bluuebunny/crossref_metadata_2025 huggingface dataset:
Genome Sequencing Providing Molecular Evidence of Tetrapolar Mating System and Heterothallic Life Cycle for Edible and Medicinal Mushroom Polyporus umbellatus Fr.
Authors: Li Shoujian , Liu Youyan , Liu Liu , Li Bing , Guo Shunxing
Published: December 2024

Polyporus umbellatus is a species whose sclerotia have been extensively employed in traditional Chinese medicine, which has diuretic, antitumor, anticancer, and immune system enhancement properties. However, prolonged asexual reproduction has resulted in significant homogenization and degeneration of seed sclerotia. In contrast, sexual reproduction has emerged as an effective strategy to address these challenges, with a distinct mating system serving as the foundation for the implementation of sexual breeding. This study presents the first sequencing and assembly of the genome of P. umbellatus, thereby providing an opportunity to investigate the mating system at the genomic level. Based on the annotated mating-type loci within the genome, monokaryotic offspring exhibiting different mating-types were identified. Through the integration of traditional mating tests, the tetrapolar mating system of P. umbellatus was distinctly elucidated. The resequencing of monokaryotic strains with four different mating-types, along with comparative analyses of mating-type loci, revealed the HD1 and HD2 (HD, homeodomain) genes determined the mating A types, and the PR4, PR5, and PR6 (PR, pheromone receptor) genes determined the mating B types. Meanwhile, this study offers a successful case study in the molecular investigation of mating systems. Additionally, the number of sterigma and basidiospores on each basidium was examined using scanning electron microscopy, while the nuclei of basidiospores and basidia at various developmental stages were analyzed through DAPI staining. This research clarifies the heterothallic life cycle of P. umbellatus. The findings of this study are expected to facilitate advancements in genetic research, breeding development, strain improvement, and the industry of P. umbellatus.
Endophytic Fungi of Calea pinnatifida (Asteraceae): Dereplication of Crude Extracts, Antimicrobial Properties, and Identification of New Tetronic Acid Derivative Produced by Hypomontagnella barbarensis
Authors: Barna Bianca , Caldas Lhaís Araújo , Monteiro Jackson , dos Santos Augusto Leonardo , Pascon Renata Castiglioni , Vallim Marcelo Afonso , Ferreira Marcelo José Pena , Gonçalves Sarah Santos , dos Santos Glaucia Queiroz , Rodrigues Anderson Messias , de Carvalho Jamile Ambrósio , de Vasconcellos Suzan Pantaroto , Sartorelli Patricia
Published: December 2024

Endophytic fungi are increasingly being recognized for their diverse metabolites that may exhibit antimicrobial properties. In our study, we isolated seven endophytic fungal strains from Calea pinnatifida, which were identified as Hypomontagnella barbarensis, Neopestalotiopsis clavispora, Nigrospora sacchari-officinarum, Annulohypoxylon moriforme, Colletotrichum siamense, and Colletotrichum karstii (with two isolates from the same species). Furthermore, the antimicrobial activity of the extracts was assessed, revealing that the extract from Hypomontagnella barbarensis demonstrated activity against Staphylococcus aureus. Further investigation of secondary metabolites, employing UHPLC-HR-ESI-MS/MS in combination with molecular networking, facilitated annotation of the nine compounds. Of these, five were identified based on matches with the GNPS spectral library, and four were predicted based on the molecular network. Notably, from the extract of Hypomontagnella barbarensis, two pairs of diastereoisomeric acyl-tetronic acid derivatives were isolated and characterized using MS and NMR spectroscopy. This study highlights the potential of endophytic fungi as a valuable source of novel antimicrobial agents.
How Does Self-Construal Influence Green Product Purchase in the Digital Era? The Moderating Role of Advertising Appeal
Authors: Su Peng , Yao Qi , Wu Xian
Published: December 2024

Advertising has become an important strategy for many enterprises to nudge consumers to buy green products and achieve sustainable development. In the context of cultural diversity, the discussion on the influence of consumers’ cultural belief variables on the effectiveness of advertising persuasion appears conducive to promoting green consumption. Through two situational experiments based on information processing theory, this study verified the impact and mechanism of the interaction between self-construal and advertising appeals on green product purchase intention, revealing the mediating role of information processing fluency (Experiment 2). The results indicate that emotional (rational)-appeal advertisements can strengthen independent (interdependent) self-constructed consumers’ stronger purchase intentions for green products (Experiment 1). Moreover, the occurrence of this effect is mediated by information processing fluency (Experiment 2). Not only do the conclusions of this research enrich the literature in the field of self-construal and advertising appeal preference but they also have managerial implications for improving green marketing performance by using advertising appeal and targeting consumers’ cultural psychological characteristics.
Territorial Brands for Rural Development Strategies in Protected Natural Spaces: A Social Demand Analysis
Authors: Albaladejo-García José A. , Martínez-García Gonzalo , Martínez-Paz José M.
Published: December 2024

The economic decline of some rural areas is leading to the development of strategies to enhance the value of local economies. This is particularly important in protected natural spaces, where the aim is to encourage the provision of ecosystem services and strengthen commitment to sustainable development and economic growth. One of the rural development strategies with a growing interest in promoting the sustainability of rural areas in protected natural spaces is the use of territorial brands. The objective of this work is to analyse the social demand for territorial-branded products in protected natural spaces. The territorial brand of Sierra Espuña Regional Park (southeastern Spain) was selected as a pragmatic case, with the aim of promoting the production and consumption of sustainable local products. To this end, a contingent valuation survey of consumers was carried out to study the demand for honey, one of the most characteristic products of this territorial brand. The results demonstrate the high social demand for honey under the Sierra Espuña Territorial Brand, with an average surcharge of almost thirty percent compared to the conventional product, and a positive influence of the perception of supporting ecosystem services on this social demand. These results provide an empirical basis for the integration and promotion of production and marketing strategies with territorial brands, in the interests of rural development from and for the territory.
Spatiotemporal Dynamics of Land Use Carbon Balance and Its Response to Urbanization: A Case of the Yangtze River Economic Belt
Authors: Jiang Xinling , Chu Xu , Yang Xinyu , Jiang Ping , Zhu Jing’an , Cai Zhongyao , Yu Siqi
Published: December 2024

Urbanization and its impact on land use and land cover change are key drivers of global carbon balance shifts. Understanding the spatiotemporal evolution of carbon balance in relation to urbanization helps optimize regional planning and sustainable development. This study develops a city-level land use carbon balance system to quantify the spatiotemporal dynamics of land use carbon balance across 130 cities in the Yangtze River Economic Belt (YREB). Moran’s Index is applied to assess the spatial correlation of carbon balance, and the Environmental Kuznets Curve (EKC) is used to explore the relationship between urbanization levels and net carbon emissions. The results show the following: (1) From 2005 to 2021, land use carbon absorption in YREB cities remained relatively stable, whereas carbon emissions increased. Net carbon emissions increased by 574.61, 456.16, and 1163.60 Mt C in the upper, middle, and lower reaches, respectively. Nearly 98% of the cities exhibited a carbon balance index greater than 1, indicating a carbon deficit. Carbon emission intensity displayed a decreasing trend, with the most significant reductions observed in the middle reaches. (2) Land use carbon balance exhibits significant positive spatial correlation, with cities in the northeastern lower reaches and southwestern upper reaches forming “high–high” and “low–low” net carbon emission clusters. (3) Urbanization and per capita net carbon emissions followed an inverted “N”-shaped curve, with turning points at around 30% and 85% urbanization. This study provides insights into optimizing land use carbon management amidst urban growth in the YREB.
Intelligent Recommendation of Multi-Scale Response Strategies for Land Drought Events
Authors: He Lei , Lei Yuheng , Yang Yizhuo , Liu Bin , Li Yuxia , Zhao Youcai , Tang Dan
Published: December 2024

Currently, land drought events have become a frequent and serious global disaster. How to address these droughts has become a major issue for researchers. Traditional response strategies for land drought events have been determined by experts based on the severity levels of the events. However, these methods do not account for temporal variations or the specific risks of different areas. As a result, they overlooked the importance of spatio-temporal multi-scale strategies. This research proposes a multi-scale response strategy recommendation model for land drought events. The model integrates characteristics of drought-causing factors, disaster-prone environments, and hazard-bearing bodies using case-based reasoning (CBR). Additionally, the analytic hierarchy process (AHP) and entropy weighting methods (EWMs) are introduced to assign weights to the feature attributes. A case retrieval algorithm is developed based on the similarity of these attributes and the structural similarities of drought cases. The research further classifies emergency strategies into long-term and short-term approaches. Each approach has a corresponding correction algorithm. For short-term strategies, a correction algorithm based on differential evolutions is applied. For long-term strategies, a correction algorithm based on drought risk assessment is developed. The algorithm considers factors such as drought risk, vulnerability, and exposure. It facilitates multi-scale decision-making for drought events. The candidate case obtained using the correction algorithm shows an overall attribute similarity of 94.7% with the real case. The emergency response levels match between the two cases. However, the funding required in the candidate case is CNY 327 million less than the actual expenditure.
Ultrasound-Guided Analgesia in Cardiac and Breast Surgeries: A Cadaveric Comparison of SPIP Block with Single and Double Injections vs. DPIP Block
Authors: Pirri Carmelo , Torre Debora Emanuela , Behr Astrid Ursula , Macchi Veronica , Porzionato Andrea , De Caro Raffaele , Stecco Carla
Published: December 2024

The evolution of regional anesthesia techniques has markedly influenced the management of postoperative pain, particularly in thoracic surgery. As part of a multimodal analgesic approach, fascial plane blocks have gained prominence due to their efficacy in providing targeted analgesia with minimal systemic side effects. Among these, the superficial intercostal plane (SPIP) block and deep parasternal intercostal plane (DPIP) block are of notable interest. The aim of this study was to investigate the dye spread to the anterior chest wall space and its spread pathway through anatomical morphometric analyses on cadavers for single-injection and double-injection SPIP blocks versus DPIP blocks. In both qualitative and quantitative evaluations, the single-injection SPIP block with 10 mL of dye demonstrated a broader and more extensive spread compared to the double-injection SPIP block, which used 5 mL of dye per injection site (p < 0.05), and the DPIP block with 10 mL of dye (p < 0.05). All the blocks had a positive correlation between the distances from the sternum border and the area of dye spread, suggesting that the crucial role of volume in fascial blocks is that it significantly affects the opening of the fascial compartment, enabling optimal spread of the anesthetic. Adequate volume facilitates proper spread and diffusion across the fascial plane, ensuring more comprehensive fascia coverage and thus enhancing the block’s effectiveness. Finally, precise volume management is key to maximizing both efficacy and safety.
Sustainability in Construction: Geopolymerized Coating Bricks Made with Ceramic Waste
Authors: Correa-Jaramillo Ramiro , Hernández-Olivares Francisco
Published: December 2024

Brick is a common construction material but often ends up as waste due to suboptimal quality. In Ecuador, artisanal brick production results in inconsistent properties for construction. This research aims to repurpose discarded bricks through geopolymerization to create a sustainable building material. The geopolymerization process was carried out using sodium hydroxide as the alkaline activator, followed by structural and chemical characterization, including X-Ray Diffraction (XRD) and X-Ray Fluorescence (XRF) to determine composition and crystalline phases. The recycled material underwent extensive testing of its physical and mechanical properties, such as density, porosity, and compressive strength. Its application as facade cladding for housing was also analyzed. The results showed that the geopolymerized material significantly reduced heating and cooling demand when used in building envelopes. A case study in Loja demonstrated a notable decrease in heating and cooling degree days, contributing to improved thermal comfort. This research highlights the potential for recycled bricks in sustainable construction, presenting viable alternatives to conventional construction materials and advancing knowledge in eco-friendly building practices.
Failure and Degradation Mechanisms of Steel Pipelines: Analysis and Development of Effective Preventive Strategies
Authors: Kowalczyk Marcin , Andruszko Jakub , Stefanek Paweł , Mazur Robert
Published: December 2024

The increasing challenges related to the reliability and durability of steel pipeline infrastructure necessitate a detailed understanding of degradation and failure mechanisms. This study focuses on selective corrosion and erosion as critical factors, analyzing their impact on pipeline integrity using advanced methods, including macroscopic analysis, corrosion testing, microscopic examination, tensile strength testing, and finite element method (FEM) modeling. Selective corrosion in the heat-affected zones (HAZs) of longitudinal welds was identified as the dominant degradation mechanism, with pit depths reaching up to 6 mm, leading to tensile strength reductions of 30%. FEM analysis showed that material loss exceeding 8 mm in weld areas under standard operating pressure (16 bar) induces critical stress levels, risking pipeline failure. Erosion was found to exacerbate selective corrosion, accelerating degradation in high-stress zones. Practical recommendations include the use of corrosion-resistant materials, such as duplex steels, and implementing integrated monitoring strategies combining non-destructive testing with FEM-based predictive modeling. These insights contribute to developing robust preventive measures to ensure the safety and longevity of pipeline infrastructure.
Improved Voltammetric Procedure for Chloride Determination in Highly Acidic Media
Authors: Maciąg Rafał , Hyk Wojciech , Ratajczyk Tomasz , Donten Mikołaj
Published: December 2024

Cyclic voltammetry (CV) can be applied as a reliable method for the determination of chloride ions in a range from several to a couple hundred (about 200) ppm. Since the standard potential of chloride ion/gaseous chlorine is 1.36 V vs. normal hydrogen electrode (NHE), the efficient oxidation of Cl− ion occurs at very positive electrode potentials, usually higher than +1.7 V vs. NHE. It is possible to observe this phenomenon only at noble-metal or inert carbon electrodes. Many other solutes, usually organic compounds, are often oxidized at this potential. This is the reason why the determination of Cl− content directly from an increase in the oxidation current is not reliable and could lead to overestimated values. However, gaseous chlorine, generated at a positive potential dissolve in the analyzed solution, could be reduced in the reverse scan of a cyclic voltammetric curve. Optimization of the experimental procedure using statistical tools enables the development of an improved method for the direct quantification of chloride ions in acid copper electroplating baths. Under the proposed experimental conditions, the calibration curve (Cl2 voltammetric reduction current vs. chloride ions concentration) is represented by the linear model for the concentration of chlorides ranging from 10 to 200 mg/dm3. The developed method for analyzing chloride ions in an acid sulfate electroplating copper bath has many unique properties. It is fast; the time of a single analysis is less than 20 min. In automatic mode, it can be repeated up to 50 times a day. The method does not require processing of the sample of the analyzed bath before measurement. As a result, no additional chemical reagents are used, and the test sample can be returned to the plating bath.
The Impact of an MDP-Containing Primer on the Properties of Zinc Oxide Networks Infiltrated with BisGMA-TEGDMA and UDMA-TEGDMA Polymers
Authors: Wellhäußer Benjamin , Saure Lena Marie , Schütt Fabian , Scherer Franziska , Wille Sebastian , Kern Matthias
Published: December 2024

This study was conducted to evaluate the material properties of polymer-infiltrated zinc oxide networks (PICN) and the effect of using a phosphate monomer-containing primer applied before polymer infiltration. A total of 148 ZnO-network (zinc oxide) specimens were produced: n = 74 were treated with a primer before polymer infiltration and light curing, while the remaining specimens were untreated. Each group was divided into two subgroups (n = 37) based on the infiltrating polymer: UDMA (aliphatic urethane-dimethacrylates)-TEGDMA (triethylene glycol-dimethacrylate) or BisGMA (bisphenol A-glycidyl-methacrylate)-TEGDMA. Additionally, n = 7 specimens of each polymer type were prepared for comparison. Then, biaxial flexural strength was measured before and after 150 days of water storage at 37 °C, including 37,500 thermal cycles (5 °C to 55 °C). The Vickers hardness, surface roughness, and water absorption at 37 °C were also tested. The initial biaxial flexural strength was reduced in the ZnO network specimens compared to in the pure polymers. Primer application improved the flexural strength, though the strength of BisGMA-TEGDMA significantly decreased after water storage. The ZnO network increased hardness, and the polymer-infiltrated networks showed higher roughness post-grinding and absorbed less water than the pure polymer groups. The ZnO networks did not improve the flexural strength over that of the pure polymers. However, the primer’s positive impact and the network’s long-term stability suggest potential if the network structure can be modified to contain thicker, more stable branches.
Development of a NC-Controlled GTAW-Based Wire Arc Additive Manufacturing System for Using Friction Stir Extrusion Recycled Wires
Authors: Carvalho Gustavo H. S. F. L. , Campatelli Gianni , Cota Bruno Silva , Campanella Davide , Di Lorenzo Rosa
Published: December 2024

This study investigates the feasibility of using friction stir extrusion (FSE) recycled aluminum wires as filler metals for gas tungsten arc welding (GTAW) and additive manufacturing applications. A NC-controlled GTAW feeding system was developed to enable the deposition of these recycled wires. The effect of cleaning the machining chips before the FSE process on the quality of the manufactured wires and the resulting welded beads was evaluated. Wires produced from uncleaned chips and cleaned chips were compared in terms of their external appearance, ductility, and the presence of porosity after the weld deposition. The results showed that cleaning the chips before the FSE process is crucial for obtaining more uniform wires with better ductility. Automatic GTAW deposition using cleaned wires resulted in significantly improved bead geometry, reduced external porosity, and overall better quality compared to uncleaned wires. However, both wire types exhibited internal porosity, with uncleaned wires showing the worst performance. The findings demonstrate the potential of using FSE recycled aluminum wires for welding and additive manufacturing while highlighting the importance of chip cleaning and the need for further optimization to minimize porosity in the deposited material.
Physics-Based Self-Supervised Grasp Pose Detection
Authors: Ruiz Jon Ander , Iriondo Ander , Lazkano Elena , Ansuategi Ander , Maurtua Iñaki
Published: December 2024

Current industrial robotic manipulators have made their lack of flexibility evident. The systems must know beforehand the piece and its position. To address this issue, contemporary approaches typically employ learning-based techniques, which rely on extensive amounts of data. To obtain vast data, an often sought tool is an extensive grasp dataset. This work introduces our Physics-Based Self-Supervised Grasp Pose Detection (PBSS-GPD) pipeline for model-based grasping point detection, which is useful for generating grasp pose datasets. Given a gripper-object pair, it samples grasping pose candidates using a modified version of GPD (implementing inner-grasps, CAD support…) and quantifies their quality using the MuJoCo physics engine and a grasp quality metric that takes into account the pose of the object over time. The system is optimized to run on CPU in headless-parallelized mode, with the option of running in a graphical interface or headless and storing videos of the process. The system has been validated obtaining grasping poses for a subset of Egad! objects using the Franka Panda two-finger gripper, compared with state-of-the-art grasp generation pipelines and tested in a real scenario. While our system achieves similar accuracy compared to a contemporary approach, 84% on the real-world validation, it has proven to be effective at generating grasps with good centering 18 times faster than the compared system.
Experimental Design and Simulation of a Fly-Cutting Plant for Academic Environment Practices
Authors: Ramírez-Jiménez Diego Fernando , Torres Valencia Cristian Alejandro
Published: December 2024

Test plants or laboratory prototypes are essential for developing training activities in engineering. In the field of automation and control, simulators or high-fidelity equipment models commonly used in industrial processes are necessary. These tools allow engineering trainees to gain experience working with devices similar to those they will encounter in their professional contexts. This paper presents the design and simulation of a fly-cutting plant for academic use. A 3D model was developed in SketchUp, incorporating features typical of industrial plants. The system’s simulation was carried out in MATLAB R2023b using mathematical modeling. The primary contribution of this work is the design of a low-cost, compact industrial prototype that includes a conveyor belt and a continuous cutting mechanism, enabling the understanding and operation of large-scale industrial processes. Performance tests were conducted using MATLAB, Simulink, and Code Composer Studio. Subsequently, operational and cutting tests were performed using classical control techniques. Additionally, the design features of the fly-cutting plant, which can be easily implemented for process control training activities, are detailed.
Online Algebraic Estimation of Parameters and Disturbances in Brushless DC Motors
Authors: Marcos-Andrade David , Beltran-Carbajal Francisco , Castelan-Perez Alexis , Rivas-Cambero Ivan , Hernández Jesús C.
Published: December 2024

Parameter identification in dynamical systems is a well-known problem with many applications in control design, system monitoring, and fault detection. As these systems are increasingly integrated into complex and demanding environments, challenges such as rapid response, uncertainty handling, and disturbance rejection must be addressed. This paper presents a real-time estimation technique for parameters and load torque in brushless DC (BLDC) motors. These electrical machines are extensively used in engineering applications and often operate under hard conditions. The proposed method is based on algebraic identification, known for its robust performance in both linear and nonlinear systems. In utilizing the mathematical model of a BLDC motor, a set of equations is derived to enable parameter estimation, assuming the availability of input and output measurements in open loop. Moreover, unknown load torque is estimated by approximating the disturbance over a short time window using Taylor series expansion polynomials. The theoretical contribution is analytically validated and is also verified through numerical evaluations revealing the effectiveness of the proposed technique for real-time parameter and disturbance estimation in BLDC motors over other important techniques. Additionally, to address potential peaks in the estimation process, a modification involving an exponent is introduced to mitigate these issues.
A Novel FS-GAN-Based Anomaly Detection Approach for Smart Manufacturing
Authors: Kim Tae-yong , Lee Jieun , Gong Seokhyun , Lim Jaehoon , Kim Dowan , Jeong Jongpil
Published: December 2024

In this study, we present the few-shot generative adversarial network (FS-GAN) model, which integrates few-shot learning and a generative adversarial network with an unsupervised learning approach (AnoGAN) to address the challenges of anomaly detection in smart-factory manufacturing environments. Manufacturing processes often encounter malfunctions or defective parts that disrupt production and compromise product quality. However, collecting and labeling sufficient data to detect anomalies is time-intensive, and abnormal data are rare, leading to data imbalances. The FS-GAN model leverages few-shot learning to enable accurate predictions with minimal data and uses the generative capabilities of AnoGAN to mitigate the scarcity of abnormal data by generating synthetic normal data. Experimental results demonstrate that FS-GAN outperforms existing models in terms of accuracy and learning speed, even with limited datasets, effectively addressing the data imbalance problem inherent in manufacturing. The model reduces dependency on extensive data collection and labeling efforts, making it suitable for real-world applications. Through reliable and efficient anomaly detection, FS-GAN contributes to production reliability, product quality, and operational efficiency in smart factories. This study highlights the potential of FS-GAN to provide a cost-effective and high-performance solution to the challenges of anomaly detection in the manufacturing industry.
Probabilistic Automated Model Compression via Representation Mutual Information Optimization
Authors: Nie Wenjie , Zhang Shengchuan , Zheng Xiawu
Published: December 2024

Deep neural networks, despite their remarkable success in computer vision tasks, often face deployment challenges due to high computational demands and memory usage. Addressing this, we introduce a probabilistic framework for automated model compression (Prob-AMC) that optimizes pruning, quantization, and knowledge distillation simultaneously using information theory. Our approach is grounded in maximizing the mutual information between the original and compressed network representations, ensuring the preservation of essential features under resource constraints. Specifically, we employ layer-wise self-representation mutual information analysis, sampling-based pruning and quantization allocation, and progressive knowledge distillation using the optimal compressed model as a teacher assistant. Through extensive experiments on CIFAR-10 and ImageNet, we demonstrate that Prob-AMC achieves a superior compression ratio of 33.41× on ResNet-18 with only a 1.01% performance degradation, outperforming state-of-the-art methods in terms of both compression efficiency and accuracy. This optimization process is highly practical, requiring merely a few GPU hours, and bridges the gap between theoretical information measures and practical model compression, offering significant insights for efficient deep learning deployment.
An Approximation Algorithm for the Combination of G-Variational Inequalities and Fixed Point Problems
Authors: Kheawborisut Araya , Kangtunyakarn Atid
Published: December 2024

In this paper, we introduce a modified form of the G-variational inequality problem, called the combination of G-variational inequalities problem, within a Hilbert space structured by graphs. Furthermore, we develop an iterative scheme to find a common element between the set of fixed points of a G-nonexpansive mapping and the solution set of the proposed G-variational inequality problem. Under appropriate assumptions, we establish a strong convergence theorem within the framework of a Hilbert space endowed with graphs. Additionally, we present the concept of the G-minimization problem, which diverges from the conventional minimization problem. Applying our main results, we demonstrate a strong convergence theorem for the G-minimization problem. Finally, we provide illustrative examples to validate and support our theoretical findings.
Pattern Dynamics Analysis of Host–Parasite Models with Aggregation Effect Based on Coupled Map Lattices
Authors: Liang Shuo , Wang Wenlong , Zhang Chunrui
Published: December 2024

Host–parasitoid systems are an essential area of research in ecology and evolutionary biology due to their widespread occurrence in nature and significant impact on species evolution, population dynamics, and ecosystem stability. In such systems, the host is the organism being attacked by the parasitoid, while the parasitoid depends on the host to complete its life cycle. This paper investigates the effect of parasitoid aggregation attacks on a host in a host–parasitoid model with self-diffusion on two-dimensional coupled map lattices. We assume that in the simulation of biological populations on a plane, the interactions between individuals follow periodic boundary conditions. The primary objective is to analyze the complex dynamics of the host–parasitoid interaction model induced by an aggregation effect and diffusion in a discrete setting. Using the aggregation coefficient k as the bifurcating parameter and applying central manifold and normal form analysis, it has been shown that the system is capable of Neimark–Sacker and flip bifurcations even without diffusion. Furthermore, with the influence of diffusion, the system exhibits pure Turing instability, Neimark–Sacker–Turing instability, and Flip–Turing instability. The numerical simulation section explores the path from bifurcation to chaos through calculations of the maximum Lyapunov exponent and the construction of a bifurcation diagram. The interconversion between different Turing instabilities is simulated by adjusting the timestep and self-diffusion coefficient values, which is based on pattern dynamics in ecological modeling. This contributes to a deeper understanding of the dynamic behaviors driven by aggregation effects in the host–parasitoid model.
A Subgradient Extragradient Framework Incorporating a Relaxation and Dual Inertial Technique for Variational Inequalities
Authors: Rehman Habib ur , Sitthithakerngkiet Kanokwan , Seangwattana Thidaporn
Published: December 2024

This paper presents an enhanced algorithm designed to solve variational inequality problems that involve a pseudomonotone and Lipschitz continuous operator in real Hilbert spaces. The method integrates a dual inertial extrapolation step, a relaxation step, and the subgradient extragradient technique, resulting in faster convergence than existing inertia-based subgradient extragradient methods. A key feature of the algorithm is its ability to achieve weak convergence without needing a prior guess of the operator’s Lipschitz constant in the problem. Our method encompasses a range of subgradient extragradient techniques with inertial extrapolation steps as particular cases. Moreover, the inertia in our algorithm is more flexible, chosen from the interval [0,1]. We establish R-linear convergence under the added hypothesis of strong pseudomonotonicity and Lipschitz continuity. Numerical findings are presented to showcase the algorithm’s effectiveness, highlighting its computational efficiency and practical relevance. A notable conclusion is that using double inertial extrapolation steps, as opposed to the single step commonly seen in the literature, provides substantial advantages for variational inequalities.
Data-Driven Fault Diagnosis in Water Pipelines Based on Neuro-Fuzzy Zonotopic Kalman Filters
Authors: Pérez-Pérez Esvan-Jesús , González-Baldizón Yair , Fragoso-Mandujano José-Armando , Guzmán-Rabasa Julio-Alberto , Santos-Ruiz Ildeberto
Published: December 2024

This work presents a data-driven approach for diagnosing sensor faults and leaks in hydraulic pipelines using neuro-fuzzy Zonotopic Kalman Filters (ZKF). The approach involves two key steps: first, identifying the nonlinear pipeline system using an adaptive neuro-fuzzy inference system (ANFIS), resulting in a set of Takagi–Sugeno fuzzy models derived from pressure and flow data, and second, implementing a neuro-fuzzy ZKF bench to detect pipeline leaks and sensor faults with adaptive thresholds. The learning phase of the neuro-fuzzy systems considers only fault-free data. Fault isolation is achieved by comparing zonotopic sets and evaluating a fault signature matrix. The method accounts for parametric uncertainty and measurement noise, ensuring robustness. Experimental validation on a hydraulic pipeline demonstrated high precision (up to 99.24%), recall (up to 99.20%), and low false positive rates (as low as 0.76%) across various fault scenarios and operational points.
Dehydrothyrsiferol Against Cutaneous Leishmaniasis: Treatment Outcome in a Murine Model
Authors: López-Arencibia Atteneri , Bethencourt-Estrella Carlos J. , San Nicolás-Hernández Desirée , Rodríguez-Expósito Rubén L. , Domínguez-de-Barros Angélica , Salazar-Villatoro Lizbeth , Omaña-Molina Maritza , Cen-Pacheco Francisco , Díaz-Marrero Ana R. , Fernández José J. , Córdoba-Lanús Elizabeth , Lorenzo-Morales Jacob , Piñero José E.
Published: December 2024

One of the most important steps in preclinical drug discovery is to demonstrate the in vivo efficacy of potential leishmanicidal compounds and good characteristics at the level of parasite killing prior to initiating human clinical trials. This paper describes the use of dehydrothyrsiferol (DT), isolated from the red alga Laurencia viridis, in a pharmaceutical form supported on Sepigel, and the in vivo efficacy against a mouse model of cutaneous leishmaniasis. Studying the ultrastructural effect of DT was also carried out to verify the suspected damage at the cellular level and determine the severity of damages produced in the homeostasis of promastigotes. BALB/c mice infected with Leishmania amazonensis were divided into four groups: untreated mice, mice treated with miltefosine orally and mice treated topically with 1% and 0.5% DT-Sepigel; treatment was carried out for two weeks. Treatment with DT significantly reduced the parasite load in skin, liver and spleen compared with the untreated group. In addition, DT-Sepigel at the lowest concentration (0.5%) showed the best results, reducing lesion size by 87% at 3 weeks post-treatment. DT-Sepigel has demonstrated to be a potent topical treatment that, in combined drug trials, may aim at combating cutaneous leishmaniasis.
The Influence Mechanism of Deformation on the Precipitation Behavior and Mechanical Properties of 7075 Aluminum Alloy During Hot Forming-Quenching Integrated Process
Authors: Li Huanhuan , Zhang Xinhang , Dai Wei , Yan Wei , He Chaomei , Luo Jiake , Li Mengxing , Wu Ruolin , Wang Dang
Published: December 2024

The hot forming-quenching integrated process (HFQ®) organically combines the deformation and heat treatment, which can improve the forming performance of aluminum alloy while ensuring the final strength of formed parts. Thermal deformation in HFQ® has a non-negligible influence on precipitation behavior in subsequent artificial aging treatment and affects the mechanical properties of the formed parts. In this study, the relationship between the precipitation behavior and thermal deformation ratios was investigated. Results indicated that the formation temperatures of η′ and η decreased with an increasing deformation ratio; however, the former decreased more than the latter. The activation energy of η′ precipitation decreased linearly with increasing deformation ratio. Additionally, the phase transition fraction of η′ increased with the deformation ratio, leading to shorter times required to reach equivalent phase transition fractions. Deformation accelerated the phase transition of η′, and greater deformation resulted in a shorter transition time. The aging time required for peak Vickers hardness decreased with increasing deformation ratio, reflecting the promotion of precipitated phase formation and transformation by introduced dislocations. Consequently, peak hardness and yield strength were achieved in shorter aging times. In terms of industrial applications, this discovery offers significant advantages for shortening the production cycle of the hot stamping process and reducing production costs.
Effect of Potassium Salt Addition on Silver Precipitation During Hydrothermal Synthesis of Argentojarosites
Authors: Cheremisina Olga , Vasiliev Roman , Fedorov Aleksei
Published: December 2024

This paper presents the laboratory study results of the hydrothermal synthesis of compounds structurally related to the jarosite group, which is characterized by basic iron sulfate AFe3(SO4)2(OH)6 as the main structural component containing A+ cations such as K+, Ag+, and NH4+. The synthesis process involves preparing the initial model solution using soluble salts of the studied metals, either jointly or individually. The resulting solution is then processed in a sealed vessel (autoclave) at a temperature exceeding 100 °C. This study was conducted within a temperature range of 105–200 °C, with experiment durations varying and a maximum dwell time of 300 min. The zero-time value was defined as the moment the autoclave reached the required temperature. It was observed that adding potassium salts to the solution during hydrothermal synthesis reduced the amount of silver precipitated as argentojarosite. An increase in process temperature from 105 °C to 200 °C resulted in a rise in silver precipitation, from 35% to 69%. The equilibrium constants of the reactions involved in the precipitation of specific jarosite group compounds were calculated, and the reaction order was determined.
Advanced Amperometric Microsensors for the Electrochemical Quantification of Quercetin in Ginkgo biloba Essential Oil from Regenerative Farming Practices
Authors: Oancea Elena , Tula Ioana Adina , Stanciu Gabriela , Ștefan-van Staden Raluca-Ioana , van Staden Jacobus (Koos) Frederick , Mititelu Magdalena
Published: December 2024

In this study, we present a novel approach using amperometric microsensors to detect quercetin in cosmetic formulations and track its metabolic behavior after topical application. This method offers a sensitive, real-time alternative to conventional techniques, enabling the detection of quercetin’s bioavailability, its transformation into active metabolites, and its potential therapeutic effects when applied to the skin. Quercetin (Q) is a bioactive flavonoid known for its potent antioxidant properties, naturally present in numerous plants, particularly those with applications in cosmetic formulations. In response to the growing interest in developing novel plant-based dermo-cosmetic solutions, this study investigates the electrochemical detection of quercetin, a ketone-type flavonoid, extracted from Gingko biloba essential oil. Three newly designed amperometric microsensors were developed to assess their efficacy in detecting quercetin in botanical samples. The sensor configurations utilized two forms of carbon material as a foundation: graphite (G) and carbon nanoparticles (CNs). These base materials were modified with paraffin oil, chitosan (CHIT), and cobalt(II) tetraphenylporphyrin (Co(II)TPP) to enhance sensitivity. Differential pulse voltammetry (DPV) served as the analytical method for this investigation. Among the sensors, the CHIT/G–CN microsensor exhibited the highest sensitivity, with a detection limit of 1.22 × 10−7 mol L−1, followed by the G–CN (5.64 × 10−8 mol L−1) and Co(II)TPP/G–CN (9.80 × 10−8 mol L−1) microsensors. The minimum detectable concentration was observed with the G–CN and CoP/G–CN microsensors, achieving a threshold as low as 0.0001 μmol L−1. Recovery rates and relative standard deviation (RSD) values averaged 97.4% ± 0.43, underscoring the sensors’ reliability for quercetin detection in botanical matrices.
Recovery Analysis of Sequentially Irradiated and NBT-Stressed VDMOS Transistors
Authors: Djorić-Veljković Snežana , Živanović Emilija , Davidović Vojkan , Veljković Sandra , Mitrović Nikola , Ristić Goran , Paskaleva Albena , Spassov Dencho , Danković Danijel
Published: December 2024

This study investigates the effects of negative bias temperature (NBT) stress and irradiation on the threshold voltage (VT) of p-channel VDMOS transistors, focusing on degradation, recovery after each type of stress, and operational behavior under varying conditions. Shifts in VT (ΔVT) were analyzed under different stress orders, showing distinct influence mechanisms, including defects creation and their removal and electrochemical reactions. Recovery data after each type of stress indicated ongoing electrochemical processes, influencing subsequent stress responses. Although the ΔVT is not particularly pronounced during the recovery after irradiation, changes in subthreshold characteristics indicate the changes in defect densities that affect the behavior of the components during further application. Additionally, the findings show that the ΔVT during the NBT stress after irradiation (up to certain doses and conditions) remains relatively stable, but this is the result of a balance of competing mechanisms. A subthreshold characteristic analysis provided a further insight into the degradation dynamics. A particular attention was paid to analyzing ΔVT with a focus on predicting the lifetime. In practical applications, especially under pulsed operation, prior stresses altered the device’s thermal and electrical performance. It was shown that self-heating effects were more pronounced in pre-stressed components, increasing the power dissipation and thermal instability. These insights additionally highlight the importance of understanding stress-induced degradation and recovery mechanisms for optimizing VDMOS transistor reliability in advanced electronic systems.
A Negative Capacitance Field-Effect Transistor with High Rectification Efficiency for Weak-Energy 2.45 GHz Microwave Wireless Transmission
Authors: Tang Hualian , Tang Ailan , Liu Weifeng , Huang Jingxiang , Song Jianjun , Sun Wenjie
Published: December 2024

This paper proposes and designs a silicon-based negative capacitance field effect transistor (NCFET) to replace conventional MOSFETs as the rectifying device in RF-DC circuits, aiming to enhance the rectification efficiency under low-power density conditions. By combining theoretical analysis with device simulations, the impacts of the ferroelectric material anisotropy, ferroelectric layer thickness, and active region doping concentration on the device performance were systematically optimized. The proposed NCFET structure is tailored for microwave wireless power transmission applications. Based on the optimized NCFET, a half-wave rectifier circuit employing a novel diode connection configuration was constructed and verified through transient simulations. The results show that at a microwave frequency of 2.45 GHz, the designed NCFET rectifier achieves rectification efficiencies of 16.1% and 29.75% at input power densities of −10 dBm and −6 dBm, respectively, which are 7.15 and 2.3 times higher than those of conventional silicon-based MOS devices. Furthermore, it significantly outperforms CMOS rectifiers reported in the literature. This study demonstrates the superior rectification performance of the proposed NCFET under low-power density conditions, offering an efficient device solution for microwave wireless power transmission systems.
Thyme Essential Oil as a Potential Tool Against Common and Re-Emerging Foodborne Pathogens: Biocidal Effect on Bacterial Membrane Permeability
Authors: Di Rosario Martina , Continisio Leonardo , Mantova Giuseppe , Carraturo Francesca , Scaglione Elena , Sateriale Daniela , Forgione Giuseppina , Pagliuca Chiara , Pagliarulo Caterina , Colicchio Roberta , Vitiello Mariateresa , Salvatore Paola
Published: December 2024

Over the past decade, foodborne diseases have become a significant public health concern, affecting millions of people globally. Major pathogens like Salmonella spp., Escherichia coli, Listeria monocytogenes, and Staphylococcus aureus contaminate food and cause several infections. This study investigates the potential of thyme essential oil (Thy-EO) as a natural antimicrobial agent against most common and re-emerging foodborne bacteria, including S. enterica, Yersinia enterocolitica, and L. monocytogenes. Preliminary tests provided qualitative evidence of Thy-EO’s efficacy by evaluating its antibacterial activity through direct contact and vapor phase exposure. Then, the Minimum Inhibitory Concentration (MIC) and Minimum Bactericidal Concentration (MBC) were defined to quantitatively evaluate the bacteriostatic and bactericidal effects of Thy-EO, revealing a strong inhibitory effect against S. enterica, Y. enterocolitica and L. monocytogenes. Additionally, Thy-EO exerted rapid bactericidal kinetics characterized by the disruption of bacterial cell membrane integrity over time. Results highlight Thy-EO’s potential as an alternative antimicrobial agent, demonstrating that treatment with Thy-EO significantly and irreversibly affects the growth of the tested foodborne pathogens.
Comparison of Lipid Content in Nine Dinoflagellate Species Using Flow Cytometry
Authors: Park Jaeyeon , Yoon Eun Young , Moon Seung Joo , Hyung Jun-Ho , Lee Hangy
Published: December 2024

The lipid content of nine dinoflagellates was analyzed using flow cytometry to compare lipid levels. Additionally, the correlation between lipid content, cell size, and carbon content in dinoflagellates was evaluated using BODIPY 505/515 staining. The flow cytometry side scatter (SSC) effectively represented relative cell size, showing a linear relationship with the equivalent spherical diameter (ESD). Larger cells exhibited higher relative lipid content; however, lipid accumulation was influenced by nutritional modes and habitats, with mixorophic and benthic species displaying higher lipid content than heterotrophic species. A comparison of fluorescent dyes revealed that Nile Red overestimated lipid content, suggesting overlap with chlorophyll autofluorescence. Flow cytometry analysis with BODIPY 505/515 demonstrated a linear correlation with the sulfo-phospho-vanillin (SPV) method, enabling determination of actual lipid content using FL1 fluorescence and the slope value. As the carbon content increased, the lipid content initially increased rapidly but plateaued at higher carbon levels, indicating saturation. These findings suggest that relative fluorescence via flow cytometry provides an effective means to estimate the lipid content and carbon content as a function of cell size.