bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on the Pricing Model of B2B Data Transactions and its Nature for a Single Industrial Chain
Authors: Zhuang Weiqing , Yu Hanyu , Wang Morgan C.
Published: February 2025

With the advancement of global digital transformation, data trading has become a pivotal element in value circulation and innovation among enterprises. In particular, pricing strategies in the industrial chain's data trading process critically influence the cooperation and market competitiveness of upstream and downstream enterprises. To address this issue, this study develops a B2B data transaction pricing model tailored to a single industry chain. The model incorporates factors such as data scarcity, encryption protection efforts, and market demand dynamics. By employing a Stackelberg dynamic model, the study systematically examines the pricing strategies of upstream and downstream enterprises under various incentive mechanisms and evaluates the impact of encryption protection efforts and incentive mechanism coefficients on the profitability of the industry chain. Experimental results reveal that introducing incentive mechanisms for downstream enterprises modestly increases the profits of both upstream and downstream entities. However, incentivizing upstream enterprises yields a multiplier effect, significantly boosting their profits while causing a slight decline in downstream enterprises' profitability.
Predicting Noise and User Distances from Spectrum Sensing Signals Using Transformer and Regression Models
Authors: Valadão Myke , Amoedo Diego , Costa André , Carvalho Celso , Sabino Waldir
Published: February 2025

The frequency spectrum allocation has been a subject of dispute in recent years. Cognitive Radio dynamically allocates users to spectrum holes using various sensing techniques. Noise levels and distances between users can significantly impact the efficiency of cognitive radio systems. Designing robust communication systems requires accurate knowledge of these factors. This paper proposes a method for predicting noise levels and distances based on spectrum sensing signals using regression machine learning models. The proposed methods achieved correlation coefficients of over 0.98 and 0.82 for noise and distance prediction, respectively. Accurately estimating these parameters enables adaptive resource allocation, interference mitigation, and improved spectrum efficiency, ultimately enhancing the performance and reliability of cognitive radio networks.
Olfactory Dysfunction as a Clinical Marker of Early Glymphatic Dysfunction in Neurodegenerative Diseases
Authors: Sánchez-Benavides Gonzalo , Iranzo Alex , Grau-Rivera Oriol , Giraldo Darly Milena , Buongiorno Mariateresa
Published: February 2025

An abnormal accumulation of misfolded proteins is a common feature shared by most neurodegenerative disorders. Olfactory dysfunction (OD) is common in elderly population and is present in 90% of patients with Alzheimer’s or Parkinson’s disease, usually preceding the cognitive and motor symptoms onset by several years. Early Aβ, tau and α-synuclein protein aggregates have been observed in brain structures involved in odor processing (olfactory bulb and tract, piriform cortex, amygdala, entorhinal cortex, and hippocampus) and seem to underly OD. Glymphatic system is a glial-associated fluid transport system that facilitates the movement of CSF and ISF and removes brain waste during specific brain waste sleep stages. Noteworthy, glymphatic system became less functional in aging and is impaired in several conditions, including neurodegenerative diseases. As the nasal pathway has been recently described as the main outflow pathway of cerebrospinal fluid and solutes, we hypothesized that OD may be indeed a clinical marker of early glymphatic dysfunction that entails abnormal accumulation of pathological proteins in olfactory structures. Here we review the physiological, anatomical, and chronological evidence supporting this suggestion. If this hypothesis is confirmed, olfactory dysfunction could be considered as a clinical proxy of glymphatic dysfunction in neurodegenerative diseases.
The Mitigation of Quercetin on Lead-induced Neuroinflammation in a Rat Model: Changes in Neuroinflammatory Markers, Hippocampal Neurons and Memory
Authors: Omoyine Iliyasu Musa , Abraham Musa Sunday , Blessing Oladele Sunday , Abdullahi Iliya Ibrahim , Oseloka Ibegbu Augustine , Nana-Hawau Nuhu , Amoto Animoku Abdulrazaq , Onoruoiza Yusuf Abdullateef , James Sambo Sohnap , Peter Akpulu Stephen , Abayomi Ajayi
Published: February 2025

The present study investigated the mitigatory effects of quercetin on neuroinflammation, hippocampal degeneration, and memory deficits in lead (Pb)-exposed rats. Wistar rats were administered orally with quercetin and succimer (standard drug) for 21 days after Pb exposure of 21 days or in combination with Pb for 42 days. Working and reference memory was assessed using an eight-arm radial water maze (8-ARWM). The changes in brain Pb level, the neuronal nitric oxide synthase (nNOS) activity, and the level of neuroinflammatory markers like tumour necrosis factor-alpha (TNF-α) and interleukin 1 Beta (IL-1β) were determined. The number of neurons and astrocyte expression were all evaluated histologically and immunohistochemically, respectively. The brain level of Pb was increased significantly in Pb-exposed rats. In the hippocampus, the number of neurons decreased while the expression of astrocytes increased, and the levels of neuroinflammatory markers increased in Pb-exposed rats. Lead impaired reference and working memory. However, quercetin treatment effectively reduced neuronal loss, improved memory, and inhibited neuroinflammation. In conclusion, quercetin mitigates neuroinflammation, hippocampal degeneration, and memory deficits in Pb-exposed rats. Neuroinflammatory markers negatively correlated with memory function. Thus, quercetin may be a promising therapy in neuroinflammation and memory dysfunction in populations prone to Pb exposure.
An Overview of Essential 21st Century Skills for Labour Market and Education
Authors: Golegou Eirini , Wallace Manolis , Peppas Kostas
Published: February 2025

21st century skills are becoming increasingly important both in education systems around the world and in the labor market. In this article, it is assumed that any individual can master all the individual skills with appropriate training. Acquiring these skills while at school will enable individuals to develop them throughout their adult working lives. Skills for the 21st century do not have a strict definition, resulting in the existence of interdependent areas. This article examines the following skills: creativity, critical thinking, collaboration, adaptability, leadership, lifelong learning and problem solving. After analyzing each of them, their commonalities are identified. The ultimate goal of all of them is to find an innovative solution to a problem. Finally, each of these skills is placed on a pyramid. Moving from the bottom of the pyramid to the top, we find the skills that are prerequisites for mastering the higher level. In this way, it is clear which skills the person needs to master first in order to progress to the next level. In an educational system where skills are cultivated from childhood, it is not necessary to master all the skills at once, but to master them gradually. The pyramid can be used as a guide as to which skills should be cultivated at the initial level.
Turbulent and Subcritical Flows over Macroroughness Elements
Authors: Martínez Francisco , Farias Javier
Published: February 2025

The determination of the friction coefficients for uniform flows over very rough bottoms is a long-standing problem in open channel hydraulics and river engineering. This experimental study reports the surface deformation, Darcy and Manning’s friction coefficients obtained from measurements on steady, turbulent (6,058≤Re≤28,502) and subcritical flows (0.14≤Fr≤0.52) over large roughness elements, where Fr,Re is the flow’s Froude and Reynolds number. The experiments were carried out in a rectangular inclined flume with a train of half-cylinders at the bottom, whose radius fall into the range 20 mm≤a≤50 mm. These obstacles are such that 1.45≤hN/a≤4.41 and e/a=12.8 far all the experimental runs, with hN the normal flow depth and e the spacing between the cylinders. The relative amplitude (Δh/a) of the surface profiles was analyzed showing a close correlation with hN/a, Re and Fr. Our results lead to very high values of the Darcy friction factor f following scaling laws of the type f∝(hN/a)n^ with n^<0 independent on a, and f∝Reβ, where β<0 closely related to a. Scaling laws for the Manning roughness coefficient (n) were also studied and reported.
Nonlinear Schrödinger Equation with a Short-Range Compensating Field
Authors: Rashkovskiy Sergey
Published: February 2025

Within the self-consistent Maxwell-Pauli theory, a nonlinear Schrödinger equation with a short-range compensating field is derived. Stationary and non-stationary solutions of the obtained nonlinear Schrödinger equation for the hydrogen atom are investigated. It is shown that spontaneous emission and the associated rearrangement of the internal structure of the atom, which is traditionally called a spontaneous transition, have a simple and natural description within the classical field theory without any quantization and additional hypotheses. The solution of the nonlinear Schrödinger equation showed that, depending on the frequency of spontaneous emission, the compensating field behaves differently. At relatively low frequencies of spontaneous emission, there is no radiation (waves) of the short-range compensating field and this field does not carry away energy. In this case, the damping rate of the spontaneous emission coincides with that obtained in quantum electrodynamics (QED). At relatively high frequencies of spontaneous emission, radiation (waves) of the compensating field arises, which, along with electromagnetic radiation, carry away some of the energy. In this case, the damping rate of the spontaneous emission is greater (up 1.5 times) than that predicted by QED.
Impact of Pesticide Exposure on High-Frequency Auditory Thresholds and Cochlear Function in Young People Residing Near Agricultural Areas
Authors: Munoz Felipe , Aedo-Sanchez Cristian , Paredes-Aravena Felipe , Aguilar-Vidal Enzo , Jilberto-Vergara Pedro , Terreros Gonzalo
Published: February 2025

Pesticide exposure poses a significant health risk, with emerging evidence suggesting its impact on auditory function. This study investigated the effects of pesticide exposure on hearing in young rural residents living near agricultural areas in Chile's O'Higgins Re-gion. We evaluated 51 participants (31 exposed, 20 unexposed) aged 18-35 years, using comprehensive audiological assessments including high-frequency audiometry, distor-tion-product otoacoustic emissions (DPOAEs), and auditory brainstem responses (ABR). Participants were classified based on residential proximity to agricultural areas and oc-cupational exposure, with exposed individuals living around 400 meters or less from monoculture fields. Results revealed significant differences in high-frequency hearing thresholds (14 and 16 kHz) in exposed individuals. The exposed group showed a higher number of absent DPOAEs and reduced ABR wave V amplitude in the right ear compared to the unexposed group. Additionally, the wave V/I ratio was significantly lower in exposed individuals. These findings suggest that pesticide exposure, even without direct occupational contact, may induce measurable changes in auditory function, particularly affecting high-frequency hearing and neural responses. These results emphasize the need for enhanced monitoring and protective measures for populations residing near agricultural areas where pesticides are extensively used.
The Middle-to-High School Transition: Key Factors Shaping 9th-Grade Computer Science Enrollment
Authors: Amiel David , Blitz Cynthia
Published: February 2025

The increasing demand for computer science (CS) skills underscores the importance of integrating CS education into K–12 curricula to best prepare students for a digitally-driven society. Despite significant progress in expanding access to CS courses, disparities in participation persist, especially among historically underrepresented groups. This study examines the transition from 8th to 9th grade as a pivotal juncture in CS education, analyzing factors linked to 9th-grade CS course-taking among 5,505 students across eight diverse school districts using logistic regression. Findings show that high academic achievers, male students, Asian students, and those with exposure to CS and Algebra 1 in middle school were more likely to enroll in 9th-grade CS courses. Conversely, participation is lower for females, English Language Learners, and students receiving special education services. These results point to persistent barriers to CS participation extending beyond access alone. We discuss practical implications for middle and high schools, emphasizing the need for targeted outreach and early exposure to CS to foster a sense of belonging and applicability of CS. By identify-ing actionable strategies to address participation gaps, this study provides data-driven recommendations for advancing equity in CS education during the critical middle-to-high school transition.
Molecular Mechanisms of Iron Metabolism and Overload in Sickle Cell Disease
Authors: Tayal Aditi , Kaur Jasmeen , Sadeghi Payam , Maitta Robert W.
Published: February 2025

Iron represents a vital element needed for normal physiologic functions across the body. A vast network of transporters is involved not only in uptake but in processing, oxidation and recycling to maintain this element in a tight balance to avoid excess storage. This complex network of transporters including heme and ferroportin among many others are responsible for facilitating inter-organ and tissue iron exchange, contributing to systemic heme homeostasis. Patients with genetic diseases such as sickle disease suffer from a chronic anemia due to the presence of an abnormal hemoglobin that requires, in most instances, a lifetime of red blood cell transfusions to overcome disease crises. These transfusions over time lead to a high iron exposure that results in a profound change to the physiology of organ systems at the cellular level requiring aggressive chelation. This exposure unfortunately leads to irreversible changes to these organs from the cardiovascular system and bone marrow, to the central nervous system. In the bone marrow, heme is synthesized, mainly within developing red blood cells, iron excess leads to impairments in cell production and differentiation due to processes needing a balanced intracellular heme concentration to prevent toxicity. In light of the extensive role of iron in the body, the aim of this review is to summarize the important metabolic pathways involved in iron homeostasis across a number of cell types and organ systems while contrasting these against effects caused by iron overload.
FERMENZA: A Patented Natural Alternative to Ketoconazole and Zinc Pyrithione for Managing Dandruff and Scalp Disorders
Authors: Bhattacharya Munna , Ghosh Sudip
Published: February 2025

Background: Dandruff and related scalp disorders, often caused by Malassezia furfur, pose significant dermatological challenges. This study evaluates FERMENZA®, a novel, patented formulation derived from pomegranate and beetroot fermented extracts, as a natural alternative to synthetic agents like ketoconazole and zinc pyrithione. Methodology and Results: In this study, mixed substrate fermentation was utilized for synergistic effect on bioactivity of natural fruits and vegetable extracts. The pomegranate-beetroot fermented extract demonstrated impressive antifungal efficacy against Malassezia furfur MTCC 1374, with percent inhibition of 96% and 86.7% compared to active pharmaceutical ingredients ketoconazole and zinc pyrithione, respectively. The investigational formulation FERMENZA® derived from pomegranate and beetroot fermented extract exhibited the highest zone of inhibition (ZOI) of 28 ± 0.12 mm, outperforming marketed products A and B lotions by achieving 93 ± 0.04% and 60 ± 0.09% inhibition, respectively. Minimum inhibitory concentration (MIC) studies revealed potent activity of the formulation at 8mg/ml. The MIC90 value was observed at 20µg/mL achieving 92 ± 0.01% inhibition compared to ketoconazole. A time-kill assay highlighted the superior antifungal potency of FERMENZA® against M. furfur, significantly reducing fungal growth intensity within 48 hours, starting from 6 hours of incubation. The mechanism of fungicidal action is attributed to gallic acid, a key active component of pomegranate and beetroot fermented extract which disrupts fungal cell structures.Conclusion: Efficacy and sensory evaluation confirmed FERMENZA®’s ability to alleviate dandruff, itching, flaking, and scaling within 10 days, with moderate benefits in reducing hairfall. These results underscore FERMENZA®'s potential as a comprehensive, natural solution for managing dandruff and scalp disorders, providing a safer alternative to synthetic antifungal agents.
SARS-CoV-2 and Mental Health: A Cross-Sectional Study of Young Individuals with Mild to Moderate COVID-19, an Average of 15 Months Post-Recovery
Authors: Latifi Ashkan
Published: February 2025

Background: The long-term effects of COVID-19 infection represent an emerging area of research that explores the relationships between a history of COVID-19 infection and its consequential sequelae. This study investigates the potential associations among the duration since infection, the severity of the acute phase of the disease, and sex, while controlling for age, in relation to mental health.; Methods: A total of 305 university students participated in this cross-sectional study, during which data were collected using the SCL-90-R questionnaire. The analysis of the collected data was conducted using MANCOVA, ANCOVA, and partial Kendall tau methods. Results: The findings indicated that factors such as sex—specifically being female—, longer time elapsed since infection, and disease severity significantly influenced multiple scales of the SCL-90-R. Conclusions: Based on these findings, it is recommended that investigations into mental health issues consider biological sex, COVID-19 severity, and the duration since infection as potential risk factors among young adults with a history of COVID-19 infection.
Characterizing Plasma-based Metabolomic Signatures for Metastasis in Non-Small Cell Lung Cancer
Authors: Liu Manlu , Zhu Yanlong , McIlwain Sean J. , Deng Haotian , Brasier Allan R. , Ge Ying , Kimple Michelle E , Baschnagel Andrew M.
Published: February 2025

Abstract: Background/Objectives: The current staging of non-small cell lung cancer (NSCLC) relies on conventional imaging, which lacks sensitivity to detect micrometa-static disease. Functional assessment of NSCLC progression may provide independent information to enhance prediction of metastatic risk.. The objective of this study was to determine if we could identify a metabolomic signature predictive of metastasis in pa-tients with NSCLC treated with definitive radiation. Methods: Plasma samples were collected prospectively from patients enrolled in a clinical trial with non-metastatic NSCLC treated with definitive radiation. Metabolites were extracted and mass spec-trometry-based analysis was performed using a flow injection electrospray (FIE) Fourier transform ion cyclotron resonance (FTICR) mass spectrometry (MS) method. Early metastasis was defined as metastasis within 1 year of radiation treatment. Results: The study cohort included 28 patients. FIE-FITCR produced highly reproducible profiles in technical replicates A total of 48 metabolic features were identified to be different in patients with early metastasis compared to patients without early metastasis (all ad-justed p values < 0.05, Welch’s t-test), including glycerophospholipids, sphingolipids, and fatty acyls. In follow up samples collected after initiation of chemotherapy and radiation treatment, a total of 154 metabolic features were significantly altered in patients who developed early metastasis compared to those who did not. Conclusions: We identified several distinct changes in the metabolic profiles of patients with NSCLC who developed metastatic disease within 1 year of definitive radiation. These findings highlight the potential of metabolomic profiling as a predictive tool for assessing met-astatic risk in NSCLC.
The Cancer and Work Scale (CAWSE): Development and Validation of a Return to Work Assessment for Cancer
Authors: Maheu Christine , Singh Mina , Tock Wing Lam , Robert Jennifer , Vodermaier Andrea , Parkinson Maureen , Dolgoy Naomi
Published: February 2025

Background: Returning to and sustaining employment after cancer presents significant challenges for individuals touched by cancer (ITBC). While vocational rehabilitation and workplace accommodations are critical, existing return to work (RTW) assessments lack cancer-specific considerations, limiting their clinical and occupational utility. Purpose: This study aimed to develop and validate the Cancer and Work Scale (CAWSE), a psychometrically robust tool designed to assess RTW likelihood and employment sustainability among ITBC, while also providing avenues for targeted interventions. Methods: A two-phase cross-sectional study was conducted. Study I (n = 130) assessed content validity and construct development, leading to a refined 43-item CAWSE. Study II (n = 216) employed exploratory and confirmatory factor analyses to establish structural validity, reliability, and responsiveness. Additional validation included correlations with fatigue, cognitive difficulties, depression, and anxiety. Results: Factor analysis supported a seven-factor structure with 31 final items. The CAWSE demonstrated strong internal consistency (α = 0.787), construct validity, and moderate responsiveness (AUC = 0.659). High sensitivity allowed for accurate identification of RTW difficulties, with an established cut-off score of 123.5 on the total CAWSE scale. Implications: The CAWSE fills a critical gap in oncology-specific vocational rehabilitation, offering healthcare providers a validated tool for targeted interventions to enhance RTW outcomes and long-term employment sustainability for ITBC.
Multifractal Analysis and Machine Learning-Based Predictive Modeling of the Tanker Freight Market: Unraveling Complexity Across Four Breaks
Authors: Chen Feier , Sha Yi , Ji Huaxiao , Peng Kaitai , Liang Xiaofeng
Published: February 2025

This study investigates the tanker freight market and its complex transformation from 1998 to 2024, uncovering a high degree of multifractality and a complex market structure shaped by temporal correlations and inherent volatility. Using multifractal dynamics analyzed through multifractal detrended fluctuation analysis (MF-DFA) and multifractal detrending moving average (MF-DMA), we explore how key external factors drive market complexity, including economic disturbances (the 2008 Financial Crisis), technological innovations (the 2014 Shale Oil Revolution), supply chain disruptions (the COVID-19 pandemic), and geopolitical uncertainties (the Russia-Ukraine conflict). Building on this, a predictive framework is introduced, leveraging the Baltic Dirty Tanker Index (BDTI) to forecast Brent oil prices. By integrating multifractal analysis with machine learning models, such as XGBoost, LightGBM, and CatBoost, the framework captures complexity transformation across these four major global events. Results demonstrate the potential of combining multifractal analysis with advanced machine learning models to improve forecasting accuracy and provide actionable insights during periods of heightened market volatility.
Cloud-Driven Data Analytics for Growing Plants Indoor
Authors: Kharraz Nezha , Szabó István
Published: February 2025

The integration of cloud computing, IoT, and artificial intelligence (AI) is transforming precision agriculture by enabling real-time monitoring, data analytics, and dynamic control of environmental factors. This study develops a cloud-driven data analytics pipeline for indoor agriculture, using lettuce as a test crop due to its suitability for controlled environments. Built with Apache NiFi, the pipeline facilitates real-time ingestion, processing, and storage of IoT sensor data measuring light, moisture, and nutrient levels. Machine learning models, including SVM, Gradient Boosting, and Deep Neural Networks, analyzed 12 weeks of sensor data to predict growth trends and optimize thresholds. Random Forest analysis identified light intensity as the most influential factor (importance: 0.7), while multivariate regression highlighted phosphorus (0.54) and temperature (0.23) as key contributors to plant growth. Nitrogen exhibited a strong positive correlation (0.85) with growth, whereas excessive moisture (–0.78) and slightly elevated temperatures (–0.24) negatively impacted plant development. To enhance resource efficiency, this study introduces the Integrated Agricultural Efficiency Metric (IAEM), a novel framework that synthesizes key factors including resource usage, alert accuracy, data latency, and cloud availability, leading to a 32% improvement in resource efficiency. Unlike traditional productivity metrics, IAEM incorporates real-time data processing and cloud infrastructure to address the specific demands of modern indoor farming. The combined approach of scalable ETL pipelines with predictive analytics reduced light use by 25%, water by 30%, and nutrients by 40%, while simultaneously improving crop productivity and sustainability. These findings underscore the transformative potential of integrating IoT, AI, and cloud-based analytics in precision agriculture, paving the way for more resource-efficient and sustainable farming practices.
A Hybrid MOO-MCDM-PSOM Approach for Mapping Urban Carbon Trade Policies
Authors: Faisal Muhammad , Hasiri Ery Muchyar , Darniati Darniati , Rahman Titik Khawa Abd , Asrul Billy Eden William , Gani Hamdan , Namruddin Respaty , Umar Najirah , Aini Nurul , Wahyuni Sri , Akib Faisal , Zuhriyah Sitti
Published: February 2025

In response to the global prioritization of environmental protection, nations increasingly focus on transitioning to low-carbon economies as a central strategy for achieving sustainable socio-economic growth. This study introduces a novel framework designed to evaluate, cluster, and map urban carbon policies by employing an integrated methodology that hybrid Multi-Objective Optimization (MOO), Multi-Criteria Decision-Making (MCDM), and Particle Swarm Optimization - Self Organizing Map (PSOM) techniques. Furthermore, a machine learning model utilizing the Random Forest algorithm is developed to enhance predictive capabilities, incorporating adaptive weighting and dynamic clustering for expert-informed analysis of sustainability strategies. Applying this hybrid approach to testing the dataset reveals that the predictive results can effectively guide city-level carbon trading strategies, thereby supporting government initiatives based on technology-based policy-making. The findings demonstrate that the proposed framework can robustly analyze and visualize complex datasets, contributing to mapping carbon trading policies against cities. Future research directions include exploring the integration of Internet of Thinks (IoT) systems to refine carbon trading strategies further, thus advancing the development of smart cities and promoting a more adaptive and sustainable urban environment.
Anomaly Monitoring Model of Industrial Processes Based on Graph Similarity and Applications
Authors: Du Guoqing , Yang Mingyi , Xu Zhigang , Wang Junyi , Xie Cheng , Lu Yuan , Yin Pengfei
Published: February 2025

Aiming at the strong spatio-temporal coupling relationship between data in the actual industrial production process, which leads to the problem of insufficient reliability and poor timeliness of traditional process anomaly monitoring methods, a time series anomaly monitoring model based on the graph similarity network with multi-scale features is proposed, which can react to the anomalies in the process in a timely and effective manner to guarantee the production safety.First, a graph-building method for spatio-temporally coupled time-series data using multidimensional time-varying feature map embedding is designed to capture the data’s dependence on time, while the topology of the graph is utilized to learn the spatial coupling of the data; second, a graph similarity-based anomaly monitoring strategy is innovatively proposed to measure the anomalies of the process using the difference degree index between the standard normal process data and the monitoring data. Finally, the proposed method is validated using the standard normal operating condition data of the Tennessee-Eastman (TE) process as well as the standard fault data. The experimental results show that the proposed model can identify anomalies more quickly and accurately than other typical methods, which significantly improves the reliability and timeliness of industrial process anomaly monitoring.
Terminal Velocity Paradoxes in Viscous Media: A Theoretical Perspective
Authors: Mosquera-Polo A. S. , Muñoz-Martínez L. F. , Deluque-Toro C. E. , García-Negrete C. A. , Parra-Jimenez K.R.C , Ariza-Echeverri E. A.
Published: February 2025

This study examines the dynamics of two spheres falling independently in a viscous fluid, highlighting conditions under which a lighter sphere can achieve a higher velocity than a heavier one. Through theoretical modeling and simulations, the motion of spheres with varying densities and radii, released simultaneously in a uniform viscous medium, was analyzed. The investigation considers gravitational, buoyant, and drag forces, with the spheres moving under identical initial conditions and without mutual interaction. The results confirm the well-established case where the heavier sphere exhibits a greater terminal velocity. However, an intriguing phenomenon is identified: under specific conditions, a lighter sphere can surpass its counterpart in terminal velocity. Additionally, when spheres of equal weight are compared, the denser sphere consistently attains a higher terminal velocity. The study reveals non-trivial time-dependent acceleration patterns, with alternating dominance between heavier and lighter spheres before terminal velocities are reached. Furthermore, the order of impact with the ground is shown to depend on the release height, illustrating a complex interplay of forces. These findings offer novel insights into fluid dynamics, with implications for education and engineering applications.
A Federated Machine Learning Approach to Predicting Traffic Flow for Virtual Traffic Lights
Authors: Egere Samuel Chukwuemeka
Published: February 2025

In order to anticipate traffic, modern traffic systems now employ non-parametric techniques like machine learning. The traffic management system’s execution depends on sensory data sent to it. A minor infrastructure breakdown, like a power outage, can significantly alter traffic patterns in the area. When this failure happens at a busy crossroads, it increases the time that cars idle, creates a traffic bottleneck, and may even result in a crash. This incident makes it clear that the existing system has weak places. A self-organizing traffic system called Virtual Traffic Light can be used to solve these problems. In this system, the vehicles at the intersection can collaboratively manage the traffic flow using data from every vehicle present. Federated machine learning can be adopted when the vehicles collaborate to predict traffic because data privacy is at the center of its operation. In this paper, we worked with traffic data from Austin Texas and focused on key metrics such as execution time and prediction accuracy of multiple federated prediction models. Among the models used, our results suggest that Stochastic Gradient Descent Regressor and Random Forest Regressor are a good choice for traffic prediction in our proposed Virtual Traffic Light system.
Class 4 Sections Computing Section Properties and Stresses Due to the Bimoment
Authors: Aguero Antonio , Baláž Ivan , kolekova Yvona
Published: February 2025

The present paper deals with warping torsion, bending and axial forces. Presenting a method to compute the shear center of the effective section, the warping constant and warping coordinates needed to compute the stresses due to the bimoment. The stresses are compared between stresses in the gross and effective section when a Bimoment only is applied for the sake of simplicity but any combination with axial and biaxial bending moment is allowed. This paper fills the gap of the current codes to deal with bimoment in Class 4 sections.
Production, Optimization and Validation Of Fig Gum Products for Extended Shelf-Life
Authors: Amanze Kenneth
Published: February 2025

One of the main plants that people grow is the fig (Ficus carica L.). Nearly every component of the fig is utilized for food and medicine, but handling and storing them after harvest is challenging because of their extreme perishability. Response Surface Methodology (RSM) and mixture design were used to optimize the composition of the fig gum jelly. The percentages of fig paste (x1), k-carrageenan (x2), and honey (x3) are independent variables. Nine reactions were assessed by the sensory panel, which included ten elements of both sexes. Y1: Exceptional, Y2: Openness, Y3: Fragrant, Texture A in Y4, Texture C in Y5, Sweetness A (Y6), Sweetness B (Y7), Mouthfeel in Y8 and Y9 - nine polynomial models were created by the overall opinion. With 55 % fig paste, 15 % k-carrageenan, and 30 % honey, the optimal fig gum jelly composition was obtained through numerical optimization. With an astounding 0.3 desirability, the same panel's validation favored the best formulation for every response.
A Narrative Review Of Minimal Hepatic Encephalopathy
Authors: Pitton Rissardo Jamir , Khalil Ibrahim , Sayad Reem , Kedwany Ahmed M. , Sayed Hager Hamdy , Chouthai Abhishek A. , Fornari Caprara Ana Letícia
Published: February 2025

Minimal hepatic encephalopathy (MHE) is primarily a cognitive disorder linked to chronic liver disease that often remains underdiagnosed due to the subtlety of its clinical manifestations. These symptoms are frequently overlooked or dismissed as inconsequential in clinical practice, leading to many undiagnosed cases. The standard neurological examination is usually normal in indi-viduals with MHE. Regular and systematic screening for MHE is essential for early detection, which can improve cognitive outcomes and prevent progression to a more serious and debilitat-ing condition also known as overt hepatic encephalopathy. The pathophysiology of MHE is very complex and multifactorial, involving several interplaying mechanisms. Mainly, hyperammone-mia, system-wide inflammation, gut-derived neurotoxins, oxidative stress, and mitochondrial dysfunction are at its root. Any of these factors may interfere with the normal functioning of neu-rotransmitters, giving rise to the typical subtle cognitive impairments that are hallmarks of MHE. The Animal Naming Test and EncephalApp-Stroop tests are useful for screening for minimal en-cephalopathy in office or bedside settings. The role potentially played by emerging diagnostic technologies of advanced neuroimaging and biomarkers has been reviewed, underscoring its promise in improving early detection and diagnosis of MHE.
Adsorption of Acetic Acid Vapours by Inorganic-Organic Nanomaterials. Implications for the Inhibition of the “Vinegar Syndrome” in 20th-Century Motion Picture Films
Authors: Porpora Francesca , Lisi Lorenzo , Carretti Emiliano , D'Aleo Carlotta , De Sanctis Marianna , Baldini Samuele , Dei Luigi
Published: February 2025

Cellulose acetate (CA) motion picture films are subjected to degradation especially due to the “vinegar syndrome”, a de-acetylation process catalyzed by high temperature, humidity, and acidity. Acetic acid is released as a by-product of this reaction and acts as a catalyst that triggers an autocatalytic process. The main aim of this study was to evaluate the use of metal oxide, hydroxide, and carbonate nanoparticles, as well as their composite inorganic-organic systems, for the ad-sorption of acetic acid and the inhibition of the deacetylation process. Various nanoparticles [Ca(OH)2, ZnO and CaCO3] were compared in terms of their ability to adsorb glacial acetic acid vapors through gravimetry analysis, Fourier Transform Infrared (FTIR) Spectroscopy, X-ray dif-fraction (XRD), and Thermogravimetric Analysis (TGA). The variation in the size and morphology of the nanoparticles was investigated via Scanning Electron Microscopy (SEM), too. Subsequently, the most promising nanoparticles (ZnO) were incorporated into composite organic-inorganic systems, made of Whatman paper (WP) and Poly-Vinyl-alcohol Formaldehyde (PVF) xerogels, and their ability to adsorb acetic acid vapors was again evaluated. Finally, the performance of both the pure ZnO nanoparticles and the organic-inorganic composite systems as inhibitors of the “vinegar syndrome” was assessed on artificially degraded motion picture films using a specifically de-veloped and validated multi-analytical protocol.
Explainable Supervised Learning Models for Aviation Predictions in Australia
Authors: Nanyonga Aziida , Wasswa Hassan , Joiner Keith , Turhan Ugur , Wild Graham
Published: February 2025

Despite its recent success in various industries, artificial intelligence has not received full acceptance; hence, it has been fully deployed by the aviation industry. This is partly attributed to, among other factors, the AI (Artificial Intelligence) model works as a black-box model with no clear explanations of how outputs are generated from the input samples. Aviation is an extremely sensitive application field, and this model’s opaqueness makes it hard for a human user in the aviation industry to trust such a model. The work in this study examines the classification performance of various AI algorithms. Then it applies the SHAP (SHapley Additive exPlanations) framework to generate and visualize global-based model explanations to understand which features are learned for the decision boundary of each model and how much each model contributes to the final model output. We also deployed a variation autoencoder to handle the imbalanced class distribution nature of the ATSB (Australian Transport Safety Bureau) dataset. We recorded competitive classification performance in accuracy, precision, recall, and F1-score for a three-class supervised learning-based classification problem.
A p-Value Paradox in Proportion Tests and Its Resolution
Authors: Huang Hening
Published: February 2025

This technical note investigates a p-value paradox that emerges in the conventional proportion test. The paradox isdefined as the phenomenon where “decisions made on the same effect size from data of different sample sizes may be inconsistent.” It is illustrated with two examples from clinical trial research. We argue that this p-value paradox stems from the use (or misuse) of p-values to compare two proportions and make decisions. We propose replacing the conventional proportion test and its p-value with estimation statistics that include both the observed effect size and a reliability measure known as the signal content index (SCI).
Environmental Study of Solid Waste Dumpsite in Rumueme, Portharcourt, South-South Nigeria
Authors: Nwugha Victor N , Amanze Kenneth O , Okeke Pamela Ify , Okore Glory J , Nwokoma Chinedum M , Chinyem Felix I
Published: February 2025

The investigation of solid waste around Port Harcourt, Rivers State Nigeria was carried out to acquire information on the condition of the soil and the types of waste as well as the nature of leachates produced within the environment. It aims at predicting hydrogeologic site conditions and contaminating transport potential. Samples were collected at three locations using hand auger at depths of 1 m, 2 m and 3 m and laboratory analyses conducted. Results of the soil analyses revealed medium grained sands with average permeability of 10-3mm3/s while the chemical analyses of leachates indicated high concentration of the waste derivates which have been degraded. Among the parameters measured, the average values of pH, 8.8; conductivities 1750 mS/cm and total dissolved solids (TDS)1150 mg/L of the boreholes (BHI, BH2 and BH3) are above the world health organization (WHO) standards of 8.0, 1500 mS/cm and 450 mg/L respectively. The government of Rivers State and Port Harcourt municipality should design, construct and control dumpsites and their associated leachates.
Producing Aerogels from Rice Straw Cellulose Obtained by a Green Method and Its Starch Blending
Authors: Freitas Pedro A. V. , Collado Paula Alonso , González-Martínez Chelo , Chiralt Amparo
Published: February 2025

Cellulose and starch-cellulose composite aerogels were obtained using green cel-lulose from rice straw (RS) purified with a more environmentally friendly process. Pure starch aerogels were also obtained for comparison purposes. The effect of the aerogel crosslinking with polyamideamine-epichlorohydrin (PAE) was also analysed. The properties of the cellulose aerogels were in the range of those reported using other RS cellulose fibres with similar compositions. Blending with starch implied a decrease in the liquid water absorption capacity but an increase in the mechanical strength and flexibility and oil absorption capacity, compared to pure cellulose aerogels. Crosslink-ing with PAE promoted the water adsorption capacity of all aerogels and the oil ab-sorption capacity and mechanical strength of cellulose aerogels but did not benefit the properties of cellulose-starch composites or pure starch areoles due to specific interac-tions with starch that negatively affect the aerogel structure. Therefore, it was possible to obtain cellulose and cellulose-starch composite aerogels from RS green cellulose with modulated properties for different applications.
Recommendations and Statements of Good Practice for Risk Assessment of Pressure Injuries in Adults Admitted to Intensive Care Units
Authors: Picoito Ricardo , Manuel Tânia , Vieira Sofia , Azevedo Rita , Nunes Elisabete , Alves Paulo
Published: February 2025

Background: the prevention of pressure injuries depends on early and correct assessment of at-risk patients. Since risk assessment is more than identifying it using a risk factor instrument, we intend to map the existing recommendations and statements of good practice for pressure injury risk assessment in adults admitted to intensive care units, as well as identifying the strengths of evidence and recommendations. Methods: scoping review, by Joanna Briggs Institute, adopting the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews as a guide for writing the study. Results: the search was carried out in six databases, resulting in 741 studies, of which 15 were included. The recommendations and statements of good practice were grouped into five categories: risk assessment instruments, skin assessment, medical device surveillance, other alternatives to risk assessment and implement the best practices in clinical settings. The strengths of evidence and recommendation were identified, when available in the literature. Conclusions: the mapping showed that the evidence is sufficient to indicate the recommendations and statements of good practice to risk assessment of pressure injuries in adults admitted to an intensive care unit. The protocol was retrospectively registered in the Open Science Framework on the 4th of august of 2023 (https://doi.org/10.17605/OSF.IO/5NF3U).
The Impact of Self-Regulated Learning Strategies on Argumentative Writing in Flipped Learning Environments
Authors: Nouraei Yeganeh Leyli , Nemati Majid
Published: February 2025

Flipped Learning (FL) has gained widespread adoption in higher education due to its potential to foster active engagement and academic performance. However, challenges such as the lack of immediate feedback and the need for self-discipline remain significant barriers. To address these limitations, this study examined the impact of integrating Self-Regulated Learning (SRL) strategies within FL environments on medical students’ Argumentative Writing (AW) proficiency. Using a quasi-experimental pretest-posttest design, 240 senior medical students were divided into an experimental group, which received FL instruction with SRL support, and a control group, which followed a conventional FL approach without explicit SRL strategies. The study employed the Toulmin model of Argumentation to analyze the development of claims and qualifiers in students’ writing. At the same time, a Self-Regulated Learning Questionnaire (SRQ) measured students’ self-reported SRL skills. Results indicated that the experimental group demonstrated significantly greater improvements in AW proficiency and self-regulation behaviors than the control group, with large effect sizes confirming the practical significance of SRL-enhanced FL instruction. These findings suggest that explicit SRL training fosters meta-cognitive awareness and enhances writing development in FL environments. The study highlights the need for structured SRL integration in FL classrooms and calls for further research into its long-term effects and applicability across disciplines.
Expression of MHC I Isoforms in Bovine Placentomes: Impact of Cloning
Authors: Barreto Rodrigo da Silva Nunes , Mançanares Ana Carolina Furlanetto , Miglino Maria Angelica , Meirelles Flávio Vieira , Oliveira Lilian de Jesus
Published: February 2025

As observed in other species during pregnancy, bovine placentomes are assumed to suppress classical MHC I antigens, whereas overexpress non-classical MHC I to be recognized but not rejected by maternal immune system. However, in cloned bovine classical antigens were overexpress early in the pregnancy instead of non-classical ones. Then, MHC I antigens were investigated by immunohistochemistry (N=23) and RT-qPCR (N=16) in control and cloned bovine placentomes in early gestation and near term. In controls, IL-A88 staining was present in all stages, majorly in maternal tissues, whereas Qa-2 reacted only near term. Clones had an opposite pattern. Trophoblast giant cells near the uterine epithelium were weakly stained. By PCR, especially the non-classical isoform BoLA-NC3 resulted in significant higher expression in early gestation and down-regulation near term in controls compared to clones, as stain produced by Qa-2 antibody. The presence of MHC I in the placentomes indicated that bovine epitheliochorial placentas followed similar principles than that known for other species. Controls and clones reacted differently to the applied antibodies and differ partly in gene expression, which may explain pregnancy problems.