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This article explores how Japanese anime has become a space of theological imagination, where viewers encounter the divine not as fixed dogma but as a lived process. Through symbolic analysis of five spiritually resonant anime series: Puella Magi Madoka Magica, To Your Eternity, Sunday Without God, Code Geass, and The Promised Neverland, the study examines how characters such as Madoka, Fushi, Ai, Lelouch, Emma, and Mujika embody a form of theosis that unfolds through memory, sacrifice, refusal, and care. Rather than representing God as omnipotent or remote, these narratives invite a vision of the divine as vulnerable, suffering, and becoming, emerging through grief, relationships, and transformations. Drawing on theological and philosophical frameworks, especially process theology and symbolic interpretation, the article argues that anime collapses the traditional boundaries between theology and philosophy by embodying both in story. In these narrative worlds, divinity is not merely represented, it is approached, co-created, and remembered. The sacred is not a theory to master, but an encounter to undergo. Anime, thus, does not offer theology as a system but rather theology as a journey: a reenchanted vision of the world where God is still becoming. Full article

(This article belongs to the Special Issue Between Philosophy and Theology: Liminal and Contested Issues)

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21 pages, 4762 KiB

Open AccessArticle

Directed Energy Deposition: A Scientometric Study and Its Practical Implications

by Mehran Ghasempour-Mouziraji, Daniel Afonso, Behrouz Nemati and Ricardo Alves de Sousa

Metrics 2025, 2(3), 14; https://doi.org/10.3390/metrics2030014 - 5 Aug 2025

Abstract

Directed Energy Deposition is an additive manufacturing subgroup that uses a laser beam to melt the wire or powder to create a melt pool. In the current study, a scientometric analysis has been carried out to analyze the contribution of countries, publication type analysis, distribution of publications over the years, keywords analysis, author analysis, cited journal, categories, institutes of publication, and report the practical implications. Firstly, the database was extracted from the Web of Science and then post-processed with CiteSpace 6.2.R4 and VOSviewer 1.6.20 software. Afterward, the associated results had been extracted and reported. It was found that China is the leader according to publication, followed by the USA and Germany, which mostly published their achievements in article and proceeding paper formats, which are increasing annually. According to the keywords, additive manufacturing, Laser Metal Deposition, and fabrication are the most commonly used. Based on the CiteSapce and VOSviewer results, Lin, Xin and Huang, Weidong are the authors with the highest publication rates. In addition, Additive Manufacturing, Materials & Design, and Materials Science and Engineering: A are the most cited journals, and regarding the categories, materials science, multidisciplinary, applied physics, and manufacturing engineering are the most commonly used DED processes. Northwestern Polytechnical University, Fraunhofer Gesellschaft, and the United States Department of Energy (DOE) have performed the most research in the field of DED. Full article

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28 pages, 11519 KiB

Open AccessArticle

Identifying Sustainable Offshore Wind Farm Sites in Greece Under Climate Change

by Vasiliki I. Chalastani, Elissavet Feloni, Carlos M. Duarte and Vasiliki K. Tsoukala

J. Mar. Sci. Eng. 2025, 13(8), 1508; https://doi.org/10.3390/jmse13081508 - 5 Aug 2025

Abstract

Wind power has gained attention as a vital renewable energy source capable of reducing emissions and serving as an effective alternative to fossil fuels. Floating wind farms could significantly enhance the energy capacities of Mediterranean countries. However, location selection for offshore wind farms (OWFs) is a challenge for renewable energy policy and marine spatial planning (MSP). To address these issues, this study considers the marine space of Greece to propose a GIS-based multi-criteria decision-making (MCDM) framework employing the Analytic Hierarchy Process (AHP) to identify suitable sites for OWFs. The approach assesses 19 exclusion criteria encompassing legislative, environmental, safety, and technical constraints to determine the eligible areas. Subsequently, 10 evaluation criteria are weighted to determine the selected areas’ level of suitability. The study considers baseline conditions (1981–2010) and future climate scenarios based on RCP 4.5 and RCP 8.5 for two horizons (2011–2040 and 2041–2070), integrating projected wind velocities and sea level rise to evaluate potential shifts in suitable areas. Results indicate the central and southeastern Aegean Sea as the most suitable areas for OWF deployment. Climate projections indicate a modest increase in suitable areas. The findings serve as input for climate-resilient MSP seeking to promote sustainable energy development. Full article

(This article belongs to the Section Marine Energy)

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34 pages, 2291 KiB

Open AccessArticle

A Study of Periodicities in a One-Dimensional Piecewise Smooth Discontinuous Map

by Rajanikant A. Metri, Bhooshan Rajpathak, Kethavath Raghavendra Naik and Mohan Lal Kolhe

Mathematics 2025, 13(15), 2518; https://doi.org/10.3390/math13152518 - 5 Aug 2025

Abstract

In this study, we investigate the nonlinear dynamical behavior of a one-dimensional linear piecewise-smooth discontinuous (LPSD) map with a negative slope, motivated by its occurrence in systems exhibiting discontinuities, such as power electronic converters. The objective of the proposed research is to develop an analytical approach. Analytical conditions are derived for the existence of stable period-1 and period-2 orbits within the third quadrant of the parameter space defined by slope coefficients

a < 0

and

b < 0

. The coexistence of multiple attractors is demonstrated. We also show that a novel class of orbits exists in which both points lie entirely in either the left or right domain. These orbits are shown to eventually exhibit periodic behavior, and a closed-form expression is derived to compute the number of iterations required for a trajectory to converge to such orbits. This method also enhances the ease of analyzing system stability by mapping the state–variable dynamics using a non-smooth discontinuous map. The analytical findings are validated using bifurcation diagrams, cobweb plots, and basin of attraction visualizations. Full article

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18 pages, 3033 KiB

Open AccessArticle

Mathematical Modelling of Upper Room UVGI in UFAD Systems for Enhanced Energy Efficiency and Airborne Disease Control: Applications for COVID-19 and Tuberculosis

by Mohamad Kanaan, Eddie Gazo-Hanna and Semaan Amine

Math. Comput. Appl. 2025, 30(4), 85; https://doi.org/10.3390/mca30040085 (registering DOI) - 5 Aug 2025

Abstract

This study is the first to investigate the performance of ultraviolet germicidal irradiation (UVGI) in underfloor air distribution (UFAD) systems. A simplified mathematical model is developed to predict airborne pathogen transport and inactivation by upper room UVGI in UFAD spaces. The proposed model is substantiated for the SARS-CoV-2 virus as a simulated pathogen through a comprehensive computational fluid dynamics methodology validated against published experimental data of upper room UVGI and UFAD flows. Simulations show an 11% decrease in viral concentration within the upper irradiated zone when a 15 W louvered germicidal lamp is utilized. Finally, a case study on Mycobacterium tuberculosis (M. tuberculosis) bacteria is carried out using the validated simplified model to optimize the use of return air and UVGI implementation, ensuring acceptable indoor air quality and enhanced energy efficiency. Results reveal that the UFAD-UVGI system may consume up to 13.6% less energy while keeping the occupants at acceptable levels of M. tuberculosis concentration and UV irradiance when operated with 26% return air and a UVGI output of 72 W. Full article

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23 pages, 85184 KiB

Open AccessArticle

MB-MSTFNet: A Multi-Band Spatio-Temporal Attention Network for EEG Sensor-Based Emotion Recognition

by Cheng Fang, Sitong Liu and Bing Gao

Sensors 2025, 25(15), 4819; https://doi.org/10.3390/s25154819 - 5 Aug 2025

Abstract

Emotion analysis based on electroencephalogram (EEG) sensors is pivotal for human–machine interaction yet faces key challenges in spatio-temporal feature fusion and cross-band and brain-region integration from multi-channel sensor-derived signals. This paper proposes MB-MSTFNet, a novel framework for EEG emotion recognition. The model constructs a 3D tensor to encode band–space–time correlations of sensor data, explicitly modeling frequency-domain dynamics and spatial distributions of EEG sensors across brain regions. A multi-scale CNN-Inception module extracts hierarchical spatial features via diverse convolutional kernels and pooling operations, capturing localized sensor activations and global brain network interactions. Bi-directional GRUs (BiGRUs) model temporal dependencies in sensor time-series, adept at capturing long-range dynamic patterns. Multi-head self-attention highlights critical time windows and brain regions by assigning adaptive weights to relevant sensor channels, suppressing noise from non-contributory electrodes. Experiments on the DEAP dataset, containing multi-channel EEG sensor recordings, show that MB-MSTFNet achieves 96.80 ± 0.92% valence accuracy, 98.02 ± 0.76% arousal accuracy for binary classification tasks, and 92.85 ± 1.45% accuracy for four-class classification. Ablation studies validate that feature fusion, bidirectional temporal modeling, and multi-scale mechanisms significantly enhance performance by improving feature complementarity. This sensor-driven framework advances affective computing by integrating spatio-temporal dynamics and multi-band interactions of EEG sensor signals, enabling efficient real-time emotion recognition. Full article

(This article belongs to the Section Intelligent Sensors)

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13 pages, 1028 KiB

Open AccessArticle

Survival and Prognostic Factors in Unresectable Head and Neck Cancer Patients

by Natsuki Oishi, Sara Orozco-Núñez, José Ramón Alba-García, Mar Gimeno-Coret and Enrique Zapater

J. Clin. Med. 2025, 14(15), 5517; https://doi.org/10.3390/jcm14155517 - 5 Aug 2025

Abstract

Background/Objectives: This single-cohort follow-up study describes the median overall survival (OS) in patients with unresectable head and neck squamous cell carcinoma (HNSCC) due to invasion of vital structures, which is under-represented in the current literature. Secondarily, subgroups were evaluated according to the type of presentation, in order to identify clinical characteristics and contribute to developing an appropriate treatment plan and managing patient’s expectations. Methods: This single-cohort observational study analysed the OS of 39 patients from the Otolaryngology Department with advanced-stage head and neck cancer with invasion of vital anatomical structures considered ineligible for surgical treatment. Secondarily, subgroups were evaluated according to type of presentation and various clinical characteristics. Results: A total of 39 patients radiologically classified as having unresectable HNSCC (i.e., unsuitable for surgical resection), with a mean age of 66.87 years, were included during a 24-month follow-up. By the end of the study, 56.4% of the patients had died. The median OS was 16.09 months. Statistically significant differences were observed when comparing human papilloma virus (HPV)-positive and -negative status and when comparing initial and recurrent tumours. Conclusions: The invasion of anatomical structures such as the skull base, internal carotid artery, and prevertebral space was associated with a marked decrease in survival, with an OS time of 16 months. This study provides valuable evidence in patients with unresectable HNSCC, highlighting tumour recurrence and HPV-negative status as important indicators of poor prognosis. Full article

(This article belongs to the Section Otolaryngology)

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Graphical abstract

14 pages, 3486 KiB

Open AccessArticle

Spatiotemporal Activity Patterns of Sympatric Rodents and Their Predators in a Temperate Desert-Steppe Ecosystem

by Caibo Wei, Yijie Ma, Yuquan Fan, Xiaoliang Zhi and Limin Hua

Animals 2025, 15(15), 2290; https://doi.org/10.3390/ani15152290 - 5 Aug 2025

Abstract

Understanding how prey and predator species partition activity patterns across time and space is essential for elucidating behavioral adaptation and ecological coexistence. In this study, we examined the diel and seasonal activity rhythms of two sympatric rodent species—Rhombomys opimus (Great gerbil) and Meriones meridianus (Midday gerbil)—and their primary predators, Otocolobus manul (Pallas’s cat) and Vulpes vulpes (Red fox), in a desert-steppe ecosystem on the northern slopes of the Qilian Mountains, China. Using over 8000 camera trap days and kernel density estimation, we quantified their activity intensity and spatiotemporal overlap. The two rodent species showed clear temporal niche differentiation but differed in their synchrony with predators. R. opimus exhibited a unimodal diurnal rhythm with spring activity peaks, while M. meridianus showed stable nocturnal activity with a distinct autumn peak. Notably, O. manul adjusted its activity pattern to partially align with that of R. opimus, whereas V. vulpes maintained a crepuscular–nocturnal rhythm overlapping more closely with that of M. meridianus. Despite distinct temporal rhythms, both rodent species shared high spatial overlap with their predators (overlap index OI = 0.64–0.83). These findings suggest that temporal partitioning may reduce predation risk for R. opimus, while M. meridianus co-occurs more extensively with its predators. Our results highlight the ecological role of native carnivores in rodent population dynamics and support their potential use in biodiversity-friendly rodent management strategies under arid grassland conditions. Full article

(This article belongs to the Section Ecology and Conservation)

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15 pages, 4422 KiB

Open AccessArticle

Advanced Deep Learning Methods to Generate and Discriminate Fake Images of Egyptian Monuments

by Daniyah Alaswad and Mohamed A. Zohdy

Appl. Sci. 2025, 15(15), 8670; https://doi.org/10.3390/app15158670 (registering DOI) - 5 Aug 2025

Abstract

Artificial intelligence technologies, particularly machine learning and computer vision, are being increasingly utilized to preserve, restore, and create immersive virtual experiences with cultural artifacts and sites, thus aiding in conserving cultural heritage and making it accessible to a global audience. This paper examines the performance of Generative Adversarial Networks (GAN), especially Style-Based Generator Architecture (StyleGAN), as a deep learning approach for producing realistic images of Egyptian monuments. We used Sigmoid loss for Language–Image Pre-training (SigLIP) as a unique image–text alignment system to guide monument generation through semantic elements. We also studied truncation methods to regulate the generated image noise and identify the most effective parameter settings based on architectural representation versus diverse output creation. An improved discriminator design that combined noise addition with squeeze-and-excitation blocks and a modified MinibatchStdLayer produced 27.5% better Fréchet Inception Distance performance than the original discriminator models. Moreover, differential evolution for latent-space optimization reduced alignment mistakes during specific monument construction tasks by about 15%. We checked a wide range of truncation values from 0.1 to 1.0 and found that somewhere between 0.4 and 0.7 was the best range because it allowed for good accuracy while retaining many different architectural elements. Our findings indicate that specific model optimization strategies produce superior outcomes by creating better-quality and historically correct representations of diverse Egyptian monuments. Thus, the developed technology may be instrumental in generating educational and archaeological visualization assets while adding virtual tourism capabilities. Full article

(This article belongs to the Special Issue Novel Applications of Machine Learning and Bayesian Optimization)

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18 pages, 2839 KiB

Open AccessArticle

Detection of Maize Pathogenic Fungal Spores Based on Deep Learning

by Yijie Ren, Ying Xu, Huilin Tian, Qian Zhang, Mingxiu Yang, Rongsheng Zhu, Dawei Xin, Qingshan Chen, Qiaorong Wei and Shuang Song

Agriculture 2025, 15(15), 1689; https://doi.org/10.3390/agriculture15151689 - 5 Aug 2025

Abstract

Timely detection of pathogen spores is fundamental to ensuring early intervention and reducing the spread of corn diseases, like northern corn leaf blight, corn head smut, and corn rust. Traditional spore detection methods struggle to identify spore-level targets within complex backgrounds. To improve the recognition accuracy of various maize disease spores, this study introduced the YOLOv8s-SPM model by incorporating the space-to-depth and convolution (SPD-Conv) layers, the Partial Self-Attention (PSA) mechanism, and Minimum Point Distance Intersection over Union (MPDIoU) loss function. First, we combined SPD-Conv layers into the Backbone of the YOLOv8s to enhance recognition performance on small targets and low-resolution images. To improve computational efficiency, the PSA mechanism was incorporated within the Neck layer of the network. Finally, MPDIoU loss function was applied to refine the localization performance of bounding boxes. The results revealed that the YOLOv8s-SPM model achieved 98.9% accuracy on the mixed spore dataset. Relative to the baseline YOLOv8s, the YOLOv8s-SPM model yielded a 1.4% gain in accuracy. The improved model significantly improved spore detection accuracy and demonstrated superior performance in recognizing diverse spore types under complex background conditions. It met the demands for high-precision spore detection and filled a gap in intelligent spore recognition for maize, offering an effective starting point and practical path for future research in this field. Full article

(This article belongs to the Section Crop Protection, Diseases, Pests and Weeds)

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21 pages, 3570 KiB

Open AccessArticle

Performance Studies on a Scaled Model of Dual Oscillating-Buoys WEC with One Pneumatic PTO

by Peiyu Liu, Xiang Rao, Bijun Wu, Zhiwen Yuan and Fuming Zhang

Energies 2025, 18(15), 4151; https://doi.org/10.3390/en18154151 - 5 Aug 2025

Abstract

A hybrid wave energy conversion (WEC) system, integrating a backward bent duct buoy (BBDB) with an oscillating buoy (OB) via a flexible mooring chain, is introduced in this study. Unlike existing hybrid WECs, the proposed system dispenses with rigid mechanical linkages and enables flexible offshore deployment. Flared BBDB and buoy models with spherical, cylindrical, and semi-capsule shapes are designed and tested experimentally in a wave flume using both regular and irregular wave conditions. The effects of nozzle ratio (NR), coupling distance, buoy draft, and buoy geometry are systematically examined to investigate the hydrodynamic performance and energy conversion characteristics. It is found that NR at 110 under unidirectional airflow produces an optimal balance between pressure response, free surface displacement, and energy conversion efficiency. Energy extraction is significantly influenced by the coupling distance, with the hybrid system achieving maximum performance at a specific normalized spacing. The semi-capsule buoy improves power extraction ability and expands effective bandwidth due to asymmetric shape and coupled motion. These findings provide valuable insights into the coupling mechanism and geometric optimization for hybrid WECs. Full article

(This article belongs to the Special Issue Advances in Marine Renewable Energy Utilization and Offshore Storage Technologies)

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23 pages, 5064 KiB

Open AccessArticle

Study on Reasonable Well Spacing for Geothermal Development of Sandstone Geothermal Reservoir—A Case Study of Dezhou, Shandong Province, China

by Shuai Liu, Yan Yan, Lanxin Zhang, Weihua Song, Ying Feng, Guanhong Feng and Jingpeng Chen

Energies 2025, 18(15), 4149; https://doi.org/10.3390/en18154149 - 5 Aug 2025

Abstract

Shandong Province is rich in geothermal resources, mainly stored in sandstone reservoirs. The setting of reasonable well spacing in the early stage of large-scale recharge has not attracted enough attention. The problem of small well spacing in geothermal engineering is particularly prominent in the sandstone thermal reservoir production area represented by Dezhou. Based on the measured data of temperature, flow, and water level, this paper constructs a typical engineering numerical model by using TOUGH2 software. It is found that when the distance between production and recharge wells is 180 m, the amount of production and recharge is 60 m³/h, and the temperature of reinjection is 30 °C, the temperature of the production well will decrease rapidly after 10 years of production and recharge. In order to solve the problem of thermal breakthrough, three optimization schemes are assumed: reducing the reinjection temperature to reduce the amount of re-injection when the amount of heat is the same, reducing the amount of production and injection when the temperature of production and injection is constant, and stopping production after the temperature of the production well decreases. However, the results show that the three schemes cannot solve the problem of thermal breakthrough or meet production demand. Therefore, it is necessary to set reasonable well spacing. Therefore, based on the strata near the Hydrological Homeland in Decheng District, the reasonable spacing of production and recharge wells is achieved by numerical simulation. Under a volumetric flux scenario ranging from 60 to 80 m³/h, the well spacing should exceed 400 m. For a volumetric flux between 80 and 140 m³/h, it is recommended that the well spacing be greater than 600 m. Full article

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16 pages, 343 KiB

Open AccessArticle

Structured Distance to Normality of Dirichlet–Neumann Tridiagonal Toeplitz Matrices

by Zhaolin Jiang, Hongxiao Chu, Qiaoyun Miao and Ziwu Jiang

Axioms 2025, 14(8), 609; https://doi.org/10.3390/axioms14080609 - 5 Aug 2025

Abstract

This paper conducts a rigorous study on the spectral properties and operator-space distances of perturbed Dirichlet–Neumann tridiagonal (PDNT) Toeplitz matrices, with emphasis on their asymptotic behaviors. We establish explicit closed-form solutions for the eigenvalues and associated eigenvectors, highlighting their fundamental importance for characterizing matrix stability in the presence of perturbations. By exploiting the structural characteristics of PDNT Toeplitz matrices, we obtain closed-form expressions quantifying the distance to normality, the deviation from normality. Full article

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21 pages, 9017 KiB

Open AccessReview

Sentence-Level Insights from the Martian Literature: A Natural Language Processing Approach

by Yizheng Zhang, Jian Zhang, Qian Huang, Yangyi Sun, Jia Shao, Yu Gou, Kaiming Huang and Shaodong Zhang

Appl. Sci. 2025, 15(15), 8663; https://doi.org/10.3390/app15158663 (registering DOI) - 5 Aug 2025

Abstract

Mars has been a primary focus of planetary science, with significant advancements over the past two decades across disciplines including geological evolution, surface environment, and atmospheric and space science. However, the rapid growth of the related literature has rendered traditional manual review methods increasingly inadequate. This inadequacy is particularly evident in interdisciplinary research, which is often characterized by dispersed topics and complex semantics. To address this challenge, this study proposes an automated analysis framework based on natural language processing (NLP) to systematically review the Martian research in Earth and space science over the past two decades. The research database contains 151,196 Mars-related sentences extracted from 10,655 publications spanning 2001 to 2024. Using machine learning techniques, the framework clusters Mars-related sentences into semantically coherent groups and applies topic modeling to extract core research themes. It then analyzes their temporal evolution across the Martian solid, surface, atmosphere, and space environments. Finally, through sentiment analysis and semantic matching, it highlights unresolved scientific questions and potential directions for future research. This approach offers a novel perspective on the knowledge structure underlying Mars exploration and demonstrates the potential of NLP for large-scale literature analysis in planetary science. The findings potentially provide a structured foundation for building an interdisciplinary, peer-reviewed Mars knowledge base, which may inform future scientific research and mission planning. Full article

(This article belongs to the Topic Artificial Intelligence Models, Tools and Applications)

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19 pages, 913 KiB

Open AccessArticle

Understanding Diversity: The Cultural Knowledge Profile of Nurses Prior to Transcultural Education in Light of a Triangulated Study Based on the Giger and Davidhizar Model

by Małgorzata Lesińska-Sawicka and Alina Roszak

Healthcare 2025, 13(15), 1907; https://doi.org/10.3390/healthcare13151907 - 5 Aug 2025

Abstract

Introduction: The increasing cultural diversity of patients poses new challenges for nurses. Cultural competence, especially knowledge of the cultural determinants of health and illness, is an important element of professionalism in nursing care. The aim of this study was to analyse nurses’ self-assessment of cultural knowledge, with a focus on the six dimensions of the Giger and Davidhizar model, prior to formal training in this area. Methods: A triangulation method combining qualitative and quantitative analysis was used. The analysis included 353 statements from 36 master’s student nurses. Data were coded according to six cultural phenomena: biological factors, communication, space, time, social structure, and environmental control. Content analysis, ANOVA, Spearman’s rank correlation, and cluster analysis (k-means) were conducted. Results: The most frequently identified that categories were environmental control (34%), communication (20%), and social structure (16%). Significant knowledge gaps were identified in the areas of non-verbal communication, biological differences, and understanding space in a cultural context. Three cultural knowledge profiles of the female participants were distinguished: pragmatic, socio-reflective, and critical–experiential. Conclusions: The cultural knowledge of the participants was fragmented and simplified. The results indicate the need to personalise cultural learning and to take into account nurses’ level of readiness and experience profile. The study highlights the importance of the systematic development of reflective and contextual cultural knowledge as a foundation for competent care. Full article

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