bluuebunny/crossref_metadata_2025 huggingface dataset:
Neural Robust Control for a Mobile Agent Leader–Follower System
Authors: Rodriguez-Castellanos David , Blas-Valdez Marco , Solis-Perales Gualberto , Perez-Cisneros Marco Antonio
Published: June 2024

A controller employing a combined new strategy of output feedback linearization and a recurrent high-order neural network (RHONN) adaptive approach for a mobile agent leader–follower system is presented. The controller structure is based on feedback linearization; then, a scheme of lumping uncertainties which are estimated via the RHONN is incorporated; with this estimate, the controller is able to produce a robust control action for mobile agents so they track a prescribed reference trajectory. Moreover, the nonlinear system part is transformed into a linearizable one; then, a specific function lumps all the nonlinearities, uncertain parameters, and unmodeled dynamics of the system; this overall function is estimated via the RHONN. Thus, both parametric uncertainties and unmodeled dynamics between agents can be compensated via the controller, and, subsequently, follower agents track the reference provided by the leader. The obtained controller is such that the estimation scheme is not based on high-gain controllers. Here, it is underlined that the main contribution consists of designing a nonlinear controller and combining it with an RHONN to estimate the nonlinear uncertainties in the leader–follower system. This control action includes robust features provided by the online recurrence and the nonlinear base of the neural network in which not general but specific parametric disturbances and unmodeled discrepancies are identified or compensated. For this control scheme, only nominal values of the system parameters are required, as well as the velocities of the agents. Numeric simulation of the model and designed tracking control are carried out in which the control law is applied to a two-wheeled differential mobile robot model, obtaining satisfactory results for tracking angular velocities of the wheels.
Research on the Design of Zhuang Brocade Patterns Based on Automatic Pattern Generation
Authors: Ni Minna , Huang Qingqing , Ni Ni , Zhao Huiqin , Sun Bo
Published: June 2024

To promote the inheritance of Zhuang brocade culture and the rapid extraction of features and automatic generation of patterns, this paper constructs a feature dataset of Zhuang brocade patterns and proposes an automatic generation technology using relative coordinates and regional content replacement. Firstly, by sorting through a large number of cases, a feature dataset of Zhuang brocade patterns is constructed. For the significant features of Zhuang brocade patterns, intelligent extraction algorithms and processes are used to effectively extract the color matching, patterns, and organizational forms of the patterns into the feature dataset. Secondly, to generate Zhuang brocade patterns quickly, an automatic generation technology based on genotype encoding and regional replacement algorithms is proposed, which encodes these pattern elements into a format that can be interpreted by computer algorithms. Finally, through similarity evaluation, the method’s feasibility for rapid extraction and generation of Zhuang brocade patterns is effectively verified. This method is significant for the inheritance of Zhuang brocade patterns and the development of the intangible cultural heritage industry.
Aflatoxin B1 Detoxification and Antioxidant Effect of Selected Omani Medicinal Plants against Aflatoxin B1-Induced Oxidative Stress Pathogenesis in the Mouse Liver
Authors: Velazhahan Rethinasamy , Al-Sadi Abdullah Mohammed , Waly Mostafa I. , Soundra Pandian Sathish Babu , Al-Sabahi Jamal , Al-Farsi Khalid
Published: June 2024

This study investigated the ability of aqueous leaf extracts of Heliotropium bacciferum (HE), Ocimum dhofarense (OE), and Zataria multiflora (ZE) to detoxify aflatoxin B1 (AFB1) under in vitro and in vivo conditions. The results showed that HE, OE, and ZE degraded 95%, 93%, and 92% of AFB1, respectively, after 72 h incubation at 37 °C. The degradation of AFB1 was validated by liquid chromatography–mass spectrometry analysis. A molecular ion peak at m/z 313 specific to AFB1 (C17H12O6) was observed in the mass spectrum of untreated AFB1 (control). However, the level of AFB1 was decreased to untraceable levels in response to treatment with these plant extracts. HE, OE, and ZE effectively detoxified AFB1 in a concentration-dependent manner, resulting in mortality rates of 65, 70, and 75% of brine shrimp, respectively, in contrast to 90% in the untreated AFB1 (control). The hepatoprotective effect of HE, OE, and ZE against AFB1-induced oxidative stress pathogenesis was investigated using mice as an experimental model. Glutathione depletion, impairment of total antioxidant capacity, and increase in DNA oxidative damage were observed in liver tissues of mice treated with AFB1. However, HE, OE, and ZE extract supplementation suppressed the oxidative damage associated with AFB1 treatment. Our findings indicated that HE, OE, and ZE were highly effective in the detoxification of AFB1. In addition, HE, OE, and ZE act as potent antioxidants and combat the AFB1-associated oxidative stress and liver pathogenesis, suggesting that these plants might be valuable for the development of functional foods aimed at minimizing the toxic effects of AFB1.
Research on Subsurface Damage Measurement of Fused Silica in Ultra-Precision Grinding Based on Laser Damage Performance
Authors: Zhong Yaoyu , Xu Mingjin , Kuang Wenjun , Wan Fubin , Lin Zhifan , Fan Yansong , Hu Qingqing , Xu Fufang
Published: June 2024

In order to achieve accurate prediction of subsurface damage (SSD) in ultra-precision grinding of high-performance ultra-violet laser-irradiated fused silica optics, the paper combines damage precursor multimodal measurement technology with magnetorheological finishing spot method detection. Various methods such as photothermal weak absorption and fluorescence confocal imaging are used for measuring the surface roughness and subsurface damage depth of a series of fused silica samples prepared under different ultra-precision grinding parameters. The correlation between surface roughness and subsurface damage depth in ultra-precision grinding based on laser damage performance is established using curve fitting. The results indicate that there is a metamorphic layer below the subsurface crack layer, which can cause additional photothermal absorption. Subsurface damage is constituted of the subsurface crack layer and metamorphic layer. Under ultra-precision grinding conditions, the maximum depth of subsurface damage is generally 2.00–4.22 times the depth of the subsurface damage cluster. The roughness Ra and the subsurface damage cluster depth correspond to SSD(cluster) = 195 × Ra − 0.13. The maximum depth of subsurface damage can be predicted by measuring the Ra value, by which accurate prediction of defect depth in ultra-precision grinding and guiding the high-performance manufacturing of ultra-violet laser-irradiated fused silica optics can be achieved.
PAM-UNet: Enhanced Retinal Vessel Segmentation Using a Novel Plenary Attention Mechanism
Authors: Wang Yongmao , Wu Sirui , Jia Junhao
Published: June 2024

Retinal vessel segmentation is critical for diagnosing related diseases in the medical field. However, the complex structure and variable size and shape of retinal vessels make segmentation challenging. To enhance feature extraction capabilities in existing algorithms, we propose PAM-UNet, a U-shaped network architecture incorporating a novel Plenary Attention Mechanism (PAM). In the BottleNeck stage of the network, PAM identifies key channels and embeds positional information, allowing spatial features within significant channels to receive more focus. We also propose a new regularization method, DropBlock_Diagonal, which discards diagonal regions of the feature map to prevent overfitting and enhance vessel feature learning. Within the decoder stage of the network, features from each stage are merged to enhance the segmentation accuracy of the final vessel. Experimental validation on two retinal image datasets, DRIVE and CHASE_DB1, shows that PAM-UNet achieves 97.15%, 83.16%, 98.45%, 83.15%, 98.66% and 97.64%, 85.82%, 98.46%, 82.56%, 98.95% on Acc, Se, Sp, F1, AUC, respectively, outperforming UNet and most other retinal vessel segmentation algorithms.
Pathogens in the Food Chain: Escherichia coli Strains in Raw Milk Originating from Ewes Treated for Mastitis with Various Therapeutic Protocols
Authors: Fotou Konstantina , Rozos Georgios , Zaralis Konstantinos , Dadamogia Aikaterini , Stavropoulou Elisavet , Demertzis Panagiotis , Akrida-Demertzi Konstantoula , Tzora Athina , Voidarou Chrysoula (Chrysa)
Published: June 2024

Dairy products from ovine milk are very popular in the Mediterranean countries and are gaining a large portion of the market in EU countries and worldwide. EU legislation permits the dairy processing of raw ovine milk under certain conditions. To study the ecology and prevalence of E. coli in raw ewes’ milk and assess thus the public health risk, samples of milk were taken from 75 different sheep farms in the rural area of Epirus, Greece. The initial sampling was conducted in clinically healthy animals which were noted as controls (group A). From the same farms, samples were taken from animals with clinical mastitis and before treatment (group B). For therapeutic purposes, to some animals, a combination of penicillin and streptomycin was administrated (group C1), or tetracycline (group C2), or enrofloxacin (group C3). Finally, samples of raw milk were taken from the C groups, on the first day after the withdrawal period of the antibiotics used, when the milk is permitted to enter the food chain. In total, 97 isolates of Escherichia coli were recovered from all groups. Analysis revealed an impressive increase in E. coli strains in the milk of group B (39.33%) with respect to group A (5%). Even after treatment, although the prevalence was decreased, it was still found to be higher in the C groups than group A. E. coli O157:H7 strains absent from group A were detected in all other groups in relatively low occurrence rates with respect to other “O” serotypes but non-O157:H7 strains. Virulence factors such as the production of toxins (32.60% for serotoxin 1 and 18.47% for serotoxin 2) and hemolysin (42.39%) as well as biofilm formation capacity (52.17% of the total) and ESDL production (43.47% of the total) were also studied. All strains were also tested for susceptibility against 12 antibiotics by the MIC method and the results showed a high prevalence of resistance and multi-resistance. The presence of various resistant strains to antibiotics and pathogenic “O” serotype strains in the milk when it can enter the food chain again is an alarming conclusion.
Semantic Hierarchical Classification Applied to Anomaly Detection Using System Logs with a BERT Model
Authors: Corbelle Clara , Carneiro Victor , Cacheda Fidel
Published: June 2024

The compaction and structuring of system logs facilitate and expedite anomaly and cyberattack detection processes using machine-learning techniques, while simultaneously reducing alert fatigue caused by false positives. In this work, we implemented an innovative algorithm that employs hierarchical codes based on the semantics of natural language, enabling the generation of a significantly reduced log that preserves the semantics of the original. This method uses codes that reflect the specificity of the topic and its position within a higher hierarchical structure. By applying this catalog to the analysis of logs from the Hadoop Distributed File System (HDFS), we achieved a concise summary with non-repetitive themes, significantly speeding up log analysis and resulting in a substantial reduction in log size while maintaining high semantic similarity. The resulting log has been validated for anomaly detection using the “bert-base-uncased” model and compared with six other methods: PCA, IM, LogCluster, SVM, DeepLog, and LogRobust. The reduced log achieved very similar values in precision, recall, and F1-score metrics, but drastically reduced processing time.
Grout Diffusion Mechanism along the Pile Shaft during the Process of Pile Tip Post-Grouting in Sand
Authors: Wu Yue , Deng Yating , Zhang Xuefu , Liu Lang , Zhao Chunfeng , Zhang Jiaqi
Published: June 2024

Pile tip post-grouting technology has been widely adopted in pile foundations to improve its bearing characteristics. Grouting in the pile tip leads to the grouting cement spreading along the pile body to a certain extent. To better understand the grout diffusion mechanism along the pile body returned, a total of 45 groups of laboratory model tests were carried out on sand, with different grouting pressures, grout volumes, and soil stress histories taken into account. By comparing the characteristics of the grouted bulbs, the grout diffusion mechanism along the pile body returned was revealed. Combined with the test results, a simplified model to describe the grout diffusion pattern and the corresponding grouting mode of grouting cement along the pile body returned during the process of pile tip post-grouting was proposed. This model can comprehensively reflect the grout diffusion characteristics along the pile body, with different grouting conditions and soil stress histories taken into account.
Influence of the Menstrual Cycle on Performance in CrossFit®
Authors: Mora-Serrano Jeimy S. , Chulvi-Medrano Iván , Martínez-Guardado Ismael , Alonso-Aubin Diego A.
Published: June 2024

The purpose of this study was to compare the fast maximal dynamic strength, maximal dynamic strength, and muscular endurance changes between the follicular phase (FP) and luteal phase (LP) in the menstrual cycle (MC). Fourteen healthy resistance-trained CrossFit® athletes and eumenorrheic women without oral contraception participated in this study (age: 29.64 ± 3.95 years; height: 1.62 ± 0.04 m and mass: 60.43 ± 6.56 kg). A double cross-sectional and descriptive study was developed to evaluate strength, power, and muscular endurance performance in the FP (days 5 to 7) and LP (days 20 to 23). In each assessment, the subjects performed three countermovement jumps (CMJs) for assessing fast maximal dynamic strength using My Jump 2, one-repetition maximum (1-RM) on deep squat for maximal dynamic strength, and the Karen® protocol for muscular endurance. The data were analyzed using a paired sample t-test to determine whether there were any significant differences between FP and LP for all the assessments and the significance was set at p ≤ 0.05. Results revealed no significant differences between the FP and LP in performance: (a) fast maximal dynamic strength (FP: 0.27 ± 0.04 m; LP: 0.29 ± 0.04 m; t = 0.98; p = 0.34; ES = 0.26); (b) maximal dynamic strength (FP: 88.14 ± 12.60 kg; LP: 87.07 ± 12.51 kg; t = 0.90; p = 0.38; ES = 0.24); and (c) muscular endurance (FP: 459.43 ± 92.71 s; LP: 456.93 ± 110.68 s; t = 0.27; p = 0.78; ES = 0.07). CrossFit® performance is not altered during the MC in CrossFit® trained athletes. However, monitoring the MC and its symptoms could be used to adapt the training prescription to the needs and preferences of the athletes.
Smartphone Sensors in Motion: Advancing Traffic Safety with Mobile Technology
Authors: Ondruš Ján , Jančár Arnold , Gogola Marián , Varga Peter , Šarić Željko , Caban Jacek
Published: June 2024

This research investigates the feasibility of using smartphones as reliable instruments to measure vehicle deceleration under different conditions and compares their accuracy and reliability with traditional decelerometers. The research was conducted using a passenger vehicle (Audi A6 Avant) on different road surfaces—dry, wet, and gravel—at several speed intervals (30, 50, 70, and 90 km/h). The vehicle was equipped with an XL Meter decelerometer and three different smartphones in different price ranges. Each device recorded deceleration data, which was then analyzed to evaluate accuracy and reliability. The findings show that while the smartphones show promising results on dry and gravel surfaces, their accuracy decreases at lower speeds and on wet surfaces due to the limitations of the sensors in detecting subtle deceleration values. The research also highlights that mid-range smartphones can perform comparably to higher-end models, suggesting that excessive investment in more expensive technology may not be necessary for scientific purposes. However, some differences in measurements are attributed to variations in device mounting and orientation sensitivity. In conclusion, this research supports the potential of integrating smartphone technology in vehicle testing for road safety, although it highlights critical limitations that need to be addressed for standardized use.
Compilation Method of Flight Service Environment Spectrum Based on Altitude Features and Fuzzy Clustering
Authors: Chen Moli , Wei Xunkai , Wang Hao , Luo Guihuo
Published: June 2024

The flight service environment spectrum is essential to the evaluation of the life of components in aeroengines; however, real altitude, as an important flight parameter, introduces considerable challenges when compiling the service environment spectrum because of its non-stationary and non-ergodic characteristics. In this article, by solving trend terms from original data and removing redundancy from peak–valley values, an altitude feature extraction method is developed for the Frequency of Climb–Descent Flight (FCDF). Then, taking the 2D vector, composed of the maximum flight altitude and FCDF, as the input of fuzzy clustering, the service environment spectrum is compiled. Some examples are given to illustrate the presented methods. The results show that the FCDF does not increase with the maximum altitude; during high-altitude flight, the FCDF is the largest, while during mid- to low-altitude flight, the time proportion is the largest. On the other hand, mid-altitude or low-altitude flight not only has a small training frequency for climb–descent actions but also a low time proportion. The research results will provide a reference for the compilation of a service environment spectrum that considers maneuvering flight actions.
Prediction of Brake Pad Wear of Trucks Transporting Oversize Loads Based on the Number of Drivers’ Braking and the Load Level of the Trucks—Multiple Regression Models
Authors: Basista Grzegorz , Hajos Michał , Francik Sławomir , Pedryc Norbert
Published: June 2024

Brake pad wear forecasting, due to its complex nature, is very difficult to describe using engineering formulas. Therefore, the aim of this publication is to create high-quality brake pad wear forecasts based on three stochastic quantitative models based on multiple regression models (linear model, inverted linear model, and power model). The matrix of explanatory variables was extracted from the controllers of 29 vehicles: A—the driver’s style of using the brake pedal specified on a 4-point scale and B—the number of vehicle load ranges specified on a 5-point scale. Methodology: A matrix of explanatory variables was obtained over a 2-year period from trucks carrying oversize loads via OBD2 socket. The trucks operated under similar operating conditions. The created models were verified in terms of their fit to the source data and by analyzing the residuals of the models. It should be emphasized that only the linear model met all the required criteria. The inverted linear and power-law models were rejected. Results: The verified linear model is characterized by very small MAPE errors. The model was validated on 4 trucks and the brake pad wear prediction errors ranged from −0.39% to 7.03%.
Electroencephalography Response during an Incremental Test According to the V̇O2max Plateau Incidence
Authors: Billat Véronique , Berthomier Christian , Clémençon Michel , Brandewinder Marie , Essid Slim , Damon Cécilia , Rigaud François , Bénichoux Alexis , Maby Emmanuel , Fornoni Lesly , Bouchet Patrick , Van Beers Pascal , Massot Bertrand , Revol Patrice , Poinsard Luc , Creveaux Thomas , Collet Christian , Mattout Jérémie , Pialoux Vincent
Published: June 2024

V̇O2max is recognized as a key measure in exercise physiology and sports medicine. However, only 20–50% of maximal incremental exercise tests (IET) result in a plateau of V̇O2 (V̇O2pl). To our knowledge, no study has yet examined the possible difference in brain activity during an IET, in V̇O2pl and non-plateau athletes with the same V̇O2max and age. This study aimed to shed light on the central governor hypothesis, namely that the inability to reach a V̇O2pl may be dictated by the brain rather than by a peripheral physical limit. This hypothesis can now be explored using electroencephalography (EEG) during IET, measuring concomitant power in specific frequency bands. Forty-two athletes were divided into two groups: those who practiced endurance sports and those who did not, and were asked to perform an IET. EEG signals and gas exchange were recorded. A V̇O2pl was observed in twenty-two subjects (52%). EEG power increased in all subjects during IET, except in the alpha band, which showed variability, but not significantly (64% increase, 34% decrease, p = 0.07). No differences were found between endurance athletes and non-endurance athletes, except for V̇O2max (60.10 ± 6.16 vs. 51.77 ± 6.41, p < 0.001). However, the baseline-corrected ratio of EEG power to V̇O2 was found to decrease in all subjects during IET, in the alpha, beta and theta bands. In conclusion, the presence or absence of a V̇O2pl is not related to the type of EEG response during an IET. Nevertheless, the decline in brain and V̇O2 powers/ratios in all frequency bands suggests that aerobic power may be constrained by brain mobilization.
A Novel Debonding Damage Identification Approach of Hidden Frame-Supported Glass Curtain Walls Based on UAV-LDV System
Authors: Zheng Haoyang , Guo Tong , Zhi Guoliang , Hu Zhiwei
Published: June 2024

This study introduces a novel Unmanned Aerial Vehicle-mounted (UAV-mounted) Laser Doppler Vibrometer (LDV) system for detecting debonding damage in Hidden Frame-Supported Glass Curtain Walls (HFSGCW). The established system enables UAVs to transport the LDV to high altitudes for operation. The vibration signals acquired by the UAV-LDV system are decomposed into different energy bands by wavelet packet analysis, and then the occurrence and location of the damage are identified by the Sum of Squared Differences (SSD) of the wavelet packet bands’ energy. This paper investigates the potential factors affecting the performance of the Unmanned Aerial Vehicle-Laser Doppler Vibrometer (UAV-LDV) system, including the arrangement of measuring points, measuring distance, noise level, and wind speed through the first-order natural frequency, the normalized frequency response functions, and the SSD indicator. Experimental and simulation results confirm the effectiveness of the UAV-LDV system, highlighting its advantages over traditional methods by offering remote, non-contact, and efficient debonding detection. This method not only indicates the presence of the damage, as traditional indicators do, but also pinpoints the exact location of it, ensuring safety and cost-effectiveness in high-rise inspections. The proposed method and indicator offer advantages in terms of convenience, visualization, and efficiency. The study discusses the impact of measurement point arrangement, measuring distance, noise levels, and wind speed on the system’s performance. The findings demonstrate that while the UAV-LDV system introduces new capabilities in rapid and reliable structural damage assessment, operational challenges such as wind and noise levels significantly influence its accuracy.
Multiscale Dynamic Diffusion Model for Ions in Micro- and Nano-Porous Structures of Fly Ash: Mineralization Experimental Research
Authors: Guo Weijie , Xia Binwei , Peng Jiansong
Published: June 2024

The leaching concentration of alkaline ions plays a crucial role in the efficiency of the CO2 mineralization reaction in fly ash. The multi-scale structural characteristics of micro–nano pores in fly ash are the primary factors that control the leaching and diffusion rate of alkaline ions. However, the existing theoretical models do not account for the multi-scale pore structure, leading to challenges in accurately describing the ion diffusion in fly ash and predicting the reaction rate and efficiency of CO2 mineralization. To address this issue, a multi-scale dynamic diffusion model of ions was developed based on the micro–nano pore structure of fly ash. This model established the relationship between the ionic leaching rate and pore structure, as well as macroscopic changes over time, which were validated through experiments. Mineralization experiments with varying soaking times and uniaxial compression experiments on mineralized specimens were conducted to investigate the relationships among soaking time, ion leaching concentration, mineralization degree, and mechanical strength. The results elucidated the impact of alkaline ion concentration on the mineralization degree and mechanical strength of fly ash materials, offering theoretical insights to enhance mineralization and material properties.
Fault Diagnosis in Solar Array I-V Curves Using Characteristic Simulation and Multi-Input Models
Authors: Lin Wei-Ti , Chang Chia-Ming , Huang Yen-Chih , Wu Chi-Chen , Kuo Cheng-Chien
Published: June 2024

Currently, fault identification in most photovoltaic systems primarily relies on experienced engineers conducting on-site tests or interpreting data. However, due to limited human resources, it is challenging to meet the vast demands of the solar photovoltaic market. Therefore, we propose to identify fault types through the current–voltage curves of solar arrays, obtaining curves for various conditions (normal, aging faults, shading faults, degradation faults due to potential differences, short-circuit faults, hot-spot faults, and crack faults) as training data for the model. We employ a multi-input model architecture that combines convolutional neural networks with deep neural networks, allowing both the imagery and feature values of the current–voltage curves to be used as input data for fault identification. This study demonstrates that by inputting the current–voltage curves, irradiance, and module specifications of solar string arrays into the trained model, faults can be identified quickly using actual field data.
How Many Lives for a Mesopotamian Statue?
Authors: Achouche Imane
Published: June 2024

Among the indicators of the value and power ascribed to statues in Mesopotamia, reuse is a particularly significant one. By studying some of the best-documented examples of the usurpation and reassignment of a new function to sculptures in the round from the 3rd and 2nd millennia BC, our study reveals the variety of motives and methods employed. We hereafter explore the ways in which the status of such artefacts is maintained, reactivated, or adapted in order to secure their agency.
A GPU-Implemented Lattice Boltzmann Model for Large Eddy Simulation of Turbulent Flows in and around Forest Shelterbelts
Authors: Wang Yansen , Zeng Xiping , Decker Jonathan , Dawson Leelinda
Published: June 2024

Using porous wind barriers for the microclimate modification of agricultural lands, urban areas, and surrounding roads is a ubiquitous practice. This study establishes a new method for numerically modeling the turbulent flow in and around forest shelterbelts using an advanced multiple-relaxation-time lattice Boltzmann model (MRTLBM). A detailed description is presented for a large eddy simulation (LES) of turbulent winds by implementing barrier element drag force in the MRTLBM framework. The model results for a forest shelterbelt are compared with a field observational dataset. The study indicated that our implementation of drag force in MRTLBM is an accurate method for modeling turbulent flows in and around forest patches. Sensitivity analyses of turbulent flow related to the shelterbelt structure parameters and wind directions are also carried out. The analysis indicated that the optimal wind shelter effect in reducing the mean wind speed and turbulent kinetic energy is maximized using a narrow, medium porosity shelterbelt, with the wind direction perpendicular to the shelterbelt. These conclusions are in agreement with other observational and modeling studies. Finally, the computational time of a central processing unit (CPU) and graphics processing unit (GPU) was compared for a large domain with 25 million grids to demonstrate the MRTLBM advantage of LES in regards to computational speed with a mixed forest and building environment. The GPU is approximately 300 times faster than a CPU, and real-time simulation for this large domain is achieved using the Nvidia V100 GPU.
Assessment of Atmospheric Particles Flux Variation on the Different Underlying Surfaces (Grasslands and Forest) in the Lake Baikal Region
Authors: Balzhanov Tumen S. , Zayakhanov Alexander S. , Zhamsueva Galina S. , Tcydypov Vadim V. , Dementeva Ayuna L.
Published: June 2024

In this study, the new data of experimental studies of the atmospheric particulate matter (PM) on the south-eastern coast of Lake Baikal (station Boyarsky) were analyzed in summer 2021. High-altitude measuring sites were arranged in the forest massif (mast, 16 m) and above the meadow vegetation (mast, 30 m). By the Giardina M. model and based on the measurements data the calculations of the deposition flux density of aerosol particles on forest and meadow vegetation were made. Our preliminary results of prediction obtained by Giardina M. model good agrees with measured dry deposition velocities across particle sizes. In the forest, the mass concentration of aerosol particles differs slightly from the mass concentrations in the grasslands and is equal on average 7.9 × 10−3 mg m−3 for the size particles below 200 nm (PM0.2) and 6.7 × 10−4 mg m−3 for particles in the size range from 0.2 to 10 μm (PM0.2–10). However, we found that mass flux density of aerosol particle is almost 4.8 times higher under forest canopy than in meadow vegetation. In addition, the leaf area index (LAI), which characterize the effective area of particle deposition, is also significantly higher in the tree canopy (5.6) compared to the grassland vegetation (2.4).
Inspection of a Time-Delayed Excited Damping Duffing Oscillator
Authors: Alluhydan Khalid , Moatimid Galal M. , Amer T. S. , Galal A. A.
Published: June 2024

This paper examines a time delay in position and velocity to minimize the nonlinear vibration of an excited Duffing oscillator (DO). This model is highly beneficial for capturing the nonlinear characteristics of many different applications in engineering. To achieve an estimated uniform solution to the problem under consideration, a modified homotopy perturbation method (HPM) is utilized. This adaptation produces a more accurate precise approximation with a numerical solution (NS). This is obtained by employing Mathematica software 12 (MS) in comparison with the analytical solution (AS). The comparison signifies a good match between the two methodologies. The comparison is made with the aid of the NS. Consequently, the work allows for a qualitative assessment of the results of a representative analytical approximation approach. A promising stability analysis for the unforced system is performed. The time history of the accomplished results is illustrated in light of a diverse range of physical frequency and time-delay aspects. The outcomes are theoretically discussed and numerically explained with a set of graphs. The nonlinear structured prototype is examined via the multiple-scale procedure. It investigates how various controlling limits affect the organization of vibration performances. As a key assumption, according to cubic nonlinearity, two significant examples of resonance, sub-harmonic and super-harmonic, are explored. The obtained modulation equations, in these situations, are quantitatively investigated with regard to the influence of the applied backgrounds.
Some New Estimations of Left and Right Interval Fractional Pachpatte’s Type Integral Inequalities via Rectangle Plane
Authors: Alshehry Azzh Saad , Ciurdariu Loredana , Saber Yaser , Soliman Amal F.
Published: June 2024

Inequalities involving fractional operators have been an active area of research, which is crucial in establishing bounds, estimates, and stability conditions for solutions to fractional integrals. In this paper, we initially presented a new class that is known as coordinated left and right ℏ-pre-invex interval-valued mappings (C·L·R-ℏ-pre-invex Ι·V-M), as well classical convex and nonconvex are also obtained. This newly defined class enabled us to derive novel inequalities, such as Hermite–Hadamard and Pachpatte’s type inequalities. Furthermore, the obtained results allowed us to recapture several special cases of known results for different parameter choices, which can be applications of the main results. Finally, we discussed the validity of the main outcomes.
Generalization of the Distance Fibonacci Sequences
Authors: Yilmaz Nur Şeyma , Włoch Andrej , Özkan Engin
Published: June 2024

In this study, we introduced a generalization of distance Fibonacci sequences and investigate some of its basic properties. We then proposed a generalization of distance Fibonacci sequences for negative integers and investigated some basic properties. Additionally, we explored the construction of matrix generators for these sequences and offered a graphical representation to clarify their structure. Furthermore, we demonstrated how these generalizations can be applied to obtain the Padovan and Narayana sequences for specific parameter values.
Gazing Strategies among Sentinels of a Cooperative Breeder Are Repeatable but Unrelated to Survival
Authors: Beauchamp Guy , Barve Sahas
Published: June 2024

Vigilance is a common behavioural adaptation to increase the chances of detecting predators before it is too late to escape. Behavioural traits are often repeatable among individuals over the long term, suggesting differences in personality. Earlier studies have documented individual consistency in the time allocated to vigilance. However, little is known about individual consistency in the ways vigilance is achieved from one moment to another and whether different patterns of vigilance among individuals are associated with survival. We aimed to determine whether sentinels of a cooperative breeder showed individual consistency in their vigilance and if individual variation was related to annual survival. During sentinel bouts from vantage points, Florida scrub-jays (Aphelocoma coerulescens) turn their heads from side to side to monitor their surroundings. Over three field seasons, we found that the head-turning frequency was repeatable in breeders but not in juveniles or non-breeding helpers. The moderate repeatability in breeders was not related to survival. Our results suggest that the head-turning frequency in sentinels of the Florida scrub-jay is repeatable in breeders but not in less experienced juveniles or helpers and, therefore, likely becomes more repeatable as individuals age. The assumption that individual variation in vigilance is related to survival was unsupported in our study and requires further study.
Rotation Culture of Macroalgae Based on Photosynthetic Physiological Characteristics of Algae
Authors: Cheng Xiaopeng , Zhao Xu , Lin Jun , Zhang Shouyu , Wang Zhenhua , Huang Hong , Wang Kai , Chen Jianqu
Published: June 2024

Seaweed farming has made outstanding contributions to food supply and the restoration of the ecological environment despite the limitations in production and ecological effects due to the current intensive farming of single algae species. These limitations can be overcome by selecting suitable algal species based on their physiological characteristics and by constructing a large-scale seaweed rotation model. This study carried out a trial culture in aquaculture sea areas, and performed in situ monitoring of the environmental conditions and physiological characteristics of Saccharina japonica, Hizikia fusiformis, and Gracilariopsis lemaneiformis. Additionally, a comparative analysis of the three macroalgae at different times was conducted to determine their response characteristics to environmental factors. The results showed that: (1) The three macroalgae had varying light tolerance. The effective quantum yield of Hizikia fusiformis and Gracilariopsis lemaneiformis remained unchanged during the changes in light environment, while that of Saccharina japonica first decreased and then recovered. (2) The relative electron transport rates of the three macroalgae were significantly different under different temperature conditions. Hizikia fusiformis and Saccharina japonica exhibited the highest relative electron transport rates (70.45 and 106.75, respectively) in May (20.3 °C). Notably, Gracilariopsis lemaneiformis demonstrated good growth and exhibited the highest relative electron transport rate (93.07) in September (27.5 °C). These findings collectively support the feasibility of establishing a macroalgae rotation model. Based on the combined environmental conditions of the seas in Shandong, Zhejiang, and Fujian, a macroalgae rotation model was proposed. The application of this model in the construction of artificial seaweed farms in marine ranches can provide a stable output of large-scale seaweed production and ecological benefits.
Differential Contributions of Fibroblast Subpopulations to Intercellular Communication in Eosinophilic Esophagitis
Authors: Li Tao , Salomon Matthew , Shao Ling , Khalatbari Atousa , Castle Joshua D. , Shaker Anisa
Published: June 2024

Fibroblast heterogeneity remains undefined in eosinophilic esophagitis (EoE), an allergic inflammatory disorder complicated by fibrosis. We utilized publicly available single-cell RNA sequencing data (GSE201153) of EoE esophageal biopsies to identify fibroblast sub-populations, related transcriptomes, disease status-specific pathways and cell–cell interactions. IL13-treated fibroblast cultures were used to model active disease. At least 2 fibroblast populations were identified, F_A and F_B. Several genes including ACTA2 were more enriched in F_A. F_B percentage was greater than F_A and epithelial–mesenchymal transition upregulated in F_B vs. F_A in active and remission EoE. Epithelial–mesenchymal transition was also upregulated in F_B in active vs. remission EoE and TNF-α signaling via NFKB was downregulated in F_A. IL-13 treatment upregulated ECM-related genes more profoundly in ACTA2− fibroblasts than ACTA2+ myofibroblasts. After proliferating epithelial cells, F_B and F_A contributed most to cell–cell communication networks. ECM–Receptor interaction strength was stronger than secreted or cell–cell contact signaling in active vs. remission EoE and significant ligand–receptor pairs were driven mostly by F_B. This unbiased analysis identifies at least 2 fibroblast sub-populations in EoE in vivo, distinguished in part by ACTA2. Fibroblasts play a critical role in cell–cell interactions in EoE, most profoundly via ECM–receptor signaling via the F_B sub-group.
Macrophage Phenotype Induced by Circulating Small Extracellular Vesicles from Women with Endometriosis
Authors: Martínez-Zamora María Angeles , Armengol-Badia Olga , Quintas-Marquès Lara , Carmona Francisco , Closa Daniel
Published: June 2024

Evidence suggests that immune system dysfunction and macrophages are involved in the disease establishment and progression of endometriosis. Among the factors involved in this alteration in macrophage activity, Small Extracellular Vesicles (sEVs) have been described to play a role favoring the switch to a specific phenotype with controversial results. This study aims to investigate the potential effect of circulating sEVs in the plasma of well-characterized patients with endometriosis on the polarization of macrophages. sEVs were isolated from the plasma of patients diagnosed with endometriosis confirmed by histopathological analysis. Two groups of patients were recruited: the endometriosis group consisted of patients diagnosed with endometriosis by imaging testing (gynecological ultrasonography and/or magnetic resonance imaging), confirmed by histopathologic study (n = 12), and the control group included patients who underwent laparoscopy for tubal sterilization without presurgical suspicion of endometriosis and without endometriosis or signs of any inflammatory pelvic condition during surgery (n = 12). Human THP1 monocytic cells were differentiated into macrophages, and the effect of sEVs on cell uptake and macrophage polarization was evaluated by fluorescent labeling and measurement of the IL1B, TNF, ARG1, and MRC1 expression, respectively. Although no changes in cell uptake were detected, sEVs from endometriosis induced a polarization of macrophages toward an M2 phenotype, characterized by lower IL1B and TNF expression and a tendency to increase MRC1 and ARG1 levels. When macrophages were stimulated with lipopolysaccharides, less activation was also detected after treatment with endometriosis sEVs. Finally, endometriosis sEVs also induced the expression of the nuclear receptor peroxisome proliferator-activated receptor-gamma (PPARG); however, treatment with rosiglitazone, a PPARG agonist, had no effect on the change in macrophage phenotype. We conclude that circulating sEVs in women with endometriosis have a certain capacity to shift the activation state of macrophages toward an M2 phenotype, but this does not modify the uptake level or the response to PPARG ligands.
The Double-Edged Effects of MLN4924: Rethinking Anti-Cancer Drugs Targeting the Neddylation Pathway
Authors: Tang Haoming , Pang Xin , Li Shun , Tang Liling
Published: June 2024

(1) Background: The neddylation pathway assumes a pivotal role in the initiation and progression of cancer. MLN4924, a potent small-molecule inhibitor of the NEDD8-activating enzyme (NAE), effectively intervenes in the early stages of the neddylation pathway. By instigating diverse cellular responses, such as senescence and apoptosis in cancer cells, MLN4924 also exerts regulatory effects on non-malignant cells within the tumor microenvironment (TME) and tumor virus-infected cells, thereby impeding the onset of tumors. Consequently, MLN4924 has been widely acknowledged as a potent anti-cancer drug. (2) Recent findings: Nevertheless, recent findings have illuminated additional facets of the neddylation pathway, revealing its active involvement in various biological processes detrimental to the survival of cancer cells. This newfound understanding underscores the dual role of MLN4924 in tumor therapy, characterized by both anti-cancer and pro-cancer effects. This dichotomy is herein referred to as the “double-edged effects” of MLN4924. This paper delves into the intricate relationship between the neddylation pathway and cancer, offering a mechanistic exploration and analysis of the causes underlying the double-edged effects of MLN4924—specifically, the accumulation of pro-cancer neddylation substrates. (3) Perspectives: Here, the objective is to furnish theoretical support and novel insights that can guide the development of next-generation anti-cancer drugs targeting the neddylation pathway.
Continuous Optical Zoom Compound Eye Imaging Using Alvarez Lenses Actuated by Dielectric Elastomers
Authors: Chen Chuanxun , Hao Qun , Liu Lin , Cao Jie , Qiao Zhibo , Cheng Yang
Published: June 2024

The compound eye is a natural multi-aperture optical imaging system. In this paper, a continuous optical zoom compound eye imaging system based on Alvarez lenses is proposed. The main optical imaging part of the proposed system consists of a curved Alvarez lens array (CALA) and two Alvarez lenses. The movement of the CALA and two Alvarez lenses perpendicular to the optical axis is realized by the actuation of the dielectric elastomers (DEs). By adjusting the focal length of the CALA and the two Alvarez lenses, the proposed system can realize continuous zoom imaging without any mechanical movement vertically to the optical axis. The experimental results show that the paraxial magnification of the target can range from ∼0.30× to ∼0.9×. The overall dimensions of the optical imaging part are 54 mm × 36 mm ×60 mm (L × W × H). The response time is 180 ms. The imaging resolution can reach up to 50 lp/mm during the optical zoom process. The proposed continuous optical zoom compound eye imaging system has potential applications in various fields, including large field of view imaging, medical diagnostics, machine vision, and distance detection.
Computer Vision Techniques Demonstrate Robust Orientation Measurement of the Milky Way Despite Image Motion
Authors: Tao Yiting , Perera Asanka , Teague Samuel , McIntyre Timothy , Warrant Eric , Chahl Javaan
Published: June 2024

Many species rely on celestial cues as a reliable guide for maintaining heading while navigating. In this paper, we propose a method that extracts the Milky Way (MW) shape as an orientation cue in low-light scenarios. We also tested the method on both real and synthetic images and demonstrate that the performance of the method appears to be accurate and reliable to motion blur that might be caused by rotational vibration and stabilisation artefacts. The technique presented achieves an angular accuracy between a minimum of 0.00° and a maximum 0.08° for real night sky images, and between a minimum of 0.22° and a maximum 1.61° for synthetic images. The imaging of the MW is largely unaffected by blur. We speculate that the use of the MW as an orientation cue has evolved because, unlike individual stars, it is resilient to motion blur caused by locomotion.
Intracerebral Hemorrhage Prognosis Classification via Joint-Attention Cross-Modal Network
Authors: Xu Manli , Fu Xianjun , Jin Hui , Yu Xinlei , Xu Gang , Ma Zishuo , Pan Cheng , Liu Bo
Published: June 2024

Intracerebral hemorrhage (ICH) is a critical condition characterized by a high prevalence, substantial mortality rates, and unpredictable clinical outcomes, which results in a serious threat to human health. Improving the timeliness and accuracy of prognosis assessment is crucial to minimizing mortality and long-term disability associated with ICH. Due to the complexity of ICH, the diagnosis of ICH in clinical practice heavily relies on the professional expertise and clinical experience of physicians. Traditional prognostic methods largely depend on the specialized knowledge and subjective judgment of healthcare professionals. Meanwhile, existing artificial intelligence (AI) methodologies, which predominantly utilize features derived from computed tomography (CT) scans, fall short of capturing the multifaceted nature of ICH. Although existing methods are capable of integrating clinical information and CT images for prognosis, the effectiveness of this fusion process still requires improvement. To surmount these limitations, the present study introduces a novel AI framework, termed the ICH Network (ICH-Net), which employs a joint-attention cross-modal network to synergize clinical textual data with CT imaging features. The architecture of ICH-Net consists of three integral components: the Feature Extraction Module, which processes and abstracts salient characteristics from the clinical and imaging data, the Feature Fusion Module, which amalgamates the diverse data streams, and the Classification Module, which interprets the fused features to deliver prognostic predictions. Our evaluation, conducted through a rigorous five-fold cross-validation process, demonstrates that ICH-Net achieves a commendable accuracy of up to 87.77%, outperforming other state-of-the-art methods detailed within our research. This evidence underscores the potential of ICH-Net as a formidable tool in prognosticating ICH, promising a significant advancement in clinical decision-making and patient care.