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Circular RNAs (circRNAs) play crucial roles in the immune and inflammatory responses of many diseases by acting as competing endogenous RNAs (ceRNAs). However, the role of circRNAs as ceRNAs in the immune and inflammatory processes of coronary atherosclerosis heart disease (CHD) remains unclear. This study aimed to identify and validate the potential immune-related circRNAs as biomarkers for CHD. Firstly, we constructed a ceRNA regulatory network including 14 circRNAs, 24 miRNAs, and 15 genes through bioinformatics analysis. Four hub genes were identified and five candidate immune-related circRNAs were screened. Subsequently, the expression levels of these candidate circRNAs were detected by qRT-PCR. Notably, hsa_circRNA_101069 and hsa_circRNA_406053 showed significant up-regulation in CHD patients (p < 0.001). The value of these circRNAs as biomarkers for CHD was evaluated by the area under the ROC curve (AUC), net reclassification improvement (NRI), and integrated discrimination improvement (IDI) indexes. Adding circRNAs to a traditional CHD model significantly enhanced classification performance, with an IDI of 0.058 and an NRI of 0.280 for hsa_circRNA_101069 and an IDI of 0.051 and an NRI of 0.480 for hsa_circRNA_406053. Furthermore, hsa_circRNA_101069 was up-regulated in ox-LDL-induced THP-1 macrophages, and silencing hsa_circRNA_101069 significantly inhibited the apoptosis rates and the inflammatory cytokines levels. This study constructed an immune-related circRNA-miRNA-mRNA network and identified two circRNAs as biomarkers for CHD, with hsa_circRNA_101069 potentially contributing to the pathological basis of CHD.

Background: Tanshinone IIA (Tan IIA) is a lipophilic active constituent derived from the rhizomes and roots of Salvia miltiorrhiza Bunge (Danshen), a common Chinese medicinal herb. However, clinical applications of Tan IIA are limited due to its poor solubility in water. Methods: To overcome this limitation, we developed a calcium alginate hydrogel (CA) as a hydrophilic carrier for Tan IIA, which significantly improved its solubility. We also prepared nanoparticles with pH-responsive properties to explore their potential for controlled drug delivery. The physicochemical properties of Tan IIA/CA nanoparticles were evaluated, including their size, stability, and release profile. We also utilized RNA sequencing to further investigate the underlying anticancer mechanisms of Tan IIA/CA nanoparticles. Results: The Tan IIA/CA nanoparticles demonstrated enhanced solubility and exhibited potent anticancer activity in vitro. Additionally, the nanoparticles showed promising pH-responsive behavior, which is beneficial for controlled release applications. Further investigation into the molecular mechanisms revealed that the anticancer effects of Tan IIA/CA were mediated through apoptosis, ferroptosis, and autophagy pathways. Conclusions: This study confirms the anticancer potential and mechanisms of Tan IIA, while also presenting an innovative approach to enhance the solubility of this poorly soluble compound. The use of CA-based nanoparticles could be a valuable strategy for improving the therapeutic efficacy of Tan IIA in cancer treatment.

In response to the structural changes of tomato seedlings, traditional image techniques are difficult to accurately quantify key morphological parameters, such as leaf area, internode length, and mutual occlusion between organs. Therefore, this paper proposes a tomato point cloud stem and leaf segmentation framework based on Elite Strategy-based Improved Red-billed Blue Magpie Optimization (ES-RBMO) Algorithm. The framework uses a four-layer Convolutional Neural Network (CNN) for stem and leaf segmentation by incorporating an improved swarm intelligence algorithm with an accuracy of 0.965. Four key phenotypic parameters of the plant were extracted. The phenotypic parameters of plant height, stem thickness, leaf area and leaf inclination were analyzed by comparing the values extracted by manual measurements with the values extracted by the 3D point cloud technique. The results showed that the coefficients of determination (R2) for these parameters were 0.932, 0.741, 0.938 and 0.935, respectively, indicating high correlation. The root mean square error (RMSE) was 0.511, 0.135, 0.989 and 3.628, reflecting the level of error between the measured and extracted values. The absolute percentage errors (APE) were 1.970, 4.299, 4.365 and 5.531, which further quantified the measurement accuracy. In this study, an efficient and adaptive intelligent optimization framework was constructed, which is capable of optimizing data processing strategies to achieve efficient and accurate processing of tomato point cloud data. This study provides a new technical tool for plant phenotyping and helps to improve the intelligent management in agricultural production.

Rice blast disease, caused by Magnaporthe oryzae (M. oryzae), is a significant threat to global rice production. Conventional methods for disease management face limitations, emphasizing the importance of sustainable alternatives. In this study, two rice cultivars with different blast resistant abilities, the susceptible variety CO39 and the resistant variety Pi4b, were used as materials to study the effects of Piriformospora indica (Pi) on the resistance to M. oryzae infection and rice growth. The in vitro tests revealed no direct antagonistic interaction between Pi and M. oryzae. However, the in vivo experiments showed that Pi promoted plant growth by increasing root and shoot length, chlorophyll content, and nitrogen uptake, particularly in CO39 during pathogen infection. Pi inoculation also significantly reduced disease severity, which was indicated by smaller lesion areas and shorter lesion lengths in both cultivars but a more pronounced effect in CO39. This occurred due to the decreasing levels of MDA and the modulating activity of antioxidant enzymes in Pi-inoculated rice plants. At the early stage of M. oryzae infection, the expression of the ethylene signaling gene OsEIN2 and the gibberellin biosynthesis gene OsGA20ox1 in Pi-inoculated CO39 decreased but significantly increased in both rice cultivars at the later stage. The reverse was found for the pathogenesis-related (PR) genes OsPR10 and OsPBZ1 and the blast-resistant genes OsBRG1, OsBRG2, and OsBRW1, suggesting early growth suppression for rice resilience to blast followed by a later shift back to growth. Meanwhile, Pi inoculation increased OsCesA9 expression in rice to strengthen cell walls and establish the primary defense barrier against M. oryzae and upregulated the expression of OsNPR1 without a significant difference in CO39 but downregulated it in Pi4b to activate PR genes to enhance plant resistance. In summary, these results underscore the potential of Pi as a sustainable biological control agent for rice blast disease, which is particularly beneficial for blast-susceptible rice cultivars.

In the domain of animal management, the technology for individual livestock identification is in a state of continuous evolution, encompassing objectives such as precise tracking of animal activities, optimization of vaccination procedures, effective disease control, accurate recording of individual growth, and prevention of theft and fraud. These advancements are pivotal to the efficient and sustainable development of the livestock industry. Recently, visual livestock biometrics have emerged as a highly promising research focus due to their non-invasive nature. This paper aims to comprehensively survey the techniques for individual livestock identification based on computer vision methods. It begins by elucidating the uniqueness of the primary biometric features of livestock, such as facial features, and their critical role in the recognition process. This review systematically overviews the data collection environments and devices used in related research, providing an analysis of the impact of different scenarios on recognition accuracy. Then, the review delves into the analysis and explication of livestock identification methods, based on extant research outcomes, with a focus on the application and trends of advanced technologies such as deep learning. We also highlight the challenges faced in this field, such as data quality and algorithmic efficiency, and introduce the baseline models and innovative solutions developed to address these issues. Finally, potential future research directions are explored, including the investigation of multimodal data fusion techniques, the construction and evaluation of large-scale benchmark datasets, and the application of multi-target tracking and identification technologies in livestock scenarios.

Aiming at the large-scale nonlinear deformation of the roadway in Liangjia Coal Mine, Shandong Province, the mudstone of the 1602 working face is taken as the research object. A high-precision mudstone weathering test system integrating monitoring and control was developed, and the weathering tests of expanded mudstone were carried out at 10 °C, 20 °C, 30 °C and 40 °C. The results show that the hygroscopic curves of expanded mudstone demonstrate a nonlinear growth trend at different temperatures, and the influence of temperature on the hygroscopic curves is less than 20%. From the overall law, it can be roughly divided into three stages: the strong hygroscopic stage, the hygroscopic deceleration stage and the stable hygroscopic stage. The maximum expansion rates of the samples were 4.1%, 5.3%, 6.2% and 6.8%, respectively, and the water content and expansion rates corresponding to different ambient temperature and humidity were generally “concave”. The mechanical tests show that the mechanical properties of mudstone decrease as the ambient temperature increases, and the corresponding compressive strength decreases by 16~50%. The linear degradation is obvious, and the gradual expansion of peak strain indicates that the plasticity of the rock increases and the elastic modulus decreases linearly.

State estimation of batteries is crucial in battery management systems (BMSs), particularly for accurately predicting the state of charge (SOC), which ensures safe and efficient battery operation. This paper proposes a joint SOC estimation method based on a fractional-order model, utilizing a multi-innovation full-tracking adaptive unscented Kalman filter (FOMIST-AUKF-EKF) combined with an extended Kalman filter (EKF) for online parameter updates. The fractional-order model more effectively represents the battery’s dynamic characteristics compared to traditional integer-order models, providing a more precise depiction of electrochemical processes and nonlinear behaviors. It offers superior modeling for long-memory effects, complex dynamics, and aging processes, enhancing adaptability to aging and nonlinear characteristics. Comparative results indicate a maximum end-voltage error reduction of 0.002 V with the fractional-order model compared to the integer-order model. The multi-innovation technology increases filter robustness against noise by incorporating multiple historical observations, while the full-tracking adaptive strategy dynamically adjusts the noise covariance matrix based on real-time data, thus enhancing estimation accuracy. Furthermore, EKF updates battery parameters (e.g., resistance and capacitance) in real time, correcting model errors and improving SOC prediction accuracy. Simulation and experimental validation show that the proposed method significantly outperforms traditional UKF-based SOC estimation techniques in accuracy, stability, and adaptability. Specifically, under varying conditions such as NEDC and DST, the method demonstrates excellent robustness and practicality, with maximum SOC estimation errors of 0.27% and 0.67%, respectively.

This study employed a template method to prepare a highly ordered and interconnected porous HOM-m MgFe2O4/MgO rare earth ion-efficient adsorbent. The specific surface area of the adsorbent was as high as 130 m2/g, with saturation adsorption capacities for Ce(Ⅲ) and La(Ⅲ) of 5689.69 mg/g and 2123.50 mg/g, respectively. The adsorbent exhibited superparamagnetism with efficient and rapid separation from an aqueous solution using a magnet. The adsorption results indicated that the adsorption mechanism of HOM-m MgFe2O4/MgO towards Ce(III) and La(III) primarily involved the ion exchange and redox reactions between Mg(II) hydrolyzed from MgO and Ce(III)/La(Ⅲ), as well as the electrostatic attraction between MgFe2O4 and Ce(Ⅲ)/La(Ⅲ). Density functional theory (DFT) calculations revealed that the adsorption process was driven by the interaction of Ce(III) and La(III) ions with the surface oxygen atoms of MgFe2O4/MgO. Moreover, MgFe2O4/MgO showed a higher affinity and stronger adsorption effect towards Ce(III) than La(III). Adsorption cycling experiments demonstrated that even after three cycles, HOM-m MgFe2O4/MgO maintained good removal efficiency for Ce(III) and La(III). Therefore, this adsorbent shows promise as an effective material for removing Ce(III) and La(III) and has significant implications for the remediation of water resources in ion adsorption-type rare earth mining areas.

Electronic and electrical products have deeply permeated all aspects of life, bringing a lot of convenience to individuals. However, the generation of e-waste after their end-of-life has resulted in serious risks both to the ecological environment and human health due to a lack of scientific and effective recycling and treatments. As two major types of components in e-waste, heavy metals and plastics can not only directly enter the human body via inhalation, ingestion, and skin absorption, but also accumulate in the human body indirectly through the food chain. E-waste is full of resources such as valuable metals like gold, silver, and copper that are often discarded incorrectly. Environmental and health risks derived from unregulated e-waste dismantling activities may be finally addressed through the application of advanced e-waste recycling technology, policy support of governments, legislation on recycling laws and regulations, and the improvement of public environmental protection awareness. This review gives a brief overview of the history, current situation, and future development of e-waste in China, which may provide novel thinking and approaches to e-waste management in the world.

For industrial tail gas to be converted into high-purity hydrogen, the H2-N2 mixture needs to be separated efficiently. This work examined the adsorption characteristics and competitive mechanisms of H2 and N2 on LTA- and FAU-type zeolites, at 77 K, 298 K, and 0.1–10 bar by thoroughly analyzing results of adsorption capacity experiments and molecular simulations. In the Grand Canonical Monte Carlo (GCMC) simulations, the force field causing a molecular dipole of H2 and the polarization force field of N2 are first applied. The accuracy of the force field was experimentally verified. The findings indicate that N2 and H2 loading on Ca-FAU (Ca-LTA) are higher than Na-FAU (Na-LTA). On NaX at 77 K, the highest adsorption selectivity (N2/H2) is observed; on NaA at 298 K, it is the opposite. The GCMC data findings demonstrate that H2 and N2 have remarkably similar adsorption sites, with framework oxygen atoms and non-framework cations serving as the main adsorption sites for adsorbate molecules. Furthermore, the rate at which H2 diffuses is higher than that of N2. The study of redistribution charge before and after adsorption demonstrated that N2 has a greater affinity for the framework oxygen atoms than H2. This study provides a molecular theoretical foundation for the adsorption behavior of H2-N2 mixture in zeolites.

The arid and semi-arid region of Northwest China plays a significant role in potato production, yet yields are often hampered by drought due to limited precipitation and irrigation water. The ridge–furrow rainwater-harvesting technology is an efficient and widely used technique to relieve drought impact and improve crop yield by changing the micro-topography to harvest rainwater to meet the water demand of crops. An analysis of precipitation, water demand, and runoff data spanning 30 years guided the selection of suitable rainwater-harvesting methods tailored to meteorological conditions. The results showed that potato water demand exceeded precipitation in the region. The mulching approach performed best in the western arid region with the most significant increase in yield and water use efficiency (WUE) and was suitable for the western semi-arid region and the agro-pastoral ecotone. In the potato dryland farming areas, the water deficit increased from southeast to northwest. Specifically, northern Gansu, northern Ningxia, and midwestern Inner Mongolia experienced a water deficit of over 200 mm, and rainwater harvesting combined with irrigation was recommended. Conversely, regarding deficits below 200 mm in southern Gansu, Ningxia, and central Inner Mongolia, a 1:1 or 2:1 pattern of ridges could be applied, and mulching was needed only in the necessary areas. For the southern Qinghai, Shaanxi, and eastern Inner Mongolia regions, ridge–furrow rainwater harvesting could be replaced by flat potato cropping. In summary, rainwater harvesting addresses water deficits, aiding climate adaptation in Northwest China’s arid and semi-arid regions. The implementation of mulching and ridge–furrow technology must be location-specific.

Grain size is one of the critical factors determining rice yield. Previous studies have found the grain-size-regulating function of Gα in rice. However, the regulatory mechanism underlying the development of rice grain mediated by Gα is still unclear. To reveal the functional mechanism of Gα in grain size regulation, a mutant of Gα (Gα-Cas9) was firstly constructed through a CRISPR/Cas9 strategy and was then grown in a greenhouse and field. The results showed that the seed length, plant height, 1000-grain weight, and spike length were significantly decreased in Gα-Cas9 compared to wild-type (WT) Pi-4b. During the grain filling stage, the increase in the grain dry weight of Pi-4b occurred earlier than that of Gα-Cas9. The total starch content and amylose content of matured grains of Pi-4b were higher than those of Gα-Cas9. Secondly, transcriptome sequencing analysis of Gα-Cas9 and Pi-4b during grain filling was performed to elucidate the functional pathways regulated by Gα. In total, 2867 and 4534 differentially expressed genes (DEGs) were discovered at 5 DAF and 10 DAF, and the starch and sucrose metabolism pathway enriched by DEGs was involved in grain size regulation mediated by Gα. Gα regulated the expression of starch-synthesis-related genes during grain filling, and the Gα protein interacted with OsNYC4 to trigger the sugar signaling pathway to promote starch accumulation in grain. Additionally, the GW2-WG1-OsbZIP47 pathway was switched off by Gα to relieve the inhibition of rice grain development. In this study, the results should provide new insights into the G protein signal transduction pathway.

Strawberry red core root rot disease affects the growth and yield of strawberry (Fragaria ananassa Duch), which leads to economic losses in China. The study employed a tissue separation method to isolate and identify the causal agent responsible for strawberry red core root rot. This was achieved by the observation of its morphological characteristics, sequencing analyses, and pathogenicity tests. The sensitivity of five chemical fungicides against the two species of Fusarium was determined using the mycelial growth rate method, and the biological characteristics of the two species were examined. The pathogens were identified as Fusarium solani and Fusarium oxysporum. The optimal conditions for the mycelial growth of F. solani and F. oxysporum were determined to be potato sucrose agar at 25 °C and pH 6, and potato dextrose agar at 30 °C and pH 8, respectively, with a 24:24 light cycle. The most suitable carbon and nitrogen sources for the mycelial growth of F. solani were sucrose and sodium nitrate (NaNO3), while for F. oxysporum, they were glucose and peptone. A fungicide sensitivity test indicated that Prochloraz had a good inhibitory effect on the growth of F. solani and F. oxysporum with EC50 values of 0.088 mg L−1 and 0.162 mg. The growth inhibition effect of Azoxystrobin to F. solani and Carbendazim to F. oxysporum was not obvious. This study provides a theoretical basis for further research on strawberry red core root disease and its prevention.

In present-day Japan, high quality is the first requirement of rice production. To maintain the quality of rice, the prejudgment technique has been proposed to control rice growth or to separately harvest rice depending on its quality. Since the quality of rice is generally indexed by grain protein content, which is strongly affected by nitrogen content of leaves, one of the major prejudgment techniques is based on leaf greenness evaluation (i.e., SPAD value). However, the technique is under research and not popular with the farmers because the reliability of prejudgment is inadequate. In this study, we investigated the leaf SPAD value at different growth stages of different cultivars and with cultivation methods in farmer fields over four years, and we validated the applicability of prejudgment by comparing with the grain protein content. The results showed that the grain protein content was positively correlated with leaf SPAD value at the maturity stage, but correlated weakly with those at the booting, heading, and milking stages. Since the regression coefficients significantly differed depending on the year, cultivar, and planting method, the acquisition of a regression equation for each target is recommended to predict grain protein content more accurately. The validation in this study suggests that the prejudgment of grain protein content just before harvest has generality for several targets and is useful for harvesting rice depending on the quality. The results in this study may contribute to the attempts to evaluate SPAD value and then rice quality by remote sensing.

More efficient resource utilization and increased crop utilization rate are needed to address the growing demand for food. The efficient quality testing of key agricultural products such as potatoes, especially the rapid testing of key nutritional indicators, has become an important strategy for ensuring their quality and safety. In this study, visible and near infrared (Vis/NIR) transmittance spectroscopy (600–900 nm) was used for the online analysis of multiple quality parameters in potatoes. The study concentrated on comparing three one-dimensional convolutional neural network (1D-CNN) models, specifically, the fine-tuned DeepSpectra, the fine-tuned 1D-AlexNet, and classic CNN, with UVE-PLS (uninformative variable elimination–partial least squares) models. These models utilized spectral data for the real-time detection of dry matter (DM) content in potatoes. To address the challenges posed by limited data from Vis/NIR, this study strategically implemented data augmentation techniques. This approach significantly enhanced the robustness and generalization capabilities of the models. The 1D-AlexNet and DeepSpectra models achieved 0.934 and 0.913 R2P and 0.0603 and 0.0695 g/100 g RMSEP for DM, respectively. Compared to UVE-PLS, the R2P value improved by 21.31% (0.770 to 0.934) for the 1D-AlexNet model and 18.64% (0.770 to 0.913) for the DeepSpectra model. The RMSEP value was reduced by 47.31% (0.114 to 0.0603) for 1D-AlexNet, and 39.30% (0.114 to 0.0695) for the DeepSpectra model. As a result, this study would be helpful for researching the online Vis/NIR transmission determination of potato DM using deep learning. These results highlighted the immense potential of employing specific spectral features in deep-learning models for a more precise and efficient online assessment of agricultural quality. This advancement provided some insight and reference for further contributing to the evolution of more targeted and efficient quality assessment methods in agricultural products.

Hydrofluorocarbons (HFCs) have important applications in different industries; however, they are environmentally unfriendly due to their high global warming potential (GWP). Hence, reclamation of used hydrofluorocarbons via energy-efficient adsorption-based separation will greatly contribute to reducing their impact on the environment. In particular, the separation of azeotropic refrigerants remains challenging, such as typical mixtures of CH2F2 (HFC-23) and CHF3 (HFC-32), due to a lack of adsorptive mechanisms. Metal–organic frameworks (MOFs) can provide a promising solution for the separation of CHF3–CH2F2 mixtures. In this study, the adsorption mechanism of CHF3–CH2F2 mixtures in TIFSIX-2-Cu-i was revealed at the microscopic level by combining static pure-component adsorption experiments, molecular simulations, and density-functional theory (DFT) calculations. The adsorption separation selectivity of CH2F2/CHF3 in TIFSIX-2-Cu-i is 3.17 at 3 bar under 308 K. The existence of similar TiF62− binding sites for CH2F2 or CHF3 was revealed in TIFSIX-2-Cu-i. Interactions between the fluorine atom of the framework and the hydrogen atom of the guest molecule were found to be responsible for determining the high adsorption separation selectivity of CH2F2/CHF3. This exploration is important for the design of highly selective adsorbents for the separation of azeotropic refrigerants.

Bacterial symbionts associated with insects can be crucial in insect nutrition, metabolism, immune responses, development, and reproduction. However, the bacterial symbionts of the fall armyworm Spodoptera frugiperda remain unclear. S. frugiperda is an invasive polyphagous pest that severely damages many crops, particularly maize and wheat. Here, we investigated the infection, composition, abundance, and diversity of bacterial symbionts, especially Wolbachia, in different tissues of S. frugiperda female adults. The infection prevalence frequencies of Wolbachia in five provinces of China, namely Pu’er, Yunnan; Nanning, Guangxi; Sanya, Hainan; Yunfu, Guangdong; and Nanping, Fujian, were assessed. The results indicated that Proteobacteria, Firmicutes, and Bacteroidetes were the three most dominant bacterial phyla in S. frugiperda adults. At the genus level, the abundant microbiota, which included Enterobacter and Enterococcus, varied in abundance between tissues of S. frugiperda. Wolbachia was found in the ovaries and salivary glands of S. frugiperda adults, and was present in 33.33% of the Pu’er, Yunnan, 23.33% of the Nanning, Guangxi, and 13.33% of the Sanya, Hainan populations, but Wolbachia was absent in the Yunfu, Guangdong and Nanping, Fujian populations. Further phylogenetic analyses revealed that all of the Wolbachia strains from the different S. frugiperda populations belonged to the supergroup B and were named the wFru strain. Since there were Wolbachia strains inducing cytoplasmic incompatibility in supergroup B, these findings may provide a foundation for developing potential biocontrol techniques against S. frugiperda.

Banana (Musa acuminate) has been popular among consumers worldwide due to its rich nutrients and minerals. However, bananas are highly susceptible to the physical and biological factors that lead to postharvest loss during transportation and storage. In this work, novel sodium alginate (SA) films incorporated with silver nitroprusside nanoparticles (AgNNPs) were prepared to extend the shelf life of bananas through antibacterial and antioxidant coating. The results exhibited that AgNNPs were cubical and that their size was L. monocytogenes, S. enterica, and E. coli at the concentration of 500 µg/mL. Moreover, during the storage of bananas, SA-AgNNPs nanocomposite coatings act as a barrier to microbial contamination and slow down the ripening of bananas. As a result, compared with SA-coated and uncoated bananas, SA-AgNNPs-coated bananas exhibited the lowest weight loss and lowest total bacterial colonies, thus greatly extending their shelf life. Particularly when coated with SA-AgNNPs films, total bacterial colonies (TBC) in the banana peel and pulp were as low as 1.13 × 103 and 51 CUF/g on the ninth day of storage, respectively. Our work offers an efficient strategy to improve the quality of bananas during the postharvest period, with extensive applications in fruit preservation and food packing.

Bacterial infections can lead to the formation of chronic wounds and delay the wound-healing process. Therefore, it is important to explore safe and efficient antimicrobial agents that have wound-healing and biocompatible properties. In this study, novel starch-fabricated silver nitroprusside nanoparticles (S-AgNP NPs) were prepared for biocompatible wound-healing applications. The study showed that S-AgNP NPs are spherical, with an average size of 356 ± 22.28 d. nm and zeta potential of −27.8 ± 2.80 mV, respectively. Furthermore, the FTIR and XRD results showed that S-AgNP NPs have functional groups and crystal structures from the silver nitroprusside nanoparticles (AgNP NPs) and starch. Additionally, S-AgNP NPs showed excellent bacterial and biofilm inhibition on B. cereus (15.6 μg/mL), L. monocytogenes (15.6 μg/mL), S. aureus (31.3 μg/mL), E. coli (31.3 μg/mL) and S. enterica (62.5 μg/mL). Moreover, S-AgNP NPs promoted cell migration and proliferation at a concentration of 62.5 μg/mL compared to AgNP NPs. Meanwhile, S-AgNP NPs had good biocompatibility and low cytotoxicity compared to AgNP NPs. Therefore, this study provided new ideas for the development of wound-healing agents with bacteriostatic properties in chronic wounds.

Agricultural land protection is vital for the realization of national food security and an ecological civilization. From the perspective of agricultural ecological value and landscape value, perfecting the theory of agricultural land rent is beneficial to the construction of an ecological civilization. Based on Marx’s land rent theory of agricultural production, the analytical framework of the agricultural decision support systems (DSS) was constructed; then, the agricultural land rent in suburbs was theoretically accounted for via a numerical example, and its realization rules were simulated according to the conditions of China (i.e., the specific solutions in force). Some interesting conclusions were found: (1) Agricultural production in suburbs involves both natural reproduction and social reproduction. (2) Agricultural land rent should include production land rent, ecological land rent, and landscape land rent. (3) The promotion of an ecological civilization and the development of the economy and society will lead to an increase in the comprehensive coefficient of agricultural land rent. (4) With the development of the economy, ecological land rent and landscape land rent should be gradually charged from zero payment to full payment. Based on these conclusions, five corresponding policy implications are proposed to improve the land profit of agricultural land owners to promote agricultural production, food security, and an ecological civilization.

The flattening behavior of in-flight particles during plasma spraying is a highly intricate process affected by numerous factors. Therefore, in this work, in-flight particles (spherical NiCrBSi powder) were collected with the water quenching process, and the morphology and composition differences between the original powder particles and the melted in-flight particles were observed using scanning electron microscopy (SEM). The particle size in various states was recorded and calculated. The internal structure of the particles was analyzed to elucidate their morphology and compositions under different flow rates of primary gas (FRPG). A coating with 1.25% porosity and a hardness of 767 HV0.5 was achieved at the FRPG of 80 L/min. X-ray diffraction (XRD) and transmission electron microscopy (TEM) were used to characterize the microstructures of the obtained coatings. It was found that the as-sprayed coating had a certain amount of the amorphous phase. A noteworthy correlation was also established, wherein a decreased distance from the substrate, augmented spraying passes, and reduced amorphous phase content were interrelated. Concurrently, a noticeable influence of the tamping effect exerted by the in-flight particles on the coating was observed.

Milk contains all nutrients needed for development of calves. One important group of components responsible for this are the milk proteins. Variation due to feed or animal health, has been studied for the most abundant milk proteins. The aim of this study was to determine the variation between and within cows for their milk serum proteome. Sample Set 1 was collected from Holstein Friesian (HF) cows between November 2011 and March 2012 and prepared using filter aided sample preparation (FASP) followed by LC-MS/MS for protein identification and quantification. The results showed that the milk serum proteome was very constant in mid lactation (four cows at five time points, p > 0.05) between 3 and 6 months in lactation. Sample Set 2 was collected from HF cows in Dec 2012 and analyzed using FASP and dimethyl labeling followed by LC-MS/MS. Significant variation in the milk serum proteome (p < 0.05) between 17 individual cows was found in Sample Set 2. The most variable proteins were immune-related proteins, which may reflect the health status of the individual cow. On the other hand, proteins related to nutrient synthesis and transport were relatively constant, indicating the importance of milk in providing a stable supply of nutrients to the neonate. In conclusion, the milk serum proteome was stable over mid lactation, but differed significantly between individuals, especially in immune-related proteins.

Sepsis-associated encephalopathy (SAE) is a common brain dysfunction, which results in severe cognitive and neurological sequelae and an increased mortality rate in patients with sepsis. Depending on the stimulus, microglia (resident macrophages in the brain that are involved in SAE pathology and physiology) can adopt two polarization states (M1/M2), corresponding to altered microglial morphology, gene expression, and function. We systematically described the pathogenesis, morphology, function, and phenotype of microglial activation in SAE and demonstrated that microglia are closely related to SAE occurrence and development, and concomitant cognitive impairment. Finally, some potential therapeutic approaches that can prime microglia and neuroinflammation toward the beneficial restorative microglial phenotype in SAE were outlined.

The large-scale and precise intelligent breeding mode for dairy cows is the main direction for the development of the dairy industry. Machine vision has become an important technological means for the intelligent breeding of dairy cows due to its non-invasive, low-cost, and multi-behavior recognition capabilities. This review summarizes the recent application of machine vision technology, machine learning, and deep learning in the main behavior recognition of dairy cows. The authors summarized identity recognition technology based on facial features, muzzle prints, and body features of dairy cows; motion behavior recognition technology such as lying, standing, walking, drinking, eating, rumination, estrus; and the recognition of common diseases such as lameness and mastitis. Based on current research results, machine vision technology will become one of the important technological means for the intelligent breeding of dairy cows. Finally, the author also summarized the advantages of this technology in intelligent dairy farming, as well as the problems and challenges faced in the next development.

The reasonable scheduling of agricultural machinery can avoid their purposeless flow during the operational service and reduce the scheduling cost of agricultural machinery service centers. In this research, a multiregional agricultural machinery scheduling model with a time window was established considering the timeliness of agricultural machinery operation. This model was divided into two stages: In the first stage, regions were divided through the Voronoi diagram, and farmlands were distributed to intraregional service centers. In the second stage, the model was solved using the hybrid particle swarm optimization (HPSO). The algorithm improves the performance of the algorithm by introducing a crossover, mutation, and particle elimination mechanism, and by using a linear differential to reduce the inertia weight and trigonometric function learning factor. Next, the accuracy and effectiveness of the algorithm are verified by different experimental samples. The results show that the algorithm can effectively reduce the scheduling cost, and has the advantages of strong global optimization ability, high stability, and fast convergence speed. Subsequent algorithm comparison proves that HPSO has better performance in different situations, can effectively solve the scheduling problem, and provides a reasonable scheduling scheme for multiarea and multifarmland operations.

Graphene oxide aerogel (GOA) has wide application prospects due to its low density and high porosity. However, the poor mechanical properties and unstable structure of GOA have limited its practical applications. In this study, polyethyleneimide (PEI) was used to graft onto the surface of GO and carbon nanotubes (CNTs) to improve compatibility with polymers. Composite GOA was prepared by adding styrene-butadiene latex (SBL) to the modified GO and CNTs. The synergistic effect of PEI and SBL, resulted in an aerogel with excellent mechanical properties, compressive resistance, and structural stability. When the ratio of SBL to GO and GO to CNTs was 2:1 and 7:3, respectively, the obtained aerogel performance was the best, and the maximum compressive stress was 784.35% higher than that of GOA. The graft of PEI on the surface of GO and CNT could improve the mechanical properties of the aerogel, with greater improvements observed with grafting onto the surface of GO. Compared with GO/CNT/SBL aerogel without PEI grafting, the maximum stress of GO/CNT–PEI/SBL aerogel increased by 5.57%, that of GO–PEI/CNT/SBL aerogel increased by 20.25%, and that of GO–PEI/CNT–PEI/SBL aerogel increased by 28.99%. This work not only provided a possibility for the practical application of aerogel, but also steered the research of GOA in a new direction.

Heavy metal-associated proteins (HMPs) participate in heavy metal detoxification. Although HMPs have been identified in several plants, no studies to date have identified the HMPs in Brassica rapa (B. rapa). Here, we identified 85 potential HMPs in B. rapa by bioinformatic methods. The promoters of the identified genes contain many elements associated with stress responses, including response to abscisic acid, low-temperature, and methyl jasmonate. The expression levels of BrHMP14, BrHMP16, BrHMP32, BrHMP41, and BrHMP42 were upregulated under Cu2+, Cd2+, Zn2+, and Pb2+ stresses. BrHMP06, BrHMP30, and BrHMP41 were also significantly upregulated after drought treatment. The transcripts of BrHMP06 and BrHMP11 increased mostly under cold stress. After applying salt stress, the expression of BrHMP02, BrHMP16, and BrHMP78 was induced. We observed increased BrHMP36 expression during the self-incompatibility (SI) response and decreased expression in the compatible pollination (CP) response during pollen–stigma interactions. These changes in expression suggest functions for these genes in HMPs include participating in heavy metal transport, detoxification, and response to abiotic stresses, with the potential for functions in sexual reproduction. We found potential co-functional partners of these key players by protein–protein interaction (PPI) analysis and found that some of the predicted protein partners are known to be involved in corresponding stress responses. Finally, phosphorylation investigation revealed many phosphorylation sites in BrHMPs, suggesting post-translational modification may occur during the BrHMP-mediated stress response. This comprehensive analysis provides important clues for the study of the molecular mechanisms of BrHMP genes in B. rapa, especially for abiotic stress and pollen–stigma interactions.

Docosahexaenoic acid (DHA) is highly enriched in the brain, and is essential for normal brain development and function. However, evidence suggests that currently used supplements, such as fish oil, do not significantly increase brain DHA levels. Therefore, this study aimed to investigate whether combined fish oil and choline supplementation could affect the type and enrich the content of DHA in the brain. The results revealed that the combined intake of fish oil and choline upregulated the expression of key transporters and receptors, including MFSD2A, FATP1, and FABP5, which increased the uptake of DHA in the brain. Additionally, this supplementation improved the synthesis and release of acetylcholine in the brain, which, in turn, enhanced the learning and memory abilities of mice. These findings suggest that the combined intake of fish oil and choline improves the bioavailability of DHA in the brain.

The direct correction method is widely used for eliminating geometric constraint violations. This method involves iteratively adjusting the generalized coordinates, which are assumed to be consistent and remain so during the velocity-level corrections. However, the corrected generalized coordinates cause a significant effect on the velocity constraint violations. In this paper, simultaneously correcting both the generalized coordinates and velocities is proposed. A semi-analytic approach to solve the Jacobian matrix, which is used to correct the generalized coordinates and velocities, was employed. Further, the position level, velocity level, and energy constraint equations were corrected simultaneously to ensure that the corrected generalized coordinates and velocities complied with the dynamic equations. The corresponding semi-analytic Jacobian matrix was derived to solve the constraint equations. The methods were demonstrated to be effective using examples, with the simultaneous correction of position-level and velocity-level constraints showing the best results when combined with the energy correction.

In this paper, an on chip two-dimensional Newton’s ring-like plasmonic sensor is designed for differentiating the chirality of circularly polarized lights (CPLS). The structure of the plasmonic sensor consists of a circular arc slit and an array of periodic rectangular nano-grooves that are etched into a silver film. When the sensor is illuminated by CPLS with a given chirality, the surface plasmon polariton waves generated by the slit and nano-groove array will selectively interfere with each other in the near field, which results in two different transmitted light intensity distributions in the far field. The generated far-field light intensity distributions are utilized as criteria to qualitatively differentiate the concrete chirality of the incident CPLS. The finite difference time domain method is utilized to theoretically investigate the function of the designed plasmonic sensor. The simulated results indicated that the proposed sensor has the ability to visually display the chirality information in the far field, and can provide a tool to conveniently and qualitatively differentiate the chirality of CPLS in the far field.

The influence of large rivers on the Subei littoral plain area requires more research than the results that have been available up to now. Thus, specific diagnostic indices of detrital mica are successfully applied for the first time to identify the detritus of the Yangtze River and the ancient Yellow River and to analyze their influence on the coast in the Subei littoral plain area. Based on field investigation and sample collection, detrital mica minerals within the 0.063–0.125 mm grain size fraction were selected and identified. Their content/ratio differentiations and possible origins were analyzed. Moreover, specific diagnostic indices were evaluated for detritus identification considering these two large rivers in addition to their provenance influences on the Subei littoral plain area. The results indicate that the detrital mica contents in the Yangtze River Estuary differed from those in the ancient Yellow River Estuary. The mass percentage in the former (average value of 32.2%) was much higher than that in the latter (average value of 13.1%). The former contained abundant weathered mica, with a particle percentage of approximately 50.6%, while the latter contained abundant biotite (with a particle percentage of approximately 40.9%). Differences, including but not limited to those above, could be attributed to basic geological, climatic and hydrodynamic conditions. In particular, the mica indices were clearly distinguished between these two river estuaries. These indices constitute specific diagnostic indices for differentiating river detritus and quantitative contribution analysis of detritus provenance in the Subei littoral plain area. Finally, the changes and quantitative contributions of four diagnostic indices demonstrated that in the Subei littoral plain area, northward from the Yangtze River Estuary to sample site SBY11 located in Yangkou town, Rudong County, detrital micas were mainly affected by the Yangtze River, and southward from the ancient Yellow River Estuary to sample site SBY12 located in Bengcha town, Rudong County, detrital micas were largely affected by the ancient Yellow River. The main mixing area should be located between these two towns. This study provides both a good example and an efficient approach to the application of detrital mica in detritus identification, mixed zone determination, sediment provenance analysis and transport tracing.

By denaturing proteins and promoting the formation of multiprotein complexes, protein phosphorylation has important effects on the activity of protein functional molecules and cell signaling. The regulation of protein phosphorylation allows microbes to respond rapidly and reversibly to specific environmental stimuli or niches, which is closely related to the molecular mechanisms of bacterial drug resistance. Accurate prediction of phosphorylation sites (p-site) of prokaryotes can contribute to addressing bacterial resistance and providing new perspectives for developing novel antibacterial drugs. Most existing studies focus on human phosphorylation sites, while tools targeting phosphorylation site identification of prokaryotic proteins are still relatively scarce. This study designs a capsule network-based prediction technique for p-site in prokaryotes. To address the poor scalability and unreliability of dynamic routing processes in the output space of capsule networks, a more reliable way is introduced to learn the consistency between capsules. We incorporate a self-attention mechanism into the routing algorithm to capture the global information of the capsule, reducing the computational effort while enriching the representation capability of the capsule. Aiming at the weak robustness of the model, EcapsP improves the prediction accuracy and stability by introducing shortcuts and unconditional reconfiguration. In addition, the study compares and analyzes the prediction performance based on word vectors, physicochemical properties, and mixing characteristics in predicting serine (Ser/S), threonine (Thr/T), and tyrosine (Tyr/Y) p-site. The comprehensive experimental results show that the accuracy of the developed technique is close to 70% for the identification of the three phosphorylation sites in prokaryotes. Importantly, in side-by-side comparisons with other state-of-the-art predictors, our method improves the Matthews correlation coefficient (MCC) by approximately 7%. The results demonstrate the superiority of EcapsP in terms of high performance and reliability.

ß-poly (L-malic acid) (PMLA) is a polyester ligated by malate subunits. It has a wide prospective application as an anti-cancer drug carrier, and its malate subunits have a great application in the food industry. The strain Aureoabsidium melanogenum could produce a high amount of PMLA during fermentation, and different substrates addition could influence the production. In this study, we directly added potassium acetate, corn steep liquor, MgSO4, MnSO4, vitamin B1, vitamin B2, and nicotinamide as the fermentation substrate to the basic fermentation medium based on a generated random matrix that represented the added value. The PMLA production and four secondary indexes, pH, biomass, osmotic pressure, and viscosity were measured after 144 h fermentation. Finally, a total of 212 samples were collected as the dataset, by which the machine learning methods were deployed to predict the PMLA production by different substrates’ concentrations and the secondary indexes. The results indicated that PMLA production was negatively correlated with corn steep liquor and betaine and positively correlated with potassium acetate. The PMLA production could be predicted using all different substrates’ concentrations with a Mean Absolute Error (MAE) of 4.164 g/L and with an MAE of 6.556 g/L by different secondary indexes. Finally, the convolutional neural network (CNN) was applied to predict the PMLA production by fermentation medium images, in which the collected images were categorized into three groups, 0–20 g/L, 21–40 g/L, and >41 g/L, based on the PMLA production. The CNN model could predict the production with high accuracy. The methods and results presented in this study provided new insight into evaluating different substrates concentration on PMLA production and demonstrating the possibility of using the convolutional neural network model in the PMLA fermentation industry.

Fusarium graminearum (F. graminearum) is the main pathogen of Fusarium head blight (FHB) in wheat, barley, and corn. Deoxynivalenol (DON), produced by F. graminearum, is the most prevalent toxin associated with FHB. The wheat defense compound putrescine can promote DON production during F. graminearum infection. However, the underlying mechanisms of putrescine-induced DON synthesis are not well-studied. To investigate the effect of putrescine on the global transcriptional regulation of F. graminearum, we treated F. graminearum with putrescine and performed RNA deep sequencing. We found that putrescine can largely affect the transcriptome of F. graminearum. Gene ontology (GO) and KEGG enrichment analysis revealed that having a large amount of DEGs was associated with ribosome biogenesis, carboxylic acid metabolism, glycolysis/gluconeogenesis, and amino acid metabolism pathways. Co-expression analysis showed that 327 genes had similar expression patterns to FgTRI genes and were assigned to the same module. In addition, three transcription factor genes were identified as hub genes in this module, indicating that they may play important roles in DON synthesis. These results provide important clues for further analysis of the molecular mechanisms of putrescine-induced DON synthesis and will facilitate the study of the pathogenic mechanisms of FHB.

The increase in temperatures and changing precipitation patterns resulting from climate change are accelerating the occurrence and development of landslides in cold regions, especially in permafrost environments. Although the boundary regions between permafrost and seasonally frozen ground are very sensitive to climate warming, slope failures and their kinematics remain barely characterized or understood in these regions. Here, we apply multisource remote sensing and field investigation to study the activity and kinematics of two adjacent landslides (hereafter referred to as “twin landslides”) along the Datong River in the Qilian Mountains of the Qinghai-Tibet Plateau. After failure, there is no obvious change in the area corresponding to the twin landslides. Based on InSAR measurements derived from ALOS PALSAR-1 and -2, we observe significant downslope movements of up to 15 mm/day within the twin landslides and up to 5 mm/day in their surrounding slopes. We show that the downslope movements exhibit distinct seasonality; during the late thaw and early freeze season, a mean velocity of about 4 mm/day is observed, while during the late freeze and early thaw season the downslope velocity is nearly inactive. The pronounced seasonality of downslope movements during both pre- and post-failure stages suggest that the occurrence and development of the twin landslide are strongly influenced by freeze–thaw processes. Based on meteorological data, we infer that the occurrence of twin landslides are related to extensive precipitation and warm winters. Based on risk assessment, InSAR measurements, and field investigation, we infer that new slope failure or collapse may occur in the near future, which will probably block the Datong River and cause catastrophic disasters. Our study provides new insight into the failure mechanisms of slopes at the boundaries of permafrost and seasonally frozen ground.

Milk proteins are prone to changes during the heat treatment process. Here, we aimed to study the changes in caprine milk fat globule membrane (MFGM) proteins with three heat treatment processes—ultra-pasteurization (85 °C, 30 min), ultra-high-temperature instant sterilization (135 °C, 5 s), and spray-drying (inlet, 160 °C and outlet, 80 °C)—using the label-free proteomics technique. A total of 1015, 637, 508, and 738 proteins were identified in the raw milk, ultra-pasteurized milk, ultra-high-temperature instant sterilized milk, and spray-dried reconstituted milk by using label-free proteomics techniques, respectively. Heat treatment resulted in a significant decrease in the relative intensity of MFGM proteins, such as xanthine dehydrogenase/oxidase, butyrophilin subfamily 1 member A, stomatin, and SEA domain-containing protein, which mainly come from the membrane, while the proteins in skimmed milk, such as β-lactoglobulin, casein, and osteopontin, increased in MFGM after heat treatment. Among these different heat treatment groups, the procedure of spray-drying resulted in the least abundance reduction of caprine milk MFGM proteins. Additionally, it showed heating is the key process affecting the stability of caprine MFGM protein rather than the spray-drying process. These findings provide new insights into the effects of heat treatment on caprine MFGM protein composition and potential biological functions.

Heat pumps with water as heat exchange medium applied in greenhouse heating have not been used for vegetable seedling cultivation. In this work, a multi-connected direct expansion capillary radiation heat pump (MDCRHP) was designed for vegetable seedling cultivation, and a closed local temperature control (CLTC) method was proposed to accurately control air and substrate temperatures in seedling beds, enhance the heating effect and reduce the equipment cost. The results show that the CLTC method can achieve good heating effect and quickly raise air/substrate temperature at a speed of 1 °C/min from 8 °C to about 20 °C within 12 min. The air and substrate temperature fields in the seedling beds were evenly distributed. The temperature differences at different horizontal positions and different heights were less than 1 °C, and the relative humidity was 100%, which is conducive to vegetable grafting seedling. It can be concluded from test results that the MDCRHP had strong adaptability for greenhouse heating and was obviously superior to the electric heating wire (EWH). The output capacity of the compressor can be controlled by adjusting the operation frequency to meet the temperature requirements at different stages of seedling cultivation. Under the conditions of similar external ambient temperature and heating effect in the seedling beds, the energy saving rate of the MDCRHP was 47–50.7% compared with the EWH. The cost of the MDCRHP is about 7.2% lower than that of the conventional heat pump. It takes 3–3.5 years to recover the equipment investment.

Three-dimensional (3D) graphene oxide aerogel (GOA) is one of the best fillers for composites for microwave absorption. However, its further development has been hindered by the poor mechanical properties. Methodology to improve the mechanical properties of the aerogel remains an urgent challenge. Herein, graphene oxide/carbon nanotube/epoxy resin composite aerogel (GCEA) was successfully prepared by a facile method. The results showed that the prepared GCEA with the hierarchical and 3D cross-linked structures exhibited excellent compression performance, structural and thermal stability, high hydrophilicity, and microwave absorption. The prepared GCEA recovered from multiple large strain cycles without significant permanent deformation. The minimum reflection loss (RL) was −39.60 dB and the maximum effective absorption bandwidth (EAB) was 2.48 GHz. The development of the enhanced GO aerogels will offer a new approach to the preparation of 3D microwave-absorbing skeletal materials with good mechanical properties.

China’s double carbon initiative faces huge challenges, and understanding the carbon sequestration service of terrestrial ecosystems under future interannual regional land use change is important to respond to China’s carbon policy effectively. Previous studies have recognized the important impact of land use/land cover (LULC) planning on carbon sequestration in terrestrial ecosystem services (ESs). However, exploring trends in carbon sequestration under sustainable development scenarios that combine economic and ecological development, particularly the mechanisms that balance the supply and demand of carbon sequestration, still requires in-depth exploration in different geographical contexts. In this study, we present the LULC simulation framework from 2000 to 2030 for four different development scenarios in the Xinjiang region, located in an important Belt and Road region, including business as usual (BAU), rapid economic development (RED), ecological land protection (ELP), and sustainable development with both economic and ecological development (SD). Our results suggest that both the supply and demand of carbon stock in Xinjiang will increase in 2025 and 2030, with the demand exceeding the supply. However, our scenario planning mitigates the supply and demand deficit situation for carbon sequestration in the context of future cropland expansion in different scenarios. In summary, our study’s findings will enrich the study of carbon sequestration under future scenarios in the Belt and Road region. Xinjiang should pay more attention to the dynamic changes in landscape type structure and its carbon storage supply and demand caused by cultivated land expansion. Among the four scenarios, the spatial difference between carbon storage supply and demand based on the SD scenario is the smallest, which is more in line with the high-quality development of regional ecological security in Xinjiang.

TCP transcription factors are a unique transcription family in higher plants, and play important roles in plant development, responses to environmental stresses and phytohormones. Radish is an important crop and widely cultivated worldwide. However, genome-wide identification and expression analysis of TCP family in radish has not been reported yet. In this study, 32 RsTCP genes were identified from the whole genome. Phylogenetic analysis showed that the RsTCP family can be divided into two major groups and three subgroups, namely Class I (PCF), Class II (CIN), and Class II (CYC/TB1). Chromosome mapping showed that 32 genes were distributed on all nine chromosomes of radish. Transcriptome data indicated that the transcription of RsTCP genes differed between tissues and developmental stages. Multiple phytohormone-related cis-acting elements in the promoter region of RsTCPs and several post-translational modification sites in RsTCP protein sequences were identified. The real-time quantitative PCR (RT-qPCR) analysis indicated that several RsTCP genes changed significantly in response to the treatments, including low temperature, drought, salt, gibberellin (GA3), and abscisic acid. Among them, RsTCP16 showed significantly higher levels in leaves than in other radish tissues, and the transcription of RsTCP16 was significantly upregulated under the five treatments, especially during low temperature, salt shock, and GA3 response, suggesting that RsTCP16 could be involved in the development of radish leaves and the response to stress. In summary, these results provided a basis for further exploring the molecular mechanism of RsTCP genes in radish.

Steam flooding is crucial for the development of heavy oil reservoirs, and the development of the steam cavity significantly determines the efficiency of steam flooding. Previous studies have elucidated the concept of steam overburden and pseudomobility ratio; however, the thermal energy loss in deep heavy oil reservoirs during steam injection needs further investigation. Therefore, in this study, the vapour–liquid interface theory and mathematical integration were used to establish a steam cavity expansion model. The wellbore heat loss rate coefficient, steam overlay, and pseudomobility ratio were used to accurately describe the development of the steam cavity in deep heavy oil reservoirs. The proposed model was experimentally validated, and it was observed that the model could accurately reflect the actual mine conditions. In addition, the pressure gradient distribution of the steam belt and the heat dissipation areas of the top and bottom layers of the steam cavity were evaluated. The results showed that the influence of the wellbore heat loss rate coefficient on the pressure gradient of the oil layer was primarily in the range of 5–20 m away from the steam injection well. Furthermore, it was observed that the pseudomobility ratio is inversely proportional to the development of the steam cavity. As the wellbore heat loss rate coefficient increased, the wellbore heat loss increased. The larger the area ratio, the more pronounced the steam overlay phenomenon, and the large area ratio does not meet the development requirements of the steam chamber. The research closely combines theory with production, and the results of this study can help actual mines by providing theoretical support for the development of deep heavy oil reservoirs.

Considering that simultaneous detection of xanthine (XA) and hypoxanthine (HXA) has been proved to be a reliable and feasible method for assessing fish freshness, a novel electrochemical sensing platform based on the ZnIn2S4/UiO-66-NH2 modified glassy carbon electrode (GCE) was constructed in this study for XA and HXA determination. X-ray powder diffraction (XRD), X-ray photoelectron spectroscopy (XPS), transmission electron microscopy (TEM), and Fourier transform infrared spectroscopy (FT-IR) were performed to exhibit the morphology and structural characteristics of ZnIn2S4/UiO-66-NH2. The Brunauer–Emmett–Teller (BET) displayed that the introduction of UiO-66-NH2 can improve the specific surface area of the hybrid. Besides, the electrochemical sensing performance of ZnIn2S4/UiO-66-NH2 was evaluated by cyclic voltammetry (CV) and differential pulse voltammetry (DPV). For simultaneously detecting XA and HXA, the fabricated electrochemical sensor shows wide linear ranges (0.025–40 µM and 0.3–40 µM) with low detection limits (0.0083 µM and 0.1 µM). This sensor also has 96–103% recovery in detecting XA and HXA content in large yellow croaker meat samples, demonstrating a promising application in the marine food industry.

Various externalities caused by highway infrastructures, such as promoting economic development, traffic congestion, and air pollution, are becoming more and more important. Currently, there is no multi-dimensional quantitative evaluation of the externalities of highway infrastructures, hindering the sustainable planning and development of highway infrastructures. Therefore, this study aims to develop a three-dimensional evaluation model of the externalities of highway infrastructures. To achieve the above objective, this study: (1) developed a three-dimensional evaluation index system through a comprehensive literature review and interviews with experts; (2) weighted the evaluation indexes using the entropy weight method; (3) developed the comprehensive evaluation model using the grey correlation analysis method; (4) validated the developed model by using statistical data of Jiangsu province, China. The analysis results showed that the developed model is feasible and effective in evaluating the externalities of highway infrastructures as the analysis results are consistent with reality. In addition, the model can capture the value of externality-related information, the distance to the optimal state of the externalities of highway infrastructures, and the temporal and spatial trends of the externalities of highway infrastructures for a region. The results of this study for the first time set a basis for investigating the influential mechanism of the multi-dimensional externalities of highway infrastructures. Moreover, the results provide theoretical support for the scientific formulation of relevant policies and decision-making for the government.

PM2.5 pollution and visibility impairment has attracted wild public attention in urban China during the past decade. Field observation was carried out in Tianjin, China, during heating (HP) and non-heating periods (NHP). The IMPROVE (Interagency Monitoring of Protected Visual Environments) method was localized to better understand the quantitative impact of PM2.5 composition on extinction coefficient (Bext). Bext of organic mass (OM) was classified into that of primary organic aerosol (POA) and secondary organic aerosol (SOA). Bext of Rayleigh scattering was calculated based on observation data directly, instead of a fixed value in the original IMPROVE method. The mass extinction efficiency (MEE) of EC was also updated based on literature research. The estimation bias of reconstructed Bext was reduced from 4.8 Mm−1 to 0.8 Mm−1 with the localized algorithm. It was found that the secondary components contribute more than 40% of Bext, and ammonium sulfate (AS) and ammonium nitrate (AN) are the dominant components. The different formation pathway leads to significant difference in secondary inorganic components during HP and NHP. Based on the positive matrix factorization (PMF) model and localized IMPROVE method, secondary aerosols were identified as the main source contributing to both PM2.5 concentration (48.2%) and Bext (44.3%) during HP, followed by vehicular emission and coal combustion, biomass burning with municipal incinerators, fugitive dust, and steel processing.

An understanding of the leaf and root traits associated with high nitrogen (N) absorption and utilization is very important in the development of N-efficient varieties in crop breeding programs. However, in rice, the relations between these traits and nitrogen use efficiencies (NUEs) have yet to be identified. Therefore, the responses of leaf and root traits and yields of the three main japonica rice cultivars in northern China were examined at a range of N application rates. The rice cultivars, Shennong 265 (SN265), Tiejing 11 (TJ11), and Fengjing (FJ), were grown in the field at six N rates (0, 60, 120, 180, 240, and 300 kg ha−1) applied during two growing seasons (2018 and 2019). With the increase in N rate, the grain yield of SN265 and TJ11 increased, whereas the grain yield of FJ first increased and then decreased. The grain yield of FJ was higher than that of SN265 and TJ11 at lower N rates, whereas the grain yields of SN265 and TJ11 were higher than that of FJ at higher N rates. The NUEs decreased with the increase in N rates. At lower N rates, the ability of rice to obtain N was the main limitation on rice yield, but with the increase in N rates, the limitation on yield due to N absorption capacity gradually weakened. However, at higher N rates, rice yields were restricted by the ability to utilize N. Compared with TJ11 or FJ, SN265 had higher N utilization capacity primarily because of its higher Rubisco activity, NR activity, GS activity, and ROA. Compared with SN265 or TJ11, FJ had a higher N absorption capacity that was attributed to its larger root architecture, which might have also been one of the reasons for lower N utilization. Therefore, by improving N absorption and utilization-related leaf and root traits, high yields and NUEs can be achieved in rice production at different N application rates.

Mosses are critical components of tropical forest ecosystems and have multiple essential ecological functions. The drying and rehydrating and often hot environments in tropical regions present some of the greatest challenges for their photosynthetic activities. There is limited knowledge available on the physiological responses to the changing environments such as temperature and water pattern changes for terrestrial mosses. We examined the seasonal dynamics of photochemical performance of PS II through the measuring of chlorophyll fluorescence of 12 terrestrial mosses in situ from five different elevations by Photosynthesis Yield Analyzer MINI-PAM-II, along with the seasonal changes of climatic factors (air temperature, dew point, relative humidity and rainfall), which were collected by local weather stations and self-deployed mini weather stations. The results showed a great seasonality during observing periods, which, mainly the changes of rainfall and relative humidity pattern, presented significant impacts on the photochemical performance of PS II of terrestrial mosses. All these tested moss species developed a suitable regulated and non-regulated strategy to avoid the detrimental effect of abiotic stresses. We found that only Hypnum plumaeforme, Pterobryopsis crassicaulis and Pogonatum inflexum were well adapted to the changes of habitat temperature and water patterns, even though they still experienced a lower CO2 assimilation efficiency in the drier months. The other nine species were susceptible to seasonality, especially during the months of lower rainfall and relative humidity when moss species were under physiologically reduced PS II efficiency. Anomobryum julaceum, Pogonatum neesii, Sematophyllum subhumile, Pseudotaxiphyllum pohliaecarpum and Leucobryum boninense, and especially Brachythecium buchananii, were sensitive to the changes of water patterns, which enable them as ideal ecological indicators of photosynthetic acclimation to stressed environments as a result of climate change.

Many force–gradient explicit symplectic integration algorithms have been designed for the Hamiltonian H=T(p)+V(q) with kinetic energy T(p)=p2/2 in the existing references. When a force–gradient operator is appropriately adjusted as a new operator, it is still suitable for a class of Hamiltonian problems H=K(p,q)+V(q) with integrable part K(p,q)=∑i=1n∑j=1naijpipj+∑i=1nbipi, where aij=aij(q) and bi=bi(q) are functions of coordinates q. The newly adjusted operator is not a force–gradient operator but is similar to the momentum-version operator associated to the potential V. The newly extended (or adjusted) algorithms are no longer solvers of the original Hamiltonian, but are solvers of slightly modified Hamiltonians. They are explicit symplectic integrators with symmetry or time reversibility. Numerical tests show that the standard symplectic integrators without the new operator are generally poorer than the corresponding extended methods with the new operator in computational accuracies and efficiencies. The optimized methods have better accuracies than the corresponding non-optimized counterparts. Among the tested symplectic methods, the two extended optimized seven-stage fourth-order methods of Omelyan, Mryglod and Folk exhibit the best numerical performance. As a result, one of the two optimized algorithms is used to study the orbital dynamical features of a modified Hénon–Heiles system and a spring pendulum. These extended integrators allow for integrations in Hamiltonian problems, such as the spiral structure in self-consistent models of rotating galaxies and the spiral arms in galaxies.

Rapid urbanization in China greatly contributes to carbon emissions, while the industrial structure greatly contributes to changes in the variation of carbon emissions. This research addresses the impact of urbanization and industrial structure on carbon emissions from 2010 to 2018, by focusing on the Huaihe River Eco-economic Zone, which is an important economic corridor along the north–south division of China. Although many studies have focused on investigating the impact of urbanization or industrial structure on carbon emissions, few studies further addressed an analysis of the impact of both on carbon emissions, using multiple measurement models. This paper reveals the holistic and local impact of industrial structure and urbanization on carbon emissions, by integrating a threshold regression model with geographically weighted regression. The results are as follows: (1) From a holistic point of view, industrial structure and urbanization had both, single threshold, and double threshold effects on carbon emissions in the Huaihe River Eco-economic Zone. (2) From a regional perspective, the coefficients of industrial structure on carbon emissions were all positive, but the rate of increase gradually slowed down. The coefficients of urbanization on carbon emissions were all negative, reaching a maximum value of negative effect in 2013. Understanding the holistic and local impact of urbanization and industrial structure on carbon emissions provides governments with differentiated and forward-looking suggestions for mitigating carbon emissions in the Huaihe River Eco-economic Zone.

The potential of photocatalysts modified cement-based materials in degrading environmental pollutants is evident in previous studies, but the application of photocatalytic cement-based materials still appears limited in actual practice due to the dispersion effect. This work seeks to prepare photocatalytic cement paste by mixing cement with BiOBr precursor solutions in terms of the improvement of dispersion efficiency, and additional hydrothermal conditions provided by autoclaved curing period are required to activate the photocatalytic activity of photocatalysts crystals. The presence of BiOBr precursor solutions results in an increase of RhB degradation rate of up to 45.4% and the NOx removal efficiency was up to 4.4%, and the formation of BiOBr photocatalysts crystals is the main reason for photocatalytic performance enhancement. The morphology of photocatalysts and the pore size distribution of cement paste also contribute to the photocatalytic activity enhancement by the exposed surface of photocatalysts, which are supported by the analyses of Scanning Electron Microscope and Mercury Intrusion Porosimetry results. A new mechanism is suggested to explain the synergistic role of crystals and microstructure on the enhancement of photocatalytic activity with the extension of autoclaved curing time. As supports for photocatalysts, the development changes of compressive strength of cement paste are also discussed.

Nowadays, IoT is being used in more and more application areas and the importance of IoT data quality is widely recognized by practitioners and researchers. The requirements for data and its quality vary from application to application or organization in different contexts. Many methodologies and frameworks include techniques for defining, assessing, and improving data quality. However, due to the diversity of requirements, it can be a challenge to choose the appropriate technique for the IoT system. This paper surveys data quality frameworks and methodologies for IoT data, and related international standards, comparing them in terms of data types, data quality definitions, dimensions and metrics, and the choice of assessment dimensions. The survey is intended to help narrow down the possible choices of IoT data quality management technique.