production rate of fermentation gas, resulting in a greater escape of gas and an increase in the number of micropores in the permeable concrete. This leads to an enhanced specific surface area, which in turn exhibits a superior adsorption effect on COD.
Impact of Childhood Food Allergy on Quality of Life: A Systematic Review
Authors: Valero-Moreno Selene , Torres-Llanos Rocío , Pérez-Marín Marián
Published: November 2024

Background: Food allergy is the third most commonly diagnosed allergic disorder in children, particularly during infancy and preschool years. Its prevalence has been rising rapidly in recent years, making it a significant public health concern. This study aims to conduct a systematic review of the impact of childhood food allergies on quality of life. Methods: A comprehensive search of databases from the last five years was conducted following the PRISMA guidelines, resulting in the selection of 21 relevant articles. Results: The findings indicate that food allergies significantly reduce children’s quality of life, with age, the number of allergens, and allergy severity being key determinants. Affected children experience higher levels of anxiety, depression, and reduced psychosocial functioning. Caregivers also face substantial burdens, including constant concerns over accidental exposure, limitations in social activities, financial strain, and increased work absences. In school settings, these children are more prone to teasing or bullying, highlighting the need for increased education and social awareness. Conclusions: Food allergies significantly impact the quality of life for both patients and their families, especially mothers, with worsening effects as children age, including heightened risks of bullying and social limitations, highlighting the need for education, psychological support, and resource allocation.
Studying the Impact of Diffuser Return Guide Vanes on the Energy Performance of a Multistage Centrifugal Pump
Authors: Górecki Jan , Klimentov Kliment , Popov Gencho , Kostov Boris , Ibrahim Salaf
Published: November 2024

The head, efficiency, and cavitation characteristics of centrifugal pumps are highly dependent on the velocity field in front of the impeller inlet. In multistage pumps, the velocity field in front of the second and each subsequent stage is determined by the shape (design) of the diffuser return guide vanes. This current work presents the results obtained by performing a numerical study using ANSYS CFX 14.0 to determine the impact of the shape (design) of diffuser return guide vanes on the head and coefficient of efficiency of one stage of a multistage centrifugal pump. Three RGVs with different Outlet angles are studied: α6—original RGV with α6=90 deg, RGV1 with α6=110 deg and RGV2 with α6=128 deg. The results obtained after performing CFD modeling indicate that with one of the studied RGVs, the pump stage head increases by nearly 20%, while the hydraulic coefficient of efficiency remains almost constant. Applying entropy production theory is used to determine the impact of the various components of entropy production on the total head loss in the studied pump stage. The impact of the Outlet angle of the RGV on the velocity field of the flow in front of the next impeller (stage) as well as the RGV head is also analyzed. The numerical results of the original RGV are compared with the experimental data obtained from large-scale studies of pumps performed at the Laboratory of Hydraulic Machines of the University “Angel Kanchev” of Ruse, Bulgaria. When using the modified RGVs, the head curve of the original pump can be obtained by operating at a lower speed or with a smaller impeller diameter. This may lead to an overall increase in the energy efficiency of the machine, which could be explored as a future task.
Data-Driven and Machine-Learning-Based Real-Time Viscosity Measurement Using a Compliant Mechanism
Authors: Satpute Nitin V. , Mahajan Pratibha , Bhagawati Abhishek M. , Kulkarni Keyur G. , Utpat Kaustubh M. , Korwar Ganesh D. , Tawade Jagadish V. , Iwaniec Joanna , Kołodziejczyk Krzysztof
Published: November 2024

In this work, a novel method of viscosity measurement is proposed using a device comprising a compliant mechanism, a vibration source, and a piezoelectric sensor. The vibration source creates linear harmonic vibrations in the compliant mechanism suspended in the liquid, and the acceleration response of the mechanism is measured using the piezoelectric sensor. The vibration source is located in the central mass of the compliant mechanism, which is designed to have the necessary directional stiffness. As the mechanism vibrates, the links in the mechanism undergo damping due to the shearing action of the fluid because of its viscosity. A series of viscosity measurements are carried out with the use of water–glycerol solutions such that the acceleration of the mass is influenced by the fluid’s viscosity. During the working of the device, the mechanism is immersed in the liquid whose viscosity is to be measured. The acceleration response of the mass is recorded as time domain data using NI Lab View hardware and software, which are used to train a machine learning model. Later, a regression-based machine learning model is used for the estimation of dynamic viscosity for the given acceleration input. Experiments are performed with the prototype device using the water–glycerol solution within a viscosity ranging from 10 cP to 60 cP. The proposed sensor can be used for in-line measurements or used as a handheld instrument for quick measurements. The machine learning model achieved a high level of accuracy, evidenced by an R-squared value of 0.99, indicating that it explains 99% of the variance in the data.
The Dynamic Soil–Foundation–Structure Interaction Problem in the Time Domain Using a Discrete Element Model
Authors: Tekin Gülçin , Gencer Soner
Published: November 2024

This study investigates the influence of the soil–structure interaction (SSI) on the seismic performance of structures, focusing on the effects of foundation size, soil type, and superstructure height. While the importance of SSI is well recognized, its impact on structural behavior under seismic loads remains uncertain, particularly in terms of whether it reduces or amplifies structural demands. A simplified dynamic model, incorporating both the mechanical behavior of the soil and structural responses, is developed and validated to analyze these effects. Using a discrete element approach and the 1940 El Centro earthquake for validation, the study quantitatively compares the response of soil-interacting structures to those with fixed bases. The numerical results show that larger foundation blocks (20 m × 20 m and 30 m × 30 m) increase the seismic response values across all soil types, causing the structure to behave more like a fixed-base system. In contrast, reducing the foundation size to 10 m × 10 m increases the flexibility of structures, particularly buildings built on soft soils, which affects the displacement and acceleration response spectra. Softer soils also increase natural vibration periods and extend the plateau region in regard to spectral acceleration. This study further finds that foundation thickness has a minimal impact on spectral displacement, but structures on soft soils show more than a 15% reduction in spectral displacement (SD) compared to those on hard soils, indicating a dampening effect. Additionally, increasing the building height from 7 to 21 m results in a more than 20% decrease in SD for superstructures with natural vibration periods exceeding 2.4 s, while taller buildings with longer natural vibration periods exhibit opposite trends. Structures built on soft soils experience larger foundation-level displacements, absorbing more seismic energy and reducing earthquake accelerations, which mitigates structural damage. These results highlight the importance of considering SSI effects in seismic design scenarios to achieve more accurate performance predictions.
Development of HTC-DBSCAN: A Hierarchical Trajectory Clustering Algorithm with Automated Parameter Tuning
Authors: Lee Dae-Han , Kim Joo-Sung
Published: November 2024

Existing route-clustering methods often fail to identify abnormal sections or similarities between routes, mainly when working with large or long datasets. While sub-route clustering can detect regional patterns, it struggles to accurately capture the overall route structure. The present study proposes a new ship route-clustering method that enhances computational efficiency and noise recognition while addressing these limitations. We refined Automatic Identification System data via four data-cleaning processes and applied a statistical distance measurement to assess ship trajectory similarity. Dimensionality reduction was then used to facilitate clustering. The clustering of ship route similarities is non-parametric and can be applied to datasets not separated based on density to find clusters of various densities. Density-Based Spatial Clustering of Applications (DBSCA) applies to many research fields; using the DBSCA with Noise (DBSCAN) algorithm, we propose an improved DBSCAN algorithm that automatically determines the parameters Epsilon and MinPts. In this study, as a core ship route-clustering process, we propose a sub-route clustering process by setting the distance and density of data points to clear standards for re-analysis and completion. The proposed approach demonstrates markedly enhanced clustering performance, offering a more sophisticated and efficient basis for ship route decision-making.
Analysis and Prediction of PM2.5 Pollution in Madrid: The Use of Prophet–Long Short-Term Memory Hybrid Models
Authors: Cáceres-Tello Jesús , Galán-Hernández José Javier
Published: November 2024

Particulate matter smaller than 2.5 μm (PM2.5) in Madrid is a critical concern due to its impacts on public health. This study employs advanced methodologies, including the CRISP-DM model and hybrid Prophet–Long Short-Term Memory (LSTM), to analyze historical data from monitoring stations and predict future PM2.5 levels. The results reveal a decreasing trend in PM2.5 levels from 2019 to mid-2024, suggesting the effectiveness of policies implemented by the Madrid City Council. However, the observed interannual fluctuations and peaks indicate the need for continuous policy adjustments to address specific events and seasonal variations. The comparison of local policies and those of the European Union underscores the importance of greater coherence and alignment to optimize the outcomes. Predictions made with the Prophet–LSTM model provide a solid foundation for planning and decision making, enabling urban managers to design more effective strategies. This study not only provides a detailed understanding of pollution patterns, but also emphasizes the need for adaptive environmental policies and citizen participation to improve air quality. The findings of this work can be of great assistance to environmental policymakers, providing a basis for future research and actions to improve air quality in Madrid. The hybrid Prophet–LSTM model effectively captured both seasonal trends and pollution spikes in PM2.5 levels. The predictions indicated a general downward trend in PM2.5 concentrations across most districts in Madrid, with significant reductions observed in areas such as Chamartín and Arganzuela. This hybrid approach improves the accuracy of long-term PM2.5 predictions by effectively capturing both short-term and long-term dependencies, making it a robust solution for air quality management in complex urban environments, like Madrid. The results suggest that the environmental policies implemented by the Madrid City Council are having a positive impact on air quality.
Polyvinyl Alcohol Nanofibers with Embedded Two-Dimensional Nanomaterials and Metal Oxide Nanoparticles: Preparation, Structural Characterization, and Biological Activity
Authors: Gomaa Islam , Kalil Haitham , Abdel-Salam Ahmed I. , Ibrahim Medhat A. , Bayachou Mekki
Published: November 2024

Eco-friendly iron and manganese oxide nanoparticles (Fe2O3 and Mn2O3) were synthesized and integrated into graphene sheets to form uniform composites. These composites were then embedded in polyvinyl alcohol (PVA) fibers using electrospinning. Comprehensive characterization of the composites and the final composite fibers was conducted using XRD, FE-SEM, and FTIR to analyze their structural complexity and morphological differences. The antibacterial efficacy of the resulting PVA nanofibers was evaluated against Escherichia coli, which is a common pathogen in hospital environments. The results show a significant bactericidal effect against these bacteria, which highlights their potential in medical applications, such as functional bandages and wound dressings. This study paves the way for potential commercial applications of these nanofibers in healthcare settings.
The Study of Radioactive Fallout Source of Low-Equivalent Nuclear Bursts Based on Nuclear Cloud Simulation Using the CFD-DPM
Authors: Li Yangchao , Liu Qiang , Liu Wei , Xian Wenshuang , Li Feifei , Zhang Kai
Published: November 2024

The activity-height distribution of radioactive particles in the stabilization cloud of a nuclear burst plays a crucial role in the radioactive fallout prediction model, serving as the source for transport, diffusion, and dose rate calculation modules. A gas-particle multiphase flow solver was developed using the OpenFOAM Computational Fluid Dynamics (CFD) library and discrete phase method (DPM) library under a two-way coupling regime to simulate the U.S. standard atmosphere of 1976 with good stability. The accuracy of the numerical model was verified through low-equivalent nuclear weapons tests, including RANGER-Able and BUSTER-JANGLE-Sugar, depicting reasonable spatio-temporal changes in cloud profiles. The initialization module of the Defense Land Fallout Interpretative Code (DELFIC) and activity-size distribution, which considered fractionation, were employed for nuclear fireball and radioactive particle initialization. Simulations indicated that the activity-height distribution of the stabilization cloud mainly concentrated on the lower third of air burst cloud caps, while settling near the burst center for surface or near-surface bursts. This study has confirmed the effectiveness of the gas-particle flow solver based on the CFD-DPM method in simulating low-equivalent nuclear clouds and enriching research on radioactive fallout prediction models.
Examining the Effectiveness of a Pilot Waste Classification Policy in Facilitating the Low-Carbon Transition Regarding Solid Waste in China
Authors: Yang Yanshuang , Li Huimin
Published: November 2024

The pilot waste classification policy is pivotal in tackling the challenges associated with the decarbonization of solid waste disposal in China; nevertheless, the efficacy of these pilot policies continues to be a topic of ongoing debate. This study presents a novel methodology utilizing an advanced difference-in-differences model, drawing on panel data from 297 cities for the period of 2016 to 2020, encompassing various types of municipal solid wastes and their corresponding carbon emissions. By integrating the waste classification performance as an intermediary variable, this research distinctly investigates how these policies facilitate the transition towards a low-carbon economy. The key findings indicate the following: (1) The implementation of pilot waste classification policies significantly accelerates the low-carbon transition of municipal solid waste disposal, with results substantiated through rigorous empirical testing. (2) The mechanistic analysis reveals a marked efficiency enhancement in waste classification within megacities, resulting in a compensatory effect, while analogous policies do not yield performance improvements in small- and medium-sized cities. (3) The effects of waste classification policies exhibit variability across cities of differing scales, with scale particularly influencing the performance of waste classification, thereby emphasizing the necessity for city-specific strategies in policy execution. The contributions of this study are rooted in its methodological advancements and its sophisticated analysis of the varying effects of waste classification policies, providing critical insights for policymakers seeking to enhance the effects of low-carbon strategies within urban environments. However, it is important to note that the scope of this study is limited to China, and the findings may be most applicable to countries with similar waste management challenges.
Ethanol’s Pharmacodynamic Effect on Odorant Detection in Distilled Spirits Models
Authors: Wang Zhuzhu , Cadwallader Keith R.
Published: November 2024

Aroma perception in distilled spirits is influenced by both the physicochemical and pharmacodynamic effects of ethanol. This study measured these effects by examining the odor detection threshold (ODT) of various odorants. The physicochemical effect influences how odorants partition into the vapor matrix (headspace), while the pharmacodynamic effect affects the functioning of olfactory receptors cells (ORCs). Both factors contribute to changes in odorant ODTs, though it remains unclear which has a greater influence. Across three exploratory experiments, we demonstrated that ethanol in the vapor matrix suppressed the olfactory detection of key odorants in distilled spirits, with some chemical groups being more affected than others. This suppression effect increased as ethanol concentration rose. Notably, our results showed that ethanol’s pharmacodynamic effect plays the primary role in elevating ODTs in ethanol/water solutions, and this effect intensifies as ethanol concentration in the liquid matrix increases. These findings highlight the significant role of ethanol concentration in the vapor matrix and provide scientific support for practices such as diluting spirits or using specifically shaped glassware to lower ethanol headspace concentration during whiskey nosing (odor evaluation).
Macro, Trace and Toxic Element Composition in Liver and Meat of Broiler Chicken Associated with Cecal Microbiome Community
Authors: Deryabin Dmitry , Kosyan Dianna , Vlasenko Ludmila , Lazebnik Christina , Zatevalov Alexander , Karimov Ilshat , Duskaev Galimzhan
Published: November 2024

The current study presents a meta-analysis of the detailed relationship between the composition of 25 essential and toxic elements in chicken tissues examined by ICP-MS and the gut microbial community analyzed using NGS techniques. The examination of chicken liver and meat revealed typical elemental compositions, called the “elementomes”. The α-elementomes showed high contents of macro elements (Na, K, Mg, Ca, P), majority trace elements (Sr, Se, Mn, Fe, Co, Cu, Zn) and some toxic elements (B, Pb, Ni, Cd); β-elementomes indicated accumulation of Si, V and Cr; γ-elementomes indicated accumulation of Al, As and Hg. Characterization of the microbiomes’ structure showed two distinct enterotypes, designated “microbiome patterns”; the first was enriched in the phylum Bacteroidota, and the second was dominated by Bacillota and coupled with members of the phyla Actinomycetota, Cyanobacteriota and Thermodesulfobacteriota. A comparison of elementomes and microbiomes demonstrated a clear correspondence between the α- and γ-elementomes belonging to the Bacteroidota-enriched pattern, while the β-elementome was predominantly found in chicken groups belonging to the Bacillota + ACT pattern. This insight proposes a novel strategy to improve deficiency or excess of certain elements in the host by gut microbiome modulation, which needs to be verified with further in vivo experiments.
Urolithin A Protects Hepatocytes from Palmitic Acid-Induced ER Stress by Regulating Calcium Homeostasis in the MAM
Authors: Ryu Gayoung , Ko Minjeong , Lee Sooyeon , Park Se In , Choi Jin-Woong , Lee Ju Yeon , Kim Jin Young , Kwon Ho Jeong
Published: November 2024

An ellagitannin-derived metabolite, Urolithin A (UA), has emerged as a potential therapeutic agent for metabolic disorders due to its antioxidant, anti-inflammatory, and mitochondrial function-improving properties, but its efficacy in protecting against ER stress remains underexplored. The endoplasmic reticulum (ER) is a cellular organelle involved in protein folding, lipid synthesis, and calcium regulation. Perturbations in these functions can lead to ER stress, which contributes to the development and progression of metabolic disorders such as metabolic-associated fatty liver disease (MAFLD). In this study, we identified a novel target protein of UA and elucidated its mechanism for alleviating palmitic acid (PA)-induced ER stress. Cellular thermal shift assay (CETSA)-LC-MS/MS analysis revealed that UA binds directly to the sarcoplasmic/endoplasmic reticulum Ca2+-ATPase (SERCA), an important regulator of calcium homeostasis in mitochondria-associated ER membranes (MAMs). As an agonist of SERCA, UA attenuates abnormal calcium fluctuations and ER stress in PA-treated liver cells, thereby contributing to cell survival. The lack of UA activity in SERCA knockdown cells suggests that UA regulates cellular homeostasis through its interaction with SERCA. Collectively, our results demonstrate that UA protects against PA-induced ER stress and enhances cell survival by regulating calcium homeostasis in MAMs through SERCA. This study highlights the potential of UA as a therapeutic agent for metabolic disorders associated with ER stress.
Steroids and Malignancy Increase Local Heparanase and Decrease Markers of Osteoblast Activity in Bone Tissue Microcirculation
Authors: Asayag Keren , Peled Eli , Assalia Mai , Crispel Yonatan , Yanovich Chen , Cohen Haim , Keren-Politansky Anat , Nadir Yona
Published: November 2024

Bone metastasis and steroids are known to activate the coagulation system and induce osteoporosis, pathological bone fractures, and bone pain. Heparanase is a protein known to enhance the hemostatic system and to promote angiogenesis, metastasis, and inflammation. The objective of the present study was to evaluate the effects of steroids and malignancy on the coagulation factors and osteoblast activity in the bone tissue. The effects of dexacort and malignant medium were evaluated in osteoblasts derived from human bone marrow mesenchymal stem cells and human umbilical vein endothelial cells (HUVECs). The bones of mice treated with dexacort for 1 month were studied. Bone biopsies of ten patients with bone metastasis, ten with steroid-induced avascular necrosis (AVN), and ten with osteoarthritis were compared to ten controls. We found that dexacort and malignant medium significantly increased the heparanase levels in osteoblasts and HUVECs and decreased the levels of alkaline phosphatase (ALKP). Peptide 16AC, derived from heparanase, which interacts with tissue factor (TF), further increased the effect, while peptide 6, which inhibits interactions between heparanase and TF, reversed the effect in these cells. The bone microcirculation of mice treated with dexacort exhibited significantly higher levels of heparanase, TF, TF pathway inhibitor (TFPI), TFPI-2, thrombin, and syndecan-1, but reduced levels of osteocalcin and ALKP. The pathological human bone biopsies’ microcirculation exhibited significantly dilated blood vessels and higher levels of heparanase, TF, TFPI, TFPI-2, and fibrin. In summary, steroids and malignancy increased the activation of the coagulation system in the bone microcirculation and reduced the osteoblast activity. Heparanase inhibitors should be further investigated to attenuate bone fractures and pain.
Sirtuin-5 Is Recruited to Hepatic Peroxisomes in Mice Fed Dodecanedioic Acid but Has Little Impact on the Peroxisomal Succinylome
Authors: Zhang Yuxun , Zhang Bob B. , Bharathi Sivakama S. , Bons Joanna , Rose Jacob P. , Shah Samah , Dobrowolski Steven F. , Sims-Lucas Sunder , Schilling Birgit , Goetzman Eric S.
Published: November 2024

Lysine succinylation, and its reversal by sirtuin-5 (SIRT5), is known to modulate mitochondrial fatty acid β-oxidation (FAO). We recently showed that feeding mice dodecanedioic acid, a 12-carbon dicarboxylic acid (DC12) that can be chain-shortened four rounds to succinyl-CoA, drives high-level protein hypersuccinylation in the peroxisome, particularly on peroxisomal FAO enzymes. However, the ability of SIRT5 to reverse DC12-induced peroxisomal succinylation, or to regulate peroxisomal FAO in this context, remained unexplored. Here, we showed that feeding DC12 strongly recruits SIRT5 into hepatic peroxisomes. Knocking out SIRT5 impaired peroxisomal FAO as evidenced by reduced 14C-DC12 flux in liver homogenates and elevated levels of partially shortened DC12 catabolites in urine. Further, mass spectrometry revealed a trend toward less peroxisomal protein succinylation in SIRT5 knockout liver. This is consistent with a reduced flux of DC12 through the peroxisomal FAO pathway, thereby reducing the production of the succinyl-CoA that chemically reacts with lysine residues to produce protein succinylation. Mass spectrometry comparisons of site-level succinylation in wildtype and SIRT5 knockout liver did not reveal any clear pattern of SIRT5 target sites in the peroxisome after DC12 feeding. However, SIRT5 co-immunoprecipitated with 15 peroxisomal proteins, including the key peroxisomal FAO enzymes acyl-CoA oxidase-1 and enoyl-CoA/3-hydroxyacyl-CoA dehydrogenase (EHHADH). In vitro, recombinant SIRT5 partially desuccinylated chemically modified recombinants ACOX1a, ACOX1b, and EHHADH. Desuccinylation by SIRT5 had no effect on enzyme activity for ACOX1a and EHHADH. For ACOX1b, SIRT5-mediated desuccinylation decreased activity by ~15%. Possible interpretations of these data are discussed.
Observational Study of Trans-Septal Endocardial Left Ventricle Lead Implant for Effective Cardiac Resynchronization Therapy in Patients with Heart Failure and Challenging Coronary Sinus Anatomy
Authors: Farhangee Arsalan , Davies Mark J. , Gaughan Katie , Mesina Mihai , Mîndrilă Ion
Published: November 2024

Background: When conventional trans-venous CS lead placement fails, trans-septal endocardial left ventricle lead placement is an alternative technique used to capture the left ventricle endocardially; however, its use is limited due to a lack of evidence, practice uptake, and clinical trials. Methods: In this single-center cohort study, we evaluated the efficiency of the procedure, post-procedural complication rate, rate of thromboembolic events, overall survival rate, and changes in the echocardiographic parameters, brain natriuretic peptide (BNP) level, and New York Heart Association (NYHA) class, both before and after TSLV lead implantation. Results: The TSLV lead implant is safe and improves EF, LVEDV, LVESV, and LVIDd. It significantly reduces the NTproBNP levels and the NYHA class; however, the rate of stroke incidence remains high, at 9%. Conclusions: We demonstrated a high success rate of trans-septal left ventricular endocardial lead implantation, LV reverse remodeling was noted, and patients had a favorable clinical response; however, there was an increased risk of systemic embolization after the trans-septal LV lead implant.
Breathless Nights and Cardiac Frights—How Snoring Is Breaking Hearts
Authors: Wester Michael , Lebek Simon
Published: November 2024

While your nightly symphony may be testing your loved one’s patience, it could also be giving your own heart reasons to complain [...]
Effect of Gold Nanoparticles in Microbial Fuel Cells Based on Polypyrrole-Modified Saccharomyces cerevisiae
Authors: Kižys Kasparas , Pirštelis Domas , Morkvėnaitė-Vilkončienė Inga
Published: November 2024

Microbial fuel cells (MFCs) are a candidate for green energy sources due to microbes’ ability to generate charge in their metabolic processes. The main problem in MFCs is slow charge transfer between microorganisms and electrodes. Several methods to improve charge transfer have been used until now: modification of microorganisms by conductive polymers, use of lipophilic mediators, and conductive nanomaterials. We created an MFC with a graphite anode, covering it with 9,10-phenatrenequinone and polypyrrole-modified Saccharomyces cerevisiae with and without 10 nm sphere gold nanoparticles. The MFC was evaluated using cyclic voltammetry and power density measurements. The peak current from cyclic voltammetry measurements increased from 3.76 mA/cm2 to 5.01 mA/cm2 with bare and polypyrrole-modified yeast, respectively. The MFC with polypyrrole- and nanoparticle-modified yeast reached a maximum power density of 150 mW/m2 in PBS with 20 mM Fe(III) and 20 mM glucose, using a load of 10 kΩ. The same MFC with the same load in wastewater reached 179.2 mW/m2. These results suggest that this MFC configuration can be used to improve charge transfer.
Urban Parrots in Southern South America: Challenges and Opportunities
Authors: Lera Daiana N. , Cozzani Natalia , Camina Julia L. , Tella José L. , Zalba Sergio
Published: November 2024

Data on the interactions between the order Psittaciformes and the anthropogenic environment are still insufficient and have not been systematized, especially in the Neotropical region. As a consequence of this coexistence, the volume of accumulated knowledge is probably significantly greater than the formal scientific contributions on the subject. In this survey, information was compiled on the wild parrots inhabiting cities in the Southern Cone of South America, based on surveys with key informants. The results obtained highlighted the presence of a large number of parrot species that form part of the urban avifauna of the region, between 67% and 90% of the total number of species of the order cited for each territory evaluated. The greatest species richness and the number of breeding species were associated with the large cities located in middle and low latitudes. We confirmed breeding within the cities for more than 40% of the species mentioned. Seventy-five percent of the species reported are native to the study area, the rest originating from other regions of South America or other continents. A quarter of the reported species are considered threatened and almost 50% have declining populations. Urban parrots represent a challenge in the search for urban models compatible with biodiversity conservation, and in the designing of innovative conservation strategies that respond to the new challenges posed by a constantly growing human population.