Regulation of seed germination: ROS, epigenetic, and hormonal aspects.

BACKGROUND: The whole life of a plant is regulated by complex environmental or hormonal signaling networks that control genomic stability, environmental signal transduction, and gene expression affecting plant development and viability. Seed germination, responsible for the transformation from seed to seedling, is a key initiation step in plant growth and is controlled by unique physiological and biochemical processes. It is continuously modulated by various factors including epigenetic modifications, hormone transport, ROS signaling, and interaction among them. ROS showed versatile crucial functions in seed germination including various physiological oxidations to nucleic acid, protein, lipid, or chromatin in the cytoplasm, cell wall, and nucleus. AIM: of review: This review intends to provide novel insights into underlying mechanisms of seed germination especially associated with the ROS, and considers how these versatile regulatory mechanisms can be developed as useful tools for crop improvement. KEY SCIENTIFIC CONCEPTS OF REVIEW: We have summarized the generation and elimination of ROS during seed germination, with a specific focus on uncovering and understanding the mechanisms of seed germination at the level of phytohormones, ROS, and epigenetic switches, as well as the close connections between them. The findings exhibit that ROS plays multiple roles in regulating the ethylene, ABA, and GA homeostasis as well as the Ca2+ signaling, NO signaling, and MAPK cascade in seed germination via either the signal trigger or the oxidative modifier agent. Further, ROS shows the potential in the nuclear genome remodeling and some epigenetic modifiers function, although the detailed mechanisms are unclear in seed germination. We propose that ROS functions as a hub in the complex network regulating seed germination.

Synthesis and preclinical evaluation of 68Ga-labeled PSMA tracers with improved pharmacological properties.

Prostate cancer (PCa) is one of the most common tumors in men, with the overexpression of prostate-specific membrane. In this study, we developed four new 68Ga-labeled PSMA-targeting tracers by introducing quinoline, phenylalanine and decanoic acid groups to enhance their lipophilicity, strategically limiting their metabolic pathway through the urinary system. Four radiotracers were synthesized with radiochemical purity >95 %, and exhibited high stability in vivo and in vitro. The inhibition constants (Ki) of SDTWS01-04 to PSMA were in the nanomolar range (<10 nM). Micro PET/CT imaging and biodistribution analysis revealed that 68Ga-SDTWS01 enabled clear tumor visualization in PET images at 1.5 h post-injection, with excellent pharmacokinetic properties. Notably, the kidney uptake of 68Ga-SDTWS01 significantly reduced, with higher tumor-to-kidney ratio (0.36 ± 0.02), tumor-to-muscle ratio (24.31 ± 2.10), compared with 68Ga-PSMA-11 (T/K: 0.15 ± 0.01; T/M: 14.97 ± 1.40), suggesting that 68Ga-SDTWS01 is a promising radiotracer for the diagnosis of PCa. Moreover, SDTWS01 with a chelator DOTA could also label 177Lu and 225Ac, which could be used for the treatment of PCa.

The impact of extreme precipitation on water use efficiency along vertical vegetation belts in Hengduan Mountain during 2001 and 2020.

In the context of climate change, extreme precipitation events are continuously increasing and impact the water­carbon coupling of ecosystems. The vertical vegetation zonation, as a characteristic of mountain ecosystems, reflects the differences in vegetation response to climate change at different elevations. In this study, we used the water use efficiency (WUE) as an indicator to evaluate the water­carbon relationship. By using MODIS data, we analyzed the spatiotemporal patterns of gross primary productivity (GPP), evapotranspiration (ET), and WUE from 2001 to 2020, as well as the responses of WUE to extreme wetness factor Number of precipitation days (R0.1), extreme dryness factor Consecutive dry days (CDD), and meteorological factors under the vertical vegetation zonation. Our results showed that annual GPP and ET displayed a significant increasing trend between 2001 and 2020, whereas WUE showed a weak decreasing trend. Spatially, GPP and WUE decreased with increasing elevation. Analyzing the WUE of mountainous ecosystems as a unified whole may not precisely capture the reactions of vegetation to severe rainfall occurrences. In fact, across different vegetation belts in mountainous areas, there exists a negative correlation between WUE and R0.1, and a positive correlation with CDD. In terms of meteorological factors, the temporal variation of GPP was primarily associated with vapor pressure deficit (VPD) and temperature (Ta), while those of ET was mainly related to soil water content (SWC). WUE was affected by a combination of meteorological factors and had a certain degree of variation between different altitude intervals. These findings contribute to a better understanding and prediction of the relationship between extreme rainfall climate and water­carbon coupling in mountainous areas.

Plant water source effects on plant-soil feedback for primary succession of terrestrial ecosystems in a glacier region in China.

Despite the extensive research conducted on plant-soil-water interactions, the understanding of the role of plant water sources in different plant successional stages remains limited. In this study, we employed a combination of water isotopes (δ2H and δ18O) and leaf δ13C to investigate water use patterns and leaf water use efficiency (WUE) during the growing season (May to September 2021) in Hailuogou glacier forefronts in China. Our findings revealed that surface soil water and soil nutrient gradually increased during primary succession. Dominant plant species exhibited a preference for upper soil water uptake during the peak leaf out period (June to August), while they relied more on lower soil water sources during the post-leaf out period (May) or senescence (September to October). Furthermore, plants in late successional stages showed higher rates of water uptake from uppermost soil layers. Notably, there was a significant positive correlation between the percentage of water uptake by plants and available soil water content in middle and late stages. Additionally, our results indicated a gradual decrease in WUE with progression through succession, with shallow soil moisture utilization negatively impacting overall WUE across all succession stages. Path analysis further highlighted that surface soil moisture (0- 20 cm) and middle layer nutrient availability (20- 50 cm) played crucial roles in determining WUE. Overall, this research emphasizes the critical influence of water source selection on plant succession dynamics while elucidating underlying mechanisms linking succession with plant water consumption.

The Influence of Drug-Eluting Beads Transarterial Chemoembolization on Serum Levels of Soluble Programmed Cell Death Protein-1 in Advanced Hepatocellular Carcinoma Patients.

Aim: This study aims to explore the role of soluble programmed cell death protein 1 (sPD-1) in individuals with hepatocellular carcinoma (HCC) undergoing treatment with drug-eluting beads transarterial chemoembolization (D-TACE). Additionally, we aim to assess the potential utility of sPD-1 for determining the optimal timing for combining D-TACE with immune checkpoint inhibitors (ICIs). Materials and Methods: A total of 44 HCC patients eligible for D-TACE and 55 healthy volunteers were enrolled in this study. Three milliliters of peripheral venous blood from the patients were collected on the day before D-TACE and 3, 7, and 30 days after D-TACE, respectively, for the assay of sPD-1. The relationships between sPD-1 levels, clinical features, outcomes, and the fluctuation of sPD-1 during treatment were analyzed. Results: The initial sPD-1 levels in patients were found to be significantly higher than those in the control group. Although the initial sPD-1 levels displayed a decreasing trend with an increase in BCLC stage, no significant differences were observed among patients at different BCLC stages. The sPD-1 level on day 3 after D-TACE was similar to that on day 7 after D-TACE and significantly lower than the initial level. The sPD-1 level on day 30 after D-TACE was significantly higher than that on day 3 and day 7 after D-TACE and nearly returned to the initial level before D-TACE. Conclusion: The level of sPD-1 was found to be significantly elevated in patients with HCC. However, further research is deemed necessary to fully understand the role of sPD-1 as a potential biomarker in the initiation, progression, and prognosis of HCC. The decrease in sPD-1 following D-TACE suggests that immune effector cells might potentially be reduced, as well as immune function weakened, highlighting the need to avoid the prompt administration of ICIs after D-TACE.

How Organic Mulching Influences the Soil Bacterial Community Structure and Function in Urban Forests.

Urban forest soil is often disturbed by frequent human activity. Organic mulching is effective for improving soil quality; however, the effects of organic mulching on soil bacterial communities in urban forests are still largely unexplored. This study evaluated how organic mulching changed the urban forest soil bacterial community through an incubation experiment. Four treatments were applied: (1) no organic mulch (CK); (2) wood chips alone (5 g, Mw); (3) wood compost alone (5 g, Mc); and (4) wood chips + wood compost (This mulch was divided into two layers, i.e., the upper layer of wood chips (2.5 g) and the lower layer wood compost (2.5 g, Mw+c).) We found significant differences in the soil physicochemical properties under organic mulching after incubation. Overall, organic mulching can alter soil bacterial community structure. Soil alkali-hydrolyzable nitrogen, soil organic carbon, soil total nitrogen, and carbon-nitrogen ratio were the main factors affecting soil microbial community structures. Soil bacterial groups under organic mulching treatments mainly acted on the C and N cycling of functional pathways in soil. This study suggests that organic mulching could maintain the development of soil bacteria, which establishes a theoretical foundation for enhancing the microbiological environment of urban forest soils.

Light Quality Effect on Internal N Retranslocation in Podocarpus macrophyllus Precultured with Exponential Nutrient Loading.

Streetlamp light is inevitable in the night landscape of a city and may affect the phenology of newly planted ornamental plants, but it has rarely been fully examined. Newly transplanted ornamental plants probably suffer periodic shocks, which mainly result from the inefficient reuse of internal nutrients for new growth. Exponential nutrient loading (ENL) is well known for its ability to overcome transplant shocks by promoting retranslocation for the reuse of strengthened nutrients from internal reserves in precultured seedlings. Transplantation to urbanized lands is distinct from that of montane areas; this is mainly due to a high frequency of exposure to the artificial illumination of night lighting. It is suspected that this lighting modifies vegetative phenology and generates potential risks by increasing reliance on internal nutrient retranslocation. In this study, Podocarpus macrophyllus seedlings were cultured with ENL at low and high rates of nitrogen (N) deliveries (40 and 120 mg N seedling-1, respectively), and the high-rate treatment was identified as being able to trap seedlings within toxic states. A labeled 15N isotope was pulsed to transplanted seedlings exposed to simulated light qualities in red, green, and blue light spectra. The seedlings harvested at one month showed rare responses to the interactive spectra and preculture treatments, but most of them responded to the low-rate N preculture treatment with stronger abilities in terms of the reuse of internal N and the synthesizing of photosynthetic pigments. In conclusion, it was verified that night light enforces the effect on newly transplanted plants; the red light invoked internal N for reuse, and the blue light promoted the uptake of the current N. The internal N reserve established through preculture ENL rarely made a contribution to the night light effect, except for the enhancement of height growth in the red light. The red light spectrum was recommended for the exposure of newly transplanted seedlings due to its effect on the enhancement of the retranslocation of internal N and the induction of a steady state of uptake from the current N input.

The seasonal variability of future evapotranspiration over China during the 21st century.

The evapotranspiration (ET) plays a crucial role in shaping regional climate patterns and serves as a vital indicator of ecosystem function. However, there remains a limited understanding of the seasonal variability of future ET over China and its correlation with environmental drivers. This study evaluated the skills of 27 models from the Six Phase of Coupled Model Intercomparison Project in modeling ET and the Bayesian Model Averaging (BMA) method was employed to merge monthly simulated ET based on the top five best-performing models. The seasonal changes in ET under three climate scenarios from 2030 to 2099 were analyzed based on the BMA-merged ET, which was well validated with observed ET collected from fourteen flux sites across China. Significant increasing ET over China are projected under all seasons during 2030-2099, with 0.05-0.13 mm yr-1, 0.11-0.23 mm yr-1, and 0.20-0.41 mm yr-1 under SSP1-2.6, SSP2-4.5 and SSP5-8.5 scenarios, respectively. Relative to the historical period (1980-2014), the relative increase in ET over China is highest in winter and lowest in summer. Seasonal ET increases significantly in all seven climate sub-regions under high forcing scenario. Higher ET increase is generally found in southeastern humid regions, while lowest ET increase occurs in northwest China. At the country level, the primary factor driving ET increase during spring, summer, and autumn seasons is the increasing net radiation and warming. In contrast, ET increase during winter is influenced not only by energy factors but also by vegetation-related factors. Future seasonal ET increase is predominantly driven by increasing energy factors in the southeastern humid region and Tibetan Plateau, while seasonal ET changes in the northwest region prevailingly depend on soil moisture. Results indicate that China will experience a "wet season will get wetter, and dry season will become drier" in the 21st century with high radiation forcing scenario.

Comparison of the efficacy of combining left bundle branch pacing with either sacubitril/valsartan or enalapril in the treatment of chronic heart failure: A retrospective observational analysis.

Objective: To assess the efficacy of left bundle branch pacing (LBBP) combined with either sacubitril/valsartan or enalapril in the treatment of chronic heart failure (CHF). Methods: We retrospectively reviewed the records of 138 patients with CHF admitted to Dazhou Central Hospital between June 2020 and June 2022 to extract clinical data. We divided the data into two treatment groups for the analysis: 71 patients received LBBP combined with sacubitril/valsartan treatment (sacubitril/valsartan group), and 67 received LBBP combined with enalapril treatment (enalapril group). The levels of cardiac and cardiopulmonary function indicators, levels of myocardial injury markers, and the scores of the Minnesota Living with Heart Failure Questionnaire (MLHFQ) before and after the treatment were compared between the two groups. Results: After six months of treatment, patients in the sacubitril/valsartan group had lower myocardial injury markers, higher cardiopulmonary function indicators, and lower MLHFQ scores (P<0.05). Conclusions: In CHF patients, the combination of LBBP with sacubitril/valsartan had a better therapeutic effect compared to LBBP with enalapril, with more effective improvement of the cardiopulmonary function, reduction of myocardial injury, and improvement in quality of life.

Depth effects on bacterial community altitudinal patterns and assembly processes in the warm-temperate montane forests of China.

Soil bacterial communities are essential for ecosystem function, yet their response along altitudinal gradients in different soil strata remains unclear. Understanding bacterial community co-occurrence networks and assembly patterns in mountain ecosystems is crucial for comprehending microbial ecosystem functions. We utilized Illumina MiSeq sequencing to study bacterial diversity and assembly patterns of surface and subsurface soils across a range of elevations (700 to 2100 m) on Dongling Mountain. Our results showed significant altitudinal distribution patterns concerning bacterial diversity and structure in the surface soil. The bacterial diversity exhibited a consistent decrease, while specific taxa demonstrated unique patterns along the altitudinal gradient. However, no altitudinal dependence was observed for bacterial diversity and community structure in the subsurface soil. Additionally, a shift in bacterial ecological groups is evident with changing soil depth. Copiotrophic taxa thrive in surface soils characterized by higher carbon and nutrient content, while oligotrophic taxa dominate in subsurface soils with more limited resources. Bacterial community characteristics exhibited strong correlations with soil organic carbon in both soil layers, followed by pH in the surface soil and soil moisture in the subsurface soil. With increasing depth, there is an observable increase in taxa-taxa interaction complexity and network structure within bacterial communities. The surface soil exhibits greater sensitivity to environmental perturbations, leading to increased modularity and an abundance of positive relationships in its community networks compared to the subsurface soil. Furthermore, the bacterial community at different depths was influenced by combining deterministic and stochastic processes, with stochasticity (homogenizing dispersal and undominated) decreasing and determinism (heterogeneous selection) increasing with soil depth.

Effects of litter and root inputs on soil CH4 uptake rates and associated microbial abundances in natural temperature subalpine forests.

Climate change altered the quantities of aboveground plant litter and root inputs, but the effects on soil CH4 uptake rates and underlying mechanisms remain unclear. To investigate these factors, a three-year detritus input and removal treatment (DIRT) study including six treatments (namely, CK, control; NL, litter removal; DL, double litter; NR, root exclusion; NRNL, root exclusion plus litter removal; and NRDL, root exclusion plus double litter) was conducted in broadleaf and coniferous forest subalpine forest ecosystems. The results showed that both the subalpine forest soils acted as sink for atmospheric CH4 across all treatments, while the broadleaf forest had consistently higher CH4 uptake rates than the coniferous forest. Based on the annual mean values, root exclusion (NR, NRNL and NRDL) significantly decreased soil CH4 uptake rates by 35.9 %, 31.0 % and 43.4 % in the broadleaf forest and 36.7 %, 31.9 % and 40.6 % in the coniferous forest compared with CK treatments, respectively. Meanwhile, the mean soil CH4 uptake rates were significantly reduced by 23.6 % and 17.3 % in the broadleaf forest and the coniferous forest under the DL treatments, respectively; nevertheless, the NL treatment significantly increased soil CH4 uptake rates by 19.68 % and 14.4 %, respectively. The results clearly demonstrated that root exclusion exerted a greater influence on soil CH4 uptake rates than plant litter manipulations. Correlation and redundancy analysis (RDA) revealed that the separation of root exclusion treatments from aboveground plant litter manipulations was based on higher soil water content, NH4+-N and NO3--N concentrations, and lower DOC (dissolved organic carbon) concentrations and methanotroph pmoA gene abundance. The results suggest that future alterations in aboveground plant litter and root input, particularly a reduction in root input, can exert a stronger influence on regulating soil CH4 uptake than aboveground litter manipulations in subalpine forests with cold and humid climatic conditions in response to future climate scenarios.

The Impact and Determinants of Mountainous Topographical Factors on Soil Microbial Community Characteristics.

Soil bacterial and fungal community communities play significant ecological functions in mountain ecosystems. However, it is not clear how topographic factors and soil physicochemical properties influence changes in microbial community structure and diversity. This study aims to investigate how altitude and slope orientation affect soil physicochemical properties, soil microbial communities, and their contributing factors. The assessment was conducted using Illumina MiSeq sequencing in various altitude gradients and on slopes with different aspects (shady slopes and sunny slopes) in the subalpine meadow of Dongling Mountain, Beijing. Topographical factors had a significant effect on soil physicochemical properties: the primary factors determining the structure of microbial communities are total potassium (TK), ammonium nitrogen (NH4+-N), and soil organic carbon (SOC). There was no significant change in the diversity of the bacterial community, whereas the diversity of the fungal community displayed a single-peaked trend. The effect of slope orientation on microbial communities was not as significant as the effect of elevation on them. The number of bacterial communities with significant differences showed a unimodal trend, while the number of fungal communities showed a decreasing trend. The co-occurrence network of fungal communities exhibits greater intricacy than that of bacterial communities, and bacterial communities are more complex in soils with sunny slopes compared to soils with shady slopes, and the opposite is true for fungal communities. The identification of the main factors that control soil microbial diversity and composition in this study, provided the groundwork for investigating the soil microbial response and adaptation to environmental changes in subalpine meadows.

Design and Testing of a Simulator for Micro-Vibration Testing of Star Sensor.

(1) Background: To simulate the micro-vibration environment of the star sensor mounting surface, a multi-dimensional micro-vibration simulator based on the Gough-Stewart platform was designed, which could effectively reproduce space six-dimensional acceleration; (2) Methods: Firstly, the integrated design of a gravity unloading system and micro-vibration simulation platform was adopted, and the first six natural frequencies and mode diagrams of the simulator were obtained by modal analysis. Then, the complete dynamic equation of the simulator was established, and the relationship between the acceleration of the upper platform and the driving force of the legs was deduced, which was verified by co-simulation. Finally, the whole machine test was carried out using the frequency response function based on the actual simulator without multiple iterations; (3) Results: The test results show that the micro-vibration simulator can reproduce space six-dimensional acceleration, with an output bandwidth of 5-300 Hz, and maximum error of 9.19%; (4) Conclusions: The micro-vibration simulator platform has the characteristics of a highly precise, large analog bandwidth and takes up less space, is conducive to transportation, and can accurately reproduce the six-degree-of-freedom space micro-vibrations for the star sensor.

Research on Configuration Design Optimization and Trajectory Planning of Manipulators for Precision Machining and Inspection of Large-Curvature and Large-Area Curved Surfaces.

In recent years, high-quality surfaces with large areas and curvatures have been increasingly used in engineering, but the precision machining and inspection of such surfaces is a particular challenge. Surface machining equipment needs to have a large working space, high flexibility, and motion accuracy to meet the demands of micron-scale precision machining. However, meeting these requirements may result in extremely large equipment sizes. To solve this problem, an eight-degree-of-freedom redundant manipulator with one linear and seven rotational joints is designed to assist in the machining described in this paper. The configuration parameters of the manipulator are optimized by an improved multi-objective particle swarm optimization algorithm to ensure that the working space of the manipulator completely covers the working surface and that the size of the manipulator is small. In order to improve the smoothness and accuracy of manipulator motion on large surface areas, an improved trajectory planning strategy for a redundant manipulator is proposed. The idea of the improved strategy is to pre-process the motion path first and then use a combination of the clamping weighted least-norm method and the gradient projection method to plan the trajectory, while adding a reverse planning step to solve the singularity problem. The resulting trajectories are smoother than those planned by the general method. The feasibility and practicality of the trajectory planning strategy are verified through simulation.

Prediction of composting maturity and identification of critical parameters for green waste compost using machine learning.

Ensuring the maturity of green waste compost is crucial to composting processes and quality control of compost products. However, accurate prediction of green waste compost maturity remains a challenge, as there are limited computational methods available. This study aimed to address this issue by employing four machine learning models to predict two indicators of green waste compost maturity: seed germination index (GI) and T value. The four models were compared, and the Extra Trees algorithm exhibited the highest prediction accuracy with R2 values of 0.928 for GI and 0.957 for T value. To identify the interactions between critical parameters and compost maturity, The Pearson correlation matrix and Shapley Additive exPlanations (SHAP) analysis were conducted. Furthermore, the accuracy of the models was validated through compost validation experiments. These findings highlight the potential of applying machine learning algorithms to predict green waste compost maturity and optimise process regulation.

Cancer survival: left truncation and comparison of results from hospital-based cancer registry and population-based cancer registry.

Background: Cancer survival is an important indicator for evaluating cancer prognosis and cancer care outcomes. The incidence dates used in calculating survival differ between population-based registries and hospital-based registries. Studies examining the effects of the left truncation of incidence dates and delayed reporting on survival estimates are scarce in real-world applications. Methods: Cancer cases hospitalized at Nantong Tumor Hospital during the years 2002-2017 were traced with their records registered in the Qidong Cancer Registry. Survival was calculated using the life table method for cancer patients with the first visit dates recorded in the hospital-based cancer registry (HBR) as the diagnosis date (OSH), those with the registered dates of population-based cancer (PBR) registered as the incidence date (OSP), and those with corrected dates when the delayed report dates were calibrated (OSC). Results: Among 2,636 cases, 1,307 had incidence dates registered in PBR prior to the diagnosis dates of the first hospitalization registered in HBR, while 667 cases with incidence dates registered in PBR were later than the diagnosis dates registered in HBR. The 5-year OSH, OSP, and OSC were 36.1%, 37.4%, and 39.0%, respectively. The "lost" proportion of 5-year survival due to the left truncation for HBR data was estimated to be between 3.5% and 7.4%, and the "delayed-report" proportion of 5-year survival for PBR data was found to be 4.1%. Conclusion: Left truncation of survival in HBR cases was demonstrated. The pseudo-left truncation in PBR should be reduced by controlling delayed reporting and maximizing completeness. Our study provides practical references and suggestions for evaluating the survival of cancer patients with HBR and PBR.

The vertical distribution and control factor of microbial biomass and bacterial community at macroecological scales.

Microorganisms exist throughout the soil profile and those microorganisms living in deeper soil horizons likely play key roles in regulating biogeochemical processes. However, the vertical differentiations of microbes along soil depth and their global biogeographical patterns remain poorly understood. Herein, we conducted a global meta-analysis to clarify the vertical changes of microbial biomass, diversity, and microbial relative abundance across the soil profiles. Data was collected from 43 peer-reviewed articles of 110 soil profiles (467 observations in total) from around the world. We found soil microbial biomass and bacterial diversity decreased with depth in soils. Among examined edaphic factors, the depth variation in soil pH exhibited significant negative associations with the depth change in microbial biomass and bacterial Shannon index, while soil total organic carbon (TOC) and total nitrogen (TN) exhibited significant positive associations. For the major bacteria phyla, the relative abundances of Proteobacteria and Bacteroidetes decreased with soil depth, while Chloroflexi, Gemmatimonadetes, and Nitrospirae increased. We found both parallels and differences in the biogeographical patterns of microbial attribute of topsoil vs. subsoil. Microbial biomass was significantly controlled by the soil nutrient concentrations in both topsoil and subsoil compared with climatic factors, while bacterial Shannon index was significantly controlled by the edaphic factors and across latitudes or climatic factors. Moreover, mean annual precipitation can also be used as a predictor of microbial biomass in subsoil which is different from topsoil. Collectively, our results provide a novel integrative view of how microbial biomass and bacterial community response to soil depth change and clarify the controlling factors of the global distribution patterns of microbial biomass and diversity, which are critical to enhance ecosystem simulation models and for formulating sustainable ecosystem management and conservation policies.

Riverine CO2 variations in permafrost catchments of the Yangtze River source region: Hot spots and hot moments.

Rivers and streams are pivotal modulators in regional and global carbon cycles, but riverine CO2 flux is still uncertain for permafrost watersheds. Here we present the seasonal CO2 partial pressure (pCO2) and CO2 emission flux (FCO2) of 8 rivers and streams in the Yangtze River source region (YRSR), which have high permafrost coverage and seasonally thawed active layer. The YRSR rivers and streams are generally supersaturated with CO2, although there are a few sites with CO2 undersaturation during spring. The small headwater streams are CO2 hot spots that show significantly higher pCO2 (52 % higher) and FCO2 (792 % higher) than larger rivers. Both pCO2 and FCO2 show distinct seasonality across the study sites. pCO2 and FCO2 peak in summer and exhibit much lower levels in autumn and spring, indicating that hot moments of riverine CO2 occur in summer. Seasonal pCO2 and FCO2 variations are jointly controlled by hydrology, active layer dynamics and associated processes. The warm summer causes active layer thaw and highly active soil respiration, which release a large quantity of soil carbon and increase the CO2 sources via strengthened hydrologic connectivity. The high rainfall and more thaw-released water in summer bring high discharge, which can increase the water velocity and gas exchange rate and thus CO2 emission flux. Most of the variances of seasonal FCO2 (95 %) can be explained by hydrology and active layer thaw depth. Nevertheless, the hydrological process and seasonally thawed active layer over Qinghai-Tibet Plateau (QTP) play crucial roles in riverine carbon export due to the summer monsoon-dominated climate in QTP. Our results suggest that full seasonal coverage of CO2 dynamics is essential to quantify the annual CO2 flux accurately. Changing climate and warming permafrost may alter the annual CO2 emission due to deeper flow paths, hydrology changes, and longer emission windows throughout the year.

Prediction of carbon dioxide production from green waste composting and identification of critical factors using machine learning algorithms.

Controlling carbon dioxide produced from green waste composting is a vital issue in response to carbon neutralization. However, there are few computational methods for accurately predicting carbon dioxide production from green waste composting. Based on the data collected, this study developed novel machine learning methods to predict carbon dioxide production from green waste composting and made a comparison among six methods. After eliminating the extreme outliers from the dataset, the Random Forest algorithm achieved the highest prediction accuracy of 88% in the classification task and showed the top performance in the regression task (root mean square error = 23.3). As the most critical factor, total organic carbon, with the Gini index accounting for about 59%, can provide guidance for reducing carbon emissions from green waste composting. These results show that there is great potential for using machine learning algorithms to predict carbon dioxide output from green waste composting.