Different developmental genes shape frequent dynamic inter-chromosomal contacts with rDNA units in human and Drosophila cells. In the course of differentiation, changes in these contacts occur, coupled with changes in the expression of hundreds of rDNA-contacting genes. The data suggest a possible role of nucleoli in the global regulation of gene expression. However, the mechanism behind the specificity of these inter-chromosomal contacts, which are rebuilt in every cell cycle, is not yet known. Here, we describe the strong association of rDNA-contacting genes with numerous long intergenic non-coding RNAs (lincRNAs) in HEK293T cells and in initial and differentiated K562 cells. We observed that up to 600 different lincRNAs were preferentially co-expressed with multiple overlapping sets of rDNA-contacting developmental genes, and there was a strong correlation between the genomic positions of rDNA-contacting genes and lincRNA mappings. These two findings suggest that lincRNAs might guide the corresponding developmental genes toward rDNA clusters. We conclude that the inter-chromosomal interactions of rDNA-contacting genes with nucleoli might be guided by lincRNAs, which might physically link particular genomic regions with rDNA clusters. Full article

Observational studies revealed changes in Immunoglobulin G (IgG) N-glycosylation during the aging process. However, it lacks causal insights and remains unclear in which direction causal relationships exist. The two-sample bidirectional Mendelian randomization (MR) design was adopted to explore causal associations between IgG N-glycans and the senescence-associated secretory phenotype (SASP). Inverse variance weighted (IVW) and Wald ratio methods were used as the main analyses, supplemented by sensitivity analyses. Forward MR analyses revealed causal associations between the glycan peak (GP) and SASP, including GP6 (odds ratio [OR] = 0.428, 95% confidence interval [CI] = 0.189–0.969) and GP17 (OR = 0.709, 95%CI = 0.504–0.995) with growth/differentiation factor 15 (GDF15), GP19 with an advanced glycosylation end-product-specific receptor (RAGE) (OR = 2.142, 95%  CI  = 1.384–3.316), and GP15 with matrix metalloproteinase 2 (MMP2) (OR = 1.136, 95%  CI =1.008–1.282). The reverse MR indicated that genetic liability to RAGE was associated with increased levels of GP17 (OR = 1.125, 95%  CI  = 1.003–1.261) and GP24 (OR = 1.222, 95%  CI  = 1.046–1.428), while pulmonary and activation-regulated chemokines (PARC) exhibited causal associations with GP10 (OR = 1.269, 95%  CI  = 1.048–1.537) and GP15 (OR = 1.297, 95%  CI = 1.072–1.570). The findings provided suggested evidence on the bidirectional causality between IgG N-glycans and SASP, which might reveal potential regulatory mechanisms. Full article

Automated ultrasonic testing (AUT) is a nondestructive testing (NDT) method widely employed in industries that hold substantial economic importance. To ensure accurate inspections of exclusive AUT data, expert operators invest considerable effort and time. While artificial intelligence (AI)-assisted tools, utilizing deep learning models trained on extensive in-laboratory B-scan images, whether they are augmented or synthetically generated, have demonstrated promising performance for automated ultrasonic interpretation, ongoing efforts are needed to enhance their accuracy and applicability. This is possible through the evaluation of their performance with experimental ultrasonic data. In this study, we introduced a real-world ultrasonic B-scan image dataset generated from proprietary recorded AUT data during industrial automated girth weld inspection in oil and gas pipelines. The goal of inspection in our dataset was detecting a common type of defect called lack of fusion (LOF). We experimentally evaluated deep learning models for automatic weld defect detection using this dataset. Our assessment covers the baseline performance of state-of-the-art (SOTA) models, including transformer-based models (DETR and Deformable DETR) and YOLOv8. Their flaw detection performance in ultrasonic B-scan images has not been reported before. The results show that, without heavy augmentations or architecture customization, YOLOv8 outperforms the other models with an F1 score of 0.814 on our test set. Full article

Mangrove ecosystems provide key ecosystem services in coastal areas. This study describes the riparian mangrove of the Wouri estuary, in the Douala region (Cameroon), emphasizing the changes in this ecosystem over the past decade and its current state. It highlights the different groups of actors who participate in the management and regulation of the resource. Finally, an analysis of the governance of the mangrove wood resource based on the theory of common goods by Elinor Ostrom (1990) is proposed by examining the results obtained from the previous points. The scientific interest lies in contributing to a better understanding of the socio-ecological changes in the mangrove in the context of increasing anthropogenic pressures, highlighting the governance challenges and conservation opportunities in a strategic region of Central Africa. This research reveals complex processes that characterize mangrove ecosystems on the Manoka and Cap Cameroon Islands. The lack of urbanization regulations, continued infrastructure growth, repeated flooding, and coastal erosion all have a negative impact on natural landscapes and forests. The use of wood for smoking and fishing, as well as coastal pollution resulting from deficient garbage management, also have a considerable influence. Strategic interventions are needed to ensure sustainable ecosystem management. Recommendations include the application of rules to prevent forest overexploitation. Full article

Eastern Diamondback Rattlesnake (Crotalus adamanteus) envenomation is a medical emergency encountered in the Southeastern United States. The venom contains a snake venom thrombin-like enzyme (SVTLE) that is defibrinogenating, causing coagulopathy without effects on platelets in humans. This investigation utilized thrombelastographic methods to document this coagulopathy kinetically on the molecular level in a rabbit model of envenomation via the analyses of whole blood samples without and with platelet inhibition. Subsequently, the administration of a novel ruthenium compound containing site-directed antivenom abrogated the coagulopathic effects of envenomation in whole blood without platelet inhibition and significantly diminished loss of coagulation in platelet-inhibited samples. This investigation provides coagulation kinetic insights into the molecular interactions and results of SVTLE on fibrinogen-dependent coagulation and confirmation of the efficacy of a ruthenium antivenom. These results serve as a rationale to investigate the coagulopathic effects of other venoms with this model and assess the efficacy of this site-directed antivenom. Full article

Iron red, a traditional Jingdezhen overglaze color, is primarily colored with iron oxide (Fe₂O₃). In traditional processes, the main ingredient for the iron red overglaze color, raw iron red, is produced by calcining iron vitriol (FeSO₄·7H₂O). Analysis of ancient iron red porcelain samples indicates that the coloration is unstable, ranging from bright red to dark red and occasionally to black. Addressing this, the present study, from a ceramic technology standpoint, conducts a series of calcination experiments on industrial iron vitriol at varying temperatures. Utilizing methodologies such as differential scanning calorimetry-thermogravimetry (DSC-TG), Raman spectroscopy, X-ray diffraction (XRD), scanning electron microscopy with X-ray energy dispersive spectrometry (SEM-EDS), and optical microscopy (OM), this research scientifically explores the impact of iron vitriol’s calcination temperature on the coloration of traditional Jingdezhen iron red overglaze color. The findings indicate that from room temperature to 550 °C, the dehydration of iron vitriol resulted in the formation of Fe₂(SO₄)₃ and a minimal amount of α-Fe₂O₃, rendering the iron red overglaze color a yellowish-red shade. At 650 °C, the coexistence of Fe₂(SO₄)₃ and α-Fe₂O₃ imparted a brick-red color to the iron red. As the temperature was elevated to 700 °C, the desulfurization of Fe₂(SO₄)₃ produced α-Fe₂O₃, transitioning the iron red to an orange red. With further temperature increase to 750 °C, the particle size of α-Fe₂O₃ grew and the crystal reflectivity decreased, resulting in a purplish-red hue. Throughout this stage, the powder remained in a single α-Fe₂O₃ phase. Upon further heating to 800 °C, the crystallinity of α-Fe₂O₃ enhanced, giving the iron red overglaze color a dark red or even black appearance. Full article

Ceramic coatings were formed on the surface of as-cast Al5.2Zn1.7Mg0.4Ni0.3Fe and heat-treated Al7.0Zn2.7Mg0.5Ni0.4Fe “nikalin” aluminum alloys by using the plasma electrolytic oxidation (PEO) technique in a silicate–alkaline electrolyte. Uniform coatings containing a minimum number of defects and consisting predominantly of a γ-Al₂O₃ phase were synthesized on the surface of both Al-Zn-Mg-Ni-Fe alloys. The coatings had a microhardness of 660–1200 HV, which is 3.5–11 times higher than that of the “bare” as-cast and heat-treated alloy. The coating on the Al5.2Zn1.65Mg0.4Ni0.3Fe alloy had the highest peak hardness, which is probably caused by the lower residual alloying elements Zn and Mg in the coating bulk. As a consequence, the PEO coating with the highest hardness synthesized on the as-cast alloy exhibited a lower wear rate as compared to the heat-treated alloy. The polarization curves in 3.5% NaCl show that the PEO coatings in all cases reduced the corrosion current density and shifted the corrosion potential toward positive values, thus indicating protective properties of the coatings. The corrosion rate of the as-cast and heat-treated Al-Zn-Mg-Ni-Fe alloys increased noticeably by about 3.7–5.7 times after PEO treatment. A relationship between the residual alloying elements Zn and Mg in the bulk of the PEO coatings and corrosion resistance was established. Full article

An epilepsy diagnosis reduces a patient’s quality of life tremendously, and it is a fate shared by over 50 million people worldwide. Temporal lobe epilepsy (TLE) is largely considered a nongenetic or acquired form of epilepsy that develops in consequence of neuronal trauma by injury, malformations, inflammation, or a prolonged (febrile) seizure. Although extensive research has been conducted to understand the process of epileptogenesis, a therapeutic approach to stop its manifestation or to reliably cure the disease has yet to be developed. In this review, we briefly summarize the current literature predominately based on data from excitotoxic rodent models on the cellular events proposed to drive epileptogenesis and thoroughly discuss the major molecular pathways involved, with a focus on neurogenesis-related processes and transcription factors. Furthermore, recent investigations emphasized the role of the genetic background for the acquisition of epilepsy, including variants of neurodevelopmental genes. Mutations in associated transcription factors may have the potential to innately increase the vulnerability of the hippocampus to develop epilepsy following an injury—an emerging perspective on the epileptogenic process in acquired forms of epilepsy. Full article

Since the start of the new century, the focus of China’s socioeconomic development has gradually shifted from prioritizing efficiency to social equity, which is an important ingredient of sustainable development. The accessibility of public service facilities (PSFs) is vital for achieving social–spatial sustainability. As a basic tool for arranging PSFs, however, traditional urban plannings mainly focus on the spatial uniform distribution of facilities rather than the variance of the spatial distribution of populations they serve. So, by taking the dual perspective view, this paper quantitatively measures the balance of PSFs’ spatial distribution of and populations of Urumqi City at the sub-district level. Based on point of interest (POI) data, this paper calculates and analyzes Gini coefficients and location entropy of three basic PSF types: living service facilities (LSFs), primary schools and kindergartens (PSAKs), and medical facilities (MFs). The research finds that the Gini coefficients of LSFs, PSAKs, and MFs in Urumqi City are 0.42, 0.36, and 0.34, respectively. Moreover, there are three significant mismatch areas: an extremely high PSF index value in low-population sub-districts, an extremely low index value in remote suburbs, and an extremely low index value in the city center. These findings indicate an obvious imbalance between the spatial distribution of PSFs and the population in Urumqi, which may be a critical impediment to sustainable development. Based on these, this paper offers guidance for achieving sustainability in the allocation of spatial resources. Full article

In an era of a significant pace of economic, technological, and social development, an uninterrupted energy supply is one of the most important variables determining a country’s economic sovereignty, position in international relations, and quality of life. The aim of this study was to develop a method of multifaceted comparative analysis of energy security of neighboring countries (Poland and Slovakia) based on the level of fulfillment of selected goals of Agenda 2030 and related tasks. The analysis of energy security, due to its multifaceted nature, requires an examination of Goal 7 (clean and accessible energy) and the corresponding tasks associated with Goals 8, 9, and 13 of Agenda 2030. The research objective involved the analysis of energy dependence, electricity, diversification of gas supply, terminals and gas storage facilities, and clean energy. The countries studied are in the midst of achieving the goals of Agenda 2030, and the current rate of growth and relevance of the energy measures taken are promising. Further actions are recommended in the areas of diversification of generation capacity, appropriate levels of investment, availability of infrastructure and expertise, increasing the share of renewable energy sources (RES) and natural gas, and increasing efficiency in electricity consumption. Full article

Shwachman Diamond Syndrome (SDS) is a multi-system disease characterized by exocrine pancreatic insufficiency with malabsorption, infantile neutropenia and aplastic anemia. Life-threatening complications include progression to acute myeloid leukemia (AML) or myelodysplastic syndrome (MDS), critical deep-tissue infections and asphyxiating thoracic dystrophy. In most patients, SDS results from biallelic pathogenic variants in the SBDS gene, different combinations of which contribute to heterogenous clinical presentations. Null variants are not well tolerated, supporting the theory that the loss of SBDS expression is likely lethal in both mice and humans. A novel complex genotype (SBDS:c.[242C>G;258+2T>C];[460-1G>A]/WFS1:c.[2327A>T];[1371G>T]) was detected in a family with recurrent neonatal deaths. A female neonate died three hours after birth with hemolytic anemia, and a male neonate with severe anemia, thrombocytopenia and neutropenia succumbed on day 40 after Staphylococcus epidermidis infection. A subsequent review of the literature focused on fatal complications, complex SBDS genotypes and/or unusual clinical presentations and disclosed rare cases, of which some had unexpected combinations of genetic and clinical findings. The impact of pathogenic variants and associated phenotypes is discussed in the context of data sharing towards expanding scientific expert networks, consolidating knowledge and advancing an understanding of novel underlying genotypes and complex phenotypes, facilitating informed clinical decisions and disease management. Full article

3-nitro-1,2,4-triazol-5-one (NTO) has been widely used as a kind of insensitive single-compound explosive owing to its excellent balance between safety and explosive energy. To reduce its possible acid corrosion and extend its application to insensitive ammunition, acid protection research on NTO-based explosives is significant. Traditionally, the acid protection effect was evaluated by metal corrosion, which is time-consuming and qualitative. An efficient and quantitative method is desirable for evaluating the acid protection effect and exploring novel protection materials. Herein, a polyimide of 4,4’-(hexafluoroisopropene)diphthalic anhydride (6FDA)/2,2-bis(trifluoromethyl)-4,4-diaminobiphenyl (TFMB) was synthesized by replacing the 4,4’-diaminodiphenyl ether (ODA) monomer with a TFMB monomer to act as an acid-protective coating material for NTO-based explosives. Compared with three other coating materials, polyvinylidene fluoride (PVDF), polyetherimide (PEI), and copolyimide (P84), the fluorinated polyimide exhibits the best acid protection effect. Moreover, a new method was constructed to obtain the pH time-dependent curve in order to evaluate efficiently the acid protection effect of the polymer materials. By the virtue of molecular dynamic simulation (Materials Studio 2023), the interfacial effects of the coating materials with NTO-based explosives were obtained. The study provides an interpretation of the acid protection effect on the molecular level, suggesting that the higher content of fluorine atoms is beneficial for stabilizing the active hydrogen atom of the NTO by forming intermolecular hydrogen bonds. Full article

A novel three-dimensional isolation system consisting of thick rubber bearing (TNRB), disc spring bearing (DSB), and laminated rubber bearing (LRB) in series combination was designed, and its composition, principle, and isolation effect were comprehensively analyzed. By combining numerical examples, the whole structure method is used to compare and analyze the dynamic characteristics, dynamic response, and structural damage of large-span isolation structures containing new three-dimensional systems, large-span horizontal isolation structures based on LRB, and corresponding non-isolation structures under multi-dimensional seismic excitation. The results show that compared with the horizontal isolation structure based on LRB, the structure of the new three-dimensional isolation system has a 33% longer vertical natural vibration period, a 17.85% attenuation in the overall damage index, and a 36.86% increase in vertical energy dissipation capacity. It can achieve good isolation effects in both horizontal and vertical directions, which can form a favorable complement to the horizontal isolation structure based on LRB in terms of vertical isolation and energy dissipation. Full article

Sea–land segmentation (SLS) is a crucial step in coastline extraction. In CNN-based approaches for coastline feature extraction, downsampling is commonly used to reduce computational demands. However, this method may unintentionally discard small-scale features, hindering the capture of essential global contextual information and clear edge information necessary for SLS. To solve this problem, we propose a novel U-Net structure called Deformable Attention Edge Network (DAENet), which integrates edge enhancement algorithms and a deformable self-attention mechanism. First of all, we designed a multi-scale transformation (MST) to enhance edge feature extraction and model convergence through multi-scale transformation and edge detection, enabling the network to capture spatial–spectral changes more effectively. This is crucial because the deformability of the Deformable Attention Transformer (DAT) modules increases training costs for model convergence. Moreover, we introduced DAT, which leverages its powerful global modeling capabilities and deformability to enhance the model’s recognition of irregular coastlines. Finally, we integrated the Local Adaptive Multi-Head Attention-based Edge Detection (LAMBA) module to enhance the spatial differentiation of edge features. We designed each module to address the complexity of SLS. Experiments on benchmark datasets demonstrate the superiority of the proposed DAENet over state-of-the-art methods. Additionally, we conducted ablation experiments to evaluate the effectiveness of each module. Full article

Indoor scenes are crucial components of urban spaces, with logos serving as vital information within these environments. The accurate perception of logos is essential for effectively operating mobile robots in indoor environments, which significantly contributes to many upper-level applications. With the rapid development of neural networks, numerous deep-learning-based object-detection methods have been applied to logo detection. However, most of these methods depend on large labeled datasets. Given the fast-changing nature of logos in indoor scenes, achieving reliable detection performance with either the existing large labeled datasets or a limited number of labeled logos remains challenging. In this article, we propose a method named MobileNetV2-YOLOv4-UP, which integrates unsupervised learning with few-shot learning for logo detection. We develop an autoencoder to obtain latent feature representations of logos by pre-training on a public unlabeled logo dataset. Subsequently, we construct a lightweight logo-detection network and embed the encoder weights as prior information. Training is performed on a small dataset of labeled indoor-scene logos to update the weights of the logo-detection network. Experimental results on the public logo625 dataset and our self-collected LOGO2000 dataset demonstrate that our method outperforms classic object-detection methods, achieving a mean average detection precision of 83.8%. Notably, our unsupervised pre-training strategy (UP) has proven effective, delivering a 15.4% improvement. Full article

Rice is one of the most important crops for food supply, and there are multiple differences in the quality of rice in different geographic regions, which have a significant impact on subsequent yields and economic benefits. The traditional rice identification methods are time-consuming, inefficient, and delicate. This study proposes a deep learning-based method for fast and non-destructive classification of rice grown in different geographic environments. The experiment collected rice with the name of Ji-Japonica 830 from 10 different regions, and a total of 10,600 rice grains were obtained, and the fronts and backsides of the seeds were photographed with a camera in batches, and a total of 30,000 images were obtained by preprocessing the data. The proposed improved residual network architecture, High-precision Residual Network (HResNet), was used to compare the performance of the models. The results showed that HResNet obtained the highest classification accuracy result of 95.13%, which is an improvement of 7.56% accuracy with respect to the original model, and validation showed that HResNet achieves a 98.7% accuracy in the identification of rice grown in different soil classes. The experimental results show that the proposed network model can effectively recognize and classify rice grown in different soil categories. It can provide a reference for the identification of other crops and can be applied for consumer and food industry use. Full article

This systematic literature review explores how the implementation of project-based-learning (PBL) as an experiential pedagogical methodology in engineering education contributes to the development of real-world skills among students. The methodology applied was the PRISMA protocol with searches in two databases in a 24 year timeframe. The research reviewed 54 pieces to explore the contribution of PBL to seven pillars of a holistic pedagogical model comprising the following categories: technology, an integrated curriculum, an international focus, sustainability, a multidisciplinary focus, simulation, and professional environments. Varied PBL developments across these pillars reveal challenges, including aligning with real-world complexities and promoting interdisciplinary integration. Despite obstacles, PBL in engineering shows promise for enhancing students’ skills and channeling the added value of a holistic pedagogical model, despite significant differences in the number of experiences associated with each category. Limitations include restricted article access, emphasizing the need for open science promotion. Full article

Processed manure products have the potential to substitute chemical fertilizers and the use of these products may increase resource efficiency in the food system and decrease emissions of ammonia (NH₃) and greenhouse gasses (GHG). The yields of maize and grass, as well as emissions, have been determined from a processed manure product: liquid ammonium sulfate from nitrogen stripping animal manure (AS), in comparison to a regular mineral fertilizer, calcium ammonium nitrate (CAN), in a greenhouse experiment and a field demonstration using a sandy and a clay soil. NH₃ emissions were determined by comparing AS with a dairy manure as a reference. The yield of both crops, their nitrogen nutrient use efficiency (NUE), and nitrous oxide (N₂O) emissions were not significantly different, while NH₃ emission was lower from AS compared to the dairy manure. As a side-effect, the sulfur (S) contents of the grass in the fields fertilized with AS were much higher than in the non-fertilized control. We conclude that AS, produced here with a pH < 5.5, can be used as an alternative for CAN in Dutch dairy systems, or similar other system, if S leaching losses do not pose a problem for the environment. Meanwhile, care should be taken not to exceed S in feed above toxic levels for ruminants. Full article

The introduction of the concepts of shear elastic strain (${\epsilon }^{-}$) and tensile elastic strain (${\epsilon }^{+}$) is a catalyst for new horizons of research into supply chain elasticity. Functional formulas encompassing the metrics of ${\epsilon }^{-}$ and ${\epsilon }^{+}$, their critical point, maximum strain value, and similar parameters are established through rigorous mathematical derivations. The supply chain elasticity of agricultural commodities, including grains, apples, and wheat, are assessed by utilizing the derived formulas. The results show that the metrics of supply chain elastic strain serve as direct metrics of measuring the supply chain’s anti-interference capability, and they also facilitate an objective assessment of the supply chain’s safety and stability. The formula is succinctly derived, and it yields objective outcomes with general applicability, particularly suited for research and application for supply chain elasticity. Full article

With uncertainty intensifying the international technological innovation environment, the innovation situation of Chinese manufacturing enterprises has been impacted. Based on 12,781 micro panel data in 2011–2020 of 2347 Chinese A-share manufacturing listed enterprises, this paper empirically analyzes the impact of innovation plight faced by enterprises on operational efficiency. The innovation plight in this article refers to the degree to which the actual innovation performance of enterprises has not reached the expected innovation performance or is introduced by an innovation gap, measured by the difference when actual innovation performance is lower than the expected innovation performance. The empirical results show that the innovation plight of manufacturing enterprises significantly inhibits operational efficiency by reducing their risk tolerance, development ability expectation, and profitability. After using a series of tests, such as the instrumental variable method, replacing the dependent variable, and changing the parameters for measuring the independent variable, the conclusion is still robust. In addition, the results illustrate that the inhibitory effect of innovation plight on operational efficiency is more obvious for non-state-owned enterprises, small and medium-sized enterprises, high-tech enterprises, and enterprises in the eastern region. Finally, we formulate some relevant management suggestions. Full article

The advent of Industry 4.0 has ushered in a new era of technological advancements, particularly in integrating information technology with physical devices. This convergence has given rise to smart devices and the Internet of Things (IoT), revolutionizing industrial processes. However, despite the push towards predictive maintenance, there still is a significant gap in fault prediction algorithms for electrical machines. This paper proposes a signal spectrum-based machine learning approach for fault prediction, specifically focusing on bearing faults. This study compares the effectiveness of traditional neural network algorithms with a novel approach integrating fuzzy logic. Through extensive experimentation and analysis of vibration spectra from various mechanical faults in bearings, it is demonstrated that the fuzzy-neuro network model outperforms traditional neural networks, achieving a validation accuracy of 99.40% compared to 94.34%. Incorporating fuzzy logic within the neural network framework offers advantages in handling complex fault combinations, showing promise for applications requiring higher accuracy in fault detection. While initial results are encouraging, further validation with more complex fault scenarios and additional fuzzy layers is recommended to fully explore the potential of fuzzy-neuro networks in fault prediction for electrical machines. Full article

The Three Gorges Project is the largest hydraulic hub project in the world, and its hydrological management has altered the hydrological environment of the reservoir area, affecting the carbon emission and absorption of the reservoir water. In this study, representative hydrological stations in the Three Gorges Reservoir area were selected as research sites to monitor the CO₂ and CH₄ fluxes of the reservoir water and nine environmental factors during the drainage and impoundment periods in 2022. The study aimed to explore the mechanisms of hydrological management and environmental factors on greenhouse gas emissions. The results showed that the mean CO₂ fluxes of the reservoir water during the drainage and impoundment periods were (103.82 ± 284.86) mmol·m⁻²·d⁻¹ and (134.39 ± 62.41) mmol·m⁻²·d⁻¹, respectively, while the mean CH₄ fluxes were (1.013 ± 0.58) mmol·m⁻²·d⁻¹ and (0.571 ± 0.70) mmol·m⁻²·d⁻¹, respectively, indicating an overall “carbon source” characteristic. Through the evaluation of the characteristic importance of environmental factors, it was found that the main controlling factors of CO₂ flux during the drainage period were total phosphorus (TP) and chlorophyll a (Chl_a), while total nitrogen (TN) was the main controlling factor during the impoundment period. Dissolved organic carbon (DOC) was the main controlling factor of CH₄ flux during the different periods. Based on these findings, a “source-sink” mechanism of CO₂ and CH₄ in the Three Gorges Reservoir water under reservoir regulation was proposed. This study is of great significance for revealing the impact of reservoir construction on global ecosystem carbon cycling and providing scientific support for formulating “emission reduction and carbon sequestration” plans and achieving “dual carbon” goals. Full article