bluuebunny/crossref_metadata_2025 huggingface dataset:
Unified Representation Learning for Relation Extraction in Visually-Rich Documents
Authors: Bennett Olivia , Marwood Emily , Carter Noah
Published: February 2025

Recent advances in multimodal integration—combining text, geometric layout, and visual cues—have led to significant improvements in the field of Visually-rich Document Understanding (VrDU), particularly in relation extraction (RE) tasks. In our work, we introduce a novel approach, termed \textbf{UniFusion}, which reimagines the process of joint representation learning through a comprehensive analysis of each modality’s contribution. Our experiments systematically exclude each data type in turn, and we also evaluate text and layout modalities in isolation, thereby providing a detailed account of the predictive capacity inherent in each signal. In our extensive study, we demonstrate that a bimodal configuration integrating textual content with layout geometry consistently outperforms other configurations, achieving an F1 score of 0.684. This observation underscores the pivotal role of textual information as the primary driver in predicting entity relationships. However, our analysis further reveals that geometric layout features, when used as a unimodal predictor, offer substantial predictive power and can serve as an effective standalone approach under certain circumstances. Although the visual modality, when used in isolation, exhibits relatively lower performance, our results indicate that its inclusion in a multimodal fusion strategy can enhance overall performance by providing supplementary contextual information. Moreover, our experiments span a diverse array of document types and noise conditions, confirming that the integration of multiple modalities via UniFusion leads to more robust performance, particularly in scenarios with incomplete or noisy textual data. In summary, our findings provide compelling evidence for the efficacy of joint representation learning, demonstrating that a carefully balanced fusion of text, layout, and visual modalities is essential for advancing the state-of-the-art in RE tasks within the VrDU framework.
A Novel Approach to Semiconductor Fabrication Using Graphene Stencils for Enhanced Nanoscale Lithography
Authors: Qadri Syed Munim
Published: February 2025

The semiconductor industry is approaching the physical limits of traditional photolithography as device features shrink into the nanometre regime. Although reducing the UV wavelength can, in theory, allow for smaller features, quantum tunnelling and diffraction effects impose fundamental limitations. In this work, we present an innovative fabrication technique that replaces the reliance on ultra-short UV wavelengths with a graphene stencil method. Our process entails sequentially processing a silicon wafer: first depositing a silicon dioxide (SiO₂) layer, then transferring a pre-patterned graphene sheet (carved via focused ion beam or electron beam lithography) onto the SiO₂, and finally depositing a photoresist layer over the graphene stencil. UV exposure then selectively activates the photoresist only in the exposed regions, allowing subsequent etching to define sub-lithographic features. We derive mathematical models—based on the Deal–Grove oxidation kinetics and Rayleigh resolution criteria—to quantify process parameters, and we validate our approach through computational simulations (using FEA and FDTD methods) with data extracted from industry and literature. In addition, we address a critical challenge: the adhesion between the graphene and the SiO₂ layer, proposing solutions such as localized oxide thickness modification and hydrophobic treatment of the graphene underside. Our results indicate that feature sizes as small as 10 nm can be reliably produced, representing a threefold improvement over conventional 193 nm UV lithography. This work provides a detailed roadmap for integrating graphene stencils into semiconductor fabrication using existing technology.
Recovery of End-of-Life Building Materials: Physicochemical Characterization of Asbestos in Fiber Cement Boards
Authors: Curado António , Nunes Leonel J. R. , Carvalho Arlete , Abrantes João C. C. , Lima Eduarda , Tomé Mário
Published: February 2025

The circular economy is strategically based on the three R's policy: reduce, recycle and reuse, which is not easy to apply to waste for which there are no processes that allow them to be recycled, or others for which reuse is not possible. One group of wastes that is particularly problematic because of its volume, quantity and diversity is the group of construction and demolition materials, including fibrous materials such as asbestos, for which there are still no clear alternatives for reintroduction into the supply chains of new processes. The destination of these end-of-life materials is landfill, with all the well-known drawbacks of limited landfill space, the high volume of material to be landfilled and the associated costs. In order to promote the reuse of asbestos fibres, it is essential to characterise them in physico-chemical terms and to assess how effectively mechanical and thermal treatments can transform these fibres for reuse, in order to provide the basis for a systematic approach to the incorporation of asbestos-containing waste into new construction applications. This analysis focuses on sustainable construction practices aimed at reusing waste materials to achieve significant reductions in carbon emissions over the entire life cycle of buildings.
Driving Sustainable Innovation in Digital Technologies: A Deep Dive into Energy-Efficient Computing and Circular Design
Authors: William Barnty , Mabel Emmanuel
Published: February 2025

This research explores the role of sustainable innovation in digital technologies, with a focus on energy-efficient computing and circular design practices. The purpose of the study is to evaluate how these practices can contribute to environmental sustainability while fostering innovation in the tech industry. The study employs a mixed-methods approach, combining qualitative interviews with industry experts and a quantitative analysis of energy consumption data in various digital systems. The key findings reveal that energy-efficient computing, when integrated into design processes, can significantly reduce the carbon footprint of digital technologies. Additionally, the adoption of circular design practices—such as reusing hardware components and optimizing resource utilization—leads to both environmental and economic benefits for technology companies. Despite these advantages, challenges such as high initial costs and technological limitations hinder widespread adoption of sustainable practices. In conclusion, the study emphasizes that driving sustainable innovation in digital technologies requires a shift toward both energy-efficient computing and circular design, supported by industry-wide collaboration, government policies, and investment in R&D. The research calls for further exploration into scalable solutions and strategies to overcome the barriers to implementation, ensuring a more sustainable future for the digital sector.
Sustainable SMEs Performance: Knowledge Management, Human Resources Digital Transformation, and Innovation Capabilities – A Practical Approach to Business in the Digital Age
Authors: Budiarti Isniar , Firmansyah Deri
Published: February 2025

The purpose of this study is to examine the influence of knowledge management (KM), and human resources digital transformation (HRDT) on sustainable performance through innovation capabilities (IC) mediators among small and medium-sized enterprises (SMEs). The explanatory survey method was developed with a questionnaire as an instrument to collect data from 353 respondents selected as employees and SMEs in Indonesia. Theoretical confirmation to test hypotheses in causality predictive models by applying structural equation modeling, covariance-based (CB-SEM) with AMOS v.24 application. The findings of the study show that KM, HDRT and IC are proven to have a positive and significant direct effect on the performance of sustainable SMEs. KM and HDRT also had a positive and significant effect on the improvement of ICs. The confir-mation provides sufficient evidence that verified ICs have a positive mediating effect on the relationship between KM and HRDT with sustainable SME performance. IC is stra-tegically a critical solution in strengthening the implementation of KM and HRDT as an effective and adaptive SME managerial tool for sustainable performance improvement. These findings provide enough valuable evidence that can fill the existing gaps related to sustainable SME performance models.
A Color-Based Multispectral Imaging Approach for a Human Detection Camera
Authors: Ono Shuji
Published: February 2025

In this study, we propose a color-based multispectral approach using four selected wavelengths (453, 556, 668, and 708 nm) from the visible to near-infrared range to separate clothing from the background. Our goal is to develop a human detection camera that supports real-time processing, particularly under daytime conditions and for common fabrics. While conventional deep learning methods can detect humans accurately, they often require large computational resources and struggle with partially occluded objects. In contrast, we treat clothing detection as a proxy for human detection and construct a lightweight machine learning model (multi-layer perceptron) based on these four wavelengths. Without relying on full spectral data, this method achieves an accuracy of 0.95, precision of 0.97, recall of 0.93, and an F1-score of 0.95. Because our color-driven detection relies on pixel-wise spectral reflectance rather than spatial patterns, it remains computationally efficient. A simple four-band camera configuration could thus facilitate real-time human detection. Potential applications include pedestrian detection in autonomous driving, security surveillance, and disaster victim searches. However, our current results are limited to daytime environments and fibers such as cotton, polyester, and wool.
Controls on the Transformation of Clay Minerals in the Miocene Evaporite Deposits of the Ukrainian Carpathian Foredeep: An Overview
Authors: Yaremchuk Yaroslava , Hryniv Sofiya , Peryt Tadeusz
Published: February 2025

Clays deposited in marine evaporite sequences are strongly altered and the most important factor determining their transformation is the brine concentration. X-ray diffraction study of clay minerals associated with the Lower and Middle Miocene evaporite formations of the Ukrainian Carpathian Foredeep indicated that the clay mineral associations in the gypsum facies are composed of smectite and illite, and in some samples mixed-layer chlorite-smectite and illite-smectite as well as chlorite. In the halite facies, illite, chlorite and mixed-layer illite-smectite occur in rock salt of Eggenburgian age (Vorotyshcha Suite); in addition to those minerals, smectite, corrensite and mixed-layer chlorite-smectite occur in the Badenian rock salt (Tyras Suite); and in the potash facies illite and chlorite were recorded. Such clay mineral associations resulted from aggradational transformation of unstable and labile minerals and phases (kaolinite, smectite and mixed-layer phases) that finally pass into illite and chlorite: minerals that are stable in an evaporite environment. In addition to brine concentration control, another important factor in the transformations of clay minerals was sorption of organic components on the mineral structure, that slows the transformation processes. The association of clay minerals in the weathering zone of the evaporite deposits, besides inherited illite and chlorite, contains also mixed-layer illite-smectite and kaolinite. The appearance of those clay minerals in hypergene deposits is the consequence of two processes: degradational transformation (illite-smectite) and neoformation (kaolinite) in conditions of decreased ionic concentrations during desalination.
From Chaos to Order: A Stochastic Approach to Self Organizing Systems
Authors: Demopoulos Nikos
Published: February 2025

The emergence of order from chaos is a fundamental question span- ning multiple scientific disciplines, from physics and biology to com- plex social and economic systems. Traditional deterministic perspec- tives often fail to account for the spontaneous organization observed in nature, where seemingly random interactions give rise to struc- tured patterns. This paper explores how stochastic processes, rather than opposing order, act as a crucial mechanism for self-organization. We propose that stochastic determinism, the interplay between ran- domness and structured evolution, underpins the formation of stable macroscopic laws. Entropy, commonly perceived as a driver of dis- order, is reinterpreted as an organizing force in open systems, where local randomness leads to global order through non-linear interactions and feedback mechanisms. By integrating mathematical models of stochastic differential equa- tions and the law of large numbers, we demonstrate how fluctuations in quantum mechanics, biological evolution, and socio-economic net- works contribute to emergent complexity. These processes, though driven by chance at a micro level, generate statistically predictable outcomes at a macro-level, bridging the gap between chaos and struc- ture. The implications of this study extend across disciplines, providing a unifying framework for understanding pattern formation, stability in dynamic systems, and the evolution of complexity. By recogniz- ing stochasticity as an essential principle of natural organization, this research paves the way for advancements in artificial intelligence, cli- mate modeling, and adaptive socio-economic policies. The findings challenge conventional views of randomness, presenting it not as an obstacle but as the fundamental catalyst for the emergence of order.
Static Shift Correction and Fractal Characteristic Analysis of Time-Frequency Electromagnetic
Authors: Hou Yujian , Jiang Qiyun , Qiao Yan , Zhao Yunsheng , He Zhanxiang
Published: February 2025

The static shift effect is a distortion in electromagnetic data that severely impacts exploration results. Traditional static effect correction methods are often ineffective, prone to overcorrection or undercorrection, and make it difficult to accurately assess the applicability of the correction. Furthermore, some correction processes require additional data, which increases correction costs. This paper first presents the theoretical foundation for correcting static shift effects in the electric field components using magnetic field component information. Based on time-frequency electromagnetic exploration technology, a method is proposed to correct static shift effects in the electric field by using simultaneously collected magnetic field data, aiming to address the distortion issues caused by static shift effects in the electric field and apparent resistivity. The method is validated through both theoretical models and field data, demonstrating its excellent correction performance. Additionally, the paper introduces the use of the multifractal spectrum analysis algorithm to analyze profile measurement points and study the fractal dimension characteristics of static shift effects, providing an effective way to evaluate the appropriateness and potential overcorrection of the correction. Finally, the multifractal features of field data are discussed, validating the ability of the multifractal spectrum to identify subsurface electrical complexity.
Literary Depictions of the Shoah as a Means of Familiarizing Primary School Pupils with Relevant Facts
Authors: Mašát Milan
Published: February 2025

The paper is devoted to contemporary artistic narratives in which the events of the Shoah are thematized. We are convinced that the selected publications intended for children, i.e. Red Ribbon, Francesco Tirelli´s Ice Cream Shop and Rywka´s Diary: The Writings of a Jewish Girl from the Lodz Ghetto, consist of an informative and formative function in addition to an aesthetic one. Through the interpretation of these publications, we show their potential in presenting facts that are connected to one line of events of the Second World War. The main benefit of narratives conceived in this way is that, based on narratives that are appropriate for children and are usually accompanied by impressive illustrations, these readers are introduced to facts in an interesting, engaging and holistically developing way. Mixing fiction and non-fiction in texts whose core is the event of the Holocaust is one of the basic functions of such oriented literature intended for children and youth. Through an aesthetic story, readers are introduced to the realities and various other facts of the Second World War period.
Health Risk Assessment of Date Palm Trees with Aerial Roots in Taiwan
Authors: Lin Cheng-Jung , Peng Bing-Syun , Cheng Cheng-Yi
Published: February 2025

This study assessed the health risks of date palms in Taiwan with aerial root growth using visual tree assessment and non-destructive testing. Key external defects included leaning and insect damage, while acoustic tomography confirmed internal structural variability but required accuracy improvements. Drilling resistance tests showed that healthy trees had the highest resistance near the bark, decreasing toward the center, while decayed trees exhibited significant amplitude reductions. The phenomenon of aerial root growth on the outer side of the trunk is presumed to be a growth response of the tree to adapt to environmental changes, while the distinct dark wood band between the decayed and sound wood in the cross-section is likely a result of wood variation. These findings highlight the need for comprehensive tree health assessments and provide a scientific basis for improved urban tree management and conservation.
Contemporary Review of Cardiovascular Computed Tomography in Coronary and Structural Heart Interventions
Authors: Hopkisson Olivia , Ibrahem Abdalazeem , Swinn Timothy , Dastidar Amardeep , Satti Zahir
Published: February 2025

Cardiovascular computed tomography (CT) enables a non-invasive assessment of a multitude of cardiac ailments notably coronary, structural and congenital heart diseases, as well as valvular disorders and cardiomyopathies. Technological advancement, including machine learning and generative artificial intelligence (AI), has revolutionized the application of cardiac CT not only as a diagnostic tool but also to guide interventions. CT-derived fractional flow reserve (FFRCT) enhanced the diagnostic accuracy of CT coronary angiography (CTCA) to detect obstructive coronary artery disease (CAD), determine plaque extension, volume and composition, quantify risk of Major Adverse Cardiovascular Events (MACE) and plan percutaneous coronary interventions (PCI) or Coronary Artery Bypass Grafting (CABG). Additionally, CTCA can provide scoring tools to improve procedural success, and minimize complications of complex coronary interventions, such as chronic total occlusion (CTO) interventions. Moreover, cardiac CT aids in pre-procedural planning and assessment of interventions like transcatheter aortic valve implantation (TAVI) and left atrial appendage occlusion (LAAO). Its ability to provide comprehensive anatomical and functional information makes it indispensable in guiding complex structural interventions and ensuring optimal patient outcomes. This review explores the evolving role of cardiac CT in coronary and structural heart disease interventions, highlighting its technological advancements, clinical applications, and future directions in cardiovascular care.
Determination of Susceptibility of Some Hybrid Grapevine Genotypes to Powdery Mildew
Authors: Bozkurt Abdurrahim , Yağci Adem , Akgül Davut Soner
Published: February 2025

The purpose of this study was to identify grape genotypes resistant to powdery mildew to reduce pesticide use in vineyards. A total of 70 hybrid genotypes from Narince x Regent and Narince Kishmish Vatkana crosses, along with four grape varieties (Narince, Regent, Kishmish Vatkana, and Isabella), were evaluated for their susceptibility to powdery mildew. Inoculations were carried out under controlled greenhouse and laboratory conditions between 2021 and 2022. The study assessed the severity of infection by measuring mycelium and sporulation density on the leaves. Results showed significant variation in susceptibility, with genotypes exhibiting differences in infection severity, ranging from resistant (Regent) to highly susceptible (Narince). Genotypes NRG-7, NRG-146, NRG-174, NRG-195, NRG-196, NRG-197, and NRG-200, as well as cultivars Regent, Kishmish Vatkana, and Isabella, showed resistance to the disease, while Narince was highly sensitive. These resistant genotypes have potential for use in organic farming, offering an opportunity to reduce fungicide applications and enhance sustainable viticulture practices.
Production Reliability Technology Based on Vacuum Infusion Process Convergence to Design Strengthen Boat Safety
Authors: Yoon Jong-Hwa , Yoon Dal-Hwan
Published: February 2025

In this paper, to reinforce the safety of boats, we develop a technology to improve the stability and quality of boat equipment manufacturing through vacuum infusion process fusion. Safe mold design and manufacture are performed to determine the resin flow rate and water surface flow of the boat, and the performance of vacuum maintenance work is guaranteed through the tensile and compressive strength of the manufactured hull and deck. When manufacturing a boat air mechanism (Aerostat), the adhesive strength between the materials of the equipment and the deformation of the joints are very important factors for safety. Process fusion to minimize a number of manual work processes due to the nature of the equipment manufacturing, minimiz-es deformation after manufacturing through an accurate manufacturing ratio. Accordingly, the mixing ratio of the resin and curing agent is accurately controlled as an optimal condition for drying and securing safety of the boat, and durability and quality are improved by analyzing working conditions such as resin flow and flowchart by time and converting optimal infor-mation into a databse. This enables efficient production process management with a small number of workers in multiple workplaces, which is expected to increase production efficiency and safety design.
Detailed Interface Composition of Graphitized Soot and Carbon T900: Reference Material for Atmospheric Studies
Authors: Rossi Michel J. , Ludwig Christian , Popovicheva Olga B.
Published: February 2025

Two graphitized thermal soot (GTS6, GTS80) and graphitized soot with a deposited overlayer of organic carboxylic acid (GTS80 impregnated with 1,2,4-benzenetricarboxylic acid (4.88 % (w/w) 1,2,4 BTCA)) have been investigated in a flowing gas experiment under molecular flow conditions in a Knudsen cell reactor. As a comparison commercial soot T900 has a significantly larger coverage of surface functional groups (SFG’s) than both GTS6 and GTS80 probed by NO2, O3, NH2OH, CF3COOH, HCl and N(CH3)3. NO2 (weak oxidizer) and O3 (strong oxidizer) probe oxidizable (or reduced) SFG’s, NH2OH interacts with surface –OH groups whereas CF3COOH, HCl and N(CH3)3 probe basic and acidic SFG’s because of their acidic and basic properties, respectively. The interface of GTS6 and GTS80 still retains a significant coverage of reduced sites probed using O3 to the extent of approximately 10 % of a monolayer (ML) compared to 46 % for T900. Using N(CH3)3 as a probe gas we established that BTCA-doped GTS80 is highly acidic having a -COOH group coverage of 51.7 ± 10.5 % of a ML. The use of NH2OH as a probe gas leads to a substantial increase in uptake upon coating GTS80 with BTCA owing to the weakly basic character of the probe interacting with the acidic monolayer. Less than 10 % of all basic sites are strong on BTCA-doped GTS80. The corresponding initial uptake coefficients or uptake probability of most of probe gases on T900 are significantly larger than both GTS, in line with the trends in coverage after saturating adsorption. For NO2 and O3 the steady-state (ss), that is long-term uptake or loss, is observed indicating a chemical reaction as opposed to mere (reversible) adsorption. The corresponding rate constant is 5·10-3 s-1 for all samples except for GTS6 where it is smaller by a factor of 8 which corresponds to the slowest uptake.
A First Calculation of Density of the Ether Based on the Variation of the Mass of Microparticles with the Magnitude of Their Velocity V in the Ether
Authors: Has Ioan , Miclaus Simona , Has Aurelian
Published: February 2025

We build on our previous results starting with the discovery of Errors 1 and 2 in Michelson's analysis of his 1881/87 interferometer experiments. By correcting these errors, it was possible to reintroduce the ether into physics by our model HM16, with a number of important consequences, including establishing the origin of the interaction between the submicroparticles (SMPs) as percussion forces created by the vibrations of the SMP transmitted through the fundamental vibrations of the ether. Therefore, the increase in the mass of the SMP by ms due to its speed v is physically constituted by the energy Es accumulated in the surrounding Ether driven by the displacement of the SMP. Here, we calculate the value of the density ρE of the ether surrounding the SMP on the basis of the equivalence between the additional mass ms created by the movement of the surrounding ET and the analogous increase by msL of the mass of the SMP on the basis of a Lorentz-type formula. The density ρE of the ether, resulting for the barium atom at v = 0.3c, yields a credible value of 1.748×10‒4 kg/m3. Previously, in none of the numerous models or theories about the Ether was the problem of Ether’s density resolved.
Treatment of Advanced NSCLC Patients with an Anti-Idiotypic NeuGcGM3-Based Vaccine: Immune Correlates in Long-Term Survivors
Authors: Mazorra Zaima , Cáceres-Lavernia Haslen H. , Neninger-Vinageras Elia , Varona-Rodríguez Leslie M. , Viada Carmen Elena , González Zuyen , Rodríguez-Zhurbenko Nely , Thierry Anne-Christine , Baumgaertner Petra , Trabanelli Sara , Jandus Camilla , Crombet Tania
Published: February 2025

Background: Racotumomab-alum is an anti-idiotype vaccine targeting the NeuGcGM3 tumor-associated ganglioside. Clinical trials in advanced cancer patients have demonstrated low toxicity, high immunogenicity and clinical benefit. The goal of this study was to identify circulating biomarkers of clinical outcome. Methods: Eighteen patients with stage IIIb/IV non-small-cell lung cancer (NSCLC) were injected with racotumomab-alum as switch maintenance therapy after first line chemotherapy. Treatment was administered until severe performance status worsening or toxicity. The frequencies of innate and adaptive lymphocytes were assessed by flow cytometry. Circulat ing factors were measured using multi-analyte flow assay kits. Results: The median overall survival was 16.5 months. Twenty-seven percent of patients were classified as long-term survivors. Patients with lower baseline frequencies of CD4+Tregs and central memory (CM) CD8+T cells displayed longer survival rates. Furthermore, higher baseline frequencies of NKT cells and a high CD8+T/CD4+Treg ratio were associated with longer survival. Interestingly, patients with significantly lower levels of effector memory (EM) CD8+T cells survived longer. The levels of NKT cells and terminal effector memory (EMRA) CD8+T cells were higher in long–term survivors in comparison with short-term survivors at post-immune samples. As expected, the ratio CD8+T/CD4+Tregs showed significantly higher values during treatment in patients with clinical benefits. Regarding serum factors, pro-tumorigenic cytokines significantly increased during treatment in poor survivors. Conclusions: In advanced NSCLC patients receiving racotumomab-alum vaccine, longer survival is associated with a unique profile of circulating lymphocyte subsets at baseline and during treatment. Additionally, certain protumor-related cytokines increased in short-term survivors. These results should be confirmed in larger clinical trials. This clinical trial was registered in Cuban Clinical Trials Register (RPCE00000279).
Prediction of Flexural Ultimate Capacity for Reinforced UHPC Beams Using Ensemble Learning and SHAP Method
Authors: Zhang Zhe , Zhou Xuemei , Zhu Ping , Li Zhaochao , Wang Yichuan
Published: February 2025

Ensemble learning (EL) models are designed to enhance the accuracy and efficiency in predicting the flexural ultimate capacity of reinforced ultra-high-performance concrete (UHPC) beams with aim to provide more reliable and efficient design experience for structural applications in this study. For model training and testing, a comprehensive database is initially established for flexural ultimate capacity of reinforced UHPC beams, composed of 339 UHPC-based specimens with varying design parameters compiled from 56 published experimental investigations. Furthermore, multiple machine learning (ML) algorithms, including both traditional and EL models, are employed to develop optimized predictive models for the flexural ultimate capacity of reinforced UHPC specimens derived from the established database. Four statistical indicators of model performance are utilized to assess the accuracies of the prediction results with ML models used. Subsequently, a highly efficient evaluation of ML models is taken by analyzing the sensitivity of ML models to varying data subsets. Finally, a Shapley Additive Explanations (SHAP) method is employed to interpret several EL models, thereby substantiating their reliability and determining the extent of influence exerted by each feature on the prediction results. The present ML models predict accurately the flexural ultimate capacity Mu of reinforced UHPC beams after optimization, with EL models providing a higher level of accuracy than the traditional ML models. The present study also underscores the significant impact of the database division ratios of training-to-testing set on the effectiveness of performance prediction for the ML models. The optimal model functionality may be accomplished by properly considering the effects of database subset distribution on the performance prediction and model stability. The CatBoost model demonstrates superior performance in terms of predictive accuracy, as evidenced by its highest R² value, the lowest RMSE value, lowest MAE value, and lowest MAPE value. This substantial improvement in performance prediction of flexural capacity for reinforced UHPC beams is notable when compared to existing empirical methods. The CatBoost model displays a more uniform distribution of SHAP values for all parameters, suggesting a balanced decision-making process and contributing to its superior and stable model performance. The current study identifies a significant positive relationship between the increases in height, and reinforcement ratio of steel rebars and the growth in normalized SHAP values. These findings contribute to a deeper understanding of the role played by each feature in the prediction of flexural ultimate capacity of reinforced UHPC beams, thereby providing a foundation for more accurate model optimization and for a more refined feature section strategy.
Analysis of Lightning Climatology for Central Europe
Authors: Müller Richard , Döpp Sophie
Published: February 2025

A lightning climatology covering 16 years based on ground measurements is presented and discussed. Instead of the lightning density, the focus lies on the analysis and interpretation of mean Amperages per thunderstorm. This enables to identify regions with a particularly high risk of strong thunderstorms. In autumn the Nort-Sea and the Po valley is characterized by few but very strong thunderstorms. During the convective the number density of thunderstorms increases significantly over land. The Alpine region is by far most affected by strong thunderstorms, whereby the severity of the thunderstorms is on average much higher in the southern (Po Valley) than in the northern foothils. Also some regions along the western and eastern border of Germany are on average affected by very strong thunderstorms. The patterns form some sort of a U-shape, which results from the lifting of incoming moist air from the west or east by the orography. The analysis reveals that the mean amperage could be a good candidate for the estimation of risks induced by strong hail events.
From Crisis to Algorithm: Credit Delinquency Prediction in Peru Under Critical External Factors Using Machine Learning
Authors: Noriega Jomark , Herrera José , Rivera Luis , Castañeda Jorge
Published: February 2025

The integration of external risk factors (EF) has become increasingly vital for robust credit risk assessment, particularly in emerging economies subject to compounded disruptions. This paper presents a comprehensive, scenario-based methodology for incorporating EF—including pandemic variables (COVID-19 mortality and positive cases), climate anomalies (temperature, road blockages), and social unrest—into machine learning (ML) models. We employ an adapted CRISP-DM workflow, testing stationarity (via Dickey-Fuller), causality (via Granger), and model performance (via AUC and ACC) under scenarios with and without government-backed guarantees. Post-hoc explainability techniques (SHAP, LIME) further reveal which features drive delinquency predictions in EF-enriched contexts. Empirical results, derived from over 8.2 million Peruvian credit records (January 2020–September 2023), confirm that EF integration significantly improves predictive accuracy. Time-lagged mortality (COVID MOV) emerges as the strongest single predictor, while combined crises (pandemic, climate, social unrest) amplify delinquency risk. Models such as XGB, CNN, and XNN exhibit the highest adaptability, consistently attaining statistical significance across different partitions of economic activities. Beyond enhancing model accuracy, EF inclusion highlights key drivers—borrower income stability, debt management, EF severity—thereby supporting more transparent, proactive strategies for financial institutions aiming to mitigate credit defaults in volatile, multi-factor environments.
Learning Self-Supervised Representations of Powder-Diffraction Patterns
Authors: Das Shubhayu , Vorholt Markus , Houben Andreas , Dronskowski Richard
Published: February 2025

The potential of machine learning (ML) models for predicting crystallographic symmetry information from single-phase powder X-ray diffraction (XRD) patterns is investigated. Given the scarcity of large, labeled experimental datasets, we train our models using simulated XRD patterns generated from crystallographic databases. A key challenge in developing reliable diffraction-based structure-solution tools lies in the limited availability of training data and the presence of natural adversarial examples, which hinder model generalization. To address these issues, we explore multiple training pipelines and testing strategies, including evaluations on experimental XRD data. We introduce a contrastive representation learning approach that significantly outperforms previous supervised learning models in terms of robustness and generalizability, demonstrating improved invariance to experimental effects. These results highlight the potential of self-supervised learning in advancing ML-driven crystallographic analysis.
Race is a Social and Biological Construct
Authors: Johnson Brian
Published: February 2025

The idea that race is a purely social construct appears to have achieved almost universal acceptance within academia. However, this consensus is artificial and maintained by a taboo on the subject of race, particularly in the biological sciences. Here, I argue that the common-sense view that race has a biological basis but is unimportant for traits such as intelligence or character best fits the scientific data. I start by showing that most past biological discussions of race have focused on the wrong concepts. Specifically, population structure at the genomic level is irrelevant to most notions of race, which stress functional differences in a handful of traits. I therefore argue that the concept of ecotype, which is associated with local adaptation of a handful of traits in a highly connected network of populations, is the best descriptor of human races. I then explain the relationship between the social construction of race and its biological basis. The essential point here is that race is socially constructed from real biological variation. I conclude with a brief discussion of scientific racism, which I argue is better labeled pseudoscientific racism. I posit that stifling discussion of race by biologists has been counterproductive and misguided. When scientists refuse to refute the racist spin doctoring of biological data that is central to scientific racism, it gives the public the notion that the data are not on their side. Moreover, ideologically driven positions, such as races do not exist, erode public confidence in the scientific community.
SARS-CoV-2 mRNA Vaccines Induce Cross-Reactive Antibodies to NL63 Coronavirus but do not Boost Pre-Existing Immunity Anti-NL63 Antibody Responses
Authors: Weiyi Tang , Zi Wei Chang , Yun Shan Goh , Yong Jie Tan , Pei Xiang Hor , Chiew Yee Loh , David Lye C , Barnaby Young E , Lisa Ng FP , Matthew Tay Zirui , Laurent Renia
Published: February 2025

MRNA vaccines have been shown to provide strong immune responses against SARS-CoV-2, but the extent of their antibody cross-reactivity against human seasonal coronaviruses, such as NL63, remains unclear. Furthermore, it is unknown whether pre-existing antibody responses against NL63 might affect the outcome of SARS-CoV-2 mRNA vaccination. This study used a flow cytometry-based serological assay and an in vitro neutralization assay to analyze NL63 antibody responses in sera from SARS-CoV-2 mRNA-vaccinated mice and plasma samples from a vaccinated human cohort. We found that the Moderna mRNA-1273 vaccine can generate cross-reactive antibodies against NL63. Importantly, SARS-CoV-2 mRNA vaccination did not boost pre-existing anti-NL63 responses in humans, and pre-existing NL63 antibody levels did not affect the antibody response induced by SARS-CoV-2 mRNA vaccination. These findings suggest that while SARS-CoV-2 mRNA vaccination can induce cross-reactive antibodies against NL63, pre-existing immunity to this seasonal coronavirus does not appear to significantly impact the effectiveness of the vaccine. This contributes to our understanding of the complex interplay between pre-existing immunity to seasonal coronaviruses and the immune response generated by SARS-CoV-2 mRNA vaccines.
Modifications of Polymer Composites in the Era of the COVID-19 Pandemic
Authors: Witko Tomasz , Kucia Malgorzata , Tataruch Kinga , Mazur Karolina Ewelina
Published: February 2025

The COVID-19 pandemic significantly impacted material sciences, particularly polymer composites, which played a crucial role in personal protective equipment (PPE), medical devices, and packaging. This study explores the modifications and advancements in polymer materials developed to meet the urgent demands of the pandemic. Key innovations include enhanced filtration efficiency in PPE, integration of antimicrobial nanoparticles, and the development of biopolymer alternatives to address environmental concerns. The incorporation of silver, copper oxide, zinc oxide, and titanium dioxide nanoparticles improved antiviral and antibacterial properties, while polymer modifications enhanced durability, thermal resistance, and recyclability. Additionally, research into biodegradable polymers such as polylactic acid (PLA) and polyhydroxyalkanoates (PHAs) gained momentum as sustainable alternatives to fossil-based plastics. The findings underscore the necessity of material innovation during global crises and highlight the future potential of modified polymer composites in healthcare and environmental sustainability.
Adicción a Internet y ciberbullying en alumnado español de Formación Profesional
Authors: Gallego-Jiménez M Gloria , Rodríguez Otero Luis Manuel
Published: February 2025

Introducción. La incursión de internet ha generado un nuevo contexto de socialización y materialización del bullying. La adicción a internet refiere a la incapacidad para no utilizar o poner límites al uso de internet, a través de la pérdida de control ante su uso y dependencia. Método. Se planteó una investigación, a través de un diseño no experimental, descriptivo-correlacional, con el objetivo de analizar la relación existente entre la adicción a internet y el ciberbullying en el alumnado español de Formación Profesional. Se utilizó un muestreo no probabilístico por conveniencia para seleccionar una muestra de 1.070 estudiantes de 13 centros educativos de 6 Comunidades Autónomas de España de diferentes áreas. Se aplicó un cuestionario autoadministrado, construido a partir de la escala Likert para evaluar la adicción a internet y el European Cyberbullying Intervention Project Questionnaire. Para el análisis de los datos se realizaron análisis paramétricos y se calculó el coeficiente de correlación de Pearson entre las escalas aplicadas. Resultados. Los resultados mostraron que los niveles de adicción a internet son altos y los de ciberbullying medios; asimismo, se identificó una correlación positiva entre ambas escalas. Conclusiones. El Desarrollo de habilidades emocionales y sociales pueden aparecer como factores protectores para prevenir tanto la adicción a internet como la ciberviolencia.
Intervenciones basadas en mindfulness y su efecto en la salud mental del adulto mayor: Revisión sistemática
Authors: Barajas Martínez Héctor Alejandro , Salazar-Moreno Carlos Alberto , Mejía Mejía Yadira , Jiménez-Padilla Benito Israel , Flores-Garza Paola Lizeth , Vargas Beltrán Mariana
Published: February 2025

Introducción. La población mundial experimenta un amento de Personas Adultas Mayores (PAM) de un 12% a un 22% para el año, 2050. Se observa un incremento de las enfermedades de salud mental, tales como la depresión, ansiedad y estrés en este grupo poblacional. Objetivo. Conocer las técnicas basadas en Mindfulness y sus efectos en la salud mental de la PAM. Método. Realizado a través de la Prefered Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA); Se incluyeron ensayos clínicos aleatorizados y no aleatorizados con aplicación de técnicas basadas en Mindfulness que tuvieran un efecto en la salud mental; búsqueda realizada en las bases de datos: MedLine/PubMed, Wiley, Science Direct, Biblioteca Virtual de Salud (BVS) y otras; evaluación del riesgo de sesgo conforme a los lineamientos de Cochrane. Resultados. Se incluyeron 13 artículos en donde se encontró que las técnicas basadas en Mindfulness tienen un efecto positivo en la salud mental de la PAM, donde la técnica de Reducción de Estrés Basada en Mindfulness MBSR fue la más empleada. Conclusiones. Se recomienda el uso de técnicas basadas en Mindfulness como una opción con fundamento científico y de bajo costo para mejorar la salud mental de la PAM.
Adicción a redes sociales y procrastinación académica en estudiantes universitarios de Lima
Authors: Lunahuana Rosales Manuel Alexander
Published: February 2025

Introducción. El uso de redes sociales en el Perú incrementó considerablemente a partir del confinamiento social por la Covid-19 y trajo consigo un riesgo de adicción a ellas. El problema de la adicción a redes sociales y la procrastinación académica se encuentran hoy perjudicando principalmente a los universitarios. Objetivo. Analizar la relación entre la adicción a redes sociales y la procrastinación académica de un grupo de universitarios limeños. Método. Estudio cuantitativo, transversal de diseño correlacional encuestó a un total de 223 universitarios. Se utilizaron dos instrumentos que evalúan la adicción a redes sociales y dos instrumentos para evaluar la procrastinación académica. Resultados. Los resultados mostraron una relación positiva y de magnitud moderada entre los niveles de adicción a redes sociales y la procrastinación académica (r= .49; p<0.010) y un modelo de regresión múltiple evidenció que la adicción a redes sociales ejerció un efecto significativo sobre la procrastinación académica explicando el 26.4% de su varianza. Conclusiones. Los niveles de adicción a redes sociales y procrastinación de los universitarios limeños del estudio evidencian una clara relación positiva. Además, la adicción a redes sociales ejerce un efecto significativo sobre la procrastinación académica tomando en cuenta como variables de control al sexo, las horas de uso de redes sociales y las horas de estudio.
Sea lamprey display context-dependent attraction to specific types of turbulence within a laboratory flume
Authors: Dennis Clark E. , Ranjan Pallav , Suski Cory , Tinoco Rafael
Published: February 2025

The development of stimuli to guide fish can both conserve native species and prevent the spread of invasive species. The manipulation of hydrodynamic features (e.g., velocity, turbulence intensity, eddy size and orientation) is a promising stimulus that can either attract or repel fishes. Management of anguilliform fishes, such as eels and lamprey, could benefit from strategies that direct upstream-swimming behavior to targeted areas, however the hydrological cues that either attract or repel anguilliform fishes have not been identified. Our study sought to define whether features of turbulent flow (specific velocity, turbulent kinetic energy or eddy time scale) could attract or repel upstream-swimming Great Lakes sea lamprey (Petromyzon marinus) for the purposes of redirection. We used a two-choice laboratory flume outfitted with structures of varying sizes and orientations to generate different turbulent environments, and quantified the preference for each feature by upstream swimming Great Lakes sea lamprey. Data showed that sea lamprey choices are not based on preference for a single, specific velocity, turbulent kinetic energy or eddy time scale. Rather, lamprey have context-dependent attraction to the turbulent features generated, showing a complex decision framework dependent on competing flow conditions. Results can be used to enhance trap efficiency for upstream migrating Great Lakes sea lamprey.
Percutaneous Stenting for Superior Vena Cava Stenosis Following Surgical Repair of Congenital Heart Defects: A Two-Case Report
Authors: Papadopoulos Georgios E. , Ninios Ilias , Evangelou Sotirios , Ioannides Andreas , Ninios Vlasis
Published: February 2025

Background: Superior vena cava (SVC) stenosis is a rare but serious complication following surgical repair of congenital heart defects, often resulting in significant venous congestion, facial and upper extremity swelling, increased venous pressures, and impaired hemodynamics. Surgical re-intervention carries substantial risks, whereas percutaneous stenting offers a minimally invasive and effective alternative.
Case presentation: We present two cases of symptomatic SVC stenosis following congenital heart defect repair. Both patients underwent detailed imaging with cardiac MRI and CT angiography, confirming severe SVC stenosis. Percutaneous intervention was performed using self-expanding Wallstents deployed under fluoroscopic guidance, with tailored post-dilation strategies to optimize luminal expansion. Immediate symptomatic relief was achieved in both cases, with complete resolution of venous congestion. Post-procedure anticoagulation included warfarin for six months, followed by long-term aspirin therapy. Follow-up imaging demonstrated sustained stent patency without restenosis or thrombosis.
Conclusion: These cases highlight percutaneous stenting as a viable and effective approach for managing post-surgical SVC stenosis, offering a safe alternative to surgical re-intervention. Future research should focus on optimizing stent designs and post-procedural management strategies to further improve patient outcomes.