bluuebunny/crossref_metadata_2025 huggingface dataset:
Phenolic Acids and Their Relationship to Nutritional and Technological Grain Parameters of Durum Wheat Under Variable Treatment Intensity in Central European Conditions
Authors: Dvořáček Václav , Jágr Michal , Jelínek Michael , Polišenská Ivana , Spitzer Tomáš , Hermuth Jiří
Published: November 2024

The objective of this two-year study was primarily the evaluation of the free and the bound forms of phenolic acids and phenolic aldehydes (PAAs) in grains of four selected cultivars of spring durum wheat subjected to three treatment intensities (GD—Green Deal, BT—Basic and IT—Intensive). All treatments included a common basic level and different spring production levels of nitrogen fertilisation (0 kg N in the case of GD; 30 kg N in the case of BT; and 60 kg N in the case of IT). Pesticide applications included herbicides and insecticides in both the BT and IT treatments, which were supplemented by combinations of fungicide and morphoregulator in the IT treatment. The GD treatment included only basic nitrogen, herbicide protection, and the application of a biostimulator (ExelGrow). The spring durum wheat cultivars subjected to testing were cultivated under Central European conditions, specifically in the Czech Republic’s central Bohemian region. UHPLC-ESI-MS/MS was used for the detection and accurate quantification of PAAs. In parallel, 12 other nutritional and basic technological parameters of the cereal were evaluated. Nine bound and seven free forms of PAAs were quantified in the analysed cereal samples. Bound forms of PAAs were dominant, accounting for 99.4% of total PAAs. Considering single PAAs, ferulic acid was the most abundant, accounting for 87% of the total bound PAAs. Interestingly, year and treatment intensity were the key factors in the variability of both free and bound PAAs, but these factors had different effects on bound PAAs. Under low nitrogen conditions, plants responded with an increase in free PAAs in particular, as well as in three bound PAAs. Unfavourable weather conditions, combined with the presence of biotic factors (e.g., Fusarium infections), significantly influenced the increase in both PAA groups, with the exception of free p-coumaric acid. PCA analysis confirmed close relationships between PAAs within both categories (free and bound). Subsequent correlation analysis further revealed that the immunoreactive gluten component (G12) exhibited a high negative correlation with the dominant ferulic acid (r = −0.70) and sinapic acid (r = −0.68). Additionally, moderate negative correlations were observed between four bound phenolic acids and grain hardness (r = −0.48–−0.60).
Development of Microsatellite Markers from Transcriptome of Eriocheir sinensis and Their Application in Multiplex PCR Panels
Authors: Xiao Qizhen , Tang Meijun , Li Qingqing , Dong Pengsheng , Cheng Yongxu , Deng Deng , Wu Xugan
Published: November 2024

Background: The development of genetic markers is crucial for aquaculture and population genetics. Polyallelic microsatellite markers are widely used for breeding and family management of Eriocheir sinensis (E. sinensis), contributing to the sustainable development of the industry. Methods: Through transcriptome analysis, 100 highly polymorphic SSR markers were identified and developed. From these, four multiplex PCR panels, each containing 16 markers, were constructed and applied to parentage assignment in six E. sinensis families. Results: The number of alleles (Na) ranged from 7 to 21, the observed heterozygosity (Ho) varied from 0.356 to 0.951, and the expected heterozygosity (He) varied from 0.656 to 0.909. The polymorphism information content (PIC) ranged from 0.633 to 0.900. The CERVUS analysis showed that using only the two most informative multiplex PCR panels, assignment success rates exceeded 90.34%, with 100% accuracy in assigning offspring to parents when three or four panels were used. Conclusions: This method significantly enhances the efficiency of microsatellite marker analysis, which provides a convenient and cost-effective method for breeding programs and family management of E. sinensis.
Sales of Veterinary Antibiotics in Serbia: Identification of Problem Areas Using Standardized Metrics
Authors: Tomas Ana , Pavlović Nebojša , Vukmirović Saša , Kovačević Zorana , Dugandžija Tihomir , Radovanović Dragana , Stilinović Nebojša
Published: November 2024

One Health, as a multi-disciplinary approach, considers animal, human, and environmental health. Serbia continuously records high rates of antimicrobial resistance, with a knowledge gap on practices regarding veterinary antibiotic use, as no standardized data regarding veterinary consumption of antibiotics that would allow for temporal or spatial comparison are available in Serbia. This study aimed to describe the sales of veterinary antibiotics in Serbia. Aggregated wholesale data on veterinary drug sales were retrieved from the annual reports available from the Medicines and Medical Devices Agency of the Republic of Serbia for a period between 2017 and 2020. Veterinary use was analyzed using standard European Medicines Agency proposed methodology and expressed in milligrams of active substance per population correction unit (mg/PCU). Overall, there has been a 13% increase in aggregated sales, in mg/PCU, of antibiotic veterinary medicinal products (VMPs) for food-producing animals in Serbia between 2017 and 2020. With sales of around 110 mg/PCU in 2020, Serbia would have ranked ninth in Europe. In 2020, the overall highest-selling antibiotic classes were penicillins (27.62 mg/PCU), tetracyclines (27.54 mg/PCU), and aminoglycosides (12.8 mg/PCU), accounting for 61.9% of the total sales of antibiotic VMPs for food-producing animals, in mg/PCU. An increase in the use of macrolides and lincosamides and a decrease in the use of penicillins and the group classified as “other antibacterials” was noted. The current study identified an increase in the sales of veterinary antibiotics in Serbia and pointed out several potential problem areas.
Antibacterial and Antibiofilm Activity of Essential Oils Against Aeromonas spp. Isolated from Rainbow Trout
Authors: Hudecová Patrícia , Koščová Jana , Hajdučková Vanda , Király Ján , Horňak Peter
Published: November 2024

Aeromonas spp. is a major pathogen in aquaculture with a great negative economic impact. Essential oils (EOs) are compounds of the secondary metabolism of plants known for their antibacterial and antibiofilm activities. In this study, in vitro antibacterial activity of eight EOs: tea tree (extracted from Melaleuca alternifolia), eucalyptus (extracted from Eucalyptus globulus LABILL.), knee timber (extracted from Pini mungo L.), peppermint (extracted from Mentha piperita L.), oregano (extracted from Origanum vulgare L.), rosemary (extracted from Rosmarinus officinalis L.), thyme (extracted from Thymus vulgaris L.) and pine EO (extracted from Pinus silvestris L.), obtained from Calendula a.s., was evaluated. Their antibacterial activity was demonstrated against Aeromonas spp. isolates. Oregano and thyme EOs showed the strongest activity against all tested isolates at low concentrations, followed by tea tree and peppermint EOs. The MIC value ranged from 0.06 µL/mL to 1.0 µL/mL. The tested EOs showed a significant antibiofilm activity against biofilm-forming isolates with MBIC50 ranging from 0.015 µL/mL to 0.25 µL/mL. All tested isolates were obtained from rainbow trout free of clinical signs of infection. Twelve isolates of Aeromonas salmonicida subsp. masoucida, four Aeromonas hydrophila, and four isolates of Aeromonas veronii were identified. The results of the in vitro study showed a significant effect of EOs against Aeromonas spp., which confirmed their potential for use in aquaculture as a prevention against bacterial diseases and a way of reducing the use of antibiotics.
Enhanced HS Code Classification for Import and Export Goods via Multiscale Attention and ERNIE-BiLSTM
Authors: Liao Mengjie , Huang Lei , Zhang Jian , Song Luona , Li Bo
Published: November 2024

Accurate classification of import and export goods’ Harmonized System (HS) codes is essential for ensuring tax security. Applying text classification technologies for HS code classification can significantly enhance the prevention and control of customs tax risks. However, the goods text is a semi-structured one that involves multi-domain Chinese professional vocabulary, which poses challenges for current classification models. These models often suffer from inadequate text representation and imprecise feature extraction. To address these challenges, we propose a novel classification model ERNIE-BiLSTM-Channel attention–Spatial attention (EBLCS). This model integrates ERNIE (Enhanced Representation through Knowledge Integration) with a Bidirectional Long Short-Term Memory Network (BiLSTM) and employs multi-scale attention mechanisms. The ERNIE-BiLSTM model provides a more comprehensive and accurate representation of the goods text, effectively capturing the global features of the text. By introducing channel attention and spatial attention mechanisms, greater weights are assigned to important words and word embedding dimensions, significantly enhancing the model’s ability to perceive key information. The experimental results on a customs dataset demonstrate that the EBLCS model consistently outperforms various baseline models across all evaluation metrics, effectively enhancing the performance of HS code classification.
FastSLAM-MO-PSO: A Robust Method for Simultaneous Localization and Mapping in Mobile Robots Navigating Unknown Environments
Authors: Bian Xu , Zhao Wanqiu , Tang Ling , Zhao Hong , Mei Xuesong
Published: November 2024

In the realm of mobile robotics, the capability to navigate and map uncharted territories is paramount, and Simultaneous Localization and Mapping (SLAM) stands as a cornerstone technology enabling this capability. While traditional SLAM methods like Extended Kalman Filter (EKF) and FastSLAM have made strides, they often struggle with the complexities of non-linear dynamics and non-Gaussian noise, particularly in dynamic settings. Moreover, these methods can be computationally intensive, limiting their applicability in real-world scenarios. This paper introduces an innovative enhancement to the FastSLAM framework by integrating Multi-Objective Particle Swarm Optimization (MO-PSO), aiming to bolster the robustness and accuracy of SLAM in mobile robots. We outline the theoretical underpinnings of FastSLAM and underscore its significance in robotic autonomy for mapping and exploration. Our approach innovates by crafting a specialized fitness function within the MO-PSO paradigm, which is instrumental in optimizing the particle distribution and addressing the challenges inherent in traditional particle filtering methods. This strategic fusion of MO-PSO with FastSLAM not only circumvents the pitfalls of particle degeneration, but also enhances the overall robustness and precision of the SLAM process across a spectrum of operational environments. Our empirical evaluation involves testing the proposed method on three distinct simulation benchmarks, comparing its performance against four other algorithms. The results indicate that our MO-PSO-enhanced FastSLAM method outperforms the traditional particle filtering approach by significantly reducing particle degeneration and ensuring more reliable and precise SLAM performance in challenging environments. This research demonstrates that the integration of MO-PSO with FastSLAM is a promising direction for improving SLAM in mobile robots, providing a robust solution for accurate mapping and localization even in complex and unknown settings.
Stress Concentration Modelling in Internal Stiffeners of Ship-to-Shore Quay Cranes Legs Due to Structural Heightening
Authors: Castillo Rivera José Roberto , Rodríguez-García María Inmaculada , Carrasco-García María Gema , Turias Ignacio J.
Published: November 2024

This paper presents a study on the modelling and estimation of stress concentration at the tips of leg stiffeners in ship-to-shore (STS) quay cranes, which is intensified in those on the sea-side leg extensions, which are more prone to crack formation, notably following structural heightening of the cranes. A computer-simulated database was generated, incorporating mechanical parameters and geometric features that impact stress concentration. These variables can then be integrated as inputs into a multiple linear regression model (MLR). This methodology offers an alternative to the finite element method (FEM) for the computation of stress concentration and deformations. At the same time, the statistical significance of the parameters influencing this scenario is determined, ensuring a comprehensive assessment of their impact on the studied phenomenon. The research underscores the importance of incorporating stress concentration and structural geometry considerations into crane design or modification, given their crucial role in preserving the remaining lifecycle of the structure. Crack initiation is significantly intensified in regions characterised by high stress concentrations, particularly in areas where there are geometric changes at the tips of the stiffeners, where local stiffness is altered. All of this is in combination with work cycles under the supported loads.
Integrated Analysis of Rockfalls and Floods in the Jiului Gorge, Romania: Impacts on Road and Rail Traffic
Authors: Puie Marian , Mihai Bogdan-Andrei
Published: November 2024

This study examines the impact of rockfalls and floods on road and rail traffic in the Jiului Gorge, Romania, a critical transportation corridor. Using Sentinel-1 radar imagery processed through ESA SNAP and ArcGIS Pro, alongside traffic detection facilitated by YOLO models, we assessed susceptibility to both rockfalls and floods. The primary aim was to enhance public safety for traffic participants by providing accurate hazard mapping. Our study focuses on the area from Bumbești-Jiu to Petroșani, traversing the Southern Carpathians. The results demonstrate the utility of integrating remote sensing with machine learning to improve hazard management and inform more effective traffic planning. These findings contribute to safer, more resilient infrastructure in areas vulnerable to natural hazards.
Thermal Stress Analysis of Maxillary Dentures with Different Reinforcement Materials Under Occlusal Load Using Finite Element Method
Authors: Benli Semih , Baş Gökhan
Published: November 2024

The purpose of this study was to determine the effect of fiber reinforcement materials on the magnitude of stresses in a critical part of the maxillary denture base under thermal and occlusal load. Thermal stress analyses of the models were carried out using the finite element method. The models consisted of bone, soft tissue, interface gap, and maxillary dentures with and without reinforcements. A concentrated occlusal load of 230 N was applied bilaterally on the molar teeth. A 36 °C reference and 0 °C, 36 °C, and 70 °C variable ambient temperatures were applied to the models. CrCo, unidirectional and woven carbon/epoxy, unidirectional and woven glass/epoxy, and unidirectional and woven Kevlar/epoxy were used as reinforcing materials in the maxillary denture base made of PMMA (polymethyl methacrylate). Stress distributions on the maxillary denture’s midline and lateral line direction were evaluated. Maximum stresses in the incisal notch and the labial frenal notch of the maxillary denture were determined. Failure analysis of reinforcement materials used in maxillary dentures was carried out using the Tsai-Wu index criterion. The results obtained show that the thermal properties of reinforcement materials should be considered as an important criterion in their selection.
The Impact of Different Footwear Conditions on Lower-Limb Biomechanical Characteristics During Single-Leg Drop Landing Movements in Individuals with Functional Ankle Instability
Authors: Wang Zilong , Lu Mengya , Wu Jun , Liu Rongsen , Kong Lingyu , Li Chenjin , Meng Lingyue , Zhang Qiuxia
Published: November 2024

(1) Background: This study investigated the impact of different footwear conditions on the biomechanics of individuals with Functional Ankle Instability (FAI) during single-leg drop landing movements. (2) Methods: Fifteen participants with FAI and a control group were tested. Kinematics and kinetics were measured using Vicon (Model: MX13, Oxford, UK) and Kistler (Model: 9287B, Switzerland) equipment. A mixed-ANOVA analyzed the impact of footwear conditions. (3) Results: At the initial contact (IC), under the shoe-wearing condition, the FAI group exhibited a significantly smaller ankle-joint plantarflexion angle compared to the control group (p = 0.001). The FAI group exhibited a significantly smaller ankle-joint plantarflexion angle under the shoe-wearing condition compared to the barefoot condition at the IC (p < 0.001). At the IC moment, regardless of the footwear conditions in this study, the FAI group showed a larger knee flexion angle (p = 0.028) and a shorter time to vertical ground reaction force (T_vGRF) (p = 0.020) compared to the control group. (4) Conclusions: The study concluded that footwear conditions significantly influence the biomechanics of FAI individuals, with shoes enhancing ankle stability and barefoot conditions leading to biomechanics similar to healthy individuals. The effect of socks on FAI individuals was not significant. Future research should further explore the impact of footwear on FAI rehabilitation.
Optimal Model-Free Mean-Square Consensus for Multi-Agents with Markov Switching Topology
Authors: Ma Ruoxun , Mo Lipo , Zhou Bokang
Published: November 2024

Due to the real applications, optimal consensus reinforcement learning with switching topology is still challenging due to the complexity of topological changes. This paper investigates the optimal consensus control problem for discrete multi-agent systems under Markov switching topologies. The goal is to design an appropriate algorithm to find the optimal control policies that minimize the performance index while achieving consensus among the agents. The concept of mean-square consensus is introduced, and the relationship between consensus error and tracking error to achieve mean-square consensus is studied. A performance function for each agent under switching topologies is established and a policy iteration algorithm using system data is proposed based on the Bellman optimality principle. The theoretical analysis shows that the consensus error realizes mean-square consensus and the performance function is optimized. The efficacy of the suggested approach is confirmed by numerical simulation using an actor–critic neural network. As a result, the value function is the optimum and the mean-square consensus can be reached using this technique.
Smart Viniculture: Applying Artificial Intelligence for Improved Winemaking and Risk Management
Authors: Izquierdo-Bueno Inmaculada , Moraga Javier , Cantoral Jesús M. , Carbú María , Garrido Carlos , González-Rodríguez Victoria E.
Published: November 2024

This review explores the transformative role of artificial intelligence (AI) in the entire winemaking process, from viticulture to bottling, with a particular focus on enhancing food safety and traceability. It discusses AI’s applications in optimizing grape cultivation, fermentation, bottling, and quality control, while emphasizing its critical role in managing microbiological risks such as mycotoxins. The review aims to show how AI technologies not only refine operational efficiencies but also raise safety standards and ensure traceability from vineyard to consumer. Challenges in AI implementation and future directions for integrating more advanced AI solutions into the winemaking industry will also be discussed, providing a comprehensive overview of AI’s potential to revolutionize traditional practices.
Investigation of the Seismic Performance of a Multi-Story, Multi-Bay Special Truss Moment Steel Frame with X-Diagonal Shape Memory Alloy Bars
Authors: Sophianopoulos Dimitrios S. , Ntina Maria I.
Published: November 2024

In this work, the seismic response of a multi-story, multi-bay special truss moment frame (STMF) with Ni-Ti shape memory alloys (SMAs) incorporated in the form of X-diagonal braces in the special segment is investigated. The diameter of the SMAs per diagonal in each floor was initially determined, considering the expected ultimate strength of the special segment, developed when the frame reaches its target drift and the desirable collapse mechanism, i.e., the formation of plastic hinges, according to the performance-based plastic design procedure. To further investigate the response of the structure with the SMAs incorporated, half the calculated SMA diameters were introduced. Continuing, three more cases were investigated: the mean value of the SMA diameter was introduced at each floor (case DC1), half the SMA diameter of case DC1 (case DC2), and twice the SMA diameter of case DC1 (case CD3). Dynamic time history analyses under seven benchmark earthquakes were conducted using commercial nonlinear Finite Element software (SeismoStruct 2024). Results were presented in the form of top-displacement time histories, the SMAs force–displacement curves, and maximum inter-story drifts, calculating also maximum SMA displacements. The analysis outcomes highlight the potential of the SMAs to be considered as a novel material in the seismic retrofit of steel structures. Both design approaches presented exhibit a certain amount of effectiveness, depending on the distribution, with the placement of the SMA bars and the seismic excitation considered. Further research is suggested to fully understand the capabilities of the use of SMAs as dissipation devices in steel structures.
Impact of Cognitive Tasks on Biomechanical Adjustments During Single-Leg Drop Landings in Individuals with Functional Ankle Instability
Authors: Wang Zilong , Lu Mengya , Kong Lingyu , Meng Lingyue , Xue Jingxian , Zheng Yan , Zhang Qiuxia
Published: November 2024

This study aimed to evaluate the biomechanics of single-leg drop landing in individuals with functional ankle instability (FAI) during cognitive tasks, contrasting these findings with those of healthy controls to provide insights for evidence-based rehabilitation strategies. Fifteen FAI participants, identified using clinical tools, were age- and activity-matched with controls. They performed drop landings with and without a cognitive task, and the data were analyzed using a 2 × 2 mixed ANOVA. At the initial ground contact (IC), the FAI group’s affected side showed a significantly smaller plantarflexion angle than the control group (p = 0.008). With cognitive tasks, this angle increased in the FAI group (p = 0.005). The FAI group also had larger knee flexion at contact (p = 0.002) and greater knee valgus at peak vertical ground reaction force (vGRF) (p = 0.027). They exhibited a higher peak vGRF, shorter time to peak vGRF (T-vGRF), and higher loading rate (LR) (all p < 0.05). No differences were found in other variables (p > 0.05). This study shows that FAI individuals make specific biomechanical adjustments under cognitive tasks, notably increased plantarflexion at IC, suggesting reactive compensations. Despite similar motor control to controls, this may reflect long-term adaptations rather than equal proficiency.
Assessing the Carbon Intensity of e-fuels Production in European Countries: A Temporal Analysis
Authors: Besseau Romain , Scarlat Nicolae , Hurtig Oliver , Motola Vincenzo , Bouter Anne
Published: November 2024

The transport sector heavily relies on the use of fossil fuels, which are causing major environmental concerns. Solutions relying on the direct or indirect use of electricity through e-fuel production are emerging to power the transport sector. To ensure environmental benefits are achieved over this transition, an accurate estimation of the impact of the use of electricity is needed. This requires a high temporal resolution to capture the high variability of electricity. This paper presents a previously unseen temporal analysis of the carbon intensity of e-fuels using grid electricity in countries that are members of the European Network of Transmission System Operators (ENTSO-E). It also provides an estimation of the potential load factor for producing low-carbon e-fuels according to the European Union legislative framework. This was achieved by building on top of the existing EcoDynElec tool to develop EcoDynElec_xr, a python tool enabling—with an hourly time resolution—the calculation, visualisation, and analysis of the historical time-series of electricity mixing from the ENTSO-E. The results highlight that, in 2023, very few European countries were reaching low carbon intensity for electricity that enables the use of grid electricity for the production of green electrolytic hydrogen. The methodological assumptions consider the consumption of the electricity mix instead of the production mix, and the considered time step is of paramount importance and drastically impacts the potential load factor of green hydrogen production. The developed tools are released under an open-source license to ensure transparency, result reproducibility, and reuse regarding newer data for other territories or for other purposes.
Regional Claims Through Exhibitions—The Transnational Circulation of Włocławek “Fajans” in East Central Europe
Authors: Majewska-Güde Karolina
Published: November 2024

The article examines the exhibition history of hand-painted ceramic objects from the “Fajans” factory in Włocławek and the politics of regional contextualization during the period of détente in the 1970s and 1980s. It extends both existing scholarship on transnational art history in socialist Europe and the notion of cultural diplomacy, approached here in the context of regional politics and economic frameworks. The paper highlights the peripheral networks and movements that developed in relation to the socialist cultural politics of working-class artistic engagement and artistic practice as labor. Questions of cooperation between Poland and other socialist states are of particular interest, as are the implications of détente for East Central Europe. The reconstruction of the transnational circulation of “Fajans” objects is based on a comparative analysis of international “Fajans” exhibitions, using documentation from the archives of the Faience Department of the Museum of the Kujawy and Dobrzyń Land, as well as from the archives of the city of Novi Sad. Based on the researched material and the conceptual framework of transnational art history, the article proposes a concept of regional cultural diplomacy.
Thermal Propagation Test Bench for the Study of the Paschen Curve and Lightning Arcs of Venting Gas
Authors: Mulder Björn , Birke Kai Peter , Obry Björn , Wigger Stefan , Kozakov Ruslan , Smirnov Pavel , Schein Jochen
Published: November 2024

Thermal propagation events are characterized by fire and thick black smoke, leading to propagation methods with a focus on preventing heat transfer and optimizing gas flow. Yet little attention is being paid to the electric conductivity of the gas, leading to possibly unexpected battery casing openings due to lightning arcs as well as potentially providing the minimum ignition energy. This gas composition (omitting particles) was used at different temperatures and pressures in a lightning arc test bench, leading to the Paschen curve. Using a mini-module cell setup, filtered venting gas was flowed through another lightning arc test bench, allowing for in situ measurements.
Prediction of Lithium-Ion Battery State of Health Using a Deep Hybrid Kernel Extreme Learning Machine Optimized by the Improved Black-Winged Kite Algorithm
Authors: Fu Juncheng , Song Zhengxiang , Meng Jinhao , Wu Chunling
Published: November 2024

The accurate prediction of lithium-ion battery state of health (SOH) can extend battery life, enhance device safety, and ensure sustained reliability in critical applications. Addressing the non-linear and non-stationary characteristics of battery capacity sequences, a novel method for predicting lithium battery SOH is proposed using a deep hybrid kernel extreme learning machine (DHKELM) optimized by the improved black-winged kite algorithm (IBKA). First, to address the limitations of traditional extreme learning machines (ELMs) in capturing non-linear features and their poor generalization ability, the concepts of auto encoders (AEs) and hybrid kernel functions are introduced to enhance ELM, resulting in the establishment of the DHKELM model for SOH prediction. Next, to tackle the challenge of parameter selection for DHKELM, an optimal point set strategy, the Gompertz growth model, and a Levy flight strategy are employed to optimize the parameters of DHKELM using IBKA before model training. Finally, the performance of IBKA-DHKELM is validated using two distinct datasets from NASA and CALCE, comparing it against ELM, DHKELM, and BKA-DHKELM. The results show that IBKA-DHKELM achieves the smallest error, with an RMSE of only 0.0062, demonstrating exceptional non-linear fitting capability, high predictive accuracy, and good robustness.
Fundamentals and Applications of Fluid Mechanics and Acoustics in Biomedical Engineering
Authors: Little Iris , Gutmark Ephraim
Published: November 2024

The field of biomedical engineering has experienced important recent advances in experimental, computational, and analytical research in fluid mechanics and acoustics [...]
Three-Dimensional Printed Customized Scaffolds Covered with Decellularized Bone Extracellular Matrix for Open-Wedge High-Tibial Osteotomy
Authors: Ahn Geunseon , Kim Jun-Young , Shim Jin-Hyung , An Sang-Hyun , Kim Junsik , Kim Changhwan , Lee In-Gyu , Shin Jung-Min , Lee Byunghoon
Published: November 2024

Void fillers are required for osseous gaps generated after orthopedic procedures as medial open-wedge high-tibial osteotomy (MOWHTO) to provide sufficient structural support and a rapid osteosynthesis. We developed a novel three-dimensional (3D) printing-based platform technology using the customized 3D scaffolds covered with polycaprolactone (PCL)/β-tri-calcium phosphates (β-TCP)/bone decellularized extracellular matrix (dECM) for use as bone substitute scaffold, which can be effectively exploited to estimate the calculated correction angle with preoperative simulations. PCL/β-TCP/bone dECM scaffolds demonstrated significantly higher cell contain levels in cell seeding efficiency, excellent proliferation capacity, and promotion of early osteogenic differentiation compared with PCL/β-TCP scaffolds. The scaffolds promoted bone mineralization at the early time points of an in vivo study (8 weeks) and exhibited biodegradable properties (38% for 16 weeks). The correction angle measured after osteotomy using 3D printed scaffolds was estimated with high accuracy with low errors (10.3° ± 0.9°) and was not significantly different even in the presence of lateral cortical hinge fractures. The customized 3D scaffold enriched with PCL/β-TCP/bone dECM yielded excellent cell seeding efficiency, proliferation capacity, early osteogenic differentiation, and bone mineralization outcomes. It is expected to solve the disadvantages related to bone union in MOWHTO and to replace autografts in the future.
The Development of a Non-Invasive Screening Method Based on Serum microRNAs to Quantify the Percentage of Liver Steatosis
Authors: Soluyanova Polina , Quintás Guillermo , Pérez-Rubio Álvaro , Rienda Iván , Moro Erika , van Herwijnen Marcel , Verheijen Marcha , Caiment Florian , Pérez-Rojas Judith , Trullenque-Juan Ramón , Pareja Eugenia , Jover Ramiro
Published: November 2024

Metabolic dysfunction-associated steatotic liver disease (MASLD) is often asymptomatic and underdiagnosed; consequently, there is a demand for simple, non-invasive diagnostic tools. In this study, we developed a method to quantify liver steatosis based on miRNAs, present in liver and serum, that correlate with liver fat. The miRNAs were analyzed by miRNAseq in liver samples from two cohorts of patients with a precise quantification of liver steatosis. Common miRNAs showing correlation with liver steatosis were validated by RT-qPCR in paired liver and serum samples. Multivariate models were built using partial least squares (PLS) regression to predict the percentage of liver steatosis from serum miRNA levels. Leave-one-out cross validation and external validation were used for model selection and to estimate predictive performance. The miRNAseq results disclosed (a) 144 miRNAs correlating with triglycerides in a set of liver biobank samples (n = 20); and (b) 124 and 102 miRNAs correlating with steatosis by biopsy digital image and MRI analyses, respectively, in liver samples from morbidly obese patients (n = 24). However, only 35 miRNAs were common in both sets of samples. RT-qPCR allowed to validate the correlation of 10 miRNAs in paired liver and serum samples. The development of PLS models to quantitatively predict steatosis demonstrated that the combination of serum miR-145-3p, 122-5p, 143-3p, 500a-5p, and 182-5p provided the lowest root mean square error of cross validation (RMSECV = 1.1, p-value = 0.005). External validation of this model with a cohort of mixed MASLD patients (n = 25) showed a root mean squared error of prediction (RMSEP) of 5.3. In conclusion, it is possible to predict the percentage of hepatic steatosis with a low error rate by quantifying the serum level of five miRNAs using a cost-effective and easy-to-implement RT-qPCR method.
Mapping the Landscape of Biomechanics Research in Stroke Neurorehabilitation: A Bibliometric Perspective
Authors: Tsiakiri Anna , Plakias Spyridon , Karakitsiou Georgia , Nikova Alexandrina , Christidi Foteini , Kokkotis Christos , Giarmatzis Georgios , Tsakni Georgia , Katsouri Ioanna-Giannoula , Dimitrios Sarris , Vadikolias Konstantinos , Aggelousis Nikolaos , Vlotinou Pinelopi
Published: November 2024

Background/Objectives: The incorporation of biomechanics into stroke neurorehabilitation may serve to strengthen the effectiveness of rehabilitation strategies by increasing our understanding of human movement and recovery processes. The present bibliometric analysis of biomechanics research in stroke neurorehabilitation is conducted with the objectives of identifying influential studies, key trends, and emerging research areas that would inform future research and clinical practice. Methods: A comprehensive bibliometric analysis was performed using documents retrieved from the Scopus database on 6 August 2024. The analysis included performance metrics such as publication counts and citation analysis, as well as science mapping techniques, including co-authorship, bibliographic coupling, co-citation, and keyword co-occurrence analyses. Data visualization tools such as VOSviewer and Power BI were utilized to map the bibliometric networks and trends. Results: An overabundance of recent work has yielded substantial advancements in the application of brain–computer interfaces to electroencephalography and functional neuroimaging during stroke neurorehabilitation., which translate neural activity into control signals for external devices and provide critical insights into the biomechanics of motor recovery by enabling precise tracking and feedback of movement during rehabilitation. A sampling of the most impactful contributors and influential publications identified two leading countries of contribution: the United States and China. Three prominent research topic clusters were also noted: biomechanical evaluation and movement analysis, neurorehabilitation and robotics, and motor recovery and functional rehabilitation. Conclusions: The findings underscore the growing integration of advanced technologies such as robotics, neuroimaging, and virtual reality into neurorehabilitation practices. These innovations are poised to enhance the precision and effectiveness of therapeutic interventions. Future research should focus on the long-term impacts of these technologies and the development of accessible, cost-effective tools for clinical use. The integration of multidisciplinary approaches will be crucial in optimizing patient outcomes and improving the quality of life for stroke survivors.
New Horizons in Cancer Progression and Metastasis: Hippo Signaling Pathway
Authors: Kuracha Murali R. , Radhakrishna Uppala , Kuracha Sreenaga V. , Vegi Navyasri , Gurung Jhyama Lhamo , McVicker Benita L.
Published: November 2024

The Hippo pathway is highly evolved to maintain tissue homeostasis in diverse species by regulating cell proliferation, differentiation, and apoptosis. In tumor biology, the Hippo pathway is a prime example of signaling molecules involved in cancer progression and metastasis. Hippo core elements LATS1, LATS2, MST1, YAP, and TAZ have critical roles in the maintenance of traditional tissue architecture and cell homeostasis. However, in cancer development, dysregulation of Hippo signaling results in tumor progression and the formation secondary cancers. Hippo components not only transmit biochemical signals but also act as mediators of mechanotransduction pathways during malignant neoplasm development and metastatic disease. This review confers knowledge of Hippo pathway core components and their role in cancer progression and metastasis and highlights the clinical role of Hippo pathway in cancer treatment. The Hippo signaling pathway and its unresolved mechanisms hold great promise as potential therapeutic targets in the emerging field of metastatic cancer research.
Beyond the Surface: Uncovering Secondary Causes of Osteoporosis for Optimal Management
Authors: Hosein-Woodley Rasheed , Hirani Rahim , Issani Ali , Hussaini Anum S. , Stala Olivia , Smiley Abbas , Etienne Mill , Tiwari Raj K.
Published: November 2024

Osteoporosis (OP), a condition marked by reduced bone mineral density and increased fracture risk, can arise either as a primary disorder or secondary to other diseases and medications. While primary OP typically relates to age-related or postmenopausal changes, secondary OP results from underlying conditions or drug exposures, complicating diagnosis and management. This review explores the pathophysiology, prevalence, and treatment approaches for secondary OP arising from endocrine, renal, gastrointestinal, hematological, and autoimmune disorders, as well as medication side effects. The findings highlight that secondary OP is frequently undiagnosed, particularly in premenopausal women and men, with conditions such as chronic kidney disease, glucocorticoid use, and diabetes among the primary contributors. Management strategies must be tailored to address the underlying conditions to effectively reduce fracture risk and improve outcomes. Ultimately, this review underscores the necessity for increased clinical awareness and more targeted interventions for optimal management of secondary OP.
Transfer Learning Approaches for Brain Metastases Screenings
Authors: Luu Minh Sao Khue , Tuchinov Bair N. , Suvorov Victor , Kenzhin Roman M. , Amelina Evgeniya V. , Letyagin Andrey Yu.
Published: November 2024

Background: In this study, we examined the effectiveness of transfer learning in improving automatic segmentation of brain metastases on magnetic resonance imaging scans, with potential applications in preventive exams and remote diagnostics. Methods: We trained three deep learning models on a public dataset from the ASNR-MICCAI Brain Metastasis Challenge 2024, fine-tuned them on a small private dataset, and compared their performance to models trained from scratch. Results: Results showed that models using transfer learning performed better than scratch-trained models, though the improvement was not statistically substantial. The custom Tversky and Binary Cross-Entropy loss function helped manage class imbalance and reduce false negatives, limiting missed tumor regions. Medical experts noted that, while fine-tuned models worked well with larger, well-defined tumors, they struggled with tiny, scattered tumors in complex cases. Conclusions: This study highlights the potential of transfer learning and tailored loss functions in medical imaging, while also pointing out the models’ limitations in detecting very small tumors in challenging cases.
Neural Mechanism of Musical Pleasure Induced by Prediction Errors: An EEG Study
Authors: Ueno Fuyu , Shimada Sotaro
Published: November 2024

Background/Objectives: Musical pleasure is considered to be induced by prediction errors (surprise), as suggested in neuroimaging studies. However, the role of temporal changes in musical features in reward processing remains unclear. Utilizing the Information Dynamics of Music (IDyOM) model, a statistical model that calculates musical surprise based on prediction errors in melody and harmony, we investigated whether brain activities associated with musical pleasure, particularly in the θ, β, and γ bands, are induced by prediction errors, similar to those observed during monetary rewards. Methods: We used the IDyOM model to calculate the information content (IC) of surprise for melody and harmony in 70 musical pieces across six genres; eight pieces with varying IC values were selected. Electroencephalographic data were recorded during listening to the pieces, continuously evaluating the participants’ subjective pleasure on a 1–4 scale. Time–frequency analysis of electroencephalographic data was conducted, followed by general linear model analysis to fit the power-value time course in each frequency band to the time courses of subjective pleasure and IC for melody and harmony. Results: Significant positive fits were observed in the β and γ bands in the frontal region with both subjective pleasure and IC for melody and harmony. No significant fit was observed in the θ band. Both subjective pleasure and IC are associated with increased β and γ band power in the frontal regions. Conclusions: β and γ oscillatory activities in the frontal regions are strongly associated with musical rewards induced by prediction errors, similar to brain activity observed during monetary rewards.
Attachment Avoidance Mediates the Relationship Between Relatedness Frustration and Social Networking Sites Addiction: Conscientiousness and Neuroticism as Moderators
Authors: Zhong Shu , Hai Ri , Ahemaitijiang Nigela , Wang Xinyue , Chen Yunxiang , Liu Xiangping
Published: November 2024

Social Networking Sites Addiction (SNSA) has become increasingly prevalent among university students, posing significant challenges to their mental health and academic performance. The psychological mechanisms and personality traits contributing to this addiction are not yet fully understood. This study explored the mediating effect of attachment avoidance (AA) between relatedness frustration (RF) and SNSA, as well as the moderating roles of Conscientiousness and Neuroticism from the Big Five personality traits. Data were collected from 489 university students (M = 18.81, SD = 0.92) using the Relatedness Frustration Scale, Ten-Item Personality Inventory in Chinese, Experiences in Close Relationships Scale (ECR) Short Form, and Social Networking Sites Addiction Scale. The findings were as follows: (1) RF significantly predicted SNSA; (2) RF significantly predicted AA, which in turn significantly predicted SNSA, indicating a partial mediation; and (3) Conscientiousness and Neuroticism moderated the effect of RF on SNSA, with higher levels of these traits amplifying the positive effect of RF on SNSA. The study concluded that individuals facing RF may avoid real-life attachments and seek connections online, increasing the risk of SNSA, especially for those with high levels of Conscientiousness and Neuroticism.
Does Smartphone Use Affect Attitudes Toward Aging Among Older Adults in Rural Areas? An Empirical Analysis Using Data from the Chinese Longitudinal Aging Social Survey
Authors: Wang Xiaohui , Zhao Yifan
Published: November 2024

Fostering positive attitudes toward aging among older adults serves as a key measure of success in promoting active aging. Based on microdata from the China Longitudinal Aging Social Survey in 2018, this study uses ordinary least squares (OLS) and the two-stage least squares (2SLS) to evaluate the impact of smartphone use on the attitudes toward aging among older adults in rural areas. The results show that smartphone use significantly relieves older adults’ negative attitudes toward aging, with effects persisting even after employing robust estimations and instrumental variable techniques to address endogeneity concerns. These results emphasize the need to improve rural internet infrastructure and to promote both smartphone access and literacy among older adults in rural China to amplify these positive effects.
Effects of Different Inhibitors on the Corrosion Mitigation of Steel Rebar Immersed in NaCl-Contaminated Concrete Pore Solution
Authors: Min Sang-Ho , Lee Han-Seung , Singh Jitendra Kumar
Published: November 2024

The corrosion of steel rebar embedded in concrete under marine conditions is a major global concern. Therefore, it needs a proper corrosion mitigation method. Various types of corrosion inhibitors are used to mitigate the corrosion of steel rebar in chloride-contaminated concrete; however, selecting the appropriate inhibitor and determining its optimal concentration remains a concern. Therefore, in the present study, three types of inhibitors—calcium nitrite (CN: Ca(NO2)2), N,N′-dimethyl ethanol amine (DMEA: (CH3)2NCH2CH2OH), and L-arginine (LA: C6H14N4O2) in three different concentrations, i.e., 0.3, 0.6 and 1.2 M—were compared with a control (without inhibitor, i.e., blank) sample to determine the optimum concentration of the inhibitor for corrosion resistance performance evaluation of reinforcement bars immersed in 0.3 M NaCl-contaminated concrete pore (NCCP) solution for various durations. The corrosion resistance properties were assessed using open circuit potential (OCP), electrochemical impedance spectroscopy (EIS) with immersion duration, and potentiodynamic polarization (PDP) after 168 h of exposure. The results showed that the CN inhibitor performed exceptionally well (corrosion inhibition efficiency greater than 97%) in terms of corrosion resistance. However, due to its hazardous nature and its ban in the U.S. and European Union, CN cannot be used in construction. In comparison, while DMEA showed some effectiveness, LA performed better and is also eco-friendly. The corrosion resistance efficiency of samples containing 0.6 M LA remains above 97% even after 168 h of immersion in the NCCP solution. This efficiency is consistent throughout the entire immersion period, from 1 h to 168 h. Therefore, it is recommended that LA be used as a corrosion inhibitor for steel reinforcement bars instead of CN, particularly in chloride-contaminated concrete, as it is both effective and safer than CN.