bluuebunny/crossref_metadata_2025 huggingface dataset:
Improved Bacterial Foraging Optimization Algorithm with Machine Learning-Driven Short-Term Electricity Load Forecasting: A Case Study in Peninsular Malaysia
Authors: Zaini Farah Anishah , Sulaima Mohamad Fani , Razak Intan Azmira Wan Abdul , Othman Mohammad Lutfi , Mokhlis Hazlie
Published: November 2024

Accurate electricity demand forecasting is crucial for ensuring the sustainability and reliability of power systems. Least square support vector machines (LSSVM) are well suited to handle complex non-linear power load series. However, the less optimal regularization parameter and the Gaussian kernel function in the LSSVM model have contributed to flawed forecasting accuracy and random generalization ability. Thus, these parameters of LSSVM need to be chosen appropriately using intelligent optimization algorithms. This study proposes a new hybrid model based on the LSSVM optimized by the improved bacterial foraging optimization algorithm (IBFOA) for forecasting the short-term daily electricity load in Peninsular Malaysia. The IBFOA based on the sine cosine equation addresses the limitations of fixed chemotaxis constants in the original bacterial foraging optimization algorithm (BFOA), enhancing its exploration and exploitation capabilities. Finally, the load forecasting model based on LSSVM-IBFOA is constructed using mean absolute percentage error (MAPE) as the objective function. The comparative analysis demonstrates the model, achieving the highest determination coefficient (R2) of 0.9880 and significantly reducing the average MAPE value by 28.36%, 27.72%, and 5.47% compared to the deep neural network (DNN), LSSVM, and LSSVM-BFOA, respectively. Additionally, IBFOA exhibits faster convergence times compared to BFOA, highlighting the practicality of LSSVM-IBFOA for short-term load forecasting.
The Phenology of Coffea arabica var. Esperanza L4A5 Under Different Agroforestry Associations and Fertilization Conditions in the Caribbean Region of Costa Rica
Authors: Morales Peña Victor Hugo , Mora Garcés Argenis , Virginio Filho Elias de Melo , Villatoro Sánchez Mario , Pazmiño Pachay Willy William , Chanto Ares Esteban
Published: November 2024

This study focused on the phenology of Coffea arabica var. Esperanza L4A5, an F1 interspecific hybrid obtained by crossing commercial varieties with wild genotypes from Ethiopia and Sudan. Most phenological studies on C. arabica have been conducted in traditional high-altitude regions, leaving a gap in the understanding of its behavior in non-traditional areas such as the Caribbean region of Costa Rica. To establish a baseline on the phenological behavior of the Esperanza L4A5 hybrid in this region, we conducted a four-year study examining the effects of different agroforestry associations: (1) Albizia saman; (2) Hymenaea courbaril and Erythrina poeppigiana; (3) Anacardium excelsum and Erythrina poeppigiana; and coffee plots under full sun. Additionally, the phenology of the coffee plants was evaluated under differentiated fertilizations (physical, chemical, and without fertilization), considering meteorological factors such as temperature, humidity, and rainfall. The observed variables included the development of floral nodes, pre-anthesis, anthesis, and fruiting stages. To analyze the relationships between environmental factors, tree cover, fertilization, and the phenological stages, we employed multiple linear regression (MLR), which revealed that both tree cover and physical and chemical fertilizations had significant effects on the presence of developed floral nodes and, consequently, on fruit production. Furthermore, the random forest (RF) model was applied to capture complex interactions between variables and to rank the importance of meteorological factors, tree cover, and fertilization practices. These analyses demonstrated that the Esperanza L4A5 hybrid exhibited viable phenological development under the atypical conditions of the Caribbean region of Costa Rica, suggesting its potential to adapt and thrive in non-traditional coffee-growing areas.
Performance Analysis and Operation Parameter Optimization of Shaker-Type Harvesting for Camellia Fruits
Authors: Gao Qiaoming , Han Jianfeng , Zeng Shan , Wang Yu , Wei Wei , Wang Dongxue , Ye Hang , Lu Jing , Zeng Haoxiang
Published: November 2024

This study aims to address the challenges of achieving a high harvesting rate and low flower bud damage rate during the harvesting of camellia fruits. To this end, a dynamic model of the camellia osmantha tree and a self-developed shaker-type harvesting machine were used as research subjects. The first 24 natural frequencies and mode shapes of the camellia tree were solved using the finite element method, and the effects of vibration frequency, excitation position, and vibration duration on the harvesting rate and flower bud damage rate were quantitatively analyzed through an orthogonal experiment. The numerical analysis results indicate that the camellia tree exhibits good response characteristics at vibration frequencies of 10–15.5 Hz and 38.5 Hz. The three-factors orthogonal experiment figured out that the optimal operational parameters for shaker-type harvesting were determined to be a vibration duration of 30 s, a motor output frequency of 12.5 Hz, and a gripping position height of 50 to 60 cm above the ground. Meanwhile, under these operational parameters, the harvesting efficiency reached 96.97%, while the flower bud damage rate was only 6%.
The Optimal Dietary Sodium or Chloride Level of Broilers Fed a Corn–Soybean Meal Diet from 22 to 42 Days of Age
Authors: Cui Xiaoyan , Gao Feiyu , Zhang Weiyun , Wu Wei , Zhang Liyang , Hu Yun , Wang Shengchen , Li Tingting , Luo Xugang
Published: November 2024

The objective of this study was to assess the ideal dietary Na or Cl level for chickens from 22 to 42 d of age, utilizing a corn–soybean meal diet that maintains a 1:1 ratio of Na to Cl. At 22 d of age, a total of 288 male broilers of Arbor Acres were selected and randomly divided into one of six treatments. Each treatment contained eight replicates, with six chicks in each replicate. The control chicks were given a basic diet including 0.02% Na and 0.07% Cl without added Na or Cl, while the birds in other treatments were given diets containing different Na or Cl levels (0.13%, 0.19%, 0.25%, 0.31%, and 0.37%). With increasing dietary Na or Cl levels, linear (p < 0.0001) and quadratic (p < 0.0001) increases occurred in ADG, ADFI, and average daily water consumption, while F/G exhibited a linear (p < 0.0001) and quadratic (p < 0.0001) decrease from 22 to 42 d of age in broilers. Linear (p < 0.02) and quadratic increases (p < 0.03) were found in the heart indicator, serum Cl− concentrations, and blood Na+ and Cl− concentrations, whereas the kidney indicator, blood K+ concentrations, and serum K+, UA, and glucose (GLU) concentrations showed a linear (p < 0.04) and quadratic (p < 0.004) decrease with an increase in dietary Na or Cl levels. The excreta water content, liver indicator, and jejunal crypt depth also showed a linear increase (p < 0.02). The ideal levels of dietary Na or Cl were estimated to be 0.07% to 0.12%, based on the most suitable broken-line and asymptotic models (p ≤ 0.0002) using those sensitive indicators mentioned above. It was suggested that the suitable dietary Na or Cl level of 0.12% would adequately fulfill the Na or Cl metabolic demands of chickens from 22 to 42 d of age.
Next-Generation Remote Sensing Data at Multiple Spatial Scales Improves Understanding of Habitat Selection by a Small Mammal
Authors: Frock Catherine F. , Conner L. Mike , McCleery Robert A.
Published: November 2024

Recent advances in optical remote sensing (RS) technology in combination with lightweight Global Positioning System (GPS) tracking devices now make analyzing the multi-scale habitat selection (HS) of small mammals < 2 kg possible. However, there have been relatively few multi-scale HS studies integrating fine-scale RS data with data-rich, GPS-derived movement data from small mammals. This is critical because small mammals commonly select habitat features across multiple scales. To address this gap, we investigated the HS of a small mammal, fox squirrels (Sciurus niger), which are known to cover relatively large areas and select fine-scale environmental features. We specifically asked the following questions: (1) Do next-generation RS variables improve HS models at single spatial scales? (2) Do multi-scale HS models improve upon those at single spatial scales? Using data from 45 individuals, we constructed HS models at three spatial scales: 4 ha (210 m × 210 m), 0.09 ha (30 m × 30 m), and 0.01 ha (10 m × 10 m) using traditional and next-generation RS data. The 4-ha model, using traditional and next-generation RS data, produced the best single-scale model, explaining 58% of the variations in HS. However, the multi-scale model provided the most informative model, explaining 68% of the variations in HS. Our models provide evidence for the value of next-generation RS data when quantifying HS and additional support for the idea of studying HS at multiple spatial scales.
Crude Garden Cress Seed Oil (Lepidium sativum Linn.) Enhances Post-Thawed Boar Sperm Quality
Authors: Khophloiklang Vassakorn , Chanapiwat Panida , Kaeoket Kampon
Published: November 2024

This study aimed to examine the effects of crude garden cress seed oil (CGCSO) on frozen–thawed boar sperm qualities. Semen ejaculates (n = 12) were collected and further divided into six equal aliquots based on CGCSO concentrations (0, 0.5, 1, 1.5, 2, and 2.5% v/v) in the freezing extender. Semen samples were processed and cryopreserved utilizing the traditional liquid nitrogen vapor technique. Subsequently, semen samples were thawed in a thermos with warm water at 50 °C for 12 s and evaluated for sperm morphology using scanning electron microscopy, sperm motility using a CASA, sperm viability, acrosome integrity, mitochondrial function, MDA level, total antioxidant capacity (TAC), glutathione peroxidase (GSH-Px), and catalase (CAT) activity. The results indicated that 1% CGCSO resulted in superior post-thaw sperm characteristics, including enhanced sperm morphology, motility, viability, acrosome integrity, and mitochondrial function. Particularly, the total motile sperm increased by 16.5%, progressive motile sperm increased by 13.0%, viability improved by 15.1%, acrosome integrity increased by 14%, and mitochondrial function improved by 14.1% compared to the control group. CGCSO treatment at 1% and 1.5% exhibited the lowest level of MDA (45.73 ± 11.2 and 45.73 ± 11.3 µmol/L, respectively) compared to the other groups. The CGCSO-supplemented groups showed higher values of TAC, GSH-Px, and CAT than the control group but not significantly.
Synergistic Effects of Mannan Oligosaccharides and Onion Peels on In Vitro Batch Culture Fermentation of High Concentrate and Forage Diets
Authors: Olagunju Lydia K. , Adelusi Oludotun O. , Dele Peter A. , Shaw Yasmine , Brice Rosetta M. , Orimaye Oluteru E. , Villarreal-González Jorge A. , Kang Hye Won , Kholif Ahmed E. , Anele Uchenna Y.
Published: November 2024

The current study evaluated the effect of combining mannan oligosaccharide (MOS) and onion peel (OP) on ruminal in vitro total gas (GP), greenhouse gas emissions, dry matter and fiber fraction digestibility, partitioning factor (PF24; mg degradable DM per mL gas), microbial mass, and volatile fatty acids using two dietary substrates: high forage (HF) and high concentrate (HC) diets. The study was arranged as a 2 × 2 × 6 factorial design with two dietary substrates, two time points (6 and 24 h), and six treatments. The treatments included a control group with no MOS or OP administration and groups administered with 2% of a mixture containing MOS and OP in the following ratios: 1:0 (MOS), 0:1 (OP), 1:1 (MOS:OP), 1:2 (MOS:2OP), and 1:3 (MOS:3OP). No significant diet × treatment interactions were observed for any of the measured parameters. However, treatments decreased (p < 0.05) the undegraded portion of HC, and treatment × substrate interactions were significant (p < 0.05) for PF24 and microbial mass. The treatments in the HC diet produced higher GP (p < 0.001) at 6 h compared to the treatments in the HF diet. Administration of MOS:2OP to the HC diet increased GP at 24 h of incubation, while the lowest GP was observed with the OP in the HF diet. The administration of MOS, OP, and MOS:2OP to the HC diet decreased methane production at 24 h of incubation. Additionally, MOS:2OP and MOS:3OP increased (p < 0.001) degradable acid detergent fiber (dADF) in the HC diet at 6 h of incubation. Both OP and MOS:3OP decreased the degradability of acid detergent lignin in the HC diet (p < 0.001). The OP also resulted in the lowest DM disappearance (p < 0.001) at 24 h of incubation in the HF diet, while the MOS:3OP had the highest dADF. At the end of incubation, the highest productions of total volatile fatty acids and acetate were observed (p = 0.002) with the MOS:OP administration in the HC diet, whereas the lowest values were observed with MOS and OP administration to the HF diet. The inclusion of mannan oligosaccharide and onion peel combinations as additives improved substrate (HC and HF) fermentation, leading to higher GP and volatile fatty production, and modulated fiber degradability by improving the breakdown of acid detergent fiber and acid detergent lignin.
The Impact of Acute Ammonia Nitrogen Stress on the Gill Tissue Structure and Antioxidant Ability of Gills and Red and White Muscle in Juvenile Yellowfin Tuna (Thunnus albacares)
Authors: Sun Yongyue , Fu Zhengyi , Liu Xuancheng , Ma Zhenhua
Published: November 2024

To explore the impacts of acute ammonia nitrogen (NH3-N) stress on gill structure and the antioxidant ability of red and white muscles in juvenile yellowfin tuna (Thunnus albacares), this study used natural seawater as a control, establishing two experimental NH3-N groups at 5 and 10 mg/L. Gills and red and white muscle were taken at 6, 24, and 36 h for the determination of malondialdehyde (MDA), superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GHS-PX) levels, and to observe gill structure. The results indicated that, with increasing time, the MDA concentration and CAT activity in the gills of the 5 mg/L group showed a trend of first increasing and then decreasing, while SOD activity exhibited a downward trend. In the 10 mg/L group, MDA concentration showed an increasing trend, while SOD, CAT, and GSH-PX activities demonstrated a trend of first increasing and then decreasing. In the 5 mg/L group, the MDA concentration and GSH-PX activity in the red muscle showed an increasing trend. In the 10 mg/L group, MDA concentration and SOD and CAT activities exhibited a downward trend. In the 5 mg/L group, the MDA concentration and SOD activity in the white muscle showed a downward trend, while CAT activity exhibited an increasing trend. In the 10 mg/L group, MDA concentration and CAT activity demonstrated a trend of first increasing and then decreasing, while SOD activity showed a downward trend. Ammonia nitrogen can lead to necrosis and shedding of gill epithelial cells, cell vacuolation, edema, as well as proliferation, hypertrophy, and fusion of secondary lamellae. This study demonstrates that NH3-N can alter gill structure and reduce the antioxidant ability of gills and red–white muscle. The findings provide scientific data that can support the aquaculture and recirculating aquaculture systems of juvenile tuna.
Air Attenuation in Octave Bands and How to Normalize Room Acoustic Measurements to a Standard Atmosphere
Authors: Rindel Jens Holger
Published: November 2024

The air attenuation of pure tones as a function of temperature and humidity is well known and described in ISO and ANSI standards. However, room acoustic measurements are performed in octave bands, which is the reason for the complicated, non-linear behavior of the air attenuation. It is known that room acoustic measurement results depend on air temperature and humidity, and these atmospheric data should always be reported in connection with room acoustic measurements. A calculation model for the air attenuation can make it possible to normalize the room acoustic results. For accurate results, it is possible to apply a summation method on each time sample in the impulse response. An approximation to the air attenuation at and above 1 kHz is possible by linearization using the pure-tone attenuation of two different frequencies, one frequency valid for the early part of the impulse response and another frequency valid for the later part of the impulse response. The purpose of the suggested methods is to make it possible to normalize room acoustic measurements to a standard atmosphere.
Shape of the Sagittal Curvatures of the Spine in Young Female Volleyball Players
Authors: Puszczalowska-Lizis Ewa , Mikulakova Wioletta , Fitas Patrycja , Lizis Sabina
Published: November 2024

Background: The issue of the relation betweeen training loads on the shape of the spine of young players is of significant importance, as with the advancement of training seniority, unfavorable changes may be perpetuated resulting in possible consequences in the next stages of ontogenesis. The aim of this study was to assess the formation of the sagittal curvatures of the spine in girls practicing volleyball versus their nonpractising peers. Methods: We examined 60 girls aged 10–13 years, including 30 volleyball players and 30 untrained peers. The Baseline Bubble inclinometer was applied as a research. The data were analyzed based on Mann–Whitney U test and Pearson Chi-square test. Results. There were statistically significant intergroup differences in lumbar lordosis curvature values (Z = −2.67; p = 0.007). The prevalence of correctness values of the thoracic kyphosis curvature, was group-dependent (χ2(1) = 4.34; p = 0.037). Group also determined the prevalence of lumbar lordosis normalities (χ2(1) = 5.41; p = 0.020). Conclusions. Volleyball has a beneficial effect on the formation of the thoracic kyphosis, while the lumbar lordosis is shallowed under the influence of training. This indicates the need for a holistic approach to player training and the need to supplement the technique and tactics training with exercises to strengthen the muscles that stabilize the lumbar spine, improve spinal mobility, learn how to control the anterior tilt of the pelvis and train the fascia.
Comparison of the Sensitivity of Various Fibers in Distributed Acoustic Sensing
Authors: Turov Artem T. , Konstantinov Yuri A. , Claude D. , Maximenko Vitaliy A. , Krishtop Victor V. , Korobko Dmitry A. , Fotiadi Andrei A.
Published: November 2024

Standard single-mode telecommunication optical fiber is still one of the most popular in distributed acoustic sensing. Understanding the acoustic, mechanical and optical features of various fibers available currently can lead to a better optimization of distributed acoustic sensors, cost reduction and adaptation for specific needs. In this paper, a study of the performances of seven fibers with different coatings and production methods in a distributed acoustic sensor setup is presented. The main results include the amplitude–frequency characteristic for each of the investigated fibers in the range of acoustic frequencies from 100 to 7000 Hz. A single-mode fiber fabricated using the modified chemical vapor deposition technique together with a polyimide coating has shown the best sensitivity to acoustic events in the investigated range of frequencies. All of this allows us to both compare the studied specialty fibers with the standard single-mode fiber and choose the most suitable fiber for a specific application, providing an enhancement for the performance of distributed acoustic sensors and better adaptation for the newly aroused potential applications.
Causes of Multi-Mechanism Abnormal Formation Pressure in Offshore Oil and Gas Wells
Authors: Xu Yang , Yang Jin , Hu Zhiqiang , Zhao Quanmin , Li Lei , Yin Qishuai
Published: November 2024

This study thoroughly investigates the complex origins of abnormal formation pressure in offshore oil and gas wells, taking the Rio del Rey Basin in Cameroon as a case study. Renowned for its abundant oil and gas resources, the area faces unique challenges in predicting overpressure due to its high-temperature and high-pressure reservoir characteristics. By quantitatively analyzing the main mechanisms such as undercompaction, high-temperature fluid expansion, and mud diapirism, the study addresses the complexities of overpressure prediction. This paper introduces an innovative analytical framework that combines hierarchical clustering algorithms with the LightGBM model. Further refined by the application of Bayesian optimization, the model intelligently adjusts hyperparameters to enhance predictive accuracy. Utilizing well logging data and applying machine learning techniques, the paper classifies and identifies different mechanisms causing abnormal pressures, achieving a model prediction accuracy of 0.942. The research findings highlight the predominant role of the undercompaction mechanism, accounting for approximately 70% of the abnormal high-pressure events in the study area. Fluid expansion and shale diapirism contribute smaller but significant proportions of 10% and 20%, respectively. These quantitative insights into the pressure mechanisms are vital for optimizing drilling operations and reducing risks in oil and gas exploration. The study’s hybrid approach, integrating geophysical analysis with advanced computational techniques, sets a precedent for future research. It provides new avenues for applying machine learning to understand complex geological phenomena in similar geological environments and makes a significant contribution to the strategic planning of hydrocarbon exploration and production activities.
Operation of Photo Electron Spectrometers for Non-Invasive Photon Diagnostics at the European X-Ray Free Electron Laser
Authors: Laksman Joakim , Dietrich Florian , Maltezopoulos Theophilos , Liu Jia , Ferreira de Lima Danilo Enoque , Gerasimova Natalia , Karpics Ivars , Kujala Naresh , Schmidt Philipp , Karabekyan Suren , Serkez Svitozar , Grünert Jan
Published: November 2024

Angle-resolved photoelectron spectrometers with microchannel plate detectors and fast digitizer electronics are versatile and powerful devices for providing non-invasive single-shot photon diagnostics at a MHz repetition rate X-ray free-electron lasers. In this contribution, we demonstrate and characterize the performance of our two operational photoelectron spectrometers for the application of hard X-rays and soft X-rays as well as new automation tools and online data analysis that enable continuous support for machine operators and instrument scientists. Customized software has been developed for the real-time monitoring of photon beam polarization and spectral distribution both in single-color and two-color operation. Hard X-ray operation imposes specific design challenges due to poor photoionization cross-sections and very high photoelectron velocities. Furthermore, recent advancements in machine learning enable resolution enhancement by training the photoelectron spectrometer together with an invasive high-resolution spectrometer, which generates a response function model.
Earthquake Prediction and Alert System Using IoT Infrastructure and Cloud-Based Environmental Data Analysis
Authors: Rosca Cosmina-Mihaela , Stancu Adrian
Published: November 2024

Earthquakes are one of the most life-threatening natural phenomena, and their prediction is of constant concern among scientists. The study proposes that abrupt weather parameter value fluctuations may influence the occurrence of shallow seismic events by focusing on developing an innovative concept that combines historical meteorological and seismic data collection to predict potential earthquakes. A machine learning (ML) model utilizing the ML.NET framework was designed and implemented. An analysis was undertaken to identify which modeling approach, value prediction, or data classification performs better in forecasting seismic events. The model was trained on a dataset of 8766 records corresponding to the period from 1 January 2001 to 5 October 2024. The achieved accuracy of the model was 95.65% for earthquake prediction based on weather conditions in the Vrancea region, Romania. The authors proposed a unique alerting algorithm and conducted a case study that evaluates multiple predictive models, varying parameters, and methods to identify the most effective model for seismic event prediction in specific meteorological conditions. The findings demonstrate the potential of combining Internet of Things (IoT)-based environmental monitoring with AI to improve earthquake prediction accuracy and preparedness. An IoT-based application was developed using C# with ASP.NET framework to enhance earthquake prediction and public warning capabilities, leveraging Azure cloud infrastructure. The authors also created a hardware prototype for real-time earthquake alerting, integrating the M5Stack platform with ESP32 and MPU-6050 sensors for validation. The testing phase and results describe the proposed methodology and various scenarios.
Research on Occurrence Law and the Prevention of Rockbursts in Main Roadways Affected by Mining Activities: Two Case Studies from Gaojiapu and Cuimu Coal Mines, Shaanxi, China
Authors: Zhang Yinfeng , Wang Guifeng , Tan Lihai , Wang Ruizhi , Mu Zonglong , Cao Anye , Dou Linming
Published: November 2024

Rockburst, one of the leading types of disaster in mining and rock engineering causing serious injuries and the loss of property, frequently occurs, involving various features and complex evolutionary mechanisms. Compared to rockbursts occurring at mining faces, those occurring in main roadways cause more serious problems for mine production. This paper first analyzes the characteristics of rockbursts in main roadways using two case studies involving the Gaojiapu and Cuimu coal mines. The causes of rockbursts in main roadways were studied using microseismic monitoring, energy density cloud maps, and seismic velocity tomography. During the mining of the 22306 working face in the Cuimu coal mine, targeted measures, such as deep-hole blasting of the roof strata and deep-hole blasting of the coal seam, were implemented to prevent rockbursts in the main roadways. The effectiveness of these measures was verified through long-term analysis of tremor activities. The study found that the influence of mining at two working faces on both sides of main roadways was significantly greater than that from a single-sided working face. The intensity of the tremor activities occurring near the main roadways was correlated with the distance from the working face to the main roadways. The closer the working face was to the main roadways, the stronger the tremor activities were near the main roadways. According to the distribution range of the tremors, the influence area of working face mining exceeded 800 m, with tremors distributed linearly along the main roadways. Even five months after the completion of working face mining, there were still a large number of tremors near the main roadways, which gradually disappeared after another five months. Mining activities were the main reason for the occurrence of main roadway rockbursts and the stress concentration within the main roadways themselves was another reason for the occurrence of rockbursts. The influence of working face mining could be reduced by deep-hole blasting of roof strata and the stress concentration within main roadways themselves could be reduced by large-diameter drilling. Those joint preventive measures effectively prevented the occurrence of rockbursts in main roadways. This study is of important theoretical and practical significance for further studies of rockburst mechanisms and prevention in regard to main roadways in coal mines, and the findings are significant in terms of the enhancement of safety in coal mines.
How Resilient Are Kolmogorov–Arnold Networks in Classification Tasks? A Robustness Investigation
Authors: Ibrahum Ahmed Dawod Mohammed , Shang Zhengyu , Hong Jang-Eui
Published: November 2024

Kolmogorov–Arnold Networks (KANs) are a novel class of neural network architectures based on the Kolmogorov–Arnold representation theorem, which has demonstrated potential advantages in accuracy and interpretability over Multilayer Perceptron (MLP) models. This paper comprehensively evaluates the robustness of various KAN architectures—including KAN, KAN-Mixer, KANConv_KAN, and KANConv_MLP—against adversarial attacks, which constitute a critical aspect that has been underexplored in current research. We compare these models with MLP-based architectures such as MLP, MLP-Mixer, and ConvNet_MLP across three traffic sign classification datasets: GTSRB, BTSD, and CTSD. The models were subjected to various adversarial attacks (FGSM, PGD, CW, and BIM) with varying perturbation levels and were trained under different strategies, including standard training, adversarial training, and Randomized Smoothing. Our experimental results demonstrate that KAN-based models, particularly the KAN-Mixer, exhibit superior robustness to adversarial attacks compared to their MLP counterparts. Specifically, the KAN-Mixer consistently achieved lower Success Attack Rates (SARs) and Degrees of Change (DoCs) across most attack types and datasets while maintaining high accuracy on clean data. For instance, under FGSM attacks with ϵ=0.01, the KAN-Mixer outperformed the MLP-Mixer by maintaining higher accuracy and lower SARs. Adversarial training and Randomized Smoothing further enhanced the robustness of KAN-based models, with t-SNE visualizations revealing more stable latent space representations under adversarial perturbations. These findings underscore the potential of KAN architectures to improve neural network security and reliability in adversarial settings.
Truck Transportation Scheduling for a New Transport Mode of Battery-Swapping Trucks in Open-Pit Mines
Authors: Xiao Yufeng , Zhou Wei , Luan Boyu , Yang Keyi , Yang Yuqing
Published: November 2024

To address the scheduling challenges associated with the increasing deployment of battery-swapping trucks in open-pit mines, this study proposes a multi-objective scheduling optimization model. This model accounts for the unique characteristics of battery-swapping trucks by incorporating constraints related to battery swapping alerts, the selection of battery-swapping stations, and the impact of ambient temperature on battery capacity. The primary objective is to minimize the total haulage cost and total waiting time. Both a genetic algorithm and an adaptive genetic algorithm are applied to solve the proposed multi-objective scheduling optimization model. The aim is to identify an optimal scheduling solution without violating any model constraints. Results demonstrate that both the basic genetic algorithm and the adaptive genetic algorithm effectively achieve truck transportation scheduling. However, the adaptive genetic algorithm surpasses the basic genetic algorithm, reducing the total transportation costs by 5.6% and total waiting time by 17.4%. It also reduces the number of battery swaps and transportation distance by 15.8% and 1.2%, respectively. The proposed multi-objective scheduling optimization model successfully minimizes the waiting time and transportation costs of battery-swapping trucks while ensuring the completion of production tasks. This approach provides valuable technical support for improving the production and transportation efficiency of open-pit mining operations.
Heart Sound Classification Using Harmonic and Percussive Spectral Features from Phonocardiograms with a Deep ANN Approach
Authors: Singh Anupinder , Arora Vinay , Singh Mandeep
Published: November 2024

Cardiovascular diseases (CVDs) are a leading cause of mortality worldwide, with a particularly high burden in India. Non-invasive methods like Phonocardiogram (PCG) analysis capture the acoustic activity of the heart. This holds significant potential for the early detection and diagnosis of heart conditions. However, the complexity and variability of PCG signals pose considerable challenges for accurate classification. Traditional methods of PCG signal analysis, including time-domain, frequency-domain, and time-frequency domain techniques, often fall short in capturing the intricate details necessary for reliable diagnosis. This study introduces an innovative approach that leverages harmonic–percussive source separation (HPSS) to extract distinct harmonic and percussive spectral features from PCG signals. These features are then utilized to train a deep feed-forward artificial neural network (ANN), classifying heart conditions as normal or abnormal. The methodology involves advanced digital signal processing techniques applied to PCG recordings from the PhysioNet 2016 dataset. The feature set comprises 164 attributes, including the Chroma STFT, Chroma CENS, Mel-frequency cepstral coefficients (MFCCs), and statistical features. These are refined using the ROC-AUC feature selection method to ensure optimal performance. The deep feed-forward ANN model was rigorously trained and validated on a balanced dataset. Techniques such as noise reduction and outlier detection were used to improve model training. The proposed model achieved a validation accuracy of 93.40% with sensitivity and specificity rates of 82.40% and 80.60%, respectively. These results underscore the effectiveness of harmonic-based features and the robustness of the ANN in heart sound classification. This research highlights the potential for deploying such models in non-invasive cardiac diagnostics, particularly in resource-constrained settings. It also lays the groundwork for future advancements in cardiac signal analysis.
Biomarkers of Frailty in Patients with Advanced Chronic Liver Disease Undergoing a Multifactorial Intervention Consisting of Home Exercise, Branched-Chain Amino Acids, and Probiotics
Authors: Laghi Luca , Ortiz Maria Àngels , Rossi Giacomo , Román Eva , Mengucci Carlo , Cantó Elisabet , Biagini Lucia , Sánchez Elisabet , Mulet Maria , García-Osuna Álvaro , Urgell Eulàlia , Kaur Naujot , Poca Maria , Padrós Josep , Nadal Maria Josep , Cuyàs Berta , Alvarado Edilmar , Vidal Silvia , Juanes Elena , Ferrero-Gregori Andreu , Escorsell Àngels , Soriano German
Published: November 2024

Frailty in cirrhosis or advanced chronic liver disease (ACLD) is a relevant prognostic factor. In the present study, we aimed to analyze potential biomarkers associated with frailty and its improvement in patients with ACLD. We analyzed the serum of outpatients with ACLD who participated in a previous study (Román, Hepatol Commun 2024) in which frailty was assessed using the liver frailty index (LFI), and patients who were frail or prefrail were randomized to a multifactorial intervention (home exercise, branched-chain amino acids, and probiotics) or control for 12 months. We determined a biomarker battery of inflammation, bacterial translocation, and liver damage in blood and urine and blood metabolomics by 1H-NMR. Thirty-seven patients were included. According to the LFI, 32 patients were frail or prefrail, and 5 were robust. At baseline, LFI correlated with LBP, sCD163, mtDNA, FGF-21, urinary NGAL, urinary claudin-3, and the metabolites mannose, ethanol, and isoleucine. During the study, patients in the intervention group showed an improvement in LFI and a decrease in CRP, LBP, sCD163, and ccK18 compared to the control group. Metabolomics showed a decrease in dimethyl sulfone and creatinine and an increase in malonate, ornithine, isoleucine, and valine in the intervention group. We conclude that frailty in patients with ACLD is associated with biomarkers of systemic inflammation, bacterial translocation, and liver damage, and alterations of amino acid and short-chain fatty acid metabolism.
Baseline Raman Spectral Fingerprints of Zebrafish Embryos and Larvae
Authors: Abreu Isabel Oliveira , Teixeira Cláudia , Vilarinho Rui , Rocha A. Cristina S. , Moreira Joaquim Agostinho , Oliva-Teles Luís , Guimarães Laura , Carvalho António Paulo
Published: November 2024

As a highly sensitive vibrational technique, Raman spectroscopy (RS) can provide valuable chemical and molecular data useful to characterise animal cell types, tissues and organs. As a label-free, rapid detection method, RS has been considered a valuable asset in forensics, biology and medicine. The technique has been applied to zebrafish for various purposes, including physiological, biochemical or bioaccumulation analyses. The available data point out its potential for the early diagnosis of detrimental effects elicited by toxicant exposure. Nevertheless, no baseline spectra are available for zebrafish embryos and larvae that could allow for suitable planning of toxicological assessments, comparison with toxicant-elicited spectra or mechanistic understanding of biochemical and physiological responses to the exposures. With this in mind, this work carried out a baseline characterisation of Raman spectra of zebrafish embryos and larvae throughout early development. Raman spectra were recorded from the iris, forebrain, melanocytes, heart, muscle and swim bladder between 24 and 168 h post-fertilisation. A chemometrics approach, based on partial least-squares discriminant analysis (PLS-DA), was used to obtain a Raman characterisation of each tissue or organ. In total, 117 Raman bands were identified, of which 24 were well represented and, thus, retained in the data analysed. Only three bands were found to be common to all organs and tissues. The PLS-DA provided a tentative Raman spectral fingerprint typical of each tissue or organ, reflecting the ongoing developmental dynamics. The bands showed frequencies previously assigned to collagen, cholesterol, various essential amino acids, carbohydrates and nucleic acids.
Effectiveness and Durability of a Workplace Sedentary Behavior Intervention Based on the Total Worker Health® Approach
Authors: Wipfli Brad , Wild Sara , Hanson Ginger , Shea Steven A. , Winters-Stone Kerri , Olawole Wura , Kozlowski Renee , Thosar Saurabh S.
Published: November 2024

We used the Total Worker Health® approach to develop a multi-component workplace sedentary behavior intervention and tested intervention effectiveness in a cluster randomized trial. Participants (n = 198; 75% female) were recruited from three call-centers (two intervention and one usual practice control). All worksites received pedal stand active workstations. The usual practice site received no additional support, while the intervention group completed a six-month program of activities including computer-based training, behavioral self-monitoring, health and safety discussions, and pedaling competitions. Data collection included a survey, a physical health assessment, and accelerometer measures of sedentary behavior, physical activity, and sitting/standing time. Primary analyses were generalized estimating equations comparing changes between intervention and usual practice conditions over time, along with analyses of changes in both groups combined over time. Six-month results revealed less prolonged sitting and reductions in musculoskeletal pain in both groups (all p < 0.05), while the intervention group showed additional improvements in moderate physical activity (p < 0.001) and use of pedal stands (p < 0.01). At 12-months, the additional physical activity and pedal stand use in the intervention group regressed to baseline levels, while reductions in prolonged sitting in both groups were durable (p < 0.01). This study adds to previous research showing the effectiveness of the Total Worker Health® approach for workplace health and safety. Results also show that, while providing employees with health and safety resources is beneficial, providing ongoing support for the adoption and use of resources is more effective.
Promoting Well-Being from a Gender Perspective: A Systematic Review of Interventions Using Digital Tools and Serious Games
Authors: Esposito Ciro , Sulla Francesco , Toto Giusi Antonia , Berardinetti Valentina , Lavanga Andreana , Savino Francesco Pio , Iuso Salvatore , Logrieco Maria Grazia Mada , Ascorra Costa Maria Eugenia Paula
Published: November 2024

Gender inequalities continue to pose a significant issue across various aspects of life, adversely impacting the well-being of both females and males. These disparities often stem from the ingrained gender stereotypes passed down to young individuals through parental guidance, educational systems, and media portrayal. For this reason, within the psycho-pedagogical field, various intervention models have been developed in recent years, leveraging digital tools to combat stereotypes and enhance well-being among adolescents. The aim of this systematic review is, therefore, to identify studies employing digital tools, particularly serious games, to promote well-being from a gender perspective. The review was conducted using the PRISMA guidelines and collected articles from four databases: Scopus, the Web of Science, PubMed, and PsycInfo. The screening process culminated in the selection of 15 articles. The findings reveal a proliferation of platforms, applications, and programs aimed at promoting well-being by addressing emotional, cognitive (or mental), physical, and sexual health dimensions. Some contributions emphasize nurturing positive attributes within individuals or fostering empowerment as a precursor to well-being. Additionally, certain articles delve into the effect of the COVID-19 pandemic on the well-being of young men and women; in particular, the authors investigated the effect of using an app to improve well-being before and after the pandemic. This systematic review aims to expand the knowledge base on technology-based interventions for social change. It endeavors to empower educators and advance the creation of innovative, evidence-based digital tools that can enhance positive mental health, promote gender equality education, and foster the well-being of young people.
Natural Disasters as a Maternal Prenatal Stressor and Children’s Neurodevelopment: A Systematic Review
Authors: Ünsel-Bolat Gül , Yıldırım Sema , Kılıçaslan Fethiye , Caparros-Gonzalez Rafael A.
Published: November 2024

The intrauterine period is a time of high sensitivity in the development of the embryo and the fetus. Therefore, low levels of maternal stress are closely associated with healthy brain development in the neonatal and early childhood periods. There is increasing evidence linking natural disasters as prenatal maternal stress (PNMS) to neurodevelopmental disorders (including subclinical manifestations). Natural disasters involve many factors in addition to the trauma they cause, including loss and the physical and psychosocial difficulties that result from that trauma. This review article aims to bring together research findings on the neurodevelopmental effects of natural disasters on children as PNMS. It also looks at how factors such as gestational age and gender contribute to these effects. We conducted a systematic review on PubMed, Web of Science, and Scopus, with 30 studies meting the inclusion criteria. This systematic review was conducted in accordance with the PRISMA guidelines. A total of 1,327,886 mother–child dyads participated in the included studies. The results of the studies indicate that natural disasters have a negative impact on children’s outcomes in terms of cognitive development, language development, autism/autism-like features, motor skills, performance in mathematics, mental development, sleep, attention, behavioral and emotional problems, and various psychiatric comorbidities.
Beta-2-Microglobulin Maintains Overall Survival Prediction in Binet A Stage Chronic Lymphocytic Leukemia Patients with Compromised Kidney Function in Both Treatment Eras of Chemoimmunotherapy and Targeted Agents
Authors: Bohn Jan-Paul , Stolzlechner Valentina , Göbel Georg , Willenbacher Wolfgang , Pirklbauer Markus , Steiner Normann , Wolf Dominik
Published: November 2024

Background: Elevated beta-2-microglobulin (B2M) plasma levels commonly imply a higher CLL-IPI risk category for short overall survival (OS), but the risk model was not adjusted for compromised kidney function and not validated in Binet A stage CLL patients. Methods: CLL patients were identified from 2000 to 2022 at Innsbruck University Hospital, Austria. B2M levels, CLL-IPI risk stratification, and kidney function were assessed. Treatment modalities in case of disease progression and OS data during follow-up were evaluated. Results: A total of 259 Binet A stage CLL patients were identified; 16.9% (n = 44/259) presented with concurrent chronic kidney disease (CKD, GFR < 60 mL/min). Median OS was 170 months and was similar in CKD and non-CKD patients (p = 0.25). The CLL-IPI facilitated prognostic segregation in both CKD (p = 0.02) and non-CKD patients (p = 0.008). Although more frequently elevated in CKD patients (44.1% versus 10.6%, p < 0.001), B2M > 3.5 mg/L remained associated with inferior OS in this subgroup (p = 0.03). Contrary to the CLL-IPI, the prognostic value of B2M alone was also maintained in CLL patients diagnosed and potentially treated frontline in the era of targeted agents (2014–2022, p = 0.03). Conclusions: B2M retains its prognostic value for OS in early-stage CLL patients with concurrent CKD and still represents a promising covariate for up-coming prognostic models to identify patients at high risk for inferior OS in the era of targeted agents.
Inhibition of K+ Channels Affects the Target Cell Killing Potential of CAR T Cells
Authors: Medyouni Ghofrane , Vörös Orsolya , Jusztus Vivien , Panyi György , Vereb György , Szöőr Árpád , Hajdu Péter
Published: November 2024

Ion channels of T cells (Kv1.3, KCa3.1, and CRAC) participate in the regulation of activation and effector functions via modulation of the Ca2+-dependent pathway. T cells expressing chimeric antigen receptors (CAR T cells) showed a remarkable role in anti-tumor therapy, especially in the treatment of chemotherapy-resistant liquid cancers. Nevertheless, many challenges remain to be overcome to improve the treatment for solid tumors. In this study, we assessed the expression and role of ion channels in CAR T cells. We found that HER2-specific CAR T cells had higher KCa3.1 conductance compared to the non-transduced (NT, control) cells, which was more prominent in the CD8+ population (CD4+ cell also showed elevation). Conversely, the Kv1.3 expression level was the same for all cell types (CD4+, CD8+, CAR, and NT). Single-cell Ca2+ imaging revealed that thapsigargin-induced SOCE via CRAC is suppressed in CD8+ CAR T cells, unlike for CD4+ and CD8+ NT cells. To dissect the functional role of Kv1.3 and KCa3.1, we used specific antagonists (Kv1.3: Vm24; KCa3.1: TRAM-34): the target cell elimination capacity of the CD8+ CAR T cells was improved either by blocking KCa3.1 or Kv1.3. These results imply that ion channels could be a target in CAR T cell immunotherapy elaboration.
Analysis of the Predictability of Postoperative Meningioma Resection Status Based on Clinical Features
Authors: Musigmann Manfred , Akkurt Burak Han , Krähling Hermann , Brokinkel Benjamin , Spille Dorothee Cäcilia , Stummer Walter , Heindel Walter , Mannil Manoj
Published: November 2024

Background: Our aim was to investigate the predictability of postoperative meningioma resection status based on clinical features. Methods: We examined 23 clinical features to assess their effectiveness in distinguishing gross total resections (GTR) from subtotal resections (STR). We analyzed whether GTR/STR cases are better predictable if the classification is based on the Simpson grading or the postoperative operative tumor volume (POTV). Results: Using a study cohort comprising a total of 157 patients, multivariate models for the preoperative prediction of GTR/STR outcome in relation to Simpson grading and POTV were developed and subsequently compared. Including only two clinical features, our models showed a notable discriminatory power in predicting postoperative resection status. Our final model, a straightforward decision tree applicable in daily clinical practice, achieved a mean AUC of 0.885, a mean accuracy of 0.866, a mean sensitivity of 0.889, and a mean specificity of 0.772 based on independent test data. Conclusions: Such models can be a valuable tool both for surgical planning and for early planning of postoperative treatment, e.g., for additional radiotherapy/radiosurgery, potentially required in case of subtotal resections.