Search Results (3,891)

Reliable crop yield estimation is fundamental to food security and efficient agricultural management. However, current deep learning models still face limitations in selecting and integrating multi-source features, and their high predictive accuracy is often accompanied by limited interpretability. This study introduces a Bayesian Optimization–Temporal Convolutional Network–Bidirectional Long Short-Term Memory–Dual Attention (BO-TCBDA) deep learning framework for winter wheat yield estimation. Using Henan Province, China, as the study area, county-level winter wheat yield from 2013 to 2022 was estimated using the Enhanced Vegetation Index (EVI), Leaf Area Index (LAI), Solar-Induced Chlorophyll Fluorescence (SIF), and climate data. The proposed model was compared with five commonly used machine learning and deep learning models. BO-TCBDA achieved the best performance, with an R² of 0.823 and an RMSE of 561.26 kg/ha. SIF improved the predictive performance of all models, with statistically significant gains observed in the deep learning models. The dual-attention mechanism provided interpretable insights by revealing relatively balanced contributions among the input features and highlighting the grain-filling stage through temporal attention. Furthermore, SHAP-based cross-validation analysis identified T12, corresponding to the latter part of the jointing stage, as the period with the highest contribution to yield prediction. The model also achieved an R² of approximately 0.80 about 25 days before harvest. Overall, BO-TCBDA provides an accurate and interpretable approach for county-level winter wheat yield estimation and supports regional food security assessments and precision agriculture. Full article

Historical pax demand estimation is important for understanding long-term demand dynamics and supporting airline planning, strategic decision-making, and transportation policy analysis. However, current decomposition approaches either estimate trends without explicitly modeling seasonality or jointly estimate trend and seasonal components without providing user control over trend smoothness. This paper proposes a Guerrero–Holt–Winters (GHW) hybrid smoothing model to estimate and reconstruct historical route-level airline pax demand. The GHW model combines Guerrero’s user-controlled trend estimation with the multiplicative seasonal structure of the Holt–Winters (HW) model to produce an interpretable decomposition of historical demand into trend, seasonal, and irregular components. The model is applied to quarterly pax demand data for ten representative U.S. domestic air routes covering the period 2015–2023. The results show that the proposed GHW model achieves lower in-sample reconstruction errors than the multiplicative HW model at lower degrees of trend smoothness within the evaluated range. Among the evaluated specifications, λ = 1, corresponding to a Guerrero smoothness index of S(1; 36) = 58.82%, produces the lowest in-sample reconstruction error. The historical reconstruction error, measured by the root mean squared error (RMSE), is reduced by approximately 54.4% relative to the multiplicative HW model. Similar improvements are observed under MAE, MAPE, and sMAPE, indicating that the reduction in reconstruction error at this smoothness level is consistent across the four error measures. An expanded benchmark comparison with HW, ETS state-space exponential smoothing, STL decomposition, and HP1600 further shows that the GHW model produces the lowest in-sample reconstruction errors across all four evaluation error metrics and all ten routes analyzed. A sensitivity analysis further demonstrates that reconstruction accuracy declines as the degree of trend smoothness increases from S(λ; 36) = 58.82% to 88.63%, whereas the estimated seasonal factors remain remarkably stable across the evaluated smoothness range. A COVID-19 robustness analysis further shows that reconstruction errors are substantially lower in the Pre-COVID period than in the Post-COVID period across all ten routes, indicating that reconstruction accuracy is sensitive to the period analyzed. Full article

Understanding the spatiotemporal evolution of waterlogging intensity across winter oilseed rape (WOSR) growth stages and its quantitative relationship with yield losses is critical for agricultural water management in the Middle-Lower Yangtze River Region (MLYRR). Here, a daily-scale agrometeorological index (SAPEI) was introduced to quantify waterlogging intensity during four WOSR growth stages from 1961 to 2020. Waterlogging intensity increased significantly over the past six decades in most areas, particularly during the overwintering stage (38 stations, 57% of all stations), with the 2000s representing the historical high levels for most provinces, followed by those in the 1990s. The northeastern and southernmost MLYRR were identified as highly waterlogging-prone regions, and the overwintering stage exhibited substantially larger daily waterlogging intensity than other stages. The yield-reducing impact of severe waterlogging (SAPEI > 1.0) was greater than general waterlogging (SAPEI > 0.5), with larger absolute regression coefficients of waterlogging indices. The flowering–maturing stage, followed by the overwintering stage, was the most waterlogging-sensitive period, and it was also selected as the sole explanatory variable in up to 14 districts in stepwise regression. A marked spatial mismatch was found between waterlogging proneness and crop sensitivity, suggesting that drainage scheduling should account for crop waterlogging sensitivity rather than waterlogging intensity alone. These findings provide guidance for targeted WOSR drainage planning in key regions of the MLYRR under climate change. Full article

Human metapneumovirus (hMPV) represents a leading cause of both upper and lower respiratory tract infections among children and adults globally. To investigate the prevalence and evolution of hMPV in the Jiaxing area of China between 2023 and 2025, we screened 3600 pharyngeal swab specimens by real-time PCR, identified 101 positives, and obtained genomic sequences of 48 viral isolates using high-throughput sequencing. Using the sequencing data, we reconstructed a phylogenetic tree and examined amino acid substitutions. The epidemiological analysis revealed an overall hMPV positivity rate of 2.81% (101/3600) in Jiaxing during 2023–2025. Although positive cases were detected across all age groups, they were mainly children, with no significant difference between genders. Regarding seasonal patterns, the peak of hMPV activity occurred predominantly during winter and spring. Over the study period, four genotypes co-circulated, in the order of B2 (41.67%), A2.2.2 (37.50%), A2.2.1 (16.67%), and B1 (4.17%). Further phylogenetic analysis showed that the B1 strains from Jiaxing clustered primarily with those from Beijing, China, while B2, A2.2.1, and A2.2.2 strains were more closely related to strains from the United States and Beijing. Of note, an A2c_111nt-dup variant was identified in Jiaxing in 2023. Starting from November 2024, the prevailing genotype transitioned from A2.2.1/A2.2.2 to B2, and B2 emerged as the absolutely dominant strain by 2025. In comparison with earlier circulating strains, several amino acid substitutions have accumulated in current isolates, such as T223N, D280N, I392T, R396Q, S444N, K450R, and T521A in the F protein of B2 strains. Furthermore, the G, L, P, and SH proteins also displayed temporally patterned amino acid replacements. While the biological significance of these mutations is yet to be determined, these results highlight the public health importance of ongoing hMPV surveillance and dynamic monitoring of its genetic evolution. Full article

This study develops a probabilistic carbon-aware optimization framework for residential 24/7 carbon-free electricity (CFE) under uncertain load, PV generation and dynamic grid carbon intensity. Historical half-hourly monitoring data are represented through KDE-Copula scenario generation, while grid carbon factors are described by time-series decomposition and ARMA-based residual scenarios. A two-stage mixed-integer linear program jointly sizes and dispatches battery energy storage (BESS) and thermal energy storage (TES) by minimizing annualized lifecycle CO₂ emissions. The results show that coordinated BESS–TES operation improves PV utilization and avoids carbon-intensive grid imports, especially in winter. In the examined capacity range, increasing BESS capacity from 0 to 100 kWh reduces annual lifecycle emissions from approximately 8600 to 6000 kg CO₂ yr⁻¹, corresponding to about a 30% reduction, whereas the marginal benefit of additional TES is constrained by DHW demand and its embodied emissions. Electrical storage is therefore the principal carbon-shifting resource, while a moderately sized TES complements it by moving heat-pump operation toward low-carbon and PV-rich periods. The framework provides a practical basis for carbon-aware design of residential electrification systems. Full article

Winter ice-cover periods pose substantial risks to Apostichopus japonicus aquaculture in northern China. We combined field monitoring of three representative aquaculture ponds between 2014 and 2017 with controlled single-factor laboratory exposures to low temperature, hypoxia, and hyposalinity in adult and juvenile sea cucumbers. Field observations revealed pronounced temporal, vertical, spatial, and interannual variability in water temperature, salinity, and dissolved oxygen (DO) during freezing and ice-melting periods. All three stressors caused clear deterioration in physiological condition, with juveniles generally exhibiting greater short-term sensitivity than adults under low-temperature and hypoxic exposure, whereas severe hyposalinity caused pronounced deterioration in both life stages. Lactate, malondialdehyde (MDA), and glutathione (GSH) showed distinct treatment- and time-dependent responses, consistent with stress-associated changes in anaerobic metabolism, lipid peroxidation, and glutathione-associated antioxidant status. Integration of field observations with laboratory responses indicated that water temperatures approaching 0 °C and salinities approaching approximately 20‰ represent environmentally relevant conditions associated with elevated overwintering risk. DO concentrations approaching approximately 3 mg/L may warrant intensified monitoring and management intervention, whereas 2 mg/L represents a more severe experimental hypoxia condition. The more extreme treatments of −2 °C and 15‰ should similarly be regarded as severe experimental scenarios rather than commonly occurring field conditions. These environmental values should therefore be interpreted as preliminary management-oriented risk references rather than definitive physiological thresholds. Overall, the study provides an empirical field-to-laboratory basis for biologically informed winter environmental monitoring and risk-based overwintering management of A. japonicus aquaculture. Full article

Oblique and Fork-shaped traces in ionosonde’s ionograms have been identified as manifestations of nighttime and daytime Medium-Scale Traveling Ionospheric Disturbances (MSTIDs), respectively. The MSTIDs associated with these singular patterns have been verified by analyzing the evolution of detrended total electron content (dTEC) perturbation maps derived from the Global Navigation Satellite System (GNSS) signals. This has made it possible to create a database of MSTIDs characterized by their dominant period, horizontal propagation speed, wavelength, and propagation direction. This also allowed comprehensive case studies and statistical analyses of their temporal occurrence, direction of propagation, seasonal dependence, and its association with Spread-F (SF) phenomena. The results reveal that approximately 92% of the “Oblique” traces and 86% of the “Fork” traces in ionograms correspond to nighttime and daytime MSTID activity, respectively, as observed in the dTEC maps. Oblique traces are predominantly observed during southwestward propagating MSTIDs and exhibit a marked seasonal occurrence during summer and winter. Fork traces occurred predominantly during equatorward propagating MSTIDs and are most frequently observed in winter. A statistically significant association has been found between daytime MSTID activity (Fork traces) and the subsequent appearance of SF, with conditional probabilities ranging from ~87% to ~78% at mid-to-high latitudes and from ~76% to ~61% at mid-to-low latitudes. However, when overall MSTID activity was considered—taking into account both the disturbances associated with the daytime Forks and those associated with nighttime Oblique traces—the statistical association with subsequent occurrence of SF increased to approximately 91%. These results show a strong statistical relationship but do not establish a direct causal link between an individual daytime MSTID activity and nighttime SF. Instead, the occurrence of MSTID is seen as an indicator of ionospheric conditions that are favorable for the development of SF at mid-latitudes. These findings offer new insights into the ionogram-based characterization of MSTID signatures and their association with nighttime SF over Europe. The results highlight that MSTID occurrence serves as a strong indicator of favorable conditions for the development of instabilities in the mid-latitude ionosphere, offering valuable implications for the possible modeling of the ionosphere and the prediction of ionospheric weather. Full article

Renewable-energy fluctuations and the conflicting economic objectives of independent stakeholders pose simultaneous physical and market challenges to the operation of flexible integrated energy systems (FIESs). To address these issues, this paper develops a market–physical coupled Stackelberg game-based coordinated operation framework incorporating the intertemporal flexibility of electrical and thermal energy storage. The integrated energy operator (IEO) acts as the leader and determines the internal electricity and heat purchase and sale prices, while the multi-energy cogeneration system (MECS) operator and the load aggregator act as followers and independently optimize generation-storage schedules and demand-response decisions, respectively. The load-aggregator response is formulated as a quadratic programming problem, whereas the MECS-side problem is formulated as a mixed-integer quadratic programming problem because of the binary storage-state variables. A nested Differential Evolution–CPLEX solution framework is employed to obtain a numerical Stackelberg equilibrium solution. A 24-h typical winter-day case study demonstrates the effectiveness of the proposed strategy. The peak electrical load decreases from 1845 kW to 1515 kW, corresponding to a reduction of 17.89%, while the peak-to-valley difference is reduced by 45.26%. The total user energy-purchasing cost decreases by 8.56%. Although the total electricity purchased from the external grid increases by 15.61%, the corresponding purchasing cost decreases by 30.98%, indicating that the coordinated strategy restructures grid transactions toward lower-price periods rather than simply minimizing grid imports. Comparative simulations with the no-storage and no-demand-response benchmark cases further confirm the complementary contributions of dual-storage flexibility and demand response to multi-agent economic performance. Moreover, the renewable curtailment rate is reduced from 6.51% to 0%, indicating that the proposed strategy enhances the local accommodation of wind-PV generation. These results show that the framework contributes to sustainable community energy operation by improving renewable-energy utilization, reducing peak-load pressure, lowering user energy expenditure, and supporting incentive-compatible coordination among independent stakeholders. Compared with conventional Stackelberg formulations that mainly focus on operator–user pricing or treat storage primarily as a balancing resource, the proposed framework explicitly embeds the intertemporal flexibility of electrical and thermal storage into the strategic response of the supply-side follower under endogenous multi-energy price signals. Full article

Mega-events can accelerate land–use/land cover change (LULCC) through infrastructure development and ecological interventions, but the carbon consequences of different land transition pathways remain unclear. Using Yanqing District, a host region of the Beijing 2022 Winter Olympics, as a case study, this study investigates LULC transitions, carbon storage dynamics, and future land management. A coupled PLUS–InVEST framework integrating transition attribution and trajectory analysis was applied to 10-m LULC datasets (2018, 2021, and 2024) to reconstruct historical transitions and simulate four land management scenarios for 2035. Results indicated that total carbon storage increased continuously from 41.19 × 10⁶ t C in 2018 to 42.14 × 10⁶ t C in 2024 despite concurrent urban expansion. This increase resulted from distinct transition processes across the two periods: cropland-to-rangeland conversion contributed most to carbon gains during 2018–2021, whereas rangeland-to-trees conversion dominated gains during 2021–2024. Pixel-level trajectory analysis further revealed that these dominant transitions rarely formed a continuous restoration sequence at the same locations, with rangeland–rangeland–trees trajectories accounting for 76.2% of trajectories leading to trees-class gains. Future simulations showed that the Urban Development Scenario would reduce carbon storage by 5.6%, whereas the Ecological Protection Scenario would increase carbon storage by 2.3% relative to the 2024 baseline. These results indicate that regional carbon dynamics depend not only on LULC composition but also on transition pathways, providing insights into how transition pathways can inform ecological restoration and sustainable land management. Full article

Coastal waters are vulnerable ecosystems that are increasingly affected by sediment and nutrient inputs, as well as pollution resulting from both natural processes and anthropogenic pressures. Monitoring the pattern of chlorophyll-a and turbidity is essential for understanding the dynamics of coastal ecosystems and supporting environmental management. This study investigates the spatial and seasonal patterns of water quality in the coastal zone of Heraklion, Crete (Greece), for the period 2016–2024 using OCEANIDS Data Cube products (GA 101112919). Water quality variability was assessed using satellite-derived spectral indices, including the Normalized Difference Chlorophyll Index (NDCI) and the Normalized Difference Turbidity Index (NDTI). Monthly observations were analyzed using a GIS-based workflow to assess seasonal spatiotemporal variability. The results revealed strong seasonal variability, with higher winter NDCI values in all coastal zones and persistent hotspots concentrated near river estuaries and waters influenced by port activities. Meanwhile, the analysis was used to prioritize the region for further monitoring and to support decision-making for stakeholders. In summary, this study demonstrates the potential of OCEANIDS Data Cube products (NDCI, NDTI) for long-term monitoring of surface coastal water quality in a Mediterranean environment with limited data and supports evidence-based coastal management. Full article

Degenerative joint disease is highly prevalent in older cats and can negatively affect mobility, behaviour, and overall welfare, yet objective evidence for the efficacy of dietary joint supplements in this species remains limited. This study evaluated the effects of a multi-ingredient oral joint supplement on activity, behaviour, and physiological parameters in domestic cats using accelerometry and blood-based measures. Sixteen cats were enrolled, with data from 11 cats (control n = 5; treatment n = 6) analysed over a 16-week period. Overall dynamic body acceleration was associated with time and showed a significant interaction between treatment and time (p = 0.001), although no main effect of treatment was detected (p = 0.323). Locomotion showed trends for both treatment (p = 0.082) and the interaction between treatment and time (p = 0.097). Grooming showed a significant interaction between treatment and time (p = 0.018), with higher grooming levels in the treatment group during early winter (weeks 2–8), followed by a decline in both groups. No differences were observed in body weight, haematology or biochemistry. These findings suggest that supplementation may influence behavioural consistency and context-dependent expression, particularly in grooming, rather than producing increases in overall activity. The supplement was well tolerated, highlighting the importance of behaviour-specific and temporal analyses when evaluating interventions in feline joint health. Full article

Camellia gauchowensis is widely distributed in South China. Field observations indicate that it produces abundant flowers but yields relatively few fruits under natural conditions. Understanding the intrinsic and extrinsic drivers of this low fruit output is essential both for revealing adaptive strategies in oil-tea camellia and informing cultivation improvement. In this study, we comprehensively investigated the flowering phenology, floral traits, pollen traits, pollinator activity, and breeding-system characteristics of C. gauchowensis. The results showed that C. gauchowensis produces perfect flowers but suffers from a narrow effective pollination window during its late-autumn-to-winter flowering period. Stomium-cell contaminants mixed with pollen grains may contribute to its poor pollen germination capacity. Cytochemical staining (TTC and FDA) significantly overestimated viability compared to in vitro germination results, and thus could not serve as a reliable substitute for functional pollen assessment. Both the outcrossing index and the pollen–ovule ratio indicated that C. gauchowensis exhibits a reproductive tendency toward outcrossing, with its sexual reproduction largely dependent on pollinators. Among the recorded floral visitors, Apis cerana represents the most promising pollinator candidate owing to its numerical dominance, frequent stigma contact, and superior cold-tolerance capacity. Our results reveal that reproductive success in C. gauchowensis is collectively constrained by multiple factors: a narrow effective pollination window, low pollen viability, winter-driven pollinator scarcity, and its reproductive tendency toward outcrossing. This study elucidates the coupled intrinsic–extrinsic mechanisms underlying low fruit output in this winter-flowering oil-tea camellia and provides theoretical underpinnings for pollination management and high-yield cultivation of this economically important woody crop. Full article

Background: Respiratory tract infections (RTIs) caused by viruses are a public health problem, contributing to hospital admissions and morbidity worldwide. The COVID-19 pandemic substantially altered the detection patterns of respiratory viruses through public health interventions. Longitudinal data on these changes and viral seasonality remain limited in Saudi Arabia. This eight-year study evaluated epidemiological and seasonal patterns of major respiratory viruses across the COVID-19 era at a major Saudi tertiary care center. Methods: A retrospective observational study was conducted at King Khalid University Hospital, Riyadh, from October 2017 to December 2025. PCR-confirmed detections for SARS-CoV-2, Influenza A, Influenza B, respiratory syncytial virus (RSV), and human metapneumovirus (HMPV) were extracted from the hospital Laboratory Information System. Demographics, co-detection, seasonality, and length of stay (LOS) were analyzed across four eras spanning the pre-COVID-19, lockdown, restriction, and post-restriction periods using descriptive statistics, the Kruskal–Wallis test, and multivariable negative binomial regression. Results: Among 5708 confirmed respiratory viral detection episodes, SARS-CoV-2 was the most frequently detected (52.5%), followed by Influenza A (19.1%), RSV (16.4%), Influenza B (8.4%), and HMPV (3.6%). Before the pandemic, Influenza A accounted for the largest proportion of detected episodes (71.1%), with detections clustering particularly during autumn and winter seasons, whereas SARS-CoV-2 accounted for the majority of detected episodes during the lockdown and restriction eras (97.4% and 93.2%). The post-restriction era became more diverse, with RSV being detected in substantial proportions (28.3%), showing prominent winter activity. RSV and HMPV predominantly affected children aged 0–5 years, whereas SARS-CoV-2 was more frequently detected among older adults. Among adults, older age was associated with prolonged LOS; Influenza A and HMPV were associated with shorter stays compared to SARS-CoV-2. Among children, no virus was independently associated with LOS after adjustment for age and sex; however, older age was associated with longer hospital stays. Conclusion: The observed detection patterns of major respiratory viruses shifted substantially across the COVID-19 eras, with notable post-restriction diversification among observed positive detections. LOS was associated with age in both adults and children and with virus type among adults, supporting continued surveillance to guide preventive and clinical strategies. Full article

Against the backdrop of global warming and the “warming and moistening” trend in northwestern China, arid inland river basins are highly sensitive to climate change, with their vegetation dynamics strongly controlled by upstream snowmelt water supply. The Keriya River Basin, situated on the northern slope of the Kunlun Mountains and the southern edge of the Taklamakan Desert, exhibits pronounced vertical zonation in vegetation cover and relies heavily on upstream snowmelt water supply for its water resources. To date, there has been a lack of systematic research into the spatiotemporal evolution patterns of long-term NDVI time series in this basin, its multiscale climate responses, and, in particular, future vegetation projections based on CMIP6 multi-scenario analyses and machine learning methods. To address this, this study utilised MODIS NDVI remote sensing data, historical data from the CMIP6 BCC-CSM2-MR model, and monthly temperature, precipitation, and snow cover data for three SSP scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5) and systematically analysed the spatiotemporal differentiation characteristics of NDVI in the Keriya River Basin and its multiscale coupling relationships with climatic factors. A multi-model selection and forecasting framework was developed, integrating feature engineering with the XGBoost machine learning algorithm. The study innovatively introduced a physically constrained scenario scaling factor based on historical correlations and future climate mean values, thereby addressing the bias where machine learning models’ predicted NDVI means converged across different SSP scenarios. This enabled the monthly estimation of NDVI under various emission pathways from 2015 to 2100. The results indicate: (1) During the historical period (2001–2024), the basin’s annual average NDVI showed an overall slight increase; the annual pattern was unimodal, peaking in July and reaching its trough in January–February; NDVI was highest in summer and lowest in winter. (2) NDVI initially increases and then decreases with altitude; the highest NDVI values are observed in the 3000–4000 m altitude band; in the mid-altitude band, NDVI rose significantly after 2010 and peaked in 2017; the low-altitude band exhibits the greatest interannual stability. (3) During the historical period, both temperature and precipitation in the catchment exhibited high levels of fluctuation, with annual mean temperatures ranging from 1.90 to 3.92 °C and annual precipitation ranging from 434.5 to 621.0 mm. NDVI showed a strong positive correlation with temperature (R = 0.86), a relatively strong negative correlation with snow cover (R = −0.71), and virtually no correlation with precipitation, indicating that upstream snowmelt is heat-driven and water-dependent. (4) Under the future SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios, temperature increases are projected to be 0.83 °C, 2.68 °C, and 5.35 °C, respectively, whilst snow cover is projected to decrease by 2.0%, 14.3%, and 34.0%, respectively; The multi-year mean NDVI values predicted using the XGBoost model (validation R² = 0.9097) are 0.0726, 0.0683, and 0.0690, respectively, all characterised by strong seasonal fluctuations. Given that these future projections are based on a single CMIP6 model and a statistical forecasting framework, they are subject to a degree of uncertainty; however, the low-emission scenario (SSP1-2.6) still indicates a trend that is relatively more conducive to maintaining vegetation stability in this region and may provide preliminary scientific guidance for water resource management along the southern margin of the Tarim Basin. Full article

Objective: The objectives of this study were to analyze the epidemiological characteristics and whole-genome features of human metapneumovirus (HMPV) among children under 14 years of age in Shijiazhuang during 2022–2025, enrich the whole-genome data of HMPV in China, and provide a basis for further understanding the genetic diversity of the virus and for its prevention, control, and transmission intervention. Methods: A total of 1920 cases of acute respiratory infection were enrolled from three sentinel hospitals in Shijiazhuang. Nucleic acid screening was performed using real-time PCR. Whole-genome sequencing was conducted on 25 positive samples. Phylogenetic trees were constructed using the neighbor-joining method in MEGA, and nucleotide and amino acid sequence identity analyses were performed. Results: The overall detection rate of HMPV from 2022 to 2025 was 4.17%. A prominent peak in winter 2024 was the major distinguishing feature. Temporally, both influenza-like illness (ILI) and severe acute respiratory infection (SARI) cases showed marked seasonality during 2022–2025, with high-incidence periods in December–March and April–June. BLAST alignment and phylogenetic analysis showed that among the 25 sequenced HMPV specimens, genotype B2 was the most frequently identified genotype (13/25, 52%). Conclusions: HMPV epidemics in Shijiazhuang during 2022–2025 mainly occurred in winter–spring and spring–summer, with a notable detection peak in December 2024. The B2 genotype predominated among the sequenced HMPV isolates obtained in this study. The amino acid variation in the G gene was significantly higher than that in other genomic regions. Full article