bluuebunny/crossref_metadata_2025 huggingface dataset:
Efficient Secure Mechanisms for In-Vehicle Ethernet in Autonomous Vehicles
Authors: Wu Yujing , Xiong Liping , Wang Caiyuan , Xu Yinan
Published: September 2024

The integration of external devices and network connectivity into autonomous vehicles has raised significant concerns about in-vehicle security vulnerabilities. Existing security mechanisms for in-vehicle bus systems, which mainly rely on appending authentication codes and data encryption, have been extensively studied in the context of CAN and CAN-FD buses. However, these approaches are not directly applicable to Ethernet buses due to the much higher data transmission rates of Ethernet buses compared to other buses. The real-time encryption and decryption required by Ethernet buses cannot be achieved with conventional methods, necessitating an acceleration in the speed of cryptographic operations to match the demands of Ethernet communication. In response to these challenges, our paper introduces a range of cryptographic solutions specifically designed for in-vehicle Ethernet networks. We employ an AES-ECC hybrid algorithm for critical vehicle control signals, combining the efficiency of AES with the security of ECC. For multimedia signals, we propose an improved AES-128 (IAES-128) and an improved MD5 (IMD), which improve encryption time by 15.77%. Our proposed security mechanisms have been rigorously tested through attack simulations on the CANoe (version 10) platform. These tests cover both in-vehicle control signals, such as braking and throttle control, and non-critical systems like multimedia entertainment. The experimental results convincingly demonstrate that our optimized algorithms and security mechanisms ensure the secure and reliable operation of real-time communication in autonomous vehicles.
A Three-Dimensional Fully Polarized Millimeter-Wave Hybrid Propagation Channel Model for Urban Microcellular Environments
Authors: Hou Chunzhi , Li Qingliang , Zhang Jinpeng , Wu Zhensen , Zhang Yushi , Guo Lixin , Zhu Xiuqin , Du Pengbo
Published: September 2024

Millimeter-wave channel modeling is the basis of fifth-generation (5G) communication network design and applications. In urban microcellular environments, the roughness of wall surfaces can be comparable to the wavelengths of millimeter waves, resulting in walls that cannot be considered as smooth surfaces. Therefore, channel modeling methods based on only traditional three-dimensional ray tracing (RT) or the three-dimensional parabolic equation (PE) result in the limited computational accuracy of millimeter-wave channel models for urban environments. Based on the scattering theory of a rough surface and the typical scattering characteristics of a millimeter wave, the end field of the three-dimensional vector PE is regarded as the initial field of three-dimensional RT. Moreover, the number of scattered rays and scattering angles are introduced. Finally, a three-dimensional fully polarized millimeter-wave hybrid propagation channel model (3DFPHPCM) is proposed. The proposed model improves the computational accuracy of a single deterministic model. Millimeter-wave channel measurements in non-line-of-sight (NLOS) environments were carried out to verify and optimize the proposed 3DFPHPCM. The results show that the root mean square error (RMSE) and mean absolute error (MAE) of the proposed 3DFPHPCM are both minimized when compared to three-dimensional RT or the three-dimensional PE, which indicates that the proposed 3DFPHPCM has higher computational accuracy. Moreover, its runtime is the shortest among the methods. The results presented herein provide technical support for the layout of base stations.
Efficient Elliptic Curve Diffie–Hellman Key Exchange for Resource-Constrained IoT Devices
Authors: Tanksale Vinayak
Published: September 2024

In the era of ubiquitous connectivity facilitated by the Internet of Things (IoT), ensuring robust security mechanisms for communication channels among resource-constrained devices has become imperative. Elliptic curve Diffie–Hellman (ECDH) key exchange offers strong security assurances and computational efficiency. This paper investigates the challenges and opportunities of deploying ECDH key exchange protocols on resource-constrained IoT devices. We review the fundamentals of ECDH and explore optimization techniques tailored to the limitations of embedded systems, including memory constraints, processing power, and energy efficiency. We optimize the implementation of five elliptic curves and compare them using experimental results. Our experiments focus on electronic control units and sensors in vehicular networks. The findings provide valuable insights for IoT developers, researchers, and industry stakeholders striving to enhance the security posture of embedded IoT systems while maintaining efficiency.
Artificial Intelligence Tool Adoption in Higher Education: A Structural Equation Modeling Approach to Understanding Impact Factors among Economics Students
Authors: Sova Robert , Tudor Cristiana , Tartavulea Cristina Venera , Dieaconescu Ramona Iulia
Published: September 2024

The integration of Artificial Intelligence (AI) in higher education has the potential to significantly enhance the educational process and student outcomes. However, there is a limited understanding of the factors influencing AI adoption among university students, particularly in economic programs. This study examines the relationship between students’ perceptions of the efficacy and usefulness of AI tools, their access to these tools, and their concerns regarding AI usage. A comprehensive survey of Romanian university students, focusing on economics students, was undertaken. This study identifies critical latent factors and investigates their interrelationships by employing advanced analytical techniques, such as Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA), and Structural Equation Modeling (SEM), with robust standard errors. The results suggest that formal training and integration, concerns regarding AI, perceived utility, and positive attitudes towards AI are positively influenced by general awareness and familiarity with AI tools. The frequency of AI tool usage is substantially increased by perceived usefulness, positive attitudes, and formal training and integration. Conversely, positive attitudes and perceived utility are adversely affected by AI-related concerns. Indirect effects suggest that formal training and positive attitudes indirectly increase the usage frequency by increasing general awareness. This research is relevant to computer science, as it helps to build strategies to integrate AI technologies into educational processes. Increasing students’ awareness and access to AI tools and addressing their concerns can facilitate the widespread adoption and effective integration of AI technologies, improving academic experiences and outcomes.
Semantic-Guided Iterative Detail Fusion Network for Single-Image Deraining
Authors: Wang Zijian , Xu Lulu , Rong Wen , Yao Xinpeng , Chen Ting , Zhao Peng , Chen Yuxiu
Published: September 2024

Existing approaches for image deraining often rely on synthetic or unpaired real-world rainy datasets, leading to sub-optimal generalization ability when processing the complex and diverse real-world rain degradation. To address these challenges, we propose a novel iterative semantic-guided detail fusion model with implicit neural representations (INR-ISDF). This approach addresses the challenges of complex solution domain variations, reducing the usual negative impacts found in these situations. Firstly, the input rainy images are processed through implicit neural representations (INRs) to obtain normalized images. Residual calculations are then used to assess the illumination inconsistency caused by rain degradation, thereby enabling an accurate identification of the degradation locations. Subsequently, the location information is incorporated into the detail branch of the dual-branch architecture, while the normalized images obtained from the INR are used to enhance semantic processing. Finally, we use semantic clues to iteratively guide the progressive fusion of details to achieve improved image processing results. To tackle the partial correspondence between real rain images and the given ground truth, we propose a two-stage training strategy that utilizes adjustments in the semantic loss function coefficients and phased freezing of the detail branch to prevent potential overfitting issues. Extensive experiments verify the effectiveness of our proposed method in eliminating the degradation in real-world rainy images.
Spectral Detection of a Weak Frequency Band Signal Based on the Pre-Whitening Scale Transformation of Stochastic Resonance in a Symmetric Bistable System in a Parallel Configuration
Authors: Qin Zhijun , Xie Tengfei , Xie Chen , He Di
Published: September 2024

The spectral detection of weak frequency band signals poses a serious problem in many applications, especially when the target is within a certain frequency band under low signal-to-noise ratio (SNR) conditions. A kind of novel technique based on the pre-whitening scale transformation of stochastic resonance (SR) in a symmetric bistable system in a parallel configuration is proposed to solve the problem. Firstly, pre-whitening can ensure the Gaussian distribution of the receiving signal fits the requirements for SR processing. Secondly, scale transformation can help to effectively utilize the properties of a weak signal, especially under a low-frequency band. Thirdly, the SR in a symmetric bistable system in a parallel configuration can try to smoothly reduce the variances in the clutter and additive noise. Fourthly, by subtracting the steady state response of the SR in the selected symmetric bistable system from the parallel output, the spectral detection of a weak signal can be realized successfully. Experiment results based on actual sea clutter radar data guarantee the effectiveness and applicability of the proposed symmetric bistable PSR processing approach.
Detection Method for Inter-Turn Short Circuit Faults in Dry-Type Transformers Based on an Improved YOLOv8 Infrared Image Slicing-Aided Hyper-Inference Algorithm
Authors: Zhang Zhaochuang , Xia Jianhua , Wen Yuchuan , Weng Liting , Ma Zuofu , Yang Hekai , Yang Haobo , Dou Jinyao , Wang Jingang , Zhao Pengcheng
Published: September 2024

Inter-Turn Short Circuit (ITSC) faults do not necessarily produce high temperatures but exhibit distinct heat distribution and characteristics. This paper proposes a novel fault diagnosis and identification scheme utilizing an improved You Look Only Once Vision 8 (YOLOv8) algorithm, enhanced with an infrared image slicing-aided hyper-inference (SAHI) technique, to automatically detect ITSC fault trajectories in dry-type transformers. The infrared image acquisition system gathers data on ITSC fault trajectories and captures images with varying contrast to enhance the robustness of the recognition model. Given that the fault trajectory constitutes a small portion of the overall infrared image and is subject to significant background interference, traditional recognition algorithms often misjudge or omit faults. To address this, a YOLOv8-based visual detection method incorporating Dynamic Snake Convolution (DSConv) and the Slicing-Aided Hyper-Inference algorithm is proposed. This method aims to improve recognition precision and accuracy for small targets in complex backgrounds, facilitating accurate detection of ITSC faults in dry-type transformers. Comparative tests with the YOLOv8 model, Fast Region-based Convolutional Neural Networks (Fast-RCNNs), and Residual Neural Networks (Retina-Nets) demonstrate that the enhancements significantly improve model convergence speed and fault trajectory detection accuracy. The approach offers valuable insights for advancing infrared image diagnostic technology in electrical power equipment.
Robustness Indicators for the Impact of Occupant Behavior Uncertainty on Building Energy Consumption
Authors: Ying Jiahui , Yao Jian , Zheng Rongyue
Published: September 2024

Due to the significant impact of occupant behavior uncertainty on building performance, robustness indicators are crucial for assessing and predicting building energy consumption. This study evaluates the robustness of building performance under occupant behavior uncertainty using various robustness indicators such as Maximax, Maximin, Hurwicz, and Laplace. Benchmark values (0.635) and coefficients of variation (0.544) from statistics were introduced to quantify the relative performance of each indicator and the relative dispersion of the data, allowing for fair comparisons across different magnitudes of indicators. “Variance”, “Starr’s Domain”, “Kurtosis”, and “Maximin” were identified as key indicators for assessing the robustness of energy consumption and load data. Based on these indicators and statistical principles, assuming the data follows a normal distribution, energy consumption and loads were predicted, showing that the optimized outcomes demonstrate good robustness.
Heat Transfer Modeling and Optimal Thermal Management of Electric Vehicle Battery Systems
Authors: Mahmood Ahmed , Cockerill Timothy , de Boer Greg , Voss Jochen , Thompson Harvey
Published: September 2024

Lithium ion (Li-ion) battery packs have become the most popular option for powering electric vehicles (EVs). However, they have certain drawbacks, such as high temperatures and potential safety concerns as a result of chemical reactions that occur during their charging and discharging processes. These can cause thermal runaway and sudden deterioration, and therefore, efficient thermal management systems are essential to boost battery life span and overall performance. An electrochemical-thermal (ECT) model for Li-ion batteries and a conjugate heat transfer model for three-dimensional (3D) fluid flow and heat transfer are developed using COMSOL Multiphysics®. These are used within a novel computational fluid dynamics (CFD)-enabled multi-objective optimization approach, which is used to explore the effect of the mini-channel cold plates’ geometrical parameters on key performance metrics (battery maximum temperature (Tmax), pressure drop (∆P), and temperature standard deviation (Tσ)). The performance of two machine learning (ML) surrogate methods, radial basis functions (RBFs) and Gaussian process (GP), is compared. The results indicate that the GP ML approach is the most effective. Global minima for the maximum temperature, temperature standard deviation, and pressure drop (Tmax, Tσ, and ∆P, respectively) are identified using single objective optimization. The third version of the generalized differential evaluation (GDE3) algorithm is then used along with the GP surrogate models to perform multi-objective design optimization (MODO). Pareto fronts are generated to demonstrate the potential trade-offs between Tmax, Tσ, and ∆P. The obtained optimization results show that the maximum temperature dropped from 36.38 to 35.98 °C, the pressure drop dramatically decreased from 782.82 to 487.16 Pa, and the temperature standard deviation decreased from 2.14 to 2.12 K; the corresponding optimum design parameters are the channel width of 8 mm and the horizontal spacing near the cold plate margin of 5 mm.
Fixed-Time Robust Fractional-Order Sliding Mode Control Strategy for Grid-Connected Inverters Based on Weighted Average Current
Authors: Song Wenbin , Dong Yanfei , He Guofeng , Zhou Zichun
Published: September 2024

To address the issues of high computational load and slow dynamic performance in traditional fractional-order sliding mode control for LCL-type grid-connected inverters, this paper proposes a fixed-time robust fractional-order sliding mode control strategy based on weighted average current control. Firstly, the weighted average current control (WACC) is used to reduce the third-order LCL filter to the first order, which simplifies the system model; secondly, in order to suppress the disturbance caused by the filter parameter perturbation to the weighted average current accuracy, a fixed-time disturbance observer (FTDO) is used to quickly estimate the disturbance caused by the filter parameter perturbation in a fixed time, so as to improve the anti-interference ability of the system; moreover, a fixed-time fractional-order sliding mode controller (FTFOSMC) is designed to achieve rapid tracking of the incoming reference current, and the stability of the proposed control strategy is confirmed by the strict Lyapunov method, which proves that the upper bound of the stability time is independent of the initial state of the system. Finally, simulation and experimental results show that the proposed method has better steady-state performance and a higher dynamic performance.
Enhancing Aggregate Load Forecasting Accuracy with Adversarial Graph Convolutional Imputation Network and Learnable Adjacency Matrix
Authors: Zhao Junhao , Shen Xiaodong , Liu Youbo , Liu Junyong , Tang Xisheng
Published: September 2024

Accurate load forecasting, especially in the short term, is crucial for the safe and stable operation of power systems and their market participants. However, as modern power systems become increasingly complex, the challenges of short-term load forecasting are also intensifying. To address this challenge, data-driven deep learning techniques and load aggregation technologies have gradually been introduced into the field of load forecasting. However, data quality issues persist due to various factors such as sensor failures, unstable communication, and susceptibility to network attacks, leading to data gaps. Furthermore, in the domain of aggregated load forecasting, considering the potential interactions among aggregated loads can help market participants engage in cross-market transactions. However, aggregated loads often lack clear geographical locations, making it difficult to predefine graph structures. To address the issue of data quality, this study proposes a model named adversarial graph convolutional imputation network (AGCIN), combined with local and global correlations for imputation. To tackle the problem of the difficulty in predefining graph structures for aggregated loads, this study proposes a learnable adjacency matrix, which generates an adaptive adjacency matrix based on the relationships between different sequences without the need for geographical information. The experimental results demonstrate that the proposed imputation method outperforms other imputation methods in scenarios with random and continuous missing data. Additionally, the prediction accuracy of the proposed method exceeds that of several baseline methods, affirming the effectiveness of our approach in imputation and prediction, ultimately enhancing the accuracy of aggregated load forecasting.
Heavy Metal Content in Medicinal Plants Grown in Hydroponics and Forest Soil in the Central Part of Western Siberia
Authors: Mulyukin Maksim A. , Sutormin Oleg S. , Samoylenko Zoya A. , Kravchenko Inessa V. , Bulatova Elena V. , Gulakova Natalia M. , Baranenko Denis A. , Petrova Yuliya Yu.
Published: September 2024

The Khanty-Mansi Autonomous Okrug-Yugra, situated within Russia’s Far North, has undergone substantial industrialization and economic development. However, it is confronted with considerable environmental challenges, notably soil contamination. This study examines the presence of heavy metals (lead, cadmium, copper and zinc) in medicinal and berry plants from the forest ecosystem of this region. The following plant species were analyzed: Hypericum perforatum, Rubus arcticus, Origanum vulgare and Thymus vulgaris. The samples were taken from both open ground and hydroponic cultivation under artificial lighting. The findings indicate that the levels of lead present in all samples remain below the permissible limit of 10 mg/kg. Cadmium levels exhibited variability, with hydroponically grown plants containing 0.01 to 0.5 mg/kg and open ground Hypericum and Rubus perforatum containing up to 0.8 mg/kg. The combination of hydroponic cultivation and specific lighting conditions has been demonstrated to reduce lead and cadmium accumulation by a minimum of 1.6 times in comparison to open ground cultivation. The copper content of the samples ranged from 3 to 8 mg/kg, while the zinc content was 1.2–1.5 times higher in the plants grown in the open compared to those grown hydroponically. Notwithstanding these variations, the heavy metal content of all plant samples remains below the threshold values, thus rendering them safe for harvesting and utilization. This research serves to illustrate the environmental impact of industrial activities and to identify hydroponics as a potential strategy for their mitigation.
Preparing for the Worst: Enhancing Seedling Traits to Reduce Transplant Shock in Semi-Arid Regions
Authors: Mainhart Douglas E. , Christoffersen Bradley O. , Thompson R. Alexander , Reemts Charlotte M. , Fierro-Cabo Alejandro
Published: September 2024

The spatial extent of semi-arid hot regions is forecasted to grow through the twenty-first century, complicating restoration and reforestation plans. In arid and semi-arid climates, seedlings are more susceptible to transplant shock due to lower soil moisture throughout the year. Determining strategies to reduce seedling stress and improve survival post-planting will be paramount to continued reforestation efforts in a changing climate. We quantified seedling physiological, morphological, and field performance (mortality and growth) response for five species native to the semi-arid region of South Texas (Erythrina herbacea L., Celtis pallida Torr., Fraxinus berlandieriana DC, Malpighia glabra L., and Citharexylum berlandieri B.L Rob) to an antitranspirant (abscisic acid), drought, and elevated CO2. We examined post-treatment seedling gas exchange, non-structural carbohydrates, osmolality, root structure, and stomatal density and evaluated mortality and growth rate on a sample of the treatment population. For elevated CO2 and drought hardening treatments, seedling gas exchange, solute content, specific root length, and stomatal density varied by species, while abscisic acid strongly reduced transpiration and stomatal conductance in all species. However, these physiological and morphological differences did not translate to reduced mortality or improved growth rate due to high herbivory and above-normal precipitation after planting precluding seedlings from stress. We conclude that the simpler antitranspirant approach, rather than the more logistically challenging eCO2, has the potential to reduce drought-related transplant shock but requires more widespread testing.
Ecology of Some Panorpa (Mecoptera, Panorpidae) Species from Several Regions of Russia
Authors: Dvořák Libor , Ruchin Alexander B. , Aleksanov Viktor V. , Egorov Leonid V. , Esin Mikhail N. , Lukiyanov Sergei V. , Lobachev Evgeniy A. , Fayzulin Alexander I.
Published: September 2024

Our study focuses on the investigation of the ecological aspects (seasonal dynamics, height distribution, and preference of biotopes) of six species within the genus Panorpa (P. alpina Rambur, 1842, P. cognata Rambur, 1842, P. communis Linnaeus, 1758, P. germanica Linnaeus, 1758, P. hybrida MacLachlan, 1882, and P. vulgaris Imhoff & Labram, 1845). The observed seasonal dynamics predominantly display a monovoltine nature. P. communis was active from the early days of May, with individuals persisting until the beginning of October. Conversely, P. vulgaris exhibits activity from the third decade of May to mid-September. P. hybrida manifests within a concise timeframe, observed from late May to late July. P. cognata demonstrates activity commencing in early May, with individuals observed until the end of September. Within forest environments, the highest population density of all species is concentrated at a height of 1.5 m above ground level, whereas the minimum population density is recorded at a height of 12 m above ground level. P. vulgaris demonstrates comparable abundance across heights ranging from 1.5 to 7.5 m, whereas P. hybrida exhibits uniform distribution solely at heights of 1.5 and 3.5 m. Furthermore, the abundance of P. communis surpasses that at other heights when observed at the height of 1.5 m. Panorpa specimens exhibit an absence in open ecosystems at heights of 8 and 10 m. The peak of population density for all species is consistently identified at heights of 2 and 4 m. The application of six diverse entomological methodologies leads to optimal outcomes. Our investigations reveal that P. communis, P. vulgaris, and P. hybrida display greater attraction to beer traps, while P. cognata exhibits a comparatively diminished propensity for such traps. P. cognata, in contrast, demonstrates a substantial presence in pan traps and pitfall traps. In Malaise traps, pan traps, and pitfall traps, five distinct species were captured, although with a species composition differing from alternative methods. To sum up, for the comprehensive study of Panorpa across an expansive geographical spectrum, it is judicious to integrate both net captures and the use of diverse trap types. In addition, it is necessary to explore all biotopes and tiers of the forest.
Targeting Gut Microbiota with Probiotics and Phenolic Compounds in the Treatment of Atherosclerosis: A Comprehensive Review
Authors: Cruz Neto José Patrocínio Ribeiro , de Luna Freire Micaelle Oliveira , de Albuquerque Lemos Deborah Emanuelle , Ribeiro Alves Rayanne Maira Felix , de Farias Cardoso Emmily Ferreira , de Moura Balarini Camille , Duman Hatice , Karav Sercan , de Souza Evandro Leite , de Brito Alves José Luiz
Published: September 2024

Atherosclerosis (AS) is a chronic inflammatory vascular disease. Dysregulated lipid metabolism, oxidative stress, and inflammation are the major mechanisms implicated in the development of AS. In addition, evidence suggests that gut dysbiosis plays an important role in atherogenesis, and modulation of the gut microbiota with probiotics and phenolic compounds has emerged as a promising strategy for preventing and treating AS. It has been shown that probiotics and phenolic compounds can improve atherosclerosis-related parameters by improving lipid profile, oxidative stress, and inflammation. In addition, these compounds may modulate the diversity and composition of the gut microbiota and improve atherosclerosis. The studies evaluated in the present review showed that probiotics and phenolic compounds, when consumed individually, improved atherosclerosis by modulating the gut microbiota in various ways, such as decreasing gut permeability, decreasing TMAO and LPS levels, altering alpha and beta diversity, and increasing fecal bile acid loss. However, no study was found that evaluated the combined use of probiotics and phenolic compounds to improve atherosclerosis. The available literature highlights the synergistic potential between phenolic compounds and probiotics to improve their health-promoting properties and functionalities. This review aims to summarize the available evidence on the individual effects of probiotics and phenolic compounds on AS, while providing insights into the potential benefits of nutraceutical approaches using probiotic strains, quercetin, and resveratrol as potential adjuvant therapies for AS treatment through modulation of the gut microbiota.
Nutritional and Functional Properties of Terminalia ferdinandiana Fruits Wild Harvested from Western Australia
Authors: Bobasa Eshetu M. , Phan Anh Dao Thi , Netzel Michael E. , Akter Saleha , Cozzolino Daniel , Sultanbawa Yasmina
Published: September 2024

This study assessed the metabolite content and bioactivities of Kakadu plum (KP) from Western Australia (WA). LC-MS/MS and UHPLC-PDA analyzed sugar, vitamin C, and ellagic acid (EA). Functional properties were evaluated by spectroscopic technique, agar well diffusion, and microplate dilution methods. WA KP exhibited higher total sugar (16.3 ± 1.0 g/100 g DW) and free ellagic acid (EA) (23.2 ± 1.7 mg/g DW), along with abundant vitamin C (25.20 ± 0.16 to 131.50 ± 0.20 mg/g DW) compared to Northern Territory KP fruits. The fruit showed strong antioxidant activities, α-glucosidase inhibition, and effectiveness against bacteria, with positive correlations to total phenolic content (TPC), vitamin C, and EA. These findings highlight WA KP’s potential for functional foods and pharmaceuticals, emphasizing the importance of TPC, vitamin C, and EA in selecting high-quality fruit.
Practical Stability of Observer-Based Control for Nonlinear Caputo–Hadamard Fractional-Order Systems
Authors: Issaoui Rihab , Naifar Omar , Tlija Mehdi , Mchiri Lassaad , Ben Makhlouf Abdellatif
Published: September 2024

This paper investigates the problem of observer-based control for a class of nonlinear systems described by the Caputo–Hadamard fractional-order derivative. Given the growing interest in fractional-order systems for their ability to capture complex dynamics, ensuring their practical stability remains a significant challenge. We propose a novel concept of practical stability tailored to nonlinear Hadamard fractional-order systems, which guarantees that the system solutions converge to a small ball containing the origin, thereby enhancing their robustness against perturbations. Furthermore, we introduce a practical observer design that extends the classical observer framework to fractional-order systems under an enhanced One-Sided Lipschitz (OSL) condition. This extended OSL condition ensures the convergence of the proposed practical observer, even in the presence of significant nonlinearities and disturbances. Notably, the novelty of our approach lies in the extension of both the practical observer and the stability criteria, which are innovative even in the integer-order case. Theoretical results are substantiated through numerical examples, demonstrating the feasibility of the proposed method in real-world control applications. Our contributions pave the way for the development of robust observers in fractional-order systems, with potential applications across various engineering domains.
Stationary Bayesian–Markov Equilibria in Bayesian Stochastic Games with Periodic Revelation
Authors: Ko Eunmi
Published: September 2024

I consider a class of dynamic Bayesian games in which types evolve stochastically according to a first-order Markov process on a continuous type space. Types are privately informed, but they become public together with actions when payoffs are obtained, resulting in a delayed information revelation. In this environment, I show that there exists a stationary Bayesian–Markov equilibrium in which a player’s strategy maps a tuple of the previous type and action profiles and the player’s current type to a mixed action. The existence can be extended to K-periodic revelation. I also offer a computational algorithm to find an equilibrium.
Pathognomonic Signs in Pancreatic Cystic Lesions: What Gastroenterologists and Involved Clinicians Need to Know
Authors: Martino Alberto , Barresi Luca , Zito Francesco Paolo , Amata Michele , Fiorentino Roberto , Campione Severo , Iacobelli Alessandro , Crolla Enrico , Di Mitri Roberto , Molino Carlo , Di Serafino Marco , Lombardi Giovanni
Published: September 2024

Pancreatic cystic lesions (PCLs) have been increasingly identified in recent years, encompassing a wide spectrum ranging from benign non-evolutive to malignant invasive lesions. Despite various clinical, laboratory, imaging, endoscopic ultrasound, and cytohistological features that may aid clinicians in the complex differential diagnosis of PCLs, only a few pathognomic signs distinctive to specific PCLs have been identified. Although rarely encountered, their proper recognition is crucial for the appropriate management of PCLs. The aim of our review is to extensively discuss and illustrate pathognomic signs in the setting of PCLs.
Genetic Modifiers of ALS: The Impact of Chromogranin B P413L in a Bulgarian ALS Cohort
Authors: Tourtourikov Ivan , Todorov Tihomir , Angelov Teodor , Chamova Teodora , Tournev Ivailo , Mitev Vanyo , Todorova Albena
Published: September 2024

This study investigated the role of the CHGB P413L variant (rs742710) in sporadic amyotrophic lateral sclerosis (sALS) within the Bulgarian population. We analyzed 150 patients with sALS (85 male and 65 female) for the presence of this variant, its potential impact on disease susceptibility, and age of onset. Genotyping was performed using PCR amplification and direct Sanger sequencing. Statistical analyses included comparisons with control data from GnomAD v2.1.1, one-way ANOVA, and Kaplan–Meier survival analysis. Results revealed a higher frequency of the minor T allele in patients with sALS compared to all control groups and a statistically significant increase in carrier genotypes compared to non-Finnish Europeans (χ2 = 15.4572, p = 0.000440). However, the impact on age of onset was less clear, with no statistically significant differences observed across genotypes or between carriers and non-carriers of the T allele. Kaplan–Meier analysis suggested a potential 2.5-year-earlier onset in T allele carriers, but the small sample size of carriers limits the reliability of this finding. Our study provides evidence for an association between the CHGB P413L variant and sALS susceptibility in the Bulgarian population, while its effect on age of onset remains uncertain, highlighting the need for further research in larger, diverse cohorts.
Hepatitis B Management in the Middle East: A Narrative Review of Current Antiviral Treatments
Authors: Beck Hannah , Dalavaye Nishaanth , Kengadaran Kalaikshiga , Khatun Mosammath Monira , Patel Ria Hitesh , Al-Rubaye Taif , Alrubaiy Laith
Published: September 2024

Introduction: Chronic hepatitis B (CHB) is a significant public health issue worldwide, especially in the Middle East region. Around 8% to 20% of patients with CHB develop cirrhosis, which may progress to hepatocellular carcinoma. The significant morbidity and mortality associated with CHB denote the importance of high-quality treatment. Methods: We searched the PubMed, Medline, and Cochrane databases from inception to January 2024 to identify relevant studies. Search terms were generated using established treatment guidelines for CHB. We also manually searched the bibliographies of relevant literature to obtain additional papers. Results: In this narrative review, we evaluated the seven currently licensed antiviral therapies for chronic Hepatitis B treatment, including nucleos(t)ide analogs (NAs) and pegylated interferon-alpha (PEG-IFNα). NAs can be divided into two categories: high barrier to resistance and low barrier to resistance. Tenofovir disoproxil fumarate, tenofovir alafenamide, and entecavir are NAs with a high barrier to resistance. Telbivudine has shown promise in providing high efficacy with low viral resistance rates; however, it is not recommended because of insufficient evidence and lack of cost-effectiveness. Lamivudine and adefovir dipivoxil, despite being efficacious, have a low barrier to resistance, the primary reason they are no longer recommended. PEG-IFNα has high efficacy and can be completed in 48 weeks. It is not associated with resistance; however, it has been reported to have several systemic adverse effects. Conclusions: Current first-line NA treatments in the Middle East include entecavir, tenofovir disoproxil fumarate, and tenofovir alafenamide. These drugs are favored over other NAs because of their low rates of resistance. PEG-IFNα has superiority over NAs in inducing a more durable antiviral response and having a finite treatment duration. The main drawback of PEG-IFNα is an unfavorable safety profile.
Does It Take a Village? The Impact of LGBTQ+ Community and Geographic Location on Associations among Parenting Stress, Parent Mental Health, and Child Adjustment
Authors: McAweeney Kevin A. , Farr Rachel H.
Published: September 2024

While LGBTQ+-parented families share many similarities with their cis-het parent counterparts, they still experience unique factors exclusive to them. One such factor is access to the LGBTQ+ community. Utilizing a diverse sample of LGBTQ+ parents with adolescents in the U.S., primarily living in Southern and Midwest states, we examined the potential moderating impact of a parent’s sense of LGBTQ+ community on the relationship between parenting stress, parent mental health, and child adjustment. Regression analyses demonstrated a series of positive associations between LGBTQ+ parent stress, parent mental health concerns, and child adjustment issues. However, sense of community failed to moderate these associations. Parent sexual identity, age, and recruitment method were found to have unique associations with outcome variables. Implications for policy, clinical practice, and future research are discussed.
Evaluation of the Monitoring Capabilities of Remote Sensing Satellites for Maritime Moving Targets
Authors: Li Weiming , Du Zhiqiang , Wang Li , Zhou Tiancheng
Published: September 2024

Although an Automatic Identification System (AIS) can be used to monitor trajectories, it has become a reality for remote sensing satellite clusters to monitor maritime moving targets. The increasing demand for monitoring poses challenges for the construction of satellites, the monitoring capabilities of which urgently need to be evaluated. Conventional evaluation methods focus on the spatial characteristics of monitoring; however, the temporal characteristics and the target’s kinematic characteristics are neglected. In this study, an evaluation method that integrates the spatial and temporal characteristics of monitoring along with the target’s kinematic characteristics is proposed. Firstly, a target motion prediction model for calculating the transfer probability and a satellite observation information calculation model for obtaining observation strips and time windows are established. Secondly, an index system is established, including the target detection capability, observation coverage capability, proportion of empty window, dispersion of observation window, and deviation of observation window. Thirdly, a comprehensive evaluation is completed through combining the analytic hierarchy process and entropy weight method to obtain the monitoring capability score. Finally, simulation experiments are conducted to evaluate the monitoring capabilities of satellites for ship trajectories. The results show that the method is effective when the grid size is between 1.6 and 1.8 times the target size and the task duration is approximately twice the time interval between trajectory points. Furthermore, the method is proven to be usable in various environments.
Circulating Polyploid Giant Cancer Cells, a Potential Prognostic Marker in Patients with Carcinoma
Authors: Chinen Ludmilla Thomé Domingos , Torres Jacqueline Aparecida , Calsavara Vinicius Fernando , Brito Angelo Borsarelli Carvalho , Silva Virgílio Sousa e , Novello Roberto Gabriel Santiago , Fernandes Thaissa Carvalho , Decina Alessandra , Dachez Roger , Paterlini-Brechot Patrizia
Published: September 2024

Polyploid Giant Cancer Cells (PGCCs) have been recognized as tumor cells that are resistant to anticancer therapies. However, it remains unclear whether their presence in the bloodstream can be consistently detected and utilized as a clinical marker to guide therapeutic anticancer regimens. To address these questions, we conducted a retrospective study involving 228 patients diagnosed with six different types of carcinomas (colon, gastric, NSCLC, breast, anal canal, kidney), with the majority of them (70%) being non-metastatic. Employing a highly sensitive liquid biopsy approach, ISET®, and cytopathological readout, we isolated and detected circulating PGCCs in the patients’ blood samples. PGCCs were identified in 46 (20.18%) out of 228 patients, including in 14.47% of 152 non-metastatic and 29.85% of 67 metastatic cases. Patients were subsequently monitored for a mean follow up period of 44.74 months (95%CI: 33.39–55.79 months). Remarkably, the presence of circulating PGCCs emerged as a statistically significant indicator of poor overall survival. Our findings suggest that circulating PGCCs hold promise as a reliable prognostic indicator. They underscore the importance of further extensive investigations into the role of circulating PGCCs as a prognostic marker and the development of anti-PGCC therapeutic strategies to improve cancer management and patient survival.
Alterations of Liver Morphology in Senescent Rats
Authors: Maldonado-Rengel Ruth , Sócola-Barsallo Zaida , Vásquez Bélgica
Published: September 2024

Age-related liver changes can have important implications for health and metabolic function. This study aimed to describe the morphoquantitative alterations of the liver in senescent rats compared to adult rats. Twelve male rats were used, divided into 6-month-old adults (group A) and 36-month-old senescent rats (group S). Morphometric and histopathological studies, quantification of collagen types I and III, and stereological analyses were performed to determine the volume density of mononucleated (VvhepM) and binucleated (VvhepB) hepatocyte nuclei, surface area density (SvhepM), and number density (NvhepM) of mononucleated hepatocyte nuclei. The findings reveal an alteration of the normal liver tissue architecture in senescent rats and the presence of inflammatory lesions and fibrosis. In addition, there was a decrease in body and liver mass and volume. Group S showed a significant reduction in VvhepM and NvhepM; however, SvhepM was significantly higher. No significant differences were noted in the percentage of binucleated hepatocytes between the two groups. This study reveals substantial morphological changes in the aging liver, with possible functional implications. More research is needed on the underlying mechanisms and their consequences at older ages.
Histaminergic System Activity in the Central Nervous System: The Role in Neurodevelopmental and Neurodegenerative Disorders
Authors: Szukiewicz Dariusz
Published: September 2024

Histamine (HA), a biogenic monoamine, exerts its pleiotropic effects through four H1R–H4R histamine receptors, which are also expressed in brain tissue. Together with the projections of HA-producing neurons located within the tuberomammillary nucleus (TMN), which innervate most areas of the brain, they constitute the histaminergic system. Thus, while remaining a mediator of the inflammatory reaction and immune system function, HA also acts as a neurotransmitter and a modulator of other neurotransmitter systems in the central nervous system (CNS). Although the detailed causes are still not fully understood, neuroinflammation seems to play a crucial role in the etiopathogenesis of both neurodevelopmental and neurodegenerative (neuropsychiatric) diseases, such as autism spectrum disorders (ASDs), attention-deficit/hyperactivity disorder (ADHD), Alzheimer’s disease (AD) and Parkinson’s disease (PD). Given the increasing prevalence/diagnosis of these disorders and their socioeconomic impact, the need to develop effective forms of therapy has focused researchers’ attention on the brain’s histaminergic activity and other related signaling pathways. This review presents the current state of knowledge concerning the involvement of HA and the histaminergic system within the CNS in the development of neurodevelopmental and neurodegenerative disorders. To this end, the roles of HA in neurotransmission, neuroinflammation, and neurodevelopment are also discussed.
Integrated Metabolome, Transcriptome and Long Non-Coding RNA Analysis Reveals Potential Molecular Mechanisms of Sweet Cherry Fruit Ripening
Authors: Liu Gangshuai , Fu Daqi , Duan Xuwei , Zhou Jiahua , Chang Hong , Xu Ranran , Wang Baogang , Wang Yunxiang
Published: September 2024

Long non-coding RNAs (lncRNAs), a class of important regulatory factors for many biological processes in plants, have received much attention in recent years. To explore the molecular roles of lncRNAs in sweet cherry fruit ripening, we conducted widely targeted metabolome, transcriptome and lncRNA analyses of sweet cherry fruit at three ripening stages (yellow stage, pink stage, and dark red stage). The results show that the ripening of sweet cherry fruit involves substantial metabolic changes, and the rapid accumulation of anthocyanins (cyanidin 3-rutinoside, cyanidin 3-O-galactoside, and cyanidin 3-O-glucoside) is the main cause of fruit coloration. These ripening-related alterations in the metabolic profile are driven by specific enzyme genes related to the synthesis and decomposition of abscisic acid (ABA), cell wall disintegration, and anthocyanin biosynthesis, as well as transcription factor genes, such as MYBs, bHLHs, and WD40s. LncRNAs can target these ripening-related genes to form regulatory modules, incorporated into the sweet cherry fruit ripening regulatory network. Our study reveals that the lncRNA-mRNA module is an important component of the sweet cherry fruit ripening regulatory network. During sweet cherry fruit ripening, the differential expression of lncRNAs will meditate the spatio-temporal specific expression of ripening-related target genes (encoding enzymes and transcription factors related to ABA metabolism, cell wall metabolism and anthocyanin metabolism), thus driving fruit ripening.
Association between Estrogen Levels and Temporomandibular Disorders: An Updated Systematic Review
Authors: Zieliński Grzegorz , Pająk-Zielińska Beata
Published: September 2024

The aim of this systematic review is to evaluate the impact of estrogen levels on the occurrence of temporomandibular disorders (TMDs) in humans. Searches were conducted in the same databases as follows: PubMed, the Cochrane Collaboration database, and the Scopus database. In accordance with the MeSH database and previous work, the following keywords were used: ‘estrogens’ and ‘temporomandibular joint disorders’. Twelve studies were included in the review and were assessed for the quality of evidence. Estrogen levels are associated with pain modulation in the temporomandibular joint and the entire orofacial region. There is insufficient evidence to either confirm or refute the influence of estrogen on the occurrence of TMDs. The study was registered under the identifier: 10.17605/OSF.IO/BC7QF.
Identification of Rapeseed (Brassica napus L.) Plant Height-Associated QTL Using BSA-seq and RNA-seq
Authors: Xia Jichun , Zhan Lanlan , Zhang Jiaying , Song Wenhui , Xu Xinfu
Published: September 2024

Plant height (PH) is a critical agronomic trait in Brassica napus, significantly impacting yield. Consequently, identifying genes associated with plant height is a pivotal objective in oilseed rape breeding. This study employed a combination of bulk segregant analysis sequencing (BSA-seq) and RNA sequencing (RNA-seq) for analysis. A novel quantitative trait locus (QTL), qPH_C02, was identified between 63,989,634 and 64,945,122 bp on chromosome C02, from which eight candidate genes were screened. The Gene Ontology (GO) analysis revealed enrichment in peroxisomes, while the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis indicated enrichment in the oxidative phosphorylation (OP) pathway. It is hypothesized that the observed differences in plant height and silique length may be attributed to the regulation of peroxidase activity in the OP pathway, which in turn alters plant energy metabolism and controls nutrient uptake. Subsequently, we will further test this hypothesis. The results of this study will contribute to our understanding of the genetic basis for differences in plant height and provide a foundation for the selection and breeding of Brassica napus varieties with desired plant shapes.