Search Results (4,934)

Background/Objectives: Brain health monitoring is increasingly essential as modern cognitive load, stress, and lifestyle pressures contribute to widespread neural instability. The paper presents BrainTwin, a next-generation cognitive digital twin, as a patient-specific, constantly updating computer model that combines state-of-the-art MRI analytics for neuro-oncological assessment related to clinical study and management of tumors affecting the central nervous system (including their detection, progression, and monitoring) with real-time EEG-based brain health intelligence. Methods: Structural analysis is driven by an Enhanced Vision Transformer (ViT++), which improves spatial representation and boundary localization, achieving more accurate tumor prediction than conventional models. The extracted tumor volume forms the baseline for short-horizon tumor progression modeling. Parallel to MRI analysis, continuous EEG signals are captured through an in-house wearable skullcap, preprocessed using Edge AI on a Hailo Toolkit-enabled Raspberry Pi 5 for low-latency denoising and secure cloud transmission. Pre-processed EEG packets are authenticated at the fog layer, ensuring secure and reliable cloud transfer, enabling significant load reduction in the edge and cloud nodes. In the digital twin, EEG characteristics offer real-time functional monitoring through dynamic brainwave analysis, while a BiLSTM classifier distinguishes relaxed, stress, and fatigue states, which are probabilistically inferred cognitive conditions derived from EEG spectral patterns. Unlike static MRI imaging, EEG provides real-time brain health monitoring. The BrainTwin performs EEG–MRI fusion, correlating functional EEG metrics with ViT++ structural embeddings to produce a single risk score that can be interpreted by clinicians to determine brain vulnerability to future diseases. Explainable artificial intelligence (XAI) provides clinical interpretability through gradient-weighted class activation mapping (Grad-CAM) heatmaps, which are used to interpret ViT++ decisions and are visualized on a 3D interactive brain model to allow more in-depth inspection of spatial details. Results: The evaluation metrics demonstrate a BiLSTM macro-F1 of 0.94 (Precision/Recall/F1: Relaxed 0.96, Stress 0.93, Fatigue 0.92) and a ViT++ MRI accuracy of 96%, outperforming baseline architectures. Conclusions: These results demonstrate BrainTwin’s reliability, interpretability, and clinical utility as an integrated digital companion for tumor assessment and real-time functional brain monitoring. Full article

Efficient crop health monitoring is crucial for global food security. Supervised deep learning approaches are often impractical due to the scarcity of large, labeled datasets. To address this limitation, this study adapts EfficientAD, an unsupervised, label-free anomaly detection framework originally designed for industrial inspection, for agricultural imagery on small datasets. The method utilizes a Patch Description Network (PDN) for localized feature extraction, a student network for local anomalies, and an autoencoder for global structural constraints. Benchmarked against AnoGAN, Pix2Pix, InTra, and Teacher–Student models, the framework demonstrated superior performance on the MVTec AD, PlantVillage, Coffee Leaf, and a custom real-world Sweet Potato dataset. The model achieved perfect area under the receiver operating characteristic curve (AUROC) scores of up to 100% in categories like “Pongamia”, “Potato”, and “Coffee Leaf”. While image-level classification was exceptionally robust, pixel-level localization (AUPRO) proved sensitive to complex agricultural backgrounds. To overcome this, a background interference analysis was conducted using Background Removed (BGRM) and out-of-distribution Background Replaced-Green (BGRP-G) strategies on the custom dataset. Notably, the BGRP-G strategy remarkably improved the image-level AUROC from 88.9% to 99.5% and substantially boosted the pixel-level AUPRO from 47.1% to 61.9%, successfully preserving the boundary integrity of severe structural defects. Achieving millisecond-level latency without complex data augmentation, this adapted label-free framework offers a versatile, highly efficient solution for real-time crop health diagnostics on resource-constrained Edge AI devices. Full article

The rapid growth in the spectrum of cyber threats, coupled with the evolution of digital uses, services and infrastructures in the healthcare sector, means that security measures need to be reassessed to ensure that they are in step with the reality on the ground and adapted accordingly, as smart healthcare systems show a dearth of privacy and security in the digitization and sharing of health records. Blockchain, being a new decentralized infrastructure, is one of the leading revolutionary emerging technologies that can be used to improve data integrity and traceability in healthcare systems. This study investigates how blockchain technology is affecting the healthcare domain, comprehensively analyzing its implications, challenges, and capabilities. The results indicate that blockchain is a revolutionary technology for creating transparent personal health records that can address the limitations of smart healthcare system management and provide a decentralized environment for exchanging healthcare data. However, there are still plenty of difficulties and obstacles that prevent it from being more widely accepted by healthcare stakeholders. Full article

Background: Artificial intelligence (AI) is increasingly integrated into healthcare systems, with important implications for nursing practice and clinical workflows. However, evidence regarding nurses’ digital skills, perceptions, and readiness to adopt AI-enabled technologies remains limited, particularly in national healthcare contexts such as Greece. Objectives: This study examined nurses’ digital skills, perceptions of AI, and readiness for AI adoption in clinical practice, and explored demographic and professional factors associated with these outcomes. Methods: A cross-sectional survey was conducted among 166 nurses working in two public hospitals in Greece. Results: Nurses reported moderate digital skills, with 59.1% indicating competence in email/video communication and 27.2% reporting adequate use of digital security tools, while exposure to AI remained limited (18.0% reported using AI products/services in daily life). Perceived professional impact of AI was moderate, whereas readiness for AI adoption was comparatively lower, with only 7.8% considering health professionals adequately prepared and 7.2% reporting adequate AI training. Statistical analyses indicated that educational level and computer literacy certification were positively associated with digital skills, whereas longer professional experience was negatively associated with readiness for AI adoption. Conclusions: These findings highlight a gap between general digital competence and preparedness for AI-driven healthcare applications and underline the need for targeted education and implementation strategies to support effective and ethical integration of AI in nursing practice. From a nursing workforce perspective, the results underscore the importance of integrating AI literacy into continuing professional education and aligning digital health implementation strategies with clinical nursing practice. Full article

Background: Undernutrition among children under five years remains a major public health challenge, particularly in low- and middle-income countries and rural communities where poverty, food insecurity, and limited access to health services persist. Maternal and caregiver perceptions play a critical role in shaping feeding practices and health-seeking behaviours that influence child nutritional outcomes. Objective: This study explored mothers’ and caregivers’ perceptions of factors contributing to undernutrition among children under five years in a rural community of Ngqeleni, Eastern Cape, South Africa. Methods: A qualitative descriptive study was conducted at a primary healthcare clinic in the Ngqeleni sub-district. Purposive sampling was used to recruit mothers and caregivers of children under five years. Data were collected through seven in-depth interviews and three focus group discussions involving a total of 25 participants. Interviews were conducted using a semi-structured guide and analyzed thematically. Results: Five major themes emerged: caregivers’ perceptions of nutrition, household food insecurity and unemployment, limited dietary diversity, culturally influenced feeding practices, and gaps in practical nutrition knowledge. Caregivers demonstrated concern for child nutrition but described constrained feeding choices shaped by poverty, reliance on social grants, environmental challenges, and limited access to diverse foods. Environmental challenges such as drought and lack of piped water further limited food production. Limited nutrition knowledge and reliance on informal information sources contributed to suboptimal feeding practices. Conclusions: Undernutrition in this rural setting is shaped by a complex interaction of economic hardship, environmental constraints, and limited caregiver knowledge. Community-based nutrition education, strengthened primary healthcare counselling, and multisectoral interventions addressing poverty, water access, and food security are essential to improve child nutrition outcomes. Full article

People spend most of their time indoors, highlighting the importance of indoor environmental quality for health and wellbeing. While previous studies have shown that exposure to nature can benefit wellbeing, much of this research has focused on outdoor environments, and less is known about how indoor plants and their spatial characteristics influence human perceptions and experiences. This paper reports on a survey study exploring how perceived health and wellbeing are influenced by indoor plants and human preferences for their characteristics, spatial arrangement, and other features within indoor environments. Indoor plants serve as visual and multisensory environmental stimuli. By examining the relationship between indoor plants, preferences, perceptions, visual comfort, multisensory experiences, and wellbeing, the study aims to understand these influences. The questionnaires include multiple-choice questions, yes-no questions, and open-ended questions, allowing the collection of both quantitative and qualitative data. The survey findings highlight the unique benefits of indoor plants, emphasising their potential to enhance wellbeing in ways that outdoor nature may not fully replicate in indoor settings. One significant finding of this study is that scattering indoor plants throughout a space can enhance the connection to nature through three-dimensional spatial interaction, potentially improving wellbeing. This arrangement may serve as a bridge to the outdoors, providing a psychological link to the natural environment. Crucial preference factors also include the complexity and coherence of indoor plants’ appearance, such as colour, shape, and size. The results further indicate that students prefer indoor plants over other elements such as cut flowers, fake plants, or artificial plant representations. The findings indicate that caring for indoor plants may foster emotional engagement, a sense of fulfilment, and place attachment through everyday interaction. In public spaces, plants may also enhance feelings of refuge and perceived security. These findings provide practical recommendations for designing indoor environments that enhance student wellbeing and human–environment interaction. Full article

Soil health monitoring is critical for the sustainable management of the black soil region, a key resource for global food security. However, traditional field surveys are constrained by high operational costs, limited spatial coverage, and low temporal frequency, making them inadequate for high-resolution and time-sensitive soil monitoring. The recently launched ZY1-02E satellite, equipped with an advanced hyperspectral imager, offers a new potential data source, yet its capability for quantitative soil modelling requires rigorous cross-sensor validation. This study conducts a cross-sensor evaluation of ZY1-02E and its predecessor, ZY1-02D, for mapping soil organic matter (SOM) and soil texture (sand, silt, and clay) in Northeast China. Optimal spectral indices were constructed through exhaustive band combination and correlation screening, and quantitative inversion models were established using a hybrid framework integrating Random Frog feature selection with Gaussian Process Regression (GPR) and Boosting Trees, based on synchronous ground observations. Results demonstrate strong cross-sensor consistency, with spectral indices showing significant linear correlations (${\mathrm{R}}^2>0.65$) between ZY1-02E and ZY1-02D. Furthermore, the quantitative retrieval models applied to ZY1-02E imagery achieved robust performance, with cross-sensor retrieval consistency exceeding ${\mathrm{R}}^2=0.60$ for all parameters and SOM exhibiting the highest agreement (${\mathrm{R}}^2=0.74$). These findings confirm the radiometric stability and algorithm transferability of ZY1-02E, demonstrating its capability to generate soil parameter products comparable to ZY1-02D without extensive model recalibration. The validated interoperability of the twin-satellite constellation substantially enhances temporal observation capacity during the narrow bare-soil window, effectively mitigating cloud-induced data gaps in high-latitude agricultural regions. Importantly, the enhanced monitoring framework provides a scalable technical paradigm for high-frequency hyperspectral soil mapping, offering critical spatial decision support for precision fertilization, soil degradation mitigation, and conservation tillage management in the Mollisol belt. Full article

The long-term sustainability of Australian agriculture is fundamentally constrained by the capacity, condition, availability, and governance of soil resources. Australian soils are among the oldest and most weathered globally, highly heterogeneous, and often slow or effectively irreversible to recover once degraded. Traditional approaches centred on soil health, while valuable at paddock scale, are insufficient to address national-scale challenges related to spatial variability, data continuity, economic valuation, and policy integration. This paper examines soil security as a policy-relevant framework for supporting more sustainable Australian agriculture. Building on the dimensions of soil security (capacity, condition, capital, connectivity, and codification), we synthesise recent Australian case studies to show how soil security extends beyond soil health to integrate biophysical properties, digital soil infrastructure, socio-economic value, and governance mechanisms. Drawing on recent Australian case studies, this review identifies advances in digital soil mapping, national soil assessments, economic valuation of soil capital, stakeholder connectivity, and emerging policy frameworks, while also identifying persistent gaps in regulation, data standardisation, and institutional coordination. The paper argues that soil security can help operationalise 3-N agriculture—Net-Zero, Nature-Positive, and Nutrient-Balanced systems—by translating sustainability goals into spatially explicit, place-based decisions grounded in soil realities. By explicitly accounting for soil capacity limits, condition trajectories, capital value, information flows, and codified rules, soil security can support more realistic climate mitigation strategies, targeted nature-positive interventions, and durable nutrient security outcomes. We conclude that embedding soil security more explicitly within Australian agricultural research, policy, and governance would strengthen efforts to deliver productive, resilient, and socially legitimate food and fibre systems. Without soil security, sustainability frameworks may remain difficult to operationalise consistently; with soil security, they can be translated more effectively into measurable, place-based, and durable decisions. Full article

The prehistoric and historic Greek populations have a long and glorious history and could teach us significant lessons relevant to water resources and their management. Most Greek civilizations lived in harmony with the environment, with a profound understanding of environmental sustainability. The Minoan era, considered as Pax Minoica (or Minoan peace), was a time when palaces and other living places did not have defensive walls; in that time, human rights and power without a military aristocracy developed. During that time, hydro-structures with a high degree of security, which remained in operation for millennia, were developed, most of them established in predominantly arid areas for reasons of security, protection, and public health. The study presents important elements of the development and progress of these technological achievements provided by ancient civilizations throughout the prehistoric to modern period, in the context of revealing and highlighting potential lessons to understand and address current critical issues in the management of water resources. Furthermore, the methodology used and the technological structural advancement of water works, their infrastructure durability, and early water law principles are considered. Many modern systems are designed for operational lifespans of 50–100 years, whereas several ancient Greek hydraulic structures remained functional for centuries by relying on renewable natural resources—reflecting a fundamentally different design philosophy centered on longevity and robustness. Thus, terms such as “sustainability” and “water security/safety”, first taught by ancient civilizations, need to be reconsidered and adopted again nowadays to inspire policies, strategies, and actions against the increasing challenges. Full article

Beekeeping is a profitable and mind-relaxing practice; however, monitoring beehives poses significant challenges, such as consuming time and potentially disturbing hive equilibrium, which may lead to colony collapse. Developing precision beekeeping (PB) systems is crucial to assist beekeepers in decision-making, automate redundant hive maintenance, and enhance the security and comfort of bee life. This review systematically explores research on PB systems, based on a keyword-driven search of Scopus and Web of Science databases, yielding 46 relevant publications. The analysis highlights a notable increase in research activity in the field since 2016. The integration of advanced technologies, including machine learning, cloud computing, IoT, and scenario-based communication methods, has proven instrumental in predicting hive states such as queen status, enemy attacks, readiness for harvest, swarming events, and population decline. Commonly measured parameters include hive weight, temperature, and relative humidity, with various sensors employed to ensure precision while minimizing bee disturbance. Additionally, bee traffic monitoring has emerged as a critical approach to assessing hive health. Most studies focus on honeybees rather than stingless bees and, in the context of enemy identification, Varroa destructor is the primary target. This review underscores the potential of novel technologies to revolutionize apiculture and enhance hive management practices. Full article

Soil salinity poses a major challenge to agricultural productivity, especially threatening food security in arid and semi-arid areas. Traditional soil reclamation methods, such as leaching, chemical amendments, and drainage engineering, usually need large amounts of water, involve high costs, and can lead to environmental problems. This review compiles existing knowledge on innovative strategies for managing saline soils, focusing on buried interlayer systems that use materials like straw, sand, gravel–sand mixtures, and biochar. These interlayers improve soil hydraulic properties by preventing capillary rise, encouraging salt leaching, and reducing surface salt buildup. Biochar stands out as a particularly useful material because of its stability, large surface area, porosity, and high cation exchange capacity. These features help improve soil structure, increase water retention, and effectively retain sodium. Evidence from lab and field tests shows that buried biochar layers can stop salt from moving upward, aid in desalinating the root zone, and boost crop yields. While straw and sand interlayers show potential in reducing salinity, biochar is noted for its multifunctionality and long-term effectiveness in addressing salinity problems. The success of buried biochar systems depends on several factors, including the properties of the biochar, how much is used, how deep it is buried, and the specific soil and climate conditions. This review highlights how these systems work, compares their performance, and points out research gaps, advocating for their potential as a sustainable, resource-efficient way to manage salinity and improve soil health over the long term. A substantial proportion of the existing evidence is derived from controlled laboratory studies, and the buried biochar layer approach remains an emerging technique that requires further validation under field conditions. Still, significant knowledge gaps persist regarding long-term performance and water-salt dynamics, while site-specific soil variability and scalability challenges may limit the effective implementation of biochar interlayer systems under field conditions. Full article

Bipolar disorder is characterized by extreme mood fluctuations that may create emotionally inconsistent caregiving environments for children. Although children of caregivers with bipolar disorder are at elevated risk for psychosocial difficulties, less is known about how parental bipolar symptoms (PBSs) relate specifically to identity development. The present study investigated associations between perceived PBSs and identity outcomes among emerging adults, examining parental attachment as a potential mediator. College students (N = 399) completed an anonymous online survey assessing identity development, attachment to parents, and perception of PBSs. PBSs were positively associated with identity distress, disturbed identity, and lack of identity, and negatively associated with identity consolidation. Mediation analyses indicated that parental attachment partially or fully mediated the relationships between PBSs and each identity variable, suggesting that higher levels of PBSs were associated with less secure attachment, which in turn were linked to greater identity difficulties. These findings highlight the role of parental mental health and attachment in shaping identity development and underscore the importance of accessible mental health care for youth navigating identity formation in the context of caregiver psychopathology. Clinical implications and future directions are discussed. Full article

Our community-based participatory research (CBPR) partnership convened an in-person, bilingual empowerment theory-based community forum to disseminate and translate findings from our trial of Nuestra Comunidad Saludable (Our Healthy Community), a multilevel intervention designed to improve uptake of COVID-19 testing and vaccination among Spanish-speaking Latine communities in North Carolina. The forum brought together community members, healthcare providers, organizational representatives, and academic researchers from across North Carolina. Drawing on findings from the intervention trial, participants engaged in facilitated, structured dialogue to identify community priorities and generate recommendations to advance health equity among Latine communities. Thirty-six participants identified eight priorities: (1) reducing health service gaps and inequities exposed by COVID-19; (2) expanding access to bilingual, culturally responsive mental health services; (3) improving understanding of HIV prevention and treatment; (4) strengthening services for children with disabilities; (5) protecting immigrant rights and ensuring safe access to services; (6) increasing political and social support for Latine health; (7) improving access to trusted, culturally responsive providers and community organizations; and (8) addressing social determinants of health, including employment, housing, and food security. The empowerment-based forum identified community priorities, challenges, and recommendations that can inform practice, intervention, policy, and research, and advance health equity for Spanish-speaking Latine communities. Full article

Soil health is essential for food security, ecosystem stability, and sustainable development, yet its spatial heterogeneity and driving mechanisms remain insufficiently understood at regional scales. This study investigates soil health in Heilongjiang Province, China. A Soil Health Index (SHI) was constructed using eight indicators covering physical, chemical, and biological properties based on multi-source datasets at 1 km spatial resolution. A random forest (RF) model was applied to identify key environmental drivers, and Moran’s I and Getis–Ord Gi* statistics were used to analyze spatial clustering. The results showed that SHI values ranged from 0.19 to 0.70, with a mean of 0.45. The RF model achieved strong performance (R² = 0.6666, RMSE = 0.03184, MAE = 0.02372), significantly outperforming linear regression (R² ≈ 0.17). Significant spatial clustering was observed, where “hotspots” refer to statistically significant clusters of high SHI values, and “coldspots” indicate clusters of low SHI values based on Getis–Ord Gi* analysis. Climate factors (temperature and precipitation) and elevation were the dominant drivers. Significant spatial clustering was observed, with clear hotspot and coldspot patterns. These findings provide spatial evidence for sustainable land-use planning and zonal soil management. However, the analysis is limited by data resolution and model interpretability, which may affect the representation of fine-scale variability. Full article

This study advances the conceptual and practical scope of social education by integrating Security and Safety Education (SSE) categories into its theoretical foundation. We demonstrate that SSE encompasses multidimensional areas highly relevant to social education and offer a structured competence model to guide curriculum design. Using a mixed-methods approach, 2926 Web of Science publications were analysed through an NVivo Word Frequency Query to identify key domains associated with security and safety. The temporal scope of the corpus (2019–2021) provides a coherent analytical baseline, capturing intensified security and health-related discourse during the COVID-19 period while preceding geopolitical disruptions that could otherwise distort thematic patterns. The results show that security is associated with broad social and geopolitical issues, including food, political, economic, public, national, and international affairs, as well as health and information. In contrast, safety is mainly linked to transport-related concerns, although both domains converge in areas such as health, social, public, national, and information matters. These findings indicate that SSE encompasses multidimensional areas relevant to social education. To support curricular integration, we propose an eMEDIATOR-derived competence model that structures SSE content into measurable, outcomes-based components. Ultimately, this research provides actionable tools to elevate social education and promote active, informed citizenship in times of global uncertainty. Full article