In recent years, great attention have been paid to the second-generation quantum technologies, delivered by the directly manipulating wave functions of quantum systems, including atomic clocks and quantum information technologies (such as quantum communication, quantum computation, and quantum sensing). As the basic and key devices, single photon detectors play an important role in optical quantum information processing. Focusing on the application in quantum information application, this paper introduces the basic principles of single-photon detection and the main performance indicators of single-photon detectors, systematically summarizes the research progress of superconducting single-photon detectors that play an important role in the research of optical quantum information processing in the past two decades, and forecasts the development prospect of microwave single photon state detector which will promote the research of microwave quantum information processing in the future.

Successive approximation register analog-to-digital converter (SAR ADC) has dominated the market for moderate speed and accuracy ADCs, with sampling frequency of up to 5 MHz and typical resolutions of 8 to 16 bits. While maintaining its inherent advantage of low power consumption, it faces the challenge of higher speeds and higher accuracy. The research status and advanced technology of successive approximation register analog-to-digital converter in recent years are summarized. Moreover, the sub-modules of capacitor array switching techniques, comparator and the calibration are generalized and discussed. The performance of capacitor array DACs combined with different switching strategies is compared. Comparator structures suitable for different scenarios are proposed. Calibration methods such as redundancy techniques and self-calibration techniques are discussed. Some recommendations are provided for designers to understand successive approximation register analog-to-digital converters.

Knowledge representation is the basis of all artificial intelligence algorithms. It can represent human knowledge as a data structure that can be processed by machines. This paper shows the knowledge matrix representation, which can fundamentally simplify the operation process of the algorithm and improve the operation efficiency of the algorithm. Specifically, this paper first transforms 13 kinds of interval relationship representations in temporal reasoning into 5×5 matrix. On this basis, the calculation and propagation of temporal relations can be obtained through matrix calculation. Then, the relationship between production rules is transformed into a matrix and encoded into a calculation formula, which is a mathematical model of uncertain reasoning. Finally, the sample relationship is expressed as a matrix, and K values and K nearest neighbors can be obtained in one step calculation. It can model the lazy learning part of KNN classification, i.e., transform it into a mathematical model. In addition, this paper also looks forward to the future work of knowledge matrix representation, and points out that knowledge matrix representation needs to define different calculation methods for different applications.

Digital image is an important information carrier in the current network environment. Once the image containing confidential information is attacked or stolen, it is very likely to bring about information security problems. Therefore, it is urgent to take effective protection schemes for image information. Takingimage data security and transmission efficiency into account,chaotic image encryption algorithm based on compressed sensinghas high value of research and application. This paper first introduces the basic principles of chaos theory, image encryption and compressed sensing. Then, the characteristics and advantages of several principal methods of chaotic image encryption based on compressed sensing are analyzed. In addition, the status quo of the current research is summarized. Finally, the remaining problems are discussed and the trend of future development is forecasted.

Large-scale pre-trained language models based on deep neural networks have achieved great success in various natural language processing tasks, such as text classification, reading comprehension, machine translation, etc., and have been widely used in the industry. However, the interpretability of these models is generally poor, that is, it is difficult for us to understand the reasons why different model structures and pre-training methods are effective, and to explain the internal mechanism of the models making predictions, which brings difficulties to the generalization of artificial intelligence models because of the uncertainty and the uncontrollability. Therefore, it is crucial to design reasonable methods to explain the model, which can not only effectively explain the behavior of the model, but also guide researchers to better improve the model. This paper introduces various research statuses of the interpretability of large-scale pre-trained language models in recent years, reviews related methods, and analyzes the shortcomings of the existing methods and possible future research directions.

Video hash is a short digital sequence based on visual content extracted from video. In practical applications, the strategy of representing a video by its video hash can reduce storage cost of video and complexity of calculating video similarity. Video hash is widely used in many applications, such as copy detection, tampering forensics, video indexing, and video retrieval, etc. In recent years, there are many progresses on video hashing research. Researchers have designed and developed some techniques of hand-craft feature extraction and presented many video hashing algorithms. This paper classifies the hand-craft features based video hashing algorithms into two categories: spatial computation, and spatial-temporal computation. Moreover, the video hashing algorithms based on spatial computation are further divided into two sub-categories: frame-by-frame calculation and key frame calculation. The video hashing algorithms based on spatial-temporal computation are further divided into five sub-categories: orthogonal transform, statistical feature, visual feature point, data dimensionality reduction and other technique. In this paper, some typical algorithms of each category are first described, and their performances are then summarized. Next, the common-used metrics of hash similarity, performance evaluation indices and video datasets are introduced. Finally, the future trend of research is presented, including video hashing for tampering forensics, efficient video hashing based on deep learning, lightweight video hashing for mobile applications, and so on.

Target tracking is one of the core basic research issues in the field of computer vision. Its performance can cooperate with the analysis and research of high-level video applications, which has important theoretical value, extensive practical value and interdisciplinary. Therefore, it has become the focus of academia, industry and national strategy. Due to the high complexity and strong interference of the tracking scene, the diversity of target apparent changes and multi-modal information fusion, the tracker needs to balance the performance measurement indicators such as robustness, accuracy and real-time. At present, a lot of work has been done to solve the challenges in the field of target tracking from different perspectives, but under the measurement of multi-dimensional performance indicators, it still can not solve the tracking problem in complex scenes. Through the research of target tracking algorithm based on Siamese network, this paper reviews the current development status of the field, discusses the existing challenges and looks forward to the research direction worthy of attention in the future, so as to provide a reference for the future research work in this field.

Bifurcation of limit cycle and isochronous center of differential systems are classical problems in the qualitative theory of differential equations which are always hot topic in the research of differential equations. The study has important theoretical and applied value. Compared with planar systems, the research of limit cycle and isochronous center for three-dimensional differential systems is a more challenging work, and the complexity of the system and the difficulty of qualitative analysis have greatly been improved. This paper mainly introduces the research progress of limit cycles and isochronous centers of three-dimensional differential systems in recent decades, and puts forward some problems to be solved in this field.

The compressible non-conservative two-phase flow models are widely used in industrial applications, such as nuclear, power, chemical-process, oil-and-gas, cryogenics, bio-medical, micro-technology and so on.This paper makes a review on the study of three types of compressible non-conservative two-phase flow models with equal pressure and capillary effect, unequal pressure without capillary effect, and equal pressure without capillary effect. Then, introduces the research developments of these three types of compressible non-conservative two-phase flow models, respectively.In particular, the linear system of the high-dimensional compressible non-conservative two-phase flow model with equal pressure without capillary effect contains zero eigenvalue, which makes the mathematical analysis of this problem very difficult. The new model has no mathematical results so far, and will be the focus of future work.

Spatial econometric data appear in almost all fields of society and have a wide application prospect. The study of the statistical inference for spatia econometric models (including the estimation and test of model parameters) has important theoretical significance and practical value. In this paper, some common spatial econometric models are briefly introduced, a brief review on the research progress of spatial econometric models except the empirical likelihood method is provided, and the background of the empirical likelihood and the research progress of the empirical likelihood for spatial econometric models are provided in detail.

Nonparametric likelihood, especially empirical likelihood, is one of the nonparametric methods, which has many similar properties with traditional parametric likelihood. This fascinating methodology has attracted the attention of many researchers, and become one of the important research fields in statistics. Numerous papers have been published and the list is getting longer every day. This review summarizes the nonparametric likelihood method from estimation, test and the applications in complex data, based on the works of the research group. The research approach and content are analyzed, some major findings are provided in the review.

Let G be a finite group, and χ∈Irr(G). The number cod(χ)=|G∶ker χ|χ(1) is called the codegree of the character χ. This paper makes a review on the results concerning codegree of irreducible character in finite groups in particular, lists some problems which are still open.

In the family of rare-earth metal complexes, radical rare-earth metal complexes have attracted great attention of the researchers in the past 30 years because of their unique chemical reactivities and magnetic properties. To fine-tune the different properties of radical rare-earth metal complexes, scientists have developed different combinations of radical ligands, closed-shell ligands and rare-earth metal centers. Herein, the reported structures, ligand types, coordination modes, chemical reactivity and magnetic properties of radical rare-earth metal complexes were reviewed according to the history of this field, and was divided into two parts as neutral/anionic radical ligands. The outlook of this field was also presented.

Faced with the increasingly severe environmental pollution and energy crisis, the development of efficient and clean energy conversion technology has attracted more attention. Electrochemical energy conversion technology represented by electrocatalysis has developed rapidly in recent years because of its high efficiency and no pollution. However, the electrocatalytic reaction at the solid/liquid interface involves a variety of reaction species, which makes its mechanism research very difficult, and limits the rational design and development of high-efficiency electrocatalysts. Electrochemical in situ enhanced Raman spectroscopy has the advantages of high sensitivity, good selectivity and fingerprint recognition. It can reveal the electrocatalytic reaction process at the molecular and atomic levels. This paper reviews the application of electrochemical in situ enhanced Raman spectroscopy to study some critical electrocatalytic reactions, including oxygen reduction reaction, hydrogen oxidation reaction, oxygen evolution reaction, hydrogen evolution reaction, carbon dioxide reduction reaction, and so on. Finally, some problems faced by in situ enhanced Raman spectroscopy in the study of electrocatalytic reactions are summarized, and its development are briefly prospected.

Surface-enhanced Raman scattering (SERS) technique is a rapidly developing analytical method in recent years. It has the advantages of simplicity, rapidity, high sensitivity, strong recognition ability and good selectivity. The sensitivity and reproducibility of SERS technology are mainly dependent on the properties of its substrate, which is the hotspot of SERS quantitative research at present. Based on the work of our group, this paper summarized the properties and preparation methods of nanosol substrates commonly used in SERS analysis and determination, such as nanogold, nanosilver and composite nanomaterials. The research status quo of SERS technology combined with aptamer reaction, immune reaction and other reactions including molecular imprinting, microfluidic and thin layer scanning as a means to improve the selectivity and sensitivity of environmental pollutants analysis was introduced. In addition, the catalytic properties of nanoscale materials and preparation methods of the metal (oxide) nanoparticles, carbon quantum dots, covalent organic framework (COF), and metal organic framework (MOF) were summed up. Combining with nanoenzyme catalysis and molecular reaction used for amplification SERS signals, the quantitative analysis method of nanosol SERS had the advantages of high sensitivity and high selectivity. In conclusion, this paper mainly summarized the hot spots of SERS quantitative research such as substrate preparation and nanocatalysis and its application in the analysis of environmental pollutants in order to provide a positive reference for theoretical research on SERS quantitative analysis and expand the application of SERS technology.

Fluorescence polarization (FP) is an analytical method for the study of intermolecular interaction or quantitative detection of target molecules through the changes of FP signals before and after the combination of fluorescent groups and other molecules in the system. It has significant advantages such as high sensitivity, rapid analysis, easy operation and high throughput, which can be combined with other analytical technologies, and has been widely used in the fields of biochemical analysis and disease diagnosis. In recent years, with the development of modern analytical techniques and technological advances in the fields of nucleic acid and material science, many FP assays with higher analytical performance have been reported. The trend of future researches is to deeply explore the fluorescence polarization detection technology with strong stability, low cost and various functions. This review,mainly summarize the recent advances of FP and their analytical applications in detection of biological small molecules, nucleic acids, proteins, biological enzymes, metal ions, pesticides and biochemically related substances. Moreover, the prospect for future development of FP is provided.

Cyclocarya paliurus (Batal) Iljinskaja, belonging to the genus Cyclocarya (Juglandaceae), consists only one species distributed in south China. C. paliurus leaves are used in traditional medicine for a long history. It contains the inorganic constant and trace components required by the human body, and it is a selenium-rich plant product. More than 240 compounds, including dammarane triterpenoids, oleanane triterpenoids, ursane triterpenoids, lupinane triterpenoids, flavonoids, isosclerones, phenolic derivatives, and polysaccharides, etc, have been separated from C. paliurus. Among them, 3,4-seco-dammarane triterpenoids are the most abundant and the most characteristic. Furthermore, the extracts and compounds from C. paliurus have been found to exert various pharmacological activities, such as anti-hyperglycemic, anti-hyperlipidemic, anti-inflammatory, immunomodulatory, cytotoxic activities. Although great breakthroughs during the past 30 years years have been made in the research of the pharmacology and constituents of C. paliurus, the research and development of drugs related to C. paliurus has lagged behind seriously. The systematic and in-depth research is still needed in the toxicity and development of C. paliurus. The present review summarizes the constituents and pharmacological activity of C. paliurus to provide reference for further research, development and utilization of this plant.

Rosinane diterpenoids are a class of compounds with a tricyclic diterpene structure, which are widely presented in plants and microorganisms and have a wide range of uses. Due to the in-depth research of natural products and the continuous modification of their structure by organic synthesis, rosinane-type diterpene-type compounds show better bioavailability. This article reviews the application of rosinane-type diterpenes in pesticide and pharmaceutical research from five aspects: pesticide science, pharmacy, chiral drug detection, and research on the relationship between the structure and properties of active compounds.

How to achieve efficient and targeted drug delivery is a current research hotspot. Ultrasound has the advantages of non-invasiveness, non-radiation, simple operation and low price. Clinical diagnosis uses the principles of reflection, refraction and diffraction of ultrasound. Attributed to its mechanical and thermal effects, ultrasound is also an efficient exogenous stimulation method for controlling drug release, which can improve the permeability of diseased tissues and cell membranes, and promote the uptake of drugs by cells. On this basis, the ultrasound mediated drug delivery has become an efficient and noninvasive delivery technology. The targeted and quantitative release of drugs can be realized by irradiating the tumor area with ultrasound, so as to increase the local drug concentration and thus improve the curative effect. Ultrasound combined with various carriers, such as ultrasonic microbubbles, liposomes and so on, has great clinical translation value in drug targeted delivery. This article will review ultrasound-enhanced drug delivery mechanism, ultrasound responsive carriers, the effect of ultrasound-enhanced drug delivery and its clinical application prospects.

Tumor-associated macrophages(TAMs) are the most widely infiltrating immune cells in the tumor microenvironment(TME). Clinically, the number of TAMs is closely related to the poor prognosis of many cancer patients. TAMs play an important role in various stages of tumor progression. A number of studies have demonstrated that reducing the density or effects of TAMs can inhibit the growth of tumors. As the relationship between TAMs and malignant tumors becomes more and more clear, TAMs has been regarded as a potential target for cancer therapy. This review summarizes the origin, classification, role in tumor growth about TAMs, and the therapeutic strategies of Targeting TAMs.

Nanozyme is a kind of nanomaterial with enzyme-like catalytic activity. Tumor microenvironment has its own unique biochemical characteristics, and this review summarizes that stimulating responsive nanozyme in tumor microenvironment can promote ROS production to enhance chemodynamic therapy in situ, by regulating acidity, increasing H₂O₂ concentration, changing glucose metabolism, eliminating antioxidants. Based on this, the research progress of nanozyme catalytic therapy synergistic photodynamic therapy, photothermal therapy, sonodynamic therapy, radiotherapy and immunotherapy were further reviewed.

Biological neuron is the basic unit for signal processing in the nervous system, and its complex anatomical structure and synaptic plasticity enable it’s self-adaption to external stimuli. As a result, its firing modes and pattern become rich and diverse. In different functional regions in brain, these neurons are clustered in networks and they are cooperated to encode all external stimuli. Neurons from different regions of the brain are communicated by triggering synchronous states in and between multi-layer networks, and then the body and organs are guided to behave suitable gaits. The collective electric activities are dependent on the local kinetics, connection links and biophysical properties of the coupling channels, topological types and physical effects as well. Researchers can start possible investigations by building reliable biophysical neuron models, enhancing the controllability of the coupling channels, exploring the energy properties when synchronization stability and pattern formation are regulated in the networks, clarifying the physical mechanism for noise driving, discovering the biophysical mechanism for frequency selection and wave filtering. And these findings can be helpful to recognize the mode response and prevent the occurrence of some neural diseases. This review aims to enhance the biophysical function of an isolated neuron, for example, a variety of electric components are incorporated into branch circuits of a generic nonlinear circuit for detecting and discerning the temperature, illumination, acoustic wave, external magnetic field and electromagnetic radiation, respectively, and different functional neural circuits are obtained. Furthermore, exchange and propagation of field energy in neuron, frequency selection in the auditory neuron and visual neuron, energy pumping and energy consumption in the coupling channel, field energy to Hamilton energy under scale transformation, field coupling synchronization to resonance synchronization, pattern selection and synchronization stability in neural network, are discussed and investigated for possible guidance. These systematic introduction and comments on the functional enhancement of neurons and dynamics in networks have potential guidance and help for further building intelligent functional neuron array and devices.

“Bitterness” is a common sense of taste, and is also the main characteristic of the property of traditional Chinese medicine. Bitterness is one of the “five flavors” in the property of traditional Chinese medicine, which is a high overview of the efficacy and the law of action of traditional Chinese medicines. Bitter drugs have the characteristics of “diarrhea, dryness and firmness”, and the functions of “purging fire, lowering qi, drying dampness and strengthening yin”. Bitter medicine accounts for a high proportion of traditional Chinese medicine. In the theory of traditional Chinese medicine, bitter ingredients are considered to be the active components of bitter traditional Chinese medicine, which mainly include alkaloids, glycosides and bitter substances. The receptor molecules of bitter sensory are distributed in taste buds, intestines, respiratory tract and other tissues or organs. This paper summarized the active substances, bitterness classification, bitterness formation mechanism, the relationship between bitterness and disease, and the biological significance of bitterness in traditional Chinese bitter medicine. It is expected to provide reference for the study of the properties of traditional Chinese medicine and the clinical application of traditional Chinese bitter medicine.

Taking the Web of Science as the data source, CiteSpace (5.7.R5W) a literature statistical analysis software was used to draw the knowledge map of the lizard and climate change research field, the annual statistics of the field, the main research strength, cooperation relations, disciplines, journals, Systematic analysis of research preface and knowledge base, research hotspots and development trends. The results show that: 1)The number of papers published in the field of lizards and climate change is increasing, and the development speed is rapid; 2)Developed countries are the main research force in the field of lizards and climate change, and the United States and Australia have the highest number of papers, occupying a major position; Australia’s James Cook University is the main research institution; moreover, the cooperation between various countries and institutions is constantly increasing; 3)The literature in the field of lizard and climate change research involves multiple disciplines, and the existing disciplines mainly involve the field of life sciences; 4)The current seven research hotspots in this field are thermoregulation, phylogeny and species evolution, biodiversity, vulnerability, assessment and modeling, conservation management, and climate change. Among them, thermoregulation, phylogeny, species evolution and vulnerability are still the research hotspots in this field in the world.

Morphometrics, as a significant part of the quantitative study of biological morphology in biology, is widely used in the study of systematics, phylogeny and morphological variation. Firstly, the analytical methods of geometric morphometrics, including Landmark methods and Outline methods, Thin-plate spline analysis and Fourier analysis, principal component analysis and phylogenetic principal component analysis, cluster analysis, discriminant analysis and module integration analysis, are summarized. Then, the common softwares for and main use of geometric morphometrics are discussed. Finally, the application of geometric morphometrics in Orthoptera is introduced in order to promote understanding of geometric morphometrics and provide new ideas for the study.

Gastrointestinal parasite is an important part of the host body and have an important impact on the growth and development of the host and immune diseases. With the increasing contact between non-human primates and humans, non-human primates are at increasing risk of gastrointestinal parasites. New diseases caused by gastrointestinal parasites pose a serious threat to the survival of primates and have become an important challenge for primate protection. This article summarizes the types and characteristics of non-human primate gastrointestinal parasites, and discusses the social behavior, growth and development, foraging and nutrition, immunity and disease, defense, and defense of intestinal parasites and non-human primate hosts. The impact of human activities on non-human primate gastrointestinal parasites and other aspects are reviewed, in order to provide a certain theoretical basis and new ideas for the study of the role of non-human primate gastrointestinal parasites and public health.

Forestry medicine planting refers to the planting mode which relies on the existing forest land resources and the ecological environment under the forest, so as to makes full use of the forest space by interplanting Chinese herbal medicines with low plant height and shade preference under the forest. Forestry medicine planting mode plays an active role in protecting forest resources and ecological environment, so the planting mode of interplanting Chinese herbal medicine under forest has become a popular choice for developing forest agriculture. This paper mainly expounds and summarizes: different forestry medicine planting models, influencing factors of forestry medicine planting, the related research progress of the relationship between gene and metabolite and metabolic pathway which is revealed by the analysis of metabolomics and transcriptomics data, in order to provide reference for the sustainable development of interplanting Chinese herbal medicines under forest and increasing the economic benefits of farmers who manage forest industry.

Soil microbial carbon use efficiency (CUE) is an index to evaluate the efficiency of microorganisms to incorporate organic carbon into microbial biomass in ecosystems. This index reflects ecosystems’ ability for carbon assimilation and sequestration. This paper mainly reviewed the researches on the impacts of soil nutrients and stoichiometry on microbial CUE, and summarized the mechanisms of the effects on CUE from the angles of the quality of soil organic matter, nutrient availability, stoichiometry of carbon, nitrogen, phosphorus and extracellular enzyme activities, nutrient limitation induced change in microbial community structure and organic priming effect. Furthermore, the indirect influences of climate, ecosystem and land-use types, soil depth and physiochemical characteristics to microbial CUE via their impacts on soil nutrient status were discussed. On the basis of the above analysis, the challenges in research approaches of microbial CUE and scales, and the future research directions were discussed.

Citrus canker disease is one of the important diseases in citrus production. Microbial control has unique advantages in the prevention and control of citrus canker disease, which can not only reduce the occurrence of the disease, but also be safe and pollution-free to the environment. Based on the analysis of the literatures about microbiological control on this disease in the past 20 years, it was found that its microbial prevention still mainly focused on the screening and identification of biocontrol bacteria in the laboratory, in which the species from bacillus and the control effect of single bacterium had been mostly reported. The main application methods were live strains or bacterial agents. While the study of the mechanism and identification of antibacterial active substances are rarely reported. There is still great potential for the development of biocontrol fungi and phages. In a word, resources, action mechanism and field application of biocontrol microorganisms for the control of citrus canker disease need to be further studied.

Sauce-flavor liquor represented by the famous Moutai, Kweichou is one of the traditional Chinese liquors, which belongs to Daqu liquor. With the continuous development of science and technology, the types of microorganisms and the substances that produced unique flavor in brewing process of sauce-flavor liquor were gradually revealed. As an important kind of microorganisms in Daqu, the bacteria could produce proteases and flavor substances, which played an extremely important role in the quality and flavor of liquor. This paper systematically reviewed the latest research progress of bacterial diversity and proteases in sauce-flavor liquor Daqu, and put forward the prospect of the future research of microorganisms related to sauce-flavor liquor.

As an important part of municipal solid waste, the outputof food wasteis increasing with the acceleration of urbanization in China. Meanwhile, the construction and upgrading of sewage treatment plants have increased the production of excess sludge. Therefore, the effective treatment of food waste and excess sludge has attracted extensive attention. Firstly, the effects and mechanisms of inhibitory substances such as lipid, ammonia, salt, capsaicin, microplastic and antibiotics on the stability of the anaerobic co-digestion of food waste and excess sludge were expounded. Secondly, it was proposed that the inhibitory substances could be removed by physical, chemical and biological pretreatment methods, and the appropriate amount of biochar, zero-valent iron and other strengthening substances should be added to improve the efficiency and stability of anaerobic co-digestion. The coupling technology combining microbial fuel cell, microbial electrolysis carbon capture, pyrolysis, microalgae with anaerobic co-digestion technology in the treatment of food waste and excess sludge was summarized. The purpose is to reduce the carbon emission in the treatment process of food waste and excess sludge, and finally realize the green and low-carbon treatment.

Automatically generating a human-like description for a given image is one of the most important tasks in artificial intelligence. Most of the existing attention-based methods explore the mapping relationships between words in sentence and regions in image. However, the quality of generated captions can be reduced by such unpredictable matching manner which sometimes cause inharmonious alignments. To solve this problem, a new method which uses word attention to improve the correctness of visual attention when generating word-by-word sequential descriptions is proposed. The special word attention emphasizes word importance when focusing on different regions of the input image, and makes full use of the internal annotation knowledge to assist the calculation of visual attention. Furthermore, in order to reveal implied information that cannot be expressed straightforwardly by machines and generate more novel and natural captions, the external knowledge which is extracted from the knowledge graphs is injected to the encoder-decoder framework. Finally, The new method is validated on two available captioning benchmarks i.e. Microsoft COCO dataset and Flickr30k dataset. The experimental results demonstrate that this new approach can achieve a good performance and outperform many of the state-of-the-art approaches.

Based on the Lorenz system, a new six-dimensional hyperchaotic system with four positive Lyapunov exponents is found with only one hyperbolic equilibrium point by using coupling techniques and linear feedback control in this paper. Meanwhile, the system has three positive Lyapunov exponents for infinitely many equilibrium lines. The stability of the hyperbolic equilibrium point is analyzed by using Routh-Hurwitz criterion, and the existence of Hopf bifurcation is proved. Using computer simulation techniques such as phase diagram, Lyapunov exponential spectrum, Poincaré map, and bifurcation diagram, the complex dynamic evolution process of the six-dimensional hyperchaotic system from periodic, quasi-periodic, chaotic to hyperchaotic is analyzed numerically.

Photocatalytic water splitting is an ideal way to utilize solar energy. In order to popularize photocatalytic water splitting on a large scale, the current problem to be solved is to prepare a low-cost photocatalyst without noble metals. An efficient and stable photocatalytic system based on CdS nanorods for photocatalytic water splitting was successfully constructed by combining P element doping with in-situ photodeposition of MoS₂ cocatalyst. The prepared CdS/P/MoS₂ system showed stronger photocatalytic activity and stability than the unmodified CdS. The photocatalytic hydrogen production rate of CdS/P/MoS₂ in distilled water reached 692.9 μmol/(g·h), and its apparent quantum efficiency (AQE) at 420 nm was 0.31%.