Search Results (778)

Compound flash drought–heatwave extremes (FDHW) expose vegetation to rapid water and heat stress, but regional assessments often conflate event detection with vegetation response and rarely resolve delayed canopy trajectories. We quantified FDHW across China’s Northeast Black Soil Region during the 1995–2024 growing seasons using ERA5-Land soil-moisture and temperature thresholds, applied a spatiotemporal graph neural network to regularize threshold-derived event masks, and reserved AVHRR NDVI for independent post-event impact assessment. Flash drought and FDHW frequencies exhibited strong interannual variability rather than a significant monotonic trend. FDHW occurrence increased from 3.8 to 4.8 d per growing season between 1995–2005 and 2016–2024, but the Theil–Sen trend was near zero (0.05 d per decade). Land–atmosphere composites indicate progressive soil-moisture depletion before FDHW occurrence and a transition from latent to sensible heat release roughly three days before maximum temperature anomalies. NDVI composites revealed a delayed greenness response: anomalies were negative through the first two post-event weeks, reached their minimum approximately one week after the reference FDHW grid-day, and then partially recovered during days 16–30. Mean NDVI suppression was modest (short-term −0.009; long-term −0.006), but persistent negative anomalies remained in 12.1% of southern cropland-dominant trajectories and 10.7% of northern forest–crop ecotone trajectories. These results show that FDHW impacts in the NBSR are expressed less as a steady rise in event frequency than as delayed and spatially heterogeneous vegetation stress, highlighting the need for post-event monitoring windows and cross-sensor validation to support agricultural risk assessment and adaptation planning. Full article

Ozone (O₃), as a key secondary pollutant, exhibits pronounced spatiotemporal heterogeneity, posing significant challenges to coordinated regional air pollution control. However, systematic understanding of high-resolution O₃ spatial inversion and its driving mechanisms in arid urban agglomerations remains limited. In this study, the Tianshan North Slope Urban Agglomeration (TNSUA) was selected as the study area, and a multi-model comparative framework was established to comprehensively evaluate the O₃ inversion performance of 16 machine learning and deep learning models, including Extreme Gradient Boosting (XGBoost), Random Forest (RF), Extremely Randomized Trees (ET), and Gradient Boosting Decision Tree (GBDT). Based on the optimal model performance, high-precision daily O₃ spatial reconstruction for the year 2023 was achieved across the study region. The contributions of individual driving factors and their nonlinear response relationships were quantitatively interpreted using Shapley Additive Explanations (SHAP). Furthermore, a backward trajectory model combined with the Weighted Potential Source Contribution Function (WPSCF) and Weighted Concentration Weighted Trajectory (WCWT) methods was employed to identify potential source regions and transport pathways of O₃. The results indicate that: (1) The XGBoost model exhibited the best performance (R² = 0.93, RPD > 3). The reconstructed results reveal that high O₃ concentrations in 2023 were primarily distributed in southern Urumqi, southern Changji, and southern Tacheng, with southern Urumqi identified as the most prominent hotspot. (2) The spatial variability of O₃ was predominantly driven by downward shortwave radiation (DSR) and air temperature (TEM), both of which showed significant nonlinear responses and threshold effects on O₃ formation. (3) Source apportionment analysis indicates that westerly transport serves as a major exogenous contribution pathway, with potential source regions mainly located in the surrounding areas of the northern Tianshan slope as well as Central Asia, particularly eastern Kazakhstan and northern Kyrgyzstan. This study systematically elucidates the formation mechanisms of O₃ pollution in arid urban agglomerations from three aspects—high-precision inversion, driving mechanism analysis, and cross-regional transport identification—thereby providing a scientific basis for precise air pollution control strategies. Full article

The accurate prediction of parturition in managed beluga whales (Delphinapterus leucas) is fundamental for optimizing maternal and neonatal care; however, reliable predictive indicators remain limited. Here, eight pregnancies (five live births and three adverse pregnancy outcomes) monitored over 25 years at a single facility were retrospectively analyzed. The rectal temperatures, serum progesterone concentrations, gestation lengths, food intake, behavioral changes, and fetal heart rates of the whales were evaluated, particularly prepartum. Five successful pregnancies exhibited consistent seasonal timing and reproducible endocrine and physiological trajectories. The mean gestation length was 466 ± 8.4 days. The rectal temperatures of dams that delivered live offspring decreased by 1.6 ± 0.5 °C approximately 1.3 ± 0.5 days before parturition. In successful pregnancies, serum progesterone concentrations declined prepartum but typically remained detectable until parturition. In contrast, a concentration of approximately 1 ng/mL prior to parturition was observed in the pregnancy that resulted in stillbirth. Adverse pregnancy outcomes were associated with deviations from the patterns observed in successful pregnancies, including abnormal gestation length, notably reduced progesterone concentrations, altered fetal heart rate trajectories, and ultrasonographic evidence of fetal cranial asymmetry. These findings highlight the importance of integrated multimodal monitoring in predicting parturition and identifying abnormal pregnancy progression in managed beluga whales. Full article

This study presents a meta-analysis of relatively high-resolution paleohydrological proxies derived from geological archives in Sardinia and in the Italian Peninsula–Sicily over the last 2000 years, with particular emphasis on the Medieval Warm Period (MWP) and the Little Ice Age (LIA). The investigated climate proxies, ranging from annual-decadal to centennial resolution, include terrestrial and marine sediment cores, glaciers, pollen spectra, speleothems, lake-level fluctuations, as well as sedimentary and geomorphological inventories. Such datasets were analyzed through holistic and stratigraphic approaches along West–East and North–South transects across the central Mediterranean. Limited temporal resolution and incomplete stratigraphic continuity of several paleoclimatic records from the investigated regions thwart full reconstructions of paleohydrological trends. Nevertheless, the presented meta-analysis has enabled: (1) the recognition of reliable paleoclimatic correlations between the two regions, which exhibit long-lasting anti-phase hydroclimatic trends (wetter conditions in Sardinia and drier conditions in central Italy during the MWP, with the opposite pattern during the LIA); and (2) the identification of the North Atlantic Oscillation (NAO) as the primary driver of these paleohydrological variations. The significance of this anti-phase pattern is discussed in the context of the North–South and West–East climatic dipoles identified in the Mediterranean region during the middle to late Holocene. Furthermore, we assessed the potential of the investigated paleohydrological network to: (1) compare reconstructed hydrological patterns with mean temperature and precipitation records derived from empirical and model-based climate reconstructions in southern Europe and the Mediterranean; and (2) identify gaps in data coverage that currently limit our understanding of high-resolution spatiotemporal hydrological variability and dynamics.The hydroclimatic pattern in Sardinia and in the Italian Peninsula–Sicily has exhibited marked spatio-temporal divergences, with major hydroclimatic transitions coincident with well-known solar minima over the last millennium, thus suggesting a possible cause-and-effect relationship. The interpretations presented in this study provide a framework for understanding how changes in the paleoclimatic variability of water resources may have influenced different regions of Italy since the Middle Ages, potentially affecting societal transitions as well as historical and socioeconomic dynamics. Comparison of the multidecadal-to-centennial reconstructions of paleohydrological patterns is presented for both areas, pending the development of new, higher-resolution, and more precisely dated proxies from the Italian records. Their importance is emphasized in order to improve reconstructions of past climate variability and to enhance assessments of future climate trajectories. Full article

Dissolved oxygen (DO) is a critical water quality parameter in aquaculture systems. Low DO events can stress, limit the growth of, or even cause mortality of aquatic life in aquaculture systems and require rapid management decisions. This study presents a process-based approach for short-term DO forecasting that is intended to support rapid deployment and transferability across various aquaculture systems. Future DO is computed using a mass-balance equation driven by daily stream metabolism and reaeration coefficients estimated from the previous 24 h of weather and water observations. These coefficients are combined with the next day’s observed water temperature, atmospheric pressure, photosynthetically active radiation, and salinity to predict DO 24 h ahead under idealized measured-input conditions with a ten-minute resolution. Model performance was evaluated across multiple aquaculture ponds with varying aeration techniques by assessing prediction accuracy of daily DO minimums using a safety-based metric and full-day DO trajectories using root mean square error. The model successfully predicted 91.77% of DO drops below 6 mg/L within 1 mg/L in a consistently aerated artificial pond and achieved high success in a natural watershed system. Performance was reduced in systems with highly variable aeration. Prediction accuracy was the highest in surface locations away from aerators. These results indicate that a minimal-history process-based framework can identify low DO risk under idealized measured-input conditions, particularly in surface locations away from aerators and in systems with constant or natural aeration. Full article

Purpose: This study aimed to develop and validate a comprehensive multi-sensor integrated platform for objective assessment of skeletal muscle recovery kinetics following exercise-induced muscle damage (EIMD), combining biomechanical, thermal, and biochemical monitoring modalities. Methods: Forty elite male athletes were randomized to microwave diathermy (MWD, n = 20, 2.45 GHz, 160 W, 45 min/session) or control (n = 20) groups. Time-synchronized multi-sensor assessments at baseline, 24 h, 48 h, and 72 h post-EIMD included: biomechanical sensors (knee flexion range of motion via goniometry and isokinetic peak torque), thermal sensor (skin surface temperature via infrared thermometry), and biochemical sensor array (serum CK, IL-6, and CRP via high-sensitivity ELISA). Two-way repeated-measures ANOVA with Bonferroni correction examined group × time interactions across all sensor channels. Results: Pre-study validation confirmed high reliability across all sensor modalities. Cross-modality concordance analysis revealed significant correlations between biomechanical and biochemical recovery trajectories (isokinetic torque vs. IL-6: r = −0.73, p < 0.001; pain vs. IL-6: r = 0.68, p < 0.001). MWD intervention demonstrated accelerated recovery across all sensor channels: complete ROM recovery by 48 h (MWDG post-2 vs. baseline, p > 0.05; CG post-3 43% below baseline, p < 0.001), complete isokinetic torque restoration by 72 h (MWDG post-3 vs. baseline, p > 0.05; CG 44% below baseline, p < 0.001), and near-complete pain resolution (VAS 1.70 ± 2.50 mm, p < 0.05). Biomarker sensors demonstrated differential recovery kinetics: IL-6 normalized by 48 h (1.52 ± 0.14 pg/mL, p > 0.05 vs. baseline), CRP approached baseline by 72 h (0.73 ± 0.24 mg/L, p > 0.05), while CK remained elevated at post-3 (169.70 ± 22.58 U/L, 30% above baseline, p < 0.001), indicating incomplete myofiber membrane integrity recovery despite resolution of systemic inflammatory markers. The control group exhibited persistent deficits across all sensor channels with no clinically meaningful recovery. Conclusions: This study validated an integrated multi-sensor platform for recovery assessment. Microwave diathermy demonstrated efficacy by 72 h with complete functional recovery and inflammatory normalization (though CK remained elevated). Cross-modality concordance (r = −0.73 to 0.68) confirmed superior assessment compared to single-modality approaches. This laboratory-based methodology provides a framework for future portable sensor systems in athletic surveillance. Full article

Hydrocarbon biodegradation in cold environments is constrained not only by microbial catabolic capacity but also by interfacial access to poorly soluble substrates and by the way remediation materials interact with microbial envelope-related structures. This study presents an uncertainty-aware low-temperature computational screening workflow for prioritizing functionalized oxide surface-patch models that may favor hydrocarbon association while avoiding excessive perturbation of simplified microbial-interface proxies. Twelve finite oxide–ligand candidates derived from TiO₂, ZnO, and CeO₂ patches functionalized with bare, catechol, glycerol, or citric acid states were evaluated against three hydrocarbon probes, hexane, toluene, and naphthalene, and two microbial-interface proxies. The workflow combined GFN2-xTB geometry optimization and relative interaction-energy screening, clean GFN2-xTB/ALPB rescoring with rescue tracking, short xTB-MD perturbation analysis, ORCA refinement of selected candidates, sensitivity analysis of ranking parameters, and integrated evidence classification. The analysis supports interfacial selectivity, rather than maximum adsorption strength, as the central design principle. TiO₂–catechol and TiO₂–glycerol remain experimentally testable primary candidates because their original screening profile combines chemically interpretable hydrocarbon association with comparatively mild microbial-proxy interaction descriptors. ZnO–catechol and ZnO–glycerol emerged as sensitivity-competitive secondary candidates under several scoring assumptions. Completed short xTB-MD trajectories further showed that TiO₂–glycerol produced moderate perturbation against the peptide proxy, whereas TiO₂–glycerol against NAG and ZnO–catechol against the peptide proxy showed very high proxy displacement. Overall, the workflow provides a transparent prioritization framework for experimental validation. Full article

The Ningxia Yellow River Urban Agglomeration, located in the ecologically fragile arid and semi-arid zone of the upper Yellow River, serves as a critical spatial carrier for maintaining the ecological security of the Yellow River Basin and supporting the regional economy and population agglomeration in Ningxia. Driven by rapid urbanization, intensified human–land conflicts have induced widespread ecological degradation and unbalanced water–soil resource allocation across the region. Based on land use data from 2010, 2015, 2020 and 2023, we applied the land use transition matrix, land use dynamic degree and standard deviational ellipse to characterize the spatiotemporal patterns of spatial expansion of the Ningxia Yellow River Urban Agglomeration over the past decade. The Patch-generating Land Use Simulation (PLUS) model was further employed to predict the land use demand and spatial distribution of the study area under diverse scenarios in 2035. The research results reveal three key findings. First, grassland, cropland and unused land constitute the dominant land use types across the study region, jointly occupying more than 90% of the total territorial area. Over the past decade, regional land use has undergone noticeable changes: grassland area has continuously declined, cropland and built-up land have sustained steady expansion, and water areas have experienced a mild reduction. Land use conversions mainly occur among grassland, cropland and built-up land. Second, driving factors vary substantially in their spatial contributions to the expansion of different land use types. The spatial growth of cropland and built-up land is comprehensively shaped by terrain conditions, economic development and transportation location superiority. In comparison, the distribution and dynamic changes in forestland, grassland and water areas are predominantly restricted by natural elements, including precipitation, temperature and soil characteristics. Third, multi-scenario simulation results verify that differentiated territorial spatial planning and regulatory policies profoundly affect the evolutionary trajectory of regional territorial patterns. The natural development scenario experienced the most intensive expansion of built-up land, with a newly increased area of 181.11 km². The ecological protection scenario can effectively curb the loss of ecological land and minimize the shrinkage of grassland resources. The cropland protection scenario is conducive to stabilizing cropland scale to the greatest extent and restraining the disorderly sprawl of urban land. The sustainable development scenario realizes coordinated and balanced changes in all land use types and delivers mutually beneficial progress between regional ecological conservation and socioeconomic development. Full article

Petrology and geochemistry reconstruct from plutons and eruptive products the underground chemical and thermodynamic conditions of magma at the time of crystallization. Accretionary layers in crystals record the composition of the surrounding melt, as well as the confining pressure and temperature. Such a backward reconstruction should be paired with a forward computation of the solidifying crystals during their transport in convective motions inside a refilled magmatic reservoir. This work develops a framework for the solution of magma fluid-dynamics and for the related Lagrangian trajectories of suspended crystals. Episodes of magma mixing due to injection of fresh magma into a shallow chamber are simulated at first in a Eulerian reference system. Afterwards, the Lagrangian trajectories of passive tracers are computed, tracking the magma composition, pressure and temperature through which these particles move. On the base of the compositional, pressure and temperature conditions, the crystallizing phases are computed with the MELTS code. The history of accretionary layers is thus obtained by interface-controlled growth and solid-state diffusion. Our results show that crystals residing in different parts of the underground system acquire a distinctive signature and are well mixed together. A small population will register the successive refilling episodes, while a substantial one will record each fresh injection. Full article

With the rapid development of cross-border collaboration, intelligent port construction, and international logistics networks, large volumes of multisource heterogeneous data are continuously generated during cross-border circulation. To address the limitations of traditional financial review and compliance auditing methods in characterizing multisource signal coupling, as well as the tendency of conventional deep models to rely on spurious correlated features with insufficient interpretability, a multisource sensing signal fusion and causally explainable risk identification framework is proposed for cross-border trade anomaly detection. In this framework, electronic trade texts, structured financial declaration fields, GPS/AIS trajectories, port weighing records, RFID data, electronic seal status, X-ray inspection images, cold-chain temperature and humidity records, and vibration data are uniformly modeled as multisource sensing signals in cross-border trade and circulation processes. Subsequently, collaborative representation among textual semantics, attribute fields, logistics status, device records, and entity relationships is achieved through a cross-modal alignment mechanism. On this basis, an engineering-constraint-guided causal risk representation module is designed to reduce the interference of spurious correlated factors, such as regions, ports, transportation modes, and textual styles, in model decisions. Meanwhile, a counterfactual anomaly response module is introduced to analyze the influence of key variable changes on risk outputs, thereby enhancing the model’s ability to identify and explain true anomaly-driving factors. Experimental results show that the proposed method achieves the best overall performance in the cross-border trade anomaly detection task, with Accuracy, Precision, Recall, F1-score, AUC, and PR-AUC reaching $0.927$, $0.842$, $0.811$, $0.826$, $0.958$, and $0.817$, respectively, clearly outperforming baseline models including Logistic Regression, Random Forest, XGBoost, BERT, BERT+MLP, and Multimodal Transformer. In cross-time, cross-region, cross-port, and cross-entity testing scenarios, high F1-score and AUC values are still maintained. Under complex conditions such as text noise, missing modalities, logistics trajectory perturbations, and missing sensing records, only limited performance degradation is observed. Ablation experiments further verify the effective contributions of cross-modal attention, contrastive alignment, causal financial debiasing, counterfactual response, and engineering constraints to performance improvement. Full article

Understanding vegetation sustainability is crucial for ensuring ecological security in dryland interior river systems. Focusing on the Manas River Basin in Xinjiang, our research extracted Landsat time-series data from 2000 to 2024 via Google Earth Engine, employing statistical approaches alongside Geodetector modeling to quantitatively evaluate the spatiotemporal dynamics of vegetation sustainability and its influencing factors. Our findings reveal that the basin’s Normalized Difference Vegetation Index (NDVI) displayed a significant upward trajectory (Sen’s slope = 0.010/yr, R² = 0.95, p < 0.01), with distinct temporal phases: the period 2000–2013 was characterized by rapid oasis expansion driven by cultivated land, while the period 2014–2024 was characterized by systematic vegetation improvement with a stabilizing land use pattern. Spatially, areas exhibiting extremely significant improvement accounted for 56.24% of the total basin area (concentrated mainly in artificial oases and the mid-mountain zone), and non-significant degradation accounted for only 1.89%. Land use type and soil texture were identified as the dominant spatial differentiation factors, followed by annual precipitation, with all pairwise factor interactions exhibiting enhancement effects. By identifying the optimal thresholds for vegetation growth (annual average temperature of 0.82–3.96 °C, elevation of 1826–2598 m, and loamy sand), this study defines the boundaries for sustainable vegetation development. These findings deliver a theoretical foundation for zonation management and habitat rehabilitation planning, supplying decision-making support for safeguarding regional ecological security and fostering sustainable development of oasis systems in arid Central Asia. Full article

To address the scarcity of natural archives in historical climate reconstruction, this study utilized the late Ming Dynasty text Jiu Jing Yi Shi (Reminiscences of the Old Capital) as a primary data source to extract botanical and phenological information, aiming to quantitatively reconstruct climate parameters for the Beijing region circa 1644 CE. Using botanical textual research, 11 out of 20 recorded plant names were identified to the species level, 2 to the genus level, and 7 were classified as non-native species. Breaking from the traditional reliance solely on woody plants, we innovatively incorporated three herbaceous species into the coexistence analysis framework to enhance the accuracy of climate reconstruction. By comprehensively comparing four climate indicators—mean annual temperature (MAT), mean temperature of the coldest month (MTCM), mean temperature of the warmest month (MTWM), and annual precipitation (AP)—across three critical nodes (1368 CE, 1644 CE, and the present), this research revealed a “decline-then-rise” trajectory in Beijing’s temperature over the past 600 years, alongside corresponding variations in precipitation patterns. Results indicated that the cooling event in the Beijing region between 1368 CE and 1644 CE was synchronous with global cooling trends during the same period and demonstrated a climatic transition from maritime to continental characteristics in the region. This work not only expands the application of historical literature in paleoclimatology but also provides critical scientific evidence for understanding centennial-scale climate evolution in the East Asian monsoon region and predicting future climate trends. Full article

Reliability prediction of aerospace dormant components requires fusing natural-storage observations at the operating temperature with accelerated-storage testing data at elevated temperatures. Existing scalar-weight fusion methods apply a global weight that cannot reflect the time-varying trustworthiness of the accelerated branch as Arrhenius extrapolation distance grows. Physics-based fusion propagates accelerated-test scatter through least squares but leaves the dominant error source—the degradation-model form itself—unaccounted for, and no method in either class verifies the coverage of its intervals. This paper proposes an empirically calibrated multi-fidelity fusion that selects a mechanism-specific natural-branch degradation model by the corrected Akaike information criterion and augments the accelerated-branch variance with an additive model-form term fitted from natural-storage residuals. This term turns the fusion weight into a continuous, time-varying diagnostic that detects Arrhenius misspecification from training data alone and falls back safely to the natural-only estimate. Prediction intervals are calibrated by split-conformal prediction on a disjoint simulated population, giving finite-sample, distribution-free coverage, and the remaining-storage-life interval follows from the band’s first-passage time. On a 1000-run varying-truth simulation, the calibrated band attains 95.5% trajectory coverage at the narrowest band width among six methods; on the torsion-bar case, the fusion reaches a held-out RMSE of 0.045 N$·$m and a remaining-life interval of 10.4–12.6 years. The model-form variance ratio provides a single-number regime diagnostic across all cases. Full article

Buildings in Lagos require mechanical cooling year-round, with air conditioning accounting for up to 80% of residential electricity consumption. Despite this, the Nigerian Building Code (NB 485:2017) still references 1990s thermal design data, creating a growing mismatch between design assumptions and actual thermal conditions. Compounding background warming and an intensifying urban heat island have widened this gap considerably, yet no study has linked long-term cooling demand trends to quantified engineering design shortfalls for any Nigerian city. This study presents a 35-year cooling degree day (CDD) trend analysis for Lagos (1990–2024), derived from 12,784 daily temperature records at four engineering base temperatures (22 °C, 23.3 °C, 26 °C, and 28 °C) respectively. Trends are detected using the Mann–Kendall test with Trend-Free Pre-Whitening and Sen’s slope as the magnitude estimator. Significantly increasing CDD trends are confirmed at three base temperatures, with a Sen’s slope of +4.55 °C·days yr⁻¹ at the primary design reference of 23.3 °C (p < 0.01). Structural break analysis identifies 2015 as the transition into a persistently above-baseline thermal regime, with mean CDD in the most recent sub-period exceeding the 1990–2001 design baseline by up to 50% at higher base temperatures. The detected trends are translated into three engineering gap analyses: required envelope U-value trajectories, an HVAC capacity undersizing index, and annual thermal cycling frequency as a structural fatigue proxy. Results show that the dominant uninsulated sandcrete typology fails ASHRAE 90.1-2019 Zone 1A prescriptive limits throughout the study horizon, installed HVAC systems are already operating in the engineering caution zone, and façade fatigue loading has intensified markedly since 2015. To the author’s knowledge, this study is the first to couple a statistically robust long-period CDD record for Lagos with code-referenced design gap figures, providing a replicable framework for climate-adaptive building code revision across similar hot–humid climates in sub-Saharan Africa. Full article

Background/Objectives: Biological ageing is accompanied by progressive alterations in mitochondrial metabolism, microvascular function, and thermoregulation. These processes collectively influence tissue heat production and dissipation, reflecting integrated metabolic, vascular, and thermoregulatory activity measurable at the physiological level. Passive microwave radiometry (MWR) provides a non-invasive, radiation-free method for detecting deep-tissue bioenergy emissions, complementing surface infrared thermography. To evaluate a thermophysiological Bioenergetic Index (BEI), derived from deep-tissue microwave emission, surface temperature, and their spatial and deep–surface relationships, as a candidate age-referenced thermophysiological marker associated with chronological ageing. Methods: Breast thermophysiology measurements from 36,391 women aged 20–80 years were analysed using data collected during routine clinical assessments. Supervised machine-learning models were trained exclusively on thermal features, with chronological age used only as the prediction target. Model performance was assessed using mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R²). In addition, data were aggregated into 5-year age bins to evaluate population-level ageing trajectories. Results: At the individual level, models predicted chronological age with MAE ≈ 3.5 years, RMSE ≈ 5.4 years, and R² ≈ 0.76. Aggregation into 5-year age bins revealed a robust nonlinear ageing trajectory characterised by midlife decline and late-life stabilisation. The increased correspondence at the grouped level reflects reconstruction of the population-level ageing trajectory rather than improved individual-level prediction accuracy, as averaging reduces inter-individual variability. Conclusions: These findings demonstrate a strong ageing-related signal in female breast thermophysiology and support thermophysiology as a candidate age-referenced physiological marker, pending longitudinal and outcome-based validation. The present analysis is cross-sectional and requires longitudinal validation before diagnostic or prognostic interpretation. Full article