bluuebunny/crossref_metadata_2025 huggingface dataset:
Correction: Lin et al. ATF3-Expressing Large-Diameter Sensory Afferents at Acute Stage as Bio-Signatures of Persistent Pain Associated with Lumbar Radiculopathy. Cells 2021, 10, 992
Authors: Lin Jiann-Her , Yu Yu-Wen , Chuang Yu-Chia , Lee Cheng-Han , Chen Chih-Cheng
Published: December 2024

In the original publication [...]
The Role of Activated Stromal Cells in Fibrotic Foci Formation and Reversion
Authors: Basalova Nataliya Andreevna , Vigovskiy Maksim Alexandrovich , Popov Vladimir Sergeevich , Lagereva Evgeniya Alexandrovna , Grigorieva Olga Alexandrovna , Efimenko Anastasia Yuryevna
Published: December 2024

Fibrotic focus is a pivotal morphofunctional unit in developing fibrosis in various tissues. For most fibrotic diseases, including progressive forms, the foci are considered unable to remodel and contribute to the worsening of prognosis. Unfortunately, the dynamics of the fibrotic focus formation and resolution remains understudied. A number of data suggest that the key cell type for focus formation are activated stromal cells marked by fibroblast activated protein alpha (FAPα) due to their high capacity for extracellular matrix (ECM) remodeling. We evaluated the dynamics of fibrotic focus formation and the contribution of the main cell types, including FAPα+ cells, in this process using a murine model of bleomycin-induced lung fibrosis. We revealed the very early appearance of FAPα+ cells in lungs after injury and assumed their important involvement to the myofibroblast pool formation. During the first month after bleomycin administration, FAPα+ cells colocalize with CD206+ M2 macrophages. Interestingly, during the reversion stage, we unexpectedly observed the specific structured foci formed by CD90+FAPα+ cells, which we suggested calling “remodeling foci”. Our findings highlight the crucial role of activated stromal cells in fibrosis initiation, progression, and reversion and provide emerging issues regarding the novel targets for antifibrotic therapy.
Getting to the Heart of the Planetary Health Movement: Nursing Research Through Collaborative Critical Autoethnography
Authors: LeClair Jessica , Sheppard De-Ann , Evans-Agnew Robin
Published: December 2024

Humans and more-than-humans experience injustices related to the triple planetary crisis of climate change, pollution, and biodiversity loss. Nurses hold the power and shared Responsibility (Note on Capitalization: Indigenous Scholars resist colonial grammatical structures and recognize ancestral knowledge by capitalizing references to Indigenous Ways of Knowing (Respect, Relations, and Responsibilities are capitalized to acknowledge Indigenous Mi’kmaw Teachings of our collective Responsibilities to m’sit no’ko’maq (All our Relations). Respect for Land, Nature, Knowledge Keepers, Elders, and the names of Tribes, including the Salmon People and sacred spaces, such as the Longhouse, are also denoted with capitals)) to support the health and well-being of each other and Mother Earth. The heart of the Planetary Health movement to address these impacts centers on an understanding of humanity’s interconnection within Nature. As nurses, we seek partnerships with more-than-human communities to promote personal and collective wellness, Planetary Health, and multispecies justice. This article introduces a longitudinal, collaborative autoethnography of our initial engagement with more-than-human communities. In this research, we utilize reflexive photovoice and shared journals to describe our early conversation about this interconnection with three waterways across diverse geographies. This work acknowledges the importance of relational and embodied Ways of Knowing and Being. We invite nurses to embrace the heart of the Planetary Health movement and share these stories with their more-than-human community partners.
Speckle Strain Analysis of Left Ventricular Dysfunction in Paediatric Patients with Bicuspid Aortic Valve—A Pilot Study
Authors: Făgărășan Amalia , Ghiragosian-Rusu Simina-Elena , Ghiragosian Claudiu , Gozar Liliana , Suteu Carmen , Toma Daniela , Al-Akel Flavia Cristina , Cucerea Manuela
Published: December 2024

Background/Objectives: Bicuspid aortic valve (BAV) is a prevalent congenital heart defect that continues to present a significant challenge in the management of paediatric patients. The assessment of left ventricle systolic function is typically conducted through the measurement of the left ventricular ejection fraction. Currently, left ventricle global longitudinal strain (LV GLS) is regarded as a more sensitive indicator, enabling the quantitative assessment of global and segmental ventricular function through the determination of myocardial deformation. Methods: A prospective study was conducted between 10 January 2023 and 10 January 2024 in a tertiary paediatric cardiology referral centre. The study enrolled children aged 6 to 17 years with BAV who were undergoing periodic evaluation, as well as a control group. The primary objective was to analyse the systolic function (global and segmental LV) using the classical method (LV EF) and speckle tracking echocardiography (STE). Results: The study group comprised 73 patients with a mean age of 13 years and was predominantly male. The control group comprised 55 patients. The phenotype IB with aortic regurgitation (AR) was the most prevalent. The results of the STE evaluation in the control group demonstrated mean GLS values between −22.1% and −22.8%. A comparison of the BAV group and the control group revealed a significant difference in GLS for the apical four-chamber view (p = 0.022). Conclusions: Although the analysis of global LV function demonstrated normal values of EF in patients with BAV, the strain analysis revealed significantly reduced strain in the inferior segment and in the apical four-chamber view, as well as in the anterior segment. Further investigation is required to determine whether reduced LV GLS in paediatric patients with BAV will ultimately result in the development of clinical heart failure. Additionally, it is necessary to ascertain whether this can identify patients with subclinical heart failure and whether early detection can result in a reduction in morbidity.
Periplosides Extract from Cortex periplocae Improve Collagen Antibody-Induced Arthritis by Regulating Macrophage Polarization
Authors: Wang Que , Xiong Xiaoyu , Chen Li , Zhu Fenghua , Yang Xiaoqian , Zhao Weimin , He Shijun , Zuo Jianping , Lin Zemin
Published: December 2024

Rheumatoid arthritis (RA) is an inflammatory autoimmune disease characterized primarily by the synovial infiltration of inflammatory cells. Macrophage infiltration in the joint synovium is one of the early hallmarks of RA disease activity. Cortex periplocae, which has been widely employed in traditional Chinese medicine (TCM) to alleviate RA, harbors a bioactive compound known as Periploca sepium periplosides (PePs). In this study, collagen antibody-induced arthritis (CAIA) was established in mice through the administration of collagen antibodies and lipopolysaccharide (LPS), followed by treatment with PePs. The therapeutic effects of PePs were evaluated by measuring paw thickness, clinical arthritis scores, and histological changes in joint tissues. Flow cytometry and qRT-PCR were used to assess macrophage polarization in vivo and in vitro. The findings indicate that PePs effectively attenuated CAIA by suppressing the polarization of RAW264.7 cells towards the M1 phenotype while promoting their polarization towards the M2 phenotype. These results provide valuable insights into the scientific significance of PePs as a potential therapeutic agent for RA.
Kinetic Study of Infrared Heat Curing of Thermosetting Polymers
Authors: Wang Tongzhao , Lun Isaac Yu Fat , Xia Liang , Wang Yongji , Pan Song
Published: December 2024

Infrared (IR) radiation curing technology has a high potential to improve the curing process of thermosetting polymers. To investigate the IR curing reaction mechanism, the present study explores the curing kinetics of glycidyl methacrylate (GMA)/dodecanedioic acid (DDDA) powder coatings subjected to IR radiation. Fourier-transformed infrared (FT-IR) spectroscopy is employed to record the concentration of epoxide groups with respect to time under different temperature conditions, with the reaction conducted under IR radiation. The resulting data are then fitted by the Levenberg–Marquardt algorithm using MATLAB software to obtain the kinetic parameters, namely the rate constant (k), catalytic constants (n, m), manifestation activation energy (E), and the pre-exponential factor (A) of the curing reaction. Additionally, this study proposes a new concept: the ‘photo-thermal synergistic effect’ of infrared curing and its evaluation criteria using a dimensionless quantity. Incredibly, this index integrates the impact of IR curing technology on two aspects: the curing process and the properties of the cured product. Overall, this study deepens our understanding of the IR curing reaction mechanism and provides a reference for the application of this technology in practical engineering.
The Corrosion Performance of Hybrid Polyurea Coatings Modified with TiO2 Nanoparticles in a CO2 Environment
Authors: Si Shanshan , Wei Qi , Li Binzhou , Jiang Yuanbo , Zhang Dayue , Wang Yijia , Yang Yu , Wang Bingying
Published: December 2024

To enhance the corrosion resistance of underground pipelines made of low carbon steel, nano-TiO2-modified polyurea was applied to their surface. The anti-corrosion performance of these nano-TiO2-modified coatings was tested by immersing them in a NACE (5 wt.% NaCl + 0.5 wt.% CH3COOH) solution under high temperatures and high CO2 pressures. The mass variation, SEM morphology, and open-circuit potential were determined. EIS tests, neutral salt spray tests, and contact angle measurements were carried out to analyze the effect of nanoparticles on corrosion resistance. Within the same pressure range, the polyurea coating shows the highest corrosion resistance when 5% TiO2 nanoparticles were added compared to that of polyurea coatings with 0%, 10%, and 15% TiO2 added. Coatings with 5% TiO2 nanoparticles showed rapid diffusion after being immersed for 96 h, indicating that the anti-corrosion performance of the coating weakened.
Synthesis of Two Structurally Different MgO Films Containing Dioxygen Species: Dioxygen Embedded at Grain Boundaries, and as Components of a Superfilled Rock Salt Structure
Authors: Fischer Dieter , Zagorac Dejan , Küster Kathrin , Schön Johann Christian
Published: December 2024

Magnesium oxide films prepared as monolayer, amorphous, and epitaxial films have different properties such as semiconducting, ferromagnetic, and dielectric behavior, respectively. Understanding the variation in these properties requires detailed information about the atomic structure of the different MgO films. In the present study, one important synthesis method, ballistic deposition, is studied, and the influence of the deposition temperature on the resulting atomic structure of the films is analyzed in detail, employing XRD, SEM, EDX, XPS, and Raman scattering. At −190 °C, compact, light-yellow films are obtained, which consist of small crystallites adopting the rock salt structure with an excess of oxygen at the grain boundaries. However, at 25 °C, nearly stoichiometric, white, columnar films exhibiting a superfilled rock salt structure are grown. In the first case, dioxygen species are formed by connecting the oxygen shells of adjacent small crystalline grains, and in the second case such species appear due to the partial occupation of tetrahedral sites in the rock salt structure. These observations should open new prospects of fine-tuning the properties of MgO films and enhance the performance of devices employing such films.
MXenes in Perovskite Solar Cells: Emerging Applications and Performance Enhancements
Authors: Luo Bin , Wang Xiaodan , Tuokedaerhan Kamale , Wang Shuying , Wang Chen , Shi Xiaohao , Yu Zhiqiang , Shen Xiangqian
Published: December 2024

Perovskite solar cells (PSCs) have emerged as promising candidates for next-generation photovoltaic technology due to their remarkable power-conversion efficiencies (PCEs). Since their introduction, the PCE of PSCs has advanced from 3.8% to over 26%. Nonetheless, challenges pertaining to stability and reliability continue to impede their commercial viability. Recent progress in interface engineering and materials science has underscored the potential of two-dimensional (2D) materials, particularly MXenes, in mitigating these challenges. MXenes represent a class of two-dimensional materials with significant potential for application in PSCs, attributed to their exceptional electrical conductivity, high carrier mobility, remarkable optical transparency, chemical stability, and tunable surface chemical properties. When employed as electron transport layers, MXenes enhance charge transfer and extraction efficiency, leading to substantial improvements in PCEs. Furthermore, their integration into hole transport layers and use as interfacial modifiers contribute to the mitigation of degradation pathways, thereby enhancing device longevity. The unique structural and electronic characteristics of MXenes facilitate their application as transparent electrodes, presenting opportunities for cost reduction and improved optical properties. This review provides a comprehensive overview of the current advancements in MXene-based PSCs, emphasizing significant accomplishments and exploring future research directions aimed at enhancing the efficiency and stability of these devices.
Information and Computing Ecosystem’s Architecture for Monitoring and Forecasting Natural Disasters
Authors: Gribova Valeria , Kharitonov Dmitry
Published: December 2024

Monitoring natural phenomena using a variety of methods to predict disasters is a trend that is growing over time. However, there is a great disunity among methods and means of data analysis, formats and interfaces of storing and providing data, and software and information systems for data processing. As part of a large project to create a planetary observatory that combines data from spatially distributed geosphere monitoring systems, the efforts of leading institutes of the Russian Academy of Sciences are also aimed at creating an information and computing ecosystem to unite researchers processing and analyzing the data obtained. This article provides a brief overview of the current state of publications on information ecosystems in various applied fields, and it also proposes a concept for an ecosystem on a multiagent basis with unique technical features. The concept of the ecosystem includes the following: the ability to function in a heterogeneous environment on federal principles, the parallelization of data processing between agents using Petri nets as a mechanism ensuring the correct execution of data processing scenarios, the concept of georeferenced alarm events requiring ecosystem reactions and possible notification of responsible persons, and multilevel information protection allowing data owners to control access at each stage of information processing.
Multispectral Imaging and OCT-Guided Precision Treatment of Rhinophyma with CO2 and Dye Lasers: A Comprehensive Diagnostic and Therapeutic Approach
Authors: Amato Simone , Nisticò Steven Paul , Clementi Alessandro , Stabile Giorgio , Cassalia Fortunato , Dattola Annunziata , Rizzuto Giuseppe , Cannarozzo Giovanni
Published: December 2024

Background/Objectives: Rhinophyma, an advanced form of rosacea, is characterized by significant nasal tissue enlargement and deformation, leading to aesthetic and psychosocial challenges. Traditional treatments are often invasive with variable outcomes, emphasizing the need for improved therapeutic approaches. This study evaluates the efficacy of a dual-laser therapy (CO2 and dye lasers) in treating rhinophyma. An innovative diagnostic algorithm using multispectral imaging guided treatment decisions, while Optical Coherence Tomography (OCT) was utilized to analyze post-treatment vascular and collagen changes. Methods: A prospective study was conducted involving 20 patients with rhinophyma. Multispectral imaging was used to guide the tailored application of CO2 laser, dye laser, or both, depending on the predominant vascular or glandular components in the nasal tissue. Post-treatment analysis employed OCT to assess changes in vascular and collagen density, providing insights into the tissue modifications induced by laser therapy. Results: The treatment significantly reduced vascular density from 35,526.75 to 26,577.55 at 300 microns and from 46,916.25 to 35,509.25 at 500 microns. Collagen density decreased from 81.35 to 66.34. All reductions were statistically significant, with highly significant p-values. These findings highlight the dual-laser therapy’s effectiveness in addressing the pathological features of rhinophyma. Conclusions: Dual-laser therapy guided by multispectral imaging provides a targeted and effective treatment for rhinophyma, addressing its vascular and glandular components. The use of OCT enhances understanding of laser-induced tissue changes and confirms significant reductions in vascular and collagen density. This approach represents a significant advancement in the management of rhinophyma, offering improved precision and therapeutic outcomes.
Multi-Modal Machine Learning Approach for COVID-19 Detection Using Biomarkers and X-Ray Imaging
Authors: Tur Kagan
Published: December 2024

Background: Accurate and rapid detection of COVID-19 remains critical for clinical management, especially in resource-limited settings. Current diagnostic methods face challenges in terms of speed and reliability, creating a need for complementary AI-based models that integrate diverse data sources. Objectives: This study aimed to develop and evaluate a multi-modal machine learning model that combines clinical biomarkers and chest X-ray images to enhance diagnostic accuracy and provide interpretable insights. Methods: We used a dataset of 250 patients (180 COVID-19 positive and 70 negative cases) collected from clinical settings. Biomarkers such as CRP, ferritin, NLR, and albumin were included alongside chest X-ray images. Random Forest and Gradient Boosting models were used for biomarkers, and ResNet and VGG CNN architectures were applied to imaging data. A late-fusion strategy integrated predictions from these modalities. Stratified k-fold cross-validation ensured robust evaluation while preventing data leakage. Model performance was assessed using AUC-ROC, F1-score, Specificity, Negative Predictive Value (NPV), and Matthews Correlation Coefficient (MCC), with confidence intervals calculated via bootstrap resampling. Results: The Gradient Boosting + VGG fusion model achieved the highest performance, with an AUC-ROC of 0.94, F1-score of 0.93, Specificity of 93%, NPV of 96%, and MCC of 0.91. SHAP and LIME interpretability analyses identified CRP, ferritin, and specific lung regions as key contributors to predictions. Discussion: The proposed multi-modal approach significantly enhances diagnostic accuracy compared to single-modality models. Its interpretability aligns with clinical understanding, supporting its potential for real-world application.
Establishment of the Normative Value of Classical Bluestone’s Nine-Step Inflation/Deflation Tympanometric Eustachian Tube Function Test
Authors: Wang Jing-Jie , Jiang Rong-San , Weng Chien-Hsiang
Published: December 2024

Background/Objectives: The nine-step inflation/deflation tympanometric Eustachian tube function test (commonly referred to as the nine-step test) is a widely utilized method for evaluating Eustachian tube function (ETF). This study aimed to establish normative values for the nine-step test to facilitate the diagnosis of Eustachian tube dysfunction (ETD). Methods: A total of 160 adults, including 70 healthy volunteers and 90 patients with chronic rhinosinusitis (CRS), were recruited for this study. Participants were further categorized into “fair ETF” and “poor ETF” groups based on their scores on the Eustachian Tube Dysfunction Questionnaire (ETDQ-7). Eustachian tube function was assessed using both the nine-step test and the ETDQ-7. The diagnostic accuracy of the maximal peak pressure difference (MPD) from the nine-step test was evaluated, using an ETDQ-7 score of ≥14 as the reference standard. Discriminative ability was analyzed using receiver operating characteristic (ROC) curves. Results: An MPD value of ≤4 yielded an area under the ROC curve (AUC) of 0.619, indicating moderate discriminative ability in the Taiwanese population. The median MPD value on the nine-step test was 9.5 (interquartile range [IQR]: 4.5–14.0) in participants with an ETDQ-7 score of <14, compared to a median MPD value of 7.5 (IQR: 2.5–12.0) in those with an ETDQ-7 score of ≥14 (p = 0.033). This finding suggests a potential association between MPD values and ETDQ-7 scores. Conclusions: This study identified an MPD value of 4 as a normative cutoff for screening ETD in a Taiwanese population. However, the diagnostic discriminative power of this parameter was moderate.
Reducing the Maximum Amplitudes of Forced Vibrations of a Quadcopter Arm Using an Aerodynamic Profile Adapter
Authors: Tofan-Negru Andra , Ștefan Amado , Casapu Maria
Published: December 2024

This research focuses on the dynamic response analysis of a quadcopter arm without an adapter mounted and with aerodynamic profile adapters mounted to enhance drone performance. Nine different adapters were simulated to assess their impact on the arm’s dynamic behavior during various motor operating regimes. The pressure force distribution from the airflow around the quadcopter arm was analyzed to determine the optimal adapter configuration. Numerical simulations revealed the best geometry for the adapter, which significantly reduced maximum displacement amplitudes compared to the non-adapter arm. The study also examined the effects of static imbalance from the rotor-propeller assembly, leading to the calculation of an eccentricity value of 0.022 mm for inertial force application. Experimental tests validated the numerical findings, with laser vibrometer measurements confirming improved dynamic responses with Adapter 8 across most operating regimes. Overall, the study shows the advantages of using better aerodynamic designs in quadcopter arms to improve stability and performance, contributing to advancements in drone technology through improved structural designs.
Control of Overfitting with Physics
Authors: Kozyrev Sergei V. , Lopatin Ilya A. , Pechen Alexander N.
Published: December 2024

While there are many works on the applications of machine learning, not so many of them are trying to understand the theoretical justifications to explain their efficiency. In this work, overfitting control (or generalization property) in machine learning is explained using analogies from physics and biology. For stochastic gradient Langevin dynamics, we show that the Eyring formula of kinetic theory allows to control overfitting in the algorithmic stability approach—when wide minima of the risk function with low free energy correspond to low overfitting. For the generative adversarial network (GAN) model, we establish an analogy between GAN and the predator–prey model in biology. An application of this analogy allows us to explain the selection of wide likelihood maxima and ab overfitting reduction for GANs.
Are Adolescents with a Wider Vocabulary Faster at Inference Making During Reading? Evidence from Self-Paced Reading
Authors: Guerra Ernesto , Kronmüller Edmundo
Published: December 2024

This study investigates the relationship between vocabulary knowledge and inference-making during real-time reading comprehension in Spanish-speaking adolescents, addressing an important gap in the literature. A large sample of adolescents (n = 265) aged between 11 and 18 were asked to perform a self-paced reading task, which required integrating words across sentence boundaries. The study compared two conditions: repetition and inference. In the repetition condition, a critical word appeared in both context and target sentences, while in the inference condition, the context allowed the inference of the critical word. Vocabulary knowledge was assessed using a standardized receptive vocabulary test. The results showed that adolescents with larger vocabularies exhibited faster reading times across conditions, particularly in the inference condition, where a stronger vocabulary facilitated more efficient word-to-text integration. The interaction between vocabulary and reading condition indicated that a larger vocabulary mitigates the cognitive cost of inference-making, supporting more effective reading comprehension. These findings highlight the role of vocabulary knowledge in reducing the cognitive load associated with inference generation during reading, offering important implications for educational strategies aimed at improving adolescent literacy.
e-Learning Challenges in STEM Education
Authors: Saldívar-Almorejo María Magdalena , Flores-Herrera Luis Armando , Rivera-Blas Raúl , Niño-Suárez Paola Andrea , Rivera-Blas Emmanuel Zenén , Rodríguez-Contreras Nayeli
Published: December 2024

This work reviews the key challenges surrounding teaching Science, Technology, Engineering, and Mathematics subjects known as STEM. The research has uncovered a significant gap between traditional teaching styles and the need to develop and adapt to new remote-learning modalities. The work describes the technological, pedagogical, social, and institutional challenges, finally identifying the importance of their joint interaction. Since the COVID-19 pandemic, it has become evident that STEM educators must increase their awareness and knowledge of instructional models focused on using digital platforms. The current trend is centred on developing remote-learning tools, which will likely become the predominant learning norm as the economy’s viability increases. However, these remote-learning approaches must maintain interaction with the physical world, as understanding real-world phenomena is crucial for improving learning processes. STEM learning through e-learning will have a greater chance of success if academic institutions collaborate with other sectors of society, such as the business sector, to receive feedback for the continuous improvement of the proposed teaching methods.
Dual-Loop Constant Voltage Regulation in Wireless Power Transfer Systems Using Phase-Shift and Duty Cycle Modulation
Authors: Zhao Zhiheng , Sun Jinhong
Published: December 2024

This study investigates the single transmitter and single receiver (STSR) with dual-output capability. This methodology utilizes dual half-wave rectification. Initially, the system topology of the STSR multi-channel voltage output is presented with the inductor-capacitor-capacitor-series (LCC-S) compensation topology, followed by an in-depth analysis of its double-channel voltage output characteristics. Through detailed analysis and empirical validation, the system is shown to maintain high efficiency and stable performance, making it well-suited for applications demanding reliable dual-voltage outputs under dynamic conditions.
FPGA Implementation of Reaction Systems
Authors: Shang Zeyi , Verlan Sergey , Lu Jing , Wei Zhe , Zhou Min
Published: December 2024

Reaction system (RS) belongs to a type of qualitative computing model inspired by biochemical reactions taking place inside biological cells. It concerns more the interactions and causality among reactions rather than concrete concentrations of chemical entities. Many biochemical processes and models can be represented in the form of reaction systems so that complex relations and ultimate products of a variety of reactions can be revealed qualitatively. The reaction system works in parallel mode. Software simulation of this kind of model may suffer from the penalty of inefficient parallelism for the limited performance of CPU/GPU, especially for the simulation of large-scale models. Considering potential applications of reaction systems in disease diagnoses and in drug developments, hardware implementation of reaction systems provides a better way to accelerate computations involved. In this paper, an FPGA implementation method of a reaction system called RSFIM is proposed. Two small-scale models, i.e., the reaction system of intermediate filaments self-assembly and heat shock response, are implemented on FPGA, achieving a computing speed of 2×108 steps per second. For large-scale models, the ErbB reaction system is implemented, obtaining a speedup of 7.649×104 compared with its highest performance GPU simulation so far. The reaction system binary counter, which is a quantitative model, is also implemented by the Boolean explanation of the qualitative character of the reaction system. FPGA implementation of reaction systems opens a novel research line to speed up the simulations of reaction systems and other biological models in the perspective of parallel digital circuits.
Prioritizing Research for Enhancing the Technology Readiness Level of Wind Turbine Blade Leading-Edge Erosion Solutions
Authors: Pryor Sara C. , Barthelmie Rebecca J. , Coburn Jacob J. , Zhou Xin , Rodgers Marianne , Norton Heather , Campobasso M. Sergio , López Beatriz Méndez , Hasager Charlotte Bay , Mishnaevsky Leon
Published: December 2024

An enhanced understanding of the mechanisms responsible for wind turbine blade leading-edge erosion (LEE) and advancing technology readiness level (TRL) solutions for monitoring its environmental drivers, reducing LEE, detecting LEE evolution, and mitigating its impact on power production are a high priority for all wind farm owners/operators and wind turbine manufacturers. Identifying and implementing solutions has the potential to continue historical trends toward lower Levelized Cost of Energy (LCoE) from wind turbines by reducing both energy yield losses and operations and maintenance costs associated with LEE. Here, we present results from the first Phenomena Identification and Ranking Tables (PIRT) assessment for wind turbine blade LEE. We document the LEE-relevant phenomena/processes that are deemed by this expert judgment assessment tool to be the highest priorities for research investment within four themes: atmospheric drivers, damage detection and quantification, material response, and aerodynamic implications. The highest priority issues, in terms of importance to LEE but where expert judgment indicates that there is a lack of fundamental knowledge, and/or implementation in measurement, and modeling is incomplete include the accurate quantification of hydrometeor size distribution (HSD) and phase, the translation of water impingement to material loss/stress, the representation of operating conditions within rain erosion testers, the quantification of damage and surface roughness progression through time, and the aerodynamic losses as a function of damage morphology. We discuss and summarize examples of research endeavors that are currently being undertaken and/or could be initiated to reduce uncertainty in the identified high-priority research areas and thus enhance the TRLs of solutions to mitigate/reduce LEE.
Research into a Two-Stage Filtration System of Inlet Air to the Internal Combustion Engine of a Motor Vehicle
Authors: Dziubak Tadeusz
Published: December 2024

The necessity of using two-stage (multicyclone–partition) inlet air filters for engines of motor vehicles operated in dusty air conditions is demonstrated. Due to the lack of information in the literature on the description of the air filtration process in the two-stage system (multicyclone–partition), its experimental tests were performed. Due to the high cost of testing the original two-stage air filter, the original test methodology of testing a single cyclone and a paper filter with an appropriately sized surface was used. When testing the assembly (cyclone–paper filter), conditions similar to the actual operating conditions of a two-stage air filter were used, including the filtration speed in the paper filter, the dust concentration in the inlet air, and the cyclone inlet speed. The characteristics of various filter baffles with appropriately sized surface area operating in three filter assemblies, the “cyclone–test filter”, and without a cyclone were determined depending on the mass of dust supplied to the assembly or directly to the filter. Experimental tests showed the existence of an initial (short) filtration period, which was characterized by low values of filtration efficiency well below the required level of 99.9%. This phenomenon occurred regardless of whether the paper filter was operated directly after the cyclone or without the cyclone. However, with the mass of dust delivered to the filter, the efficiency and precision increase and in a short time achieve the required values, which are maintained for the rest of the filter’s operation. The air behind the paper filter contained dust grains of 10–25 µm with the required 2–5 µm. The increase in the pressure drop was lower for the paper filter operating in an assembly (cyclone–paper filter). Therefore, the operating time of the unit (cyclone–paper filter) to reach the permissible flow resistance value was four times longer than that of the paper filter, as could be demonstrated.
Quadruple Deep Q-Network-Based Energy Management Strategy for Plug-In Hybrid Electric Vehicles
Authors: Guo Dingyi , Lei Guangyin , Zhao Huichao , Yang Fang , Zhang Qiang
Published: December 2024

This study proposes the use of a Quadruple Deep Q-Network (QDQN) for optimizing the energy management strategy of Plug-in Hybrid Electric Vehicles (PHEVs). The aim of this research is to improve energy utilization efficiency by employing reinforcement learning techniques, with a focus on reducing energy consumption while maintaining vehicle performance. The methods include training a QDQN model to learn optimal energy management policies based on vehicle operating conditions and comparing the results with those obtained from traditional dynamic programming (DP), Double Deep Q-Network (DDQN), and Deep Q-Network (DQN) approaches. The findings demonstrate that the QDQN-based strategy significantly improves energy utilization, achieving a maximum efficiency increase of 11% compared with DP. Additionally, this study highlights that alternating updates between two Q-networks in DDQN helps avoid local optima, further enhancing performance, especially when greedy strategies tend to fall into suboptimal choices. The conclusions suggest that QDQN is an effective and robust approach for optimizing energy management in PHEVs, offering superior energy efficiency over traditional reinforcement learning methods. This approach provides a promising direction for real-time energy optimization in hybrid and electric vehicles.
Potential Reductions in Carbon Emissions from Indonesian Forest Concessions Through Use of Reduced-Impact Logging Practices
Authors: Hermudananto  , Belair Ethan P. , Hasbillah Hasbie , Ellis Peter W. , Ruslandi  , Putz Francis E.
Published: December 2024

To estimate the potential and realized carbon emission reductions from implementation of reduced-impact logging (RIL) in Indonesia, we compiled logging emissions data from 15 concessions in Kalimantan and 10 from the Papuan provinces. Committed emissions data were collected for harvested timber as well as from collateral damage caused by felling, skidding, and clearing for haul roads and log yards. Emissions expressed as mean ± standard error per cubic meter of timber harvested, per area harvested, and per Mg of timber harvested (i.e., the ‘Carbon Impact Factor’) were 1.30 ± 0.15 Mg C m−3, 27.52 ± 4.44 Mg C ha−1, and 6.88 ± 0.84 Mg Mg−1, respectively. Among the sampled concessions, felling, hauling, and skidding caused 18–86%, 2–48%, and 6–75% of these emissions, respectively. Potential emission reductions calculated as the difference between observed emissions and those of the five best-performing concessions are 0.67 ± 0.15 Mg C m−3, 21.11 ± 4.38 Mg C ha−1, and 4.20 ± 0.83 Mg Mg−1, which represents reductions of 51%, 76%, and 61%, respectively. Extrapolating these estimates to all of Indonesia using average log production data from 2018 to 2021 results in an estimated annual emissions reduction of 14.47 Tg CO2 from full adoption of RIL, which is 2.9% of Indonesia’s nationally determined contribution (NDC) from the forestry sector.
Microbial Conversion of Inulin to Valuable Products: The Biorefinery Concept
Authors: Tsigoriyna Lidia , Stefanov Stefan , Armenova Nadya , Petrova Penka , Petrov Kaloyan
Published: December 2024

The global transition to a sustainable bioeconomy requires the engagement of renewable and cost-effective substrates to obtain valuable bio-based products. Inulin-rich plant materials have promising applications in white biotechnology. This review evaluates the potential of converting inulin through an integrated biorefinery into high-value products by microbial fermentation. It describes the methods for raw biomass and inulin pretreatment, the possibilities of simultaneous saccharification and fermentation (SSF), and the use of wild-type and genetically modified microbial strains. The bioconversion of inulin enables the efficient synthesis of biofuels such as ethanol, butanol, and 2,3-butanediol and biochemicals such as lactic, citric, and poly-γ-glutamic acid. By analyzing the advances in inulin hydrolysis methods, microbial engineering, and bioprocess optimization approaches, this review highlights the broad applicability of inulin in the biorefinery context as a multifunctional, sustainable substrate, which contributes to the development of the circular economy.
A Survey on MLLMs in Education: Application and Future Directions
Authors: Xing Weicheng , Zhu Tianqing , Wang Jenny , Liu Bo
Published: December 2024

This survey paper examines the applications, methodologies, and future prospects of multimodal large language models (MLLMs) within the educational landscape. MLLMs, which integrate multiple data modalities such as text, images, and audio, offer innovative solutions that enhance learning experiences across various educational domains, including language acquisition, STEM education, interactive content creation, and medical training. The paper highlights how MLLMs contribute to improved engagement, personalized learning paths, and enhanced comprehension by leveraging their ability to process and generate contextually relevant content. The key findings underscore the transformative potential of MLLMs in modern education, suggesting significant improvements in both learner outcomes and pedagogical strategies. The paper also explores emerging trends and technological advancements that could shape the future of education, advocating for continued research and collaboration among stakeholders to fully harness the capabilities of MLLMs. As the integration of MLLMs into educational settings progresses, addressing ethical considerations and ensuring equitable access remain critical to maximizing their benefits.
Novel Formulations of Sourdough Bread Based on Supplements Containing Chokeberry Juice Fermented by Potentially Probiotic L. paracasei SP5
Authors: Mantzourani Ioanna , Daoutidou Maria , Terpou Antonia , Plessas Stavros
Published: December 2024

The current study focused on sourdough breads produced with various supplements consisting of freeze-dried black chokeberry juice, (i) unfermented and (ii) fermented by Lactiplantibacillus paracasei SP5, aiming to enhance their functionality and nutritional value. Specifically, the impact of these supplements on the quality of sourdough breads was evaluated in terms of their nutritional features, antimicrobial capacity, and sensorial characteristics. Sourdough breads produced with freeze-dried fermented chokeberry juice exhibited elevated concentrations of lactic acid (2.82–2.99 g/kg) and acetic acid (0.93–0.99 g/kg), which significantly prolonged their resistance to mould growth and rope contamination, maintaining freshness for over 13 days. These samples also demonstrated higher antioxidant activity, with DPPH values exceeding 4 μmol TE/g and ABTS values surpassing 218 mg TE/100 g, along with a total phenolic content ranging from 85.9 to 96.3 mg GAE/100 g. Additionally, these samples showed a greater reduction in phytate, an antinutrient, compared to all other samples, including the control. The sensory evaluation conducted with consumer panels indicated that sourdough breads prepared with freeze-dried fermented chokeberry juice achieved the highest ratings in terms of taste and appearance among all tested samples. The findings are highly promising and suggest the potential for commercializing the developed supplements in the production of additive-free sourdough bread with enhanced nutritional value.
Comparison of Interactions Between Soy Protein Isolate and Three Folate Molecules: Effect on the Stabilization, Degradation, and Oxidization of Folates and Protein
Authors: He Linlin , Yan Yuqian , Song Dandan , Li Shuangfeng , Zhao Yanna , Ding Zhuang , Wang Zhengping
Published: December 2024

This study selected three approved folate sources—folic acid (FA), L-5-methyltetrahydrofolate (MTFA), and calcium 5-methyltetrahydrofolate (CMTFA)—to explore their interaction mechanisms with soy protein isolate (SPI) through spectrofluorometric analysis and molecular docking simulations. We investigated how these interactions influence the structural and physicochemical stability of folates and SPI. Three folates spontaneously bound to SPI, forming complexes, resulting in a decrease of approximately 30 kJ·mol−1 in Gibbs free energy and an association constant (Ka) of 105 L·mol−1. The thermodynamic parameters and molecular docking study revealed the unique binding mechanisms of FA and MTFA with SPI. FA’s planar pteridine ring and conjugated double bonds facilitate hydrophobic interactions, whereas MTFA’s reduced ring structure and additional polar groups strengthen hydrogen bonding. Although the formation of SPI–folate complexes did not result in substantial alterations to the SPI structure, their binding has the potential to enhance both the physical and thermal stability of the protein by stabilizing its conformation. Notably, compared with free FA, the FA-SPI complexes significantly enhanced FA’s stability, exhibiting 71.1 ± 1.2% stability under light conditions after 9 days and 63.2 ± 2.6% stability in the dark after 60 days. In contrast, no similar effect was observed for MTFA. This discrepancy can be ascribed to the distinct degradation pathways of the Fa and MTFA molecules. This study offers both theoretical and experimental insights into the development of folate-loaded delivery systems utilizing SPI as a matrix.
Influence of Algal Incorporation on Sensory and Physicochemical Attributes of Caseless Sausage—Ćevap (CSC)
Authors: Siladji Caba , Djordjevic Vesna , Borovic Branka , Heinz Volker , Terjung Nino , Katanic Nenad , Tomasevic Igor
Published: December 2024

This study explores the influence of algal incorporation on the sensory and physicochemical attributes of caseless sausage—ćevap (CSC). Various algae, including Chlorella vulgaris, Himanthalia elongata (sea spaghetti), and Undaria pinnatifida (wakame), were added at different concentrations to standard CSC formulations. Proximate analysis revealed that the addition of algae did not significantly change crude protein and fat content (p > 0.05). Furthermore, sea spaghetti and wakame resulted in lower moisture levels and decreased cooking loss, while all algae varieties raised the salt content (p < 0.05) due to their inherent sodium levels. Texture analysis demonstrated that the inclusion of sea spaghetti and Chlorella led to reductions in hardness and chewiness, while wakame resulted in a firmer texture, highlighting its substantial impact on textural attributes. Color measurements indicated that wakame significantly affected the color profile (p < 0.05), resulting in decreased lightness and increased darkness in the sausage, surpassing the effects of other algae. Sensory evaluations showed that formulations containing wakame received the lowest scores for color, smell, taste and overall acceptability—up to 1.5 points lower compared to the control samples. On the other hand, some formulations with other algae showed promising small deviations from the control. Overall, this research supports the viability of using algae as functional ingredients in meat products, emphasizing the importance of selecting the appropriate type and concentration of algae to optimize both physicochemical parameters and sensory qualities in caseless sausages.
Introducing an Enhanced Cumulative Size Distribution Model to Unearth the Origins of Macropore Heterogeneity of the Chang-7 Shale Oil Reservoirs in the Ordos Basin
Authors: Wang Ziyi , Dong Lin , Jin Zhijun , Wang Xubin , Fu Jinhua , Liu Xianyang , Zhu Rukai
Published: December 2024

Characterizing the fractal nature of shale pores is critical for understanding their heterogeneity, which significantly impacts hydrocarbon mobility. A critical technique in this analysis involves the digital evaluation of scanning electron microscopy (SEM) images. While the cumulative size distribution model is a viable method in SEM fractal analysis, its accurate application necessitates exhaustive microimaging of entire sample cross-sections, rendering it impractical. To address this challenge, we propose an innovative approach that develops a universal equation for this model, along with numerical solving methods. This approach expands the model’s applicability, enabling accurate fractal analysis of entire samples using only randomly selected microscopic fields. It enhances the existing framework for fractal modeling and potentially serves as a valuable tool for studying fractal structures. Using this method, we investigated the fractal characteristics of various macropore types across different lithological units in the Chang-7 shale of the Ordos Basin. Our findings indicate that macropore heterogeneity is influenced by variations in pore type composition, their response under compaction, and organic acid dissolution, all of which are driven by differences in lithology. These findings provide new insights into the mechanisms driving macropore heterogeneity from the perspective of lithological and pore-type variations, potentially yielding valuable implications for the exploration and development of Chang-7 shale oil.
Bridging Pre-Invex Mappings and Fractional Integrals: A Pathway to Iterative Schemes via Error Boundaries of Maclaurin’s Rule
Authors: Liu Qi , Rukhsar  , Awan Muhammad Uzair , Bin-Mohsin Bandar , Javed Muhammad Zakria , Ciurdariu Loredana , Meftah Badreddine
Published: December 2024

In this paper, we aim to investigate corrected Euler–Maclaurin inequalities involving pre-invex mappings within the framework of fractional calculus. We want to find a number of important results for differentiable pre-invex mappings and Riemann–Liouville (RL) fractional integrals so that we can make more accurate error estimates. Additionally, we present examples with graphical illustrations to substantiate our major findings and deduce several special cases under certain conditions. Afterwards, we introduce applications such as the linear combination of means, composite corrected Maclaurin’s rule, modified Bessel mappings, and novel iterative methods for solving nonlinear equations.