bluuebunny/crossref_metadata_2025 huggingface dataset:
Exploring the Posterolateral Corner of the Knee Joint: A Detailed Review of Recent Literature
Authors: Abu-Mukh Assala , Lee Seungyup , Rhim Hye Chang , Jang Ki-Mo
Published: February 2025

One of the least understood and most elaborate and neglected knee stabilizers is the posterolateral corner (PLC) complex. PLC injury is associated with a high risk of re-injury, early athletic career termination, instability, progressive osteoarthritis, and a high risk of artificial knee replacement. The growing focus on the PLC, along with various recent anatomical and biomechanical studies, has provided further insights into the anatomy and function of posterolateral structures in knee stabilization and kinematics. The PLC should be considered as a functional unit, not only an anatomical unit. A low suspicion threshold should be maintained when considering PLC injuries, and thorough history evaluation, clinical examination, and adequate imaging should be conducted to reduce the chances of neglected PLC injuries. Various PLC repair and reconstruction techniques, ranging from non-anatomical to anatomical, have been introduced, with treatments increasingly favoring minimal incisions and arthroscopic procedures. Recent studies on the PCL have reported an increasing number of satisfactory clinical outcomes. This study aimed to provide a deeper understanding, as well as review the current and most feasible treatments for PLC injuries.
Evaluation of Radiation Dose and Image Quality in Clinical Routine Protocols from Three Different CT Scanners
Authors: Prabsattroo Thawatchai , Phaorod Jiranthanin , Tathuwan Piyaphat , Tongluan Khanitta , Punikhom Puengjai , Maharantawong Tongjit , Sudchai Waraporn
Published: February 2025

Computed tomography examination plays a vital role in imaging and its use has rapidly increased in radiology diagnosis. This study aimed to assess radiation doses of routine CT protocols of the brain, chest, and abdomen in three different CT scanners, together with a qualitative image quality assessment. Methods: A picture archiving and communication system (PACS) and Radimetrics software version 3.4.2 retrospectively collected patients’ radiation doses. Radiation doses were recorded as the CTDIvol, dose length product, and effective dose. CT images were acquired using the Catphan700 phantom to evaluate image quality. Results: The findings revealed that median values for the CTDIvol and DLP across the brain, chest, and abdomen protocols were lower than the national and international DRLs. Effective doses for brain, chest, and abdomen protocols were also below the median value of R. Smith-Bindman. Neusoft achieved higher spatial frequencies in brain protocols, while Siemens outperformed others in chest protocols. Neusoft consistently exhibited superior high-contrast resolution. Siemens and Neusoft outperformed low-contrast detectability, while Siemens also outperformed the contrast-to-noise ratio. In addition, Siemens had the lowest image noise in brain protocols and high uniformity in chest and abdomen protocols. Neusoft showed the lowest noise in chest and abdomen protocols and high uniformity in the brain protocol. The noise power spectrum revealed that Philips had the highest noise magnitude with different noise textures across protocols and scanners. Conclusions: This study provides a comprehensive evaluation of radiation doses and image quality for three different CT scanners using standard clinical protocols. Almost all CT protocols exhibited radiation doses below the DRLs and demonstrated varying image qualities across each protocol and scanner. Selecting the right CT scanner for each protocol is essential to ensure that the CT images exhibit the best quality among a wide range of CT machines. The MTF, HCR, LCD, CNR, NPS, noise, and uniformity are suitable parameters for evaluating and monitoring image quality.
From Material to Solution: Implementing Shape Memory Behavior of Thermoplastic Polymers in Commercial FEA Software for Structural Analysis
Authors: Neumann Fabian , Cerbe Ferdinand , Sinapius Michael
Published: February 2025

The production of one-piece composite hollow profiles with undercuts presents significant challenges to conventional mold concepts. Mandrels made of thermoplastic shape-memory polymers could facilitate demolding and reduce tooling costs. To design molds in a commercial environment, it is critical to determine their behavior using off-the-shelf Finite Element Analysis (FEA) software. This paper investigates all of the necessary steps, from the material model generation, its implementation in commercial FEA software, to the simulation of shape-memory test specimens under unidirectional tensile loading with off-the-shelf FEA modules. The material investigated is PA6. Differential Scanning Calorimetry (DSC) is used to determine the glass transition, crystallization and melting temperatures of the material. The Dynamic Mechanical Analysis (DMA) is then used to determine the elastic modulus versus temperature and frequency. A viscoelastic material model is derived from DMA data. Parameters necessary for the implementation are derived by using fully open-source Python scripts. A unidirectional shape-memory tensile test simulation is performed and compared with the experimental data from a thermo-mechanical shape-memory test. The applied methods allow for the generation and implementation of a viscoelastic material model in commercial FEA software. The simulation shows good results in comparison with the thermo-mechanical shape-memory test. In conclusion, the straightforward “from material to solution” path presented allows us to model and simulate the shape memory behavior of viscoelastic polymers.
A Spatially Informed Machine Learning Method for Predicting Sound Field Uncertainty
Authors: Chen Xiangmei , Li Chao , Wang Haibin , Tai Yupeng , Wang Jun , Migniot Cyrille
Published: February 2025

Predicting the uncertain distribution of underwater acoustic fields, influenced by dynamic oceanic parameters, is critical for acoustic applications that rely on sound field characteristics to generate predictions. Traditional methods, such as the Monte Carlo method, are computationally intensive and thus unsuitable for applications requiring high real-time performance and flexibility. Current machine learning methods excel at improving computational efficiency but face limitations in predictive performance, especially in shadow areas. In response, a machine learning method is proposed in this paper that balances accuracy and efficiency for predicting uncertainties in deep ocean acoustics by decoupling the scene representation into two components: (a) a local radiance model related to environmental factors, and (b) a global representation of the overall scene context. Specifically, the internal relationships within the local radiance are first exploited, aiming to capture fine-grained details within the acoustic field. Subsequently, local clues are combined with receiver location information for joint learning. To verify the effectiveness of the proposed approach, a dataset of historical oceanographic data has been compiled. Extensive experiments validate the efficiency compared to traditional Monte Carlo techniques and the superior accuracy compared to existing learning method.
Five New Species of Marquandomyces (Clavicipitaceae, Ascomycota) from Asia
Authors: Peng Lu-Yao , Wang Yi-Fan , Song He , Urinboev Islomjon , Zhuang Wen-Ying , Gafforov Yusufjon , Wang Xin-Cun
Published: February 2025

Marquandomyces is a recently established genus in the Clavicipitaceae and previously comprised only two known species. This study expands the understanding of its generic concept and species diversity through comprehensive fungal diversity surveys conducted from soil samples in China and Uzbekistan. As a result, five new species were identified based on morphological characterization and molecular phylogenetic analyses, and their detailed descriptions and illustrations are provided. This study emphasizes the unique ecological roles and specific habitats of these fungi and contributes to a relatively deep understanding of the genus Marquandomyces as well as its ecological significance.
Assessment of the Sex Hormone Profile and Its Predictive Role in Consciousness Recovery Following Severe Traumatic Brain Injury
Authors: Naseri Alavi Seyed Ahmad , Pourasghary Sajjad , Rezakhah Amir , Habibi Mohammad Amin , Kazempour Aydin , Mahdkhah Ata , Kobets Andrew
Published: February 2025

Introduction: Traumatic brain injuries (TBIs) are conditions affecting brain function caused by blunt or penetrating forces to the head. Symptoms may include confusion, impaired consciousness, coma, seizures, and focal or sensory neurological motor injuries. Objective: This study evaluated sex hormone profiles and their predictive role in returning consciousness after severe traumatic brain injury. Materials and Methods: We included 120 patients with TBIs and collected comprehensive information about each patient, including the cause of the trauma, age, gender, Glasgow Coma Scale (GCS) score, Injury Severity Score (ISS), and neuroradiological imaging data. The ISS was used to assess the severity of the trauma. At the same time, the lowest GCS score was recorded either before sedation and intubation in the emergency room or by emergency medical services personnel. For female participants, samples were collected during the luteal phase of the menstrual cycle (days 18 to 23). Results: The mean age of male patients was 33.40 years, ranging from 23 to 45 years, while female patients had an average age of 34.25 years, ranging from 25 to 48 years. The primary cause of injury for both genders was motor vehicle accidents. In male patients, testosterone levels were significantly higher in those classified as responsive (RC) compared to those non-responsive (NRC), with levels of 2.56 ± 0.47 ng/mL versus 0.81 ± 0.41 ng/mL (p = 0.003). A cut-off point of 1.885 ng/mL for testosterone levels in males was established, achieving a sensitivity and specificity of 86.7% and 86.7%, respectively. In female patients, progesterone levels were elevated in those who regained consciousness, measuring 1.80 ± 0.31 ng/mL compared to 0.62 ± 0.31 ng/mL (p = 0.012). A cut-off point of 1.335 ng/mL for progesterone levels in females was determined, with a sensitivity and specificity of 93.3% and 86.7%, respectively. Conclusions: We can conclude that sex hormone levels in the acute phase of TBIs can vary between males and females. Notably, serum testosterone levels in males and progesterone levels in females with TBIs are significant prognostic factors for assessing the likelihood of regaining consciousness after such injuries. These findings underscore the importance of considering sex hormone profiles in TBI recovery prognosis.
C-2,8,14,20-tetra(propyl)-5,11,17,23-tetrakis(N–(piperidine)methyl)calix[4]resorcinarene
Authors: Niño-Ramírez Victor Alfonso , Rivera-Monroy Zuly Jenny , Maldonado Mauricio
Published: February 2025

Calix[4]resorcinarenes are polyhydroxylated macrocyclic compounds with four units of resorcinol. These compounds can be derivatized through modifications at the upper rim, allowing reactivity with secondary amines to produce Mannich base derivatives via Mannich-type aminomethylation reactions. In this paper, we report the reaction of C-tetra(propyl)calix[4]resorcinarene with piperidine in acetonitrile. The aminomethylated compound C-2,8,14,20-tetra(propyl)-5,11,17,23-tetrakis(N–(piperidine)methyl)calix[4]resorcinarene was obtained with a 52% yield, with an exact mass of 1044.6994 u and a mass error of 7.6 ppm. The reaction progress and product formation were monitored by RP-HPLC, and the compound was characterized using LC ESI-TOF/MS, one- and two-dimensional 1H and 13C NMR, and FTIR spectroscopy. Chromatographic and spectroscopy data are presented and discussed.
Modification of Aluminum Hydroxide by Ball Milling: A Feasible Method to Obtain High-Efficiency Flame Retardants for Production of High-Performance EVA Composites
Authors: Yang Man , Yuan Bihe
Published: February 2025

Aluminum hydroxide (ATH) is an environmentally friendly flame retardant widely employed in polymers. However, the high loading of ATH, due to its limited efficiency, potentially compromises other properties, including mechanical properties. This work explores a feasible ball milling strategy for high-efficiency ATH-based flame retardants (PPA-ATH and PPOA-ATH), fabricated by employing phenylphosphinic acid (PPA) and phenylphosphonic acid (PPOA) as surface modifiers and water as the processing solvent. The characterization study of PPA-ATH and PPOA-ATH demonstrates that ball milling effectively reduces their particle size, enhances their specific surface area, and improves their dispersibility within the ethylene-vinyl acetate (EVA) matrix. PPOA-ATH exhibited superior capabilities in enhancing the thermal stability and flame retardancy of EVA composites compared to PPA-ATH. The incorporation of PPOA-ATH resulted in the retarding in the temperature at 50% mass loss by 21 °C and an increase in the char residue of 34.5% at 700 °C. Furthermore, PPOA incorporation led to reductions of 81.0% in the peak heat release rate, 48.1% in the total heat release, 73.7% in the peak smoke production rate, and 41.2% in the total smoke production compared to neat EVA. This green modification strategy successfully addresses the application limitations of ATH, providing a feasible and environmentally friendly method for high-efficiency ATH-based flame retardant fabrication.
Mechanical Properties of 3D Printed vs. Subtractively Manufactured Composite Resins for Permanent Restorations: A Systematic Review
Authors: Mandurino Mauro , Cortili Silvia , Coccoluto Luca , Greco Katia , Cantatore Giuseppe , Gherlone Enrico Felice , Vichi Alessandro , Paolone Gaetano
Published: February 2025

Objective: To conduct a systematic review on the mechanical properties of 3D printed resin-based composites when compared with those of subtractively manufactured resin-based composites. Materials and Methods: In vitro studies comparing the mechanical properties of additively and subtractively manufactured resin-based composites were sought. A systematic search, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), was performed on four databases (PubMed, Embase, Web of Science, and Scopus) for articles published until 23 December 2024. The quality of the studies was assessed with the QUIN tool (risk-of-bias tool for assessing in vitro studies conducted in dentistry) and those assessed with a high risk of bias were excluded. Results: Of the 1058 screened articles, 13 were included in this review. A noticeable heterogeneity emerged in the methodologies employed, mainly regarding samples’ fabrication techniques, materials involved, and parameters analyzed. The most investigated mechanical property was fracture resistance, followed by microhardness, flexural strength, and wear behavior. Among the tested materials, the most used 3D printable resins were VarseoSmile Crown Plus (Bego) and Crowntec (Saremco Dental), whereas for the subtractive groups, the most investigated was Brilliant Crios (Coltène). Conclusions: The mechanical properties of 3D printed resins designed for permanent restorations are still lower than those of their subtractively manufactured counterparts. Moreover, in the long term, the degradation processes that inevitably occur might significantly increase their chances of failure.
Autogenously Calcined Clays from Coal Tailings Dumps as Supplementary Cementitious Material: From Exploratory Investigations to an Industrial Trial
Authors: Overmann Steffen , Vollpracht Anya
Published: February 2025

Autogenously calcined clays from tailings dumps, which are formed by the ignition of the contained residual coal, represent a huge resource of potentially pozzolanic material worldwide. This work presents preliminary studies of samples from the Western coal regions in Germany and investigations on the first industrially produced cement with autogenously calcined tailings concerning its suitability as supplementary cementitious material (SCM). Samples of the tailings materials and blended cements were thoroughly characterized physically, chemically and mineralogically. The reactivity was studied using the R3 test and mortar compressive strength testing. The influence on cement hydration was studied using X-ray diffractometry (XRD) and isothermal calorimetry. The preliminary investigations showed that the material is basically suitable as SCM, as it consists mainly of SiO2 and Al2O3, which partially occurs in X-ray amorphous form and has a low content of impurities, which can impair cement properties such as carbon or sulfur. The R3 reactivity and the relative compressive strength differed significantly depending on the sample. For the industrial cement production trial, low-processed material was used which still contained inert fractions. The average sample showed a relatively low R3 reactivity but still significantly higher than mostly inert materials such as limestone or quartz powder. Calorimetry and XRD investigations on cement pastes showed that the clinker reactions remain basically unaffected by the tailings. Mortar tests showed that the material contributes to strength development at a late age. It can be concluded that the tailings are basically suitable as SCM and, in appropriate blends, a clinker factor and, thus, the CO2 footprint of cement can be reduced.
Experimental Study on the Compression Characteristics of Sand–Silt–Clay Mixtures
Authors: Li Tao , Li Jixiao , Li Bingyang , Yu Guangtao
Published: February 2025

In order to investigate the influence of the coexistence of clay and silt on the compression characteristics of sand, one-dimensional compression consolidation tests were carried out on reconstituted saturated sand–silt–clay mixtures with a constant initial void ratio, and the effects of fines content (FC) and clay–silt ratio (CS) on the compression characteristics of mixed soils were studied. The mechanism of the experimental results was additionally explained from a microscopic perspective. The test results show that: the compressibility of mixed soil increased with the increase in FC; the compressibility change rule of mixed soils with different CS is consistent under the same FC; the influence of CS on the e–lgp (the void ratio (e) versus logarithm of the pressure (p)) curve of mixed soil is inconsistent when FC is different: when FC = 3%, the compressibility of mixed soil decreased with the increase in CS; when FC = 7% and 10%, the compressibility of mixed soil gradually increased with the increase in CS; when FC = 5%, the compressibility of mixed soil did not show an obvious changing law with the increase in CS, and the compressibility of the specimen with FC = 5%–CS = 1 (FC = 5%, CS = 1) was the largest; when CS was same, the difference between e–lgp curves of mixed soil with different FC increased with the increase in CS. The compression model of sand–silt–clay mixtures was established, which can consider the effects of FC and CS. The reliability and applicability of the proposed model were verified by combining the experimental results of this paper and the test data of sand–clay mixture and sand–silt mixture in other literature.
Three-Dimensional Multi-Material Topology Optimization: Applying a New Mapping-Based Projection Function
Authors: Simonetti Hélio Luiz , Neves Francisco de Assis das , Almeida Valério Silva , Silva Marcio Maciel da , Neto Luttgardes de Oliveira
Published: February 2025

This paper presents an efficient and compact MATLAB code for 3D topology optimization of multi-materials. The multi-material problem using a mapping-based material interpolation function is adopted from previous work, in which each material is modeled in the same way, presenting a clear (clean) result of 0 and 1 for each material of the optimized structures, without gray elements, thus facilitating the manufacturing process. A new projection function, the sigmoid function, is adopted for the filtered design variables for each material in the domain. The proposed method improves computational efficiency, reducing computational costs by up to 36.7%, while achieving a 19.1% improvement in the objective function compared to the hyperbolic tangent function. A multi-material topology optimization solution with minimal compliance under volume constraints, including details of the optimization model, filtering, projection, and sensitivity analysis procedures, is presented. Numerical examples are also used to demonstrate the effectiveness of the code, and the influence of the position of the support on the optimized results is also proven. The complete MATLAB code for 3D elastic structures is presented as an example.
Kenaf Fiber-Reinforced Biocomposites for Marine Applications: A Review
Authors: Huang Yang , Sultan Mohamed Thariq Hameed , Shahar Farah Syazwani , Łukaszewicz Andrzej , Oksiuta Zbigniew , Grzejda Rafał
Published: February 2025

Fiber-reinforced composites are widely utilized across various industries, including aerospace, automotive, and marine, due to their outstanding mechanical properties and lightweight characteristics. Natural fibers, as promising reinforcements, have the potential to replace synthetic fibers in certain areas to meet the growing demand for environmental protection and sustainability. These biocomposites offer numerous benefits, including reduced carbon footprints, diminished reliance on non-renewable resources, and increased natural biodegradability. In addition, utilizing such eco-friendly materials is a critical strategy for balancing industry progress and environmental protection. Kenaf fiber, a superior bast fiber known for its excellent mechanical properties and high cellulose content, presents considerable advantages for enhancing the performance of biocomposites. This review explores the potential of kenaf fiber-reinforced biocomposites for marine applications, focusing on their fabrication and testing methods to evaluate their physicochemical and mechanical properties. This paper examines the chemical composition and mechanical properties of the kenaf fiber, investigates the excellent performance advantages of kenaf fiber-based biocomposites by hybridization manufacturing, and provides an overview of the status and challenges of applying such biocomposites in marine environments. Based on this review, it is evident that kenaf fiber-reinforced biocomposites have significant superiority for marine applications with the advancement of manufacturing techniques.
Effects of Sand Type and Alkali Equivalent on Drying Shrinkage and Microstructure of Seawater–Sea Sand Alkali-Activated Slag Concrete
Authors: Zhang Jianbin , Kang Sixiang , Shen Yanran , Song Chenhao , Lei Haoliang , Xie Wei , Chen Xianyun , Wang Jize , Wu Wenda , Wang Xuefang
Published: February 2025

The use of seawater and sea sand for the preparation of alkali-activated concretes plays an important role in reducing carbon emissions and alleviating resource scarcity. However, both alkali-activated concretes and products made from seawater and sea sand tend to exhibit significant drying shrinkage. Therefore, this study investigates the effect of the addition of seawater and sea sand on the basic properties and drying shrinkage properties of alkali-activated concretes, and regulates the properties of seawater and sea sand alkali-activated slag (SSAS) concretes with the key parameter of the alkali equivalent. Finally, the mechanism of SSAS drying shrinkage improvement was investigated using XRD, TG, MIP, and SEM. The results show that the addition of seawater and untreated sea sand accelerates the hydration reaction of alkali-excited cement and can significantly reduce its drying shrinkage. A moderate increase in alkali content can improve the compressive strength and reduce the drying shrinkage. However, an excessively high alkali content reduces the flexural strength. Finally, we propose the existence of a quantitative relationship between drying shrinkage, mass loss, and the evaporable water content, which better explains the mechanism of shrinkage variation. These effects are mainly attributed to changes in microstructure and phase composition. This study provides theoretical support for engineering applications of seawater–sea sand alkali-activated materials.
Corrosion Behavior and Mechanical Properties of Metallic Materials
Authors: Li Xiaogang , Zhang Xu , Yan Xuelan , Zhang Haiquan
Published: February 2025

Worldwide, more than USD 400 million/year is spent on corrosion protection and productivity losses due to corrosion [...]
Gesture-Controlled Robotic Arm for Small Assembly Lines
Authors: Angelidis Georgios , Bampis Loukas
Published: February 2025

In this study, we present a gesture-controlled robotic arm system for small assembly lines. Robotic arms are extensively used in industrial applications; however, they typically require special treatment and qualified personnel to set up and operate them. Towards this end, hand gestures can provide a natural way for human–robot interaction, providing a straightforward means for control without the need for significant training of the operators. Our goal is to develop a safe, low-cost, and user-friendly system for environments that often involve non-repetitive and custom automation processes, such as in small factory setups. Our system estimates the 3D position of the user’s joints in real time with the help of AI and real-world data provided by an RGB-D camera. Then, joint coordinates are translated into the robotic arm’s desired poses in a simulated environment (ROS), thus achieving gesture control. Through the experiments we conducted, we show that the system provides the performance required to control a robotic arm effectively and efficiently.
Revisiting the Marcus–de Oliveira Conjecture
Authors: Bebiano Natália , da Providência João P.
Published: February 2025

The Marcus–de Oliveira determinantal conjecture claims that the determinant of the sum of two normal matrices A and B with the prescribed spectra σ(A)={a1,⋯,an} and σ(B)={b1,⋯,bn}, respectively, is contained in the convex hull of the points zσ=∏i=1n(ai+bσ(i)) for σ∈Sn, the symmetric group of degree n. The conjecture was independently proposed by Marvin Marcus in 1973 and de Oliveira in 1982, inspired by a result obtained by Miroslav Fiedler in 1971. We survey the main achievements relating to this open problem in matrix analysis. Some related results and questions that it has raised are also briefly reviewed. This overview aims to bring the attention of researchers to this problem and to stimulate the development of original approaches and techniques in the area. Ideally, this work may inspire further progress towards the solution of this long-standing conjecture.
Online Machine Learning for Intrusion Detection in Electric Vehicle Charging Systems
Authors: Makhmudov Fazliddin , Kilichev Dusmurod , Giyosov Ulugbek , Akhmedov Farkhod
Published: February 2025

Electric vehicle (EV) charging systems are now integral to smart grids, increasing the need for robust and scalable cyberattack detection. This study presents an online intrusion detection system that leverages an Adaptive Random Forest classifier with Adaptive Windowing drift detection to identify real-time and evolving threats in EV charging infrastructures. The system is evaluated using real-world network traffic from the CICEVSE2024 dataset, ensuring practical applicability. For binary intrusion detection, the model achieves 0.9913 accuracy, 0.9999 precision, 0.9914 recall, and an F1-score of 0.9956, demonstrating highly accurate threat detection. It effectively manages concept drift, maintaining an average accuracy of 0.99 during drift events. In multiclass detection, the system attains 0.9840 accuracy, precision, and recall, with an F1-score of 0.9831 and an average drift event accuracy of 0.96. The system is computationally efficient, processing each instance in just 0.0037 s, making it well-suited for real-time deployment. These results confirm that online machine learning methods can effectively secure EV charging infrastructures. The source code is publicly available on GitHub, ensuring reproducibility and fostering further research. This study provides a scalable and efficient cybersecurity solution for protecting EV charging networks from evolving threats.
A Note on the Dynamics of Modified rf-SQUIDs: Simulations and Possible Control over Oscillations
Authors: Kyurkchiev Nikolay , Zaevski Tsvetelin , Iliev Anton , Branzov Todor
Published: February 2025

The so-call SQUIDs (abbreviated from superconducting quantum interference device) are very sensitive apparatuses especially built for metering very low magnetic fields. These systems have applications in various practical fields—biology, geology, medicine, different engineering areas, etc. Their features are mainly based on superconductors and the Josephson effect. They can be differentiated into two main groups—direct current (DC) and radio frequency (RF) SQUIDs. Both of them were constructed in the 1960s at Ford Research Labs. The main difference between them is that the second ones use only one superconducting tunnel junction. This reduces their sensitivity, but makes them significantly cheaper. We investigate namely the rf-SQUIDs in the present work. A number of authors devote their research to the rf-SQUIDs driven by an oscillating external flux. We aim to enlarge the theoretical base of these systems by adding new factors in their dynamics. Several particular cases are explored and simulated. We demonstrate also some specialized modules for investigating the proposed model. One application for possible control over oscillations is also discussed. It is based on the Fourier transform and, as a consequence, on the characteristic function of some probability distributions.
Convergence of Infinite Products of Uniformly Locally Nonexpansive Mappings
Authors: Reich Simeon , Zaslavski Alexander J.
Published: February 2025

The generic convergence of infinite products of nonexpansive mappings was established in a 1999 paper of ours. In the present paper, such results are extended to infinite products of uniformly locally nonexpansive mappings. In particular, the convergence of infinite products of uniformly locally contractive mappings, as well as its stability, are proved. Moreover, the Baire category approach and the porosity notion are used to show that most sequences of uniformly locally nonexpansive mappings are, in fact, uniformly locally contractive.
Utilizing the Attention Mechanism for Accuracy Prediction in Quantized Neural Networks
Authors: Wei Lu , Ma Zhong , Yang Chaojie , Yao Qin , Zheng Wei
Published: February 2025

Quantization plays a crucial role in deploying neural network models on resource-limited hardware. However, current quantization methods have issues like the large accuracy loss and poor generalization for complex tasks. These issues pose obstacles to the practical application of deep learning and large language models in smart systems. The main problem is our limited understanding of quantization’s effect on accuracy, and there is also a need for more effective approaches to evaluate the performance of the quantized models. To address these concerns, we develop a novel method that leverages the self-attention mechanism. This method predicts a quantized model’s accuracy using a single representative image from the test set. It utilizes the transformer encoder and decoder to perform this prediction. The prediction error of the quantization accuracy on three types of neural network models is 2.44%. The proposed method enables rapid performance assessment of the quantized models during the development stage, thereby facilitating the optimization of the quantization parameters and promoting the practical application of neural network models.
A Fast Algorithmic Way to Calculate the Degree Growth of Birational Mappings
Authors: Grammaticos Basil , Ramani Alfred , Carstea Adrian-Stefan , Willox Ralph
Published: February 2025

We present an algorithmic method for the calculation of the degrees of the iterates of birational mappings based on Halburd’s method for obtaining the degrees from the singularity structure of the mapping. The method uses only integer arithmetic with additions and, in some cases, multiplications by small integers. It is therefore extremely fast. Several examples of integrable and non-integrable mappings are presented. In the latter case, the dynamical degree we obtain from our method is always in agreement with that calculated by previously known methods.
Elementary Operators with m-Null Symbols
Authors: Marrero Isabel
Published: February 2025

Motivated by Botelho and Jamison’s seminal 2010 study on elementary operators that are m-isometries, in this paper, we introduce the concept of m-null pairs of operators and establish some structural properties and characterizations of the class of elementary operators whose symbols are m-null (so-called m-null elementary operators). It is shown that if the symbols of an elementary operator L are, in turn, a p-null elementary operator and a q-null elementary operator, then L is a (p+q−1)-null elementary operator. Some extant results on elementary m-isometries can be recovered from this renewed perspective, often providing added value.
A Mathematical Perspective on the Influence of Allee Effects in Oncolytic Virotherapy
Authors: Hernández-López Eymard , Wang Jin
Published: February 2025

This article is concerned with the mathematical modeling of cancer virotherapy, emphasizing the impact of Allee effects on tumor cell growth. We propose a modeling framework that describes the complex interaction between tumor cells and oncolytic viruses. The efficacy of this therapy against cancer is mathematically investigated. The analysis involves linear and logistic growth scenarios coupled with different Allee effects, including weak, strong, and hyper Allee forms. Critical points are identified, and their existence and stability are analyzed using dynamical system theories and bifurcation techniques. Also, bifurcation diagrams and numerical simulations are utilized to verify and extend analytical results. It is observed that Allee effects significantly influence the stability of the system and the conditions necessary for tumor control and eradication.
Optimizing Inventory for Imperfect and Gradually Deteriorating Items Under Multi-Level Trade Credit in a Sustainable Supply Chain
Authors: Bansal Abhay , Panwar Aastha , Unhelkar Bhuvan , Mittal Mandeep
Published: February 2025

Reducing carbon emissions is of immense interest to most modern organizations striving for sustainability. Effective inventory management is crucial for achieving resource optimization and minimizing environmental impact. Very little work has been conducted up to this point on slowly declining, low-quality products with multi-level trade credit rules under the influence of carbon emissions. In this study, an inventory model is tailored specifically for imperfect and gradually deteriorating products with a multi-level trade credit policy. Further, the impact of carbon emissions on the retailer’s ordering strategies is also considered. To determine the optimal policy for supply chain partners, three trade credit instances with seven subcases are taken into consideration. To choose the best scenario out of ten cases, an algorithm is also developed. The model’s validity is illustrated through a numerical experiment and sensitivity analysis. This study is an innovative approach to balancing economic trade credit policy in sustainable supply chain management.
Reconstruction and Prediction of Regional Population Migration Neural Network Model with Age Structure
Authors: Li Cuiying , Wu Yulin , Cheng Yi , Guo Yandong , Wei Kun , Zhao Jie
Published: February 2025

The rationale for age-structured population migration system models lies in the significant impact of age patterns on migration dynamics, as age-specific migration rates exhibit distinct regularities and are influenced by life course transitions, socio-economic conditions, and demographic structures. Based on artificial neural networks, this article proposes a class of population models with age structure described by partial differential equations to predict the future trends of regional population changes. The population migration rate, as a complex nonlinear feature, can be trained through artificial neural networks, providing a population approximation system. By employing semigroup theory, we establish the well-posedness of the proposed system. It is shown that the solution of the approximation system can converge to that of the original system in the sense of the L2-norm. Finally, several simulation experiments are provided to verify the effectiveness of the population forecasting model.
Tripled Fixed Points, Obtained by Ran-Reunrings Theorem for Monotone Maps in Partially Ordered Metric Spaces
Authors: Ali Aynur , Dinkova Cvetelina , Ilchev Atanas , Kulina Hristina , Zlatanov Boyan
Published: February 2025

Using the deep result of Ran & Reunrings, we generalize existing results for tripled fixed points. In contrast to the previously known results for tripled fixed points of maps with or without the mixed monotone property in partially ordered complete metric spaces, we demonstrate that it is possible to obtain results for the existence and uniqueness of such points for arbitrary maps with a type of monotonicity, with the partial ordering in the Cartesian product arising from the maps itself. We prove theorems that ensure the existence and uniqueness for tripled fixed points for maps with different types of monotone properties. We obtain sufficient conditions for the existence and uniqueness of systems of three nonlinear matrix equations. The obtained results are illustrated by solving systems of matrix equations.
Mechanical Stimulation of Red Blood Cells Aging: Focusing on the Microfluidics Application
Authors: Gural Alexander , Pajić-Lijaković Ivana , Barshtein Gregory
Published: February 2025

Human red blood cells (RBCs) are highly differentiated cells, essential in almost all physiological processes. During their circulation in the bloodstream, RBCs are exposed to varying levels of shear stress ranging from 0.1–10 Pa under physiological conditions to 50 Pa in arterial stenotic lesions. Moreover, the flow of blood through splenic red pulp and through artificial organs is associated with brief exposure to even higher levels of shear stress, reaching up to hundreds of Pa. As a result of this exposure, some properties of the cytosol, the cytoskeleton, and the cell membrane may be significantly affected. In this review, we aim to systematize the available information on RBC response to shear stress by focusing on reported changes in various red cell properties. We pay special attention to the results obtained using microfluidics, since these devices allow the researcher to accurately simulate blood flow conditions in the capillaries and spleen.
A Study on the Oxidative Functionalization of a Poplar Biochar
Authors: Di Vincenzo Antonella , Madonia Ettore , Librici Calogero , Bambina Paola , Chillura Martino Delia , Guernelli Susanna , Lo Meo Paolo , Conte Pellegrino
Published: February 2025

This study investigates the functionalization of a poplar biochar (PB), obtained by high-temperature pyrolysis, under oxidative conditions typically used in organic synthesis. In particular, concentrated nitric acid, a sulfonitric mixture and a piranha mixture were applied as oxidants at different temperatures and reaction times. In order to assess the outcome of the reaction conditions on the characteristics of the resultant products, these were characterized by a combination of imaging (SEM), spectroscopic (ATR-FTIR, RAMAN) and FFC-NMR relaxometric techniques. The latter techniques, rationalized in terms of the Kohlrausch-type stretched exponential kinetic model, were analyzed using a recently developed heuristic Monte Carlo method, providing insights into the water dynamics within material pore networks. Additionally, the water-holding capacity of the modified biochars and their abilities to adsorb some model dyes were evaluated. The results clarify the relationship between oxidative treatment conditions and biochar properties, highlighting their impact on both structural modifications and water dynamics within the porous network, and enabling us to identify the best reaction conditions for optimizing the features of the oxidized product.
Beneficial Effects of Butyrate on Kidney Disease
Authors: Diep Tram N. , Liu Haoxin , Yan Liang-Jun
Published: February 2025

The gut microbiota influences and contributes to kidney health and disease. Butyrate, a short-chain fatty acid molecule generated via the fermentation of gut bacterial catabolism of nondigestible dietary fiber, has been shown to exert numerous beneficial effects on kidney disorders. The objective of this review was to discuss the latest findings on the protective effects of butyrate on a variety of animal models of kidney injury. We conducted a PubMed search using the title word “butyrate” and keyword “kidney” to generate our literature review sources. The animal models covered in this review include ischemia–reperfusion renal injury, cisplatin- and folic acid-induced kidney injury, septic kidney injury, diabetic kidney disease (DKD), high-fat diet (HFD)-induced glomerulopathy, adenine-induced chronic kidney disease (CKD), high-salt-induced renal injury, and T-2 toxin-induced kidney injury in birds. The protective mechanisms of butyrate that are most shared among these animal model studies include antioxidative stress, anti-fibrosis, anti-inflammation, and anti-cell death. This review ends with suggestions for future studies on potential approaches that may modulate gut microbiota butyrate production for the well-being of kidneys with the kidney disorders covered in this review.
#WhatIEatinaDay: The Quality, Accuracy, and Engagement of Nutrition Content on TikTok
Authors: Zeng Michelle , Grgurevic Jacqueline , Diyab Rayan , Roy Rajshri
Published: February 2025

Background: Social media platforms such as TikTok are significant sources of nutrition information for adolescents and young adults, who are vulnerable to unregulated, algorithm-driven content. This often spreads nutrition misinformation, impacting adolescent and young adult health and dietary behaviors. Objectives: While previous research has explored misinformation on other platforms, TikTok remains underexamined, so this study aimed at evaluating the landscape of nutrition-related content on TikTok. Methods: This study evaluated TikTok nutrition-related content by (1) identifying common nutrition topics and content creator types; (2) assessing the quality and accuracy of content using evidence-based frameworks, and (3) analyzing engagement metrics such as likes, comments, and shares. Results: The most common creators were health and wellness influencers (32%) and fitness creators (18%). Recipes (31%) and weight loss (34%) dominated the list of topics. When evaluating TikTok posts for quality, 82% of applicable posts lacked transparent advertising, 77% failed to disclose conflicts of interest, 63% promoted stereotypical attitudes, 55% did not provide evidence-based information, 75% lacked balanced and accurate content, and 90% failed to point out the risk and benefits of the advice presented. A total of 36% of posts were considered completely accurate, while 24% were mostly inaccurate, and 18% completely inaccurate. No statistical significance was associated between the level of accuracy or evidence and engagement metrics (p > 0.05). Conclusions: TikTok prioritizes engagement over accuracy, exposing adolescents to harmful nutrition misinformation. Stricter moderation and evidence-based nutrition content are essential to protect adolescent and young adult health. Future research should explore interventions to reduce the impact of misinformation on adolescent dietary behaviors and mental well-being.
Vitamin D Supplementation: Practical Advice in Different Clinical Settings
Authors: Bendotti Giulia , Biamonte Emilia , Leporati Paola , Goglia Umberto , Ruggeri Rosaria Maddalena , Gallo Marco
Published: February 2025

A global deficiency in vitamin D is now widely prevalent. Extensive scientific research has provided compelling evidence of the detrimental effects of vitamin D deficiency on the skeletal system. Furthermore, vitamin D supplementation not only helps prevent bone fractures but may also slow the progression of various conditions, such as diabetes, autoimmune disorders, and cardiovascular disease. Achieving optimal circulating vitamin D levels can be challenging, particularly in certain clinical scenarios. Moreover, the effect of vitamin D supplementation varies depending on factors such as body weight, pregnancy status, absorption capacity, metabolic rate, and renal function. This review aims to explore which vitamin D formulations are most effective in specific clinical contexts where reaching adequate vitamin D levels may not be straightforward.
Mothers’ Body Appreciation and Postpartum Self-Esteem in Relation to Body Changes and Breastfeeding Difficulties: A Cross-Sectional Survey in Cyprus
Authors: Kalli Anastasia , Iliadou Maria , Palaska Ermioni , Louverdi Sevasti , Dagla Calliope , Orovou Eirini , Dagla Maria
Published: February 2025

Objectives: This study explores the effect of pregnancy weight gain, acceptance of body changes, and breastfeeding difficulties on mothers’ self-esteem and body appreciation during the postpartum period. Methods: A cross-sectional survey was conducted among 100 puerperae (at 2nd day postpartum), during August 2022–March 2023 in Paralimni/Cyprus, with exclusion criteria being the presence of postpartum depression. The Body Appreciation Scale—BAS—was administrated in order to investigate the level of body appreciation, and the Rosenberg Self-Esteem Scale—RSES-10—was used for assessing self-esteem. Results: Findings indicated that the higher the pregnancy weight gain (r = −0.293), the lower the measured levels of the mothers’ self-esteem and body appreciation are (r = −0.292). Mothers whose level of acceptance of body changes was low to moderate appeared to demonstrate lower self-esteem (p = 0.027) and lower body appreciation (p < 0.001) at two days postpartum. Also, mothers who had breastfeeding difficulties at two days postpartum seem to demonstrate lower self-esteem (p = 0.032), and increased support from their husbands in terms of breastfeeding is associated with higher levels of mothers’ self-esteem (r = 0.235). Additionally, greater support for breastfeeding, both in the clinic (r = 0.314) and from their husbands (r = 0.290), appears to be linked to higher levels of body appreciation. The psychological influence of pregnancy weight gain (β = −0.236, p = 0.04) and breastfeeding difficulties (β = −0.284, p = 0.008) appeared to be predictors of mothers’ self-esteem at two days postpartum. Conclusions: The findings highlight the need for further research in areas including mothers’ body image and self-esteem and breastfeeding difficulties and further longitudinal studies to determine the exact nature of the pathways involved.