bluuebunny/crossref_metadata_2025 huggingface dataset:
Implications of Time-Invariant Space Model in Fundamental Physics and Cosmology
Authors: Šorli Amrit
Published: November 2024

Time is what we measure with clocks. With clocks, we measure the duration of material change tuning in space. Material change runs in space only, time, as duration enters existence when measured. Time is an emergent physical reality that enters existence when measured by the observer. No measurement means no time. The motion does not require time. Motion requires only space and the physical object that moves in space, which is time-invariant. There is no physical past; there is no physical future. Past and future exist only in the human mind. Humans, we experience time-invariant space as NOW. The entire universe exists and develops into NOW.
Understanding Quantum Nothingness Thanks to Non-Classical Logics: The Relevance of Free Logic
Authors: Maldonado Carlos
Published: November 2024

Since Dirac’s paper from 1930 on the theory of electrons and protons, the question aboutnothingness has pervaded the right conception of reality at large. Quantum Mechanics (QM)both allows and demands, at the same time, a highly counterintuitive take on the universeand the world. However, science at large remains cautious about the issue of nothingness.Apparently a referential and objectivistic view of the universe and things is preferred. Thispaper argues in favor of nothingness based on non-classical logics (NCLs) in general, andfree logic, in particular. The crux of the issue is about thinking without presuppositions, oralso, thinking about phenomena, systems and behaviors free of existence.
A Cable Defect Assessment Method Based on Mixed-Domain Multi-Feature Set of Overall Harmonic Signals
Authors: Wang Ruidong , Pan Ruzheng
Published: November 2024

This paper presents a cable defect assessment method based on a mixed-domain multi-feature set derived from overall harmonic signals. Four typical defect types—thermal ageing, cable moisture, excessive bending, and insulation damage—were simulated under laboratory conditions. Grounding current tests and Variational Mode Decomposition (VMD) time series analysis were performed on the test samples to extract the overall harmonic sequences in the grounding current. Mixed-domain multi-feature set is then formed through feature extraction and validity analysis. To optimize the assessment performance, a Support Vector Machine (SVM) classifier optimized by the Sparrow Search Algorithm (SSA) was constructed. The results show that different defects lead to significantly differentiated harmonic distortions in the grounding currents, which is proved to be a reliable data basis for cable defect assessment. The proposed method refines the data information and achieves the most accurate recognition of cable defects, which may contribute to the reliable operation of power networks.
The Power of the Tongue: A Scoping Review of Inclusive Language Practices in Healthcare Settings
Authors: Perry Brittney A. , Otero Jessica , Marconi Vincent C. , Ordóñez Claudia E.
Published: November 2024

Patient-provider communication is a crucial aspect of the work conducted in healthcare settings. Studies have shown that spoken and written language used by providers during healthcare conversations can positively or negatively impact health outcomes. A scoping review was conducted to map peer-reviewed research articles focused on the use of spoken/written language in healthcare settings, identify and clarify key related concepts, and find best practices for decreasing the use of harmful and biased language among healthcare professionals. Peer-reviewed articles published in English from 2003 to 2023 were identified through ProQuest Sociological Abstracts, PubMed, and ScienceDirect databases. Covidence was used to perform screening and data extraction. The search initially identified 128 records for title and abstract screening, with 33 articles deemed relevant for a full-text screen. A total of nine articles met the review’s inclusion criteria. Findings indicated a need for increasing and expanding inclusive language training for healthcare providers to enhance patient care quality and health equity and to ensure the next generation of healthcare providers adopt these practices. Training healthcare providers in inclusive language is crucial to improving patient care and addressing systemic biases in the healthcare system. Integrating this training into educational curriculums and continuing education opportunities can help reduce biases, empower patients, and support better health outcomes.
A Hybrid Approach for Damage Identification of Steel Bridges with Discrete Cracks
Authors: Brenner Christoph , Thiele Klaus , Unglaub Julian
Published: November 2024

Many steel bridges are reaching the end of their service life due to increased traffic loads and outdated design practices. To predict their future condition, a hybrid approach for identifying fatigue-related damage, particularly discrete cracks, is applied to steel bridges with orthotropic decks. This method combines a data-driven selection of potential damage locations with highly detailed, physics-based simulation models using the Static Condensation Reduced Basis Element method (SCRBE). Synthetic data from static load tests, based on real-world loading scenarios, demonstrates the approach’s effectiveness on a steel arch bridge with various damage states. The results show that the method can identify damage using global displacement measurements. However, higher loads are required for practical damage detection due to the small effect of discrete damage on the global load-bearing behaviour. The study highlights the importance of focusing on realistic, localised damage, rather than extensive, fictitious scenarios in all damage identification methods. Incorporating innovative simulation techniques and Structural Health Monitoring can improve predictive maintenance for steel bridges, especially given the challenges of complex damage in large structures.
Adjustment of Magnetic Characteristics for [Co/Pt] Multilayer Thin Films
Authors: Dorokhin Mikhail , Zdoroveyshchev Anton , Demina Polina , Kuznetsov Yurii , Zdoroveishchev Daniil , Kudrin Alexey , Temiryazeva Marina , Temiryazev Alexei , Kalentyeva Irina , Ved' Mikhail , Kryukov Ruslan , Zubkov Sergey , Tatarskiy Dmitry
Published: November 2024

In the present paper we discuss the results of the study of magnetic properties and micromagnetic structure of multilayer [Co(4×t) Å/Pt(5×t) Å]10 thin films with varied bilayer thickness (t). The structures were fabricated by alternating electron beam evaporation of Co and Pt targets. The measurements of the element distribution profile, magnetic field dependence of magnetization and magnetic force microscopy pictures have shown that varying the t coefficient allows manipulating the degree Co and Pt layers intermixing, which, in turn, changes the magnetic properties of the films over a wide range. In particular, in structures representing a CoxPt1-x solid solution with a variable composition, magnetic skyrmions were revealed upon magnetization of the films. Varying the Co vs Pt composition heterogeneity makes it possible to control the skyrmion density. The results are believed to be promising for fabrication of skyrmion-based memory elements.
Skin Cancer Detection Using Transfer Learning and Deep Attention Mechanisms
Authors: Alotaibi Areej , AlSaeed Duaa
Published: November 2024

Early and accurate diagnosis of skin cancer improves survival rates; however, dermatologists often struggle with lesion detection due to similar pigmentation. Deep learning and transfer learning models have shown promise in diagnosing skin cancers through image processing. Integrating Attention Mechanisms (AMs) with deep learning have further enhanced the accuracy of medical image classification. While significant progress has been made, further research is needed to im-prove detection accuracy. Previous studies have not explored the integration of attention mechanisms with the pre-trained Xception transfer learning model for binary classification of skin cancer. This study investigates the impact of various attention mechanisms on the Xception model's performance in detecting benign and malignant skin lesions. Using the HAM10000 dermatoscopic image dataset, four experiments were conducted. Three models incorporated self-attention (SL), hard-attention (HD), and soft-attention (SF), respectively, while the fourth model used standard Xception without AMs. Results demonstrated the effectiveness of AMs, with models incorporating self, soft, and hard attention mechanisms achieving accuracies of 94.11%, 93.29%, and 92.97%, respectively, compared to 91.05% for the baseline model, representing a 3% improvement. Both self-attention and soft-attention models outperformed previous studies on recall metrics, which are crucial for medical investigations. These findings suggest that AMs can enhance performance on complex medical imaging tasks, potentially supporting earlier diagnosis and improving treatment outcomes.
Simultaneous Determination of the Main Aromatic Com-pounds and Divanillin in Vanilla planifolia Jacks. ex Andrews by HPLC-DAD
Authors: Torres-Zamudio Yunuen Erandy , Rodríguez-Jimenes Guadalupe del Carmen , Fernández Barbero Gerardo , Pérez-Silva Araceli
Published: November 2024

Vanilla planifolia Jacks. ex Andrews pods can lose up to 50% of their vanillin during curing. One explanation for this is the transformation of vanillin due to enzyme action, such as peroxidases, which generate the formation of dimers like divanillin. Therefore, in this work, a simultaneous high-performance liquid chromatography method (HPLC-DAD) was developed and validated for the separation and quantification of the main compounds present in Vanilla planifolia Jacks. ex Andrews and divanillin. The separation of 9 compounds of interest was achieved within 15 minutes using a Zorbax Eclipse XDB-C18 column (250 mm x 4.6 mm i.d., 5 μm particle size). The variables optimized included the mobile phase (water as solvent A, methanol as solvent B, and acidified water, 10–2 M H3PO4, as solvent C), the separation gradient, and the column tempera-ture (40-60 °C). The maximum divanillin content was 0.02 g/100 g d.w. in a sample from Papantla de Olarte. Chromatographic performance evaluation revealed excellent resolution, retention factor, and selectivity. The method was successfully validated in terms of limits of detection and quantification, linearity, and precision, as well as its application to cured pods, with evidence of divanillin presence in all analyzed sample.
Optimal Control of a Harmonic Oscillator with Parametric Excitation
Authors: Kamzolkin Dmitrii , Ternovski Vladimir , Ilyutko Victor
Published: November 2024

This paper investigates the optimal control of a harmonic oscillator governed by the second-order linear equation:
$$
\ddot{x}(t) + \omega^2(t) x(t) = 0,
$$
where $x(t)$ represents the system’s position, and $\omega(t)$ is the time-varying frequency. The primary objective is to determine the minimal time T required for the system to transition from an initial state,
$x(0) = x_0,\
\dot{x}(0)=v_0$ to a final state
$
x(T) = x_T,\
\dot{x}(T) = v_T$, under the constraint that the frequency $\omega(t)$ remains a bounded function. The main challenge involves identifying the optimal switching times between two frequencies while satisfying all boundary conditions. Various boundary scenarios are analyzed, and the reachable set of all trajectories is constructed. Analytical techniques, combined with control theory and a proven theorem, are utilized to solve this problem. This study is particularly relevant for applications requiring time-optimal control, such as mechanical vibration systems or signal processing, where rapid state transitions are crucial. The methods developed provide a robust framework for time-optimal control in oscillatory systems and are adaptable to other systems facing similar control challenges.
Abandoning the Car to Embrace the Bicycle in Urban France: A Model of Modal Shift
Authors: Gras Gentiletti Marion , Cahour Béatrice , Safin Stéphane
Published: November 2024

The current climate context is prompting stakeholders in the ecological transition to reconsider our transportation modes. The bicycle, in particular, appears promising, offering numerous benefits such as reducing polluting emissions and CO2, limiting noise pollution, alleviating urban congestion, and improving both the physical and mental health of citizens. However, despite policies aimed at encouraging cycling and the measures implemented, how can we explain the difficulty of urban French citizens in adopting the bicycle? Rather than focusing on the barriers to cycling, we have chosen to center our study on citizens who have opted to reduce or even abandon car use in favor of cycling in urban areas. This study provides a detailed description of the modal shift process that leads 20 individuals to transition from car use to cycling. By adopting a fine-grained approach through semi-structured and biographical interviews, it is possible to highlight the mechanisms behind this modal shift. Key stages appear to emerge: predispositions, triggering factors, the exploration and trial phase, and, in the longer term, the phase of appropriation. The article also explores the situations that lead cyclists to return to using their cars for specific trips.
Considerations on UAS-Based In-Situ Weather Sensing in Winter Precipitation Environments
Authors: Britto Hupsel de Azevedo Gustavo , Avery Alyssa , Schvartzman David , Landolt Scott , DiVito Stephanie , Revard Braydon , Jacob Jamey D.
Published: November 2024

Freezing rain and freezing drizzle can produce nearly undetectable hazards with potentially catastrophic consequences for aircraft within low altitudes (e.g., the terminal area). However, the lack of direct observations of the low-altitude freezing precipitation environment creates a challenge for forecasters, flight crews, dispatchers, and air traffic controllers. This research demonstrates how unmanned aerial vehicles (UAVs) can be designed and instrumented to create unmanned aerial weather measurement systems (WxUAS) capable of characterizing the low-altitude freezing precipitation environment and providing insight into the mechanisms that govern it. This article discusses the design considerations for WxUAS-based in-situ sampling in active precipitation, results from controlled experiments at the Oklahoma Mesonet’s calibration laboratory, as well as results from intercomparison studies with collocated well-established ground-based instruments in Oklahoma and Colorado. Additionally, we explore the insights provided by high-resolution thermodynamic and particle size distribution profiles and their potential contributions to a better understanding of the low-altitude freezing precipitation environment.
Innovative Acquired Deforming Hypertonia’s Treatment in the Geriatric Institution(s) Using Radical Innovation Design Methodology
Authors: Gatin Laure , Abdelatif Naila , Blancheteau Yannick , Sahin Evren , Jankovic Marija , Yannou Bernard
Published: November 2024

Abstract: Background/Objectives:. According to a recent study, about 22% of residents in re-tirement homes suffer from troublesome acquired deforming hypertonia (ADH). Very few of them benefit from the necessary care due to the difficulties inherent to travel and hospitalisation. To reduce the medical impact of surgical and hospitalisation duration, existing solutions like botuli-num toxin injections and needle tenotomy are not requiring a full surgery room or a night hospi-talization. Actual situations are deficient in detecting and treating patients with ADH problems. Hence, the idea of developing a mobile unit has been seen as a possibility to address the issue of accessibility for such a procedure near retirement homes and reduce hospitalisation time. Methods: To explore the lack of effective solutions in the care of patients suffering from ADH in France, and assess the potential advantages of this new concept, we used Radical Innovation De-sign (RID) methodology, well adapted to supporting usage-based innovation projects. Results: The study has allowed us to identify a refined understanding of the existing pain points of different ADH stakeholders (ADH patients, medical staff, retirement home staff) and investigate how ex-isting solutions address these pain points. We found value buckets which were starting points to imagine innovative solutions. The study allowed identifying six novel solution scenarios to reduce ADH patients’ suffering and assess them against their ability to alleviate the RID whole “quantities of pain” of ADH issue. Conclusions: One of the significant results partly based on this study is the decree allowing the use of the botulinum toxin in home healthcare in France. One of the novel solution scenarios had been allowed for an experimental part in 8 mobiles unit in France, for 3 years, since the 22 nd December 2022.
Dynamics of the Interaction Between Two Coherent States in a Cavity with Finite Temperature Decay
Authors: Hernández-Sánchez Leonardi , Ramos-Prieto Iran , Soto-Eguibar Francisco , Moya-Cessa Héctor M.
Published: November 2024

In this study, we provide an exact solution to the Lindblad master equation that describes the interaction of two quantized electromagnetic fields in a decaying cavity, coupled to a thermal reservoir at finite temperature. The solution is obtained using the superoperator technique, leveraging commutation relations to express the exponential of the Lindblad operators as a product of exponentials. This method allows for the solution to be directly applied to any initial condition of the system, offering a versatile approach to a wide range of configurations. To demonstrate its utility, we explore the case where the field modes are initially in non-entangled coherent states and investigate how the interaction with the reservoir affects the preservation or modification of the non-entanglement feature over time.
FAMHE-Net: Multi-scale Feature Augmentation and Mixture of Heterogeneous Experts for Oriented Object Detection
Authors: Chen Yixin , Jiang Weilai , Wang Yaonan
Published: November 2024

Object detection in remote sensing images is essential for applications like UAV-assisted agricultural surveys and aerial traffic analysis, facing unique challenges such as low resolution, complex backgrounds, and variability of object scales. Current detectors struggle with integrating spatial and semantic information effectively across scales and often omit necessary refinement modules to focus on salient features. Furthermore, a detector head that lacks meticulous design may face limitations in fully understanding and accurately predicting based on the enriched feature representations. These deficiencies can lead to insufficient feature representation and reduced detection accuracy. To address these challenges, this paper introduces a novel deep-learning framework, FAMHE-Net, for enhancing object detection in remote sensing images. Our framework features a consolidated multi-scale feature enhancement module (CMFEM) with integrated PAFPN, utilizing our efficient atrous channel attention (EACA) within CMFEM for enhanced contextual and semantic information refinement. Additionally, we introduce a sparsely gated mixture of heterogeneous expert heads (MOHEH) to adaptively aggregate detector head outputs. Compared to the baseline model, FAMEH-Net demonstrates significant improvements, achieving a 0.90% increase in mAP of the DOTA dataset and a 1.30% increase of mAP12 of HRSC2016 datasets. These results highlight the effectiveness of FAMEH-Net in object detection within complex remote sensing images.
A Paradigm for Modeling Infectious Diseases: Assessing Malware Spread in Early-Stage Outbreaks
Authors: Ginters Egils , Dumpis Uga , Liñán Laura Calvet , Eroles Miquel Angel Piera , Nazemi Kawa , Matvejevs Andrejs , Estrada Mario Arturo Ruiz
Published: November 2024

As digitalization and artificial intelligence advance, cybersecurity threats intensify, making malware—a type of software installed without authorization to harm users—an increasingly urgent concern. Due to malware's social and economic impacts, accurately modeling its spread has become essential. While diverse models exist for malware propagation, their selection tends to be intuitive, often overlooking the unique aspects of digital environments. Key model choices include deterministic vs. stochastic, planar vs. spatial, analytical vs. simulation-based, and compartment-based vs. individual state-tracking models. In this context, our study assesses fundamental infection spread models to determine those most applicable to malware propagation. It is organized in two parts: the first examines principles of deterministic and stochastic infection models, and the second provides a comparative analysis to evaluate model suitability. Key criteria include scalability, robustness, complexity, workload, transparency, and manageability. Using consistent initial conditions, control examples are analyzed through Python-based numerical methods and agent-based simulations in NetLogo. The findings yield practical insights and recommendations, offering valuable guidance for researchers and cybersecurity professionals in applying epidemiological models to malware spread.
On the Application of the Autoregressive–Moving-Average Model for Studying Phylogenetic Rate of Trait Evolution
Authors: Jhwueng Dwueng-Chwuan
Published: November 2024

The rate of evolution plays a crucial role in understanding the pace at which species evolve.
Various statistical models have been developed to estimate the rate parameters for a group of related species evolving along a phylogenetic tree.
Existing models often assume the independence of the rate parameters;
however,
this assumption may not account for scenarios where the rate of evolution correlates with its evolutionary history.
We propose using the autoregressive-moving-average (ARMA) model for modeling the rate of evolution along the tree,
hypothesizing that rates between two successive generations (ancestor-descendant) are time dependent and correlated along the tree.
We denote \texttt{phyrateARMA}$(p,q)$ as a phylogenetic ARMA($p$,$q$) model in our innovation.
Our algorithm begins by utilizing the tree and trait data to estimate the rates on each branch,
followed by implementing the ARMA process to infer the relationships between successive rates.
We apply our innovation to analyze the primate body mass dataset and plant genome size dataset and test for the autoregressive effect of rate of evolution along the tree.
Overall Warehouse Effectiveness (OWE): A New Integrated Performance Indicator for Warehouse Operations
Authors: Chiaraviglio Alessandro , Grimaldi Sabrina , Zenezini Giovanni , Rafele Carlo
Published: November 2024

Warehouses play a vital role in logistics systems, not only for storing goods but also for provid-ing value-added services. To improve warehouse productivity and reduce costs, it is essential to measure their performance and identify inefficiencies. This paper introduces a new aggregated Key Performance Indicator (KPI), called Overall Warehouse Effectiveness (OWE), to evaluate the effectiveness of the physical structure of a warehouse. OWE utilizes the concepts of Availability, Performance, and Quality, similar to the Overall Equipment Effectiveness (OEE) metric used in manufacturing. The proposed indicator is then applied to a case study to demonstrate its use and provide theoretical and practical implications. In terms of theoretical implications, the proposed metric fills a gap in the literature by providing an aggregated indicator specifically designed for storage systems. For practitioners, OWE enables the identification of waste, customer service faults and adequacy of inventory management policies.
Optimizing Cucumber Fruit Metabolomics under Elevated CO2 and High-Temperature Stress in Protected Horticulture
Authors: Du Xian , Song Yang , Pan Lu , Cui Shimao
Published: November 2024

Elevated carbon dioxide concentrations can mitigate significant threats posed by high-temperature stress to cucumber fruit yield and quality during summer. To investigate the potential metabolic mechanisms, this study employed untargeted metabolomics methods to analyze the effects of varying temperatures and carbon dioxide concentrations on the metabolomic profiles of cucumber fruits. Under high-temperature stress, elevated carbon dioxide concentrations altered 27 differential metabolites, including tyramine, xylitol, linolenic acid, L-asparagine, α-linolenic acid, and L-phenylalanine. These alterations are associated with the metabolic pathways of alanine, aspartate, glutamate, glutathione, glyoxylate, and dicarboxylic acids. Compared to the addition of carbon dioxide at normal temperatures, elevated carbon dioxide at high temperatures modified 38 differential metabolites, including vitamin B6, L-citrulline, inositol, L-aspartic acid, sucrose, and palmitic acid. These modifications were linked to the galactose metabolic pathway and the zeatin and arginine biosynthetic pathways. The accumulation of cysteine, glutamic acid, and glycine is essential for the formation of antioxidant glutathione; thus, cucumber fruits with higher amino acid content exhibit an enhanced capacity to withstand severe high-temperature stress. Under high-temperature conditions, elevated carbon dioxide adds complexity to the changes in differential metabolites within cucumber fruits. These fruits accumulate sugars, organic acids, and amino acids through the galactose metabolism pathway (map00052), the arginine biosynthesis pathway (map00220), and the glutamate synthesis pathway (map00250), thereby improving their heat resistance.
Unmanned Aircraft Systems in Colombia: A Chronological and Sectoral Analysis
Authors: González Medina Sara Valentina , Melo Daza Pedro Fernando , Sanchez Garcia Angie Valentina
Published: November 2024

The Colombian Aeroclub licensed the first use of Unmanned Aircraft Systems (UAS) in Colombia in 2004. Initially, this technology was used for research and development purposes. In 2004, several UAS were obtained from the Aeroclub de Colombia, and this is considered the first recorded use of UAS in Colombia. In 2015, Aerocivil issued Circular 005 as an initial operational regulation for UAS in Colombia, a significant step towards the regulation of these aircraft. The establishment of the National UAS Commission in 2016 to foster responsible development within the UAS industry has marked another milestone. For 2023, Aerocivil brings to light Circular 008 that serves as a regulation that governs the operation of UAS specifically in urban landscapes, to which the National Development Plan (2022-2026) is later added. This plan adds a section dedicated to describing how drones can be used for economic and social growth; Two intertwined but distinct spheres. The use of unmanned aircraft systems (UAS) has revolutionized government decision-making, providing smart alternatives for information collection and processing, surveillance and monitoring are the two main components of security with many details. This helps stakeholders to take timely and effective action in different fields, including but not limited to medical situations that require emergency responses or natural calamities (where specific efforts can be concentrated based on identified needs), security to ensure peace among citizens, urban development through proper planning of resource allocation and use, etc. The use of drones in government has a far-reaching impact on many sectors that fall under scientific and technological research.
Creation of CCT Diagram Using Comprehensive Dilatometric Analysis of HSLA Steel S700MC
Authors: Moravec Jaromír , Klápště Daniel , Švec Martin
Published: November 2024

The use of High-Strength LowAlloy (HSLA) steels for welded parts and structural assemblies is increasingly common. Steel S700MC is one of the most widely used HSLA steels, especially in the automotive and manufacturing industries. It combines high-strength properties with good ductility, toughness and reasonable technological workability in forming and welding. Despite all these advantages, there is still not enough information describing the processes and changes in material properties that occur in different heating and cooling conditions. The present study aims to describe such processes in detail using dilatometric studies. Thus, it results not only in a newly developed Continuous Cooling Transformation (CCT) diagram of the S700MC steel, but also in an assessment of the heating rate effect on the change of austenitizing temperatures. Then, the influence of the cooling rate on the bandwidth of transformation changes is defined, and the impact of temperature cycles on the changes in mean grain size is assessed. A comprehensive study of this type has not yet been published for S700MC steel.
First Molecular Characterization of Fusarium circinatum Isolated from Pinus oocarpa in Honduras
Authors: Ortiz Bryan , Mendoza Keylin , Enríquez Lourdes , Aguilar Kateryn , Yánez-Euceda Yensi , Amaya-Funes Kevin , Umaña-Valle Isis , Fontecha Gustavo
Published: November 2024

Fusarium circinatum (anamorph of Gibberella circinata) is the etiological agent of resinous canker in conifers, especially within the genus Pinus. This pathogen can impact all phases of tree development. Infections caused by F. circinatum in pine forests have been catastrophic in numerous countries globally, underscoring the necessity of understanding the geographical distribution of this fungus to enhance ecological comprehension and inform effective control measures. This study aims to report the existence of F. circinatum as a potential pathogen of pine trees in Honduras. Samples were obtained from mature trees and tree nurseries of Pinus oocarpa in three departments of Honduras, exhibiting symptoms such as chlorosis, needle wilting, and progressive mortality. Samples underwent microbiological and molecular identification. The isolates were identified using phenotypic approaches focused on micro and macro morphology, followed by the amplification and sequencing of three genes: ITS, EF-1α, and Beta-tubulin. Three isolates of the fungus were identified as F. circinatum. No genetic diversity was seen among the three isolates; nevertheless, some diversity was evident in comparison to sequences deposited in databases from different geographic regions. This is the first report and molecular characterization of F. circinatum isolated from Pinus oocarpa in Honduras.
Preparation of a New Active Component 1,10-B10H8(S(C18H37)2)2 for Potentiometric Membranes, for the Determination of Terbinafine Hydrochloride
Authors: Turyshev Eugeniy S. , Bykov Alexander Yu. , Golubev Aleksei V. , Zhizhin Konstantin Yu. , Kuznetsov Nikolay T.
Published: November 2024

This paper presents a methodology for the preparation of a new active component for ion-selective membranes, based on a di-substituted sulfonium derivative of the closo-decaborate anion at the apical vertices with octadecylalkyl substituents 1,10-B10H8(S(C18H37)2)2. This approach is characterised by physicochemical methods of analysis (11B, 1H, 13C NMR spectroscopy, IR spectroscopy and elemental analysis). The compound obtained was used as an active component of a PVC-membrane selective to terbinafine hydrochloride. The sensor developed is highly selective to the drug to be detected, and has a linearity range of 4.0 × 10-8 – 1.0 × 10-2 and a detection limit of 1.0 × 10-8, and can detect terbinafine hydrochloride in the pH range of 3 to 6.
Calculation of the Optimal Duty Cycle for a Coaxial Magnet of a Rotary Type Magnetic Refrigerator
Authors: Lee Chih-Hao , Cheng Pai-Hsiang , Leou Keh-Chyang , Hsieh Chih-Ming , Su Yu-Chuan
Published: November 2024

In a design of rotary type magnetic refrigerator, a high field of coaxial magnet is desired. Typically, a high field design can be achieved with a small duty cycle which might not be optimized from the viewpoint of the thermal hydraulics of a magnetic refrigerator. Numerical simulation analysis of a coaxial magnet-designed using COMSOL program for rotary type active magnetic refrigeration (AMR) system has been performed for magnet structures based on neodymium-iron-boron permanent magnets. The AMR material considered was thin gadolinium plates. For a rotary type magnetic cooling system, from the thermal hydraulic point of view, the best duty cycle of coaxial magnet should be 50% if the magnetic field can be kept as constant during the period of duty cycles. However, the simulation calculation shows that a serious reduction of the magnetic field strength at higher duty cycles resulting in lower magnetic cooling efficiency. After considering the thermo-hydraulic part, the optimized duty cycle is around 30% in case of a temperature span of 8 K between the hot and cold ends on a rotary type magnetic cooling system.
AI in Hepatology: Revolutionizing the Diagnosis and Management of Liver Disease
Authors: Malik Sheza , Das Rishi , Thongtan Thanita , Thompson Kathryn , Dbouk Nader
Published: November 2024

The integration of artificial intelligence (AI) into hepatology is revolutionizing the diagnosis and management of liver diseases amidst a rising global burden of conditions like metabolic-associated steatotic liver disease (MASLD). AI, particularly machine learning (ML) and deep learning (DL), harnesses vast datasets and complex algorithms to enhance clinical decision-making and patient outcomes. AI's applications in hepatology span a variety of conditions, including autoimmune hepatitis, primary biliary cholangitis, primary sclerosing cholangitis, MASLD, hepatitis B, and hepatocellular carcinoma. It enables early detection, predicts disease progression, such as fibrosis and cirrhosis, and supports more precise treatment strategies. Despite its transformative potential, challenges remain, including data integration, algorithm transparency, and computational demands. This review examines the current state of AI in hepatology, exploring its applications, limitations, and the opportunities it presents to enhance liver health and care delivery.
Kinetic Modeling of Social Crowds with Infectious Disease Contagion
Authors: Agnelli Juan P. , Armas Claudio , Knopoff Damián A.
Published: November 2024

This paper introduces a kinetic model that couples social behavior in crowds (such as social interpersonal distance or herding) with contagion dynamics. The approach is based on the so-called kinetic theory of active particles where the activity variable represents the psychological state of pedestrians as well as their state related to an infectious disease (e.g., susceptible, infected, etc.). The activity evolves as the crowd moves and eventually exits a closed room. Some case studies are proposed in order to demonstrate the role of activity and how contagion awareness and stress influence the crowd movement and its shaping behavior.
Probably A New Species Of Bacteria Of The Genus Pseudomonas Accelerates And Enhances The Destruction Of Perfluorocarboxylic Acids
Authors: Chetverikov Sergey , Hkudaigulov Gaisar , Sharipov Danil , Starikov Sergey
Published: November 2024

Bacteria of the genus Pseudomonas are the most studied microorganisms in the biodestruction of persistent perfluoroorganic pollutants, and the research on their application for the remediation of environmental sites using biotechnological methods remains relevant. The aim of this study was to investigate the ability of a known destructor of perfluorooctane sulfonic acid from the genus Pseudomonas to accelerate and enhance the depth of destruction of long-chain perfluorocarboxylic acids (PFCAs), specifically perfluorooctanoic acid and perfluorononanoic acid, in water and soil in association with the strain P. mosselii 5(3), which has previously confirmed genetic potential for degrading PFCAs. The complete genome (length 5.86 million base pairs) of the strain 2,4-D, a new species of Pseudomonas, was sequenced, assembled, and analyzed. The genomes of both strains contain genes involved in the defluorination of fluorinated compounds, including haloacetate dehalogenase H-1 (dehH1) and haloalkane dehalogenase (dhaA). The strain 2,4-D also has a multi-component enzyme system consisting of a dioxygenase component, an electron carrier, and 2-halobenzoate 1,2-dioxygenase (CbdA) with a preference for fluorides. The strain 2,4-D was able to completely decarboxylate and defluorinate PFCAs in an aqueous cultivation system within 7 days, using them as the sole source of carbon and energy, but it only converted them to perfluorheptanoic acid. However, it assisted strain 5(3) (which defluorinated them during the same period to perfluorohexanoic acid) in converting PFCAs to perfluoropentanoic acid, accelerating the process by 24 hours. The degradation and transformation of the anionic acids were assessed using LC-MS analysis, and the release of indicators for mineralization of fluoride ions was determined by ion chromatography. In a model experiment for bioaugmentation of microorganisms in artificially contaminated soil, the degradation of PFCAs by the association of pseudomonads also occurred faster and deeper than by the individual strains, achieving a degree of biodestruction of 75% over 60 days, with perfluoropentanoic acid being the main metabolite of destruction. Thus, it has been demonstrated that strains of Pseudomonas bacteria with genetic potential for the biodegradation of PFCAs are capable of realizing this potential in association, exhibiting an additive effect.
Harnessing the Power of Metabolomics for Precision Oncology: Current Advances and Future Directions
Authors: Kohli Manas , Poulogiannis George
Published: November 2024

Metabolic reprogramming is a hallmark of cancer, with cancer cells acquiring many unique met-abolic traits to support malignant growth, and extensive intra- and inter-tumour metabolic het-erogeneity. Understanding these metabolic characteristics presents opportunities in precision medicine for both diagnosis and therapy. However, despite its potential, metabolic phenotyping has lagged behind genetic, transcriptomic and immunohistochemical profiling in clinical appli-cations. This is partly due to the lack of a single experimental technique capable of profiling the entire metabolome, necessitating the use of multiple technologies and approaches to capture the full range of cancer metabolic plasticity. This review examines the repertoire of tools available for profiling cancer metabolism, demonstrating their applications in preclinical and clinical settings. It also presents case studies illustrating how metabolomic profiling has been integrated with oth-er omics technologies to gain insights into tumour biology and guide treatment strategies. This information aims to assist researchers in selecting the most effective tools for their studies and highlights the importance of combining different metabolic profiling techniques to comprehen-sively understand tumour metabolism.
The Age of Sexual Initiation Among Polish Youth: The Role of Individual and Social Factors
Authors: Izdebski Zbigniew , Kozakiewicz Alicja , Mazur Joanna
Published: November 2024

Sexual development is a natural part of adolescence and can be influenced by various factors. This study involved 3,296 Polish adolescents aged 15–17 who participated in the international Health Behaviour in School-aged Children (HBSC) survey in 2018. The main dependent variable was the declared age of sexual initiation. The study examined the determinants of this age by investigating the relationship with gender and 15 factors related to lifestyle and functioning within the family, school, and social environment. The Cox proportional hazard model (aligned with censored data) revealed that frequent use of psychoactive substances is the main predictor of the age of sexual initiation (HR=5.20; 95% CI: 3.66-7.38), with even moderate use having an impact (HR=2.81; 95% CI: 2.04-3.86). Gender was not found to significantly influence the age of initiation, but the determinants did vary by gender. For boys, high physical activity and intensive socializing with peers are important factors. For girls, a positive self-assessment of appearance is more strongly associated with earlier initiation, while good academic performance and family support have a delaying effect. Effective intervention programs should consider these diverse determinants since they profoundly shape adolescents’ decisions about sexual activity and their ensuing psychological experiences.
Exploring the Socio-economic Drivers of Child Labor: A Case Study of the Hotel Industry in Quetta, Balochistan
Authors: Ullah Hamid , Ullah Abid
Published: November 2024

Child labor is a complex issue influenced by various socio-economic and political factors. This study aims to explore the socio-economic causes of child labor in Quetta, Balochistan, with a specific focus on the hotel and restaurant sector. Using a quantitative approach, the study surveyed 200 children employed in these industries through structured questionnaires. In addition, key informant interviews were conducted to gain deeper insights into the root causes of child labor. The findings reveal a strong correlation between child labor and the socio-economic conditions of the family. However, poverty alone does not account for the prevalence of child labor. The study distinguishes between two sets of factors: push factors (such as poverty, unemployment of adult family members, and the need to meet basic family needs) and pull factors (including parental pressure, family size, limited access to quality education, and cultural norms). The study concludes with practical recommendations for stakeholders to address the issue of child labor.
Social Media Activism In Underrepresented Communities: A Case Study of Indigenous Narratives
Authors: Okonkwo Peter , Njoku PhD Ignatius Achilike , Okonkwo Rosemary Ngozi
Published: November 2024

This research explored the role of social media in empowering Indigenous narratives, focusing on how digital platforms enabled Indigenous communities to challenge colonial histories, promote cultural sovereignty, and advocate for social justice. Using a mixed-methods approach that included case studies, interviews, surveys, and content analysis, the study investigated key social media campaigns such as #IdleNoMore and #MMIW, along with the perspectives of Indigenous activists and community members. The findings identified the primary enablers and barriers to effective digital activism, examined patterns of audience engagement, and assessed the impact of social media in reshaping public perceptions of Indigenous issues. The research also addressed challenges such as algorithmic bias, the digital divide, and cyber harassment and provided recommendations for both Indigenous communities and social media platforms to improve digital activism efforts. Ultimately, the study contributed to the growing field of digital activism by highlighting the transformative potential of social media in amplifying Indigenous voices and fostering a more inclusive digital space for social change.
Information That Cannot Be Gained by Studies of Serum Antibodies: ImmunoSpot Assays Permit Detailed Assessment of Antigen-Specific Memory B Cells Through Defining Their Frequency, Affinity, Cross-Reactivity Profile, and Antibody Class/Subclass Utilization
Authors: Kirchenbaum Greg A. , Pawelec Graham , Lehmann Paul V.
Published: November 2024

Determining an individual’s humoral immune reactivity to a pathogen, autoantigen, or environmental agent is traditionally accomplished through assessment of specific antibody levels in blood. However, in many instances, titers of specific antibodies decline over time and thus do not faithfully reveal prior antigen exposure or establishment of immunological memory. To estimate an individual’s humoral immune competence, it is therefore necessary to assess functional B cell memory. Here, we describe novel B cell ELISPOT and FluoroSpot assays (collectively referred to as ImmunoSpot®) that can be rapidly developed and validated to characterize the memory B cell repertoire specific for any desired antigen ex vivo and at single-cell resolution. Moreover, multiplexed variants of the B cell FluoroSpot assay enable high-throughput testing of antigen-specific B cells secreting distinct antibody classes and/or IgG subclasses, with minimal cell material requirements. B cell ImmunoSpot assays also enable measurement of affinity distributions within the antigen-specific memory B cell compartment and permit cross-reactivity measurements that can provide insights into B cell memory established against future pathogen variants. Collectively, the ImmunoSpot® system presented here is highly reproducible, and can be readily validated for regulated tests. The newly gained ability to monitor the antigen-specific memory B cell compartment should catalyze a more comprehensive understanding of humoral immunity in health and disease.
Planetary Health Diet and Cardiovascular Disease Risk in the Seguimiento Universidad De Navarra (SUN) Cohort
Authors: Guzmán-Castellanos Karen Berenice , Zazpe Itziar , Santiago Susana , Bes-Rastrollo Maira , Martínez-González Miguel Ángel
Published: November 2024

Noncommunicable diseases, particularly cardiovascular disease (CVD), represent a significant global public health challenge, with unhealthy diets as a major risk factor. This study investigates the association between adherence to the Planetary Health Diet proposed by the EAT-Lancet Commission and CVD risk. Methods: Utilizing data from the Seguimiento Universidad de Na-varra (SUN) cohort, which included 18,656 participants (mean age 38 years, 61% women), we as-sessed dietary intake using a validated food frequency questionnaire and the Planetary Health Diet Index to evaluate adherence (range 0-42). CVD was defined as new-onset stroke, myocardial in-farction, or CVD death. Results: After a median follow-up time of 11.5 years, 220 cases of CVD were identified. Higher adherence to the Planetary Health Diet revealed no statistically significant reduction in CVD risk associated with the diet. Cox proportional hazard models indicated a trend towards lower CVD risk in the highest adherence quartile, but this did not reach significance (HR 0.77, 95% CI 0.51-1.18, p-trend = 0.127). Sensitivity analyses corroborated these results. Discrep-ancies in previous studies highlight the complexity of dietary assessments and underscore the need for standardized scoring systems. Conclusions: In a large Spanish cohort, adherence to the Plan-etary Health Diet showed no significant reduction in CVD risk. Further research is needed to reach a consensus on the operational definition of the Planetary Health Diet and to clarify the rela-tionship between diet and CVD risk.
CNSL Based Green Catalyst Schiff Base Ligand and Its Metal(II) Complexes Synthesis, Characterization, Antibacterial, Anticancer and Molecular Docking Studies
Authors: Mohana priya T , Krishna Moorthy C , GOMATHI T , M. Kannan
Published: November 2024

A Schiff base ligand is synthesized from the condensation of dapsone and 4-dimethylaminobenzaldehyde using cashew nut shell liquid (CNSL) anacardic acid as a green and natural effective catalyst via solvent-free simple physical grinding technique. Furthermore, metal(II) complexes Co(II), Cu(II) and Zn(II) coordinated by a new Schiff base ligand (L) were prepared. The composition of Schiff base ligand and its metal(II) complexes were analyzed by various analytical techniques. The Schiff base ligand and its complexes have been tested in vitro to evaluate their antimicrobial activity against Escherichia coli, Staphylococcus aureus and Candida albicans using well-diffusion method. It has been found that the Schiff base ligand and its complexes show significant antimicrobial activity against all tested bacterial species. Molecular docking study of Cu(II) complex with target protein HER2 has revealed good binding energy.