Biomacromolecular drugs have become an important component of the new generation of therapeutic drugs due to their high efficiency and specificity. However, their molecular stability are poor, and they are prone to enzymatic hydrolysis, and are difficult to cross biofilms. The effectiveness of traditional nano delivery strategies for biomacromolecule drugs is mainly limited by the low escape efficiency of lysosome. It is of great significance to develop endocytosis independent direct cytoplasmic delivery strategies. This paper reviews the effect mechanism and research progress of cell penetrating peptide, low pH insertion peptide, scavenger receptor mediated non endocytosis, membrane fusion, endoplasmic reticulum pathway, mercaptan mediated, non endosome capture based intracellular delivery strategy of biomacromolecule drugs based on liquid-liquid phase separation technology, and analyzes the difficulties in technology transformation.

As an adsorption material, biochar has been widely used in the field of wastewater treatment. The use of single metal/nonmetal and nitrogen co-doping, under certain conditions, has a synergistic effect between them, which can enrich the catalytic sites on the surface of biochar and increase the catalytic activity. Firstly, the mechanism of the preparation of metal/nonmetal and nitrogen co-doped biochar is summarized. The discussion then focuses on the progress of metal/non-metal and nitrogen co-doped biochar applications in organic wastewater treatment in recent years; Finally, the development direction and application prospect of metal/nonmetal and nitrogen co-doped biochar are prospected.

Bitter taste detection is essential for animal survival. Bitter taste receptors are encoded by bitter taste receptor genes. Bitter chemicals in food stimulate bitter taste receptors in the oral cavity. The information is fed back to the brain via signal conduction to mediate bitter taste perception and ultimately influence food selection and rejection. In exception to the basic taste perception functions, bitter taste receptors are commonly expressed in other organs and tissues beyond the oral cavity playing important roles in cell reproduction, metabolic regulation, inflammation and other important biochemical responses. Although the experimental structures of bitter taste receptors are lacking, it is still important on the treatment of diseases as ideal drug targets due to numerous subtypes and broad expressions. This review presents the expressions of bitter taste receptors in some tissues outside the oral cavity and research advances in diseases, which can help to understand bitter taste receptors comprehensively.

In order to accurately identify the internal relationship between various influencing factors and the key factors in the driving risk system under urban road congestion conditions, an improved DEMATEL-ISM evaluation method is proposed. Firstly, the traffic risk under the condition of urban road congestion is analyzed, and 18 risk factors are selected. Secondly, a traffic risk assessment model of road congestion is established by using the questionnaire method of multi-group inquiry and the improvement of the standard integrated decision Test and evaluation laboratory (DEMATEL) and the interpretive structure model (ISM) combined with the maximum inter-class variance method. Finally, the results of example verification show that the driving risk assessment system based on the improved DEMATEL-ISM method can accurately divide the levels of the hierarchical interpretation structure chart, and is more realistic compared with other methods. Key link factors such as traffic density, headway, stopping times and lane change frequency have a strong linkage effect on other factors, which will increase the probability of traffic accidents or secondary traffic congestion.

With the orderly reform of the energy market, the electricity market has also shown a diversified, open, and competitive development trend. However, when blockchain technology is applied to energy storage transactions, there are still disadvantages such as poor transaction reliability, redundant data, and single energy. Given the above problems, the establishment of a multi-distributed energy storage trading platform based on the alliance chain is studied, Firstly, a node reputation evaluation model is established for the default behavior in distributed energy storage transactions. Secondly, a multi-distributed energy storage transaction mechanism based on on-chain and off-chain collaboration is designed. After the energy storage transmission service party verifies the validity of the smart contract signed by the on-chain network layer transaction user, the off-chain physical layer energy storage transmission is carried out. Thirdly, the alliance chain and the cloud server are combined to establish a data index, and the historical energy storage transaction data is stored in the cloud server. Finally, based on the Fabric network, a multi-distributed energy storage trading platform is built. The simulation example verifies that the trading mechanism proposed in this paper can improve the transaction efficiency while ensuring the security and reliability of the energy storage transaction, and meet the requirements of the multi-distributed energy storage transaction scenario for transaction reliability, data flexibility, and energy storage diversity.

In the context of promoting the low carbon transition of Integrated Energy Systems (IES), a model is proposed in which Photothermal Methane Reforming to Hydrogen (PMRH) and Gas Doping with Liquid Carbon Capture Storage (LCCS) operate together. The optimal scheduling model of the system is proposed. A model of the PMRH plant and the electrolyser is developed first, followed by a model of the hydrogen-doped gas units and the carbon capture plant to address the carbon emission issue. Based on this, the IES low carbon optimization model is constructed with the objective of minimizing economic and environmental costs, taking into account constraints such as power and hydrogen doping ratios. The analysis of different scenarios of the constructed model shows that the total cost of the system is reduced by 27.9% and the carbon emissions are reduced by 28.2%, which verifies the advantages of the proposed model in terms of economy and low carbon.

The effects of electromagnetic induction coefficient and membrane surface charge size on the memristor Morris-Lecar (ML) neural network dynamics are investigated. Using charge size as a parameter to study the discharge behavior of memristor ML neural network, it is found that increasing charge size will inhibit the firing frequency and amplitude of neurons, and the neurons will enter the resting state over time. The synchronization behavior of neural network is studied with electromagnetic induction coefficient and charge size as variables. When the electric charge size is fixed and the electromagnetic induction coefficient is increased, the neural network becomes orderly from chaos. The electromagnetic induction coefficient is the key factor to determine neural network synchronization. When the electromagnetic induction coefficient K>3.2, the synchronization can be induced and enhanced more effectively. Synchronization factor and standard deviation are introduced to quantify the degree of network synchronization and neuron firing. The experimental results show that the electromagnetic induction coefficient can effectively regulate the synchronization behavior of neural network, and has the function of controlling the discharge mode and network synchronization.

In response to the two core issues of implicit appearance of target topics in Weibo texts and implicit expression of text semantics in text position detection, a new position detection method, KE-BERT, is proposed in this paper, based on the combination of multi-type knowledge enhancement and pre-trained language models. Therefore, KE-BERT can overcome semantic deficiencies. The model incorporates relevant commonsense knowledge from knowledge graphs and Baidu encyclopedia, utilizes the enhanced pre-trained language model BERT as the encoder, and employs convolution attention mechanisms to combine and focus commonsense knowledge. Finally, the stance is determined through softmax classification. Experimental results on the NLPCC-2016 corpus demonstrate the effectiveness of the model, achieving a macro average F₁-score of 0.803. KE-BERT outperforms the other existing methods in classification performance.

Diabetic retinopathy is a common complication of diabetes. A classification algorithm based on split residual network is proposed to improve the classification accuracy of diabetic retinopathy images. Through the fusion of normalized attention, the ability to identify key feature information is enhanced, which makes the model more targeted for extracting lesion feature information. The global context module is used to comprehensively consider the feature information learned from different scales and network layers, and further contact the characteristics of diabetic retinopathy in different periods to enhance the expression ability of the model. The output structure uses multi-branch structure to classify images, which avoids the problem that the uneven distribution of data sets affects the classification accuracy. Experimental results show that the model accuracy is 94.86%, and other evaluation indexes are improved compared with the original backbone network model. The proposed model has good performance, and the high-precision diagnosis and grading of diabetic retina images are realized.

A substation personnel detection based on the L-ConvNeXt network is proposed to solve the problems of excessive amount of network parameters and unclear characteristics of operational personnel detection in the complex environment of substations. Firstly, the backbone feature extraction network is built by the lightweight ConvNeXt to enhance the feature extraction capability of the network while keeping the backbone with a low parameter. Then, the transformer prediction head(TPH) is selected as the end detection head to enhance the detection of low-resolution features by the network. Finally, VariFocal Loss is introduced to replace Focal Loss as target loss and confidence loss to improve the loss weight of the network for positive samples. The experimental results on the public dataset of Tianchi show that the proposed network achieves a better detection results, the average detection accuracy reaches 89.6% and the number of model parameters is 13.2×10⁶, which can effectively detect the operation of substation personnel and meet the detection requirements of substation operators in complex scenarios.

In view of the large difference of different sizes of aluminum surface defects leading to poor detection effect, an aluminum surface defect detection algorithm based on improved YOLOv5 is proposed. Firstly, CA attention mechanism module is embedded in the network to make the network better suppress the interference of invalid samples in the image and focus more on useful information. Secondly, a small target detection layer is added to the original detection layer to acquire and transmit more abundant and discriminant small target features, so as to solve the problem of low detection accuracy of small target defects and improve the overall detection accuracy. Finally, the SIoU loss function is introduced and the vector angle between boundary box regression is introduced to redefine the loss function, which effectively reduces the total freedom of loss and improves the reasoning precision. The improved algorithm is applied to Tianchi aluminum data set for verification. The experimental results show that the model can effectively identify different types of defects on aluminum profiles, which is 11.4% higher than the original YOLOv5 algorithm mAP, and the detection speed is up to 66.4 frame/s. The proposed method can meet the requirements of on-site defect detection in aluminum profile factories.

In this paper, the large time behavior of the solutions to magnetohydrodynamic equations is investigated, focusing on the regularity of the global attractor. Using the embedding theorem of fractional order spaces and the existence theorem of global attractor, it is obtained that the magnetohydrodynamic equations have global attractors in H¹ and H² spaces, respectively. Furthermore, by using an iteration method, regularity estimates for the linear operator semigroup and existence theorem of global attractor, it is proved that the magnetohydrodynamic equations have a global attractor in H^k for any k≥0, which attracts any bounded set in the H^k-norm.

A new Tseng outer gradient algorithm for solving pseudomonotonic variational inequality problems is proposed in Hilbert space. Under appropriate conditions, it is proved that the iterative sequence generated by the algorithm strongly converges to the common element of the solution set of pseudomonotonic variational inequality problem and the set of fixed points of the quasi-non-expansion map, and numerical experiments are given to illustrate the effectiveness of the proposed algorithm.

Practical-component consensus refers to the fact that the error of some components of all state variables in a multi-agent system always fluctuate within a bounded interval. In this paper, the practical-component consensus problem of a first-order nonlinear leader-follower multi-agent system is explored based on a directed network topology. Firstly, a segmented pinning control protocol is constructed for the system. Then, the original error system is transformed into a new error system by using the method of permutation matrix, so that the practical-component consensus problem of the original system is transformed into a strong practical stability problem with zero solutions in the new error system, and the sufficient conditions for the practical-component consensus of the system is derived with the knowledge of matrix theory and stability theory. Finally, the numerical simulation verifies the correctness of the theoretical results.

In order to provide theoretical basis for the material basis of analgesic effect, the chemical constituents and analgesic mechanism of Rhododendron molle G. Don root were studied. Component separation was carried out using macroporous resin, silica gel column chromatography and preparative chromatography, and the compound structures were identified by ¹H NMR, ¹³C NMR and UPLC-QTOF-MS/MS. And the main targets and key pathways of components were analyzed by network pharmacology method. Nine compounds, including three dihydrochalcones, three triterpenoids and three fatty acids, were isolated and identified. The results of network pharmacology showed that 9 compounds mainly acted on MAPK1, MAPK3, MAPK8, IL-6 and CASP3 targets, regulated arachidonic acid metabolism and inflammatory mediators in tryptophan channels, and exerted anti-inflammatory and analgesic effects. In this study, the chemical constituents and potential mechanism were clarified, which provided a scientific theoretical basis for screening of analgesic substance of the root of Rhododendron molle G. Don.

S-CuCo₂O₄ was prepared by using thiourea as sulfur source to vulcanize CuCo₂O₄ via a simple hydrothermal method. The composite catalyst S-CuCo₂O₄ was characterized by XRD, FT-IR, SEM, XPS, ICP-OES and EPR, and the degradation effect of ciprofloxacin by activating PMS was investigated. The experimental results showed that S-CuCo₂O₄ catalyst has been prepared successfully, and its surface is rich in Co(Ⅱ) and Cu(Ⅰ); when the dosage of catalyst was 0.06 g/L, the dosage of PMS was 0.2 g/L and pH was 6.4, the S-CuCo₂O₄ showed superior behavior for degradation of ciprofloxacin with the efficiency as high as 96.8% in 25 min, better than that of CuCo₂O₄ and CuCo₂S₄. Finally, it was proved that SO^-₄· and ¹O₂ were the main reactive oxygen species in the reaction system by free radical quenching experiment and EPR test. The possible catalytic mechanism is as follows: Cu(Ⅰ) and Co(Ⅱ) can react directly with persulfate (PMS) to form free radicals, and Cu(Ⅰ) can reduce Co(Ⅲ) to form Co(Ⅱ), promoting the Co(Ⅱ)/Co(Ⅲ) cycle,the oxygen vacancies on the catalyst surface can also react with PMS to form ¹O₂, and ciprofloxacin can be efficiently degraded under the joint action of reactive oxygen species. The degradation efficiency of the compound catalyst S-CuCo₂O₄ for ciprofloxacin was still up to 93.5% after four cycles, which proved that the cyclic stability was good. It also has good degradation efficiency for other pollutants, and excellent generality, suggesting its potential in wastewater treatment.

Nuclear pore complexes (NPCs) form channels to transport materials across the nuclear membrane. Nucleoporin can affect the material exchange between nucleoplasm and cytoplasm, and the nucleoplasm transport has the ability to coordinates germ cells into female or male differentiation pathways. Gonadal soma-derived factor (Gsdf) can regulate the male germ cells of Oryzias latipes and play a key role in switching on/off gametogenesis before the last turn of mitosis. The expression of nup58 (nucleoporin 58) was higher in normal testis than that in normal ovary detected by RT-qPCR. Moreover, compared with normal testicular transcriptome data of medaka(Oryzias latipes), the expression of nup58 in gsdf deficient testis was found to significantly increase by the RNA-seq. The results of immunofluorescence assay showed that nup58 was expressed in all germ cells at different stages of gametogenesis in both wild type and gsdf-knockout medaka gonads. This research shows that Nup58, as a nucleoporin, is regulated by gsdf signal and is closely related to the proliferation of male germ cells. Nup58 participates in dynamic events of nuclear cytoplasmic transport during sexual differentiation, and its synergistic effects need to be explored.

To explore the effects of different biochar application amounts on soil organic carbon components and carbon pool management index of moso bamboo forests, this study took the soil of the moso bamboo forests in the upper reaches of the Lijiang River as objects, and the biochar from high-temperature pyrolysis of bamboo waste materials as test materials. After the one-year field application experiment in the moso bamboo forests, the changed characteristics of soil active organic carbon components and soil carbon pool management index under different biochar application amounts (0 (CK), 10 t·hm^-2 (BC1), 20 t·hm^-2 (BC2), 40 t·hm^-2 (BC4)) were measured, and the impact of environmental factors on them were analyzed. The results showed that: the high additive amounts of the biochar (BC4) significantly increased the contents of soil pH, available phosphorus, available potassium, ammonium nitrogen, soluble organic nitrogen, and microbial biomass nitrogen to compare with that of the control treatment (CK), but significantly decreased soil total phosphorus content (P<0.05). Biochar could significantly promote the total organic carbon, easily oxidized organic carbon, particulate organic carbon and carbon pool management index. All of them reached the maximum at the treatment of BC4. The correlation analysis showed that the soil carbon pool management index was positively related to pH, NH⁺₄-N, EOC, and POC (P<0.01). A path analysis model found that soil properties and available nutrients directly affected the active carbon components, and then indirectly affected the soil carbon pool management index after adding the biochar. In summary, the application of biochar in the moso bamboo forests was an effective pathway to improve soil quality, promote soil carbon sequestration and appropriately use bamboo waste materials. The best effect in the studied area was the treatment of biochar amount with 40 t·hm^-2.

This study was aimed to investigate the effects of fermented Siraitia grosvenorii residue on the intestinal morphology and flora of yellow-feathered broilers. 360 one day old healthy yellow-feathered broilers were randomly divided into 4 groups with 6 replicates in each group and 15 broilers per replicate; Broilersin the control Group (Ⅰ)were fed a basal diet, and the others in (Ⅱ,Ⅲ,Ⅳ) group, 1-21 days old were fed with 1%, 3% and 5% fermented siraitia pomace in the basic diet to replace corn; 22-42 days and 43-70 days old were fed with 5%, 8% and 10% fermented siraitia pomace, respectively. The trial period was 70 days. The results showed that compared with the control Group I, the age of 21 days and 42 days,there were no significant difference between Group in the villus height, recess depth and V/C of duodenum, jejunum and ileum in Ⅰ, Ⅲ and Ⅳ. At 70 days of age, the duodenal recess depth of Group III and Group Ⅳ decreased by 36.01% (P<0.05) and 33.46% (P<0.05), the V/C increased by 78.05% (P<0.05) and 69.98% (P<0.05), respectively. In terms of intestinal flora, the number of OTUs shared by Group I and Group Ⅲ were 537, and the number of unique OTUs in Group I and Group Ⅲ were 55 and 7 respectively; At the phyla level, the core microflora are Firmicutes, Bacteroides and Proteus, among which, the relative abundance of Proteus and Epsilon bacteraeotain Group Ⅲ were significantly lower than that in Group I (P<0.05); At the genus level, the uncultured_bacterium_f_Clostridialgroup in Group III was significantly higher than that of trial Group I (P<0.05); Alpha diversity index and Beta diversity index of Group I and Group III were not significantly different (P>0.05). Fermented Siraitia grosvenorii residue could ameliorate intestinal micro environment and health of Yellow-Feathered Broilers.