bluuebunny/crossref_metadata_2025 huggingface dataset:
The Use of Sodium Hypochlorite and Plant Preservative Mixture Significantly Reduces Seed-Borne Pathogen Contamination When Establishing In Vitro Cultures of Wheat (Triticum aestivum L.) Seeds
Authors: Bošnjak Mihovilović Anita , Kereša Snježana , Lazarević Boris , Topolovec Pintarić Snježana , Martinko Katarina , Marković Zvjezdana , Turkalj Katarina , Habuš Jerčić Ivanka
Published: March 2024

In vitro plants that are free of pathogens are crucial for biotechnological breeding methods. The present study investigates the effects of sterilization with sodium hypochlorite (NaClO) and the addition of Plant Preservative Mixture (PPMTM) to the growth medium on pathogen elimination, germination, and seedling development of the winter wheat (Triticum aestivum L.) variety Mara. The sterilization treatments differed in the duration of seed sterilization in 4% NaClO and the PPM concentration added to the growth medium. Pathogenic fungi of the genera Aspergillus, Cladosporium, Penicillium, and Bipolaris were completely eliminated when the seeds were sterilized in NaClO and placed on growth media with the addition of PPM. Extending the duration of the sterilization treatment with NaClO to 50 min reduced Fusarium contamination, while the interaction between the 50 min sterilization treatment with NaClO and the addition of PPM to the growth medium reduced Alternaria contamination. Our results suggest that PPM could complement sterilization procedures with NaClO in the introduction of highly infected wheat seeds in vitro. Seed germination was not affected by sterilization with NaClO or by the addition of PPM. However, PPM at a concentration of 4 mL L−1 had a negative effect on seedling development.
Epidemiological Insights into Feline Leukemia Virus Infections in an Urban Cat (Felis catus) Population from Brazil
Authors: Diesel Laura Pancich , de Mello Lauren Santos , de Oliveira Santana Weslei , Ikuta Nilo , Fonseca André Salvador Kazantzi , Kipper Diéssy , Redaelli Raquel , Pereira Vagner Reinaldo Zingali Bueno , Streck André Felipe , Lunge Vagner Ricardo
Published: March 2024

Feline leukemia virus (FeLV) is a retrovirus distributed worldwide in domestic cats and with different outcomes (progressive, regressive, abortive, focal). The present study reports an epidemiological survey of FeLV frequency and the evaluation of some risk factors and the two main disease outcomes (progressive and regressive) in an urban cat population from Brazil. A total of 366 cats with sociodemographic information and p27 FeLV antigen test performed were included in the study. FeLV DNA (provirus) in the blood samples of all cats was detected via real-time polymerase chain reaction (qPCR). Plasma samples from 109 FeLV-positive and FeLV-negative cats were also submitted to reverse transcription (RT-qPCR) to determine the FeLV viral load. The results demonstrated that 112 (30.6%) cats were positive through the p27 antigen and/or qPCR. A risk factor analysis demonstrated that cats without vaccination against FeLV (OR 9.9, p < 0.001), clinically ill (OR 2.9, p < 0.001), with outdoors access (OR 2.7, p < 0.001), and exhibiting apathetic behavior (OR 3.1, p < 0.001) were more likely to be infected with FeLV. FeLV-infected cats were also more likely to present with anemia (OR 13, p < 0.001) and lymphoma (OR 13.7, p = 0.001). A comparative analysis of the different detection methods in a subset of 109 animals confirmed FeLV infection in 58 cats, including 38 (65.5%) with progressive, 16 (27.6%) with regressive, and 4 (6.9%) with probably focal outcome diseases. In conclusion, this study demonstrates a high prevalence of FeLV in this urban cat population from Brazil and highlights the need to establish more effective prevention strategies (such as viral testing, vaccination programs, specific care for FeLV-positive cats) to reduce diseases associated with this virus in Brazil.
Subtherapeutic Kitasamycin Promoted Fat Accumulation in the Longissimus Dorsi Muscle in Growing–Finishing Pigs
Authors: Han Ge , Yu Jie , He Jun , Zheng Ping , Mao Xiangbing , Yu Bing
Published: March 2024

Kitasamycin (KM), a broad—spectrum macrolide antibiotic, has implications for growth performance and residue in animals and humans. This study aimed to explore the effects of different KM doses on intramuscular fat accumulation, cecal microflora, and short—chain fatty acids (SCFAs) using a growing–finishing pig model. Forty—two pigs were divided into three groups: control, subtherapeutic KM (50 mg/kg, KM50), and therapeutic KM (200 mg/kg, KM200) diets over 8 weeks. KM50 led to increased back fat thickness, fat content in the longissimus dorsi muscle (LM), and elevated plasma total cholesterol (TC) levels (p < 0.05), supported by upregulated lipid synthesis gene expression (Acc1, Fas, Scd1) (p < 0.05) in the LM. KM50 altered cecal microflora, reducing Lactobacillus spp. and Bifidobacterium spp. abundance, while increasing SCFA concentrations (acetic acid, propionic acid, total SCFAs) (p < 0.05). KM200 had minimal effects on intestinal weight and density, with increased apparent digestibility of nutrients. These findings highlight the dose-dependent impact of KM on intramuscular fat deposition. Subtherapeutic KM induced ectopic fat deposition, emphasizing potential risks in disease treatment for humans and animals.
Transcriptomic Association Analysis of the Metabolic Mechanism of Sulfamethoxazole in Channel Catfish (Ictalurus punctatus)
Authors: Du Xiangxuan , Sun Ruyu , Zhang Lei , Liu Yongtao , Ai Xiaohui
Published: March 2024

Sulfamethoxazole is a widely used antimicrobial drug used to treat bacterial diseases in aquaculture. To understand the gene expression in channel catfish liver after treatment with sulfamethoxazole, in this study, the treatment group received sulfamethoxazole (100 mg/kg bw), which was administered orally once, and samples were taken at 5 h, 12 h, and 6 d after the administration of sulfamethoxazole, while the control group was orally administered sterile water. To further identify potentially significant genes, a transcriptome analysis using RNA-seq was carried out. More than 50 million high-quality reads were found. After filtering and quality analysis, these reads were identified as 54,169,682, 51,313,865, 51,608,845, and 49,333,491. After counting 23,707 of these transcripts for gene expression, it was discovered that 14,732 of them had genes with differential expression. Moreover, we found that the annotation with the most GO variation was “cellular process” (1616 genes), “metabolic process” (1268 genes), “binding” (1889 genes), and “catalytic activity” (1129 genes). KEGG pathways showed that the “metabolic pathway” was the pathway that was significantly enriched in both experimental groups when comparing the experimental groups: 5 h and 12 h (128 genes); 5 h and 6 d (332 genes); and 12 h and 6 d (348 genes). Also, UDP- glucuronosyltransferase (ugt), which is associated with glucuronidation, and UDP-glucuronosyltransferase 2C1-like (ugt2a1) showed significant upregulation. Carboxylesterase 5A-like (ces3), which promotes fatty acyl and cholesteryl ester metabolism, and the glutathione transferase family were upregulated in the expression of sulfamethoxazole metabolism in the liver, which significantly affected the metabolic effects of the drug. Meanwhile, dypd, uck2b, and rrm2, which are related to nucleotide synthesis and metabolism, were upregulated. Our study extends the knowledge of gene expression in drug metabolism in channel catfish and further provides insight into the molecular mechanism of sulfamethoxazole metabolism.
Estimate of Growth Parameters of Penaeus kerathurus (Forskäl, 1775) (Crustacea, Penaeidae) in the Northern Adriatic Sea
Authors: Scanu Martina , Froglia Carlo , Grati Fabio , Bolognini Luca
Published: March 2024

Crustacean fisheries are gaining prominence globally amid a decline in finfish stocks. Some decapod crustacean species have experienced increased landings in response to shifting market demands and environmental dynamics. Notably, the caramote prawn (Penaeus kerathurus—Forskål, 1775) in the northern Adriatic Sea, Geographical Sub Area (GSA) 17, has risen in both landings and economic importance in recent years. However, despite its significance, comprehensive information on fishery-dependent data, age, and growth in this region remains lacking. To address this gap, this study employs modal progression analysis and the ELEFAN approach, utilizing the “TropFishR” R package and newly developed functions, including bootstrapping procedures. These advancements aim to overcome issues identified in previous versions and enhance the accuracy and reliability of age and growth estimations. The study leverages one year of monthly length-frequency distributions (LFDs) collected from commercial bottom trawls in the northern Adriatic Sea. The results of the analysis confirm the presence of sexual dimorphism in the caramote prawn species, with females exhibiting faster growth rates compared to males. Additionally, the growth performance index supports this observation, further underscoring the importance of accounting for sexual dimorphism in growth modeling and fisheries management strategies. By contributing to a growing body of knowledge on the growth dynamics of the caramote prawn, this study provides valuable insights for sustainable fisheries management in the northern Adriatic Sea. Understanding the age and growth patterns of key crustacean species is essential for developing effective conservation measures and ensuring the long-term health and productivity of marine ecosystems. The findings of this study serve as a foundation for informed decision-making and proactive management practices aimed at preserving the ecological integrity and economic viability of crustacean fisheries in the region.
Telomerase Inhibition in the Treatment of Leukemia: A Comprehensive Review
Authors: Bartoszewska Elżbieta , Molik Klaudia , Woźniak Marta , Choromańska Anna
Published: March 2024

Leukemia, characterized by the uncontrolled proliferation and differentiation blockage of myeloid or lymphoid precursor cells, presents significant therapeutic challenges despite current treatment modalities like chemotherapy and stem cell transplantation. Pursuing novel therapeutic strategies that selectively target leukemic cells is critical for improving patient outcomes. Natural products offer a promising avenue for developing effective chemotherapy and preventive measures against leukemia, providing a rich source of biologically active compounds. Telomerase, a key enzyme involved in chromosome stabilization and mainly active in cancer cells, presents an attractive target for intervention. In this review article, we focus on the anti-leukemic potential of natural substances, emphasizing vitamins (such as A, D, and E) and polyphenols (including curcumin and indole-3-carbinol), which, in combination with telomerase inhibition, demonstrate reduced cytotoxicity compared to conventional chemotherapies. We discuss the role of human telomerase reverse transcriptase (hTERT), particularly its mRNA expression, as a potential therapeutic target, highlighting the promise of natural compounds in leukemia treatment and prevention.
Speech Audiometry: The Development of Lithuanian Bisyllabic Phonemically Balanced Word Lists for Evaluation of Speech Recognition
Authors: Vainutienė Vija , Ivaška Justinas , Kardelis Vytautas , Ivaškienė Tatjana , Lesinskas Eugenijus
Published: March 2024

Background and Objectives: Speech audiometry employs standardized materials, typically in the language spoken by the target population. Language-specific nuances, including phonological features, influence speech perception and recognition. The material of speech audiometry tests for the assessment of word recognition comprises lists of words that are phonemically or phonetically balanced. As auditory perception is influenced by a variety of linguistic features, it is necessary to develop test materials for the listener’s mother tongue. The objective of our study was to compose and evaluate new lists of Lithuanian words to assess speech recognition abilities. Materials and Methods: The main criteria for composing new lists of Lithuanian words included the syllable structure and frequency, the correlation between consonant and vowel phonemes, the frequency of specific vowel and consonant phonemes, word familiarity and rate. The words for the new lists were chosen from the Frequency Dictionary of Written Lithuanian according to the above criteria. Word recognition was assessed at different levels of presentations. The word list data were analyzed using a linear mixed-effect model for repeated measures. Results: Two hundred bisyllabic words were selected and organized into four lists. The results showed no statistically significant difference between the four sets of words. The interaction of the word list and presentation level was not statistically significant. Conclusions: Monaural performance functions indicated good inter-list reliability with no significant differences between the word recognition scores on the different bisyllabic word lists at each of the tested intensities. The word lists developed are equivalent, reliable and can be valuable for assessing speech recognition in a variety of conditions, including diagnosis, hearing rehabilitation and research.
An Intelligent Detection and Classification Model Based on Computer Vision for Pavement Cracks in Complicated Scenarios
Authors: Wang Yue , Qi Qingjie , Sun Lifeng , Xian Wenhao , Ma Tianfang , Lu Changjia , Zhang Jingwen
Published: March 2024

With the extension of road service life, cracks are the most significant type of pavement distress. To monitor road conditions and avoid excessive damage, pavement crack detection is absolutely necessary and an indispensable part of road periodic maintenance and performance assessment. The development and application of computer vision have provided modern methods for crack detection, which are low in cost, less labor-intensive, continuous, and timely. In this paper, an intelligent model based on a target detection algorithm in computer vision was proposed to accurately detect and classify four classes of cracks. Firstly, by vehicle-mounted camera capture, a dataset of pavement cracks with complicated backgrounds that are the most similar to actual scenarios was built, containing 4007 images and 7882 crack samples. Secondly, the YOLOv5 framework was improved from the four aspects of the detection layer, anchor box, neck structure, and cross-layer connection, and thereby the network’s feature extraction capability and small-sized-target detection performance were enhanced. Finally, the experimental results indicated that the proposed model attained an AP of the four classes of 81.75%, 83.81%, 98.20%, and 92.83%, respectively, and a mAP of 89.15%. In addition, the proposed model achieved a 2.20% missed detection rate, representing a 6.75% decrease over the original YOLOv5. These results demonstrated the effectiveness and practicality of our proposed model in addressing the issues of low accuracy and missed detection for small targets in the original network. Overall, the implementation of computer vision-based models in crack detection can promote the intellectualization of road maintenance.
STPA-RL: Integrating Reinforcement Learning into STPA for Loss Scenario Exploration
Authors: Chang Jiyoung , Kwon Ryeonggu , Kwon Gihwon
Published: March 2024

Experience-based methods like reinforcement learning (RL) are often deemed less suitable for the safety field due to concerns about potential safety issues. To bridge this gap, we introduce STPA-RL, a methodology that integrates RL with System-Theoretic Process Analysis (STPA). STPA is a safety analysis technique that identifies causative factors leading to unsafe control actions and system hazards through loss scenarios. In the context of STPA-RL, we formalize the Markov Decision Process based on STPA analysis results to incorporate control algorithms into the system environment. The agent learns safe actions through reward-based learning, tracking potential hazard paths to validate system safety. Specifically, by analyzing various loss scenarios related to the Platform Screen Door, we assess the applicability of the proposed approach by evaluating hazard trajectory graphs and hazard frequencies in the system. This paper streamlines the RL process for loss scenario identification through STPA, contributing to self-guided loss scenarios and diverse system modeling. Additionally, it offers effective simulations for proactive development to enhance system safety and provide practical assistance in the safety field.
Analysis and Experimental Tests of Potential New Mounting Techniques for Use in Vibration Testing of Electric Vehicle Battery Packs on Electromagnetic Exciters: Advantages and Disadvantages
Authors: Ślaski Grzegorz , Spadło Mikołaj , Marcinkiewicz Jacek , Konieczny Wojciech
Published: March 2024

The use of electric drives and energy storage devices in vehicles presents fresh challenges for system designers. Among these is addressing the susceptibility of battery packs to mechanical vibrations, necessitating vibration testing. In failure scenarios, like a battery fire, swiftly detaching the battery pack from the vibration platform is vital. It is also essential to ensure that the mounting system—fixture and fastener—effectively transfers vibration between the exciter and the battery pack. The article discusses the basic requirements for the fixture of specimens subjected to vibration testing and fastening it to a slip table of head expander, giving a better understanding of its role. It then presents the results of a theoretical analysis of the fixing forces and their laboratory testing using prototype customized fastening solutions with potential for use in vibration testing. The results of the conducted research and analyses demonstrate that non-standard mounting techniques have limited potential to replace screw mountings in vibration testing, particularly as fully universal techniques. However, the generated mounting forces, with potential resulting from the possibility of tailored implementation of the tested mounting techniques in the design of tables or head expanders, appropriately designed, justify further research work in this area.
State-of-All-the-Art and Prospective Hydrogel-Based Transdermal Drug Delivery Systems
Authors: Alex Meera , Alsawaftah Nour M. , Husseini Ghaleb A.
Published: March 2024

Over the past few decades, notable advancements have been made in the field of transdermal drug delivery systems (TDDSs), presenting a promising alternative to conventional oral drug administration. This comprehensive review aims to enhance understanding of this method by examining various transdermal techniques, the skin’s role as a barrier to TDDS, factors affecting skin diffusion, and current challenges in TDDSs. The primary focus of this analysis centers on TDDSs utilizing hydrogels. A thorough exploration of hydrogel fundamentals, encompassing structure, properties, and synthesis, is provided to underscore the importance of hydrogels as carriers in transdermal drug delivery. The concluding section delves into strategies for hydrogel-based drug delivery, addressing challenges and exploring future directions.
Characteristics of the Colorectal Cancer Microenvironment—Role in Cancer Progression and Therapeutic Possibilities
Authors: Pieniądz Paulina , Pięt Mateusz , Paduch Roman
Published: March 2024

Colorectal cancer (CRC) is one of the most common and deadliest cancers worldwide. According to the GLOBOCAN (WHO) report in 2020, nearly 2 million patients were diagnosed globally. Despite the advances in cancer diagnosis and therapy, CRC remains a global challenge. Recently, attention has been paid to the tumor microenvironment (TME), which constitutes a significant part of the tumor and mainly includes various immune cells, fibroblasts, vascular cells, and extracellular elements, such as the extracellular matrix (ECM). Many components of the stroma initially exert an anti-tumor effect, but over time, they undergo functional transformation into elements that promote tumor growth. As a result, conditions conducive to further cancer development, invasion into local tissues, and distant metastasis arise. The microenvironment of colorectal cancer (CRC) may be an important direction in the search for therapeutic targets, but it requires further understanding. The main purpose of our review is to explain the role of the complex CRC microenvironment in the progression of this cancer and highlight the potential of targeted therapy directed at the TME. Therefore, continued research into its components and typical biomarkers is necessary to improve therapy and enhance the quality of life for patients.
Numerical Simulation of Tunnel Face Support Pressure in Layered Soft Ground
Authors: Xiao Bihan , Li Xibing , Huang Linqi
Published: March 2024

In shield construction, the limit support pressure of the tunnel face has an important influence on ground settlement and construction safety. In this study, MIDAS GTS NX software was used to conduct a series of three-dimensional finite element simulations to investigate variations in excavation face support pressure under different layered ground conditions. By changing the shear strength parameters of the top or bottom layers, the influence of composite layers with different formation boundaries on the support pressure of the excavation face was studied. It was observed that when the formation boundary is placed above the axis, the support pressure of the excavation face is more sensitive to a change in the parameters in the lower part of the formation than in the upper part. Conversely, when the formation boundary lies below the axis, this sensitivity becomes reversed. Additionally, we derived a robust and accurate equation to estimate the limiting face support pressure in layered soft ground based on numerical modeling.
Research on Large Language Model for Coal Mine Equipment Maintenance Based on Multi-Source Text
Authors: Cao Xiangang , Xu Wangtao , Zhao Jiangbin , Duan Yong , Yang Xin
Published: March 2024

The efficient management and utilization of coal mine equipment maintenance knowledge is an indispensable foundation for advancing the establishment of intelligent mines. This knowledge has problems such as scattered, low sharing, and insufficient management, which restricts the development of coal mine intelligence. For the above-mentioned problems, a large language model for the maintenance of coal mine equipment based on multi-source text (XCoalChat) was proposed to better manage and utilize the existing massive knowledge of coal mine equipment maintenance. The dataset of coal mine equipment maintenance based on ReliableCEMK-Self-Instruction was constructed to obtain a wide and diverse amount of knowledge through sample generation. Aiming at the illusory problem of the large language model, a knowledge graph enhancement method based on the “Coal Mine Equipment Maintenance System—Full Life Cycle—Specification” was proposed to improve the knowledge density. A triple-LoRA fine-tuning mechanism and DPO direct preference optimization method were introduced into the top of the baseline model, which guarantees that XCoalChat can handle multiple Q&A and maintenance decision analysis tasks with limited computing power. Compared with ChatGLM, Bloom, and LLama, the comprehensive assessment of XCoalChat was performed by experiments including coal mine dialog consulting, coal mine professional consulting, and maintenance decision analysis. The results showed that XCoalChat achieved the best response accuracy in professional consulting and maintenance decision analysis; XCoalChat also took the least reasoning time on average. XCoalChat outperformed other mainstream large language models, which verify that XCoalChat is an effective large language model in the field of coal mine equipment maintenance.
Neuromuscular Response Disparities in Non-Professional Athletes during Side-Cutting: Exploring Sex Differences through Electromyographic Analysis
Authors: Feria-Madueño Adrián , Parraca Jose A. , Batalha Nuno , Sañudo Borja
Published: March 2024

This study aims to fill a knowledge gap by investigating electromyographic disparities in anterior and posterior muscle activation and coactivation ratios among non-professional men and women during side-cuttings. A cohort of 162 non-professional athletes participated in directional change maneuvers. Electromyographic assessments focused on coactivation ratios during the initial 50, 100, 150, and 200 ms of contraction, analyzing thigh muscle activations and exploring sex-based differences. Findings revealed higher quadriceps than hamstring muscle activation during directional changes, emphasizing the pivotal role of timing and coactivation ratios. Although the coactivation ratio, indicative of protective muscle control, approached 1 in all directional changes, 40% of subjects exhibited ratios below 0.8, suggesting an elevated injury risk. During open side-cutting at 30°, no significant sex differences were observed in anterior and posterior thigh muscle activation. However, in explosive ratios, women outperformed men, potentially attributable to uncontrolled motor unit recruitment. In open side-cutting at 45° and closed side-cutting at 45°, women displayed significantly higher H/Q ratios, indicating a nuanced sex-specific response. The study underscores the importance of an innovative coactivation ratio approach, revealing its early association with injury risk. Although anterior thigh muscle activation generally exceeded posterior, women exhibited poorer coactivation, potentially heightening knee injury risks during directional changes. This research contributes valuable insights into neuromuscular responses among non-professional athletes, particularly within the context of sex-specific differences.
A Multi-Scale Attention Fusion Network for Retinal Vessel Segmentation
Authors: Wang Shubin , Chen Yuanyuan , Yi Zhang
Published: March 2024

The structure and function of retinal vessels play a crucial role in diagnosing and treating various ocular and systemic diseases. Therefore, the accurate segmentation of retinal vessels is of paramount importance to assist a clinical diagnosis. U-Net has been highly praised for its outstanding performance in the field of medical image segmentation. However, with the increase in network depth, multiple pooling operations may lead to the problem of crucial information loss. Additionally, handling the insufficient processing of local context features caused by skip connections can affect the accurate segmentation of retinal vessels. To address these problems, we proposed a novel model for retinal vessel segmentation. The proposed model is implemented based on the U-Net architecture, with the addition of two blocks, namely, an MsFE block and MsAF block, between the encoder and decoder at each layer of the U-Net backbone. The MsFE block extracts low-level features from different scales, while the MsAF block performs feature fusion across various scales. Finally, the output of the MsAF block replaces the skip connection in the U-Net backbone. Experimental evaluations on the DRIVE dataset, CHASE_DB1 dataset, and STARE dataset demonstrated that MsAF-UNet exhibited excellent segmentation performance compared with the state-of-the-art methods.
Analysis of Cryptographic Algorithms to Improve Cybersecurity in the Industrial Electrical Sector
Authors: Alonso Francisco , Samaniego Benjamín , Farias Gonzalo , Dormido-Canto Sebastián
Published: March 2024

This article provides a general overview of the communication protocols used in the IEC61850 standard for the automation of electrical substations. Specifically, it examines the GOOSE and R-GOOSE protocols, which are used for exchanging various types of information. The article then presents real cases of cyber attacks on the industrial sector, highlighting the importance of addressing cybersecurity in the IEC61850 standard. The text presents security drawbacks of the communication protocols mentioned earlier and briefly explains two algorithms defined in the IEC61850 standard to address them. However, the authors suggest that having only a couple of algorithms may not be sufficient to ensure digital security in substations. This article presents a study on the cryptographic algorithms ChaCha20 and Poly1305. The purpose of the study is to experimentally verify their adaptation to the strict time requirements that GOOSE must meet for their operation. These algorithms can operate independently or in combination, creating an Authenticated Encryption with Associated Data (AEAD) algorithm. Both algorithms were thoroughly reviewed and tested using GOOSE and R-GOOSE frames generated by the S-GoSV software. The computational time required was also observed. The frames were analysed using the Wireshark software. It was concluded that the algorithms are suitable for the communication requirements of electrical substations and can be used as an alternative to the cryptographic algorithms proposed under the IEC61850 standard.
Drive-by Bridge Damage Detection Using Continuous Wavelet Transform
Authors: Demirlioglu Kultigin , Erduran Emrah
Published: March 2024

Bridges serve as vital engineering structures crafted to facilitate secure and effective transportation networks. Throughout their life-cycle, they withstand various factors, including diverse environmental conditions, natural hazards, and substantial loads. Recent bridge failures underscore the significant risks posed to the structural integrity of bridges. Damage detection techniques, being core components of structural health monitoring, play a crucial role in objectively assessing bridge conditions. This article introduces a novel framework for identifying damage in bridges utilizing continuous wavelet analysis of accelerations recorded using two sensors mounted on a vehicle traversing the bridge. The proposed method leverages changes in the static response of the bridge, which has proven to be more sensitive to damage than its dynamic counterpart. By doing so, the method eliminates the reliance on modal parameters for damage identification, addressing a significant challenge in the field. The proposed framework also addresses key challenges encountered by drive-by monitoring methods. It mitigates the adverse effects of road roughness by utilizing residual accelerations and efficiently detects and locates damage even in the absence of corresponding data from an undamaged bridge. Numerical investigations demonstrate the robustness of the proposed method against various parameters, including damage location and extent, vehicle speeds, road roughness levels, different boundary conditions, and multi-damage scenarios.
An Unsupervised Learning Method for Suppressing Ground Roll in Deep Pre-Stack Seismic Data Based on Wavelet Prior Information for Deep Learning in Seismic Data
Authors: Xia Jiarui , Dai Yongshou
Published: March 2024

Ground roll noise suppression is a crucial step in processing deep pre-stack seismic data. Recently, supervised deep learning methods have gained popularity in this field due to their ability to adaptively learn and extract powerful features. However, these methods rely on a large amount of clean seismic records without ground roll noise as reference labels. Unfortunately, generating high-quality and realistic clean seismic records for training remains a challenge. To tackle this problem, an unsupervised learning method called WPI-SD (wavelet prior information for deep learning in seismic data) is proposed for ground roll noise suppression in deep pre-stack seismic data. This approach takes into account the distinct temporal, lateral, and frequency characteristics that differentiate ground roll noise from real reflected waves in deep pre-stack seismic records. By designing a ground roll suppression loss function, the deep learning network can learn the specific distribution characteristics of real reflected waves within seismic records containing ground roll noise, even without labeled data. This enables the extraction of effective reflection signals and subsequent suppression of ground roll noise. Applied to actual seismic data processing, this method effectively mitigates ground roll noise while preserving valuable reflection signals, proving its practical significance.
Analysis of the Post-Cyclonic Physical Flood Susceptibility and Changes of Mangrove Forest Area Using Multi-Criteria Decision-Making Process and Geospatial Analysis in Indian Sundarbans
Authors: Mondal Biraj Kanti , Mahata Sanjib , Basu Tanmoy , Das Rima , Patra Rajib , Abdelrahman Kamal , Fnais Mohammed S. , Praharaj Sarbeswar
Published: March 2024

Tropical cyclones, one of the most extreme and destructive meteorological incidents, cause extensive damage to lives and livelihoods worldwide. This study utilized remotely sensed data along with multi-criteria decision-making, geospatial techniques, and major cyclonic events Aila, Amphan, and Yaas to identify the changes in the vulnerability of cyclone-induced floods in the 19 community development blocks of Indian Sundarbans in the years 2009–2010, 2020–2021, and 2021–2022 (the post-cyclonic timespan). The Sundarbans are a distinctive bioclimatic region located in a characteristic geographical setting along the West Bengal and Bangladesh coasts. In this area, several cyclonic storms had an impact between 2009 and 2022. Using the variables NDVI, MNDWI, NDMI, NDBI, BSI, and NDTI, Landsat 8 Operational Land Imager, Thermal Infrared Sensor, Resourcesat LISS-III, and AWiFS data were primarily utilized to map the cyclonic flood-effective zones in the research area. The findings indicated that the coastline, which was most impacted by tropical storms, has significant physical susceptibility to floods, as determined by the AHP-weighted overlay analysis. Significant positive relationships (p < 0.05, n = 19 administrative units) were observed between mangrove damage, NDFI, and physical flood susceptibility indicators. Mangrove damage increased with an increase in the flood index, and vice versa. To mitigate the consequences and impacts of the vulnerability of cyclonic events, subsequent flood occurrences, and mangrove damage in the Sundarbans, a ground-level implementation of disaster management plans proposed by the associated state government, integrated measures of cyclone forecasting, mangrove plantation, coastal conservation, flood preparedness, mitigation, and management by the Sundarban Development Board are appreciably recommended.
A Fuzzy-Based Analysis of Air Particle Pollution Data: An Index IMC for Magnetic Biomonitoring
Authors: Chaparro Mauro A. E. , Chaparro Marcos A. E. , Molinari Daniela A.
Published: March 2024

Airborne magnetic particles may be harmful because of their composition, morphology, and association with potentially toxic elements that may be observed through relationships between magnetic parameters and pollution indices, such as the Tomlinson pollution load index (PLI). We present a fuzzy-based analysis of magnetic biomonitoring data from four Latin American cities, which allows us to construct a magnetic index of contamination (IMC). This IMC uses four magnetic parameters, i.e., magnetic susceptibility χ, saturation isothermal remanent magnetization SIRM, coercivity of remanence Hcr, and SIRM/χ, and proposes summarizing the information to assess an area based exclusively on magnetic parameters more easily. The fuzzy inference system membership functions are built from the standardization of the data to become independent of the values. The proposed IMC is calculated using the baseline values for each case study, similar to the PLI. The highest IMC values were obtained in sites close to industrial areas, and in contrast, the lowest ones were observed in residential areas far from avenues or highways. The linear regression model between modeled IMC and PLI data yielded robust correlations of R2 > 0.85. The IMC is proposed as a complementary tool for air particle pollution and is a cost-effective magnetic approach for monitoring areas.
Some Remarks on Smooth Mappings of Hilbert and Banach Spaces and Their Local Convexity Property
Authors: Prykarpatskyy Yarema A. , Pukach Petro Ya. , Vovk Myroslava I. , Greguš Michal
Published: March 2024

We analyze smooth nonlinear mappings for Hilbert and Banach spaces that carry small balls to convex sets, provided that the radii of the balls are small enough. We focus on the study of new and mildly sufficient conditions for the nonlinear mapping of Hilbert and Banach spaces to be locally convex, and address a suitably reformulated local convexity problem analyzed within the Leray–Schauder homotopy method approach for Hilbert spaces, and within the Lipschitz smoothness condition for both Hilbert and Banach spaces. Some of the results presented in this work prove to be interesting and novel, even for finite-dimensional problems. Open problems related to the local convexity property for nonlinear mappings of Banach spaces are also formulated.
Numerical Simulation of Flows Using the Fourier Pseudospectral Method and the Immersed Boundary Method
Authors: Albuquerque Laura Augusta Vasconcelos de , Villela Mariana Fernandes dos Santos , Mariano Felipe Pamplona
Published: March 2024

The present work proposes the application of a computational methodology based on the coupling of the Fourier Pseudospectral Method (FPSM) and the Immersed Boundary Method (IBM) for conducting flow simulations over slender airfoils. This methodology, termed IMERSPEC, leverages the benefits of both high accuracy and low computational cost inherent in pseudospectral methods, thanks to the utilization of the Fast Fourier Transform algorithm. IBM is employed to impose non-periodic boundary conditions in the Navier–Stokes equations, addressing the requirement of periodicity at boundaries for FPSM convergence and to accurately represent the immersed slender airfoil in the flow. The aerodynamic behavior of the analyzed profiles was assessed by calculating lift and drag coefficients, which were then compared with existing literature results. Consistently favorable outcomes were observed, particularly in flows at lower Reynolds numbers, demonstrating the effectiveness of the IMERSPEC methodology for simulating complex flows computationally. Additionally, weight functions, fundamental to IBM, are employed flexibly for aerodynamic force calculations. Specifically, within the same simulation, a Cubic function is utilized for drag calculation while a Hat function is employed for lift calculation, yielding results more closely aligned with the literature’s findings. This approach offers an alternative to previously proposed methods for IBM implementation.
Two Different Analytical Approaches for Solving the Pantograph Delay Equation with Variable Coefficient of Exponential Order
Authors: Alrebdi Reem , Al-Jeaid Hind K.
Published: March 2024

The pantograph equation is a basic model in the field of delay differential equations. This paper deals with an extended version of the pantograph delay equation by incorporating a variable coefficient of exponential order. At specific values of the involved parameters, the exact solution is obtained by applying the regular Maclaurin series expansion (MSE). A second approach is also applied on the current model based on a hybrid method combining the Laplace transform (LT) and the Adomian decomposition method (ADM) denoted as (LTADM). Although the MSE derives the exact solution in a straightforward manner, the LTADM determines the solution in a closed series form which is theoretically proved for convergence. Further, the accuracy of such a closed-form solution is examined through various comparisons with the exact solution. For validation, the residual errors are calculated and displayed in graphs. The results show that the solution obtained utilizing the LTADM is in full agreement with the exact solution using only a few terms of the closed-form series solution. Moreover, it is found that the residual errors tend to zero, which reflects the effectiveness of the LTADM. The present approach may merit further extension by including other types of linear delay differential equations with variable coefficients.
The Restricted Edge-Connectivity of Strong Product Graphs
Authors: Ye Hazhe , Tian Yingzhi
Published: March 2024

The restricted edge-connectivity of a connected graph G, denoted by λ′(G), if it exists, is the minimum cardinality of a set of edges whose deletion makes G disconnected, and each component has at least two vertices. It was proved that λ′(G) exists if and only if G has at least four vertices and G is not a star. In this case, a graph G is called maximally restricted edge-connected if λ′(G)=ξ(G), and a graph G is called super restricted edge-connected if each minimum restricted edge-cut isolates an edge of G. The strong product of graphs G and H, denoted by G⊠H, is the graph with the vertex set V(G)×V(H) and the edge set {(x1,y1)(x2,y2)|x1=x2 and y1y2∈E(H); or y1=y2 and x1x2∈E(G); or x1x2∈E(G) and y1y2∈E(H)}. In this paper, we determine, for any nontrivial connected graph G, the restricted edge-connectivity of G⊠Pn, G⊠Cn and G⊠Kn, where Pn, Cn and Kn are the path, cycle and complete graph of order n, respectively. As corollaries, we give sufficient conditions for these strong product graphs G⊠Pn, G⊠Cn and G⊠Kn to be maximally restricted edge-connected and super restricted edge-connected.
Effect of Transarterial Chemotherapy on the Structure and Function of Gut Microbiota in New Zealand White Rabbits
Authors: Bai Liuhui , Yan Xiangdong , Qi Ping , Lv Jin , Song Xiaojing , Zhang Lei
Published: March 2024

The gut microbiota (GM) are closely related to hepatocellular carcinoma (HCC) occurrence and development. Furthermore, patients with HCC who have received transcatheter arterial chemoembolization (TACE) treatment often experience adverse gastrointestinal reactions, which may be related to changes in the GM caused by the chemotherapeutic drugs used in TACE. Therefore, we conducted animal experiments to investigate these changes. We analyzed changes in the GM of New Zealand white rabbits treated with hepatic arterial chemotherapy by measuring the levels of serological and colonic tissue markers. Simultaneously, we evaluated the correlation between the GM and these markers to explore the mechanism by which chemotherapy affects the GM. Following transarterial chemotherapy with epirubicin, the Firmicutes abundance decreased, whereas that of Proteobacteria increased. The relative abundance of beneficial bacteria, such as Muribaculaceae, Enterococcus, Ruminococcus, and Clostridia, decreased in the experimental group compared with those in the control group. However, the relative abundance of harmful bacteria, such as Bacteroides and Escherichia (Shigella), was higher in the experimental group than in the control group. Following chemotherapy, the GM of rabbits showed a dynamic change over time, first aggravating and then subsiding. The changes were most notable on the fourth day after surgery and recovered slightly on the seventh day. The changes in the host’s GM before and after arterial chemotherapy are evident. Hepatic arterial chemotherapy induces dysbiosis of the intestinal microbiota, disrupts intestinal barrier function, damages the integrity of the intestinal mucosa, increases intestinal permeability, facilitates excessive passage of harmful substances through the gut–liver axis communication between the liver and intestine, and triggers activation of inflammatory pathways such as LPS-TLR-4-pSTAT3, ultimately leading to an inflammatory response. This study provides a theoretical basis for combining TACE with targeted GM intervention to treat HCC and reduce adverse gastrointestinal reactions.
Hemodynamic Melody of Postnatal Cardiac and Pulmonary Development in Children with Congenital Heart Diseases
Authors: Zheng Sixie , Ye Lincai
Published: March 2024

Hemodynamics is the eternal theme of the circulatory system. Abnormal hemodynamics and cardiac and pulmonary development intertwine to form the most important features of children with congenital heart diseases (CHDs), thus determining these children’s long-term quality of life. Here, we review the varieties of hemodynamic abnormalities that exist in children with CHDs, the recently developed neonatal rodent models of CHDs, and the inspirations these models have brought us in the areas of cardiomyocyte proliferation and maturation, as well as in alveolar development. Furthermore, current limitations, future directions, and clinical decision making based on these inspirations are highlighted. Understanding how CHD-associated hemodynamic scenarios shape postnatal heart and lung development may provide a novel path to improving the long-term quality of life of children with CHDs, transplantation of stem cell-derived cardiomyocytes, and cardiac regeneration.
Fish Oil Improves Offspring Metabolic Health of Paternal Obese Mice by Targeting Adipose Tissue
Authors: Pérez Lugo Mariana I. , Salas Melanie L. , Shrestha Akriti , Ramalingam Latha
Published: March 2024

Obesity is a fast-growing epidemic affecting more than 40% of the US population and leads to co-morbidities such as type 2 diabetes and cancer. More importantly, there is a rapid increase in childhood obesity associated with obesity in parents. Further, offspring are encoded with approximately half of their genetic information from the paternal side. Obesity in fathers at the preconceptional period likely influences the intergenerational development of obesity. This study focuses on the role of fish oil supplementation as a non-pharmacological intervention in fathers and its impact on childhood obesity using animal models. Male mice were fed a low-fat diet or high-fat diet with or without fish oil for 10 weeks and mated with female mice on a chow diet. Offspring were then continued on a chow diet until 8 or 16 weeks. In vivo insulin tolerance was tested to assess the metabolic health of offspring. Further, adipose tissue was harvested upon sacrifice, and genetic markers of inflammation and lipid metabolism in the tissue were analyzed. Offspring of males supplemented with fish oil showed lower body weight, improved insulin tolerance, and altered inflammatory markers. Markers of fatty acid oxidation were higher, while markers of fatty acid synthesis were lower in offspring of fathers fed fish oil. This supports fish oil as an accessible intervention to improve offspring metabolic health.
Microbiota Metabolite Profiles and Dietary Intake in Older Individuals with Insomnia of Short vs. Normal Sleep Duration
Authors: Even Carmel , Magzal Faiga , Shochat Tamar , Haimov Iris , Agmon Maayan , Tamir Snait
Published: March 2024

Recent evidence suggests that the gut microbiota plays a role in insomnia pathogenesis. This study compared the dietary habits and microbiota metabolites of older adults with insomnia of short vs. normal sleep duration (ISSD and INSD, respectively). Data collection included sleep assessment through actigraphy, dietary analysis using the Food Frequency Questionnaire, and metabolomic profiling of stool samples. The results show that ISSD individuals had higher body mass index and a greater prevalence of hypertension. Significant dietary differences were observed, with the normal sleep group consuming more kilocalories per day and specific aromatic amino acids (AAAs) phenylalanine and tyrosine and branch-chain amino acid (BCAA) valine per protein content than the short sleep group. Moreover, metabolomic analysis identified elevated levels of the eight microbiota metabolites, benzophenone, pyrogallol, 5-aminopental, butyl acrylate, kojic acid, deoxycholic acid (DCA), trans-anethole, and 5-carboxyvanillic acid, in the short compared to the normal sleep group. The study contributes to the understanding of the potential role of dietary and microbial factors in insomnia, particularly in the context of sleep duration, and opens avenues for targeted dietary interventions and gut microbiota modulation as potential therapeutic approaches for treating insomnia.