Search Results (10,682)

Global climate change is reshaping Central European conifer forests, affecting growth and ecosystem dynamics. At the same time, tree species differ in their productivity and responses to climatic conditions. Across mid-elevation monocultures of European yew (Taxus baccata L.), Norway spruce (Picea abies [L.] Karst.), Scots pine (Pinus sylvestris L.), silver fir (Abies alba Mill.), and European larch (Larix decidua Mill.), we quantified stand structure, volume, biomass carbon sequestration, and growth–climate responses (1971–2023). Silver fir reached the highest stand volume (711 m³ ha⁻¹), with lower productivity in pine (−17.0%), larch (−22.9%), spruce (−26.0%), and yew (−70.6%). In contrast, larch maximised biomass carbon sequestration (267.7 t ha⁻¹), whereas yew had the lowest value (87.7 t ha⁻¹), but the greatest stand diversity (except high differentiation), while pine showed the lowest diversity. Radial growth was most constrained by warm Junes and dry Julys; an early-season multi-month drought compounded by heat further suppressed radial increments, and severe winter frosts added stress. Among the studied species, spruce was the most climate-sensitive, whereas fir and pine showed comparatively more resilience. From a practical forestry perspective, promoting structurally diverse stands with high production potential and prioritising climate-resilient tree species, especially fir, can help sustain production and stability at mid elevations under climate warming. Our results provide species-specific benchmarks for adaptive silviculture and identify the seasonal windows when growth is most vulnerable. Full article

Increasing the carbon sink function of forests is critical for achieving carbon (C) neutrality in the context of global climate change. Past studies have focused on the estimation of forest biomass or C storage, while those on forest C sink potential remain limited. In particular, there remain few systematic investigations to define the forest C sink, to characterize the synergistic influencing factors, and to develop related quantitative analysis methods. The development of scientific C enhancement strategies requires the construction of C density-age models integrating multiple stand factors. These models allow accurate quantification of the gap (∆C) between actual and maximum C sequestration capacity. This study used permanent sample plot data to develop and validate a novel multi-model assessment approach for quantifying the C sink potential of Larix olgensis plantations in Heilongjiang Province, China, and to translate the results into precise management tools. An Average-Level Model (ALM) was established to define baseline C sequestration. Three innovative potential assessment models were then proposed: (1) the Empirical Upper Boundary Model (PLM1); (2) the Dummy Variable Model (PLM2); and (3) the Quantile Regression Model (PLM3). These models define the maximum C sequestration capacity from distinct perspectives. PLM1 (R² = 0.7910) characterized the theoretical upper limit of C sink potential (79.86 Mg·ha⁻¹), making it suitable for macro-strategic goal setting, though it is somewhat dependent on extreme data points. PLM2 (R² = 0.7943) achieved the best fit, and when combined with measurable stand conditions (site class index [SCI] > 16 m, stand density index [SDI] > 800 trees·ha⁻¹), it provides clear guidance for management practices. Although PLM3 showed a lower goodness-of-fit (R² = 0.1056), it provided reasonable parameter estimates and robust predictions, offering a reliable upper-bound reference for C sink project planning and risk control. At a stand age of 60 years (yr), the C sink enhancement potentials (“∆” C) corresponding to the three models were 15.73, 14.48, and 13.26 Mg·ha⁻¹, representing increases of 24.53%, 22.58%, and 20.68%, respectively, over the average level (64.13 Mg·ha⁻¹); the peak C sequestration rates of the models were 104.3%, 82.7%, and 60.5% higher than that of the ALM, with peak times occurring earlier at 9, 7, and 11 yr, respectively, underscoring the importance of the early management. The multi-model assessment approach developed here facilitates “precision carbon enhancement” by quantifying C sink potential across its theoretical, achievable, and robust upper-bound dimensions. This quantification provides both mechanistic insights into C sequestration processes and a critical link between theoretical understanding and practical forest management. This work holds significant value for advancing forestry C sinks in service of national strategies. Full article

To better understand the complexity of biological systems, research has shifted from a reductionist to a holistic approach, expanding the focus from single genes to a genome-scale view of gene activity and regulation. This is known as transcriptomics, a continuously growing field generating gene expression signatures from different technologies. A comparable paradigm shift has occurred in computational systems biology with the implementation of Artificial Intelligence (AI) learning models for gene expression analysis and integration. These models enable transcriptome-based profiling to address challenges of data heterogeneity, integration, and updating, assisting human intelligence and enhancing their ability to retrieve, analyze, integrate, and generate data recursively, thanks to their intrinsic predictive, inferential, reinforcement, and generative capabilities. Additionally, while scientists worldwide are still learning how to leverage AI methods that can maintain the human-in-the-loop, a new fundamental change is emerging: agentic AI, which can autonomously act and employ other AI methods to pursue its objectives. As a futuristic perspective, the proposed data analysis pipeline imagines agentic AI systems allowing the automated retrieval and pre-processing of heterogeneous transcriptomics data, analysis and integration with other omics datasets, performed with an incremental updating and recurrent analysis (IURA) model that could allow the detection of guideline updates (e.g., disease reclassification) and the generation of new hypotheses, such as candidate biomarkers or transcriptome–phenotype correlations. Since personalized medicine could derive profound benefits from its use, this scenario also raises important considerations regarding the advantages and concerns associated with the use of scientific AI agents in research and clinical practice. Full article

Computational methods have become increasingly prominent within the historical sciences, generating significant enthusiasm among some scholars. Yet their practical demands, epistemic limits, and ethical implications are less often critically examined than praised. This article explores what it means to do computational history today, arguing that it is not primarily defined by algorithms but by datasets. It is methodologically specific, resource-intensive, selective in scope, labour-heavy, and dependent on pre-digitised sources, specialised infrastructure, and interdisciplinary collaboration. These dependencies limit the scope of research questions and can produce narrow outcomes despite substantial effort, lending some validity to the concern over whether the field yields sufficient historiographical return for the labour invested. Corpus construction and data work lie at the epistemic core of computational history. These often undervalued tasks are not merely technical precursors to analysis, but interpretive and epistemic acts. Data are shaped by digitisation politics, historical bias, and institutional power. They shape the questions asked, the answers produced, and the legitimacy of findings. Recognising and valuing data work is essential, both to embed critical perspectives into computational humanities and to counteract the privileging of certain forms of labour over others. Due to the association of quantification with rigour and scholarly prowess, algorithmic work receives more credit, creating a two-tier system in this division of labour in which those who develop algorithms are elevated above those who curate data, despite their symbiotic interdependence. Computational history, when done well, requires deep engagement with our sources, be they historical or data. For computational history to stabilise as a meaningful discipline, it must prioritise building better datasets over pursuing increasingly complex algorithms on an unstable basis of data. Full article

Soil fungi play a pivotal role in maintaining ecosystem functions and regulating plant health. Although plant root traits can significantly impact the abundance and diversity of different fungal groups, the mechanism by which plant root strategies drive the assembly of soil fungal guilds remains limited. Utilizing Root Economics Space theory, this study investigates how four green manures (hairy vetch, rye, radish, and rapeseed) with contrasting root functional strategies (along the ‘fast–slow’ and ‘outsourcing–DIY’ axes) regulate the composition and functional structure of soil fungal communities. Community characteristics of three functional guilds (plant pathogens, saprophytes, and arbuscular mycorrhizal fungi), as well as relationships between these communities and plant root traits, were evaluated using a combination of Illumina high-throughput sequencing, functional annotation, and multivariate statistical analysis. Overall, different root strategies were associated with distinct fungal community patterns, potentially related to differences in root-derived resource inputs and soil properties. The ‘slow’ and ‘DIY’ strategies were associated with lower relative abundance of plant pathogenic fungi and higher relative abundance of saprotrophic fungi, whereas the ‘fast’ and ‘outsourcing’ strategies were associated with higher relative abundance of plant pathogens and AMF. These findings suggest that root functional strategies may help explain variation in fungal guild composition under different green manure species. From a practical perspective, the results provide a basis for selecting green manure species to help manage soil-borne disease risk, regulate beneficial soil microbial communities, and support more sustainable soil management in agricultural production. Full article

Jellyfish, as representatives of the phylum Cnidaria, possess venoms characterized by structurally diverse and functionally complex toxins, rendering them a central focus in cnidarian toxin research. This article presents a systematic review of the physicochemical properties of jellyfish toxins, examines their mechanisms of action from a molecular biology perspective, investigates the patterns of toxin transformation in organisms, elucidates the structure–activity relationships between structure and toxicity, introduces advancements in research on novel jellyfish toxins, and offers an outlook on future developments in this field. By integrating modern proteomic techniques, such as liquid chromatography-tandem mass spectrometry, this review provides comprehensive theoretical support for the foundational research and application development of jellyfish toxins, as well as a scientific basis for practical applications, including antivenom serum development and novel marine drug design. Full article

The rapid rise in generative AI (GenAI) in higher education creates a tension between institutional goals for AI literacy and everyday classroom practice: while universities increasingly call for ethical and skills-focused engagement, faculty adoption is uneven and often constrained by uncertainty. To examine this gap, we combined campus-wide attitude surveys, a longitudinal content analysis of 1716 syllabi, and a review of publicly available GenAI assignment collections. Results revealed a persistent implementation gap: although sustained professional development was associated with shifts in faculty perspectives, a majority of course-level policies remained prohibitive or punitive and were not aligned with stated institutional aims. While consistent professional development has helped faculty accept the need for GenAI literacy, most individual faculty policies remain prohibitive, at odds with both the institutional push for transparency in GenAI literacy and the faculty’s stated stance toward the need for teaching GenAI skills. Our analysis of publicly available GenAI-themed assignments demonstrated that engaging students with GenAI can take various shapes depending on instructor and course goals. This work positions AI-themed assignments as a practical solution to faculty reluctance, providing a promising pathway for hesitant educators to integrate AI literacy into their courses and meet the evolving needs of their students. Full article

Objective: Nutrition is a key determinant of women’s health across all life stages. Clinical practice remains heterogeneous because of lack of evidence and non-homogeneous guidelines. Despite growing research on micronutrient supplementation, skeptical opinions persist around universal versus individualized approaches, optimal dosages, and life-stage-specific recommendations. Material and methods: This is a modified Delphi process conducted under the supervision of the Italian Association of University Gynecologists and Obstetricians (AGUI). Thirteen Italian experts in gynecology and obstetrics completed two rounds of anonymous online surveys (September–November 2025). The questionnaire, developed through a scoping review, covered six domains: pre-/periconception, pregnancy, postpartum, routine supplementation in non-pregnant women, nutrition in gynecological conditions, and menopause. Consensus was defined as ≥75% agreement on a 10-point Likert scale. Quantitative data were summarized descriptively, and qualitative comments contextualized findings. Results: Experts strongly supported personalized nutritional strategies across all life stages. Consensus was reached on individualized micronutrient supplementation in the preconception period and on the prescription of active folates for women undergoing assisted reproduction. In pregnancy, agreement emerged for universal DHA supplementation (200–300 mg/day); however, universal vitamin D supplementation lacked consensus except in gestational diabetes. In the postpartum period, iron supplementation for non-breastfeeding women reached consensus, while micronutrient recommendations for breastfeeding women remained uncertain. Strong agreement supported personalized dietary approaches for PCOS, endometriosis, and gestational diabetes, including inositol use, while evidence for interventions in severe premenstrual syndrome remained insufficiently supported. In menopause, consensus was reached for macronutrient adjustments and universal calcium and vitamin D supplementation. Conclusions: This Delphi consensus highlights shared expert perspectives on nutritional care in women and identifies key evidence gaps, particularly regarding vitamin D in physiological pregnancy, postpartum micronutrient needs during breastfeeding, and nutritional strategies for premenstrual disorders. Unified life-course guidelines and future research on standardized nutritional assessments are necessary for nutritional approach management. Full article

Technological advances such as Vehicle-to-Grid (V2G) have the potential to support renewable energy integration and grid stability, but large-scale deployment depends on users’ willingness to participate, particularly in public charging environments. While prior research has examined V2G from technical feasibility and system-level perspectives, everyday public settings remain unexplored. This study investigates electric vehicle (EV) users’ willingness to engage in V2G services in public spaces, with a focus on incentives, expectations, and how participation aligns with existing routines and parking conditions. A mixed-method approach was applied, combining a survey of 544 car users with two waves of user-centered interviews. The survey data were analyzed using factor analysis and linear regression models, while the interview data were thematically analyzed. The results show that users’ evaluations of V2G are shaped by sustainability expectations, perceived efficiency, and uncertainties, and preferences for public V2G participation are strongly influenced by convenience, clarity of the offer, and perceived control. Home charging practices emerged as a key reference point shaping expectations of public V2G services. Across both methods, simple and transparent incentives, such as reduced charging or parking costs, were consistently preferred over more complex reward models, including point-based systems or dynamic energy trading. Concerns related to control over trips, battery degradation, trust in service providers, and added complexity remain important barriers to participation. The findings highlight the need for user-centered and socio-technical design of public V2G services that align with users’ everyday routines, parking conditions, and expectations to support broader adoption beyond the home context. Full article

In recent years, China’s rapid economic development has driven the improvement of infrastructure, with mass concrete widely applied in engineering for its unique structural functions. However, mass concrete is prone to temperature stress and thermal cracks due to its low thermal conductivity, huge volume, complex construction conditions, and frequent environmental changes, which pose potential structural safety risks. The hydration heat of mass concrete can also cause structural deformation, so targeted measures must be taken based on actual engineering conditions to minimize cracks. Real-time temperature monitoring during pouring is of crucial significance to ensure the quality and safety of mass concrete in practical projects. Taking the Phase I Project of Qingdao Metro Line 9 as the research object, this paper explores the temperature variation characteristics of mass concrete during pouring and forming on-site. It analyzes the temperature changes in mass concrete based on field temperature-monitoring data and laboratory test results, plots temperature measurement curves, and identifies the temperature variation trend of mass concrete caused by hydration heat. A numerical model is established via ANSYS to study the effects of ventilation temperature and velocity by simulation. Results show that the temperature of mass concrete pouring blocks rises rapidly to a peak and then decreases to room temperature, which is analyzed from the perspectives of hydration heat reaction mechanism and heat transfer. Laboratory test data are highly consistent with field data, verifying the temperature variation characteristics of concrete pouring. The numerical simulation of heat transfer-influencing factors reveals that the optimal ventilation velocity is 4 m/s for sufficient air circulation in the foundation pit; when the ventilation temperature is below 25 °C, the surface temperature of concrete decreases significantly with an obvious cooling effect. Full article

3D digitization of museum artifacts is essential for both their virtual presentation and re-exhibition in the event of damage or loss. Given the number of artifacts that can be exhibited in a museum, the effectiveness of single-digitization practices under designed conditions is limited in terms of realism. In this study, a highly detailed sine quadrant object was digitized in a museum environment using photogrammetry and structured-light scanning (SLS) techniques. 3D models were generated from point clouds derived in photogrammetry and directly obtained from SLS. In the qualitative assessment based on the distinguishability of linear and edge details, the photogrammetric technique was found to be better; in the quantitative assessment based on the reference length values on the artifact, SLS was better, while photogrammetry was also found to be adequate. The maximum difference values for photogrammetry and SLS were 0.40 and 0.27 cm, respectively, while the average difference values were 0.24 cm and 0.10 cm. Additionally, cloud-to-cloud distance analysis revealed that two-point clouds overlapped quite well geometrically. Point clouds were also compared in terms of homogeneity using outlier detection analysis. This analysis showed that noise in the photogrammetric point cloud had a wider distribution over the artifact. In terms of data acquisition and processing time, SLS was found to be better, while the cost was comparable. After evaluating the techniques from various perspectives, photogrammetry was found to be preferable for modeling in a museum environment due to the priority need for high texture quality from the end-user’s perspective. In this respect, SLS is highly dependent on hardware capability for both data acquisition and processing. Full article

Global population aging has led to a substantial increase in the number of older adults receiving long-term pharmacological treatment, often involving polypharmacy. Long-term medication use is often linked to negative oral health outcomes, such as xerostomia, periodontal disease, dental caries, and changes in the oral microbiome, even if it is necessary for treating systemic conditions. The general health, nutritional state, and quality of life of elderly people are all significantly impacted by these diseases. This narrative review integrates recent data on biological causes, genetic vulnerability, and public health consequences to investigate oral self-care as a preventive strategy in older persons on medication. The effects of long-term medication therapy on oral tissues, salivary function, inflammatory responses, and microbial balance are given special attention, as is the role of genetic variants linked to immunological and inflammatory pathways on individual variability. The review also evaluates oral self-care interventions aimed at reducing medication-related oral complications, such as the use of fluoride, mechanical plaque control measures, and caregiver-assisted oral care practices. Oral self-care is viewed from a public health perspective as a scalable and affordable strategy for reducing oral health disparities in older populations. The results highlight the significance of preventative, individualized, and integrated oral health interventions within larger healthcare frameworks for older persons taking long-term medications. Full article

The evolution of future Internet and sixth-generation (6G) networks is driving a paradigm shift from classical bit-centric communication toward meaning-aware and task-oriented communication models. Traditional information theory, while fundamental for ensuring reliable symbol transmission, does not account for semantic relevance or task effectiveness, which are critical for emerging applications such as autonomous systems, immersive services, and ultra-low-latency communications. This article presents a comprehensive review of Semantic Communications (SemCom) from a future Internet perspective. The review systematically analyses representative extensions of classical information theory aimed at quantifying semantic information, including semantic information measures, semantic channel capacity, and semantic rate–distortion formulations. In addition, the main mathematical and computational frameworks enabling practical semantic communication systems are examined, including the Information Bottleneck principle, learning-based end-to-end communication architectures, and reinforcement learning approaches for task-oriented optimization under network constraints. The review further discusses the role of semantic metrics, contextual modelling, and task-driven performance evaluation in the design of semantic-aware communication systems. The analysis identifies key open challenges, particularly the lack of a unified theoretical framework, the need for robust and context-aware semantic performance metrics, and the integration of semantic awareness into network-level design. Overall, this review highlights Semantic Communications as a promising paradigm for future Internet and 6G networks, where communication efficiency is increasingly determined by semantic relevance and task effectiveness rather than bit-level fidelity alone. Full article

Background/Objectives: Carotid body paragangliomas, commonly referred to as Carotid Body Tumors (CBTs), are rare, highly vascular paragangliomas arising at the carotid bifurcation and pose significant surgical challenges due to their proximity to critical neurovascular structures. Optimal management remains debated, particularly for large or complex lesions. This study aims to present a structured neurosurgical operative workflow as an educational and practical resource to help young surgeons understand operative decision-making and technical execution from a neurosurgical perspective. Methods: We retrospectively reviewed patients diagnosed with CBTs and identified three cases that underwent microsurgical resection by a single neurosurgeon. Clinical presentation, radiographic findings, operative strategies, intraoperative microsurgical techniques, and postoperative outcomes were analyzed. Surgical procedures for all three cases are further illustrated with technical video demonstrations highlighting meticulous microsurgical techniques performed by a single neurosurgeon. Results: All three patients presented with either incidental or slowly progressive neck masses, with imaging demonstrating classic splaying of the internal and external carotid arteries. One patient exhibited elevated catecholamine metabolites, while another had a familial history of paragangliomas. Preoperative embolization was successfully performed in all three cases. Complete tumor resection was achieved in each patient. One patient developed post-embolization embolic ischemic changes with transient neurological deficits that were resolved within several hours. No permanent cranial nerve deficits, vascular injuries, or tumor recurrences were observed. Pathology confirmed paraganglioma in all cases. Conclusions: Surgical resection remains an effective treatment for CBTs, which are commonly managed by vascular or head and neck surgeons. This case series illustrates the technical feasibility of CBT resection using a comprehensive neurosurgical strategy that integrates endovascular preparation, cerebral perfusion assessment, and meticulous microsurgical technique. Rather than proposing novel surgical innovation, this report aims to provide a structured operative framework and detailed video-based illustration of complex carotid bifurcation management from a neurosurgical perspective. Full article

White mold caused by Sclerotinia sclerotiorum (Lib.) de Bary continues to threaten yield and quality and remains a stubborn, sometimes unpredictable constraint in many cropping systems. The pathogen’s broad host range and its capacity to persist for years as sclerotia mean that fields can carry risk long after visible symptoms fade. Disease development is often driven by short windows of favorable temperature and moisture that promote germination and ascospore release and dispersal, while myceliogenic infection from soil-borne sclerotia can also initiate disease directly. Yet dependable control is still undermined by durable inoculum, limited stable host resistance, variable biocontrol performance, and shrinking chemical options together with fungicide resistance risk. Here we consolidate current understanding and ongoing uncertainties around sclerotial formation and germination cues, the environmental drivers that shape epidemic onset, and the processes governing host colonization, including the roles of cell wall-degrading enzymes, oxalic acid, and redox regulation, as well as the continuing debate over necrotrophic versus hemibiotrophic phases. Management is considered from a practical perspective, covering cultural risk reduction, forecasting-guided fungicide programmes supported by resistance-management principles, and biological control strategies targeting sclerotia. Across systems, the evidence points to the same lesson: single tactics rarely remain reliable under field variability, whereas integrated packages that reduce soil inoculum and align interventions with risk are more durable. Future priorities include resolving early infection events, improving prediction of carpogenic germination under changing climates, increasing the consistency of biocontrol, and accelerating resistance breeding supported by genomic resources. Full article