bluuebunny/crossref_metadata_2025 huggingface dataset:
Estimation and Validation of the “c” Factor for Overall Cerebral Functioning in the Philadelphia Neurodevelopmental Cohort
Authors: Moore Tyler M. , Calkins Monica E. , Wolf Daniel H. , Satterthwaite Theodore D. , Barzilay Ran , Scott J. Cobb , Ruparel Kosha , Gur Raquel E. , Gur Ruben C.
Published: February 2025

While both psychopathology and cognitive deficits manifest in mental health disorders, the nature of their relationship remains poorly understood. Recent research suggests a potential common factor underlying both domains. Using data from the Philadelphia Neurodevelopmental Cohort (N = 9494, ages 8–21), we estimated and validated a “c” factor representing overall cerebral functioning through a structural model combining cognitive and psychopathology indicators. The model incorporated general factors of psychopathology (“p”) and cognitive ability (“g”), along with specific sub-domain factors. We evaluated the model’s criterion validity using external measures, including parent education, neighborhood socioeconomic status, global functioning, and intracranial volume, and assessed its predictive utility for longitudinal psychosis outcomes. The model demonstrated acceptable fit (CFI = 0.98, RMSEA = 0.021, SRMR = 0.030), and the “c” factor from this model showed stronger associations with parent education (r = 0.43), neighborhood SES (r = 0.47), and intracranial volume (r = 0.39) than “p” and “g” factors alone. Additionally, baseline “c” factor scores significantly predicted psychosis spectrum outcomes at follow-up (d = 0.30–0.57). These findings support the utility of a “c” factor in capturing overall cerebral function across cognitive and psychopathology domains, with potential implications for understanding brain function, improving clinical assessment, and optimally focusing interventions.
Purification of Produced Water by Solvents to Enhance Oil Recovery and Reuse Separated Droplets
Authors: Aljadiri Aqeel Shaikhah Arafat , Bailón-Moreno Rafael
Published: February 2025

In crude oil production, large volumes of produced water are generated as a highly polluting waste byproduct. On average, at least two barrels of produced water are generated for every barrel of oil. This water contains oil traces in stable and complex emulsions. To purify it, a method is proposed based on breaking these emulsions using solvents that induce the coalescence of oil droplets, facilitating their separation from the water. The method has two main objectives: (1) To identify the characteristics a solvent must have to effectively break oil emulsions according to the Hansen solubility parameter (HSP) model. (2) To select, from 40 solvents of different chemical families, the most suitable ones based on efficiency, low toxicity, industrial availability, and cost. The experimental procedure included the following steps: (1) Contacting the solvent with produced water containing 150 ppm of oil under agitation. (2) Allowing the mixture to rest until a layer of recovered oil formed. (3) Spectrophotometric analysis of the residual oil. Three distinct HSP solubility spheres were identified, within which the most effective solvents were xylene (99.4% recovery), cyclohexane (99.5% recovery), and tetrahydrofuran (100% recovery). Their high efficiency not only facilitated oil separation but also made the recovered oil suitable for commercialization.
Advancements in Digital Workflows for 3D-Printed Maxillofacial Soft Prostheses: Exploring Design and Materials in Direct Additive Manufacturing: A Scoping Review
Authors: Tarba Cristian Ioan , Cristache Mircea Alexandru , Baciu Ioana Medeea , Cristache Corina Marilena , Burlacu Vatamanu Oana Elena , Oancea Luminita
Published: February 2025

The treatment of maxillofacial defects presents significant challenges due to the complexity of facial anatomy and the diversity of affected tissues. Traditional workflows are labor-intensive, costly, and limited in customization. Recent advancements in fully digital workflows and direct 3D printing technologies offer new possibilities for improving the fit, aesthetics, and efficiency of prosthetic manufacturing. This scoping review aims to evaluate the current state of direct 3D printing for maxillofacial soft prostheses, assess material properties and biocompatibility, and identify challenges and future directions in this field. Methods: A comprehensive search of PubMed and Scopus databases, along with a manual search of relevant journals, was conducted to identify studies published up to December 2024. Articles focusing on direct 3D printing of maxillofacial soft prostheses were included, while studies involving traditional or mold-based workflows, ocular prostheses, and literature reviews were excluded. Data on materials, manufacturing techniques, and clinical outcomes were extracted and analyzed. Results: Out of 898 articles screened, 11 were included, 5 of which were in vivo studies (case reports). The additive manufacturing methods used in these case reports were Drop-on-Demand (DoD) silicone printing and PolyJet technology. Conclusions: Fully digital workflows and direct 3D printing technologies show promise for advancing maxillofacial prosthesis manufacturing. However, the absence of dedicated software, biocompatible materials, and medium- to long-term clinical evaluations highlight significant research gaps. Future research should focus on material development, workflow optimization, and clinical validation to enable widespread clinical adoption.
Hybrid Heat Pipe-PCM-Assisted Thermal Management for Lithium-Ion Batteries
Authors: Sharifi Nourouddin , Shabgard Hamidreza , Millard Christian , Etufugh Ugochukwu
Published: February 2025

A hybrid cooling method for 18650 lithium-ion batteries has been investigated using both experimental and numerical approaches for electric vehicle applications. The experimental setup includes a heater section, a phase change material (PCM) reservoir, and a cooling section. The heater section simulates battery heat generation with two cylindrical aluminum housings, each sized to match an 18650 battery, two cartridge heaters, and an aluminum heat sink. An airflow channel is incorporated into the cooling section. Heat transfers sequentially from the heaters to aluminum housings, the heat sink, through three copper-water heat pipes (HPs), to/from the PCM, and finally to the cooled air in the airflow channel. This innovative design eliminates direct contact between the PCM and the batteries, unlike recent studies where the PCM has been in direct contact with the batteries. Decoupling the PCM reduces system design complexity while maintaining effective thermal management. Temperature measurements at various locations are analyzed under different heater powers, air velocities, and scenarios with and without PCM. Results show that the experimental design effectively maintains battery temperatures within acceptable limits. For a power input of 16 W, steady-state temperatures are reduced by approximately 14%, 10%, and 4% with PCM compared to without PCM for air velocities of 2 m/s, 3 m/s, and 4 m/s, respectively. A transient three-dimensional numerical model was developed in ANSYS-FLUENT to provide insights into the underlying physics. The phase change was simulated using the enthalpy-porosity approach, with computational results showing reasonable agreement with experimental data.
Lifecycle Evaluation of Lithium-Ion Batteries Under Fast Charging and Discharging Conditions
Authors: Bruj Olivia , Calborean Adrian
Published: February 2025

By employing electrochemical impedance spectroscopy, we performed an impedance analysis of three commercial Li-ion Panasonic NCR18650B cells in order to investigate the direct effects of their internal impedance on the operating voltage, rate capability, and efficiency and their practical capacity. We aimed to assess their performance, safety, and longevity when distinct fast charge/discharge rates were applied. By maintaining a constant fast discharge rate of 2C, we monitored the degradation speed and the influence of the C-rates on the LIBs by applying distinct charge rates, namely, 1C, 1.5C, and 2C. In order to understand how their performance correlates with usage conditions, an SoH evolution analysis, together with a Q–Q0 total charge and energy consumption examination, was performed, taking into account that cycling monitoring is vital for ensuring their longevity and/or safety. Increasing the Icharge from 1C to 1.5C reduces the battery lifetime by ~50%, while in the case of fast charge/discharge rates of 2C, the lifetime performance decrease is almost ~70% due to a capacity loss that accelerates quickly when the charge rates increase. Moreover, for the latter cell, the last discharge rate can only go up to ~80% SoH, as the battery charge rate can no longer support faster degradation. In agreement with these results, the fluctuations in the Q–Q0 total charge become more pronounced, clearly affecting LIB efficiency. High charge rates add an additional high voltage that increases the batteries’ stress, leading to a shorter lifetime. Energy consumption data follow the same trend, in which efficiency decreases dramatically when losses appear because the internal resistance causes more and more heat to be produced during both fast charging and discharging.
Spatio-Temporal Distribution of Four Trophically Dependent Fishery Species in the Northern China Seas Under Climate Change
Authors: Ren Jun , Liu Qun , Ma Yihong , Ji Yupeng , Xu Binduo , Xue Ying , Zhang Chongliang
Published: February 2025

Climate change is a major challenge affecting marine environments, making it essential to understand species distribution responses in both time and space for effective conservation strategies. Meanwhile, varying responses of species to climate change may lead to changes in interspecific relationships and future spatial distributions. This study assessed spatial and temporal distributions of four trophically dependent species of economic importance in the China seas, including largehead hairtail (Trichiurus lepturus), Spanish mackerel (Scomberomorus niphonius), chub mackerel (Scomber japonicus), and anchovy (Engraulis japonicus). By incorporating fishery-dependent survey data and environmental variables, we developed a spatio-temporal mixed-effects model to analyze the distributional correlations among these species and predicted their distributions by the end of the century under different climate change scenarios. The results showed that the selected environmental factors influenced encounter probability and catch rates differently. Predictions for the end of the century under representative concentration pathways (RCPs) 2.6 and RCP8.5 suggested significant shifts in population densities, with species like T. lepturus and S. niphonius experiencing reduced densities and altered spatial patterns, while E. japonicus may benefit from climate change. The center of gravity for most species was projected to shift northward by the year 2050, with notable variations under RCP8.5. Additionally, spatial overlap among species was expected to decrease significantly by the year 2100, indicating increasing divergence in their distributions. This study underscores the effects of climate change on species habitat distribution and offers a scientific basis for future habitat protection.
Effects of Animal-Based and Plant-Based Nitrates and Nitrites on Human Health: Beyond Nitric Oxide Production
Authors: Membrino Valentina , Di Paolo Alice , Di Crescenzo Tiziana , Cecati Monia , Alia Sonila , Vignini Arianna
Published: February 2025

Nitrate (NO3) and nitrite (NO2) are important nitrogen compounds that play a vital role in the nitrogen cycle, contributing to plant nutrition and broader ecological functions. Nitrates are produced from nitric acid (HNO3), while nitrites come from nitrous acid (HNO2). These substances are commonly found in the environment, especially in food and water, due to contamination from both human and natural sources. Human activities are major contributors to the high levels of nitrates found in water, leading to environmental pollution. Although nitrogen is crucial for plant growth, excessive fertilizer use has caused ecological disruptions. In plants, nitrates tend to accumulate primarily in the leaves of non-leguminous crops, such as leafy vegetables, which are known for their high nitrate content. Furthermore, nitrates and nitrites are added to animal-based foods, especially processed meats and cheeses, to prevent bacterial growth, slow spoilage, and improve flavor and color. The concentration of these compounds in food can vary due to different factors like farming practices, climate, soil conditions, and food production methods. This review seeks to examine the differences between the plant-based and animal-based sources of these compounds and assess their potential impact on human health, considering also the paradigm that goes beyond nitric oxide production.
Exploring the Effects of Metformin on the Body via the Urine Proteome
Authors: Chen Yuzhen , Wang Haitong , Yang Minhui , Shen Ziyun , Gao Youhe
Published: February 2025

Metformin is the first-line medication for treating type 2 diabetes mellitus, with more than 200 million patients taking it daily. Its effects are extensive and play a positive role in multiple areas. Can its effects and potential mechanisms be explored through the urine proteome? In this study, 166 differential proteins were identified following the administration of 150 mg/(kg·d) of metformin to rats for five consecutive days. These included complement component C6, pyruvate kinase, coagulation factor X, growth differentiation factor 15, carboxypeptidase A4, chymotrypsin-like elastase family member 1, and L-lactate dehydrogenase C chain. Several of these proteins have been reported to be directly affected by metformin or associated with its effects. Multiple biological pathways enriched by these differential proteins, or proteins containing differentially modified peptides, have been reported to be associated with metformin, such as the glutathione metabolic process, negative regulation of gluconeogenesis, and the renin–angiotensin system. Additionally, some significantly changed proteins and enriched biological pathways, not yet reported to be associated with metformin’s effects, may provide clues for exploring its potential mechanisms. In conclusion, the application of the urine proteome offers a comprehensive and systematic approach to exploring the effects of drugs, providing a new perspective on the study of metformin’s mechanisms.
Electroacupuncture Modulates Programmed Cell Death 1 Ligand 1 on Peripheral and Central Nervous Systems in a Mouse Fibromyalgia Pain Model
Authors: Lin Huan-Chin , Hsu Hsin-Cheng , Liao Hsien-Yin , Chen Arbee L.P. , Lin Yi-Wen
Published: February 2025

Background: Fibromyalgia, a chronic condition that causes long-lasting pain over several months, is a global medical issue with both personal and societal implications. It is one of the hardest types of pain to heal, given the lack of objective parameters for diagnosis and progression evaluation. The main symptoms of fibromyalgia are long-lasting widespread pain alongside with anxiety, fatigue, sleep disorders, cognitive dysfunction, and obesity. Programmed cell death 1 ligand 1 (PD-L1) has been used as a target in cancer immunotherapy. It can inhibit acute and chronic pain by suppressing nociceptive neuron activity via PD-1 receptors. Methods: The current study aimed to investigate the role of PD-L1/PD1 in a mouse fibromyalgia pain model. Mice were exposed to intermittent cold stress (ICS) to produce a murine fibromyalgia model characterized using von Frey and Hargreaves tests. Results: The ICS-induced mice fibromyalgia pain model showed mechanical (2.26 ± 0.18 g) and thermal (4.36 ± 0.31 s) hyperalgesia. Nociceptive responses could be relieved with electroacupuncture, intracerebral PD-L1 injection, or Trpv1 deletion. We also identified a lower PD-1 level in the dorsal root ganglion, spinal cord, thalamus, and somatosensory cortex. In contrast, levels of pain-related kinases increased after fibromyalgia induction, an effect which could be reversed by EA, PD-L1, or Trpv1 deletion. Conclusions: Our findings shed light on the contribution of PD-L1/PD1 to EA and fibromyalgia pain, indicating its potential as a treatment target for fibromyalgia.
Clinical and Epidemiological Characteristics of Patients with Functional Stroke Mimics: A Case–Control Study from Southern Portugal
Authors: Domingos Miguel , Silva Vítor Hugo , Schuh Sara , Correia Helena , Palma Pedro , Pedro João Pedroso , Nova Bruno Vila , Marreiros Ana , Félix Ana Catarina , Nzwalo Hipólito
Published: February 2025

Background: Patients with functional neurological disorder presenting as stroke mimics or functional stroke mimics (FSMs) pose significant diagnostic challenges. In the acute phase, especially when patients are present within the therapeutic window for acute reperfusion treatments, a misdiagnosis of FSM can lead to unnecessary and costly interventions. Despite its clinical importance, the literature on the risk factors for FSM is limited. This study aims to compare the clinical and epidemiological characteristics of patients with FSM to those with confirmed acute ischemic stroke (AIS). Methods: This case–control study involved temporal matching between consecutive series of patients with FSM and controls with AIS from a single tertiary university hospital in southern Portugal. Results: A total of 188 patients were included: 64 cases (FSM) and 188 controls (AIS). The rate of stroke code activation and use of ambulance between was comparable between the two groups. The group of patients with FSM was younger (53.2 years vs. 69.5 years, p < 0.001) and had a higher proportion of females (52.4% vs. 47.6%, p = 0.001). There was no difference in terms of clinical severity at presentation. The proportion of specific signs, such as transcortical aphasia (3.1% vs. 20.9%, p = 0.014), gait abnormalities (15.6% vs. 33.9%, p = 0.004), and cranial nerve abnormalities (31.2% vs. 43.5%, p = 0.042), was lower in the FSM group compared to the AIS group. The proportion of patients on antithrombotic therapy (90.9% vs. 9.1%, p = 0.007) and antihypertensive drugs (78.5%, vs. 21.5%, p < 0.001) prior to the event was significantly higher in the AIS group. Likewise, the prevalence of cerebrovascular risk factors such as diabetes mellitus (14.3% vs. 85.7%, p = 0.005), arterial hypertension (23.8% vs. 76.2%, p = 0.001), and smoking (43.7% vs. 56.3%, p = 0.005) was lower in the FSM group compared to the AIS group. No statistically significant differences were observed in cholesterol levels or the prevalence of dyslipidemia between the two groups. Psychiatric comorbidities, including generalized anxiety disorder (71.4% vs. 28.6%, p = 0.05) and major depressive disorder (61.9% vs. 28.1%, p = 0.01), were more prevalent in the FSM group. Conclusions: Patients with FSM display different clinical and epidemiological profiles, with a higher likelihood of being younger, female, having prior psychiatric conditions, and lacking traditional cerebrovascular risk factors.
Bending Performance of Steel-Reinforced Concrete Beams Strengthened with Highly Ductile Cementitious Composites in the Compression Zone
Authors: Pan Yunfeng , Wang Junmin , Chang Bing , Ma Zhi , Li Chenggao
Published: February 2025

By replacing ordinary concrete in the compressed zone with high-ductility materials, it is possible to improve the ductility of reinforced concrete beams. The effects of the properties of the materials in the compressed zone and the height of the zone on the performance of steel-reinforced concrete beams were investigated experimentally and theoretically. The performances of the steel-reinforced concrete beams strengthened with slurry infiltrated fiber concrete (SIFCON) in the compression zone were tested by four-point bending experiments. Based on an accurate validation of the experimental results, a parametric analysis using the finite strip method was conducted. The tested results show that after replacing the ordinary concrete in the compressed zone with SIFCON, the strain distribution of the concrete beam cross-section remains linear along the height, adhering to the plane section assumption. An equation was developed using a strip method, and the prediction results showed an error of less than 11% compared to the experimental data. The theoretical calculations predict that the moment–curvature relationship of the beams enhanced with high-ductility-cement-based materials aligns well with the experimental results. This study reveals that adjusting the height, initial modulus, and compressive strength of compressed zone materials effectively enhances ductility, with minimal impact on load-bearing capacity. Increasing the material strength and height improves the ultimate curvature and maximum bending moment. The elastic modulus of the compressed zone has a greater effect on the ultimate curvature than on the maximum bending moment. With a replacement of the compressed zone height of 60 mm (section height 300 mm), the ultimate curvature increases by 177% when the elastic modulus of the material is increased by 2.5 times. The present study provides a calculation method for the retrofitting and reinforcement of over-reinforced concrete beams.
Historical, Geometrical, and Constructive Analyses of the Rotonda Roman Baths in Catania (Sicily)
Authors: Tardo Carola , Floriano Laura , Liuzzo Mariangela , Gueli Anna Maria , Stella Giuseppe , Margani Giuseppe
Published: February 2025

One of the main icons of the Roman civilisation are thermal baths, built as public places for personal hygiene, body and mind relaxation, recreation, social encounters, and sport. In Sicily, there is evidence of several thermal buildings dating back to the time of the Roman Empire. Notably, the “Terme della Rotonda”, in the city of Catania, have always attracted strong interest due to their intricate and fascinating architecture. However, at present the dating of the building remains within the complex is still uncertain, and diverse assumptions have been advanced on their original use. In this framework, this study presents the findings of a multidisciplinary research initiative aimed at advancing knowledge of this thermal complex. To this end, a 3D integrated survey of the complex was carried out, and architectural, typological, and construction analyses were conducted to examine the primary building elements. These investigations enabled us to provide detailed insights into the materials and construction techniques used, leading to a new hypothesis on the original layout of the thermal rooms. Additionally, a virtual platform of the archaeological site was developed to serve as a spatial information database, facilitating both scientific research and the dissemination of knowledge about the complex.
ATP-Dependent Chromatin Remodeler CSB Couples DNA Repair Pathways to Transcription with Implications for Cockayne Syndrome and Cancer Therapy
Authors: Bilkis Rabeya , Lake Robert J. , Fan Hua-Ying
Published: February 2025

Efficient DNA lesion repair is crucial for cell survival, especially within actively transcribed DNA regions that contain essential genetic information. Additionally, DNA breaks in regions of active transcription are prone to generating insertions and deletions, which are hallmark features of cancer genomes. Cockayne syndrome protein B (CSB) is the sole ATP-dependent chromatin remodeler that is essential for coupling DNA repair pathways with transcription, leading to more efficient DNA repair in regions of active transcription. CSB is best known for its essential function in transcription-coupled nucleotide excision repair (TC-NER), a process that rapidly removes helix-distorting DNA lesions that stall RNA polymerase II, such as those created by chemotherapeutic platinum compounds and UV irradiation. In addition to NER, CSB has also been reported to couple homologous recombination to transcription. Most recently, CSB has also been shown to couple single-strand DNA break repair to transcription. In this review, we will discuss the overlapping and distinct mechanisms by which CSB couples these different DNA repair pathways to transcription. We will also discuss how these CSB functions may account for Cockayne syndrome and the emerging roles of CSB as an innovative target for cancer therapy.
A Numerical Investigation of the Potential of an Enhanced Geothermal System (EGS) for Power Generation at Mount Meager, BC, Canada
Authors: Chai Yutong , Chen Zhuoheng , Yuan Wanju , Yin Shunde
Published: February 2025

This study aims to better harness the geothermal potential of Mount Meager in British Columbia, a premier reserve of geothermal resources in Canada. Numerical investigations explore the feasibility and optimization of an Enhanced Geothermal System to boost geothermal energy extraction capabilities. Utilizing COMSOL Multiphysics, the model simulates non-isothermal fluid flow and heat transfer through complex subsurface geology with discrete fracture planes. The sensitivity analyses assess the impact of various operational parameters, including injection strategies, reservoir characteristics, and wellbore configurations on heat extraction efficiency. These analyses indicate that a higher injection rate, lower injection temperatures, and optimized fracture areas significantly enhance system performance by maximizing thermal energy capture and minimizing thermal breakthrough. Additionally, specific wellbore configurations, particularly the triplet setup with deeper depth, significantly improve geothermal fluid circulation and heat extraction compared to doublet configurations at shallower depths. This study reveals that the base case scenario of the EGS could generate approximately 8.311× 109 kWh over 30 years, while optimization strategies could elevate potential production to up to 16.68× 109 kWh. These findings underscore the critical role of carefully designed operational strategies that leverage local geological and thermal characteristics to optimize geothermal systems, thereby enhancing efficiency and promoting sustainable energy development at Mount Meager.
Use of Biowaste for Sodium Removal in Mediterranean Irrigation Water: A Sustainable Approach
Authors: Núñez-Gómez Dámaris , Maciá-Vázquez Alejandro Andy , Giménez-Valero Carlos , Martínez-Nicolás Juan José , Legua Pilar , Melgarejo Pablo
Published: February 2025

The Mediterranean region faces significant water scarcity, a challenge intensified by climate change, impacting both agricultural productivity and water quality. High sodium levels in irrigation water compromise soil structure, leading to reduced crop yields and economic strain. This study investigates the use of sustainable adsorbents derived from agricultural residues (almond shell, eggshell, and pumice) for the removal of sodium from irrigation water. These materials, widely available in the Mediterranean, support circular economy principles by repurposing biowaste to address agricultural challenges. Adsorption experiments were conducted using real irrigation water, capturing the complexity of its physicochemical properties to evaluate the effectiveness of these biosorbents under practical conditions. A Central Composite Rotational Design (CCRD) was applied to optimize adsorption parameters, focusing on adsorbent concentration, agitation, and contact time. Kinetic studies indicated that sodium adsorption adhered to a pseudo-second order model, suggesting a chemically controlled process. Isotherm analysis, with a strong fit to the Jovanovic model, confirmed a predominantly monomolecular adsorption mechanism across all adsorbents, while the Freundlich model highlighted site heterogeneity. Microscopy and energy-dispersive X-ray spectroscopy (EDX) revealed structural modifications in the adsorbents before and after treatment. The porous internal structure of the almond shell displayed significant sodium retention, while the calcified eggshell surface showed high initial adsorption efficiency but rapid site saturation. Pumice, noted for its extensive porosity, sustained adsorption capacity even with surface deposits formed during treatment. This research demonstrates the potential of biowaste-derived adsorbents for efficient sodium removal from complex aqueous systems, offering a viable solution for sustainable agriculture and improved soil and water management in Mediterranean regions.
Optimization of Coarse Aggregate Size Distribution for Preplaced Aggregate Cement Paste Coating Concrete
Authors: Duan Denghui , Chen Jiajian , Wang Wenxue
Published: February 2025

The novel casting method of preplaced aggregate cement paste coating (PACPC) concrete is helpful in solving engineering problems. The effects of aggregate particle size distribution and W/C on groutability, mechanical properties, and cement efficiency were investigated through experimental and theoretical analysis. The results showed that, with the increase in the proportion of aggregate with finer size, the groutability first decreased and then increased, while the compressive strength and cement efficiency first increased and then decreased. Widening the particle size distribution increased the aggregate packing density by 12.3%, the compressive strength by 12.7%, and the cement efficiency by 30.3% but decreased the groutability by 3.5%. The packing density of the aggregate skeleton was found to be a governing parameter of the performances of PACPC. As the groutability of grouted preplaced aggregate is generally contradictory to the strength, a proper balance should be struck between the fresh and hardened performance.
Performance Evaluation of an Eco-Friendly Prime Coat Material Formulated with Reclaimed Asphalt Pavement and Waste Bio-Oil
Authors: Liu Shaoxiong , Liu Chaochao , Yang Zhiyu , Li Jue , Gong Jian
Published: February 2025

To address the insufficient interlayer bonding performance and high preparation costs associated with conventional prime coat materials for semi-rigid base asphalt pavement, in this study, we utilized waste bio-oil to enhance asphalt–aggregate separation in recycled asphalt pavement (RAP) and collected the filtrate after separation. The RAP–bio-oil filtrate acts as a diluent, which is reintroduced into the asphalt to form a novel prime coat material: RAP–bio-oil filtrate cut-back asphalt (RFCA). The optimal proportions of each component in RFCA were determined through penetration tests, interlayer shear tests, and interlayer tensile tests. Subsequently, interlayer shear strength tests were conducted to evaluate the bond strength of RFCA compared to traditional prime coat materials, such as PC-2 emulsified asphalt (PC-2 EA) and kerosene cutback asphalt (KCA). Additionally, interlayer shear fatigue tests were performed to assess the durability of the bond provided by RFCA between the surface and base layers. The experimental results indicate that the optimal formulation for RFCA comprises 60% asphalt by mass of the RAP–bio-oil filtrate and 10% penetrant agent by mass of the RAP–bio-oil filtrate. Under conditions of 15 °C, 40 °C, and 15 °C water immersion, the interlayer shear strength of RFCA demonstrates an enhancement compared to PC-2 EA and KCA. Compared to PC-2 EA, the interlayer shear fatigue life of RFCA improved by 39.7% at a stress ratio of 0.2, 40.8% at 0.3, 51.2% at 0.4, and 40.3% at 0.5. The application of RFCA as a prime coat material significantly enhances interlayer durability. Based on the cost analysis, the application cost per square meter for RFCA is lower than that of PC-2A. Consequently, RFCA presents a viable option as a green, renewable, low-cost, and high-performance prime coat material for application on semi-rigid base asphalt pavement.
Computational Representation of Fractional Inequalities Through 2D and 3D Graphs with Applications
Authors: Younis Muhammad , Mehmood Ahsan , Samraiz Muhammad , Rahman Gauhar , Haque Salma , Aloqaily Ahmad , Mlaiki Nabil
Published: February 2025

The aim of this research article is to use the extended fractional operators involving the multivariate Mittag–Leffler (M-M-L) function, we provide the generalization of the Hermite–Hadamard–Fejer (H-H-F) inequalities. We relate these inequalities to previously published disparities in the literature by making appropriate substitutions. In the last section, we analyze several inequalities related to the H-H-F inequalities, focusing on generalized h-convexity associated with extended fractional operators involving the M-M-L function. To achieve this, we derive two identities for locally differentiable functions, which allows us to provide specific estimates for the differences between the left, middle, and right terms in the H-H-F inequalities. Also, we have constructed specific inequalities and visualized them through graphical representations to facilitate their applications in analysis. The research bridges theoretical advancements with practical applications, providing high-accuracy bounds for complex systems involving fractional calculus.
A Bayesian State-Space Approach to Dynamic Hierarchical Logistic Regression for Evolving Student Risk in Educational Analytics
Authors: Mosia Moeketsi
Published: February 2025

Early detection of academically at-risk students is crucial for designing timely interventions that improve educational outcomes. However, many existing approaches either ignore the temporal evolution of student performance or rely on “black box” models that sacrifice interpretability. In this study, we develop a dynamic hierarchical logistic regression model in a fully Bayesian framework to address these shortcomings. Our method leverages partial pooling across students and employs a state-space formulation, allowing each student’s log-odds of failure to evolve over multiple assessments. By using Markov chain Monte Carlo for inference, we obtain robust posterior estimates and credible intervals for both population-level and individual-specific effects, while posterior predictive checks ensure model adequacy and calibration. Results from simulated and real-world datasets indicate that the proposed approach more accurately tracks fluctuations in student risk compared to static logistic regression, and it yields interpretable insights into how engagement patterns and demographic factors influence failure probability. We conclude that a Bayesian dynamic hierarchical model not only enhances prediction of at-risk students but also provides actionable feedback for instructors and administrators seeking evidence-based interventions.
Clinical Resolution of Plantar Warts Using the Needling Technique
Authors: Sobrín-Valbuena María-Luisa , Aldana-Caballero Alberto , Martín-Casado Laura , Palomo-Fernández Inés , Mayordomo Raquel , Marcos-Tejedor Félix
Published: February 2025

Background: Plantar warts, caused by the human papillomavirus (HPV), are a common skin condition characterized by painful lesions on the soles of the feet. These lesions can significantly impact skin appearance, quality of life, and, in severe cases, mobility. Traditional treatment methods, such as chemical cauterization or pharmaceutical therapies, are often painful and require multiple visits to achieve complete wart removal and skin regeneration. This study aims to assess the clinical effectiveness of the needling technique as an alternative treatment. This method involves repeatedly puncturing the lesion under local anesthesia or posterior tibial nerve block to trigger an immune response and promote wart clearance. Methods: A total of 26 patients underwent the needling procedure, which included puncturing the wart under local anesthesia, followed by wound dressing and topical application of iodopovidone to facilitate scab formation. Follow-up visits were scheduled until full wart resolution was observed. Analgesics were provided for moderate pain management when necessary. Results: After 30 days, a success rate of 57.7% was achieved. Patients reported mild pain, which subsided within a few days, and expressed high levels of satisfaction with the treatment outcome. Conclusions: The needling technique emerges as an effective alternative to chemical treatments, offering a notable wart clearance rate. Its use under local anesthesia enhances patient comfort and reduces treatment-associated anxiety compared to conventional therapies.
Enhanced Control Strategies for Improving Low Fault Ride-Through Capability of Grid-Connected Doubly Fed Induction Wind Turbines
Authors: Yang Yuanjia , Gao Man , Zhou Zhenxiong
Published: February 2025

The DFIG faces challenges in providing fast and accurate support during grid voltage fluctuations. Severe voltage dips can trigger peak currents, which may damage the converter equipment and even lead to the disconnection of turbines from the grid. This paper deeply analyzes the transient characteristics of stator flux dynamics under voltage dips and identifies the transient component of the rotor-induced EMF as the primary cause of rotor overcurrent. To address this issue, an improved control strategy is proposed that utilizes stator current as a rotor voltage compensation method to effectively suppress rotor overcurrent. Furthermore, an LVRT hardware protection scheme, combining both Crowbar and Chopper circuits, is designed to handle converter capacity limitations during deep voltage dips. The proposed control strategy and protection scheme are validated through simulations conducted on the Matlab/Simulink platform, demonstrating their effectiveness and accuracy.
Applications of Electrical Load Modelling in Digital Twins of Power Systems
Authors: Jayasinghe Hasith , Gunawardane Kosala , Nicholson Robert
Published: February 2025

Accurate electrical load modeling is crucial for both transient and steady-state power system studies. Although various load modeling techniques are documented in the literature, a comprehensive review of the latest advancements in these techniques is lacking. This manuscript addresses this gap by presenting a detailed review of load modeling techniques, emphasizing their applications, recent advancements, and key distinguishing characteristics. Additionally, it explores the role of Digital Twin Models (DTM) in power systems, which offers a virtual representation of the system to simulate diverse operational scenarios and inform future investment and operational decisions. The integration of load models into DTMs poses challenges, such as computational demands and microcontroller limitations, which can be alleviated by adopting advanced load modeling techniques. This work further examines the application of load modeling techniques in the design and development of DTMs for power systems, as well as strategies to enhance the performance of load models in DTM applications. Finally, the manuscript outlines future research opportunities for integrating load modeling within DTM-based power system applications.
Automatic Fault Classification in Photovoltaic Modules Using Denoising Diffusion Probabilistic Model, Generative Adversarial Networks, and Convolutional Neural Networks
Authors: da Silveira Junior Carlos Roberto , Sousa Carlos Eduardo Rocha , Fonseca Alves Ricardo Henrique
Published: February 2025

Current techniques for fault analysis in photovoltaic (PV) systems plants involve either electrical performance measurements or image processing, as well as line infrared thermography for visual inspection. Deep convolutional neural networks (CNNs) are machine learning algorithms that perform tasks involving images, such as image classification and object recognition. However, to train a model effectively to recognize different patterns, it is crucial to have a sufficiently balanced dataset. Unfortunately, this is not always feasible owing to the limited availability of publicly accessible datasets for PV thermographic data and the unequal distribution of different faults in real-world systems. In this study, three data augmentation techniques—geometric transformations (GTs), generative adversarial networks (GANs), and the denoising diffusion probabilistic model (DDPM)—were combined with a CNN to classify faults in PV modules through thermographic images and identify the type of fault in 11 different classes (i.e., soiling, shadowing, and diode). Through the cross-validation method, the main results found with the Wasserstein GAN (WGAN) and DDPM networks combined with the CNN for anomaly classification achieved testing accuracies of 86.98% and 89.83%, respectively. These results demonstrate the effectiveness of both networks for accurately classifying anomalies in the dataset. The results corroborate the use of the diffusion model as a PV data augmentation technique when compared with other methods such as GANs and GTs.
Thyroid-Active Agents Triiodothyronine, Thyroxine and Propylthiouracil Differentially Affect Growth, Intestinal Short Chain Fatty Acids and Microbiota in Little Yellow Croaker Larimichthys polyactis
Authors: Liang Xiao , Zhang Yu , Ye Ting , Liu Feng , Lou Bao
Published: February 2025

Thyroid dysfunction may affect the intestinal microbiota through short-chain fatty acids (SCFAs) in marine fish. This study investigated the effects of triiodothyronine (T3, 20 ng/g) and thyroxine (T4, 20 ng/g), and propylthiouracil (PTU, 5000 ng/g) on growth performance, intestinal SCFA profiles, and microbiota composition in little yellow croakers Larimichthys polyactis. The results showed that dietary thyroid-active agent supplementation significantly decreased weight gain, and specific growth ratio. Moreover, dietary T3, T4, and PTU induced the states of hyperthyroidism, hyperthyroidism, and hypothyroidism, respectively, leading to differential alterations in intestinal SCFA profiles. Specifically, only dietary T4 supplementation significantly increased the diversity of intestinal microbiota. Our findings suggest that the genera Vibrio and Sediminibacterium play key roles in multiple metabolic pathways within the host intestine. Correlation analyses further indicated that intestinal acetic acid and isobutyric acid were characteristic metabolites involved in the alteration of the genus Vibrio abundance. These results provide a foundation for further investigation into the effects of thyroid-disrupting activities on growth, intestinal SCFA profiles, and microbiota composition in marine fish.
The Yearlong Effect of COVID-19 on Food Safety: Consumer Practices and Perceptions Using Longitudinal Consumer Surveys and Focus Groups
Authors: Thomas Merlyn Suzanne , Kontor-Manu Elma , Feng Yaohua
Published: February 2025

Coronavirus disease 2019 (COVID-19) caused many consumers in the United States to change their perceptions and food handling practices at the height of the pandemic. We used a quantitative–qualitative mixed-method approach to assess consumers’ risk perceptions and food safety practices during the COVID-19 pandemic. Nine waves of surveys were distributed to an online consumer panel over a 13-month period (April 2020–May 2021), and four waves of focus groups were conducted (May–July 2020 and June 2021). While the pandemic elevated peoples’ perceptions of risks related to food safety practices, many consumers were reverting to past behaviors by May 2021. Participants asserted high confidence in their food safety measures; however, they perceived a low risk of contracting COVID-19 from food. Contrasts in food handling became apparent when assessing different age groups; observations revealed that practices in households with high-risk individuals differed significantly from those without. Although not recommended, the practice of washing produce with soap was consistent, predicting a possible continuation of this practice over time. This study highlights various factors that food safety educators and policymakers need to consider for effective communication about risks associated with food safety practices in preparation for pandemics and other major health events.
Effects of Selenium Nanoparticle Application on Flavor Volatiles of Aromatic Rice
Authors: Luo Haowen , Zhang Simin , Pu Xiaojuan , Xia Longfei , Yi Wentao , Yu Xianghai , Zuo Changjian , Tang Xiangru
Published: February 2025

Aromatic rice is famous for its pleasant aroma which consists of many flavor volatiles. The present study was to explore the effects of selenium nanoparticle (SeNP) application on flavor volatiles of aromatic rice based on a worldwide database of flavor molecules accessed on November 19 2024. A field experiment was carried out with the foliar application of SeNP at early growth stage (S1), middle growth stage (S2), and late growth stage (S3) of aromatic rice plants in two cropping seasons. In the control group (CK), no selenium-based treatment was applied. There were in total 27 and 24 flavor volatiles registered in FlavorDB2 detected in aromatic rice in the early and late cropping seasons, respectively. The flavors that appear most often were fat, fresh, fruit, aldehydic, green, sweet, citrus, and waxy. Compared with CK, S3 treatment caused the absence of 5 and 4 flavor volatiles in the early and late seasons, respectively. S2 treatment caused the exclusive presence of 2-undecenal and 3-hexenal,(Z)- in the early season and the exclusive presence of 2-hexenoic acid and decanal in the late season. The results of principal components analysis (PCA) showed that S2 and S3 treatments substantially impacted the flavor volatiles of aromatic rice in the early season while S1 and S2 treatments substantially impacted the flavor volatiles of aromatic rice in the late season. There were 12 and 4 differential flavor volatiles found in the early and late cropping seasons respectively. S2 treatment significantly increased the content of 10 flavor volatiles including 2-acetyl-1-pyrroline, benzaldehyde, 2-hexenoic acid, hexanoic acid, octanal, 2-octenal,(E)-, heptanal, 2,4-heptadienal,(E,E)-, 3-hexenoic acid,(E)-, and n-hexadecanoic acid. In addition, the effects of SeNP on flavor volatiles varied between different cropping seasons indicated that climate had a substantial impact on flavor volatiles in aromatic rice. Overall consideration, the heading stage, i.e., the middle growth stage, is the most suitable stage to apply SeNP to maximize the benefits on the flavor volatiles of aromatic rice.
Determining a Suitable Local Green Biorefinery Model for Adoption by Irish Livestock Farmers Using a Mixed-Method Co-Design Employing Economic and Geographical Information Systems Analysis
Authors: Hand Alice , Marsh Emily , Giron Dominguez Carmen , Menon Abhay , Rubhara Theresa , McMahon Helena , O’Dwyer Breda , Holloway Paul , Gaffey James
Published: February 2025

To support the ambitious bioeconomy vision outlined in Ireland’s Bioeconomy Action Plan, there is an urgent need to bring together the necessary stakeholders required to implement this vision. Farmers and other primary producers who oversee the production of sustainable biomass constitute one of the most important categories of stakeholders in the bio-based value chain. To ensure scalable, long-lasting bioeconomy collaboration, it is essential that farmers are involved in developing this bioeconomy vision. The current study provides a mixed-methods approach to co-design a green biorefinery vision with Irish farmers and other key value-chain actors. The selected value chain targeting a medium-scale grass silage biorefinery focused on the production of eco-insulation materials, with protein and biogas co-products for local markets. This was then assessed economically using an economic model, which provided a payback period of five years. To identify suitable sites for deployment of the green biorefinery in rural areas, geographical information systems (GIS) analysis was undertaken, considering various environmental, socio-economic and infrastructural variables, which identified 26 potential sites for deployment of the green biorefinery model in Ireland. This study found that early engagement with and inclusion of the farmers in a co-designed process of innovation and alternative revenue streams for them is essential. While a preferred cooperative-based business model for a grass silage biorefinery was identified in consultation with the multiple stakeholders, further research on its long-term commercial sustainability is proposed as future research.