bluuebunny/crossref_metadata_2025 huggingface dataset:
Facilitation of Tumor Stroma-Targeted Therapy: Model Difficulty and Co-Culture Organoid Method
Authors: Feng Qiu-Shi , Shan Xiao-Feng , Yau Vicky , Cai Zhi-Gang , Xie Shang
Published: January 2025

Background: Tumors, as intricate ecosystems, comprise oncocytes and the highly dynamic tumor stroma. Tumor stroma, representing the non-cancerous and non-cellular composition of the tumor microenvironment (TME), plays a crucial role in oncogenesis and progression, through its interactions with biological, chemical, and mechanical signals. This review aims to analyze the challenges of stroma mimicry models, and highlight advanced personalized co-culture approaches for recapitulating tumor stroma using patient-derived tumor organoids (PDTOs). Methods: This review synthesizes findings from recent studies on tumor stroma composition, stromal remodeling, and the spatiotemporal heterogeneities of the TME. It explores popular stroma-related models, co-culture systems integrating PDTOs with stromal elements, and advanced techniques to improve stroma mimicry. Results: Stroma remodeling, driven by stromal cells, highlights the dynamism and heterogeneity of the TME. PDTOs, derived from tumor tissues or cancer-specific stem cells, accurately mimic the tissue-specific and genetic features of primary tumors, making them valuable for drug screening. Co-culture models combining PDTOs with stromal elements effectively recreate the dynamic TME, showing promise in personalized anti-cancer therapy. Advanced co-culture techniques and flexible combinations enhance the precision of tumor-stroma recapitulation. Conclusions: PDTO-based co-culture systems offer a promising platform for stroma mimicry and personalized anti-cancer therapy development. This review underscores the importance of refining these models to advance precision medicine and improve therapeutic outcomes.
Nanoformulation of Polymyxin E Through Complex Coacervation: A Pharmacokinetic Analysis
Authors: Chen Xiaobao , Liu Li , Wang Weidan , Yuan Yuan , Wang Wei
Published: January 2025

Objectives: Polymyxin E (PME), a polymyxin antibiotic, serves as a final resort against antibiotic resistance. Nephrotoxicity is the primary concern when employing PME. To alleviate this issue, researchers have explored strategies including dosing adjustments and innovative formulations. This study employed complex coacervation to create PME nanoformulations, capitalizing on PME’s charge properties. The research question and hypothesis posed pertained to whether neutralization of PME’s positive charge during formulation would reduce its antibiotic efficacy and alter its tissue distribution and other pharmacokinetic parameters. Our objective was to evaluate the capability of complex coacervation to mitigate the adverse effects of PME while preserving its antibacterial potency and therapeutic effectiveness. Methods: Three negatively charged polyions: potassium sucrose octasulfate, polytamic acid, and sodium hyaluronate, were used for formulation. We performed characterization on the nanocomplex formed by the polyions and PME. The nanoformulations underwent several tests, including minimum inhibitory concentration, in vivo efficacy on an infected mouse model, pharmacokinetic assessments, tissue distribution, and toxicity. Results: the three polyions formed coacervation complexes with PME at varying charge ratios, yielding nanoparticles smaller than 30 nm with low polydispersity (PDI < 0.3). The results demonstrated that complex coacervation-mediated PME nanoformulations exhibited equivalent or superior antibacterial activity, increased maximum tolerant dose, and fewer adverse reactions in animal tests. Conclusions: Utilizing complex coacervation, PME nanoformulations were developed, demonstrating efficacy in the formulation process. Pharmacokinetic assessments revealed absorption and distribution profiles akin to those of standalone PME. The positive charge inherent in PME causing its toxicity was mitigated after complex coacervation.
Leaf and Root Functional Traits of Woody and Herbaceous Halophytes and Their Adaptations in the Yellow River Delta
Authors: Wang Yan , Wu Hao , Wang Jian , Mu Liqiang , Li Zhongyue
Published: January 2025

Leaves and roots perform assimilation, supporting plant growth and functionality. The variations in their functional traits reflect adaptive responses to environmental conditions, yet limited information is available regarding these trait variations and their coordination in saline environments. In this study, 18 common woody and herbaceous halophyte species from the Yellow River Delta were collected, and their leaf and root functional traits were assessed and compared. Our results showed that, compared with herbaceous species, woody species had greater root diameter, cortex thickness, and stele diameter, but lower specific root length and leaf area. Meanwhile, root diameter was strongly correlated with cortex thickness and stele diameter; leaf thickness was also tightly related with palisade tissue thickness. However, fewer correlations were found between paired leaf and root traits in either herbaceous or woody species, indicating that the variations in leaves and roots appeared relatively independent, which might be related to the different abiotic environmental conditions experienced by above- and belowground organs. These results highlight that woody species tended to be more conservative in resource acquisition and establishment; meanwhile, the herbaceous ones were acquisitive. Such patterns show the contrasting survival strategies of different plant taxa, which also provide valuable insights for future vegetation restoration efforts in this salinized region.
Green Extraction of Bioactives from Curcuma longa Using Natural Deep Eutectic Solvents: Unlocking Antioxidative, Antimicrobial, Antidiabetic, and Skin Depigmentation Potentials
Authors: Jovanović Jelena , Jović Marko , Trifković Jelena , Smiljanić Katarina , Gašić Uroš , Krstić Ristivojević Maja , Ristivojević Petar
Published: January 2025

This study evaluates the efficiency of 20 Natural Deep Eutectic Solvents (NADES) formulations for extracting curcuminoids and other bioactive compounds from turmeric and emphasize their ability to preserve and enhance antioxidant, antimicrobial, antidiabetic, and skin depigmentation effects. The NADES formulations, prepared using choline chloride (ChCl) combined with sugars, carboxylic acids, glycerol, amino acids, urea, polyols, and betaine, were assessed for their extraction efficiency based on the total phenolic content and curcumin concentration. Fourier transform infrared spectroscopy was employed to characterize the synthesized NADES and confirm their chemical composition. Bioactivity evaluations included antioxidant assays (ABTS and DPPH), antidiabetic tests (α-amylase inhibition), antimicrobial assays, and skin depigmentation (tyrosinase inhibition). The results demonstrated that NADES significantly enhanced the extraction efficiency and bioactive properties of turmeric extracts compared to water as a conventional green solvent. NADES 18 (ChCl/1,2-propanediol/water 1:1:1) and NADES 19 (glycerol/betaine/water 1:1:3) exhibited the highest extraction yields, with curcumin concentrations of 30.73 ± 1.96 mg/g and 31.70 ± 2.02 mg/g, respectively, outperforming water (26.91 ± 1.72 mg/g), while NADES 17 (ChCl/1,2-propanediol/water 0.5:3:0.5:5) and NADES 20 (glycerol/lysine/water 1:1:3) exhibited the most potent antioxidant activity. Furthermore, NADES 14 (ChCl/lactic acid/water 1:2:5) demonstrated the strongest tyrosinase inhibition (98.7%), supporting its potential for skin-brightening applications, including notable α-amylase inhibition exceeding 90%. This study aligns with the principles of green chemistry, as NADES are effective and sustainable solvents for natural product extraction. The presenting benefits of improved extraction efficiency and enhanced bioactivities position NADES as a promising and eco-friendly approach for developing efficient bioactive compound extraction methodologies.
Aerogels Based on Chitosan and Collagen Modified with Fe2O3 and Fe3O4 Nanoparticles: Fabrication and Characterization
Authors: Granados-Carrera Carmen Mª , Castro-Criado Daniel , Abdullah Johar Amin Ahmed , Jiménez-Rosado Mercedes , Perez-Puyana Víctor M.
Published: January 2025

The necessity to mitigate the intrinsic issues associated with tissue or organ transplants, in order to address the rising prevalence of diseases attributable to increased life expectancy, provides a rationale for the pursuit of innovation in the field of biomaterials. Specifically, biopolymeric aerogels represent a significant advancement in the field of tissue engineering, offering a promising solution for the formation of temporary porous matrices that can replace damaged tissues. However, the functional characteristics of these materials are inadequate, necessitating the implementation of matrix reinforcement methods to enhance their performance. In this study, chemical and green iron oxide nanoparticles, previously synthesized and documented in existing research, were incorporated into hybrid aerogels combining collagen (C) and chitosan (CH). The characterization of these aerogels was conducted through rheological, microstructural, and functional analyses. The results demonstrate that the incorporation of iron oxide nanoparticles has a significant influence on the properties of the aerogels fabricated with them. In particular, the incorporation of these nanoparticles has been observed to modify the mechanical properties, with an increase in strength and porosity that may support cell proliferation.
X-Ray Shielding Polymer Based on Sequential Polycondensation of BiPh3 and Carboxylic Acids and Radical Polymerization
Authors: Ochiai Bungo , Kamiya Ryo , Matsumura Yoshimasa , Tanaka Hiroyasu , Ueda Hideki , Uera Kazuyoshi , Furukawa Kikuo , Nishimura Yoshio
Published: January 2025

Transparent X-ray shielding polymer films were developed by bulk photo copolymerization of in situ prepared bismuth carboxylate prepolymers with polymerizable exomethylene moieties and N,N-dimethylacrylamide (DMAA). The bismuth-containing prepolymers were prepared via the polycondensation of BiPh3, 2-octenylsuccinic acid (OSA), and itaconic acid (IA) bearing an exomethylene group for polymerization. OSA was a chain extender by intermolecular condensation and a stopper by intramolecular cyclization to inhibit cross-linkage. The resulting photocured films exhibit high visible-light transparency and high nD, reaching 1.57. The X-ray shielding ability increased with the bismuth content and reached an aluminum equivalent of 0.80.
A Study on Production of Canned Minced Chicken and Pork and Formation of Heterocyclic Amines During Processing
Authors: Inbaraj Baskaran Stephen , Lai Yu-Wen , Chen Bing-Huei
Published: January 2025

Toxic compounds such as heterocyclic amines (HAs) are formed during the processing of protein-rich foods, especially meat products. This study aims to investigate the formation of HAs during the canning of chicken and pork by using an ultra-performance liquid chromatograph coupled with tandem mass spectrometer (UPLC-MS/MS). Minced samples of both chicken and pork were separately subjected to marinating, stir-frying and degassing for subsequent canning and sterilization for 60 min at 115 °C (low temperature–long time, LL–ST) or 25 min at 125 °C (high temperature–short time, HS–ST) and analyzed for HAs. The results showed that both marinating and sterilization could significantly affect the HA formation in canned minced chicken and pork, with the LL–ST treatment being more liable to total HA formation than the HS–ST treatment, and the total HAs (especially, Harman and Norharman) was produced at a higher level in canned minced pork than in canned minced chicken under the same sterilization treatment. A reduction in reducing sugar, creatine, and amino acid contents resulted in HA formation in canned minced chicken and pork during processing. The results were confirmed by principal component analysis and showed that HAs were formed at significant levels in canned minced chicken and pork, with the level of major HA content following the order of Harman > Trp-P-1 > Norharman > DMIP. Although the presence of non-mutagenic HAs (Harman, Norharman and DMIP) and possibly carcinogenic HA (Trp-P-1) contributed to 95.8% of total HAs formed in both canned pork and chicken in this study, it is imperative to reduce the HA exposure to humans for improved public health by decreasing the consumption of processed meat and increasing the intake of fruits and vegetables, as well as incorporating natural antioxidant-rich ingredients into foods during processing to minimize the formation of HAs.
Band Selection Algorithm Based on Multi-Feature and Affinity Propagation Clustering
Authors: Zhuang Junbin , Chen Wenying , Huang Xunan , Yan Yunyi
Published: January 2025

Hyperspectral images are high-dimensional data containing rich spatial, spectral, and radiometric information, widely used in geological mapping, urban remote sensing, and other fields. However, due to the characteristics of hyperspectral remote sensing images—such as high redundancy, strong correlation, and large data volumes—the classification and recognition of these images present significant challenges. In this paper, we propose a band selection method (GE-AP) based on multi-feature extraction and the Affine Propagation Clustering (AP) algorithm for dimensionality reduction of hyperspectral images, aiming to improve classification accuracy and processing efficiency. In this method, texture features of the band images are extracted using the Gray-Level Co-occurrence Matrix (GLCM), and the Euclidean distance between bands is calculated. A similarity matrix is then constructed by integrating multi-feature information. The AP algorithm clusters the bands of the hyperspectral images to achieve effective band dimensionality reduction. Through simulation and comparison experiments evaluating the overall classification accuracy (OA) and Kappa coefficient, it was found that the GE-AP method achieves the highest OA and Kappa coefficient compared to three other methods, with maximum increases of 8.89% and 13.18%, respectively. This verifies that the proposed method outperforms traditional single-information methods in handling spatial and spectral redundancy between bands, demonstrating good adaptability and stability.
Discovering Tree Architecture: A Comparison of the Performance of 3D Digitizing and Close-Range Photogrammetry
Authors: Šleglová Kristýna , Hrdina Marek , Surový Peter
Published: January 2025

Accurate measurement of tree architecture is vital for understanding forest dynamics and supporting effective forest management. This study evaluates close-range photogrammetry (CRP) using TreeQSM (v2.4.1) software, reconstructing 3D tree structures in both deciduous and coniferous species and comparing its performance to the Fastrak 3D digitizing method. CRP proved less labor-intensive and effective for estimating parameters like tree height, stem diameter, and volume of thicker branches in small trees. However, it struggled with capturing intricate structures, overestimating volumetric values and underestimating branch lengths and counts. Mean relative root mean square errors for height, diameter at 0.3 m height, volume, and branch count were 34.19%, 69.9%, 107.87%, and 142.03%, respectively. These discrepancies stem from challenges in reconstructing moving objects and filtering non-woody elements. While CRP shows potential as a complementary method, further advancements are necessary to improve 3D tree model reconstruction, emphasizing the need for ongoing research in this domain.
A Novel Particle Filter Based on One-Step Smoothing for Nonlinear Systems with Random One-Step Delay and Missing Measurements
Authors: Yang Zhenrong , Zhang Xing , Xiang Wenqian , Lin Xiaohui
Published: January 2025

In this paper, a novel particle filter based on one-step smoothing is proposed for nonlinear systems with random one-step delay and missing measurements. Such problems are commonly encountered in networked control systems, where random one-step delay and missing measurements significantly increase the difficulty of dynamic state estimation. The particle filter is a nonlinear filtering method based on sequential Monte Carlo sampling. It shows excellent state estimation performance when dealing with nonlinear and non-Gaussian dynamic systems. However, the particle filter has certain limitations in complex dynamic scenarios, with particle degradation being the most typical issue, which can significantly reduce estimation accuracy. To address particle degradation, the proposed particle filter iteratively incorporates current measurement information derived from sensors into the prior distribution to construct a new importance function. This approach can limit particle degeneracy and improve the efficiency of importance sampling in the bootstrap particle filter. Simulation experiments demonstrate that the proposed particle filter effectively limits particle degradation and improves estimation accuracy compared to the existing bootstrap particle filter for nonlinear systems with random one-step delay and missing measurements.
On the Performance of Energy Harvesting Dual-Hop Free-Space Optical Communication Systems with Secrecy Analysis
Authors: Ibrahim Abdulgani A. , Ata Serdar Özgür , Durak-Ata Lütfiye
Published: January 2025

In this study, we present a dual-hop decode-and-forward relaying-based free-space optical (FSO) communication system. We consider utilizing simultaneous lightwave information and power transfer (SLIPT) with a time-splitting technique at the relay, where the direct current component of the received optical signal is harvested as a transmit power for the relay. It is assumed that the FSO links experience a Malaga turbulence channel with pointing errors. In order to evaluate the performance of the proposed communication system, closed-form expressions for outage probability, ergodic capacity, average bit error rate, and throughput are derived. Additionally, to analyze the physical layer security of the proposed system, closed-form expressions for secrecy outage probability and strictly positive secrecy capacity are obtained. Finally, the accuracy of the derived analytical expressions are validated with Monte Carlo simulations. Results show that our proposed system model outperforms its non-SLIPT counterpart.
GPS Phase Integer Ambiguity Resolution Based on Eliminating Coordinate Parameters and Ant Colony Algorithm
Authors: Liu Ning , Zhang Shuangcheng , Wu Xiaoli , Shen Yu
Published: January 2025

Correctly fixing the integer ambiguity of GNSS is the key to realizing the application of GNSS high-precision positioning. When solving the float solution of ambiguity based on the double-difference model epoch by epoch, the common method for resolving the integer ambiguity needs to solve the coordinate parameter information, due to the influence of limited GNSS phase data observations. This type of method will lead to an increase in the ill-posedness of the double-difference solution equation, so that the fixed success rate of the integer ambiguity is not high. Therefore, a new integer ambiguity resolution method based on eliminating coordinate parameters and ant colony algorithm is proposed in this paper. The method eliminates the coordinate parameters in the observation equation using QR decomposition transformation, and only estimates the ambiguity parameters using the Kalman filter. On the basis that the Kalman filter will obtain the float solution of ambiguity, the decorrelation processing is carried out based on continuous Cholesky decomposition, and the optimal solution of integer ambiguity is searched using the ant colony algorithm. Two sets of static and dynamic GPS experimental data are used to verify the method and compared with conventional least squares and LAMBDA methods. The results show that the new method has good decorrelation effect, which can correctly and effectively realize the integer ambiguity resolution.
Advanced Wearable Sensors Technologies for Healthcare Monitoring
Authors: Tamura Toshiyo
Published: January 2025

Wearable sensor technologies are rapidly evolving and expanding their reach into critical wellness and healthcare applications [...]
Abnormal Operation Detection of Automated Orchard Irrigation System Actuators by Power Consumption Level
Authors: Ahmed Shahriar , Reza Md Nasim , Karim Md Rejaul , Jin Hongbin , Kim Heetae , Chung Sun-Ok
Published: January 2025

Information and communication technology (ICT) components, especially actuators in automated irrigation systems, are essential for managing precise irrigation and optimal soil moisture, enhancing orchard growth and yield. However, actuator malfunctions can lead to inefficient irrigation, resulting in water imbalances that impact crop health and reduce productivity. The objective of this study was to develop a signal processing technique to detect potential malfunctions based on the power consumption level and operating status of actuators for an automated orchard irrigation system. A demonstration orchard with four apple trees was set up in a 3 m × 3 m soil test bench inside a greenhouse, divided into two sections to enable independent irrigation schedules and management. The irrigation system consisted of a single pump and two solenoid valves controlled by a Python-programmed microcontroller. The microcontroller managed the pump cycling ‘On’ and ‘Off’ states every 60 s and solenoid valves while storing and transmitting sensor data to a smartphone application for remote monitoring. Commercial current sensors measured actuator power consumption, enabling the identification of normal and abnormal operations by applying threshold values to distinguish activation and deactivation states. Analysis of power consumption, control commands, and operating states effectively detected actuator operations, confirming reliability in identifying pump and solenoid valve failures. For the second solenoid valve in channel 2, with 333 actual instances of normal operation and 60 actual instances of abnormal operation, the model accurately detected 316 normal and 58 abnormal instances. The proposed method achieved a mean average precision of 99.9% for detecting abnormal control operation of the pump and solenoid valve of channel 1 and a precision of 99.7% for the solenoid valve of channel 2. The proposed approach effectively detects actuator malfunctions, demonstrating the potential to enhance irrigation management and crop productivity. Future research will integrate advanced machine learning with signal processing to improve fault detection accuracy and evaluate the scalability and adaptability of the system for larger orchards and diverse agricultural applications.
Brain Oxygenation During Exercise in Different Types of Chronic Lung Disease: A Narrative Review
Authors: Kritikou Stella , Zafeiridis Andreas , Pitsiou Georgia , Gkalgkouranas Ioannis , Kastritseas Leonidas , Boutou Afroditi , Dipla Konstantina
Published: January 2025

Chronic lung diseases such as Chronic Obstructive Pulmonary Disease, Interstitial Lung Disease (ILD), and Pulmonary Hypertension (PH) are characterized by progressive symptoms such as dyspnea, fatigue, and muscle weakness, often leading to physical inactivity, and reduced quality of life. Many patients also experience significantly impaired exercise tolerance. While pulmonary, cardiovascular, respiratory, and peripheral muscle dysfunction contribute to exercise limitations, recent evidence suggests that hypoxia and impairments in cerebral oxygenation may also play a role in exercise intolerance. This narrative review (i) summarizes studies investigating cerebral oxygenation responses during exercise in patients with different types of chronic lung diseases and (ii) discusses possible mechanisms behind the blunted cerebral oxygenation during exercise reported in many of these conditions; however, the extent of cerebral desaturation and the intensity at which it occurs can vary. These differences depend on the specific pathophysiology of the lung disease and the presence of comorbidities. Notably, reduced cerebral oxygenation during exercise in fibrotic-ILD has been linked with the development of dyspnea and early exercise termination. Understanding the effects of chronic lung disease on cerebral oxygenation during exercise may improve our understanding of exercise intolerance mechanisms and help identify therapeutic strategies to enhance brain health and exercise capacity in these patients.
A Diagnostic and Performance System for Soccer: Technical Design and Development
Authors: Gascón Alberto , Marco Álvaro , Buldain David , Alfaro-Santafé Javier , Alfaro-Santafé Jose Victor , Gómez-Bernal Antonio , Casas Roberto
Published: January 2025

This study presents a novel system for diagnosing and evaluating soccer performance using wearable inertial sensors integrated into players’ insoles. Designed to meet the needs of professional podiatrists and sports practitioners, the system focuses on three key soccer-related movements: passing, shooting, and changes of direction (CoDs). The system leverages low-power IMU sensors, Bluetooth Low Energy (BLE) communication, and a cloud-based architecture to enable real-time data analysis and performance feedback. Data were collected from nine professional players from the SD Huesca women’s team during controlled tests, and bespoke algorithms were developed to process kinematic data for precise event detection. Results indicate high accuracy rates for detecting ball-striking events and CoDs, with improvements in algorithm performance achieved through adaptive thresholds and ensemble neural network models. Compared to existing systems, this approach significantly reduces costs and enhances practicality by minimizing the number of sensors required while ensuring real-time evaluation capabilities. However, the study is limited by a small sample size, which restricts generalizability. Future research will aim to expand the dataset, include diverse sports, and integrate additional sensors for broader applications. This system offers a valuable tool for injury prevention, player rehabilitation, and performance optimization in professional soccer, bridging technical advancements with practical applications in sports science.
Building Sustainable Career Skills in Youth Through Adaptive Learning and Competency Self-Assessment Tools
Authors: Abina Andreja , Kovačič Darko , Prucnal Marika , Kiratzouli Vaia , Zidanšek Aleksander
Published: January 2025

The DECIDE project entitled “Career choices competencies for the post-pandemic future using multicriteria decision-making”, aimed to empower young individuals in their career decision-making by providing them with personalised learning sources and tools to monitor the development of essential career competencies. This paper presents the findings from evaluating two key components of the DECIDE project: an e-guide for developing career competencies and a web-based application that monitors individuals’ progress in competency development. These tools help young people identify the skills and knowledge they lack to meet the demands of employers for sustainable and innovative career paths. The e-guide was designed as a self-learning programme that guides users through interactive models focused on building the competencies required for sustainable and innovative career profiles. Pre-tests and post-tests were developed to assess the effectiveness of the e-guide and measure the participants’ competency levels before and after engaging with the learning content. The application utilises advanced algorithms and visualisation techniques to analyse pre-test and post-test data, identify competency gaps, and provide users with a clear understanding of their competency development progress and areas for further improvements. The results of the testing and user feedback indicate that the developed tools positively impacted the development of career competencies. The study reveals that the e-guide provided educational value and effectively supported self-directed learning. At the same time, the web-based application offered a valuable tool for self-assessment and identifying competency gaps in career decision-making.
Oil Palm Bagasse as a Treatment for Soils Contaminated with Total Petroleum Hydrocarbons
Authors: Orejuela-Romero Jennifer Alexandra , Santillán-Quiroga Luis Miguel , Herrera Cuadrado Zayda Vanessa , Heredia Jara Daniel Alejandro , Núñez Moreno María Soledad , Barahona Marcos , Prado Seleni , Zurita Ordóñez Michelle Elisa
Published: January 2025

Soil contamination from oil spills in the canton of Francisco de Orellana in Ecuador is the biggest contamination problem in the region. It affects the quality of resources and poses health risks to the surrounding communities. To find an economical and efficient alternative for the remediation of soils contaminated with total petroleum hydrocarbons (TPHs), the application of oil palm bagasse was proposed. This is a locally available industrial waste. The methodology of the study was based on the application of six treatments (G-A, G-B, O-A, O-B, M-A, M-B) belonging to the bagasse of Elaeis guineensis and Elaeis oleifera, in two percentages of concentration, 98:2 and 96:4, during a period of 20 days. To determine the efficacy of the treatments, the bagasse of the two palms was characterized. In addition, the initial physicochemical characterization of the soil and the final characterization after the treatments were carried out. Soil characterization included analyses of macronutrients, micronutrients, metals, pH, EC and TPH. The results of the initial characterization revealed that the concentrations of electrical conductivity and TPH were more than 70 and 50 times the values established in the 97-A ministerial agreement, respectively. However, after the final characterization, the effectiveness of the treatments in reducing metal concentrations was observed. Likewise, conductivity levels were reduced by more than 10 times. As for TPH, the G-B treatment stood out by achieving a 56% removal of this pollutant.
Sustainability Impact Evaluation of the Recycling of End-of-Life Crystalline Silicon Solar Photovoltaic Panel Waste in South Korea
Authors: Kwon Soonho , Kim Hae Jong , Kim Samyeon , Hong Sung Joo
Published: January 2025

The end-of-life (EoL) management of solar panel waste has emerged as an important issue related to first-generation solar panels in South Korea, which have already entered their retirement stage. In this study, the sustainability impacts of three scenarios for recycling EoL solar panels, namely mechanical recycling (MR), chemical recycling (CR), and thermal recycling (TR), were investigated, and their environmental and economic benefits were evaluated using the life cycle sustainability assessment (LCSA) method, with landfilling as the reference scenario. The results obtained showed a high global warming potential (GWP) as well as acidification for MR owing to the additional burden of transportation and industrial processes associated with MR. For CR, the use of chemicals and subsequent landfilling resulted in approximately 4.7 times higher terrestrial eco-toxicity than was observed for the landfilling scenario. Further, the GWP of TR was approximately 1.5 times higher than that of CR owing to its high energy consumption. However, its environmental burden was generally lower than that of MR and CR. The results of this study, which capture the current situation of EoL PV panels in South Korea, can be employed to facilitate the establishment of regulations that ensure sustainable management in this regard.
Explainable Warm-Start Point Learning for AC Optimal Power Flow Using a Novel Hybrid Stacked Ensemble Method
Authors: Xu Kaijie , Zhang Xiaochen , Qiu Lin
Published: January 2025

With the development of renewable energy, renewable power generation has become an increasingly important component of the power system. However, it also introduces uncertainty into the analysis of the power system. Therefore, to accelerate the solution of the OPF problem, this paper proposes a novel Hybrid Stacked Ensemble Method (HSEM), which incorporates explainable warm-start point learning for AC optimal power flow. The HSEM integrates conventional machine learning techniques, including regression trees and random forests, with gradient boosting trees. This combination leverages the individual strengths of each algorithm, thereby enhancing the overall generalization capabilities of the model in addressing AC-OPF problems and improving its interpretability. Experimental results indicate that the HSEM model achieves superior accuracy in AC-OPF solutions compared to traditional Deep Neural Network (DNN) approaches. Furthermore, the HSEM demonstrates significant improvements in both the feasibility and constraint satisfaction of control variables. The effectiveness of the proposed HSEM is validated through rigorous testing on the IEEE-30 bus system and the IEEE-118 bus system, demonstrating its ability to provide an explainable warm-start point for solving AC-OPF problems.
A Reinforcement Learning-Based Dynamic Clustering of Sleep Scheduling Algorithm (RLDCSSA-CDG) for Compressive Data Gathering in Wireless Sensor Networks
Authors: El-Shenhabi Alaa N. , Abdelhay Ehab H. , Mohamed Mohamed A. , Moawad Ibrahim F.
Published: January 2025

Energy plays a major role in wireless sensor networks (WSNs), and measurements demonstrate that transmission consumes more energy than processing. Hence, organizing the transmission process and managing energy usage throughout the network are the main goals for maximizing the network’s lifetime. This paper proposes an algorithm called RLDCSSA-CDG, which is processed through the 3F phases: foundation, formation, and forwarding phases. Firstly, the network architecture is founded, and the cluster heads (CHs) are determined in the foundation phase. Secondly, sensor nodes are dynamically gathered into clusters for better communication in the formation phase. Finally, the transmitting process will be adequately organized based on an adaptive wake-up/sleep scheduling algorithm to transmit the data at the “right time” in the forwarding phase. The MATLAB platform was utilized to conduct simulation studies to validate the proposed RLDCSSA-CDG’s effectiveness. Compared to a very recent work called RLSSA and RLDCA for CDG, the proposed RLDCSSA-CDG reduces total data transmissions by 22.7% and 63.3% and energy consumption by 8.93% and 38.8%, respectively. It also achieves the lowest latency compared to the two contrastive algorithms. Furthermore, the proposed algorithm increases the whole network lifetime by 77.3% and promotes data recovery accuracy by 91.1% relative to the compared algorithms.
Algae-Based Coatings for Fully Bio-Based and Colored Textile Products
Authors: Blanckart Leon , Munasinghe Emalika Ayomani , Bendt Ellen , Rahaman Atiqur , Abomohra Abdelfatah , Mahltig Boris
Published: January 2025

Utilizing natural fibers for production of a fully bio-based textile is an appropriate approach to align with sustainability objectives. In case of dyed products, the used dye and further finishing agents also have to be bio-based. Algae-based materials are naturally colored and can be used as a natural dye product. The present study aims to investigate the use of algae materials as a color pigment for coating on cotton as a natural fiber material using a bio-based binder. Three different algae representing blue-green algae (BGA), unicellular microalgae (UNI), and filamentous algae (FIL) are investigated as colored additives for textile coatings. The algae are applied as powder to the coating recipe together with sodium alginate as binder component. Modification of the application is conducted by addition of calcium dichloride (CaCl2) acting as a crosslinker for the natural binder system. Using these applications, strong coloration of cotton fabrics can be achieved. Scanning electron microscopy (SEM), infrared spectroscopy (FT-IR), color measurements, light fastness tests, and tests on the rubbing fastness are performed. Good values in rubbing and light fastness are reached (4–5 and 5, respectively) depending on the used algae material and the addition of calcium dichloride. Applications using the algae BGA and UNI perform better due to light fastness. In contrast, applications with the filamentous algae FIL lead to better rubbing fastness. The present study confirms that the proposed technique and formulations are appropriate for achieving fully bio-based, naturally colored textile products, offering a promising foundation for further research into and development of the use of algae for the modification and functionalization of textile materials.
Structural Analysis of Inhibitor Binding to Enterovirus-D68 3C Protease
Authors: Azzolino Vincent N. , Shaqra Ala M. , Ali Akbar , Kurt Yilmaz Nese , Schiffer Celia A.
Published: January 2025

Enterovirus-D68 (EV68) continues to present as a global health issue causing respiratory illness and outbreaks associated with long-lasting neurological disease, with no antivirals or specific treatment options. The development of antiviral therapeutics, such as small-molecule inhibitors that target conserved proteins like the enteroviral 3C protease, remains to be achieved. While various 3C inhibitors have been investigated, their design does not consider the potential emergence of drug resistance mutations. For other antivirals where resistance has been a challenge, we have demonstrated that the likelihood of resistance can be minimized by designing inhibitors that leverage the evolutionary constraints of the target. Here, we characterize a series of 3C inhibitors against EV68-3C protease through enzyme inhibition, protein crystallography, and structural analysis. We have determined and analyzed three high-resolution inhibitor-bound crystal structures of EV68-3C protease, which revealed possible sites of resistance mutations, a key structural water molecule conserved during ligand binding, and the conformational flexibility of the catalytic histidine H40. This structural analysis combined with enzymatic assays provides insights for the rational design of inhibitors that are robust against resistance toward developing antiviral treatments for EV68 infections.
The Strategies Used by Animal Viruses to Antagonize Host Antiviral Innate Immunity: New Clues for Developing Live Attenuated Vaccines (LAVs)
Authors: Chen Na , Zhang Baoge
Published: January 2025

As an essential type of vaccine, live attenuated vaccines (LAVs) play a crucial role in animal disease prevention and control. Nevertheless, developing LAVs faces the challenge of balancing safety and efficacy. Understanding the mechanisms animal viruses use to antagonize host antiviral innate immunity may help to precisely regulate vaccine strains and maintain strong immunogenicity while reducing their pathogenicity. It may improve the safety and efficacy of LAVs, as well as provide a more reliable means for the prevention and control of infectious livestock diseases. Therefore, exploring viral antagonistic mechanisms is a significant clue for developing LAVs, which helps to explore more viral virulence factors (as new vaccine targets) and provides a vital theoretical basis and technical support for vaccine development. Among animal viruses, ASFV, PRRSV, PRV, CSFV, FMDV, PCV, PPV, and AIV are some typical representatives. It is crucial to conduct in-depth research and summarize the antagonistic strategies of these typical animal viruses. Studies have indicated that animal viruses may antagonize the antiviral innate immunity by directly or indirectly blocking the antiviral signaling pathways. In addition, viruses also do this by antagonizing host restriction factors targeting the viral replication cycle. Beyond that, viruses may antagonize via regulating apoptosis, metabolic pathways, and stress granule formation. A summary of viral antagonistic mechanisms might provide a new theoretical basis for understanding the pathogenic mechanism of animal viruses and developing LAVs based on antagonistic mechanisms and viral virulence factors.
Data Platform for Animal Mortality Information System (DATASIMA): Monitoring Companion Animal’s Euthanasia Causes in City of João Pessoa, Brazil
Authors: Sousa Eduardo S. S. , Sousa Maria E. S. , Pereira Moisés D. C. A. , Negreiros Ricardo A. M. , Eloy Lilian R. C. , Brasil Arthur W. L. , Clementino Inácio J. , Azevedo Sérgio S. , Lucena Ricardo B.
Published: January 2025

The literature regarding causes of animal mortality varies greatly in how it evaluates and describes reasons for euthanasia, showing a clear need for tools to identify, standardize, and map diseases. This study describes the application of the Animal Mortality Information System Database (DATASIMA) to monitoring and georeferencing animal mortality. An observational study was conducted on the dogs and cats euthanized at the Municipal Center for Environmental and Zoonotic Surveillance in João Pessoa, Paraíba. The deaths were reported through DATASIMA, an online platform created and developed in Brazil, which is aimed at observing animal mortality through the Animal Death Declaration between April and September 2022. A total of 403 euthanized animals were recorded, including 204 dogs and 199 cats. The most common diseases leading to euthanasia were as follows: (i) Sporotrichosis (171 cats); (ii) Leishmaniasis (75 dogs); (iii) Distemper (35 dogs); (iv) Trauma from vehicle collisions (ten dogs and nine cats). The DATASIMA platform proved to be an effective system for keeping records and reporting causes of animal mortality. Through georeferencing, it was possible to map areas with higher frequencies of zoonotic outbreaks in the municipality studied, thus providing useful data to implement health promotion strategies.
Effect of Bovine Serum Albumin (BSA) Concentration on Cryopreservation of Booroolong Frog Sperm with Evaluation of Post-Thaw Motility in Caffeine
Authors: Anastas Zara M. , Silla Aimee J. , Byrne Phillip G. , Hobbs Rebecca J. , McFadden Michael S. , Daly Jonathan , O’Brien Justine K.
Published: January 2025

Reproductive technologies, including sperm cryopreservation, offer conservationists enhanced capacity to genetically manage populations and improve the outcomes of conservation breeding programs (CBPs). Despite this potential, the post-thaw quality of amphibian sperm is highly variable following cryopreservation, and research focused on protocol refinement is needed. The aim of this study was twofold: (1) to investigate the effect of the addition of bovine serum albumin (BSA) to the cryopreservation medium (pre-freeze), and (2) the effect of the addition of caffeine to the activation medium (post-thaw), on post-thaw sperm characteristics in the critically endangered Booroolong frog (Litoria booroolongensis). Spermic urine samples were collected from 14 male frogs following hormonal induction of spermiation, and each sample was split among three cryopreservation treatments, where the cryopreservation medium contained either 0 (control), 0.5, or 1% BSA (w/v). Samples were cryopreserved and thawed, and sperm motility was then activated in one of two activation treatments: Milli-Q water (control) or Milli-Q water plus 4.5 mM caffeine. Sperm viability (proportion live/dead) was assessed using fluorescent microscopy, and sperm motility metrics were evaluated using computer-assisted sperm analysis (CASA). Results from this study showed that BSA concentration had no effect on post-thaw sperm viability. Additionally, neither BSA concentration nor activation in caffeine influenced post-thaw sperm motility characteristics (total motility, forward progressive motility, and velocity). Assessment time of sperm motility varied from 5 to 13 min post-activation and was significantly correlated with each motility measure, with motility and velocity metrics decreasing as time post-activation increased. The results reported herein provide no evidence for an effect of BSA or caffeine at the concentrations tested on post-thaw sperm characteristics in the Booroolong frog, but they highlight the time-sensitive nature of sperm assessment post-thaw and implications for the timing of sperm handling during assisted fertilisation efforts.
Correction: Salman, A. Field Trips and Their Effect on Student Learning: A Comparison of Knowledge Assessment for Physical versus Virtual Field Trips in a Construction Management Course. Virtual Worlds 2023, 2, 290–302
Authors: Salman Amna
Published: January 2025

In the original publication [...]
Shallow Hydrostratigraphy Beneath Marsh Platforms: Insights from Electrical Resistivity Tomography
Authors: Kelly Jacque L. , Hladik Christine M.
Published: January 2025

Salt marshes are ecologically and economically valuable ecosystems, yet are vulnerable to marsh dieback, the rapid death of marsh vegetation, which has affected coastal areas along the southeastern and Gulf coasts of the United States in recent decades. This study used multichannel electrical resistivity tomography (ERT) surveys to investigate the shallow hydrostratigraphy (up to 39.2 m depth) of three dieback-affected salt marshes along the Georgia coast to evaluate the influence of site location, vegetation status (dieback versus healthy), and tidal conditions on ERT profiles. ERT profiles revealed consistent subsurface resistivity patterns across the marsh platforms, with low resistivity (0.2 ohm-m) at shallow depths indicating saltwater saturation and a transition to higher resistivity (up to 8.1 ohm-m) at greater depths, potentially signifying a shift to brackish conditions and/or sandy strata. The ERT data indicated that the hydrostratigraphy is similar across all study sites. Furthermore, the ERT data remained consistent regardless of vegetation status, tidal variations, and seasonal changes, suggesting that the processes driving the recovery of marsh dieback are independent of the shallow marsh stratigraphy. These findings enhance our understanding of marsh subsurface conditions, supporting efforts to better understand marsh resilience and guide future research on salt marshes.
Mechanosensory Perception and Food Localisation in Pangasius nasutus Larvae: A Developmental Perspective
Authors:   Microalgae-Biota Technology and Innovation Group (ALBIC), Department of Aquaculture, Faculty of Agriculture, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor, Malaysia, SYUKRI FADHIL , ALIA NIK NOOR , ESA YUZINE , CHRISTIANUS ANNIE , SALEHUDIN FAIZ , ARSHAD AZIZ
Published: January 2025

Patin fish (Pangasius nasutus) larvae hatch with immature morphological features, but as the larvae grow, all their sensory organs develop rapidly. The objectives of this study were to observe the behaviour of P. nasutus larvae and evaluate the development of their sensory organs. The larvae's behaviour was observed from the time of hatching, while the development of sensory organs was examined through histology and scanning electron microscope (SEM) analysis. This study demonstrated that changes in larval behaviour were influenced by the development of their sensory organs. During the initial stages, at Day 1 after hatching (DAH), most of the sensory organs were not yet fully developed. As a result, the larvae remained at the bottom of the aquarium and swam in a vertical direction. However, as the sensory organs started to develop, their behaviour changed. They became more active and began to swim horizontally throughout the aquarium, exhibiting phototaxis. The increased number of taste buds facilitated easier food detection, while the presence of free neuromasts enabled the larvae to respond to water movement, exhibiting rheotaxis at 3 DAH, the day of their first feeding. Furthermore, the development of other sensory organs, such as larvae's retina, at this stage enhanced their ability to navigate. The study found that larvae primarily use mechanosensory perception to locate food. This reliance is due to the earlier development of taste buds and olfactory organs compared to other sensory organs, with the sensory organ of P. nasutus taking 21 days after hatching to fully develop.