Search Results (193)

For decades, cervical insufficiency (CI) has been framed predominantly as a mechanical failure of the cervix resulting in painless mid-trimester dilatation. This disease-centered paradigm, reinforced by clinical teaching and administrative coding, does not fully capture the dynamic and biologically integrated nature of cervical remodeling. Accumulating evidence suggests that cervical change is governed by coordinated mechanical, inflammatory, and immunologic interactions rather than by a purely anatomic defect. To outline a process-oriented conceptual framework that situates CI within the broader preterm-birth continuum, this perspective aims to integrate biomechanical, inflammatory, and immunologic dimensions of cervical remodeling and to emphasize that infection- and inflammation-related changes represent dynamic, potentially modifiable elements that may inform more individualized, biology-guided clinical decision-making. This Perspective traces the evolution from a traditional “disease entity” interpretation of CI toward a more integrated view of cervical remodeling as a dynamic, biology-responsive process. Emerging data suggest that when intra-amniotic infection or inflammation is appropriately managed, cervical competence may be partially restored, and mechanical support can be applied more safely in selected patients. Clinical observations indicate that infection-controlled cerclage is associated with meaningful prolongation of gestation. Earlier reports describing double-level mechanical reinforcement techniques conceptually align with contemporary interpretations of infection-controlled emergent cerclage by linking surgical timing with the underlying biology of cervical change. Rather than proposing a prescriptive management pathway, this framework highlights how mechanical, inflammatory, and immunologic factors may interact across heterogeneous CI etiologies and how individualized intervention may be guided by biologic context. Understanding CI as a dynamic rather than a fixed condition provides a framework that integrates its mechanical, inflammatory, and immunologic dimensions within the preterm birth continuum. Such a perspective encourages individualized, biology-informed interpretation of cervical change and supports more context-specific use of established interventions such as cerclage. By emphasizing developmental processes rather than a static defect, this approach seeks to bridge classical clinical practice with contemporary insights into cervical remodeling. Full article

A thermo-mechanical fracture modeling is proposed to address thermal failure issues, where the temperature field is calculated by a heat conduction model based on classical continuum mechanics (CCM), while the deformation field with discontinuities is calculated using the peridynamic (PD) model. The model is calculated using a CCM/PD alternating solution based on finite element discretization, which ensures the calculation accuracy and facilitates engineering applications. The original PD model defines damage solely based on the number of broken bonds in the vicinity of the material point, neglecting the distribution of these bonds. To address this limitation, a new definition of the PD damage accounting for both the number of broken bonds and their specific distribution is proposed. As a result, damage in various directions can be captured, enabling more realistic thermal fracture simulations based on a unified mesh discretization. The effectiveness of the proposed model is validated by comparing numerical examples with analytical solutions. Moreover, simulation results, including a thermal shock case with a transient temperature field, demonstrate the model’s ability to aid in understanding the initiation and propagation mechanisms of complex thermal fractures. Full article

This paper investigates land-use as the cornerstone of spatial planning in rapidly urbanising contexts, focusing on the critical gaps at the mesoscale between centralised vision and local implementation. By exploring Java’s complex desakota landscapes, this study employs an innovative GIS-based land-use cluster analysis using multidimensional parameters—including slope, population density, agricultural land, forest cover, and surface water—to categorise land-use patterns. The resulting mesoscale clusters reveal cohesive functional territories that transcend traditional political boundaries, articulating distinctive ‘mixtures’ of urbanity within Java’s rural-urban continuum. This approach not only captures socio-environmental dynamics across administrative silos but also establishes a new strategic framework for regional planning challenges. By advancing boundary-making beyond mere political convention to reflect on-the-ground ecological and functional coherence, this framework responds to the urgent global challenge of reconciling accelerating suburban and regional development pressures with the preservation of local communities, agricultural systems, and natural landscapes. Full article

Although there have been advancements in stroke treatment (reperfusion) therapy, and it has been shown that many individuals continue to suffer from partial recoveries and continuing decline in their neurological status as a result of suffering a stroke, a primary barrier to providing precise care to patients with stroke continues to be the inability to capture changes in molecular and cellular programs over time and in biological compartments. This review synthesizes evidence that represents the entire continuum of ischemia, beginning with acute metabolic failure and excitotoxicity, and ending with immune response in the nervous system, reprogramming of glial cells, remodeling of vessels, and plasticity at the level of networks, and organizes this evidence in a temporal framework that includes three biological compartments:central nervous system tissue, cerebrospinal fluid, and peripheral blood. Additionally, this review discusses new technologies which enable researchers to discover biomarkers at an extremely high resolution, including single-cell and spatial multi-omics, profiling of extracellular vesicles, proteoform-resolved proteomics, and glymphatic imaging, as well as new computational methods and machine-learning algorithms to integrate data from multiple modalities and predict trajectories of disease progression. The final section of this review will provide an overview of translationally relevant and ethically relevant issues regarding the deployment of predictive biomarkers, such as privacy, access, equity, and fairness, and emphasize the importance of global coordination of research efforts in order to ensure the clinical applicability and global equity of biomarker-based diagnostics and treatments. Full article

REM sleep behavior disorder (RBD) represents a prodromal manifestation of Parkinson’s disease (PD), reflecting the breakdown of inhibitory networks extending from the brainstem to the cortex. This review synthesizes pathological, physiological, and behavioral evidence to illustrate how early α-synuclein pathology disrupts REM-sleep atonia and motor automaticity through degeneration of pontomedullary and cholinergic–inhibitory circuits. The resulting failure of inhibitory precision links nocturnal REM sleep without atonia to daytime gait and postural abnormalities, framing RBD as a dynamic systems disorder rather than a purely sleep-related phenomenon. By examining this continuum across neurophysiological, behavioral, and clinical domains, the review highlights current knowledge gaps, particularly regarding the temporal dynamics of degeneration and compensation. It further integrates multimodal biomarkers that capture these transitions in vivo and discusses therapeutic strategies aimed at preserving inhibitory network integrity and delaying phenoconversion to overt Parkinsonian syndromes. Full article

Volume electron microscopy (Volume-EM) has transformed structural cell biology by enabling nanometre-resolution imaging across cellular and tissue scales. Serial-section TEM, Serial Block-Face Scanning Electron Microscopy (SBF-SEM), Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) and multi-beam SEM now routinely generate terabyte-scale volumes that capture organelles, synapses and neural circuits in three dimensions, while cryogenic Volume-EM extends this landscape by preserving vitrified, fully hydrated specimens in a near-native state. Together, these room-temperature and cryogenic modalities define a continuum of approaches that trade off volume, resolution, throughput and structural fidelity, and increasingly interface with correlative light microscopy and cryo-electron tomography. In parallel, advances in computation have turned Volume-EM into a data-intensive discipline. Multistage preprocessing pipelines for alignment, denoising, stitching and intensity normalisation feed into automated segmentation frameworks that combine convolutional neural networks, affinity-based supervoxel agglomeration, flood-filling networks and, more recently, diffusion-based generative restoration. Weakly supervised and self-supervised learning, multi-task objectives and human-AI co-training mitigate the scarcity of dense ground truth, while distributed storage and streaming inference architectures support segmentation and proofreading at the terascale and beyond. Open resources such as COSEM, MICRONS, OpenOrganelle and EMPIAR provide benchmark datasets, interoperable file formats and reference workflows that anchor method development and cross-laboratory comparison. In this review, we first outline the physical principles and imaging modes of conventional and cryogenic Volume-EM, then describe current best practices in data acquisition and preprocessing, and finally survey the emerging ecosystem of AI-driven segmentation and analysis. We highlight how cryo-Volume-EM expands the field towards native-state structural biology, and how multimodal integration with light microscopy, cryo-electron tomography (cryo-ET) and spatial omics is pushing Volume-EM from descriptive imaging towards predictive, mechanistic, cross-scale models of cell physiology, disease ultrastructure and neural circuit function. Full article

Kiwifruit (Actinidia spp.) is valued for its sensory quality and nutritional richness but faces postharvest challenges such as rapid softening, chilling injury, and physiological disorders. Conventional management strategies help maintain quality yet insufficient to capture the complexity of ripening, stress physiology, and cultivar-specific variation. Recent research emphasizes the continuum from preharvest to postharvest, where orchard practices, harvest maturity, and handling conditions influence quality and storage potential. Omics-driven studies, particularly transcriptomics and metabolomics, have revealed molecular networks regulating softening, sugar–acid balance, pigmentation, antioxidant properties, and chilling tolerance. Integrated multi-omics approaches identify key biomarkers and gene–metabolite relationships linked to ripening and stress responses. Complementing omics, nondestructive estimation technologies, including hyperspectral imaging, near-infrared spectroscopy, acoustic profiling, and chemometric models are emerging as practical tools for real-time classification of maturity, quality, and storability. When calibrated with omics-derived biomarkers, these technologies provide predictive, non-invasive assessments that can be deployed across the supply chain. Together, the convergence of postharvest physiology, omics, and nondestructive sensing offers a pathway toward precision quality management and sustainable kiwifruit production. This review synthesizes recent advances across these domains, highlighting mechanistic insights, practical applications, and future directions for integrating omics-informed strategies with commercial postharvest technologies. Full article

This paper presents a systematic literature review (SLR) of research on strategic positioning of companies and the measurement of greenwashing in sustainability reporting. Its main aim is to synthesize and organize the existing literature, identify key research gaps, and outline directions for future studies. Drawing on a rigorous content analysis of 88 studies, we delineate strategic typologies of greenwashing in sustainability reporting and examine content-analysis-based measurement approaches used to detect it. Our SLR shows that most strategic typologies draw on theories such as legitimacy theory, impression management theory, signaling theory, and stakeholder theory. Several studies adopt a four-quadrant matrix with varying conceptual dimensions, while others classify strategic responses to institutional pressures along a passive–active continuum. However, the evidence suggests that to assume that companies uniformly pursue sustainability reporting strategies is a major oversimplification. The findings also indicate that the literature proposes a variety of innovative, content-analysis-based approaches aimed at capturing divergences between communicative claims and organizational realities—most notably, discrepancies between disclosure and measurable performance, and between symbolic and substantive sustainability actions, as well as the identification of selective or manipulative communication practices that may signal greenwashing. Analytical techniques commonly focus on linguistic and visual cues in sustainability reports, including tone (sentiment and narrative framing), readability (both traditional readability indices and machine learning–based textual complexity measures), and visual content (selective emphasis, imagery framing, and graphic distortions). We also synthesize studies that document empirically verified instances of greenwashing and contrast them with research that, in our view, relies on overly simplified or untested assumptions. Based on this SLR, we identify central theoretical and methodological priorities for advancing the study of greenwashing in sustainability reporting and propose a research agenda to guide future research. Full article

Grapevine water relations are increasingly influenced by drought under climate change, with significant implications for yield, fruit composition and wine quality. Stable isotopes of hydrogen, oxygen, carbon and nitrogen (δ²H, δ¹⁸O, δ¹³C and δ¹⁵N) provide sensitive tracers of plant water sources and physiological responses to stress. Here, we combined dual water isotopes (δ²H, δ¹⁸O), carbon and nitrogen isotopes (δ¹³C, δ¹⁵N), and high-resolution micrometeorological/soil observations to diagnose drought dynamics in Vitis vinifera cv. Sauvignon blanc (Orlești, Romania; 2023–2024). Dual-isotope relationships delineated progressive evaporative enrichment along the soil–plant–atmosphere continuum, with slopes LMWL ≈ 6.41 > stem ≈ 5.0 > leaf ≈ 2.2, consistent with kinetic fractionation during transpiration (leaf) superimposed on source-water signals (stem). Weekly leaf δ¹⁸O covaried strongly with relative humidity (RH; r = −0.69) and evapotranspiration (ET; r = +0.56), confirming atmospheric control of short-term enrichment, while stem isotopes showed buffered responses to soil water. We integrated Δ¹⁸O (leaf–stem), RH, ET, and soil matric potential at 60 cm (Soil₆₀) into an Isotopic Drought Index (IDI), which captured the onset, intensity, and persistence of the July–August 2024 drought (IDI_0–100 > 90; RH < 60%, ET > 40 mm wk⁻¹, Soil₆₀ > 100 cb). Carbon and nitrogen isotopes provided complementary, integrative diagnostics: δ¹³C increased (less negative) with drought (r = −0.52 with RH; +0.49 with IDI), reflecting higher intrinsic water-use efficiency, whereas δ¹⁵N rose with soil dryness and IDI (leaf: r ≈ +0.48 with Soil₆₀; +0.42 with IDI), indicating constraints on N acquisition and enhanced internal remobilization. Together, multi-isotope and environmental data yield a mechanistic, field-validated framework linking atmospheric demand and edaphic limitation to vine physiological and biogeochemical responses and demonstrate the operational value of an isotope-informed drought index for precision viticulture. Full article

Determining the postmortem interval remains one of the most persistent and fragmented challenges in forensic science. Conventional approaches—thermal, biochemical, molecular, or entomological—capture only isolated fragments of a single physical reality: the irreversible drift of a once-living system toward equilibrium. This Perspective proposes a unifying paradigm in which death is understood as a progressive rise in entropy, encompassing the loss of biological order across thermal, chemical, structural, and ecological domains. Each measurable postmortem variable—temperature decay, metabolite diffusion, macromolecular breakdown, tissue disorganization, and microbial succession—represents a distinct expression of the same universal law. Within this framework, entropy becomes a dimensionless index of disorder that can be normalized and compared across scales, transforming scattered empirical data into a coherent continuum. A Bayesian formulation further integrates these entropic signals according to their temporal reliability, yielding a probabilistic, multidomain equation for PMI estimation. By merging thermodynamics, information theory, and biology, the concept of death as rising entropy offers a comprehensive physical description of the postmortem process and a theoretical foundation for future computational, imaging, and metabolomic models in forensic time analysis. Full article

This study introduces a comprehensive three-dimensional micromechanical framework to capture the nonlinear mechanical behavior of diverse composite materials, including coupled elastic degradation, inelastic strain evolution, and phenomenological failure in their constituents. The primary objective is to integrate a generalized elastic degradation–inelasticity (EDI) model into the parametric high-fidelity generalized method of cells (PHFGMC) micromechanical approach, enabling accurate prediction of nonlinear responses and failure mechanisms in multi-phase composites. To achieve this, a unified three-dimensional orthotropic EDI modeling formulation is developed and implemented in the PHFGMC. Grounded in continuum mechanics, the EDI employs scalar field variables to quantify material damage and defines an energy potential function. Thermodynamic forces are specified along three principal directions, decomposed into tensile and compressive components, with shear failure accounted for across the respective planes. Inelastic strain evolution is modeled using incremental anisotropic plasticity theory, coupling damage and inelasticity to maintain generality and flexibility for diverse phase behaviors. The proposed model offers a general, unified framework for modeling damage and inelasticity, which can be calibrated to operate in either coupled or decoupled modes. The PHFGMC micromechanics framework then derives the overall (macroscopic) nonlinear and damage responses of the multi-phase composite. A failure criterion can be applied for ultimate strength evaluation, and a crack-band type theory can be used for post-ultimate degradation. The method is applicable to different types of composites, including polymer matrix composites (PMCs) and ceramic matrix composites (CMCs). Applications demonstrate predictions of monotonic and cyclic loading responses for PMCs and CMCs, incorporating inelasticity and coupled damage mechanisms (such as crack closure and tension–compression asymmetry). The proposed framework is validated through comparisons with experimental and numerical results from the literature. Full article

Introduction: In recent decades, the burden of mental disorders has become a major determinant of population health in the European Union, generating profound clinical, socioeconomic, and institutional consequences. Despite political recognition of this silent crisis, substantial methodological challenges persist in the transnational monitoring of mental health and in linking disease burden with the resources allocated to address it. The present analysis develops a multivariate taxonomy of EU Member States from a psychosocial perspective, using an integrative quantitative approach. Methods: This cross-sectional, comparative study follows international standards for transparent and reproducible quantitative reporting and is based on 18 harmonized clinical, epidemiological, and institutional indicators collected for 27 EU Member States over the period 2014–2023. The indicators used in this study were grouped according to their position along the care continuum. Hospital-based indicators refer to inpatient activity and institutional capacity, including total hospital discharges, psychiatric admissions (affective disorders, schizophrenia, dementia, alcohol- and drug-related disorders), and hospital bed availability. Outpatient and community-level indicators reflect the capacity of systems to provide non-hospital psychiatric care and consist primarily of psychiatrist density and total specialist medical workforce. Finally, subjective perception indicators capture population-level self-assessed health status, complementing clinical and institutional measures by integrating a psychosocial perspective. After harmonization and standardization, Principal Component Analysis (PCA) with Varimax rotation was applied to identify latent dimensions of mental health. Model adequacy was confirmed using the Kaiser–Meyer–Olkin coefficient (0.747) and Bartlett’s test of sphericity (p < 0.001). Results: Three latent dimensions explaining 77.7% of the total variance were identified: (1) institutionalized psychiatric burden, (2) functional capacity of the health care system, and (3) suicidal vulnerability associated with problematic substance use. Standardized factor scores allowed for the classification of Member States, revealing distinct patterns of psychosocial risk. For example, Germany and France display profiles marked by high levels of institutionalized psychiatric activity, while the Baltic and Southeast European countries exhibit elevated suicidal vulnerability in the context of limited medical resources. These results highlight the deep heterogeneity of psychiatric configurations in Europe and reveal persistent gaps between population needs and institutional response capacity. Conclusions: The analysis provides an empirical foundation for differentiated public policies aimed at prevention, early intervention, and stigma reduction. It also supports the case for institutionalizing a European mental health monitoring system based on harmonized indicators and common assessment standards. Overall, the findings clarify the underlying structure of mental health across the European Union and underscore the need for coherent, evidence-based strategies to reduce inequalities and strengthen system performance at the continental level. Full article

Nanostructures, such as carbon nanotubes (CNTs), graphene, nanoplates, etc., show behaviors that classical continuum theories cannot capture. At the nanoscale, size effects, surface stresses, and nonlocal interactions become important, so new models are needed to study nanostructures. The main nanomechanics theories that are used in recently published papers include nonlocal elasticity theory (NET), couple stress theory (CST), and nonlocal strain gradient theories (NSGTs). To solve these models, methods such as finite elements, isogeometric analysis, mesh-free approaches, molecular dynamics (MD), etc., are used. Also, this review categorizes and summarizes the major theories and numerical methods used in nanomechanics for the analysis of nanostructures in recently published papers. Recently, machine learning methods have enabled faster and more accurate prediction of nanoscale behaviors, offering efficient alternatives to traditional methods. Studying these theories, numerical models and data driven approaches provide an important foundation for future research and the design of next generation nanomaterials and devices. Full article

Fatigue damage is critical for 0Cr17Ni4Cu4Nb stainless-steel components that may operate near yield under stress-controlled cycles and occasional peak holds. This work investigates the cyclic response of 0Cr17Ni4Cu4Nb stainless-steel under near-yield-stress-controlled (NYSC) loading and proposes a unified damage framework that bridges monotonic ductile fracture, near-yield stress-controlled fatigue. Building on the Enhanced Lou-Yoon model, an elastic-damage term is introduced and embedded within a continuum damage mechanics framework, allowing elastic (sub-yield) and plastic (post-yield, Ultra-Low-Cycle-Fatigue/Low-Cycle-Fatigue (ULCF/LCF)) damage to be treated in a unified, path-averaged stress-state description defined by stress triaxiality and the Lode parameter. Five stress-controlled test groups are examined, with applied load amplitudes from 20.6 to 25.1 kN (equivalent stress amplitudes 858~1044 MPa) yielding fatigue lives ranging from 32 to 13,570 cycles. The extended model captures the evolution of damage origin mechanisms from elasticity-dominated to plasticity-dominated as loading severity increases, demonstrating a unified elastic-plastic damage modeling approach. As a result, it accurately predicts fatigue lives spanning two orders of magnitude with an average absolute percentage error of approximately 14.5% across all conditions. Full article

The increasing demand for sustainable engineering solutions has driven extensive research into natural fibre-reinforced composites (NFCs), notably flax fibre-reinforced polymers (FFRPs), which offer promising eco-friendly alternatives to synthetic composites. This study presents a comprehensive application of continuum damage mechanics (CDM) methodology to unidirectional (UD) FFRPs, addressing critical gaps in predictive modelling of progressive intralaminar damage for sustainable structural applications. A systematic experimental characterisation protocol was developed to identify material parameters that account for the inherent variability and complex nonlinear behaviour of natural fibres. The CDM model was calibrated using comprehensive quasi-static testing on multiple laminate configurations and validated through finite element analysis (FEA) in Siemens Simcenter Samcef. The model accurately captures the nonlinear behaviour and damage mechanisms of notched flax–epoxy laminates, achieving prediction accuracies of 97.61% and 88.98% for the force-displacement response in open-hole tensile (OHT) validation tests. Integrating experimental characterisation with FEA enables robust virtual prototyping of sustainable composite structures, supporting design optimisation and lifecycle assessment. This research establishes validated damage modelling methodologies for eco-friendly NFC, facilitating accelerated adoption in automotive, marine, and construction sectors. Full article