bluuebunny/crossref_metadata_2025 huggingface dataset:
Network representations of drum sequences for classification and generation
Authors: Gómez-Marín Daniel , Jordà Sergi , Herrera Perfecto
Published: January 2025

Complex networks have emerged as a powerful framework for understanding and analyzing musical compositions, revealing underlying structures and dynamics that may not be immediately apparent. This article explores the application of complex network representations to the study of symbolic drum sequences, a topic that has received limited attention in the literature. The proposed methodology involves encoding drum rhythms as directed, weighted complex networks, where nodes represent drum events, and edges capture the temporal succession of these events. This network-based representation allows for the analysis of similarities between different drumming styles, as well as the generation of novel drum patterns. Through a series of experiments, we demonstrate the effectiveness of this approach. First, we show that the complex network representation can accurately classify drum patterns into their respective musical styles, even with a limited number of training samples. Second, we present a generative model based on Markov chains operating on the network structure, which is able to produce new drum patterns that retain the essential features of the training data. Finally, we validate the perceptual relevance of the generated patterns through listening tests, where participants are unable to distinguish the generated patterns from the original ones, suggesting that the network-based representation effectively captures the underlying characteristics of different drumming styles. The findings of this study have significant implications for music research, genre classification, and generative music applications, highlighting the potential of complex networks to provide a transparent and elegant approach to the analysis and synthesis of rhythmic structures in music.
Impact of sperm DNA fragmentation index on assisted reproductive outcomes: a retrospective analysis
Authors: Yang Bin , Xia Leizhen , Deng Rufei , Wu Liping , Zhang Zhiqin , Wu Xingwu , Ding Tao , Zhao Yan , Huang Jialyu , Huang Zhihui
Published: January 2025

Background

The role of sperm DNA fragmentation index (DFI) in fertility remains controversial. Herein, we analyzed its association with semen parameters, embryonic development, and pregnancy outcomes after in vitro fertilization (IVF) treatment. Additionally, we assessed whether DFI had a potential impact on long-term maternal and neonatal complications.

Methods

A total of 5,271 women who underwent IVF treatment for the first time between October 1, 2020, and July 31, 2023, were included from an academic fertility center. Participants were categorized into three groups based on sperm DFI: DFI < 15%, 15 ≤ DFI < 30%, and DFI ≥ 30%. We collected data on patient demographics, semen parameters, embryonic development, clinical outcomes, maternal and infant complications. Multivariate logistic regression analyses were conducted to control for potential confounders.

Results

The DFI value was negatively correlated with semen quality in males. High DFI affected the blastocyst formation rate (56.44%, 55.32%, 53.72%, respectively; P=0.045) and the rate of transferable embryos (3.97 ± 2.71, 3.90 ± 2.7, 3.38 ± 2.4, respectively; P<0.001); however, no significant difference in pregnancy outcomes was observed among the three groups. Elevated DFI did not contribute to clinically relevant adverse maternal events during pregnancy, but it was associated with an increased risk of low birth weight (3.9%, 6.6%, 10.1%, respectively; P=0.006) in newborns.

Conclusions

Sperm DFI could influence embryonic development, with a higher risk of low birthweight infants in the high DFI group. However, it does not appear to affect clinical outcomes or other perinatal complications. The role of DFI as a predictive factor in assisted reproduction, especially regarding offspring outcomes, requires further investigation with larger sample sizes.
Machine learning-based analysis of sea fog’s spatial and temporal impact on near-miss ship collisions using remote sensing and AIS data
Authors: Liu Dan , Ke Ling , Zeng Zhe , Zhang Shuo , Liu Shanwei
Published: January 2025

Sea fog is a severe marine environmental disaster that significantly threatens the safety of maritime transportation. It is a major environmental factor contributing to ship collisions. The Himawari-8 satellite’s remote sensing capabilities effectively bridge the spatial and temporal gaps in data from traditional meteorological stations for sea fog detection. Therefore, the study of the influence of sea fog on ship collisions becomes feasible and is highly significant. To investigate the spatial and temporal effects of sea fog on vessel near-miss collisions, this paper proposes a general-purpose framework for analyzing the spatial and temporal correlations between satellite-derived large-scale sea fog using a machine learning model and the near-miss collisions detected by the automatic identification system through the Vessel Conflict Ranking Operator. First, sea fog-sensitive bands from the Himawari-8 satellite, combined with the Normalized Difference Snow Index (NDSI), are chosen as features, and an SVM model is employed for sea fog detection. Second, the geographically weighted regression model investigates spatial variations in the correlation between sea fog and near-miss collisions. Third, we perform the analysis for monthly time series data to investigate the within-year seasonal dynamics and fluctuations. The proposed framework is implemented in a case study using the Bohai Sea as an example. It shows that in large harbor areas with high ship density (such as Tangshan Port and Tianjin Port), sea fog contributes significantly to near-miss collisions, with local regression coefficients greater than 0.4. While its impact is less severe in the central Bohai Sea due to the open waters. Temporally, the contribution of sea fog to near-miss collisions is more pronounced in fall and winter, while it is lowest in summer. This study sheds light on how the spatial and temporal patterns of sea fog, derived from satellite remote sensing data, contribute to the risk of near-miss collisions, which may help in navigational decisions to reduce the risk of ship collisions.
Beyond sensitivity: what are the enabling opportunities of OPM-MEG?
Authors: Roberts Timothy P. L. , Birnbaum Charlotte , Bloy Luke , Gaetz William
Published: January 2025

While optically-pumped magnetometer (OPM) technology offers a number of compelling advantages over its SQUID predecessor for magnetoencephalography (MEG), many studies and viewpoints focus on issues of (i) scalp placement, with commensurate increases in sensitivity to weak magnetic fields and (ii) room temperature operation (without the need for baths of liquid helium to maintain superconducting properties of SQUIDs). This article addresses another unique and tantalizing opportunity—the ability for the OPM array to be “wearable”, and thus to move with the participant. This is critical in adoption of naturalistic paradigms that move beyond “laboratory neuroscience” toward “real world neuroscience”. It is also critically important in application to pediatric populations who cannot or will not remain still during conventional MEG scan procedures. Application to the developing infant brain will be considered as well as application to pediatric neuropsychiatric and developmental disorders, such as autism spectrum disorder. Rather than present solutions, this article will highlight the challenges faced by conventional SQUID-based cryo-MEG and explore the potential avenues for OPM-MEG to make a positive impact to the field of pediatric neuroscience.
Case report: Near-complete response to neratinib-based treatment in HR-positive HER2-amplified metastatic breast cancer refractory to trastuzumab deruxtecan
Authors: Tokat Ünal Metin , Adibi Ashkan , Aydın Esranur , Bilgiç Şevval Nur , Özgü Eylül , Tutar Onur , Demiray Mutlu
Published: January 2025

Breast cancer (BC) is the leading cause of cancer-related mortality among women. The backbone of first-line treatment in HR+/HER2+ BC is dual anti-HER2 blockade combined with taxane chemotherapy. Although this regimen exhibits high rates of response and disease control in both HR+ and HR− cohorts, some patients could have intrinsic or develop acquired resistance to trastuzumab and/or pertuzumab. Here, we achieved a near-complete response in HR+ HER2-amplified and overexpressing metastatic BC twice through molecular tumor board (MTB) discussions: initially, with trastuzumab deruxtecan (T-DXd) when HER2 IHC was positive, and, then, with neratinib plus fulvestrant plus paclitaxel when IHC was negative. Our case presents GATA3 and NOTCH2 mutations, MCL1 and CKS1B amplifications, as well as ERBB3/KRAS overexpression and ER signaling as potential new mechanisms of resistance to T-DXd. Furthermore, we demonstrated that triplet combination could induce a remarkable response in the T-DXd–refractory setting, which could be explored in future clinical trials in HR+ and HER2-activated (by RNA or protein overexpression, amplification, and mutation) patients. Our case also highlights the importance of the MTBs to dynamically and reactively manage the course of disease and treatment on a per-patient basis.
Different nitrogen uptake patterns of plant and soil microorganisms in the forest-grassland transition zone on the Loess Plateau
Authors: Wang Lina , Deng Xu , Zhou Ying , Geng Xueqi , Zhang Zeling , Tang Yakun
Published: January 2025

Introduction

It is unclear whether plants and microorganisms achieve niche complementarity by taking up different inorganic nitrogen (N) forms to alleviate N competition, particularly in N–limited regions.

Methods

This paper conducted a 15-day 15N tracer study (15NH4NO3 or 15NH4NO3) in situ to quantitatively calculate the uptake rates of plants and microorganisms in four stands (pure Hippophae rhamnoides L, pure Pinus tabuliformis Carrière, mixed H. rhamnoides–P. tabuliformis, and Artemisia gmelinii Weber ex Stechm grassland) in the forest–grassland transition zone on the Loess Plateau during the growing season. Among them, H. rhamnoides and P. tabuliformis can associated with arbuscular mycorrhizal and ectomycorrhizal, respectively.

Results

The results indicated that H. rhamnoides in the pure stand and A. gmelinii preferred to take up 15NO3–, whereas P. tabuliformis in the pure stand preferred 15NH4+. Compared to pure stands, mixed afforestation decreased the NH4+ and NO3– uptake rate of H. rhamnoides by 87% and 70%, respectively, but did not alter the N preference of plants. Plants and microorganisms differed in their N preferences in the pure stand, whereas this was not the case in the mixed stand. The proportional similarity index between H. rhamnoides and P. tabuliformis (0.90 ± 0.01) was higher than that between plants and microorganisms in forest stands, except for P. tabuliformis and microorganisms in the mixed stand (0.90 ± 0.02).

Discussion

Those results indicated that niche complementarity by preferring different N forms can alleviate N competition. This study helped to gain a deeper understanding of the plasticity of N uptake patterns by plants and microorganisms in the forest–grassland transition zone, and provides theoretical support for vegetation restoration during the implementation of the Grain for Green program on the Loess Plateau.
Integrated metabolome and transcriptome analysis reveals potential mechanism during the bud dormancy transition of Astragalus membranaceus (Fisch.) Bge. var. mongholicus (Bge.) Hsiao
Authors: Guan Huan , Zhao Yuhuan , Chen Qing , Zhang Qianqian , Yang Pengpeng , Sun Shuying , Chen Guilin
Published: January 2025

Astragalus membranaceus (Fisch.) Bge. var. mongholicus (Bge.) Hsiao (AMM) is an important medicinal plant that is used for both medicine and food. It is widely used in Asia and South Asia. It is normally cultivated by transplanting the annual rhizomes. Understanding the dormancy of underground buds of AMM is essential for its harvest and transplantation. Despite thorough research on bud dormancy in perennial woody plants, perennial herbs, and especially medicinal plants, such as AMM, have rarely been studied. We analyzed the transcriptome and non-targeted metabolome of dormant buds stage-by-stage to investigate the regulatory mechanism of the transition from endo- to ecodormancy. A total of 1,069 differentially accumulated metabolites (DAMs) participated in amino acid and carbohydrate metabolism. Transcriptome analysis revealed 16,832 differentially expressed genes (DEGs). Functional enrichment analysis indicated that carbohydrate metabolism, hormone signaling pathways, and amino acid metabolism contributed to the transition from endo- to ecodormancy. Starch and sucrose metabolism and hormone signaling pathways were mainly analyzed in the transition between different dormancy states. During the transition from endo- to ecodormancy, the highest content of indole-3-acetic acid (IAA) and the highest number of DEGs enriched in the IAA signaling pathway demonstrated that IAA may play a key role in this process. We obtained candidate genes through co-expression network analysis, such as BGL, GN, glgC, and glgB, which are involved in starch and sucrose metabolism. The transcription factors MYB, ERF, bHLH, zinc finger, and MADS-box may regulate the genes involved in hormone signal transduction and starch and sucrose metabolism, which are critical for regulating the transition from endo- to ecodormancy in AMM buds. In summary, these results provide insights into the novel regulatory mechanism of the transition of endo- to ecodormancy in underground buds of AMM and offer new analytical strategies for breaking dormancy in advance and shortening breeding time.
Comprehensive analysis of histophysiology, transcriptomics and metabolomics in goslings exposed to gossypol acetate: unraveling hepatotoxic mechanisms
Authors: Yu Jun , Yang Haiming , Wang Jian , Huang Zixin , Chen Shi , Zhao Hongchang , Wang Jun , Wang Zhiyue
Published: January 2025

Cottonseed meal is a promising alternative to soybean meal in poultry feed, but concerns over free gossypol limit its use. Although the general toxicity of free gossypol is well-known, its specific effects on the liver—the primary site where it accumulates—are less thoroughly studied, particularly at the molecular level. This study investigated the hepatotoxic effects of gossypol acetate (GA) on goslings through a comprehensive analysis combining morphology, transcriptomics, and metabolomics. Forty-eight 7-day-old male goslings with similar body weight (BW) were randomly assigned to two groups: a control group, receiving a saline solution (0.9%, 2.5 mL/kg BW), and a GA-treated group, administered GA at 50 mg/kg BW orally for 14 days. Histological analysis revealed signs of liver damage, including granular degeneration, hepatocyte enlargement, necrosis, and mitochondrial injury. Transcriptomic analysis identified 1,137 differentially expressed genes, with 702 upregulated and 435 downregulated. Key affected pathways included carbon metabolism, glycolysis/gluconeogenesis, pyruvate metabolism, propanoate metabolism, TCA cycle, fatty acid degradation, primary bile acid biosynthesis, tryptophan metabolism, cysteine and methionine metabolism, focal adhesion, and the PPAR signaling pathway. Metabolomic analysis revealed 109 differential metabolites, 82 upregulated and 27 downregulated, implicating disruptions in linoleic acid metabolism, arachidonic acid metabolism, cAMP signaling, and serotonergic synapse pathways. Overall, GA-induced hepatotoxicity involves impaired energy production, disrupted lipid metabolism, and abnormal liver focal adhesion, leading to liver cell dysfunction. These findings highlight the vulnerability of mitochondria and critical metabolic pathways, providing insights into the molecular mechanisms of GA toxicity and guiding future studies on mitigating GA-induced liver damage in goslings.
Code Obfuscation: A Comprehensive Approach to Detection, Classification, and Ethical Challenges
Authors: Raitsis Tomer , Elgazari Yossi , Toibin Guy E. , Lurie Yotam , Mark Shlomo , Margalit Oded
Published: January 2025

Code obfuscation has become an essential practice in modern software development, designed to make source or machine code challenging for both humans and computers to comprehend. It plays a crucial role in cybersecurity by protecting intellectual property, safeguarding trade secrets, and preventing unauthorized access or reverse engineering. However, the lack of transparency in obfuscated code raises significant ethical concerns, including the potential for harmful or unethical uses such as hidden data collection, malicious features, back doors, and concealed vulnerabilities. These issues highlight the need for a balanced approach that ensures the protection of developers’ intellectual property while addressing ethical responsibilities related to user privacy, transparency, and societal impact. This paper investigates various code obfuscation techniques, their benefits, challenges, and practical applications, underscoring their relevance in contemporary software development. This study examines obfuscation methods and tools, evaluates machine learning models—including Random Forest, Gradient Boosting, and Support Vector Machine—and presents experimental results aimed at classifying obfuscated versus non-obfuscated files. Our findings demonstrate that these models achieve high accuracy in identifying obfuscation methods employed by tools such as Jlaive, Oxyry, PyObfuscate, Pyarmor, and py-obfuscator. This research also addresses emerging ethical concerns and proposes guidelines for a balanced, responsible approach to code obfuscation.
Aircraft System Identification Using Multi-Stage PRBS Optimal Inputs and Maximum Likelihood Estimator
Authors: Mazhar Muhammad Fawad , Wasim Muhammad , Abbas Manzar , Riaz Jamshed , Swati Raees Fida
Published: January 2025

A new method to discover open-loop, unstable, longitudinal aerodynamic parameters, using a ‘two-stage optimization approach’ for designing optimal inputs, and with an application on the fighter aircraft platform, has been presented. System identification of supersonic aircraft requires formulating optimal inputs due to the extremely limited maneuver time, high angles of attack, restricted flight conditions, and the demand for an enhanced computational effect. A pre-requisite of the parametric model identification is to have a priori aerodynamic parameter estimates, which were acquired using linear regression and Least Squares (LS) estimation, based upon simulated time histories of outputs from heuristic inputs, using an F-16 Flight Dynamic Model (FDM). In the ‘first stage’, discrete-time pseudo-random binary signal (PRBS) inputs were optimized using a minimization algorithm, in accordance with aircraft spectral features and aerodynamic constraints. In the ‘second stage’, an innovative concept of integrating the Fisher Informative Matrix with cost function based upon D-optimality criteria and Crest Factor has been utilized to further optimize the PRBS parameters, such as its frequency, amplitude, order, and periodicity. This unique optimum design also solves the problem of non-convexity, model over-parameterization, and misspecification; these are usually caused by the use of traditional heuristic (doublets and multistep) optimal inputs. After completing the optimal input framework, parameter estimation was performed using Maximum Likelihood Estimation. A performance comparison of four different PRBS inputs was made as part of our investigations. The model performance was validated by using statistical metrics, namely the following: residual analysis, standard errors, t statistics, fit error, and coefficient of determination (R2). Results have shown promising model predictions, with an accuracy of more than 95%, by using a Single Sequence Band-limited PRBS optimum input. This research concludes that, for the identification of the decoupled longitudinal Linear Time Invariant (LTI) aerodynamic model of supersonic aircraft, optimum PRBS shows better results than the traditional frequency sweeps, such as multi-sine, doublets, square waves, and impulse inputs. This work also provides the ability to corroborate control and stability derivatives obtained from Computational Fluid Dynamics (CFD) and wind tunnel testing. This further refines control law design, dynamic analysis, flying qualities assessments, accident investigations, and the subsequent design of an effective ground-based training simulator.
The Challenge of Defining Laterality in Horses: Is It Laterality or Just Asymmetry?
Authors: Haussler Kevin K. , le Jeune Sarah S. , MacKechnie-Guire Russell , Latif Selma N. , Clayton Hilary M.
Published: January 2025

The defining characteristic of laterality is the dominance of one side of the brain controlling specific functions of paired organs or on one side of the body. Structural and functional asymmetries are ubiquitous in horses and range from anatomical features (e.g., the length of long bones) to the gathering of sensory information (e.g., which eye is used to observe unfamiliar scenes) and motor functions (e.g., left–right differences in locomotion). There is a common tendency to assign observed structural or functional asymmetries to lateralization, which often involves more than a simple left–right difference in observed behavior. This narrative review explores the concept of laterality relative to the structural and functional asymmetries reported in horses. Inconsistent and poorly defined terminology, a widely disparate methodology, and a lack of standardized thresholds make it difficult to assess the presence or degree of laterality. Within this context, there seems to be limited evidence of laterality in horses and much more prevalent and stronger support for structural and functional asymmetries due to a wide range of well-established behavioral, nociceptive, and biomechanical mechanisms. The authors caution against generalizing the idea that all observed structural or functional asymmetries in horses are due to laterality.
Immune Modulation Effect of Administration of Rice Bran Extract with Increased Solubility Fermented by Lentinus edodes UBC-V88 in Cyclophosphamide-Treated Mice Model
Authors: Kim Gi-Jung , Jang Yelim , Hong Ji-Yoon , Kwon Kyoung-Tae , Kim Dae-Weon , Kang Dae-Jung , Hwang Sung-Joo , Lee Jung-Yun , Apostolidis Emmanouil , Kwon Young-In
Published: January 2025

There is a global and increasing demand for natural ingredients that support the human immune response. In this study, the immunomodulatory effect and mechanism of action of rice bran extract fermented by Lentinus edodes was investigated. The potential immunomodulatory effect of fermented rice bran (FRB) and processed rice bran (RB) was evaluated using male BALB/c mice whose immunity was lowered by Cyclophosphamide (CY). The changes in the weight of the thymus and the spleen, immunoglobulins, and cytokine expressions were measured as biomarkers of immunomodulating potential after 14 days of oral administration of FRB and RB (0.5 g/kg-body weight (b.w.), respectively). The FRB and RB groups treated with CY resulted in increased weight of the thymus (1.73 ± 0.40 and 1.45 ± 0.43 mg/g-b.w., respectively) compared to the CY-treated control group (1.05 ± 0.36 mg/g-b.w.). The levels of the immunoglobulin (Ig) G in the group treated with FRB (21.98 ± 2.17, p < 0.01) were significantly increased when compared to the RB group (18.48 ± 1.52 μg/mL, p < 0.01). The expression of serum cytokines, including IL-1α (p < 0.05), IL-2 (p < 0.05), IL-6 (p < 0.001), IL-12 p70 (p < 0.01), IFN-γ (p < 0.01), and TNF-α (p < 0.01) were also significantly increased by the administration of FRB (0.5 g/kg-b.w.). Similarly, the expression of spleen cytokines, including IL-1α (p < 0.05), IL-2 (p < 0.05), IFN-γ (p < 0.01), and TNF-α (p < 0.05), was also significantly increased in the group receiving the FRB (0.5 g/kg-b.w.). The natural killer cell (NK) cell activities at a 1:25 ratio of YAC-1 cells to splenocytes were significantly increased in positive control red ginseng extract 0.5 g/kg (38.64 ± 2.13%, p < 0.05), FRB (34.85 ± 3.45%, p < 0.05), and RB (25.00 ± 4.18%), compared to that of negative control CY group (12.67 ± 3.23%). These results suggest that FRB administration could stimulate the innate immune system by increasing the expression of cytokines in splenocytes and serum, especially IFN-γ, IL-2, and IL-12 (p70), which are associated with TNF-α and NK cell activities. The above results could provide the biochemical rationale to further evaluate the use of FRB for immunomodulatory applications.
Sensitivity Analysis of P-Wave Polarization Direction and Velocity Gradient Inversion
Authors: Zhao Jingru , Jing Xili , Yin Zhiyong , Fang Mengyu , Gao Shan , Zhang Tianrun
Published: January 2025

Velocity gradient is an important parameter for interpreting tomographic velocity field and identifying geological boundaries. It is usually translated from the results of seismic travel-time tomography. Recent researches show seismic polarization direction appears to be a promising data source for obtaining velocity gradient field directly. However, what remains unclear is the sensitivity of polarization direction to velocity gradient, which causes difficulty for correctly inverting polarization direction data. To clarify this problem, the sensitivity of velocity gradient parameters on polarization direction is discussed in this paper. It was found that the sensitivity of polarization direction is related to the spatial position of the model parameter. The further the parameter position is from the sensor, the lower the sensitivity is. Such nonuniform distribution of sensitivity may cause distortion of inversion results with incomplete projection data. Based on this analysis, adjustment factors are introducing to the polarization direction inversion algorithm for correctly inverting polarization direction data. Numerical tests are conducted to verify our theoretical analysis and inversion algorithm. Test results show that our theoretical analysis is accurate in both homogeneous velocity field and near velocity interfaces. The inversion method with the adjustment factor can more accurately recover the velocity gradient, offering a promising approach for geological boundary imaging.
Advanced Energy Management for Residential Buildings Optimizing Costs and Efficiency Through Thermal Energy Storage and Predictive Control
Authors: Felez Ricardo , Felez Jesus
Published: January 2025

This paper addresses the challenge of decarbonizing residential energy consumption by developing an advanced energy management system (EMS) optimized for cost reduction and energy efficiency. By leveraging the thermal inertia of building envelopes as a form of thermal energy storage (TES), the proposed EMS dynamically balances energy inputs from the electrical grid, photovoltaic (PV) systems, and battery storage, while regulating HVAC operations. Employing model predictive control (MPC) and integrating real-time data on energy prices, weather conditions, and consumption patterns, the system minimizes energy costs, while maintaining indoor thermal comfort. Simulations conducted for both summer and winter scenarios demonstrate significant reductions in energy costs. Laboratory and real-world testing confirm the EMS’s efficacy in enhancing energy efficiency, increasing PV self-consumption, and reducing reliance on grid energy, marking a step forward in sustainable energy solutions for residential applications.
Dynamic Classifier Auditing by Unsupervised Anomaly Detection Methods: An Application in Packaging Industry Predictive Maintenance
Authors: Mateo Fernando , Vila-Francés Joan , Soria-Olivas Emilio , Martínez-Sober Marcelino , Gómez-Sanchis Juan , Serrano-López Antonio José
Published: January 2025

Predictive maintenance in manufacturing industry applications is a challenging research field. Packaging machines are widely used in a large number of logistic companies’ warehouses and must be working uninterruptedly. Traditionally, preventive maintenance strategies have been carried out to improve the performance of these machines. However, these kinds of policies do not take into account the information provided by the sensors implemented in the machines. This paper presents an expert system for the automatic estimation of work orders to implement predictive maintenance policies for packaging machines. The central innovation lies in a two-stage process: a classifier generates a binary decision on whether a machine requires maintenance, and an unsupervised anomaly detection module subsequently audits the classifier’s probabilistic output to refine and interpret its predictions. By leveraging the classifier to condense sensor data and applying anomaly detection to its output, the system optimizes the decision reliability. Three anomaly detection methods were evaluated: One-Class Support Vector Machine (OCSVM), Minimum Covariance Determinant (MCD), and a majority (hard) voting ensemble of the two. All anomaly detection methods improved the baseline classifier’s performance, with the majority voting ensemble achieving the highest F1 score.
Functional and Antimicrobial Properties of Propolis from Different Areas of Romania
Authors: Albanese Gianluca , Giurgiu Alexandru Ioan , Bobiș Otilia , Urcan Adriana Cristina , Botezan Sara , Bonta Victorița , Ternar Tudor Nicolas , Pașca Claudia , Iorizzo Massimo , De Cristofaro Antonio , Caprio Emilio , Dezmirean Daniel Severus
Published: January 2025

Propolis is a complex resinous substance produced by Apis mellifera L. through a process of mixing tree resins with saliva and beeswax. This substance plays a crucial role in the hive’s defence against a range of pathogenic agents, maintaining a consistent internal temperature and aseptic environment for the bee colony. The objective of the present study was to assess the chemical composition and antibacterial characteristics of five hydroalcoholic propolis extracts sourced from diverse geographic regions within Romania. This study shows that the biological and functional properties of propolis extracts are related to the plant resources in the vicinity of the hives, and this relates to greater or lesser bioactivity of the extracts; therefore, to standardise the extracts, it is essential to catalogue the plant essences in the proximity of the hives. The antimicrobial activity of propolis extract from each apiary was evaluated against five Gram-positive, five Gram-negative bacteria, and one fungal strain, using the difuzimetric method and minimum inhibitory concentration (MIC). The results showed some variability, supporting the hypothesis that not only may the botanical origin influence the properties of propolis but also that a higher number of flavonoids influences the higher antimicrobial activity in the extracts.
Enhanced Human Skeleton Tracking for Improved Joint Position and Depth Accuracy in Rehabilitation Exercises
Authors: Abromavičius Vytautas , Gisleris Ervinas , Daunoravičienė Kristina , Žižienė Jurgita , Serackis Artūras , Maskeliūnas Rytis
Published: January 2025

The objective of this work is to develop a method for tracking human skeletal movements by integrating data from two synchronized video streams. To achieve this, two datasets were created, each consisting of four different rehabilitation exercise videos featuring various individuals in diverse environments and wearing different clothing. The prediction model is employed to create a dual-image stream system that enables the tracking of joint positions even when a joint is obscured in one of the streams. This system also mitigates depth coordinate errors by using data from both video streams. The final implementation successfully corrects the positions of the right elbow and wrist joints, though some depth error persists in the left hand. The results demonstrate that adding a second video camera, rotated 90° and aimed at the subject, can compensate for depth prediction inaccuracies, reducing errors by up to 0.4 m. By using a dual-camera setup and fusing the predicted human skeletal models, it is possible to construct a complete human model even when one camera does not capture all body parts and to refine depth coordinates through error correction using a linear regression model.
Modelling Upholstered Furniture Frames Using the Finite Element Method
Authors: Matwiej Łukasz , Wiaderek Krzysztof , Jarecki Witold , Orlikowski Dariusz , Wieruszewski Marek
Published: January 2025

This study employs the finite element method to propose a model-based design strategy for upholstered furniture frames. Three-dimensional discrete models of these frames were created, considering the orthotropic characteristics of pine (Pinus sylvestris L.) and spruce (Picea abies L.) wood, reinforced structurally with glue joints and upholstery staples. The modelling process utilised the CAE system Autodesk Inventor Nastran, applying the finite element method (FEM). Static analyses were performed by simulating standard loading conditions. The calculations incorporated the stiffness coefficients of the frame’s comb joint connections. The findings illustrate the stress distribution, displacements, and equivalent strains within the furniture frame models. The deformation and strength parameters of the frames introduce a novel perspective on designing upholstered furniture structures using the component-based FEM approach. These outcomes are applicable to the development of upholstered furniture designs.
Development and Field Testing of a Suspended Mulberry Branch Harvesting and Stubble Cutting Machine
Authors: Liu Tianhong , Yan Yunpeng , Sui Haitao , Tian Fuyang , Yan Yinfa , Zhao Bo , Song Zhanhua
Published: January 2025

Stubble cutting is a critical step in the mechanized harvesting of mulberry trees. Poor stubble cutting quality can lead to root decay, and even the death of the trees, reducing the rate of rejuvenation. In view of the relatively high damage rate of stubble cutting in the mulberry harvesting operations, this paper has conducted in-depth research and designed a mulberry branch harvesting and stubble cutting test machine. The overall structure and key technical parameters of the machine were determined and the design of critical components was theoretically analyzed. Field tests identified an optimized set of cutting parameters that effectively reduced stubble damage and energy consumption. The optimal parameter combination included a saw blade line speed of 74 m/s, a star-wheel ground clearance of 727 mm, and a cutting speed ratio of 93, resulting in a cutting energy consumption within 1 m of 241 mJ and a stubble score of 8.5. These parameters met the quality standards for mulberry harvesting. This research provides valuable data support for analyzing and optimizing the cutting parameters of mulberry stubble-cutting machines, laying a solid foundation for advancing mechanized harvesting technology for mulberry trees.
Evaluation of Condyle–Fossa Relationships in Adults with Various Skeletal Patterns Using Cone-Beam Computed Tomography
Authors: Choi Alice , Park Jae Hyun , Bay Curt , Chae Jong-Moon
Published: January 2025

This study assessed the condyle–fossa relationships in adults with different skeletal patterns using cone-beam computed tomography (CBCT). A total of 135 adult participants were included in the analysis of the CBCT images. Participants were categorized based on gender, age, race, and skeletal patterns. The measurements of the temporomandibular joint spaces were taken, which include the anterior (AS), superior (SS), posterior (PS), medial (MS), central (CS), and lateral (LS) spaces. Additionally, the dimensions of the condyle were assessed, including mediolateral thickness (MLT), anteroposterior thickness (APT), articular slope (ArS), and the vertical height of the fossa (VHF). These measurements were then compared. The average ratios of AS:SS:PS and MS:CS:LS were 1.00:1.61:1.18 and 1.00:1.15:0.79, respectively. The average values of most measurements were significantly higher in males than in females. The average value of APT was significantly higher in the late age group than in others, but there was no statistical difference according to race. The average values of PS, CS, and LS were significantly higher on the left side than on the right, while the average value of AS was significantly higher on the right side than on the left. The average values of SS, CS, and MLT were significantly higher in hypodivergent than in hyperdivergent skeletal patterns, while the average values did not show any statistical differences based on horizontal skeletal patterns. The average values of SS and CS in the Class II horizontal skeletal group were significantly lower in hyperdivergent individuals compared to other vertical skeletal patterns. In adults, statistical differences in condyle–fossa relationships were observed based on gender, age, sides, and skeletal patterns, but no differences were identified according to race.
Identifying the Spatial Range of the Pearl River Delta Urban Agglomeration from a Differentiated Perspective of Population Distribution and Population Mobility
Authors: Cao Yongwang , Li Qingpu , Yang Zaigao
Published: January 2025

Accurate identification of urban agglomeration spatial range is essential for scientific regional planning, optimal resource allocation, and sustainable development, forming the basis for regional development policy. To improve the accuracy of identifying urban agglomeration boundaries, this study fuses nighttime light data, which reflects urban economic levels, with LandScan data representing population distribution and heatmap data indicating population mobility. This fusion allows for identification from a differentiated perspective of population distribution and mobility. We propose a new method for identifying the dynamic boundaries of urban agglomerations through multi-source data fusion. This method not only provides technical support for scientific regional planning but also effectively guides the functional positioning of edge cities and the optimization of resource allocation. The results show that the spatial range identified by NTL_LS has an accuracy of 80.37% and a kappa coefficient of 0.5225, while NTL_HM achieves an accuracy of 89.17% with a kappa coefficient of 0.7342, indicating that the fusion of economic level with population mobility data more accurately reflects the spatial range of urban agglomerations in line with real development patterns. By adopting a differentiated perspective on population distribution and mobility, we propose a new approach to identifying urban agglomeration spatial range. The research results based on this method provide more comprehensive and dynamic decision-making support for optimizing transportation layouts, allocating public resources rationally, and defining the functional positioning of edge cities.
Harvesting Baltic Microalgae Chlorella vulgaris BA-167 Using Coagulant Flokor 1.2A via Static Sedimentation Under Auto- and Targeted Flocculation
Authors: Płaczek Małgorzata , Błasiak Agnieszka , Witczak Stanisław
Published: January 2025

High dewatering costs, resulting from the harvesting and separation of microalgae from the cultivation medium, pose a significant challenge to the large-scale commercial production of algae-based products, accounting for 20–60% of total cultivation expenses. This study presents research findings on the recovery of Baltic green microalgae Chlorella vulgaris BA-167 from water under static sedimentation conditions, evaluating its potential as a cost-effective harvesting method. The study investigates the effect of suspension concentration on the kinetics and efficiency of sedimentation under both autoflocculation and targeted flocculation conditions, using the Flokor 1.2A coagulant, which is commonly employed in industrial water treatment processes in Poland. The novelty of this research lies in the application of the new coagulant Flokor 1.2A to explore its potential for harvesting Chlorella vulgaris BA-167 cultivated under laboratory conditions. The results demonstrate a strong correlation between the algae removal rate and their initial concentration in the suspension, within the range of 0.375–2.380 g/L. Under autoflocculation conditions, the final minimum algae concentration in the liquid after sedimentation ranged from 0.078 to 0.148 g/L, corresponding to initial concentrations of 0.960 g/L and 0.615 g/L, respectively. Experimental results indicate that combining sedimentation with targeted flocculation significantly increases microalgae harvesting efficiency. Flokor 1.2A facilitates the coagulation and agglomeration of microalgae cells, promoting the formation of larger aggregates (flocs) ranging from 20 μm to 690 μm, which settle more easily during gravity-driven sedimentation. Within the coagulant concentration range (CF) of 0.01–0.36 g/L, sedimentation time was reduced by 3–7 times, and algae harvesting efficiency exceeded 92%. The greatest reductions in algae concentration occurred with 0.12 g/L of coagulant for 0.615 g/L algae and 0.17 g/L for 0.960 g/L algae, achieving maximum harvesting efficiencies of 83.2% and 92.9%, respectively. These results represent a 2.02–2.53-fold improvement over autoflocculation.
Continuous Wavelet Transform and CNN for Fault Detection in a Helical Gearbox
Authors: Lupea Iulian , Lupea Mihaiela
Published: January 2025

This paper studies the relevance of CWT (continuous wavelet transform) processing of vibration signals for improving the performance of CNN-based models that detect certain types of helical gearbox faults. Gear tooth damages, such as incipient and localized pitting and localized wear on helical pinion tooth flanks, combined with improper lubrication, are the faults under observation. Vibrations at the housing level for three rotating velocities of the AC motor and three load levels (for each velocity) are acquired with a triaxial accelerometer. Through CWT, the vibration signal is decomposed into 2D time-frequency grayscale images, with a filter bank of ten voices per octave in the frequency band of interest. Three 2D-CNN-based models trained on the CWT-based representation of the vibration signals measured on individual accelerometer axes (X, Y, and Z) are proposed to detect the four health states (one normal and three faulty) of the helical gearbox, regardless of the selected load level or speed on the test rig. These models achieve an accuracy higher than 99%. By fusing the CWT-based representations of the signals on individual axes for use as input to a 2D-CNN, the best-performing model for the proposed defect detection task is generated, reaching an accuracy of 99.91%.
Eye Movement Parameters in Children with Reading Difficulties
Authors: Ceple Ilze , Krauze Linda , Serpa Evita , Svede Aiga , Goliskina Viktorija , Vasiljeva Sofija , Kassaliete Evita , Ganebnaya Angelina , Volberga Liva , Truksa Renars , Ruza Tomass , Krumina Gunta
Published: January 2025

Children with dyslexia have previously been demonstrated to perform more corrective saccades in sequential non-reading saccade tasks, having trouble with maintaining a stable fixation, as well as reduced performance in smooth pursuit tasks. The current study aims to provide a comprehensive analysis of different eye movements (saccades, smooth pursuit eye movements and fixation stability) in children with and without reading difficulties who were tested by a validated reading performance test applied in the school environment. Altogether, 377 children (6–13 years old; 182 boys and 196 girls) were voluntarily involved in the study. Reading performance was determined by the Acadience® Reading literacy assessment tool. The Tobii Pro Fusion Eye-tracker was applied to determine oculomotor performance in children with and without reading difficulties. The results of saccadic eye movement, smooth pursuit eye movement, and fixation stability in a non-reading task did not reveal a statistically significant difference in oculomotor performance in children with and without reading difficulties. The results of the current study indicate that the oculomotor system in children with reading difficulties (not excluding dyslexia) is intact. The results propose that the observed differences with previous studies exploring eye movements in dyslexic children might be attributed to the participant selection.
Residual Life Prediction of SA-CNN-BILSTM Aero-Engine Based on a Multichannel Hybrid Network
Authors: He Yonghao , Wen Changjun , Xu Wei
Published: January 2025

As the core component of an airplane, the health status of the aviation engine is crucial for the safe operation of the aircraft. Therefore, predicting the remaining service life of the engine is of great significance for ensuring its safety and reliability. In this paper, a multichannel hybrid network is proposed; this network is a combination of the one-dimensional convolutional neural network (1D-CNN), the bidirectional long short-term memory network (BiLSTM), and the self-attention mechanism. For each sensor of the engine, an SA-CNN-BiLSTM network is established. The one-dimensional convolutional neural network and the bidirectional long short-term memory network are used to extract the spatial features and temporal features of the input data, respectively. Moreover, multichannel modeling is utilized to achieve the parallel processing of different sensors. Subsequently, the results are stitched together to establish a mapping relationship with the engine’s remaining useful life (RUL). Experimental validation was conducted on the aero-engine C-MAPSS dataset. The prediction results were compared with those of the other seven models to verify the effectiveness of this method in predicting the remaining service life. The results indicate that the proposed method significantly reduces the prediction error compared to other models. Specifically, for the two datasets, their mean absolute errors were only 11.47 and 11.76, the root-mean-square error values were only 12.26 and 12.78, and the scoring function values were only 195 and 227.
Comprehensive Nutrient Profiling and Untargeted Metabolomic Assessment of Siraitia grosvenorii from Different Regions and Varying Degrees of Processing
Authors: Liu Yuqiang , Yu Weiqian , Bi Mengfei , Zhang Yuting , Guan Yuan , Jiang Tiemin
Published: January 2025

The primary objective of this study was to compare the nutrition and metabolite profiles of Siraitia grosvenorii from different regions (namely Yongfu and Longsheng) and processing stages. Our findings showed that fresh Siraitia grosvenorii from Longsheng contained higher levels of total sugars, protein, and crude fat compared with those from Yongfu, though both regions had similar dietary fiber and ash content. Dried Yongfu Siraitia grosvenorii showed increased nutrient levels. A mineral analysis revealed that fresh Siraitia grosvenorii from Yongfu had the highest levels of calcium, magnesium, and potassium along with distinct differences in other mineral concentrations compared with Longsheng. Notably, fresh Yongfu fruits had higher mineral content than dried ones, except for aluminum and selenium. Through an untargeted metabolomics analysis, we identified 470 metabolites, showing significant variation between fresh samples from Yongfu and Longsheng and between fresh and dried Yongfu samples. Key metabolites included carboxylic acids, fatty acyls, and organooxygen compounds. Additionally, we observed significant enrichment in metabolic pathways such as phenylpropanoid biosynthesis, galactose metabolism, and linoleic acid metabolism, with notable differences in metabolite regulation depending on the region and processing stage. These findings highlight the influence of regional environmental factors and drying processes on the nutrient and metabolite composition of Siraitia grosvenorii.