To enhance the sensitivity of fluorescence probes for the detection of Zn²⁺, this study introduces an OFF-ON Zn²⁺ detection strategy. This approach utilizes a dual quenching mechanism involving fluorescein ring closure-opening and (E)-4-((4-(dimethylamino) phenyl) diazenyl) benzoic acid (DABCYL) as a dual quencher. The primary objective is to address the issue of high background fluorescence associated with bis (pyridin-2-ylmethyl) amine (DPA) based Zn²⁺ recognition groups in various fluorescence probes. The Zn²⁺ fluorescence probe 4',5'-bis((bis(pyridin-2-ylmethyl)amino)methyl)-2', 7'-dichloro-3'-hydroxy-3-oxo-3H-spiro [isobenzofuran-1,9'-xanthen]-6'-yl (E)-4-((4-(dimethylamino) phenyl) diazenyl) benzoate (FL-ZJ) was synthesized using a fluorescein precursor molecule, with DPA serving as the recognition group and DABCYL functioning as the dual quencher. The fluorescence response of FL-ZJ to Zn²⁺ was investigated through fluorescence spectroscopy. Results indicated that FL-ZJ exhibited minimal fluorescence activity at 526 nm in the absence of Zn²⁺. Upon introduction of Zn²⁺, the fluorescence intensity at 526 nm increased to approximately 17.4-fold, accompanied by a color change from colorless to yellow. The detection limit for Zn²⁺ using this probe was determined to be 14.6 nmol/L. Further analysis via Job's Plot experiments and high-performance liquid chromatography revealed that coordination-induced ring opening of the fluorescein moiety and intramolecular elimination of the quenching group facilitated the selective detection of Zn²⁺.

In order to analyze and evaluate the uncertainty of determination of famoxadone pesticide residues in grape by UPLC-tandem mass spectrometry, the pesticide famoxadone was selected to evaluate the measurement uncertainty of the methods from six aspects including sample weigh, standard solution preparation and standard curve fitting, etc., with "National food safety standard-Determination of 331 pesticides and metabolites residues in foods of plant origin-Liquid chromatography-tandem mass sprctrometry method" (GB 23200.121-2021) and "Determination of 450 pesticides and related chemicals residues in fruits and vegetables-LC-MS-MS method" (GB/T 20769-2008) standard methods as the research objects. The results showed that the relative extended uncertainty of famoxadone pesticide residue was about 0.22% (k=2), in which the main uncertainties were derived from the use of UPLC-tandem mass spectrometer, standard solution preparation, standard curve fitting and standard recovery rate. In order to reduce the uncertainty of test results, in actual work, we need to improve the stability of equipment, optimize the preparation process of standard solution and improve the operating skills of test personnel. At the same time, we should also take the results of uncertainty as an important reference to judge whether the limit threshold data meets the requirements of the limit standard.

Changes in the composition and diversity of plant communities during vegetation restoration in reclaimed areas can enhance our understanding on the evolutionary processes and patterns of plant communities. Four planted forests, Populus simonii, Pinus tabuliformis, Ulmus pumila and Robinia pseudoacacia in a typical coal mine reclamation area in Pingshuo, Shanxi, were selected to analyze the composition and species diversity of the understory herbaceous community and to investigate the influence of soil and stand on the herbaceous layer of the plant community. The aim of the present study was to provide basis information for species selection in the later stage of mining area reclamation. The results showed that: (1) there were 25 families, 49 genera and 59 species of understory herbaceous plants, among which the A. Bercht has the most species, followed by the F. Lindl and P. Barnhart, and the life type is mainly perennial herbs. The dominant species of plants are mainly woodland P. nemoralis, M. sativa and S. chamaejasme. (2) The herbaceous diversity of the P. tabuliformis showed a trend of increasing and then decreasing during vegetation recovering, while the opposite trend was observed in the U. pumila, and no obvious trends were observed in the P. simonii and R. pseudoacacia communities. (3) Soil organic matter and total nitrogen increased significantly (P < 0.05), soil bulk density decreased significantly (P < 0.05), and total phosphorus increased significantly (P > 0.05), except for R. pseudoacacia, while soil water content did not change significantly (P > 0.05). (4) Soil physical and chemical properties and highly significant effects on herbaceous community composition (P < 0.01). The study reveals the successional characteristics of herbaceous communities under different plantation forests in the Pingshuo coal mining reclamation area, which can provide a scientific basis for the ecological restoration in this area.

The genome of Deinococcus sp. RM strain and its transcriptome in the process of chicken feather degradation were sequenced, the protease gene with high expression was selected and recombined in Pichia pastoris GS115 strain for induction expression. The purification, enzymatic properties and the effects of chicken feather degradation of the recombinant protease were determined. The results showed that RM strain had 4 132 genes and 3 844 genes expressed, of which 444 genes expressed extracellular proteins and 26 were extracellular proteases. The high expression gene sp02200 was successfully expressed in the P. pastoris GS115 strain. The recombinant protease rSp02200 belonged to a novel DegQ protease of high-temperature requirement family, with an optimal reaction temperature of 37 ℃, and remained good stability below 30 ℃. The optimal pH was 7.5, and maintained more than 70% protease activity at pH 4.0-11.0. The protease can degrade long and thick feather axes and branches into small feather axes and branches. Therefore, Sp02200 protease was an important protease in the chicken feather degradation process of RM strain, which provides a reference for exploring related genes involved in feather degradation of RM strain.

In this paper, we used MATLAB (MATrix LABoratory) to simulate the interference patterns of two fractional-order vortex beams (Laguerre-Gaussian beams) with opposite topological charges (l), as well as the interference patterns of two unequal vortex beams (Laguerre-Gaussian beams) with different topological charges, in which the radial indices (p) are arbitrary non-negative integers. Through theoretical analysis, we found that as the topological charges and radial indices of the beams change, the interference patterns of the Laguerre-Gaussian beams change accordingly. The number of spots in the interference pattern of the equal-heterodyne fractional-order Laguerre-Gaussian beam is \mathrm{2} \left|l\right|, and the number of spot layers is p+1; the interference result of the non-equal-heterodyne Laguerre-Gaussian beam is similar to that of the equal-heterodyne Laguerre-Gaussian beam. In the interference pattern of non-equal same-sign Laguerre-Gaussian beams, when the absolute value of the difference in topological charges is small, the number of bright spots is \left|l_{\mathrm{2}}\right| - \left|l_{\mathrm{1}}\right|. When this absolute value is large, a pattern of alternating bright and dark concentric rings appears. Our work may provide a new method for measuring the topological charges and radial indices of vortex beams.

A matching pursuit algorithm for regularization backtracking based on QR decomposition (QR-RBMP) is proposed in this paper to solve the problems of low precision of directional of arrival (DOA) estimation in the cases of low signal noise ratio (SNR), small snapshot and coherent signals. Firstly, the algorithm is performed on sensing matrix by QR decomposition to increase the independence of the sensing matrix. Then, the regularization idea and backtracking mechanism are used to optimize matching pursuit algorithm to improve the signal reconstruction precision. The regularization idea carries out secondary screening on the atoms initially selected by the matching tracking algorithm, and selects the most relevant atoms with the largest energy. The backtracking idea carries out secondary screening on the atoms selected by the regularization, deletes the incorrect atoms, improves the correctness of the selected atoms, and thus improves the reconstruction accuracy of the matching tracking algorithm. Finally, we obtain the reconstructed signal. The position of the non-zero element of the signal is the result of DOA estimation. Through a series of simulation experiments, the proposed algorithm is compared with MUSIC algorithm, regularized orthogonal matching pursuit algorithm (ROMP), subspace tracking algorithm, SP algorithm without Square Root (ISP) and energy sorting based backtracking regularized matching pursuit algorithm (ESBRMP) based on RMSE and POR. The results show that the proposed algorithm reduces the RMSE by 42% and improves the POR by 8% compared with the existing optimal methods under the same conditions.

The transverse momentum spectra of charm-strange meson D_S ^± by model research in Au + Au collisions at 200 GeV is studied. The non-extensive Tsallis statistic model, Blast-wave model and Tsallis Blast-wave model are applied to analyze the particle distributions in various centrality bins. They are compared with the STAR experiment results. The appropriate range of the transverse momentum and the kinetic freeze-out parameters in each model are studied. The non-extensive parameter q and the kinetic freeze-out temperature rise with the centrality percentage. The mean radial flow decreases with the centrality percentage. Fireballs produced in central collisions survive longer and have a longer evolution time than those produced in peripheral collisions. Compared with the light hadrons, D_S ^± freeze out earlier and has smaller radial velocity and higher kinetic freeze-out temperature. Particles are created in earlier stage due to the larger mass and carry the information of Quark-Gluon Plasma （QGP). These freeze-out properties can help us to better understand the evolution of the matter in high-energy nucleus collisions.

In order to study the development of the reproductive system of the "pre-pupa" and "pupa" of Didesmococcus koreanus Borchsenius, the morphological characteristics during the process from the 2nd instar nymphs to male adults were observed under the microscope (Olympus). The results showed that: the prepupal duration is 2-4 days, and the pupal duration is 4-6 days; The male reproductive system is composed of a pair of testis (T), a pair of vas deferens (vd), ejaculatory sac (es), ejaculatory duct (ej), and a pair of mesadenia (me). At different stages of development, the morphological structure of the male reproductive system of the D. koreanus was observed a series of changes. At the end of the 2nd instar nymphs, the apex of the T is enlarged and full of white content. In prepupal stage, the base of the T became thicker, the contents showed light and dark stripes, and the length of the vd and ej increased. The stripes in the T of the pupal stage disappear and the contents are gel-like. The T of the male adult became distorted, with a pointed end and enlarged base. The es of the male adult was enlarged and filled with white gelatinous spermatozoa.

Person aspect term extraction aims to extract various attributes of individuals such as gender and nationality from their descriptions. Existing extraction methods typically train sequence labeling models on distantly-supervised data to obtain the extraction model. However, this approach has issues with inaccurate annotations and overlapping different attribute values in the data, and lacks scalability and generalizability in their models. To solve the problems, this article proposes to transform this task into a machine reading comprehension (MRC) problem, that is, to fill in the person attribute-value table by reading the person profile. This paper constructs a person attribute recognition data based on the reading comprehension framework from the person encyclopedia, and constructs two baseline models of bidirectional encoder representations from transformers-machine reading comprehension (BERT-MRC) and bidirectional encoder representations from transformers-conditional random field-machine reading comprehension (BERT-CRF-MRC). Among them, BERT-CRF-MRC is three percentage points higher than BERT-MRC on average in F1 score and the experimental results of BERT-CRF-MRC are about 92% F1 average in short text person profiles while about 75% in long text person profiles. The constructed data and code are exposed on Github.

In this paper, the existence of traveling wave solutions of mixed diffusive competition systems with spatio-temporal delays was studied. Firstly, in order to eliminate the influence of spatio-temporal delays, the delayed diffusion system with two equations was changed into the non-delay diffusion system with four equations based on the property of the kernels in spatio-temporal delays. Then the system was further changed into the monotone system. Finally, the main results were obtained by using the super- and sub-solutions method and the fixed point theorem.

Based on fractional Schrödinger equation with variable coefficient, the transmission characteristics of symmetric Pearcey pulse are studied. When the variable coefficient is not considered, it is found that under the action of Lévy index, the symmetric Pearcey pulse splits into two pulses of equal intensity. Especially, when Lévy index equals one, the two Pearcey pulses can maintain the stable transmission over a long distance. When the variable coefficient is considered, under the action of periodic modulation, the symmetric pulse is periodically focused during transmission. The pulse is reshaped at the focal point and the intensity remains basically unchanged. Secondly, the influence of Lévy index and chirp parameter on the transmission characteristics of Pearcey pulse is discussed. The results show that the pulse intensity at the focal point can be controlled by Lévy index and the chirp parameter. The larger the Lévy index, the greater the intensity at the focus. Similarly, the larger the absolute value of the chirp, the greater the intensity at the focus. In addition, the influence of different parameters on the Pearcey pulse interaction is also studied. The change of the pulse spacing and phase, pulse intensity at the focus will also change accordingly.

To address the issue of insufficient feature information extraction caused by neural network architecture in current encrypted traffic recognition research, this paper proposes a multi-feature fusion encrypted traffic recognition method based on attention mechanism. The proposed method focuses on the hierarchical structure characteristics of encrypted traffic and designs two parallel network branches for feature extraction. Branch one uses residual neural network(ResNet) to extract the original features of traffic, while branch two uses an Inception-CNN composed of irregular-sized convolution kernels to extract statistical features of traffic for characterization and compensate for the information loss caused by traffic cropping. In addition, this paper converts the statistical features from the existing grayscale image to the RGBA image format as input to help the model more effectively extract features. The features extracted by the two branches are merged into a new feature vector and input into the channel attention module for weighting to enhance the representation ability of traffic features. The experimental results show that the proposed model performs better than existing typical encrypted traffic classification methods, with significantly improved accuracy, recall rate, and F1-score, among which the comprehensive performance metric F1-score is increased by an average of 6% compared to existing methods.

This article investigates the dynamic response of a viscoelastic shape memory alloy (SMA) spring oscillator system under narrow-band noise excitation. According to the constitutive relation of SMA polynomial, viscoelastic medium is introduced to describe spring damping, and the stochastic SMA dynamic equation is established. By using the method of combining Lindstedt-Poincaré and multi-scale, we get the amplitude-frequency response and steady-state moment equation of the system, and discuss the influence of viscoelastic parameters and noise intensity on the amplitude-frequency response and steady-state moment. The results show that the viscoelastic term can affect the nonlinear stiffness and structural damping of the system. Both noise intensity and viscoelastic parameters can induce random transition in the system. These results provide a theoretical reference for the stability of viscoelastic SMA composite structures.

We study the dynamical evolution of a two-component Bose-Einstein condensate under a periodic gradient magnetic field. The research methods include analytical analysis in linear regime and numerical simulations in nonlinear regime. In linear regime, the system's wave function, evolving over time, can be analytically solved by applying the rotating wave approximation. The results reveal that the atoms of the two components in the condensate undergo Rabi oscillations under the influence of the magnetic field. By adjusting the gradient and period of the periodic gradient magnetic field, the amplitude and period of the Rabi oscillations can be easily controlled. In the nonlinear regime, we numerically solve the Gross-Pitaevskii equation and find that the results are similar to the linear case when the nonlinearity is weak. However, as the nonlinearity coefficient increases, the resonant points of the system shift, and the proportion of ground state atoms transferred to the excited state gradually decreases. The focus of this study is to, under resonant conditions, transfer ground-state atoms to the excited state through Rabi oscillations. This paves the way for further investigation into the dynamical characteristics of the excited state.

A pH-responsive host-guest recognition system based on the morphine group modified pillar[5]arene host (H1) and the organic amine salt guest molecule G1 was constructed. Under neutral conditions, H1 and G1 formed a [2]pseudorotaxane after host-guest complexation. This host-guest system displayed dual-pH responsive property; under acidic conditions, H1 was protonated and converted into H2, resulting in the disassociation with G1; under basic conditions, G1 was transformed into G2, leading to the disassociation of the host-guest complex. Based on this host-guest system, we have successfully constructed a molecular logic gate system in which different combinations of host-guest complexes, acids and bases acted as input and outputted different information.

Considering the influence of the viral load in the host and limited medical resources on the transmission of infectious diseases, a multi-scale infectious disease model with saturated treatment rate coupling within-host and between-host dynamics is proposed. Firstly, for the between-host disease transmission model, the basic reproduction number is obtained, and a criterion describing the existence and stability of the disease-free and endemic equilibrium for the coupled model is given. Particularly, when the basic reproduction number is less than 1, the model has two endemic equilibria, one of which is locally asymptotically stable and the other is unstable. When the basic reproduction number is greater than 1, the model has a unique endemic equilibrium, which is global asymptotically stable under specific conditions. In addition, The existence of forward/backward bifurcation caused by limited medical resources is analyzed. This means that the elimination or prevalence of the disease no longer depends on the basic reproduction number but is closely related to the initial state of infected humans and the supply of medical resources. Finally, the main theoretical results of this paper are explained by numerical simulation.

In the context of global aging, the health problems of the elderly have gradually become prominent, and cognitive stimulation dialogue is an important means to maintain the cognitive health of the elderly. Previous researchers constructed a Chinese cognitive stimulation dialogue dataset (CSConv) that includes emotional support, thereby initiating research in the field of Chinese cognitive stimulation dialogue. However, the authors did not fully model the logical reasoning relationships within cognitive stimulation dialogues and did not effectively utilize the guiding role of strategy labels during dialogue generation. This study regards cognitive stimulation dialogue generation as a multi-task integration thinking and reasoning process, and models the logical relationship among emotion classification tasks, decision-making tasks and dialogue response generation tasks as a reasoning process to guide the generation of large language models. For decision-making tasks, this paper proposes a decision-making model with a hierarchical encoder structure. The results of the decision-making experiment show that the decision-making model improves the accuracy of the cognitive stimulation therapy principles and emotional support strategies decision-making tasks by 3.96% and 2.1%, respectively. For multi-task logical thinking and reasoning process, this paper proposes a multi-task integration method to combine the models corresponding to the three tasks. The experimental results show that the multi-task integration method has improved BLEU-4 by 7.95% compared with the previous baseline, indicating that the dialogue response ability has been improved, proving the effectiveness and advancement of this method.

In this paper, we report that pyrene-containing imine covalent organic framework material (Py-COF) supported Pd nanoparticles exhibit significantly high activity in the hydrogenation of quinoline to 1,2,3,4-tetrahydroquinoline, with a turnover frequency (TOF) value 2.1 times that of commercial Pd/C. Through techniques such as high-resolution electron microscopy, X-ray photoelectron spectroscopy, cyclic voltammetry of CO stripping, and control experiments, we have identified that the heightened activity of the Pd/Py-COF catalyst in quinoline hydrogenation stems from the electron-rich Pd surface, which facilitates substrate adsorption/desorption, and the weak interactions between quinoline and Py-COF. Furthermore, Pd/Py-COF demonstrates excellent recyclability and superior catalytic performance in the hydrogenation of various quinoline derivatives. This work underscores the significance of utilizing COFs to regulate the catalytic performance of metal catalysts.

Edge computing structures are more complex than traditional cloud computing, so data integrity issues become even more important. In order to solve the problems of poor privacy protection ability, high computing and storage overhead, high system complexity, and lack of support for dynamic operation in the current integrity audit schemes, this paper proposes an integrity audit scheme based on dynamic chameleon authentication tree. In the data encryption stage, the scheme introduces a certificateless public key cryptography system to generate a data encryption and decoding key at the user end to ensure the integrity and confidentiality of the data in the process of system transmission; in the data upload stage, the dynamic chameleon authentication tree storage structure is adopted to ensure the full dynamic operation of the data access process and reduce the communication computing overhead; and the computing power of the edge node is used to carry out integrity audit, which avoids the problem of single point failure caused by the third-party audit agency. Under the stochastic oracle model, the confidentiality of the scheme is proved based on the computational DH difficulty problem and the discrete logarithmic difficulty problem. The experiments show that compared with other integrity audit schemes, the proposed scheme has better computing efficiency and can save about 50% of computing and storage overhead.

This paper embarks on an extensive exploration of the challenges inherent in traditional three-way decision-making methodologies. First, these conventional approaches necessitate precise subjective threshold definitions, rendering them less adaptable across diverse scenarios. Second, their interpretability in information fusion is often lacking, resulting in ambiguous decision criteria. To address these issues, this paper introduces a novel approach that leverages complex fuzzy sets to establish an adjustable multi-granularity complex fuzzy information system. It integrates decision-based three-way decision techniques to derive classification thresholds objectively, yielding an adjustable multi-granularity complex fuzzy probabilistic rough set. Furthermore, the paper acknowledges the constraints of bounded rationality that decision-makers encounter in real-world scenarios. Within the framework of behavioral decision theory, this work provides a more comprehensive depiction of how psychological factors influence decision outcomes. In essence, this paper proposes a multi-granularity three-way decision model grounded in complex fuzzy sets and regret theory, designed to tackle complex multi-attribute group decision-making problems. To validate the model's effectiveness in addressing decision challenges related to decision risk and bounded rationality within a complex fuzzy environment, the paper conducts an in-depth experimental analysis using a shared bicycle rental dataset. The results underscore the model's feasibility and efficacy, particularly in enhancing fault tolerance and leveraging expert experience.