bluuebunny/crossref_metadata_2025 huggingface dataset:
How Does the National Key Ecological Function Areas Policy Affect High-Quality Economic Development?—Evidence from 243 Cities in China
Authors: Zhang Yuqian , Su Chenchen , Xu Chen
Published: February 2025

Achieving a balance between environmental protection and high-quality economic development forms the cornerstone for fostering a harmonious coexistence between humanity and nature. Consequently, the interplay between these two domains has garnered extensive attention from various stakeholders. However, the current discourse on environmental policies tailored for high-quality economic development remains insufficiently robust. From a policy standpoint, we employ the difference-in-differences methodology to investigate whether China’s National Key Ecological Function Areas Policy, enacted in 2016, can catalyze high-quality economic development. Our findings reveal that this environmental policy has a notably positive influence on high-quality economic development. This effect is indirectly potentiated through increased investments in science and education, as well as the stimulation of consumer demand. Notably, the policy effect varies by region. To ensure a steady enhancement of the policy’s effectiveness, it is imperative to implement differentiated measures tailored to the unique characteristics of different regions, thereby fostering coordinated development. Furthermore, we anticipate that our study will offer empirical insights and data-driven examples for the implementation of environmental policies in developing countries.
Spatiotemporal Evolution Mechanism and Spatial Correlation Network Effect of Resilience in Different Shrinking Cities in China
Authors: Yu Weijun , Zhang Siyu , Pang Entao , Wang Huihui , Yang Yunsong , Zhong Yuhao , Jing Tian , Zou Hongguang
Published: February 2025

Bolstering the resilience of shrinking cities (SCs) is essential for maintaining urban dynamic security and fostering sustainable development. Accurately assessing and revealing the resilience level and impact mechanism of SCs to cope with disturbances and shocks has become a hot topic of research in urban sustainable development. In this research, we presented a systematic conceptualization of the fundamental components of urban shrinkage (US) and urban resilience (UR) and, based on US and UR theories, constructed a methodological framework aimed at investigating the spatiotemporal evolution mechanism and spatial correlation network effect of resilience in different SCs in China. This paper initially evaluates the UR levels of various types of SCs in China by establishing an evaluation model for US and a multidimensional evaluation index system for UR based on the theoretical frameworks, aligned with the national context in China. We also define the spatiotemporal evolution patterns of UR for different types of SCs. Subsequently, this paper employs a coupled coordination model and a geographical detector model to elucidate the influencing mechanisms on UR of different types of SCs, focusing on UR subsystems and indicators. Finally, this paper empirically examines the spatial correlation network effects of UR under various US scenarios using a social network analysis model. The results show that many SCs have progressively adjusted to the challenges posed by US, and the UR of SCs has shown an upward trend from 2010 to 2021. Cities with higher US levels generally show lower coordination in UR subsystems. The comprehensive utilization rate of industrial solid waste and road freight per capita are crucial for improving the UR of cities with higher US levels. Moreover, US probably strengthens UR connections between cities, facilitating resilience transmission and dissemination. These findings advance UR research within the US framework and offer theoretical foundations and planning guidance for environmentally friendly and high-quality development in shrinking cities.
LSAF-LSTM-Based Self-Adaptive Multi-Sensor Fusion for Robust UAV State Estimation in Challenging Environments
Authors: Irfan Mahammad , Dalai Sagar , Trslic Petar , Riordan James , Dooly Gerard
Published: February 2025

Unmanned aerial vehicle (UAV) state estimation is fundamental across applications like robot navigation, autonomous driving, virtual reality (VR), and augmented reality (AR). This research highlights the critical role of robust state estimation in ensuring safe and efficient autonomous UAV navigation, particularly in challenging environments. We propose a deep learning-based adaptive sensor fusion framework for UAV state estimation, integrating multi-sensor data from stereo cameras, an IMU, two 3D LiDAR’s, and GPS. The framework dynamically adjusts fusion weights in real time using a long short-term memory (LSTM) model, enhancing robustness under diverse conditions such as illumination changes, structureless environments, degraded GPS signals, or complete signal loss where traditional single-sensor SLAM methods often fail. Validated on an in-house integrated UAV platform and evaluated against high-precision RTK ground truth, the algorithm incorporates deep learning-predicted fusion weights into an optimization-based odometry pipeline. The system delivers robust, consistent, and accurate state estimation, outperforming state-of-the-art techniques. Experimental results demonstrate its adaptability and effectiveness across challenging scenarios, showcasing significant advancements in UAV autonomy and reliability through the synergistic integration of deep learning and sensor fusion.
Addressing Due Date and Storage Restrictions in the S-Graph Scheduling Framework
Authors: Bakon Krisztián Attila , Holczinger Tibor
Published: February 2025

This paper addresses the Flexible Job Shop Scheduling Problem (FJSP) with the objective of minimizing both earliness/tardiness (E/T) and intermediate storage time (IST). An extended S-graph framework that incorporates E/T and IST minimization while maintaining the structural advantages of the original S-graph approach is presented. The framework is further enhanced by integrating linear programming (LP) techniques to adjust machine assignments and operation timings dynamically. The following four methodological approaches are systematically analyzed: a standalone S-graph for E/T minimization, an S-graph for combined E/T and IST minimization, a hybrid S-graph with LP for E/T minimization, and a comprehensive hybrid approach addressing both E/T and IST. Computational experiments on benchmark problems demonstrate the efficacy of the proposed methods, with the standalone S-graph showing efficiency for smaller instances and the hybrid approaches offering improved solution quality for more complex scenarios. The research provides insights into the trade-offs between computational time and solution quality across different problem configurations and storage policies. This work contributes to the field of production scheduling by offering a versatile framework capable of addressing the multi-objective nature of modern manufacturing environments.
Anterior Cruciate Ligament Reconstruction Using Lateral Extra-Articular Procedures: A Systematic Review
Authors: Migliorini Filippo , Lucenti Ludovico , Mok Ying Ren , Bardazzi Tommaso , D’Ambrosi Riccardo , De Carli Angelo , Paolicelli Domenico , Maffulli Nicola
Published: February 2025

Background and Objectives: The present systematic review investigated the efficacy of lateral extra-articular tenodesis (LET) and anterolateral ligament (ALL) as lateral extra-articular procedures (LEAPs) for anterior cruciate ligament (ACL) reconstruction. ACL reconstruction using LEAP may reduce graft rupture and rotatory laxity and allow a quicker return to sports. The outcomes of interest were patient-reported outcome measures (PROMs), return to sport, laxity, failure rate, and safety profile. Materials and Methods: The present systematic review followed the 2020 PRISMA guidelines. In December 2024, PubMed, EMBASE, and Web of Science were accessed without constraints. All clinical investigations evaluating LEAP for ACL reconstruction were considered. Only studies that considered LET and ALL as LEAP were considered. Only studies using a hamstring tendon autograft associated with LET or ALL were considered. Results: Data from 27 clinical studies (3423 patients) were retrieved. The mean length of follow-up was 61.8 ± 39.5 months. ACL reconstruction using LEAP led to a statistically significant improvement in the Lysholm score (p < 0.01) and IKDC (p < 0.01). The mean joint laxity, as measured by the arthrometer, was 1.5 ± 1.8 mm. Finally, 72.3% (623 of 668) of patients returned to their pre-injury level of sport at a mean of 6.3 ± 4.4 months. At the last follow-up, the LET group showed greater IKDC (p = 0.04). On the other hand, there was a statistically significant greater rate of patients positive to the Lachman test (p < 0.01), return to sport (p < 0.01), and reoperation (p = 0.01). No significant differences were found in Lysholm scores (p = 0.6), Tegner scores (p = 0.2), arthrometer measurements (p = 0.2), Pivot shift test results (p = 0.1), time to return to sport (p = 0.3), and failure rates (p = 0.7). Conclusions: LEAP for ACL reconstructions seems to be effective and safe. Most patients returned to their pre-injury level of sport after a mean of 6 months. LET-based ACL reconstruction may be associated with greater clinical outcomes and a higher reoperation rate compared to ALL-based reconstruction.
Late-Onset Myocarditis Following Immune Checkpoint Inhibitors Therapy: A Case Series with Literature Review
Authors: Muğlu Harun , Sünger Erdem , Köylü Bahadır , Tunalı Didem , Erol Cengiz , Selcukbiricik Fatih , Bilici Ahmet , Olmez Omer Fatih
Published: February 2025

Immune checkpoint inhibitors (ICIs) therapy has revolutionized cancer treatment. However, it is important to acknowledge that ICI therapy can lead to immune-related adverse events (irAEs), including myocarditis. While early-onset myocarditis is well-documented, late-onset cases are increasingly recognized. This case series presents four cases of late-onset ICI-associated myocarditis, emphasizing the need for long-term surveillance of this potentially fatal complication. Patients exhibited a range of cardiac symptoms, including chest pain, shortness of breath, and arrhythmias. The diagnosis was confirmed through cardiac magnetic resonance imaging (MRI) and elevated cardiac biomarkers. Treatment involved the immediate discontinuation of ICI therapy and the initiation of high-dose corticosteroids. In cases with an inadequate response, additional immunosuppressive agents were considered. This case series underscores the importance of prolonged monitoring for late-onset ICI-associated myocarditis. Further research is needed to establish optimal treatment strategies and long-term management approaches for this complex condition.
Rheumatoid Arthritis Prevalence and Risk Factors in Korean Adults: A Focus on Age and Sex Differences
Authors: Lee Do-Youn
Published: February 2025

Rheumatoid arthritis (RA) is a chronic autoimmune disorder that affects the joints, causing swelling, pain, stiffness, and functional decline. This study aims to clarify the prevalence and risk factors of RA based on sex and age among Korean adults, providing essential data for targeted prevention and management strategies. We analyzed data from the Korea National Health and Nutrition Examination Survey 2016–2021, comprising 25,166 participants aged 20 and older. Sociodemographics, health status, and behavior factors were evaluated, with RA defined based on self-reported diagnosis. A complex sampling design was utilized to ensure representative results and multiple logistic regression was employed to determine the risk factors linked to RA. The overall prevalence of RA among Korean adults was 1.1%, showing a significant sex-based disparity: 0.6% and 1.7% in men and women, respectively. RA prevalence increased with age, peaking at 3.5% in individuals over 70. This study identified education level, subjective health status, and age as key predictors of RA. Among men, significant predictors of RA included education level and subjective health status, with a higher risk observed in men with only elementary education and poor perceived health. For women, age and subjective health status were the main risk factors, with RA risk increasing markedly in older age groups, particularly in those aged 70 and above. This study highlights the distinct prevalence and risk factors for RA among Korean adults by sex and age. Key predictors—education level, subjective health status, and age—suggest that tailored health interventions addressing these factors are crucial to reducing the RA burden and enhancing health outcomes among affected populations.
Isolation and Characterization of Carbonosomes from Pseudomonas sp. phDV1 Grown Using Phenol as Carbon Source
Authors: Geladas Ermis Dionysios , Lyratzakis Alexandros , Drakonaki Athina , Gkikas Georgios , Tsiotis Georgios
Published: February 2025

The Pseudomonas sp. strain phDV1 was found to utilize monocyclic aromatic compounds as a sole carbon source and has a variety of potential applications in the bioremediation and biosynthesis of biodegradable plastics. It was possible to produce polyhydroxybutyrate when cultivated in the presence of monocyclic aromatic compounds as the sole carbon source. This study provides the small-scale optimization for phenol bioremediation and polyhydroxybutyrate production. The bacterium was cultivated in minimal medium supplemented with different concentrations of phenol. The formation and localization of the polyhydroxybutyrate granules (carbonosomes) in the cell were determined after 72 h of cultivation using Nile Red stain in combination with fluorescence microscopy. Analytical HPLC was also used to quantify the PHB content in the cells and to optimize the production. Finally, comparative proteomic analysis of isolated carbonosomes was used to characterize of their protein composition.
Enhanced Capacitive Performance of Microwave-Driven CNTs on Carbonized Cigarette Filter Waste for Sustainable Energy Storage
Authors: Choi Young Joong , Lee Damin , Kwon Se-Hun , Kim Kwang Ho
Published: February 2025

Microplastic pollution represents a significant global environmental issue, with cigarette filters being a major contributor due to their slow biodegradation. To address this issue while creating valuable materials, we developed a novel approach to synthesize nitrogen-doped carbon nanotubes on carbonized cigarette filter powder (NCNT@cCFP) using a microwave irradiation and nickel-catalyzed process. The successful incorporation of nitrogen (~6.6 at.%) and the enhanced graphitic structure create a hierarchical conductive network with abundant active sites for electrochemical reactions. The resulting NCNT@cCFP electrode exhibits a specific capacitance of 452 F/g at 1 A/g in a three-electrode configuration. The integrated hierarchical structure facilitates efficient electron transport and ion diffusion, leading to excellent rate capability (91.6% at 10 A/g) and cycling stability (96.5% retention after 5000 cycles). Furthermore, a symmetric supercapacitor device demonstrates promising energy storage capability with a maximum energy density of 14.0 Wh/kg at 483.1 W/kg, while maintaining 10.4 Wh/kg at a high power density of 4419.1 W/kg. This synergistic waste recycling strategy combined with microwave-driven synthesis offers a sustainable pathway for developing high-performance energy storage materials.
β-Lactam/β-Lactamase Inhibitor Combination Antibiotics Under Development
Authors: Katsarou Angeliki , Stathopoulos Panagiotis , Tzvetanova Iva D. , Asimotou Christina-Maria , Falagas Matthew E.
Published: February 2025

Antimicrobial resistance remains a public health problem of global concern with a great health and financial burden. Its recognition as a threat by political leadership has boosted the research and development of new antibiotics and particularly novel combinations of β-lactams/β-lactamase inhibitors against multidrug-resistant (MDR) Gram-negative pathogens, which remain the major concern in clinical practice. The incorporation of ceftolozane/tazobactam, ceftazidime/avibactam, meropenem/vaborbactam, and imipenem/cilastatin/relebactam has provided new therapeutic options in the treatment of patients with infections due to MDR pathogens. Cefiderocol along with cefepime/enmetazobactam, avibactam/aztreonam, and sulbactam/durlobactam have been recently added to these agents as therapeutic choices, particularly for metallo-β-lactamase producing Gram-negative bacteria. Currently, many combinations are being studied for their in vitro activity against both serine- and metallo-β-lactamases. However, only a few have advanced through phase 1, 2, and 3 clinical trials. Among them, in this article, we focus on the most promising combinations of cefepime/zidebactam, cefepime/taniborbactam, and imipenem/cilastatin/funobactam, which are currently under investigation in phase 3 trials.
The Prevalence of Schistosoma haematobium and Its Impact on the Hematological Profile of Children Living in Northern Madagascar
Authors: Wilczyńska Wanesa , Kasprowicz Daniel , Świetlik Dariusz , Korzeniewski Krzysztof
Published: February 2025

Schistosomiasis is a parasitic disease that is considered a major threat to public health in Madagascar. The condition is endemic in more than 90% of the country’s districts. It is estimated that as much as 52% of the country’s general population is infected with Schistosoma spp. trematodes. The aim of the present study was to assess the prevalence values of Schistosoma haematobium infections in a population of children living in northern Madagascar and to determine the impact of trematode infections on the hematological profiles of the children included in the study. This screening study was conducted in 2024, and it involved a group of 170 children aged 0–17 years. The participants were required to provide urine samples for microscopic and molecular examination. The urine samples were preserved on Whatman 903 protein sever cards using the dried urine spot (DUS) sampling technique and then were transported from Madagascar to a molecular laboratory in Poland, where the samples were tested for the presence of S. haematobium. The present study found that the incidence of S. haematobium infections in the study group consisting of 170 children was as high as 67.6%. The authors observed a reduction in mean hemoglobin (Hb) and mean corpuscular hemoglobin concentration (MCHC) values in the infected children. In spite of continuous efforts to prevent the transmission of schistosomiasis in endemic countries (WHO-recommended mass drug administration campaigns), the incidence of S. haematobium infections was found to be exceptionally high among the study participants. S. haematobium infections present with a characteristic hematological picture showing signs of increased immune response and anemia. The DUS technique has been successfully used for the molecular diagnosis of S. haematobium. This method opens up possibilities for more effective and less expensive sample collection.
Predictive Value of STC2 Gene Expression in Chemotherapy Response in Breast Cancer
Authors: Muñoz Juan P. , Lampe-Huenul Nicolás
Published: February 2025

Background: Breast cancer is the most commonly diagnosed cancer among women, and resistance to chemotherapy presents a significant challenge in its treatment. Stanniocalcin-2 (STC2), a glycoprotein involved in calcium homeostasis and cellular stress responses, is frequently overexpressed in various human cancers. Despite its critical role in cellular adaptation to stress, the potential of STC2 as a biomarker for predicting chemotherapy response has not been evaluated. This study aimed to assess the potential of STC2 as a predictive biomarker of response to chemotherapy in breast cancer. Methods: We utilized publicly available databases to characterize STC2 expression in breast cancer patients and its role in predicting relapse-free survival (RFS). Moreover, we evaluated the treatment responses of patients subjected to chemotherapy, correlating their outcomes with STC2 expression levels to determine its potential as a predictive biomarker. Finally, we evaluated the STC2 expression levels in breast cancer cell lines following exposure to doxorubicin (Dox), the primary anthracycline used in chemotherapy, and they were contrasted with the publicly available dataset. Results: The analysis showed that STC2 is significantly overexpressed in luminal A breast cancer, where it is linked to genetic amplifications. High STC2 expression was associated with improved RFS in ER-positive patients but correlated with worse outcomes in ER-negative cases. Furthermore, in grade II ER-positive patients, higher STC2 expression is linked to better chemotherapy response, while in grade II ER-negative patients, it was associated with poorer response. Finally, STC2 downregulation was observed in response to Dox treatment. Conclusions: These findings suggest that STC2 expression serves as a predictive biomarker for chemotherapy response in grade II breast cancer patients.
Oral Administration of Neratinib Maleate-Loaded Lipid–Polymer Hybrid Nanoparticles: Optimization, Physical Characterization, and In Vivo Evaluation
Authors: Mahajan Radhika Rajiv , Ravi Punna Rao , Jadhav Sakshi , Pansuriya Prinsi Kishorbhai , Naik Bhushan Gopalsing , Anture Shalaka Hanmant , Szeleszczuk Łukasz
Published: February 2025

Background: Neratinib maleate (NM), a tyrosine kinase inhibitor, is used in the treatment of breast cancer. Current oral therapy of NM suffers from low and variable bioavailability due to the solubility and permeability-related issues of the drug. To overcome the low oral bioavailability, the drug is recommended to be administered at high doses, causing severe gastrointestinal side effects leading to discontinuation of the drug therapy. Methods: In this work, NM-loaded lipid–polymer hybrid nanoparticles (NM-LPNs) were designed and optimized to improve the oral bioavailability of the drug. A systematic approach involving a screening design followed by an optimization design based on the principles of design of experiments (DoE) was used to prepare NM-LPNs. Minimum particle size (PS) ranging between 200 and 300 nm and maximum drug loading (DL (%)) were set as the target physicochemical properties. The optimized NM-LPNs, with a mean PS of 278.57 ± 21.16 nm and a DL (%) of 25.77 ± 1.11%, were further characterized for physicochemical properties, thermal and diffractometric analysis, stability, in vitro drug release, and oral pharmacokinetic studies. Results: The nanoparticles exhibited a burst release followed by a prolonged release up to 12 h in the in vitro drug release studies in pH 6.8 media. Conclusions: The mean Cmax and the AUClast values were found to increase significantly for NM-LPNs by 1.72 times (p < 0.01) and 1.58 times (p < 0.01), respectively, when compared to plain NM in the oral pharmacokinetic studies. The optimized NM-LPN formulation can reduce the oral dose of NM and, thereby, its dose-dependent side effects.
The Co-Administration of Paclitaxel with Novel Pyridine and Benzofuran Derivatives that Inhibit Tubulin Polymerisation: A Promising Anticancer Strategy
Authors: Perużyńska Magdalena , Birger Radosław , Kłos Patrycja , Kwiecień Halina , Struk Łukasz , Sośnicki Jacek G. , Lafanechère Laurence , Droździk Marek
Published: February 2025

Background: Paclitaxel (PTX), a crucial microtubule-stabilising agent in cancer treatment, is limited by its adverse effects and hydrophobic nature, which necessitate the use of toxic solvents. This study proposes a novel approach combining PTX with new microtubule-destabilising compounds at low, safe doses that are ineffective when used individually. Objective: The aim was to evaluate the therapeutic efficacy of combining PTX with previously described pyridine (S1, S22) and benzofuran derivatives (13b, 14), which have demonstrated promising anticancer properties by inhibiting microtubule polymerisation. Methods: The PrestoBlue assay was used to determine the optimal concentrations of each compound, enabling synergistic interactions with a low dose of PTX in HeLa cervical cancer cells. The combined effects of the compounds and PTX on apoptosis, cell cycle distribution, and mitotic spindle formation were then evaluated. Results: The results showed that compounds 13b (1 µM), 14 (0.1 µM), S1 (2 µM), and S22 (2 µM) enhanced the proapoptotic and antimitotic effects of 1 nM PTX, which was ineffective alone. Notably, live-cell imaging revealed that the concurrent use of S1 and PTX produced effects similar to those of a higher PTX concentration (5 nM). Conclusions: These findings suggest that these compounds enhance the anticancer efficacy of low-dose PTX, potentially paving the way for more effective and safer cancer therapies.
Technical Advancements and Applications in Predictive Modeling of Polyurethane Foaming Height
Authors: Kuo Chil-Chyuan , Lu Yi-Qing , Farooqui Armaan , Huang Song-Hua
Published: February 2025

Various polyurethane foams (i.e., rigid, flexible, and spray polyurethane foams) offer diverse applications due to their unique properties, including thermal insulation, cushioning, and seamless gap filling. These foams provide solutions across industries such as construction, automotive, and refrigeration. However, the foaming process presents several challenges that may result in various defects in the final products. This work provides innovative predictive techniques for polyurethane foam expansion and applications in advanced manufacturing processes. The foaming height of the third polyurethane foaming agent (PU-3) closely aligned with the experimentally measured values. The relationship between foaming height and time is influenced by the type and concentration of catalysts, as well as the blowing agents used. However, simulations using Moldex 3D Version 2024 revealed a nonlinear relationship between foaming height and time, characterized by three distinct foaming rates. Zone B demonstrated the highest foaming rate, followed by Zone C, while Zone A showed the lowest rate. The foaming height and rate were significantly influenced by the foaming angle, with smaller angles enhancing both parameters. At a mold temperature of 30 °C and with an expansion coefficient of 35, the predicted foaming height of the polyurethane agent achieved an average accuracy of approximately 96% across four foaming angles. Based on these experimental findings, this study introduces three mechanisms involved in the foaming process of polyurethane foam components.
Electron-Shuttling Characteristics of Cassia obtusifolia Seed Extracts and Antiviral Activities of Anthraquinone Compounds Through In Silico Studies
Authors: Tiongson Stephanie Claire M. , Chen Bor-Yann , De Castro-Cruz Kathlia A. , Hsueh Chung-Chuan , Lien Yeh , Tsai Po-Wei
Published: February 2025

Previous studies have linked the electron-shuttling properties of Traditional Chinese Medicine (TCM) species to antiviral efficacy. This study explores the antiviral potential of Cassia obtusifolia seeds through electrochemical analyses using microbial fuel cells (MFCs) and cyclic voltammetry (CV) complemented by in silico methods. The phytochemical contents and antioxidant activity of Cassia seed extracts were assessed and correlated with bioenergy generation and electrochemical stability. A principal component analysis (PCA) indicated that phytochemical and antioxidant activity influence Cassia’s power-generating potential. The MFC study revealed a 1.87-fold power amplification in unprocessed Cassia seed water extract (CTS-W), while CV analysis demonstrated enhanced electrochemical stability and reversibility due to the presence of electron-shuttling (ES) species. In silico analyses, including network pharmacology and molecular docking, provided supporting evidence for the antiviral potential of bioactive metabolites in Cassia seeds, particularly in targeting Hepatitis B virus-related genes. Furthermore, a mathematical model highlighted the superior therapeutic efficacy of electron-shuttling (ES) species compared to antioxidants in disease treatment. These findings demonstrate a strong correlation between the electron-shuttling properties and the antiviral potential of C. obtusifolia seed extracts, suggesting that bioenergy-mediated mechanisms may play a crucial role in the development of effective antiviral therapies.
Esterification of Kenaf Core Fiber as a Potential Adsorbent for Oil Removal from Palm Oil Mill Effluent (POME)
Authors: Alias Nor Halaliza , Abdullah Luqman Chuah , Yaw Thomas Choong Shean , Jamil Siti Nurul Ain Md , Ting Teo Ming , Asis Ahmad Jaril , Lee Chuan Li , Adeyi Abel Adekanmi
Published: February 2025

Palm oil mill effluent (POME) is a major contributor to industrial oily wastewater in Malaysia, demanding effective treatment solutions. This study explores the potential of esterified kenaf core (EKC) fiber as an oil adsorbent for oil removal from POME, optimized using a full central composite design (CCD) within the response surface methodology (RSM) framework. The optimum conditions achieved 76% oil removal efficiency, with a 1:0.5 ratio of mercerized kenaf core to stearic acid (MKC:SA), 15 wt% of catalyst, and 1 h reflux time during the esterification process. The regression model exhibited strong predictive capability, with a significant quadratic correlation and an R2 value of 0.94. The Fourier transform infrared (FTIR) spectroscopy revealed the existence of ester functional groups characterized by significant hydrophobicity and a decrease in hydroxyl groups, indicating the chemical changes of EKC. Moreover, the scanning electron microscopy (SEM) research demonstrated structural alterations in EKC, including heightened surface roughness, fibrillation, and pore development, which improved oil adhesion relative to raw kenaf core (RKC). These findings indicate that EKC provides an effective, environmentally sustainable solution for managing oil wastewater issues in the palm oil sector, facilitating enhanced ecological sustainability and resource management.
Intelligent Micro-Kick Detection Using a Multi-Head Self-Attention Network
Authors: Zhang Dezhi , Sun Weifeng , Dai Yongshou , Wang Dongyue , Guo Yanliang , Gong Chentao
Published: February 2025

Accurate micro-kick detection is crucial for blowout accident preventions. The more drilling parameters that change due to kicks, the more accurate the warning results become. However, when the micro-kick occurs, there is a significant time lag between these parameter changes. Dominant kick detection methods based on long short-term memory (LSTM) forget early parameter trends when dealing with long time series. To improve the recognition accuracy of micro-kicks and avoid potential blowout accidents by memorizing the early or long-term trends in drilling parameters, an intelligent micro-kick detection method based on a multi-head self-attention network is proposed. First, a novel multi-head structure is designed to separate various types of features due to different monitoring parameter changes at different speeds or trends. Second, a self-attention mechanism is employed to focus on parameter changes in separated monitoring data sequences. Then, a feed-forward network with parallel computation capability is utilized to analyze long-range correlations, thus avoiding the loss of early or long-term trend information. Finally, an artificial neural network is used to establish nonlinear relationship models between the trend features of each monitoring parameter and kick accidents. The experiment results demonstrate that the recognition accuracy of the proposed micro-kick detection method is 7.9% higher than that of the LSTM-based method.
Investigation and Optimization of Existing Laminar Flame Velocity Reaction Mechanisms in NH3 and NH3/H2 Flames
Authors: Xu Shaowen , Liu Zhigang , Chen Huiming , Chao Yun , Xu Liang
Published: February 2025

With the increasing greenhouse effect and energy crisis, ammonia is one of the most promising alternative fuels. However, the research on the combustion characteristics of ammonia needs to be further improved. In this paper, the combustion characteristics of two kinds of ammonia and ammonia–hydrogen amino fuels (laminar flame velocity) are investigated through experimental data and kinetic mechanism analysis, and the laminar flame predictions are calculated for 20 kinds of ammonia mechanisms with different equivalence ratios, oxygen contents, and hydrogen doping ratios, after which MAPE and sensitivity analysis are used to determine the applicability of the mechanisms. The results indicate that the incorporation of hydrogen and the augmentation of oxygen concentration induce exponential and linear increases in the laminar flame speed of ammonia, respectively. The laminar flame speed of ammonia reaches its maximum at an equivalence ratio of approximately 1.1, with a value ranging from 6 to 7 cm/s. Under a hydrogen addition ratio of 0.4, the laminar flame speed of ammonia even reaches 29–30 cm/s. The Otomo and Zhang mechanisms are recommended for ammonia fuels with different equivalence ratios and oxygen contents. For different equivalence ratios and hydrogen doping ratios of ammonia–hydrogen combustion, the Gotama and Stagni mechanisms are more suitable. For the overall conditions, the Zhang mechanism is recommended in this paper to simulate the laminar flame velocity for ammonia and ammonia–hydrogen mechanisms. Based on the Glarborg mechanism, an optimized mechanism is proposed to simulate the laminar flame velocity for both fuels, which reduces to 9.55% compared to 43% for the average calculation error of the original mechanism.
Use of Wastewaters from Ethanol Distilleries and Raw Glycerol for Microbial Oil Production
Authors: Faife Evelyn , Ochoa Nayra , Xu Jingyang , Liu Dehua , Du Wei , Díaz Manuel , Aguilar-Uscanga María Guadalupe
Published: February 2025

The production of biodiesel from single-cell oils (SCOs) utilizing industrial wastes as feedstock presents an economically viable approach. To date, studies have rarely reported the utilization of vinasse combined with industrial glycerol for the production of SCO. This study aimed to assess the performance of a Rhodotorula toruloides strain in vinasse from ethanol distilleries supplemented with pure/raw glycerol as an affordable carbon feedstock for SCO production. Several critical factors, including the C/N ratio, the impact of impurities in the crude glycerol, the proper nitrogen source, and the effects of the vinasse compositions, were evaluated. The results showed that the incorporation of urea and raw glycerol increased the lipid content to 51.8 ± 1.6% and the lipid productivity to 0.034 ± 0.001 g L−1h−1. Elevated biomass (42.5 g L−1) and lipid (11.0 g L−1) concentrations indicated that impurities in the raw glycerol positively affected the growth and lipid accumulation of this strain. Notably, supplementing raw glycerol to the vinasse led to a 16.1% increase in biomass concentration and a 25.7% rise in lipid content, significantly enhancing lipid productivity by 59.6%. The fatty acid profile predominantly featured unsaturated fatty acids (96.8%), including high percentages of stearic acid (41.8 ± 2.6%), palmitic acid (21.8 ± 1.5%), and oleic acid (18.3 ± 1.4%), aligning with the standards for vegetable-oil-based biodiesel manufacture. Fed-batch strategies using pulse-feeding turned out to be less effective than the constant-flow feeding strategy with vinasse supplemented with raw glycerol, which achieved a higher lipid productivity of 0.30 g L−1h−1.
Industrial Compressor-Monitoring Data Prediction Based on LSTM and Self-Attention Model
Authors: Pu Liming , Zhang Lin , Liu Jie , Qiu Limin
Published: February 2025

The compressor is a critical component of cryogenic separation industrial systems, and its reliable operation is essential for the stable functioning of the entire system. Existing research focuses on predicting compressor conditions using experimental or simulation data, often neglecting analysis based on actual industrial data. To address this gap, this paper presents an innovative prediction model for compressor data utilizing an LSTM–self-attention mechanism, specifically designed for real industrial systems. The proposed model combines the sequential learning capabilities of LSTM with the dynamic feature extraction strengths of self-attention, enabling highly accurate predictions by enhancing sensitivity to critical data features. The actual vibration data from a compressor spanning 12 months are analyzed and compared. The results demonstrate that the proposed model reduces prediction error by 46% in MSE and 50% in RMSE compared to SVR. These findings highlight the model’s potential for real-time monitoring and early fault detection, providing a robust theoretical foundation for condition-based analysis and preventive maintenance in industrial compressor applications.
Research on Single-Phase Grounding Fault Line Selection in Resonant Grounding System Based on Median Complementary Ensemble Empirical Mode Decomposition and Multiscale Permutation Entropy Normalization and K-Means Algorithm
Authors: Li Yueheng , Li Chen , Cao Wensi
Published: February 2025

When a single-phase grounding fault occurs in a resonant grounding system, due to the compensation effect of the arc coil on the system, there are problems such as the fault signal amplitude and the signal waveform being close, which leads to difficulties in line selection. This paper proposes a fault line selection discrimination method based on MCEEMD-MPE normalization and a k-means clustering analysis algorithm. The method is applied to the single-phase grounding fault of a resonant grounding system. The zero-sequence current is obtained and decomposed by MCCEEMD to obtain a number of components. The components with obvious characteristics are selected for normalization calculation by multi-scale permutation entropy, which not only avoids mode aliasing, but also highlights the characteristics of the fault signal at different scales. Finally, the k-means clustering analysis algorithm is used to correctly distinguish the fault and non-fault lines. The effectiveness of the method is verified in a real test field case. The results of the calculation show that the method can accurately identify the fault line under different faults when a single-phase grounding fault occurs. The recognition accuracy is 100%, which effectively improves the grounding fault line selection rate of the resonant grounding.
Multirotor UAV—A Multidisciplinary Platform for Teaching Mechatronics Engineering
Authors: Kotarski Denis , Pranjić Marko , Alharbat Ayham , Piljek Petar , Bjažić Toni
Published: February 2025

This paper provides a comprehensive guide for educators on how multirotor UAV platforms can be utilized to achieve various learning outcomes in undergraduate mechatronics education. This study is based on a PX4 ecosystem combined with the MATLAB Simulink programming environment, covering both hardware and software aspects to support engineering education. The paper explains (i) which learning outcomes can be obtained, (ii) how mathematical models can be derived and implemented in simulation software, (iii) which hardware components are essential, their approximate costs, and possible upgrades based on available budgets, and (iv) which experiments students can perform using the UAV platform. A proposed educational prototype integrates airframe parts produced using additive manufacturing technologies with standard multirotor components. Additionally, a series of experiments were designed, including extensive testing of the multirotor control module. Three learning outcomes related to UAV hardware were incorporated into the engineering curriculum, while two software-related outcomes were addressed through student workshops. Future plans include the implementation of multiple UAV platforms in the educational process to further enhance learning outcomes.
Frequency Response and Material Property Sensitivity Analysis of Moving-Coil Geophone Using Finite Element Simulation
Authors: Yang Zesheng , Xue Qingfeng , Yao Yi , Wang Yibo
Published: February 2025

In the process of unconventional oil and gas production, a large number of microseismic signals are generated. These signals are received by geophones deployed on the ground or in wells and used for safety monitoring. The moving-coil geophone is a commonly used geophone, which is widely used for collecting vibration signals. However, the current conventional moving-coil geophones have certain limitations in terms of frequency band range and cannot fully meet the low-frequency requirements of microseismic signals. We studied the structure and material properties of moving-coil geophones to understand the factors that affect their frequency band. In this paper, we use finite element analysis method to perform structural analysis on a 10 Hz moving-coil geophone, and we combine modal analysis and excitation response analysis to obtain its operating frequency range of 10.63–200.68 Hz. We then discuss the effect of the vibrating components of a moving-coil geophone on its operating frequency range. The material properties of the spring sheet mainly affect the natural frequency of the first-order mode (natural frequency, the lower limit of the operating frequency of the geophone), and the material properties of the lead spring mainly affect the natural frequency of the second-order mode (spurious frequency, the upper limit of the operating frequency of the geophone). By analyzing the sensitivity of the material properties of the vibration system parts and selecting more suitable spring sheets and lead spring materials, a lower natural frequency and a higher spurious frequency can be obtained, thereby achieving the purpose of broadening the operating frequency range of the geophone, which is expected to provide help in actual production.
Augmented Reality for Therapeutic Education in Patients with Diabetes: Short- and Mid-Term Learning Benefits
Authors: Calle Marcelo , Abad Francisco , Juan M.-Carmen
Published: February 2025

This work aims to evaluate the effectiveness of knowledge transfer through an Augmented Reality (AR) application, assessing short- and mid-term retention in children and adults with Type 1 diabetes. One objective is to determine if the AR application helps patients learn about the carbohydrate content of different foods (N = 27 Ecuadorian patients). Another objective is to evaluate the usability and satisfaction perceived by the patients. An additional objective is to compare the data from our study in Ecuador with data from a similar study conducted with Spanish children (N = 42). The results show that the AR application is effective for short-term knowledge transfer (p < 0.001) and has a suggestively significant effect on mid-term retention (p < 0.05). The AR application had an equalizing effect on knowledge outcomes between the groups (Ecuador and Spain) despite initial differences. The AR application significantly increased patients’ knowledge (p < 0.001) and was effective for both children and adults. Patient satisfaction was high, and learning outcomes were not influenced by age or gender. The AR application is effective for short-term knowledge transfer and mid-term retention, benefiting children and adults regardless of gender. The patients’ experience was very positive. Therefore, the AR application is a valuable tool for therapeutic education in diabetes since it offers support that is easily accessible on mobile devices, enabling autonomous learning, and it contributes to the creation of innovative, patient-centered healthcare solutions.
Position Detection System for Moving-Magnet Linear Motors Based on a Magnetoresistive Sensor Array
Authors: Wang Jun , Chen Xiang , Chen Quyan , Xi Qing , Sun Haiyang
Published: February 2025

The moving-magnet linear motor has received considerable attention in the development of logistic and factory automation in recent years. A reliable position detection system is the key to achieving the precise position and control of the motor. At present, the magnetic grid-scale and grating-scale are the most widely used traditional detection methods. However, these are not suitable for position detection with moving-magnet linear motors. They have the disadvantages of being easy to disturb, having a high cost, and exhibiting a limited measurement range. In this work, a moving-magnet linear motor position detection system based on an array of magnetoresistive sensors is used. The array is configured by arranging the magnetoresistive sensors at equal intervals along a line parallel to the trajectory of the armature. Then, the permanent magnet is fixed on the rotor and detected by sensors. When the rotor crosses the sensors in a parallel line, the changes in the magnetic field cause the magnetoresistive sensors to output two voltage signals directly proportional to the corresponding position changes. The signals are collected by the AD7606 and transmitted to the FPGA and STM32 controller for data processing, and the actual position of the rotor is calculated. This method has no length limitation and can be used for long-distance position detection. The experimental results show that the position detection system has a higher linear correlation coefficient compared with the magnetic grid ruler, in addition to a capability of ±9 μm accuracy, which verifies the validity of the position detection method for the moving-magnet linear motor.
A Real-Time Fish Detection System for Partially Dewatered Fish to Support Selective Fish Passage
Authors: Gregory Jonathan , Miehls Scott M. , Eickholt Jesse L. , Zielinski Daniel P.
Published: February 2025

Recent advances in fish transportation technologies and deep machine learning-based fish classification have created an opportunity for real-time, autonomous fish sorting through a selective passage mechanism. This research presents a case study of a novel application that utilizes deep machine learning to detect partially dewatered fish exiting an Archimedes Screw Fish Lift (ASFL). A MobileNet SSD model was trained on images of partially dewatered fish volitionally passing through an ASFL. Then, this model was integrated with a network video recorder to monitor video from the ASFL. Additional models were also trained using images from a similar fish scanning device to test the feasibility of this approach for fish classification. Open source software and edge computing design principles were employed to ensure that the system is capable of fast data processing. The findings from this research demonstrate that such a system integrated with an ASFL can support real-time fish detection. This research contributes to the goal of automated data collection in a selective fish passage system and presents a viable path towards realizing optical fish sorting.
A Blockchain Solution for the Internet of Vehicles with Better Filtering and Adaptive Capabilities
Authors: Shen Xueli , Ma Runyu
Published: February 2025

The traditional consensus algorithm based on the Internet of Vehicles (IoV) system has the disadvantages of high latency, low reliability, and weak fault tolerance, and it cannot make real-time adjustments according to the actual environment, making the system vulnerable to malicious control, inefficiency, and poor environmental adaptability. To solve this problem, we propose a gradually accelerating environment adaptive consensus algorithm, AE-PBFT, that can be applied to IoV. It includes a trust management model that achieves gradual acceleration by recording the historical continuous behavior of nodes, thereby improving the efficiency of screening nodes with different intentions, accelerating the consensus process, and reducing latency. At the same time, we introduce a dynamic consensus group division mechanism based on environmental adaptive changes, which can adaptively adjust the number of nodes participating in the consensus process according to the needs of the operating environment, to deal with extreme situations, thereby improving the reliability and fault tolerance of the system. Experiments confirm that the performance of our proposed solution is superior to current solutions in terms of consensus latency and fault tolerance and is more suitable for the operating environment of IoV.