After the rural tax and fee reform in China in the 2000s, the increased administrative nature of rural governance weakened state–peasant connections, rendering local cadres’ traditional societal-oriented consent strategies ineffective. To gain peasants’ consent to state policies and reconnect with them, grassroots officials adopted a more complex, covert and naturalized strategy for constructing consent, integrating it into peasants’ daily lives. This study uses the “rural construction” initiative in Chuxi county, China, as a case study to explore the construction of consent. The findings indicate that constructing peasant consent is a process of continuous interaction between the individual actor and social structures. In the regularization phase, grassroots officials use institutional practices to facilitate consent, including winning the hearts and minds of villagers, solving “thought” problems, shaping behavioural norms and cultivating lower-level agents. In the mobilization phase, when consent is needed, grassroots officials flexibly adapt the pre-established institutional elements to elicit specific consent. They do this by fostering an atmosphere of consent, employing divide-and-rule tactics, and contextualizing rules. The study concludes that the party-state is building a broader form of peasant consent in the Xi era, which extends beyond consent to policies.

Detecting cracks in underwater dams is crucial for ensuring the quality and safety of the dam. However, underwater dam cracks are easily obscured by aquatic plants. Traditional single-view visual inspection methods cannot effectively extract the feature information of the occluded cracks, while multi-view crack images can extract the occluded target features through feature fusion. At the same time, underwater turbulence leads to nonuniform diffusion of suspended sediments, resulting in nonuniform flooding of image feature noise from multiple viewpoints affecting the fusion effect. To address these issues, this paper proposes a multi-view fusion network (MVFD-Net) for crack detection in occluded underwater dams. First, we propose a feature reconstruction interaction encoder (FRI-Encoder), which interacts the multi-scale local features extracted by the convolutional neural network with the global features extracted by the transformer encoder and performs the feature reconstruction at the end of the encoder to enhance the feature extraction capability and at the same time in order to suppress the interference of the nonuniform scattering noise. Subsequently, a multi-scale gated adaptive fusion module is introduced between the encoder and the decoder for feature gated fusion, which further complements and recovers the noise flooding detail information. Additionally, this paper designs a multi-view feature fusion module to fuse multi-view image features to restore the occluded crack features and achieve the detection of occluded cracks. Through extensive experimental evaluations, the MVFD-Net algorithm achieves excellent performance when compared with current mainstream algorithms.

The underwater target detection is affected by image blurring caused by suspended particles in water bodies and light scattering effects. To tackle this issue, this paper proposes a reparameterized feature enhancement and fusion network for underwater blur object recognition (REFNet). First, this paper proposes the reparameterized feature enhancement and gathering (REG) module, which is designed to enhance the performance of the backbone network. This module integrates the concepts of reparameterization and global response normalization to enhance the network’s feature extraction capabilities, addressing the challenge of feature extraction posed by image blurriness. Next, this paper proposes the cross-channel information fusion (CIF) module to enhance the neck network. This module combines detailed information from shallow features with semantic information from deeper layers, mitigating the loss of image detail caused by blurring. Additionally, this paper replace the CIoU loss function with the Shape-IoU loss function improves target localization accuracy, addressing the difficulty in accurately locating bounding boxes in blurry images. Experimental results indicate that REFNet achieves superior performance compared to state-of-the-art methods, as evidenced by higher mAP scores on the underwater robot professional competitionand detection underwater objects datasets. REFNet surpasses YOLOv8 by approximately 1.5% in $mAP_{50:95}$ on the URPC dataset and by about 1.3% on the DUO dataset. This enhancement is achieved without significantly increasing the model’s parameters or computational load. This approach enhances the precision of target detection in challenging underwater environments.

The Eastern population of the Lesser White-fronted Goose (EPLWFG) Anser erythropus is shared between Russia and China. The summer range of the EPLWFG has been recognised as a continuous area extending from the Olenyok River in the west to the Anadyr River in the east and northwards from 64°N. The aim of this study was to provide information on breeding behaviour; nest-sites, nesting habitats, and time of nesting; nesting success; timing of summer movements including moult migration; moult timing, duration, and moulting habitats; site fidelity; and the effect of human presence. To accomplish this, we combined the results from field surveys with GPS/GSM tracking. A total of 30 summer tracks from 19 individual EPLWFG were analysed. We estimated breeding propensity in 93.8% of adult LWFG, and this factor did not seem to depend on breeding success in the previous season. Reproductive success was 13.3% in all nesting attempts. Non-breeders arrived three-week later and departed a week earlier. The EPLWFG are highly mobile during the summer. The core moulting site for the entire EPLWFG was discovered by this study and is located along the lower reaches of the San-Yuryakh and Kyuanekhtyakh rivers flowing towards the Omulyakhskaya Bay of the East Siberian Sea. The EPLWFG flightless period was 24.8 ± 2.8 days. A part of failured EPLWFG (43.7 %) migrated back to its early summer breeding/staging site after having completed moult. The strong site fidelity (100%) of adult birds to both nesting and moulting sites promotes the formation of local breeding populations, which could be considered conservation units if genetic studies support this differentiation. The EPLWFG selects the remotest and least human-accessible area for their remigial moult, and the main site was discovered with the help of tracking.

Foodborne diseases are ongoing and significant public health concerns. This study analysed data obtained from the Foodborne Outbreaks Surveillance System of Wenzhou to comprehensively summarise the characteristics of foodborne outbreaks from 2012 to 2022. A total of 198 outbreaks were reported, resulting in 2,216 cases, 208 hospitalisations, and eight deaths over 11 years. The findings suggested that foodborne outbreaks were more prevalent in the third quarter, with most cases occurring in households (30.8%). Outbreaks were primarily associated with aquatic products (17.7%) as sources of contamination. The primary transmission pathways were accidental ingestion (20.2%) and multi-pathway transmission (12.1%). Microbiological aetiologies (46.0%), including Vibrio parahaemolyticus, Salmonella ssp., and Staphylococcus aureus, were identified as the main causes of foodborne outbreaks. Furthermore, mushroom toxins (75.0%), poisonous animals (12.5%), and poisonous plants (12.5%) were responsible for deaths from accidental ingestion. This study identified crucial settings and aetiologies that require the attention of both individuals and governments, thereby enabling the development of effective preventive measures to mitigate foodborne outbreaks, particularly in coastal cities.

Michelia lacei W.W. Smith, a magnolia species categorized as Endangered on the IUCN Red List, is subject to severe disturbance. We carried out field surveys and a review of literature records to present a detailed description of the current status of M. lacei. We then predicted the potential distribution of M. lacei under different climatic scenarios based on 60 occurrence records (53 recorded during our field surveys and 7 earlier records) and 19 bioclimatic variables from the WorldClim database. We selected 18 locations and four bioclimatic variables for model training. Temperature seasonality and annual temperature range were the most influential variables for predicting the potential distribution of the species. We used MaxEnt to model distribution under current climate conditions and four Shared Socioeconomic Pathway scenarios in four future time periods to determine the effects of future climate change on the habitat suitable for the species. We predict areas of moderately and highly suitable habitat will gradually decrease over time. We recommend increased in situ and ex situ conservation efforts to mitigate this habitat decline and protect populations of M. lacei.

To develop more economical and efficient heavy metal adsorbents, natural bentonite was employed as a raw material, and triethoxyvinylsilane served as a grafting agent to achieve the grafting bonding of sodium polyacrylate and bentonite. Structural alterations in the modified bentonite were analyzed through thermogravimetric analysis (TGA), scanning electron microscopy (SEM), and X-ray diffraction (XRD). The adsorption and desorption characteristics of SAPAS-Bentonite and raw bentonite were compared and tested under various conditions, including time, temperature, pH, and lead ion concentration. The adsorption and desorption properties of sodium polyacrylate-grafted bentonite (SAPAS-Bentonite) were compared under various conditions (time, temperature, pH, and lead ion concentration). The results revealed that the modified method successfully achieved nano-scale coating of bentonite particles with sodium polyacrylate, leading to an increase in the maximum adsorption capacity of lead ions by 47.5%, reaching 165.73 mg g. A greater adsorption affinity for lead ions was exhibited by the outer sodium polycarboxylate portion of SAPAS-Bentonite compared with the inner bentonite. The adsorption of internal bentonite was limited by blocking when the adsorption of sodium polyacrylate did not reach the upper limit. The adsorption isotherm shifted from the Langmuir monolayer characteristic of the original bentonite to the S-shaped isotherm, reflecting the sodium polycarboxylate properties of SAPAS-Bentonite. Both bentonites demonstrated strong retention capacity for lead, with SAPAS-Bentonite surpassing raw bentonite in performance. This study provides valuable insights into the potential of SAPAS-Bentonite in the treatment of heavy metal pollution.

The recognizing underwater targets is a crucial component of autonomous underwater vehicle patrols and detection efforts. In the process of visual image recognition in real underwater environment, the spatial and semantic features of the target often appear to different degrees of loss, and the scarcity of specific types of underwater samples leads to unbalanced data on categories. This kind of problem makes the target features appear weak and seriously affects the accuracy of underwater target recognition. Traditional deep learning methods based on data and feature enhancement cannot achieve ideal recognition effect. Based on the above difficulties, this paper proposes an improved feature enhancement network for weak feature target recognition. Firstly, a multi-scale spatial and semantic feature enhancement module is constructed to extract the feature information of the extraction target accurately. Secondly, this paper solves the influence of target feature distortion on classification through multi-scale feature comparison of positive and negative samples. Finally, the Rank & Sort Loss function was used to train the depth target detection to solve the problem of recognition accuracy under highly unbalanced sample data. Experimental results show that the recognition accuracy of the proposed method is 2.28% and 3.84% higher than that of the existing algorithms in the recognition of underwater fuzzy and distorted target images, which demonstrates the effectiveness and superiority of the proposed method.

Smectite illitization is an important diagenetic phenomenon of mudstones, but only rarely has the influence of organic matter (OM) on this process been examined. In the present study, hydrothermal experiments were conducted with smectite (M1, total organic carbon (TOC) <0.3%) and a smectite and N,N-dimethylhexadecylamine (16DMA) complex (M2, TOC >1%). X-ray diffraction (XRD), infrared, X-ray fluorescence (XRF), and organic carbon analyses were employed to characterize the mineralogy and OM of the samples and the effect of OM on smectite illitization. The XRD patterns showed changes in clay mineral parameters with increased temperature. These changes varied in both M1 and M2 and indicated a difference in the degree of smectite illitization. Moreover, the OM in M2 was mainly adsorbed in smectite interlayers, the OM was largely desorbed/decomposed at temperatures above 350°C, and the OM was the main reason for differences in the degree of smectite illitization between M1 and M2. Bulk mineral composition, elemental content, and infrared absorption band intensities were changed with increased temperature (especially above 350°C). This indicated the formation of new minerals (e.g., ankerite). Overall, OM entered the interlayer space of smectite in M2 and delayed the exchange of K+ by interlayer cations, and thus, suppressed the transformation of smectite to illite and resulted in differences in smectite illitization of M1 and M2. In particular, the formation of CO2 after the decomposition of OM at temperatures above 300°C led to the formation of ankerite in M2. This demonstrated the effect of organic-inorganic interactions on smectite illitization and mineral formation. The disparities in smectite illitization between M1 andM2, therefore, were linked to differences in the mineral formation mechanisms of a water-rock system (M1) and a water-rock-OM system (M2) in natural environments. The insights obtained in the present study should be of high importance in understanding organic-mineral interactions, hydrocarbon generation, and the carbon cycle.

Our previous studies have suggested that spastin, which aggregates on spindle microtubules in oocytes, may promote the assembly of mouse oocyte spindles by cutting microtubules. This action may be related to CRMP5, as knocking down CRMP5 results in reduced spindle microtubule density and maturation defects in oocytes. In this study, we found that, after knocking down CRMP5 in oocytes, spastin distribution shifted from the spindle to the spindle poles and errors in microtubule–kinetochore attachment appeared in oocyte spindles. However, CRMP5 did not interact with the other two microtubule-severing proteins, katanin-like-1 (KATNAL1) and fidgetin-like-1 (FIGNL1), which aggregate at the spindle poles. We speculate that, in oocytes, due to the reduction of spastin distribution on chromosomes after knocking down CRMP5, microtubule–kinetochore errors cannot be corrected through severing, resulting in meiotic division abnormalities and maturation defects in oocytes. This finding provides new insights into the regulatory mechanisms of spastin in oocytes and important opportunities for the study of meiotic division mechanisms.

Dietary antioxidant indices (DAI) may be potentially associated with relative telomere length (RTL) of leucocytes. This study aimed to investigate the relationship between DAI and RTL. A cross-sectional study involving 1656 participants was conducted. A generalised linear regression model and a restricted cubic spline model were used to assess the correlation of DAI and its components with RTL. Generalised linear regression analysis revealed that DAI (β = 0·005, P = 0·002) and the intake of its constituents vitamin C (β = 0·043, P = 0·027), vitamin E (β = 0·088, P < 0·001), Se (β = 0·075, P = 0·003), and Zn (β = 0·075, P = 0·023) were significantly and positively correlated with RTL. Sex-stratified analysis showed that DAI (β = 0·006, P = 0·005) and its constituents vitamin E (β = 0·083, P = 0·012), Se (β = 0·093, P = 0·006), and Zn (β = 0·092, P = 0·034) were significantly and positively correlated with RTL among females. Meanwhile, among males, only vitamin E intake (β = 0·089, P = 0·013) was significantly and positively associated with RTL. Restricted cubic spline analysis revealed linear positive associations between DAI and its constituents’ (vitamin E, Se and Zn) intake and RTL in the total population. Sex-stratified analysis revealed a linear positive correlation between DAI and its constituents’ (vitamin E, Se and Zn) intake and RTL in females. Our study found a significant positive correlation between DAI and RTL, with sex differences.

Underwater archaeology is of great significance for historical and cultural transmission and preservation of underwater heritage, but it is also a challenging task. Underwater heritage is located in an environment with high sediment content, objects are mostly buried, and the water is turbid, resulting in some of the features of objects missing or blurred, making it difficult to accurately identify and understand the semantics of various objects in the scene. To tackle these issues, this paper proposes a global enhancement network (GENet) underwater scene parsing method. We introduce adaptive dilated convolution by adding an extra regression layer, which can automatically deduce adaptive dilated coefficients according to the different scene objects. In addition, considering the easy confusion in the process of fuzzy feature classification, an enhancement classification network is proposed to increase the difference between various types of probabilities by reducing the loss function. We verified the validity of the proposed model by conducting numerous experiments on the Underwater Shipwreck Scenes (USS) dataset. We achieve state-of-the-art performance compared to the current state-of-the-art algorithm under three different conditions: conventional, relic semi-buried, and turbidified water quality. The experimental results show that the proposed algorithm performs best in different situations. To verify the generalizability of the proposed algorithm, we conducted comparative experiments on the current publicly available Cityscapes, ADE20K, and the underwater dataset SUIM. The experimental results show that this paper achieves good performance on the public dataset, indicating that the proposed algorithm is generalizable.

Coupling of clearance joint and harsh aerodynamic heating environment is an inevitable nonlinear factor in folding mechanism of the fin of high-speed aircrafts that remarkably modifies natural frequencies and modes of vibration from the initial design state. However, accurately predicting dynamic properties of deployable fin with full consideration of these effects is not common industry practice. A practical semi-analytical model based on Hertz contact theory and ESDU-78035 model is proposed in this study to investigate high-temperature connection stiffness of local hinged–locked mechanisms. Material property degradation and clearance variation caused by thermal expansion are comprehensively considered and quantified in this model. Vibration characteristics of the assembled deployable fin are then solved using finite element method (FEM). The real-time evolutionary process of thermal mode of the fin is discussed. And natural frequencies of fixed-value and time-varying connection stiffness are compared. The simulation results of this study demonstrate that the relative error of structure temperature between the sequential approach and fully coupled simulations is less than 6.98%. The connection stiffness (slope of the load-displacement curve) of the folding mechanism under high temperature conditions decreases by 3.52%, and the variation is mainly caused by the degradation of the elastic modulus of the material, while the clearance change due to the thermal expansion has no significant effect on the slope. The natural frequency of the deployable fin exhibits an inverse correlation with the temperature change trend, and the first three frequencies decrease by 1.67, 7.75, and 16.28 Hz compared to the initial value, respectively.

The relationship between erythrocyte membrane n-3 PUFA and breast cancer risk is controversial. We aimed to examine the associations of erythrocyte membrane n-3 PUFA with odds of breast cancer among Chinese women by using a relatively large sample size. A case–control study was conducted including 853 newly diagnosed, histologically confirmed breast cancer cases and 892 frequency-matched controls (5-year interval). Erythrocyte membrane n-3 PUFA were measured by GC. Logistic regression and restricted cubic spline were used to quantify the association between erythrocyte membrane n-3 PUFA and odds of breast cancer. Erythrocyte membrane α-linolenic acid (ALA), docosapentaenoic acid (DPA) and total n-3 PUFA were inversely and non-linearly associated with odds of breast cancer. The OR values (95 % CI), comparing the highest with the lowest quartile (Q), were 0·57 (0·43, 0·76), 0·43 (0·32, 0·58) and 0·36 (0·27, 0·49) for ALA, DPA and total n-3 PUFA, respectively. Erythrocyte membrane EPA and DHA were linearly and inversely associated with odds of breast cancer ((EPA: ORQ4 v. Q1 (95 % CI) = 0·59 (0·45, 0·79); DHA: ORQ4 v. Q1 (95 % CI) = 0·50 (0·37, 0·67)). The inverse associations were observed between ALA and odds of breast cancer in postmenopausal women, and between DHA and oestrogen receptor+ breast cancer. This study showed that erythrocyte membrane total and individual n-3 PUFA were inversely associated with odds of breast cancer. Other factors, such as menopause and hormone receptor status, may warrant further investigation when examining the association between n-3 PUFA and odds of breast cancer.