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Found 5152 publications
Deep learning approach for automated hMPV classification
Publication Name: Scientific Reports
Publication Date: 2025-12-01
Volume: 15
Issue: 1
Page Range: Unknown
Description:
Human metapneumovirus (hMPV) is a significant cause of respiratory illness, particularly in children, elderly individuals, and immunocompromised patients. Despite its clinical relevance, hMPV poses diagnostic challenges due to its symptom similarity with other respiratory illnesses, such as influenza and respiratory syncytial virus (RSV), and the lack of specialized detection systems. Traditional diagnostic methods are often inadequate for providing rapid and accurate results, particularly in low-resource settings. This study proposes a novel deep learning framework, referred to as hMPV-Net, which leverages Convolutional Neural Networks (CNNs) to facilitate the precise detection and classification of hMPV infections. The CNN model is designed to perform binary classification by differentiating between hMPV-positive and hMPV-negative cases. To address the lack of real-world patient data, simulated image datasets were used for model training and evaluation, allowing the model to generalize to various clinical scenarios. A key challenge in developing this model is the imbalance within the dataset, where hMPV-positive cases are often underrepresented. To mitigate this, the framework incorporates advanced techniques such as data augmentation, weighted loss functions, and dropout regularization, which help to balance the dataset, improve model robustness, and enhance classification accuracy. These techniques are crucial in addressing issues such as overfitting and generalization, which are common when working with limited datasets in medical imaging tasks. The dataset used for model training and testing consists of 10,000 samples, with an equal distribution of hMPV-positive and hMPV-negative cases. Experimental results demonstrate that the hMPV-Net model achieves a high test accuracy of 91.8%, along with impressive test precision, recall, and F1-score values around 92%. These metrics indicate that the model performs exceptionally well in classifying both hMPV-positive and hMPV-negative cases. Furthermore, the model exhibits superior computational efficiency, requiring only 3.2 GFLOPs, which is significantly lower than other state-of-the-art models such as ResNet-50 and VGG-16. This reduction in computational cost makes the model suitable for deployment in resource-constrained healthcare environments, where computing power and infrastructure may be limited.
Open Access: Yes
A novel numerical investigation of fiber Bragg gratings with dispersive reflectivity having polynomial law of nonlinearity
Publication Name: Scientific Reports
Publication Date: 2025-12-01
Volume: 15
Issue: 1
Page Range: Unknown
Description:
Fiber Bragg gratings represent a pivotal advancement in the field of photonics and optical fiber technology. The numerical modeling of fiber Bragg gratings is essential for understanding their optical behavior and optimizing their performance for specific applications. In this paper, numerical solutions for the revered optical fiber Bragg gratings that are considered with a cubic-quintic-septic form of nonlinear medium are constructed first time by using an iterative technique named as residual power series technique (RPST) via conformable derivative. The competency of the technique is examined by several numerical examples. By considering the suitable values of parameters, the power series solutions are illustrated by sketching 2D, 3D, and contour profiles. The results obtained by employing the RPST are compared with exact solutions to reveal that the method is easy to implement, straightforward and convenient to handle a wide range of fractional order systems in fiber Bragg gratings. The obtained solutions can provide help to visualize how light propagates or deforms due to dispersion or nonlinearity.
Open Access: Yes
Evaluation of early warning signals for soil erosion using remote sensing indices in northeastern Iran
Publication Name: Scientific Reports
Publication Date: 2025-12-01
Volume: 15
Issue: 1
Page Range: Unknown
Description:
Soil erosion represents a major challenge to natural resource conservation, causing land degradation, biodiversity loss, and diminished soil quality. This study explored the use of satellite imagery to evaluate the spatiotemporal risk of soil erosion in northeastern Iran. The ICONA model was applied to identify areas at severe erosion risk, while remote sensing indices (NDVI, NDSI, and TGSI) were employed to analyze erosion trends. NDVI is used to monitor vegetation health, NDSI detects soil salinity levels, and TGSI assesses topsoil grain size distribution, collectively providing critical insights into soil erosion risk in the study area. These indices, derived from the Google Earth Engine with a 30-meter spatial resolution and monthly temporal intervals (2003–2022), were assessed at 100 points, equally divided between eroded and non-eroded regions. Field data, including vegetation plots and soil profiles, were used to validate the remote sensing outputs. Early warning signals were analyzed through three statistical indices—autocorrelation coefficient, skewness, and standard deviation—using Kendall’s tau. Results revealed that 39.7% of the area falls under low erosion risk, 58.4% under medium risk, and 1.9% under severe risk. Significant breakpoints in NDSI and NDVI were identified in 2013, while TGSI showed no detectable change. Major shifts occurred near the Alagol, Almagol, and Ajigol wetlands and northern drylands. This study underscores the importance of integrating satellite data with field validation to improve soil management, protect biodiversity, and guide sustainable erosion mitigation strategies.
Open Access: Yes
Valuation of ecosystem services from forests in Chinese rural areas based on forest resource investment
Publication Name: Humanities and Social Sciences Communications
Publication Date: 2025-12-01
Volume: 12
Issue: 1
Page Range: Unknown
Description:
Forest resources provide rural areas with abundant products and ecosystem services. However, due to difficulties and shortcomings in assessing the ecosystem service value of these resources in rural areas, investors or funding institutions often lack a comprehensive understanding of their true value. Consequently, challenges such as difficulties in securing rural forestry guarantees, limited loan amounts, and inadequate compensation standards have emerged, resulting in severely restricted investments in rural forest resources. This study aims to address these issues by establishing a comprehensive valuation system for the ecosystem services provided by rural forest resources, thereby enabling a more accurate assessment of their value. This study focuses on Muyun She Nationality Township in Fuan City, China, and valuates the ecosystem service value of the forest resources in this locality. The findings reveal that the annual economic value of ecosystem services provided by forest resources in Muyun She Nationality Township amounts to 397,899,293.49 yuan. Direct value constitutes over 63% of the total, with forest by-products contributing the largest share at 32%, followed by forest-related rural tourism at 31%. This underscores the significant contribution of agricultural products and tourism from rural forest resources to the local economy. Moreover, the study highlights the crucial role of rural forest resources in providing agricultural by-products, promoting rural tourism, enhancing rural economic development, and facilitating rural revitalization efforts. In light of these findings, this paper advocates for private-sector investment, expanding financing channels, and developing tourism projects to diversify investment channels for rural forest resources and increase investment amounts.
Open Access: Yes
Understanding patient perception of digital value co-creation in electronic health record through clustering approach
Publication Name: Scientific Reports
Publication Date: 2025-12-01
Volume: 15
Issue: 1
Page Range: Unknown
Description:
Patients are central to healthcare services, and comprehending their perceptions is crucial for fostering effective value co-creation. This study aimed to investigate the user characteristics and perceptions of value co-creation within the context of Mobile Electronic Health Records (EHR). Using a questionnaire collected from 422 patients, the study employed the K-modes clustering algorithm in R-Studio to group users based on shared characteristics and perceptions of value co-creation. The analysis revealed three distinct user clusters, which are high familiarity-positive perception, low familiarity-positive perception and high familiarity-neutral to negative perception. These clusters characterized by unique attributes such as socio-economic, history of medical visit, intention to use, technological familiarity, and different perception of value co-creation in Mobile EHR systems. Descriptive statistics were used to further interpret the clusters, revealing differences in user characteristics and perception across cluster. The findings emphasize the importance of alignment between user expectations and system interactions. Effective alignment fosters value co-creation through resource access, sharing, integration, and recombination, while misalignment may result in value destruction. This study highlights the need to design and implement Mobile EHR systems that align with the diverse characteristics and of their users to enhance engagement and promote value co-creation.
Open Access: Yes
Biogeography-Based Optimization of Machine Learning Models for Accurate Penetration Rate Prediction Using Rock Texture Coefficient
Publication Name: International Journal of Computational Intelligence Systems
Publication Date: 2025-12-01
Volume: 18
Issue: 1
Page Range: Unknown
Description:
Predicting drill penetration rate (PR) in rock environments remains a significant challenge due to the complex interplay between rock texture, drilling fluid properties, and operational parameters. Traditional empirical models often lack generalizability and are based on inconsistent datasets, limiting their reliability. To address these limitations, this study develops a comprehensive experimental dataset using rock samples collected from various mines in Iran, tested under controlled laboratory conditions with different drilling fluids, bit loads, and rotational speeds. Texture coefficient (TC), electrical conductivity (EC), load on bit (LOB), and bit rotational velocity (BRV) were selected as input features. Four machine learning models—support vector regression (SVR), stochastic gradient descent (SGD), K-nearest neighbors (KNN), and decision tree (DT)—were trained to predict PR. A biogeography-based optimization (BBO) algorithm was employed to fine-tune hyperparameters and enhance model accuracy. Additionally, a novel hybrid error index (HEI) was introduced to comprehensively evaluate model performance. Among all models, the DT achieved the best accuracy with an HEI of 0.3753, followed by KNN, SVR, and SGD. These findings demonstrate the potential of the DT model, combined with optimized learning and a robust dataset, to reliably predict penetration rate in rock-based engineering projects.
Open Access: Yes
Qualitative analysis of the sustainability of local attachment and identity based on in-depth interviews conducted in two scattered farmstead settlements
Publication Name: Discover Sustainability
Publication Date: 2025-12-01
Volume: 6
Issue: 1
Page Range: Unknown
Description:
Based on qualitative research, the paper focuses on the transformation of the traditional lifestyle of scattered farmsteads in recent decades, primarily driven by economic shifts and demographic changes. The challenging conditions of agriculture and farming, and the rise of alternative economic activities, such as tourism, recreation, and small-scale business, have reshaped these rural settlements, contributing to a different social landscape. Besides, another important trend is the influx of newcomers, including professionals, entrepreneurs, and pensioners, who adopt alternative, often non-agricultural lifestyles while maintaining a strong sense of place attachment and identity. In contrast, younger generations of native inhabitants tend to migrate elsewhere due to limited prospects, better education and job opportunities, leading to a generational shift in the population base. This study investigates two farmstead settlements exemplifying the tendencies, highlighting how sustainability is increasingly supported not by the continuation of traditional practices, but by the emergence of new lifestyle patterns such as agritourism and rural commuting. The process of change reflects a transition in the meaning and practice of rural living, where sustainability is redefined by changing forms of identity and attachment supporting the survival of farmsteads in a postmodern world.
Open Access: Yes
Dynamic response distortion due to changing excitation frequency
Publication Name: Ain Shams Engineering Journal
Publication Date: 2025-12-01
Volume: 16
Issue: 12
Page Range: Unknown
Description:
This study addresses the distortion in system response caused by continuously changing excitation frequency. The distortion leads to reduced resonance peak amplitude and shifts the resonance frequency as well. The novelty of this work lies in providing an analytically established, model-based methodology that not only describes but also predicts and enables one to control this distortion, in contrast to existing studies that mainly describe the phenomenon characteristically [1,2]. The proposed approach incorporates the influencing parameters, such as the sweep direction and rate of linearly changing excitation frequency, and applies a first-order ODE (ordinary differential equation) formulation to approximate the distortion. This enables a sensitivity analysis across frequency and damping ranges, which has not been previously reported in the literature. The methodology is validated with experimental data from an E-drive system, demonstrating how optimal sweep rates and other test conditions can be derived from model fitting. While nonlinear effects may occur in E-drives, the present study focuses on their linear regime to isolate distortion effects. The findings provide both fundamental insights into resonance distortion and practical guidelines for improving the accuracy and reliability of swept-excitation-based NVH (noise, vibration, harshness) measurements in engineering applications.
Open Access: Yes
First report of Haemaphysalis bispinosa, molecular-geographic relationships of Ixodes granulatus and a new Dermacentor species from Vietnam
Publication Name: Parasites and Vectors
Publication Date: 2025-12-01
Volume: 18
Issue: 1
Page Range: Unknown
Description:
Background: Vietnam and its region are regarded as an ixodid tick biodiversity hotspot for at least two genera: Haemaphysalis and Dermacentor. To contribute to our knowledge on the tick fauna of this country, ticks from these two genera as well as an Ixodes species were analyzed morphologically and their molecular-phylogenetic relationships were examined in taxonomic and geographical contexts. Methods: For this study, seven Haemaphysalis sp. ticks were removed from dogs and collected from the vegetation. These showed morphological differences from congeneric species known to occur in Vietnam. In addition, three Ixodes sp. ticks were collected from pygmy slow lorises (Xanthonycticebus pygmaeus), and a Dermacentor female had been previously collected from the vegetation. After DNA extraction, these were molecularly or phylogenetically analyzed based on the cytochrome c oxidase subunit I (cox1) and 16S rRNA genes. Results: The three species were morphologically identified as (i) Ixodes granulatus, which had nearly or exactly 100% sequence identities to conspecific ticks reported from large (approximately 2000 km) geographical distances but was more different (having lower, only 94.2% cox1 and 96.7% 16S rRNA sequence identity) from samples collected within 1000 km of Vietnam in Southern China and Malaysia, respectively; (ii) Haemaphysalis bispinosa, which showed 100% sequence identity to samples reported within both narrow and broad geographical ranges; and (iii) a new species, Dermacentor pseudotamokensis Hornok sp. nov., described here morphologically and shown to be phylogenetically a sister species to Dermacentor tamokensis. Conclusions: Haemaphysalis bispinosa shows genetic homogeneity in the whole of South and Southeast Asia, probably owing to its frequent association with domestic ruminants and dogs (i.e. frequently transported hosts). However, I. granulatus, the Asian rodent tick, has a mixed geographical pattern of haplotypes, probably because it may associate with either synanthropic or wild-living rodents as primary hosts. This tick species is recorded here, for the first time to our knowledge, as parasitizing lorises in Vietnam and its region. Based on phylogenetic analyses, D. pseudotamokensis Hornok sp. nov., recognized and described here for the first time, was almost certainly misidentified previously as Dermacentor steini, drawing attention to the need to barcode all Dermacentor spp. in Southern Asia.
Open Access: Yes
