The twisted Wang transform distribution family, defined as the composition of parameter shifted inverse CDF function with an original CDF function, is found to be most suitable for matching low shape factor distributions, characterizing hard to fit or to simulate reinsurance portfolio losses for some perils from our previous study. Among them, the best form for matching a hard-to-fit empirical loss distribution for a specific peril, is the Exponential Fractional Extra Power 0 Distribution in (0,1) with CDF:.The simplest yet still a good form of this family is the Transformed Hyperbolic Tangent Distribution with CDF:,which has analytical formulas for the moments. The twisted Wang transform distribution family is compared and confirmed to be superior to all other well-known distribution families through extensive numerical optimization practice, distribution forms guesses, and computer-aided exploration experiments.

We suppose that vacuum is filled with a kind of continuously distributed matter which may be called the $\Omega(1)$ substratum, or the electromagnetic aether. Suppose that the time scale of a macroscopic observer is very large compares to the the Maxwelllian relaxation time of the $\Omega(1)$ substratum. Thus, the macroscopic observer concludes that the $\Omega(1)$ substratum behaves like a Newtonian-fluid. Inspired by H. A. Lorentz, we speculate that electric charges may be extremely small hard spherical sources or spherical sinks with finite radii. Based on the spherical source and spherical sink model of electric charges, we derive Coulomb's law of interactions between static electric charges in vacuum. Further, we derive a reduced form of the Lorentz's force law for static electric charges in vacuum.

The speech-to-song illusion is a type of auditory illusion that the repetition of a part of a sentence would change people’s perception tendency from speech-like to song-like. The study aims to examine how pace, emotion, and language tonality affect people’s experience of the speech-to-song illusion. It uses a between-subject (Pace: fast, normal, vs. slow) and within-subject (Emotion: positive, negative, vs. neutral; language tonality: tonal language vs. non-tonal language) design. Sixty Hong Kong college students were randomly assigned to one of the three conditions characterized by pace. They listened to 12 audio stimuli, each with repetitions of a short excerpt, and rated their subjective perception of the presented phrase, whether it sounded like a speech or a song, on a five-point Likert-scale. Paired-sample t-tests and repeated measures ANOVAs were used to analyze the data. The findings reveal that a faster speech pace could strengthen the tendency of the speech-to-song illusion. Neither emotion nor language tonality show a statistically significant influence on the speech-to-song illusion. This study suggests that the perception of sound should be in a continuum and facilitates the understanding of song production in which speech can turn into music by having repetitive phrases and to be played in a relatively fast pace.

We suppose that a Cooper pair (CP) will experience a damping force exerted by the condensed matter. A Langevin equation of a CP in two dimensional condensed matter is established. Following a method similar to Nelson's stochastic mechanics, generalized Schr\"{o}dinger equation of a CP in condensed matter is derived. If the CPs move with a constant velocity, then the corresponding direct current (DC) electrical conductivity can be calculated. Therefore, a Drude like formula of resistivity of CPs is derived. We suppose that the damping coefficient of CPs in two dimensional cuprate superconductors is a linear function of temperature. Then the resistivity and scattering rate of CPs turn out to be also linear-in-temperature. The origin of linear-in-temperature resistivity and Planckian dissipation in cuprate superconductors may be the linear temperature dependence of the damping coefficient of CPs.

J. C. Maxwell, B. Riemann and H. Poincar$\acute{e}$ have proposed the idea that all microscopic particles are sink flows in a fluidic aether. Following this research program, a previous theory of gravitation based on a mechanical model of vacuum and a sink flow model of particles is generalized by methods of special relativistic continuum mechanics. In inertial reference frames, we construct a tensorial potential which satisfies the wave equation. Inspired by the equation of motion of a test particle, a definition of a metric tensor of a Riemannian spacetime is introduced. Applying Fock's theorem, generalized Einstein's equations in inertial systems are derived based on some assumptions. These equations reduce to Einstein's equations in case of weak field in harmonic reference frames. There exist some differences between this theory and Einstein's theory of general relativity.

Inspired by Dirac's large number hypothesis (LNH), Zeldovich proposed a relation between the cosmological constant (CC), the mass of a proton, the Planck constant and Newton's gravitational constant. Zeldovich's formula suggests that the substance which is responsible for CC may interact with elementary particles. Since Newton's gravitational constant and the Planck constant appear in Zeldovich's formula, these interactions may be related to gravitational phenomena and quantum phenomena. Following this clue, we propose a liquid droplet model of electron. Applying the Laplace's equation, Zeldovich's formula of CC is derived. Weinberg proposes a relation between the mass of a pion, the Planck constant, the Hubble constant, Newton's gravitational constant and the velocity of light in vacuum when discussing cosmological models with a varying constant of gravitation. Weinberg pointed out that this relation may not merely be regarded as a meaningless random combinations of these fundamental constants in physics. The Weinberg's relation is derived based on the critical mass density formula in the Friedmann model of the universe and Zeldovich's formula.

herein, we have compared the performance of SVM and MLP in emotion recognition using speech and song channels of the RAVDESS dataset. We have undertaken a journey to extract various audio features, identify optimal scaling strategy and hyperparameter for our models. To increase sample size, we have performed audio data augmentation and addressed data imbalance using SMOTE. Our data indicate that optimised SVM outperforms MLP with an accuracy of 82 compared to 75%. Following data augmentation, the performance of both algorithms was identical at ~79%, however, overfitting was evident for the SVM. Our final exploration indicated that the performance of both SVM and MLP were similar in which both resulted in lower accuracy for the speech channel compared to the song channel. Our findings suggest that both SVM and MLP are powerful classifiers for emotion recognition in a vocal-dependent manner.

Lord Kelvin believed that the electromagnetic aether must also generate gravity. Presently, we have no methods to determine the density of the electromagnetic aether, or we say the $\Omega(1)$ substratum. Thus, we also suppose that vacuum is filled with another kind of continuously distributed substance, which may be called the $\Omega(2)$ substratum. Based on a theorem of V. Fock on the mass tensor of a fluid, the contravariant energy-momentum tensors of the $\Omega(1)$ and $\Omega(2)$ substrata are established. Quasi-static solutions of the gravitational field equations in vacuum are obtained. Based on an assumption, relationships between the contravariant energy-momentum tensors of the $\Omega(1)$ and $\Omega(2)$ substrata and the contravariant metric tensor are obtained. Thus, the cosmological constant is calculated theoretically. The $\Omega(1)$ and $\Omega(2)$ substrata may be a possible candidate of the dark energy. According to the theory of vacuum mechanics, only those energy-momentum tensors of discrete or continuously distributed sinks in the $\Omega(0)$ substratum are permitted to act as the source terms in the generalized Einstein's equations. Thus, the zero-point energy of electromagnetic fields is not qualified for a source term in the generalized Einstein's equations. Some people believed that all kinds of energies should act as source terms in the Einstein's equations. It may be this unwarranted belief that leads to the cosmological constant problem. The mass density of the $\Omega(1)$ and $\Omega(2)$ substrata is equivalent to that of around $3$ protons contained in a box with a volume of $1$ cubic metre.

When solving the Einstein's equations for an isolated system of masses, V. Fock introduces harmonic reference frame and obtains an unambiguous solution. Further, he concludes that there exists a harmonic reference frame which is determined uniquely apart from a Lorentz transformation if suitable supplementary conditions are imposed. It is known that wave equations keep the same form under Lorentz transformations. Thus, we speculate that Fock's special harmonic reference frames may have provided us a clue to derive the Einstein's equations in some special class of non-inertial reference frames. Following this clue, generalized Einstein's equations in some special non-inertial reference frames are derived based on the theory of vacuum mechanics. If the field is weak and the reference frame is quasi-inertial, these generalized Einstein's equations reduce to Einstein's equations. Thus, this theory may also explain all the experiments which support the theory of general relativity. There exist some differences between this theory and the theory of general relativity.

The airborne and satellite-based synthetic aperture radar enables the acquisition of high-resolution SAR oceanographic images in which even the outlines of ships can be identified. The detection of ship targets from SAR images has a wide range of applications, such as the military, where the dynamic grasp of enemy targets can help improve the early warning capability of naval defence, and the civilian detection of illegal fishing vessels can help improve the level of maritime management. Due to the density of ships in SAR images, the extreme imbalance between foreground and background clutter, and the diversity of target sizes, achieving lightweight and highly accurate multi-scale ship target detection remains a great challenge. To this end, this paper proposes an attention mechanism for multiscale receptive fields convolution block (AMMRF). AMMRF not only makes full use of the location information of the feature map to accurately capture the regions in the feature map that are useful for detection results, but also effectively captures the relationship between the feature map channels, so as to better learn the relationship between the ship and the background. Based on this, a new YOLOv7-based ship target detection method, You Only Look Once SAR Ship Identification (YOLO-SARSI), is proposed, which acquires the abstract semantic information extracted from the high-level convolution while retaining the detailed semantic information extracted from the low-level convolution. Compared to the deep learning detection methods proposed by previous authors, our model is more lightweight, only 18.43M. We examined the effectiveness of our method on two SAR image public datasets: the High-Resolution SAR Images Dataset (HRSID) and the Large-Scale SAR Ship Detection Dataset-v1.0 (LS-SSDD-V1.0). The results show that the average accuracy AP50 of the detection method YOLO-SARSI proposed in this paper on the HRSID and LS-SSDD-V1.0 datasets is 4.9% and 5% higher than that of YOLOv7, respectively.

Distributed/semi-distributed models are considered to be sensitive to the spatial resolution of the data input. In this paper, we take a small catchment in high urbanized Yangtze River Delta, Qinhuai catchment as study area, to analyze the impact of spatial resolution of precipitation and the potential evapotranspiration (PET) on the long-term runoff and flood runoff process. The data source includes the TRMM precipitation data, FEWS download PET data, and the interpolated metrological station data. GIS/RS technique was used to collect and pre-process the geographical, precipitation and PET series, which were then served as the input of CREST (Coupled Routing and Excess Storage) model to simulate the runoff process. The results clearly showed that, the CREST model is applicable to the Qinhuai catchment; the spatial resolution of precipitation had strong influence on the modelled runoff results and the metrological precipitation data cannot be substituted by the TRMM data in small catchment; the CREST model was not sensitive to the spatial resolution of the PET data, while the estimation fourmula of the PET data was correlated with the model quality. This paper focused on the small urbanized catchment, suggesting the influential explanatory variables for the model performance, and providing reliable reference for the study in similar area.

An energy model that correlates fan airflow, head, speed, and system power input is essential to detect device faults and optimize control strategies in fan systems. Since the application of variable frequency drives (VFDs) makes the motor efficiency data published by manufacturers inapplicable, the fan efficiency and drive (belt-motor-VFD) efficiency must be identified for each individual system to obtain accurate energy models. The objectives of this paper are to identify an energy model of existing VFD-motor-fan systems using available experimental data and demonstrate its applications in loose belt fault detection and virtual airflow meter development for optimal control. First, an approach is developed to identify the fan head, fan efficiency and drive efficiency curves using available fan head, speed, and system power input as well as temporarily measured airflow rate without measuring shaft power. Then the energy model is identified for an existing VFD-motor-fan system. Finally, the identified model is applied to detect the slipped belt faults and develop the virtual airflow meter. The experiment results reveal that the developed approach can effectively obtain the energy model of VFD-motor-fan systems and the model can be applied to effectively detect slipped belt faults and accurately calculate the fan airflow rate.

Recently deep cross-modal hashing networks have received increasing interests due to its superior query efficiency and low storage cost. However, most of existing methods concentrate less on hash representations learning part, which means the semantic information of data cannot be fully used. Furthermore, they may neglect the high-ranking relevance and consistency of hash codes. To solve these problems, we propose a Self-Attention and Adversary Guided Hashing Network (SAAGHN). Specifically, it employs self-attention mechanism in hash representations learning part to extract rich semantic relevance information. Meanwhile, in order to keep invariability of hash codes, adversarial learning is adopted in the hash codes learning part. In addition, to generate higher-ranking hash codes and avoid local minima early, a new batch semi-hard cosine triplet loss and a cosine quantization loss are proposed. Extensive experiments on two benchmark datasets have shown that SAAGHN outperforms other baselines and achieves the state-of-the-art performance.

Permanent magnet brushless DC motor (BLDCM) is usually controlled by six step commutation method, and flux-weakening method is used to make the motor run higher above the base speed. For now, it is considered that the weak magneto-electric angle range is 0-pi/3, and that of deep weakening is pi/3-pi/2. In the field- weakening control, the forward shift of commutation point will form inverter circulating current in the three-phase bridge of inverter and the stator winding of the motor. In this paper, the principle of inverter circulating current formed by inverter is analyzed. Through magnetic potential analysis and Simulink simulation, it is concluded that flux-weakening control will generate inverter circulating current in the inverter and motor stator winding. The inverter circulating current affects the magnetic potential of motor, and magnetic potential will move to the rotating direction of motor rotor. When the forward shift angle of inverter commutation point is 0-pi/6 electrical angle, the movement amplitude of current circulating current of inverter is less than pi/6, which plays the role of weakening magnetic field and driving effect; when the forward moving angle is pi/6-pi/3, the movement amplitude of inverter circulating current exceeds pi/6, which plays the role of magnetic weakening and braking. When the braking effect occurs, the reverse torque will appear, resulting in the decrease of motor torque and efficiency. Therefore, the range of weak magneto-electric angle should be between 0-pi/6.

For the task planning problem of the command and control architecture, the existing algorithms have problems such as low efficiency and poor re-planning quality under abnormal conditions. Based on the requirements of the current accusation architecture, this paper constructs a distributed command and control architecture model based on multi-agents, which makes use of the superiority of multi-agents in dealing with complex tasks. The concept of MultiAgents-HTN is proposed under the framework. The original hierarchical task network planning algorithm is optimized, the multi-agent collaboration framework is redefined, and the coordination mechanism of local conflict is designed. Taking the classical resource scheduling problem as the experimental background, the comparison between the proposed algorithm and the classical HTN algorithm is carried out. The experimental results show that the proposed algorithm has higher quality and higher efficiency than the existing algorithm, and the space anomaly is heavy during processing. The planning is more efficient, and the time is more complicated and superior in dealing with the same problem, with good convergence and adaptability. The conclusion proves that the distributed command and control architecture proposed in this paper has high practicability in related fields and can solve the problem of distributed command and control architecture in multi-agent environment.

Thin-wall heat pipe is an efficient heat transfer component, which has been widely used in the field of heat dissipation of high-power electronic equipment in recent years. In this study, the orange peel morphology defect of thin-wall heat pipes after bending deformation was analyzed both for the macro 3D profile and for the micro-formation mechanism. The results show that after high temperature sintering treatment, the matrix grains of heat pipe are coarsened seriously and formed a strong Goss texture, while a certain annealing twins with the unique Copper orientation are retained. The distribution of Schmid factor value subjected to the uniaxial stress indicate the inhomogeneity of intergranular deformation exist among the annealing twins and matrix grains. The annealing twin exhibit a “hard-oriented” component during the deformation; thus, it plays a role as barrier and hinder the slipping of dislocation. As the strain accumulates, part of the annealing twins may protrude from the surface of heat pipe, forming a large-scale fluctuation of the surface as the so called the “orange peel” morphology. The 3D profile shows the bulged twins mostly perpendicular to the drawing direction, with about 200-300μm in width and 10-20μm in height.

Gliomas, the most prevalent and lethal form of brain cancer, are known to exhibit metabolic alterations that facilitate tumor growth, invasion, and resistance to therapies. Peroxisomes, essential organelles responsible for fatty acid oxidation and reactive oxygen species (ROS) homeostasis, rely on the receptor PEX5 for the import of metabolic enzymes into their matrix. However, the prognostic significance of PEX5 for glioma patients remains unclear. We developed a robust prognosis model based on PEX5-dependent signature. This signature not only serves as a robust prognosis model capable of accurately predicting outcomes for glioma patients but also effectively distinguishes several clinicopathological features, including the grade, isocitrate dehydrogenase (IDH) mutation, and 1p19q codeletion status. Furthermore, we developed a nomogram that integrates the prognostic model with other clinicopathological factors, demonstrating highly accurate performance in estimating patient survival. Patients classified into the high-risk group based on our prognostic model exhibit an immunosuppressive microenvironment. Finally, we validated that the peroxisomal localization of the signature genes depends on PEX5 and demonstrated that PEX5 is required for cell growth, migration and invasion of glioma cells. These findings identify the PEX5-dependent signature as a promising prognostic tool for gliomas.

Under the action of cement hydration heat, construction environment, thermal insulation measures, and pipe cooling system, the mass concrete pile cap produces a complex temperature field inside the structure, which makes it difficult to control the internal surface temperature difference, the maximum adiabatic temperature rise and the surface temperature of the structure. In this paper, the mass concrete pile cap of a super large bridge (the length, width, and height are 26.40m，20.90m, and 5.00m, respectively, and the central pier pile cap is constructed with concrete with a strength of C40) is taken as the research support project. The controlling factors affecting the temperature field of the mass concrete pile cap are found by comparing the temperature monitoring of the pile cap with the calculated value of finite element software simulation analysis. Through the finite element software Midas Civil and Midas FEA, the control factors affecting the temperature field of the main pier cap (concrete mold temperature, concrete surface convection coefficient, ambient temperature, and pipe cooling system parameters, etc.) are numerically analyzed, and the influence law and influence degree of the control factors are found out.

Existing methods for 3D human pose estimation mainly divide the task into two stages. The first stage identifies the 2D coordinates of the human joints in the input image, namely the 2D human joint coordinates. The second stage uses the results from the first stage as input to recover the depth information of human joints from the 2D human joint coordinates to achieve 3D human pose estimation. However, the recognition accuracy of the two-stage method relies heavily on the results of the first stage and includes too many redundant processing steps, which reduces the inference efficiency of the network. To address these issues, we propose the EDD, a fully End-to-end 3D human pose estimation method based on transformer architecture with Dual Decoders. By learning multiple human poses, the model can directly infer all 3D human poses in the image using a pose decoder, and then further optimize the recognition result using a joint decoder based on the kinematic relations between joints. With the attention mechanism, this method can adaptively focus on the most relevant features to the target joint, effectively overcoming the feature misalignment problem in the human pose estimation task and greatly improving the model performance. Any complex post-processing step, such as non-maximum suppression, is eliminated, further improving the efficiency of the model. The results show that the method achieves an accuracy of 87.4% on the MuPoTS-3D dataset, significantly improving the accuracy of end-to-end 3D human pose estimation methods.

Food security is the cornerstone of national security, and exploring the resilience of the grain industry chain is particularly important under the current complex and changing external environment. The study is to evaluate the grain industry chain resilience and identify its influencing factors. Based on the panel data of 30 provinces (cities) in China from 2011 to 2022, this paper adopted Partial Least Squares structural equation modeling method to carry out comprehensive evaluation, applied Dagum Gini coefficient to analyze spatial differences, and used geo-detectors to identify the influencing factors. The results showed that (1) from an overall perspective, the resilience of China's grain industry chain showed an overall upward trend, and each region had been greatly improved; (2) from the perspective of spatial differences, the overall spatial variability of China's grain industry chain is relatively small, and the gap mainly originates from inter-regional differences; (3) from the perspective of influencing factors, the level of grain foreign trade, regional market size and agricultural innovation level were important factors. In order to enhance the resilience of China's grain industry chain, based on the heterogeneous characteristics, the coordinated development of each region should be integrated, and the endogenous power should be given full play to enhance the resilience of the industry chain.

With the rapid advancements in remote sensing technology, the spectral information from hyperspectral remote sensing images has become increasingly rich, facilitating detailed spectral analysis of the Earth's surface objects. However, this abundance of spectral data poses significant challenges in data processing, such as the curse of dimensionality leading to the “Hughes” phenomenon, "strong correlation" due to high resolution, and "non-linear characteristics" caused by varied surface reflectance rates. Therefore, dimensionality reduction of hyperspectral data has become a crucial task. This paper, grounded in manifold theory and manifold learning techniques, and considering the non-linear structures and features in hyperspectral remote sensing data, elucidates the principles and processes of dimensionality reduction in hyperspectral remote sensing images using manifold learning, with a formalized expression of the process. This article introduces spectral information divergence (SID) into the nearest neighbor graph computation of manifold learning algorithms. The principles and computational processes of nearest neighbor graph algorithms based on Euclidean distance (ED), spectral angle mapping (SAM), and SID are studied, and a comparative analysis of the dimensionality reduction effects under these three metrics in hyperspectral data is conducted. Experiments on feature extraction under different metrics were performed using the publicly available Indian Pines hyperspectral dataset. The intrinsic features obtained post-dimensionality reduction were used as inputs for classification algorithms in ground objects classification experiments, with algorithm runtime, overall accuracy, and Kappa coefficient as evaluation metrics for dimensionality reduction quality. The results demonstrate that nearest neighbor graph computation based on SAM and SID outperforms traditional ED methods; SAM-based computation has the lowest time complexity, while SID-based manifold learning yields the highest accuracy in ground objects classification. Thus, manifold learning based on SAM and SID metrics proves to be an effective method for feature extraction in hyperspectral remote sensing data, underscoring the potential of manifold learning techniques in the dimensionality reduction of hyperspectral remote sensing images.

The improvement of agricultural low-carbon efficiency is an important path to promote the realization of the "double carbon" goal in the Yellow River Basin. In the context of rapid urbanization development, it is of great significance to explore whether the promotion of urbanization will affect the agricultural low-carbon efficiency. Based on the panel data of 75 cities in the Yellow River Basin from 2000 to 2020, this paper uses super-DEA model, three-dimensional kernel density model and Markov chain model to measure and analyze the spatio-temporal evolution of agricultural low-carbon efficiency in the Yellow River Basin, on this basis, the panel Tobit model is used to analyze the relationship between urbanization and low-carbon efficiency in agriculture. The results show that: (1) The level of agricultural low-carbon efficiency in the Yellow River Basin is low and has not reached the effective state, showing a slow downward trend in general, among which, the agricultural low-carbon efficiency in the lower reaches is higher than that in the middle reaches, and the upper reaches is the lowest. (2) The agricultural low-carbon efficiency in the Yellow River Basin has a negative trend of transferring to the low level on the whole, and tends to maintain the original state level, and it is difficult to realize the leapfrog transfer between states. Agricultural low-carbon efficiency has obvious spatial spillover effect and "club convergence" phenomenon, high efficiency area has a positive driving effect on the neighborhood area, while low efficiency area has a negative impact on the neighborhood area. (3) The level of urbanization has a significant positive impact on the low-carbon efficiency of agriculture in the upper, middle and lower reaches of the Yellow River Basin, which plays an important role in promoting the green development of agriculture. Finally, based on the above research conclusions, relevant policy recommendations were put forward, in order to provide references for promoting the improvement of low-carbon agricultural efficiency and promoting high-quality agricultural development in the Yellow River Basin.

To solve the problem that the common long-tailed classification method does not use the semantic features of the original label text of the image, and the difference between the classification accuracy of most classes and minority classes is large, the long-tailed image classification method based on enhanced contrast visual language trains the head class and tail class samples separately, uses text image to pre-train the information, and uses enhanced momentum contrast loss function and RandAugment enhancement to improve the learning of tail class samples. On the ImageNet-LT long-tailed dataset, the enhanced contrastive visual-language based long-tailed image classification method has improved all class accuracy, tail class accuracy, middle class accuracy, and F1 values by 3.4%, 7.6%, 3.5%, and 11.2%, respectively, compared to the BALLAD method. The difference in accuracy between the head class and tail class is reduced by 1.6% compared to the BALLAD method. The results of three comparative experiments indicate that the long-tailed image classification method based on enhanced contrastive visual-language has improved the performance of tail classes and reduced the accuracy difference between majority and minority classes.

Standard Ethernet (IEEE 802.3 and the TCP/IP protocol suite) is gradually applied in industrial control system (ICS) with the development of information technology. It breaks the natural isolation of ICS, but contains no security mechanism. A modified intrusion detection system (IDS), which is strongly correlated to specific industrial scenario, is necessary for modern ICS. On the one hand, this paper outlines attack models, including infiltration attacks and our creative forging attack. On the other hand, we proposes a hierarchical IDS, which contains a traffic prediction model and an anomaly detection model. The traffic prediction model, which is based on autoregressive integrated moving average (ARIMA), can forecast the traffic of ICS network in the short term and precisely detect the infiltration attacks according to abnormal changes in traffic pattern. The anomaly detection model using one-class support vector machine (OCSVM) is able to detect malicious control instructions by analyzing the key field in EtherNet/IP packets. The experimental results show that the hierarchical IDS has an outstanding performance in detecting infiltration attacks and forging attack compared with other two innovative IDSs.

The retrieval of tree height percentiles with satellite lidar waveforms over the mountainous ar-eas is greatly challenged due to slanted and rugged topographic relief of underlying ground. A novel algorithm is proposed to extract the height percentiles based on the target response waveform (TRW) that is resolved by using a Richardson–Lucy deconvolution algorithm with an adaptive iterative time. The height metrics of the energy percentiles of 25%, 50%, 75% and 95% for the cumulative TRW distribution are determined by their vertical distances relative to the ground elevation in this study. To validate the proposed algorithm, we select the received waveforms of the Global Ecosystem Dynamics Investigation (GEDI) lidar over the Pahvant Mountains of central Utah, USA. The results reveal that the resolved TRWs resemble closely to the actual target response waveforms from the coincident airborne lidar data, with the mean values of the coefficient of correlation, total bias and root mean square error (RMSE) taking val-ue of 0.92, 0.0813 and 0.0016. In addition, the accuracies of the derived height percentiles from the proposed algorithm have been greatly improved compared with the conventional Gaussian de-composition method and the slope-adaptive waveform metrics method. The RMSE values de-crease by the mean values of 1.96 m and 2.72 m, respectively. It demonstrates that the proposed algorithm has good potential in the extraction of forest structure parameter over rugged moun-tainous areas.

This study simulated the effects of direct predatory pressure, indirect predatory pressure, and conspecific injury signals on the sea cucumber (Apostichopus japonicus) to determine changes in the activity of immune defense enzymes (lysozyme, acid phosphatase, alkaline phosphatase) and antioxidant stress enzymes (catalase, superoxide dismutase, malondialdehyde). Samples of sea cucumber juveniles were collected at 3 hours, 12 hours, 72 hours, and 96 hours post-predatory stress, and six enzymes related to immune defense and antioxidant stress were selected for activity assays, namely lysozyme (LZM), acid phosphatase (ACP), alkaline phosphatase (AKP), superoxide dismutase (SOD), catalase (CAT), and malondialdehyde (MDA). The results indicated that under direct predatory pressure, the activity of catalase in sea cucumbers was significantly higher than that of the control group at 3 hours (P < 0.05), while the activities of acid phosphatase, alkaline phosphatase, and catalase were significantly lower at 72 hours (P < 0.05). Under indirect predatory pressure, the activity of malondialdehyde in sea cucumbers was significantly higher than that of the control group at 12 hours (P < 0.05), the activity of alkaline phosphatase was significantly higher at 72 and 96 hours (P < 0.05), catalase was significantly lower at 72 hours, and the activity of superoxide dismutase was significantly higher at 72 hours (P < 0.05). Under the influence of conspecific injury signals, the activity of malondialdehyde in sea cucumbers was significantly higher than that of the control group at 12 hours (P < 0.05), and the activity of superoxide dismutase was significantly higher at 96 hours (P < 0.05). The sea cucumber enhanced its antioxidant capacity 3 hours after facing the predator, while its immune defense mechanism was suppressed at 72 hours. When facing indirect predatory pressure, the sea cucumber may have made immune and antioxidant preparations for the arrival of unknown risks. The experimental results show that predatory pressure has a significant impact on the immune and antioxidant functions of sea cucumbers, which may be related to the physiological state and environmental adaptability of the sea cucumber. This study provides a new perspective for understanding how sea cucumbers cope with predatory pressure in the natural environment and offers theoretical support for the cultivation management of sea cucumbers.

This article explores the relationship between Wang Yangming's philosophy and the new quality productivity, revealing how the new quality productivity, while inheriting the core ideas of Yangming's philosophy, achieves a higher level through innovation and development. The new quality productivity emphasizes the integration and innovation of knowledge, technology, and information, characterized by knowledge-driven innovation, information technology support, sustainable green development, and global collaborative development. The fusion of Yangming's philosophy and the new quality productivity holds significant theoretical and practical implications.

Rice canopy height and density are directly usable crop phenotypic traits for the direct estimation of crop biomass. Therefore, it is crucial to rapidly and accurately estimate rice canopy phenotypic parameters. To achieve non-destructive detection and estimation of essential phenotypic parameters in rice, a platform based on LiDAR point cloud data for rice phenotypic parameter detection was established. Data collection of rice canopy layers was performed across multiple plots. The LiDAR-detected canopy top point clouds were selected using a method based on the highest percentile, and the rice canopy surface model was calculated. Canopy height estimation was the difference between ground elevation and percentile value. To determine the optimal percentile defining the rice canopy top, testing was conducted incrementally from 0.8 to 1 with an increment of 0.005. The optimal percentile value was found to be 0.975. The root mean square error (RMSE) between LiDAR-detected canopy height and manually measured canopy height was calculated. The prediction model based on canopy height (R2=0.941, RMSE=0.019) exhibited a strong correlation with actual canopy height. Linear regression analysis was conducted between gap fraction of different plots and manually detected average Leaf Area Index (LAI) of rice canopy. Prediction models for canopy LAI based on ground return counts (R2=0.24, RMSE=0.1) and ground return intensity (R2=0.28, RMSE=0.09) showed strong correlations but had lower correlation with rice canopy LAI. Regression analysis was performed between LiDAR-detected canopy height and manually measured rice canopy LAI. The results indicated that the prediction model based on canopy height (R2=0.77, RMSE=0.03) was more accurate.

The Oriental ratsnake Ptyas mucosa is a common non-venomous snake of the colubrid family, with a wide geographic range spanning much of South and Southeast Asia. P. mucosa is widely cultivated dut to it used in traditional medicine, scientific research, and handicrafts. Therefore, genome resources could play an important role in the efficacy of traditional medicine and the analysis of the living environment of the species. We collected a snake sample in Hezhou, Guangxi, China, which was identified as P. mucosa by morphological identification. Here we present a highly continuous P. mucosa genome with a genome size of 1.74Gb. The scaffold N50 length is 9.57Mb and the maximal length of scaffold is 78.3Mb, the P. mucosa genome has a CG content of 37.9% and the integrity of the gene reached 86.6%.Assembled using long-reads, the total length of the repeat sequence in the genome reached 735 Mb, and its repeat content was as high as 42.19%. A total of 24,869 functional genes were annotated. This study will assist in the understanding of the P. mucosa, and also provide a basis for medicinal research.

Membrane materials are most widely applied in construction engineering with small mass and high flexibility, it presents strong geometric nonlinearity in the process of vibration. In the paper, an improved multi-scale perturbation method is used to solve the aeroelastic stability of closed and open membrane roofs for quantify the effect of geometric nonlinearity on the single-mode aeroelastic instability wind speed of membrane roofs. The results show that the critical wind speed values of the two models are small when the geometrical nonlinearity of membrane material is neglected. In addition, under normal wind load, the influence of geometrical nonlinearity of membrane on the aerodynamic stability of roof can be neglected, However, under strong wind load, when the roof deformation reaches 3% of the span, the influence of geometric nonlinearity should be considered and the influence increases with the decrease of transverse and downwind span of membrane roof. The results obtained in this paper have important theoretical reference value for the design the membrane structures.

In this study, cotton fabric reinforced phenolic resin (CPF) composites were modified by adding four two-dimensional fillers: graphitic carbon nitride (g-C3N4), graphite (Gr), molybdenum disulfide (MoS2), and hexagonal boron nitride (h-BN). The tribological properties of these modified materials were investigated under dry friction and water lubrication conditions. CPF/ Gr composite exhibits significantly better tribological performance than the other three fillers modified CPF composites under dry friction, with a 24% reduction in friction coefficient and a 78% reduction in wear rate compared to unmodified CPF composite. Under water lubrication conditions, all four fillers did not significantly alter the friction coefficient of the CPF composite. However, except for an excessive amount of Gr, the other three fillers can reduce the wear rate. Particularly, in the case of 10% MoS2 content, the wear rate decreased by 56%. Scanning electron microscopy (SEM) and X-ray photoelectron spectroscopy (XPS) were employed for the analysis of the morphology and composition of the transfer films. Additionally, molecular dynamics (MD) simulations were conducted to investigate the adsorption effects of Gr, MoS2, and PF on the counterpart surface under both dry friction and water lubrication conditions. The difference in the adsorption capacity of Gr and MoS2 on the counterpart, as well as the resulting formation of transfer films, accounts for the variation in tribological behavior between CPF/Gr and CPF/MoS2 composites. By combining the lubrication properties of MoS2 and Gr under dry friction and water lubrication conditions, using them as co-fillers can achieve a synergistic lubrication effect.

Codon use bias is an important characteristic in the process of genetic information transmission of species. With the publication of the genome of C. panzhihuaensis, it is of great significance to investigate the codon use bias for understanding the genetic evolution of this species and for molecular breeding. In this study, Perl language and CodonW 1.4.2 software was used to systematically analyze the coding gene sequences of the C. panzhihuaensis genome, obtain the characteristics of codon use, and identify the sources of variation affecting codon use. The results showed that GC3s content, GCall content, and ENC value were 46.75%, 47.67%, and 52.8 respectively. As the first seed plant, the GC3 content of Cycas is similar to that of most gymnosperms and most dicotyledons, but considerably different from that of monocotyledons.RSCU value was greater than 1, among which 21 codons ended in U or A. Enc-plot analysis, PR2-plot neutral plot analysis, and correlation coefficient analysis of Axis1 with GC3s and CAI revealed that the codon bias was mainly affected by natural selection, but also by mutation pressure and other factors. Thirty-one optimal codons of Cycas genes were screened. This research can provide a reference for the phylogeny and genome codon evolution of Cycas.

Hot deformation at elevated temperature is essential to densify the particle reinforced Aluminum matrix composites (AMCs) and improve their performance. However, hot deformation behavior of the AMCs is sensitive to the variation of hot processing parameters. In this paper, optimal processing parameters of the dual-scale SiCp/A356 composites was determined to explore the control strategy of the microstructure. Hot compression tests were conducted at the temperature ranging from 460 to 520℃ under strain rates from 0.01 to 5 s−1. Constitutive equation and processing maps were presented to determine the hot processing parameters. Microstructure evolution of the dual-scale SiCp/A356 composites was analyzed. The strain rate of 0.62 ~ 5s-1 and deformation temperature of 495 ~ 518℃ is suitable for the hot processing. The number of DRX grains in the “safe” domains is larger and the dislocation density is lower compared to those of instability domains. DRX particles mainly occurred around SiC particles. The presence of SiC particles can promote effectively the DRX nucleation, which result in that the dynamic softening mechanism of the dual-scale SiCp/A356 composites is dominated DRX.

This paper proposes a multi-terminal adaptive collaborative operation method to solve the problem of unstable internal force tracking in clamping and handling unknown objects by multi-terminal robots. In the proposed method, the internal command force changes the complex internal force control problem into an internal force tracking problem from multi-slave to master. Moreover, we develop an algorithm for multi-slave setups to estimate object stiffness and motion uncertainty in the direction of the internal command force according to Lyapunov theory. Finally, the impedance control generates a reference trajectory for the multi-slave to maintain the desired internal force and track the master’s motion. Several experiments are conducted on a self-made robot equipped. The experimental results show that the oscillation amplitude of each slave end is less than 1 mm, the directional oscillation amplitude is less than 1 degree during the tracking of the desired commanded internal force. For objects with low stiffness, the error of the commanded internal force is less than 1 N (6%) per slave. The error in tracking the commanded internal force for objects with high stiffness is less than 2 N (8%). The results prove the feasibility and effectiveness of the proposed method.

The objective of this investigation was to enhance the sensory appeal of Cerasus humilis (C. humilis) juice and ascertain potential interactions among bioactive compounds within a functional juice matrix. Sensory attributes, color, antioxidant potential, polyphenol and vitamin C (VC) concentrations, and sugar levels were assessed. Diverse dosage combinations were examined to determine their impact on the quality of both C. humilis and Green grape juices. Among the formulations, CG5 exhibited elevated antioxidant activit y and polyphenol content (455.02 mg TE/100 ml and 173.1 mg/100 ml, respectively), coupled with favorable consumer preference. Notable variations in compound content were observed across the seven analyzed juices. In the blended juices (CG1–CG5), interactions between distinct juices influenced VC and sugar levels, with other bioactives contributing to beneficial modifications, displaying a progressive rise. This study innovatively crafted delectable and convenient C. humilis juice, upholding its intrinsic high antioxidant activity, thereby presenting a novel avenue for marketable functional juice offerings.

Multi-cameras system is widely applied in 3D computer vision especially when multiple cameras are distributed on both sides of the measured object. The calibration methods of multi-cameras system are critical to the accuracy of vision measurement and the key is to find an appropriate calibration target. In this paper, a high-precision camera calibration method for multi-cameras system based on transparent glass checkerboard and ray tracing is described, which is used to calibrate multiple cameras distributed on both sides of the glass checkerboard. Firstly, the intrinsic parameters of each camera is obtained by Zhang’s calibration method. Then, multiple cameras capture several images from the front and back of the glass checkerboard with different orientations, and all images contain distinct grid corners. As the cameras on one side are not affected by the refraction of glass checkerboard, extrinsic parameters can be directly calculated. However, the cameras on another side are influenced by the refraction of glass checkerboard, and the direct use of projection model will produce calibration error. A multi-cameras calibration method using refractive projection model and ray tracing is developed to eliminate this error. Furthermore, both synthetic and real data are employed to validate the proposed approach. The experimental results of refractive calibration show that the error of the 3D reconstruction is smaller than 0.2 mm, the relative errors of both rotation and translation are less than 0.014%, and the mean and standard deviation of reprojection error of 4-cameras system are 0.00007 and 0.4543 pixel. The proposed method is flexible, high accurate, and simple to carry out.

Raindrop size distribution (RSD) is an index for reflecting precipitation characteristics. Analyzing the differences of RSD plays an important role in understanding the precipitation microphysical processes and improving quantitative precipitation prediction of radar. In this paper, the RSD data of Dafang (57708) station, Majang (57828) station, and Luodian (57916) station (with an altitude of 1722.7m, 985.0m, and 441.5m, respectively) in Guizhou are analyzed according to the precipitation microphysical characteristics. First,Particles with particle size less than 1mm contributes the highest value to the density of particle number , and decrease with the descending altitude. Second, the GAMMA distribution fit shows a better fit compare to M-P distribution fit, and GAMMA distribution fit increases with the ascending altitude. Third, the mass-weighted average diameter is not sensitive enough to the change of precipitation intensity with correlation coefficients of 54.84%, but there is a obvious relationship between the average volume diameter and the precipitation intensity with correlation coefficients of 69.15%. Then, the precipitation prediction model is established using LSTM neural network after fusing the representative microphysical characteristics of RSD with radar and rain gauge data. The precipitation prediction model is applied to the Dafang (57708) site to predict precipitation for time range of 0-180 minutes, and it is found that for the prediction of convective cloud and stratiform cloud precipitation, the 60-minute prediction results are the most consistent with the actual precipitation, where the correlation coefficients are 92.87% and 92.57%, respectively. Conclusively, the results demonstrate that combining with the RSD base data could improve the reliability of precipitation forecasting.

Background: The aim of this study is to explore the independent and joint associations between physical activity (PA) and sleep duration with depressive symptoms. Methods: We included and analyzed 18,052 participants (age ≥ 20 years) from the cross-sectional National Health and Nutrition Examination Survey (NHANES) conducted between 2007 and 2014. Results: After adjustment, both males and females showed a significant correlation between PA, sleep duration, and depressive symptoms. In the joint association analysis, we found: 1. The interaction between PA and sleep duration was statistically significant in males but not significant in females (P=0.380). 2. Compared to individuals with the lowest PA level and not meeting the National Sleep Foundation's (NSF) guidelines, those with the highest PA level and recommended sleep duration had a 79% decrease in depression risk in males (odds ratio [OR] 0.21, 95% confidence interval [CI] 0.14-0.32) and a 74% decrease in females (OR 0.26, 95% CI 0.20-0.35). 3. In male participants adhering to NSF guidelines, each increase in PA quartile is associated with a 19% reduction in the risk of depression (OR 0.81, 95% CI 0.71-0.92). Conversely, among male participants not adhering to NSF guidelines, there is a 23% decrease in depression risk (OR 0.77, 95% CI 0.69-0.86). For female participants, the respective reductions in depression risk are 20% (OR 0.80, 95% CI 0.73-0.89) and 14% (OR 0.86, 95% CI 0.80-0.93). Conclusion: For males, adherence to recommended sleep duration weakens the relationship between physical activity and depression, while the opposite is observed for females.

Channel estimation is an important module to enhance the performance of orthogonal frequency division multiplexing (OFDM) systems. However, the presence of a large amount of noise in multipath fading time-varying channels significantly affects the channel estimation accuracy and thus the recovery quality of the received signals. Therefore, this paper proposes a double-threshold (DT) channel estimation method based on adaptive frame statistics (AFS). The method first adaptively determines the number of statistical frames based on the temporal correlation of the received signals, and preliminarily detects the channel structure by analyzing the distribution characteristics of multipath sampling points and noise sampling points during adjacent frames. Subsequently, a multi-frame averaging technique is used to expand the distinction between multipath and noise sampling points. Finally, the DT is designed to better recover the channel based on the preliminary detection results. Simulation results show that the proposed adaptive frame statistics-double-threshold (AFS-DT) channel estimation method is effective and has better performance compared with many existing channel estimation methods.

Taking capital, manpower, and natural resources as inputs, regional GDP as expected output, and industrial pollution as undesired output, this study measures the ecological efficiency of various regions in China through the Global-Malmquist model. The results show a trend of an initial sharp decline in ecological efficiency followed by a gradual increase in the time dimension, but there is no significant correlation in the spatial dimension. Using the gravity model to quantify the attractiveness of the regions’ capital and human resources for collaborative innovation, it estimates the impact of collaborative innovation on eco-efficiency through the system-Generalized Method of Moments (GMM) model. The results show that technological innovation capital in other regions has a negative “U” relationship with local ecological efficiency, while scientific and technological innovation human resources have a positive “U” relationship. In addition, government financial support in science and technology and the ecological efficiency of the previous period serve as promoting factors of the current local ecological efficiency, while the introduction of foreign technological innovation is likely to inhibit improvements in ecological efficiency. Based on these findings, this study puts forward corresponding policy recommendations for local governments to advance their development agendas alongside their environmental priorities in line with their specific circumstances.

Flexible electrochemical sensors can adhere to any bendable surface with conformal contact, enabling continuous data monitoring without compromising the surface's dynamics. Among various materials that have been explored for flexible electronics, metal-organic frameworks (MOFs) exhibit dynamic responses to physical and chemical signals, offering new opportunities for flexible electrochemical sensing technologies. This review aims to explore the role of electrocatalysis in MOF films specifically designed for flexible electrochemical sensing applications, with a focus on their design, fabrication techniques, and applications. We systematically categorize the design and fabrication techniques used in preparing MOF films, including in-situ growth, layer-by-layer assembly, and polymer-assisted strategies. The implications of MOF-based flexible electrochemical sensors are examined in the context of wearable devices, environmental monitoring, and healthcare diagnostics. Future research is anticipated to shift from traditional microcrystalline powder synthesis to MOF thin-film deposition, which is expected to not only enhance the performance of MOFs in flexible electronics but also improve sensing efficiency and reliability, paving the way for more robust and versatile sensor technologies.

Tea (Camellia sinensis) is one of the most popular beverages worldwide. Many types of tea prod-ucts continuously emerge in an endless stream; so, the classification or verification of tea be-comes more difficult. Aroma is a vital indicator of tea quality. The present study deals with the identification of aroma compounds in 18 different kinds of tea belonging to three typical tea va-rieties, including green tea, oolong tea, and black tea, using GC-IMS and GC×GC-O-MS. More-over, the clustering of all 18 tea samples and the in-depth correlation analysis between sensory evaluation and instrumental data were performed using the PCA and OPLS-DA. The results re-vealed that in all 18 kinds of tea, a total of 85 aroma compounds were detected by GC-IMS, whereas 318 were detected by GC×GC-O-MS. The PCA result revealed that green tea, oolong tea, and black tea could be clearly separated based on their peak areas. The OPLS-DA result showed that a total of 49 aroma compounds with VIP value > 1.0 could be considered as the potential in-dicators to quickly classify or verify tea types. This study not only compared the aroma differ-ences across different types of teas, but also provided ideas for the rapid monitoring of tea qual-ity and variety.

Light trapping in single nanowires (NWs) are of vital importance for photovoltaic applications. However, circular NWs (CNWs) can limit its light-trapping ability due to high geometrical symmetry. In this work, we present a detailed study of light trapping in single NWs with an elliptical cross-section (ENWs). We demonstrate that the ENWs exhibit significantly enhanced light trapping compared with the CNWs, which can be ascribed to the symmetry-broken structure that can orthogonalize the direction of light illumination and the leaky mode resonances (LMRs). That is, the elliptical cross-section can simultaneously increase the light path length by increasing the vertical axis and reshape the LMR modes by decreasing the horizontal axis. We found that the light absorption can be engineered via tuning the horizontal and vertical axes, the photocurrent is significantly enhanced by 374.0% (150.3%, 74.1%) or 146.1% (61.0%, 35.3%) in comparison with that of the CNWs with the same diameter as the horizontal axis of 100 (200, 400) nm or the vertical axis of 1000 nm, respectively. This work advances our understanding of how to improve light trapping based on the symmetry breaking from the CNWs to ENWs and provides a rational way for designing high-efficiency single or self-assembled NW photovoltaic devices.

Saccharomyces cerevisiae (S. cerevisiae) ethanol fermentation has left an indelible trace in human history. It is regarded as the original beverage synthesis, and has developed into an essential energy supply for mankind today. However, the history of ethanol synthesis using S. cerevisiae, including the mechanism analysis process, has not been carefully and succinctly reported. In this paper, we review the history of ethanol synthesis using S. cerevisiae. In addition, we also review the substrates that drive S. cerevisiae ethanol synthesis, including the utilization of glucose, sucrose, starch and molasses, in order to summarize the current development status and to contribute to the further improvement of this field.

Aimed for the difficulty and complexity of detecting the piston error for segmented telescope, this paper proposed a new piston error measurement method based on a hybrid artificial neural net-work. Firstly, we use Resnet network to learn the mapping relationship between the focal plane degradation image and the signs of the piston error. Then, based on the established theoretical re-lationship between modulation transfer function and the piston error, BP neural network is used here to learn the mapping relationship between the MTF and the absolute value of the piston error. After the training of the hybrid network is completed, a wide-range and high-precision detection of the piston error of the sub-mirrors can be achieved using the combined output of the two net-works only a focal plane image of a point source with broadband illumination is used as input. The detection range can reach the whole coherent length of the input broadband light, and the detec-tion accuracy can reach 10nm. The method proposed in this paper has the advantages of high de-tection accuracy, wide detection range, low hardware cost, small network scale and low training difficult.

In order to study the movement characteristics of fuel in the fuel tank during aircraft maneuvering, this paper conducts numerical simulations of a typical wing fuel tank using the finite point set method based on certain boundary conditions and excitation. The results show that the finite point set method can capture the complex phenomena of fuel free surface fluctuations, surging, rolling and breaking, as well as the change in center of gravity caused by fuel movement. Under aircraft acceleration and pitch angle excitation, fuel will generate sustained impact pressure on the fuel tank wall. The velocity attenuation of fuel flowing through the baffle communication hole is fast, and the flow resistance and energy dissipation of the communication hole buffer the impact of fuel on the fuel tank wall.

Atherosclerosis is a chronic inflammatory disease which results in thickening of the vessel wall and narrowing of the lumen. It is a leading cause of death worldwide. Preventive treatment is taken into prioritized consideration since currently no effective approaches to cure atherosclerosis are available. These treatments mainly focus on lowering blood cholesterol levels, especially LDL-C, by statins. Even so, lowering lipid levels is not sufficient to reduce the risk of cardiovascular events in all patients. Recently, atherosclerosis has increasingly been recognized as a chronic inflammatory disease involving the immune system, initiating new therapeutic approaches which could alleviate or prevent atherosclerosis by modulating inflammation. Mesenchymal stem cells (MSCs) have emerged as a promising option to relieve inflammation and balance immune responses in inflammatory diseases. Several studies including our group also reported that MSCs may be a new therapeutic option for atherosclerosis. This review summarizes the updated state of our knowledge in the administration of MSCs to alleviate atherosclerosis and discusses some of the key unresolved challenges that need to be solved in future studies.

Based on the plate tectonic theory, using seismic, geology, and public literature data, the proto-type basins and lithofacies paleogeography during the main geological periods of the passive continental margin of East Africa are restored, and the architecture characteristics of the basins and the differences in sedimentary fillings are analyzed. Combined with the dissection of discovered oil and gas reservoirs, four types of hydrocarbon accumulation models are established, the favorable hydrocarbon accumulation combinations (plays), and the next exploration directions in this region are explored. The passive continental margin basins in East Africa experienced three proto-type stages: intracontinental aborted rift during the Late Carboniferous-Triassic Karoo period, intracontinental-intercontinental rift during the Jurassic period, and passive continental margin basin since the Cretaceous period. Affected by the difference in sedimentary filling thickness between the rift period and depression period, four types of passive continental margin basins are formed: rifted type, depressed type, faulted depression type, and reformed delta type. The maximum sedimentary thickness of the rifted basins during the rift period is greater than 3500 m, and that during the depression period is less than 4000 m, forming a "single-source structure type" hydrocarbon accumulation model. The exploration of rifted basins should focus on giant structural traps at the top of the rifted sequences. The maximum sedimentary thickness of the depressed basins during the depression period exceeds 4000 m, forming a "single-source fan group type" hydrocarbon accumulation model. The dominant exploration directions of depressed basins are sedimentary sand bodies and structural-lithologic traps during the depression and drift periods. The maximum sedimentary thickness of the faulted depression basins during the rift period is greater than 3500 m, and that during the depression period is greater than 4000 m, forming a "double-source and double-combination type" hydrocarbon accumulation model. The exploration of rifted basins should focus on giant slip-collapse-debris flow sedimentary sand bodies on the upper and middle slopes. In addition to the large sedimentary thickness of the early rift and the central depression, the delta thickness of the reformed delta basins during the late depression period since the Miocene is more than 4000 m, and four structural belts (growth fault, mud diapir, thrust fold, and foredeep gentle slope) were formed from onshore to offshore, forming a "three-source and multi-combination type" hydrocarbon accumulation model. All four structural belts can form giant oil and gas fields.

In this study, a composite film was developed for electrochemical sensing of tryptophan (Trp). Porous reduced graphene oxide (PrGO) was utilized as the electron transfer layer, and a C-undecylcalix[4] resorcinarene Langmuir-Blodgett (CUCR-LB) film served as the molecular recognition layer. Atomic force microscopy (AFM), transmission electron microscopy (TEM), Raman spectroscopy, scanning electron microscopy (SEM), and electrochemical experiments were employed to analyze the characteristics of the CUCR-LB/PrGO composite film. The electrochemical behavior of Trp on the CUCR-LB/PrGO composite film was investigated, revealing a linear response range of Trp was 1.0×10-7 to 3.0×10-5 mol L-1 and a detection limit of 3.0×10-8 mol L-1. Furthermore, the developed electroanalytical method successfully determined Trp content in an amino acid injection samples. This study not only introduces a rapid and reliable electrochemical method for determination of Trp but also presents a new strategy for constructing high-performance electrochemical sensing platforms.

In the present study, an attempt was made to induce rooting from single-node cuttings of hybrid aspen (Populus tremula L. ×P. tremuloides Michx.) with different concentrations of IAA, IBA and NAA during rooting. Among the three auxins used, NAA showed more effective induction on rooting as compared to IAA and IBA at the whole level. Thereafter, NAA was used further in experiments for anatomical and biochemical investigation. The results showed that it took 12 days from the differentiation of primordium to the appearance of young adventitious roots with NAA application. It was found that endogenous IAA, ZR and GA3 levels increased, but ABA decreased in cuttings with 0.54 mM NAA treatment. In contrast to the endogenous IAA level, NAA had negative effect on IAA-oxidase (IAAO) activity. Similarly, the decreased peroxidase (POD) activity, consistent with down-regulation of expressed levels of POD1 and POD2, was observed in NAA-treated cuttings. Whereas, NAA resulted in a higher activity in polyphenol oxidase (PPO) compared to the control cuttings. Collectively, the study highlighted that 0.54 mM NAA is efficient on rooting in hybrid aspen, and its effect on metabolic changes during rooting is discussed, which provide valuable information for propagating hybrid aspen.

Clinical ketosis is a crucial metabolic disease in dairy cows that is often accompanied by severe lipolysis and inflammation in adipose tissue. Our previous study suggested that the fold change of calmodulin (CaM) was upregulated 2.401-fold in the adipose tissue of cows with clinical ketosis. Therefore, we hypothesize that CaM may regulate lipolysis and inflammatory responses in clinical ketosis cows. To verify the hypothesis, we conducted a thorough veterinary assessment of clinical symptoms and serum β-hydroxybutyrate (BHB) concentration before collecting subcutaneous adipose tissue samples from six healthy and six clinically ketotic Holstein cows at 17 ± 4 days postpartum. Commercial kits were used to test the abundance of BHB, Non-esterified fatty acid (NEFA), Liver function index (LFI), interleukin-6 (IL-6), interleukin-1β (IL-1β), and tumor necrosis factor-α (TNF-α). We found that Clinical ketosis cows had higher levels of BHB, NEFA, LFI, IL-6, IL-1β, TNF-α, and lower glucose levels compared to healthy cows. Furthermore, the abundance of CaM, toll-like receptor 4 (TLR4), inhibitor of nuclear factor κB kinase subunit β (IKK), phosphorylated nuclear factor κB/nuclear factor κB, (p-NF-κB/NF-κB), adipose triglyceride lipase (ATGL) and phosphorylated hormone-sensitive lipase/hormone-sensitive lipase (p-HSL/HSL) were increased, while that of perilipin-1 (PLIN1) was decreased in the adipose tissue of cows with clinical ketosis. To investigate the mechanistic underlying the responses, we isolated the primary bovine adipocytes from the adipose tissue of healthy cows and induced the inflammatory response mediated by TLR4/IKK/NF-κB with lipopolysaccharide (LPS), in addition to treating with CaM overexpression adenovirus and CaM small interfering RNA. In vitro, LPS upregulated the abundance of CaM, TLR4, IKK, NF-κB, ATGL, p-HSL/HSL, and CaM and downregulated PLIN1. CaM silencing downregulated the abundance of LPS-activated p-HSL/HSL, TLR4, IKK, and NF-κB and upregulated PLIN1 in bovine adipocytes, except for ATGL. By contrast, CaM overexpression upregulated the abundance of LPS-activated p-HSL/HSL, TLR4, IKK, and NF-κB and downregulated PLIN1 expression in bovine adipocytes. In summary, these data suggest that CaM promotes lipolysis in adipocytes through HSL and PINL1 while activating the TLR4/IKK/NF-κB inflammatory pathway to promote an inflammatory response. There is a positive feedback loop between CaM, lipolysis, and inflammation. Overall, inhibiting CaM may act as an adaptive mechanism to alleviate metabolic dysregulation in adipose tissue, contributing to relief from lipolysis and inflammatory response.

In recent decades, as eutrophication in inland and coastal waters (ICWs) has increased due to anthropogenic activities and global warming, so has the need for timely monitoring. Compared with traditional sampling and laboratory analysis methods, satellite remote sensing technology can provide macro-scale, low-cost, and near real-time water quality monitoring services. The Geostationary Ocean Color Imager (GOCI), integrated onboard the Communication Ocean and Meteorological Satellite (COMS) from the Republic of Korea, was the first geostationary ocean color observation satellite and was operational from April 1, 2011 to March 31, 2021. Over ten years, GOCI has observed oceans, coastal waters, and inland waters within its 2,500 km×2,500 km target area centered on the Korean Peninsula. The most attractive feature of GOCI, compared with other commonly used watercolor sensors, was its high temporal resolution (1h, eight times daily from 0 UTC to 7 UTC), providing the opportunity to monitor the quality of ICWs, where optical properties can change rapidly throughout the day. This systematic review aims to comprehensively review GOCI features and applications in ICWs, analyzing progress in atmospheric correction algorithms and water quality monitoring. Analyzing 123 articles from the Web of Science and China National Knowledge Infrastructure (CNKI) through a bibliometric quantitative approach, we examined GOCI’s strength and performance with different processing methods. These articles reveal that GOCI played an essential role in monitoring the ecological health of ICWs in its observation area in East Asia. GOCI has led the way to a new era of geostationary ocean satellites, providing new technical means for monitoring water quality in oceans, coastal zones, and inland lakes. We also discuss the challenges encountered by geostationary satellites in monitoring water quality and provide suggestions for improvements.

In the present work, the effects of ageing treatment on the microstructures of a near-β Ti alloy (TC18) are studied. The influence of ageing treatment on the tensile properties and failure mechanisms are systematically analyzed. It is found that the size and morphology of the primary α (αp) phases are insensitive to ageing temperature and time. Furthermore, the ageing temperature and time dramatically influence the precipitation of the secondary α (αs) phases. Massive αs phases precipitate and gradually coarsen, and finally weave together with increasing the ageing temperature or extending the ageing time. The thickness of αs phases is responsible for the material strengths, while the content of α phases can enhance the material ductility. The ductile characteristics of the alloy with coarser αs phases are more obvious than those with thinner αs phases. Therefore, the ageing treatment is helpful for the precipitation and homogeneous distribution of αs phases, which is essential for balancing the strengths and ductility of the studied Ti alloy.

The ANFC/ABPE-10 composite film was prepared by ABPE-10 impregnating into ANFC films under negative pressure. And the composite film had meted high performance FOLED substrate requirement even when ANFC dosage was high for approximately 70%, which was consistent with for low cost efficiency, recyclability, and environmentally friendly. The enhanced properties of ANFC films were mainly because of the nature of ABPE-10 itself and the IPN structure formed between ABPE-10 and ANFC film. The transparency of composite films with different ANFC dosage was significantly increased from 67% to 88% by UV-Vis analysis. The composite film inherited the properties of AFNC, obtaining low CTE characteristics and ductile compact structure. The contact angles of ANFC films increased by 102% from 49.2° to 102.9°after dipping ABPE-10. Additionally, the composite films had outstanding mechanical properties such as tensile strength 173.72 MPa, Young’s modulus 4.06 GPa, and elongation at break 5.81%.

This work describes the catalytic performances of attapulgite/ZSM-5 extrudate in comparison to conventional alumina-bound ZSM-5 extrudate in toluene methylation. The novel attapulgite/ZSM-5 extrudate is prepared by using natural clay attapulgite as binder which introduces mobile alkaline species and macropores to the extrudate. In contrast to alumina-bound extrudate, this novel extrudate shows significantly higher para-selectivity and stability. By using characterization techniques, including in-situ XRD, SEM, NH3 temperature programmed desorption (TPD), thermogravimetric analysis and n-hexane/cyclohexane physical adsorption, the catalytic performance improvement of attapulgite/ZSM-5 extrudate is correlated with the neutralization of Brønsted acid sites by mobile alkaline species during calcination and reaction process. Moreover, a higher para-selectivity was obtained over attapulgite-bound modified ZSM-5 extrudate. The strategy of extruding ZSM-5 catalysts with attapulgite as binder is facile and universal. Such method paves a new way for preparation of shaped toluene methylation catalyst with enhanced para-selectivity and stability.

Using numerical simulation method, combined with the pre-branch material characteristics of the measurement results, based on the LS-DYNA software to simulate the branch crushing process, the analysis found that not only the existence of the cutter cutting in the branch destruction process, there is also the cutting of the opposing surface of the bending fracture, with the increase in the speed of the knife rollers, the cutter cutting resistance increases, the cutting resistance reaches 2690 N when the cutter at 2500 r/min, the cutter cutting resistance is the smallest in the cutting simulation at the blade angle of 55°, the blade angle is more suitable for the cutting of the branch. In the cutting simulation under different cutting edge angles, the cutting resistance of the tool is the smallest when the edge angle is 55°, which is 1860 N. This edge angle is more suitable for branch crushing and cutting. Using Fluent software to analyse the airflow characteristics of the crushing device, it was found that with the increase of the knife roller speed, the inlet flow and negative pressure of the crushing chamber are increasing, the speed of 2500 r/min, the inlet flow and negative pressure were 1.92 kg/s and 37.16 Pa, which will be conducive to the feeding of branches, but the speed is too high and it will also lead to the enhancement of the vortex of part of the area in the crushing device, which will affect the feeding of branches and the throwing of the crushed material. affect the feeding of branches and the throwing out of crushed materials, and finally determined the speed range of the crushing knife roller is 1800 ~ 2220 r/min. Based on ANSYS/Model module modal analysis of the crushing knife roller, the knife roller of the first six orders of the intrinsic frequency and vibration pattern, crushing knife roller of the lowest order of the modal intrinsic frequency of 137.42 Hz, much larger than the crushing knife roller operating frequency of 37 Hz, the machine will not resonate during operation.

Natural vegetation restoration has become an effective and rapid way for eco-logical restoration in fragile areas. However, the response of soil microorgan-isms remains unclear. Using high-throughput sequencing methods, we evalu-ated the dynamics of soil bacterial and fungal communities during forest suc-cession (shrubland, secondary forest, and primary forest) in the karst region of Southwest China. Secondary forest had significantly higher bacterial α-diversity than the shrubland and primary forest. Soil bacterial community in the primary forest was close to the shrubland but diverged from the secondary forest, and that the fungal community could be discriminated along forest suc-cession. Also, the microbial co-occurrence network indicated that soil fungi had less but more intense relationships than bacteria in the karst forests. Further-more, soil properties (pH, SOC, TN, moisture, and AK), soil microbial biomass (MBP, and MBN), and plant factors (Shannon index of woody plants) drove the dynamics of the soil bacterial community, while soil properties (i.e., pH) mostly explained the variation of the soil fungal community along karst forest succession. Different responses of soil bacteria and fungi to forest succession in a karst region give hints for ecological restoration along forest succession in the karst region.

Remote sensing (RS) technology has significantly contributed to geological exploration and mineral resource assessment. However, its effective application in vegetated areas encounters various challenges. This paper aims to provide a comprehensive overview of the challenges and opportunities associated with RS-based lithological identification in vegetated regions. The article begins by introducing the sources and processing methods of RS data, which serve as the foundation for subsequent analysis. Moreover, it highlights the techniques and methodologies employed for lithological classification in vegetated areas. Notably, hyperspectral RS and Synthetic Aperture Radar (SAR) have emerged as prominent tools in lithological identification. In addition, this paper addresses the limitations inherent in RS technology, including issues related to vegetation cover and terrain effects, which significantly impact accurate lithological mapping. To propel further advancements in the field, the paper proposes promising avenues for future research and development. These include the integration of multi-source data to enhance classification accuracy and the exploration of novel RS technologies and algorithms. In summary, this paper presents valuable insights and recommendations for advancing the study of RS-based lithological identification in vegetated areas.

Surface activity of humic acid (HA) and its six sub-fractions isolated from forest soil were characterized by surface tension measurements, dynamic light scattering, and laser doppler electrophoresis. The surface tension of HA sub-fractions decreased from 72.4 mN·m-1 to 36.8 mN·m-1 with the increasing concentration from 0 to 20000 mg·L-1. The critical micelle concentration (CMC) of HA and its sub-fractions ranged from 216 to 1024 mg·L-1 with the multiple linear regression equation of CMC = 18896–6.9×C–296×alkyl-C–331×aromatic-C–17019×H/C+4054×HB/HI (p &lt; 0.05). The Z-average particle size ranges from 108.2 nm to 186.9 nm. The maximum particle size was 5000 nm after filtered with a membrane of 0.45 μm, indicating HA and its sub-fractions progressed self-assembly during 2000 mg·L-1, pH = 6.86. The number-base particle size distribution of HA sub-fractions was identified as four peaks by Gaussian model, and the aggregate sizes were mainly in six clusters including 2 ± 1 nm, 5 ± 2 nm, 10 ± 3 nm, 21 ± 8 nm, 40 ± 10 nm, and &gt; 50 nm indicating multiple aggregations of different particle sizes in the HA fractions solution.

Penile squamous cell carcinoma (SCC) is a rare disease. Treatment options for advanced penile cancer are often limited and prognosis remains poor. We reported a 52-year-old male recurrent and metastatic penile SCC patient with high PD-L1 expression(90%) and TMB(14.4 muts/Mb). He had undergone penectomy, bilateral inguinal lymph node dissection and excision of the abdominal wall mass during two surgeries. Despite cisplatin-based concurrent chemoradiotherapy and sequential chemotherapy with docetaxel plus cisplatin were then carried out, the carcinoma still had progressed. The patient then obtained progression free survival exceeding 32 months with continuous sintilimab, although new onset of ICI-induced diabetes after 24 cycles of sintilimab and required sustained insulin treatment. He didn’t have positive type 1 diabetes associated autoantibodies, but had susceptible HLA genotype DR3-DQ2 haplotype. This is the first patient with radiation and multichemorefractory penile SCC obtained remarkable anti-tumor effect of partial regression exceeding 32 months during continuous sintilimab.

The cross-linkable PCL-PEG analogues block-graft copolymer was designed and synthesized, which with the copolymer of the MEO₂MA and OEGMA as graft chains to improve the mPEG-b-PCL-b-mPEG copolymer the aqueous solution properties. And successfully prepared two hydrogels via a copper-catalyzed 1, 3-dipolar azide-alkyne cycloaddition reaction of alkyne-terminated poly[glycidyl methacrylate-co-2-(2-methoxyethoxy) ethyl methacrylate-co-oligo (ethylene glycol) methacrylate] [P(GMA-co-MEO₂MA-co-OEGMA)] with azide end-functionalized PCL-PEG analogues block-graft copolymer, and tetrakis (2-propynyloxymethyl) -methane (TPOM) and with azide end-functionalized PCL-PEG analogues block-graft copolymer. The copolymer's chemical structure was characterized by proton nuclear magnetic resonance spectroscopy and fourier transform infrared spectroscopy. The molecular weights of the copolymers were decided with gel permeation chromatography. The water solubility and temperature sensitivity of the copolymers were studied by taking digital photos and transmittance change measured by UV spectrophotometer at different temperatures. Fluorescence probes, surface tension, dynamic light scattering and transmission electron microscopy were used to analyze the micelles that copolymers self-assembly in aqueous solution. The sol-gel behavior of copolymer solutions at high concentrations was explored by vial inversion experiments. Finally, the network structure of the gels was observed by scanning electron microscopy. These conclusions indicate that these hydrogels are expected to be used as a new material in the field of biomedicine.

With the long-term and large-scale use, herbicides have been well known to influence tritrophic interactions particularly natural enemies of pests in agro-ecosystems. On the other hand, herbivorous insects, especially the generalist pests, have developed antagonistic interaction to different insecticides, toxic plant secondary metabolites and even heavy metals. However, whether exposure to herbicides would affect resistance of insects against insecticides is largely unknown, especially in agricultural pests. Here, we first reported that pre-exposure to two widely used herbicides butachlor and haloxyfop-methyl for 48 h can prime resistance of a generalist agricultural pest Helicoverpa armigera Hübner against insecticide methomyl and fungal toxin aflatoxin B1. In addition, there were no significant differences between control and herbicides-treated caterpillars on weight gain, pupal weight and pupation rates, suggesting that exposure to herbicides induce resistance of H. armigera accompanied with no fitness cost. Moreover, by determining detoxifying enzyme activities and toxicity bioassay with additional inhibitor of cytochrome P450 piperonyl butoxide (PBO), we showed that exposure to herbicides might prime P450-mediated detoxification of H. armigera against insecticide. Based on these results, we propose that exposure to herbicides primes resistance of H. armigera against insecticide by eliciting a clear elevation of predominantly P450 monooxygenase activities in midgut and fat body.

Crop residue burning produces a lot of polluting gases and fine particles, endangering human health, damaging soil structure, and causing fire accidents. In addition to the impact of residue burning on the local environment, pollutants can spread with the wind to more distant areas and impact the air quality of surrounding areas, especially cities. Nevertheless, a comparative analysis of the impact of two common residue burning parameters, the number of residue fire points and residue burned area, on urban air quality indicators has not been reported. In this study, the correlation between these two different residue burning parameters on air quality in Daqing City was investigated comparatively using the Visible Infrared Imaging Radiometer Suite (VIIRS) fire point product, the Moderate-resolution Imaging Spectroradiometer (MODIS) burned area product, and buffer zone analysis. The association between MODIS burned area products and air quality index (AQI) was found to be around 0.8, with a maximum of 0.816 at a buffer zone radius of 50 km. Meanwhile, it was found that the correlation between the number of residue fire points extracted from the VIIRS active fire products and air quality was above 0.6, again with a maximum of 0.745 at a buffer radius of 50 km. Within other levels of buffer zones, the correlation between residue burned area and AQI was consistently higher than that between residue fire points and AQI. By comparing the correlation between VIIRS fire points, MODIS burned area, and AQI with the concentration of each pollutant, we found that the correlation between residue burned area and AQI and the concentration of each pollutant is higher. MODIS burned area monitoring, on the other hand, detects changes in the time series of images taken by satellite at two transit moments to obtain the new burned area and cumulative burned area during this period, allowing the monitoring of fire traces caused by fire points at non-transit moments. From analyzing the correlation between residue fire points, residue burned area, and the concentration of each pollutant (PM2.5, PM10, CO, NO2, SO2, O3), we found significant correlations between residue burning and PM2.5, PM10, CO, and NO2 concentrations, with the highest correlation (R2) of 0.81 for PM2.5. Moreover, the correlation between residue burned area and PM2.5, PM10, CO, and NO2 concentrations was significantly higher than that between the number of residue fire points and their concentrations.

Recently, a large number of Transformer-based solutions have emerged for the trajectory prediction task, but there are shortcomings in the effectiveness of Transformers in trajectory prediction. Specifically, while position encoding preserves some of the ordering information, the self-attention mechanism at the core of the Transformer has its alignment invariance that leads to the loss of temporal information, which is crucial for trajectory prediction. For this reason, we design a simple and efficient strategy for temporal information extraction and prediction of trajectory sequences using the self-attention mechanism and linear layers. Experimental results show that the strategy we designed can effectively combine the advantages of the linear layer and self-attention mechanisms, compensating for the shortcomings of the Transformer. Additionally, we conducted an empirical study to explore the effectiveness of the linear layer and sparse self-attention mechanisms in trajectory prediction.

The tribology behavior, tribofilm formation and structure evolution of polytetrafluoroethylene (PTFE) filled with α-Al2O3 and SiO2 nanoparticles during sliding against steel counterparts under different loads were studied. It is found that both composites exhibit good wear resistance across the pressure of 1 MPa to 10 MPa, with the α-Al2O3/PTFE composite demonstrates better performance stability compared to the SiO2/PTFE composite. The high wear resistance is attributed to the formation of tribofilms at the friction interface. For the α-Al2O3/PTFE, an island-like tribofilm is formed with a thickness ranging from 100 to 200 nm, while the tribofilm of the SiO2/PTFE composite is thinner, measuring approximately 50 to 100 nm, and manifest a striped pattern. The chemical composition, both at the surface and subsurface levels, as well as the morphology of the tribofilms were studied using FTIR spectrometry, X-Ray photoelectron spectroscopy (XPS), and FIB-TEM. It is found that the difference in thickness and microstructure of the tribofilms for the two composites is mainly due to the tribochemistry of the nanoparticles. The α-Al2O3 nanoparticle plays a "cohesion" role during the formation of the tribofilm, which facilitates the formation of a thicker, more uniform, and stronger adhered tribofilm on the metallic counterpart, making it more robust against higher shear stress.

Intermetallic compounds are increasingly being expected to utilize in tribological environments, but to date the works are hindered by insufficient ductility at low and medium temperature. This paper presents a novel multiphase intermetallic alloy with the chemical composition of Mo-40Ni-13Si (at.%). Microstructure characterization reveals that a certain amount of ductile Mo phases formed during the solidification process of ternary Mo-Ni-Si alloy melt, which is undoubtedly beneficial to the ductility improvement of intermetallic alloy. Tribological properties of the designed alloy, including wear resistance, friction coefficient and metallic tribological compatibility, were evaluated under dry sliding wear test conditions at room temperature. Results suggested that the multiphase alloy possesses an excellent property for room-temperature wear applications, which is attributed to the unique microstructural features and thereby good combination in hardness and ductility. The corresponding wear mechanism is also reported by observing the worn surface, subsurface and wear debris of alloy, which to be found is soft abrasive wear.

Benign design of alkali-activated slag/FA geopolymer paste has intriguing increasing attention for optimizing its service performance. Therefore, the replacement of fly ash (FA) with 10 wt% silica fume (SF) is investigated by mechanical strength after freeze-thawing cycles and microstructure characterization. The results show that an appropriate dosage (30 wt%) of slag is necessary to attain alkali-activated slag/FA geopolymer paste with excellent mechanical performance, and the SF/slag/FA (SF: slag: FA= 10:30:60, wt%) geopolymer paste exerts the compressive and flexural strength of 95.2 and 3.2 MPa, respectively. Meanwhile, the doped 10 wt% SF facilitates the propagation of (N, C)-A–S–H chains, rather than the formation of C-S-H gels, evidenced by the absent exothermic peak at about 861oC from the differential scanning calorimetry (DSC) curves, leading to the increases in the pores volume with a pore diameter<20 nm and tortuosity by mercury intrusion porosimeter (MIP) results, corresponding to an improved freezing-thawing resistance with the residual compressive strength of 52.8 MPa and the weight loss of 10.5% after 300 freeze-thawing cycles. It explores a cost-effective and benign facile approach to designing heating curing-free alkali-activated slag/FA geopolymer paste with good freezing-thawing resistance.

Recycling of metallurgical solid waste has intriguing increasing attention for fabricating cementitious materials, due to its low-carbon emission, cost-effectiveness, and environmental conservation. Herein, the effects of silica fume (SF) on the microstructure and mechanical properties of alkali-activated slag/FA (fly ash) pastes subjected to elevated temperatures (150, 500, 850, and 1200℃) are investigated, to clarify the fact that whether or not the SF generates positive roles in mechanical properties of slag/FA geopolymers. The results show that the replacement with 10 wt% SF (silica fume) promotes the increasing pore volume with a diameter of 0.2~3 μm at room temperature, leading to an increase in the compressive or flexural strength, “right shifts” of endothermic peak and the initial-final temperature of mass loss, presenting a denser and compact fracture surface. Meanwhile, the mineral phase of gehlenite and labradorite emerges after exposure above 850℃ from the XRD results. Furthermore, the bloating effect of the incorporated SF occurs due to the formation of a liquid phase altogether with the amorphous silicates after exposure to 1200℃, leading to a greater deformation and enhancement of restructuring involved in the [SiO4]4− and [AlO4]5−. It explores an effective recycling approach for fabricating paste binders using metallurgical solid wastes.

In this work, a ZIF-67/MWCNTs/Nafion sensor platform was constructed based on the good adsorption capacity of ZIF-67, the electrical conductivity of multiwalled carbon nanotubes (MWCNTs) and the excellent chemical stability of Nafion for the detection of Cu2+ in water. Meanwhile, the modified materials were characterized by scanning electron microscopy (SEM), Transmission electron microscopy (TEM), BET specific surface area test, X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD) and Fourier transform infrared spectrometry (FT-IR). Cyclic voltammetry (CV), electrochemical impedance (EIS), and square wave solvation voltammetry (SWSV) electrochemical methods were used to perform applied test studies on ZIF-67/MWCNTs/Nafion/GCE. The results show that ZIF-67/MWCNTs/Nafion/GCE has high sensitivity (57.5 μA/μM) and a low limit of detection (15.0 nM) for the electrochemical detection of Cu2+ ions in an electrochemical sensing system. It has high adsorption selectivity for Cu2+, and the recovery of Cu2+ in real water reached 98.6%-103%. The modified electrode has good repeatability, reproducibility, anti-interference, and stability, which makes this sensing platform can be practically applied to the detection of domestic water.

Recently, a high internal surface of the titanium alloy pipe is required due to the increment of various applications of the pipe such as aerospace. However, the traditional machining process is unable to effectively polish the internal surface of the slender pipe. Thus, a vertical magnetorheological polishing (VMRP) apparatus is carried out in this work to implement high polishing performance on the internal surface of the titanium alloy pipe. The polishing process is realized by the combination of the rotating motion of the pipe and the reciprocating linear motion of the polishing head. Moreover, a series of comparative experiments are conducted to investigate the polishing mechanism of magnetorheological (MR) fluid and enhance the polishing performance. It is shown from the experimental results that proposed VMRP approach exhibits the better polishing performance than the conventional horizontal MR polishing method under same testing conditions. This is because the proposed VMRP method well eliminates the traces of polishing particles owing to the combination of polishing particles with different sizes. In addition, it is identified from the experimental test that the polishing time of the VMRP required to achieve the same polishing effect as the conventional method is shortened under the combination of different rotation speeds. It is identified from the above benefits of the VMRP that the final surface roughness after polishing is below 0.05 μm.

Crystallization often occurs in the laser welding of amorphous alloys, reducing the amorphous alloys’ properties. So, it is necessary to simulate the temperature field curve of the welding area by computer and then determine the power and laser moving speed of laser welding. In this paper, the temperature field curve of Zr41.2Ti13.8Cu12.5Ni10Be22.5(Vit1) amorphous alloy in laser welding is obtained by finite element analysis. The continuous heating curve (CHT) of Vit1 is fitted by the Vogel-Fulcher-Tammann (VFT) equation and the Kissinger equation. If the temperature field curve intersects with the CHT curve, crystallization occurs. The experiment results show that the VFT equation can be used to predict the crystallization of Vit1 better in laser welding. The tem-perature and welding time are increased by using low welding speed. Therefore, the temperature of the weld zone cannot fall in time, resulting intersection of the temperature field curve and the CHT curve. So, crystallization can be avoided if the welding speed is controlled within a rea-sonable range, and the highest temperature is kept under the CHT curve.

A large number of studies have concluded that since housing pressure will affect the mobility of highly skilled young migrants (HSYM) in Chinese cities and regions, it is necessary to apply corresponding housing policies to adjust housing unaffordability for HYSM. This study uses a survey data conducted in China's Zhejiang Province of China, where specific policies have been implemented to attract talent and found that housing does crowds out the HSYM from a city, but the HSYM who have a master's degree or above or who work in government organizations or state-owned enterprises are more tolerant of housing unaffordability. The unmarried or those staying in the city for a long period are less tolerant of housing unaffordability. Meanwhile, there are the heterogeneous impacts of factors on the HSYM's tolerance for housing unaffordability across cities of different levels. Therefore, housing policies should highlight urban differences and intra-group differences.

Double suction centrifugal pump installed along the Yellow River faces the serious sediment erosion due to the high sediment content which cause the poor operation efficiency of pump unit. The particle motion characteristics and erosion characteristics in the pump under different flow rates and different particle concentrations were numerically simulated based on the particle track model of solid-liquid two-phase flow. The results show that the flow rate has a significant effect on the particle tracks and the erosion caused by the particles in the impeller. The total erosion rate is positively correlated with the flow rate, and increases with the increase of flow rate. The vortex and secondary flow in the impeller have obvious influence on the particle trajectory, which increases the particle concentration at the trailing edge of the pressure surface and intensifies the impact erosion in this area. The particles carried by the vortex intensifies the local erosion. The particle concentration mainly affects the erosion rate, but has little effect on the erosion position. The in-fluence of flow rate on the pump erosion is greater than that of the particle properties. These results provide a reference for optimization of the design of anti-erosion blades of the double-suction pump and regulation-operation of pumping station.

In this paper, the effect of microstructure on the thermal conductivity of plasma-sprayed Y₂O₃ stabilized ZrO₂ (YSZ) thermal barrier coatings (TBCs) is investigated. Nine freestanding samples deposited on aluminum-base superalloy are studied. Cross-section morphology such as pores, cracks, m-phase content, grain boundary density of the coated samples are examined by scanning electron microscopy (SEM) and electron back-scattered diffraction (EBSD). Multiple linear regressions are used to develop quantitative models which describe the relationship between the particle parameters, m-phase content and the microstructure such as porosity, crack-porosity, the length density of small-angle-crack and the length density of big-angle-crack. Moreover, the relationship between microstructure and thermal conductivity is investigated. Results reveal that the thermal conductivity of the coating is mainly determined by the microstructure and grain boundary density at room temperature (25 ℃) and by the length density of big-angle-crack, monoclinic phase content and grain boundary density at high temperature (1200 ℃).

We analyzed the plant-litter-soil continuum to investigate the carbon and nitrogen distribution and ecological stoichiometry of an evergreen broad-leaved forest at Dagangshan Mountain, Jiangxi. The results showed that the average C and N contents and C:N ratios in the leaves and fine roots among 6 different tree species were 401.87g/kg, 21.41g/kg, 19.27 and 348.64g/kg, 15.73g/kg, 23.97, respectively; the average C and N contents and C:N ratios were 323.06 g/kg, 12.76 g/kg, 25.58 respectively in leaf litter, and 16.40 g/kg, 1.09 g/kg, 16.27 respectively for soil. In contrast with the C content, the total N content of the fine roots and litter had a high coefficient of variation and a high spatial heterogeneity. We ranked the six different representative tree species according to total C and N content in leaves and fine roots. The results for each species were generally consistent with each other, showing a positive correlation relationship between total C and N content in the leaves and roots. Among them, S. discolor (Champ. ex Benth.) Muell. plants displayed high carbon and nitrogen storage capacities, and on the other hand, C. fargesii Franch., C. myrsinifolia (Blume) Oersted, A. fortunei (Hemsl.) Makino, and V. fordii (Hemsl.) Airy Shaw showed a high nitrogen transfer rate. Total soil N and C decreased with depth. Soil organic carbon (SOC), soil resistant organic carbon (ROC), total N, alkali nitrogen, NH4+-N and NO3--N contents were all also negative correlated with soil depth, but the contents of the NH4+-N and NO3--N did not change significantly; The spatial distribution of soil NO3--N was significantly heterogeneous. At 0-10 cm soil depth, SOC was positively correlated with alkaline nitrogen, and at 10-20 cm soil depth, SOC was significantly positively correlated with total N. In general, when soil carbon was abundant, nitrogen supply capacity was also high.

Klebsiella pneumonia (K. pneumoniae) is a Gram-negative bacterium that causes nosocomial infections in the lung, bloodstream, and urinary tract. Therefore, detecting K. pneumoniae in early time is important in preventing severe infections. However, clinical detection of K. pneumoniae requires a long time of agar plate culture. Nucleic acid detection like qPCR is precise but requires expensive equipment. Recent research reveals that collateral cleavage activity of CRISPR-LbCas12a has been applied in nucleic acid detection. In this study, PCR combined with CRISPR-LbCas12a targeting the K. pneumoniae system was established. This system showed excellent detection specificity and sensitivity in both bench work and clinical samples. Due to its advantages, its application can meet different detection requirements in health centers where qPCR is not accessible.

Compared with ordinary asphalt pavement, the application of modified asphalt will improve the performance of asphalt pavement. However, using the same modification method for the whole road section can cause modification waste or result in some parts not meeting performance standards. This paper proposes a whole road section modification method. First of all, a finite element model was established using Abqus according to the actual road pavement material to analyze the mechanical response of each layer under different working conditions and establish the grading standard under comprehensive working conditions. Secondly, different modification methods were analyzed according to investigation and their modification effects were graded through clustering analysis method. Finally, different working conditions and different modification methods were reasonably matched and a section of highway was selected for verification. The results show that before modification, the calculated rutting is 6.23mm and after modification, it is reduced to 2.45mm which indicates that reasonable modification has a better effect and can achieve the purpose of rutting equalization control on the whole road section. It is of great significance to carry out reasonable modification on different conditions to control rutting equalization of asphalt pavements.

The study of mechanical properties of rock mass can be effectively carried out through rock-like material model test. The similarity of mechanical properties between rock-like material and protolith is dependent on the appropriate selection of composition and content of rock-like materials. In this research, X-Ray diffraction test was conducted to analyze the composition of deep rock, which confirmed silica, quartz, and dolomite as the primary components of deep sandstone. An orthogonal design test was used to execute the ratio test of rock-like material. River sand was used as an aggregate, cement as a binder, gypsum powder as a regulator, and polystyrene foam (EPS) as rock damage simulation material. The influencing factors considered in the orthogonal mechanical tests were the proportion of aggregate and binder, ratio of binder and regulator, quantity of damage simulation material, and size of damage simulation material. Three levels were set for each factor, and mechanical parameters such as compressive strength, tensile strength, elastic modulus, axial strain, and Poisson's ratio were tested for each group of samples. The changes of those parameters with the levels of the above four factors were studied. The study revealed that adjusting the size of polystyrene foam (EPS) can adjust the values of elastic modulus, tensile strength, and Poisson's ratio of rock-like material. Similarly, changing the ratio of binder and regulator can adjust the values of axial strain and compressive strength of rock-like material. The rock-like material developed in the study can simulate the mechanical properties of different rock masses such as granite, sandstone, shale, and limestone.

To improve water injection effect, microemulsions (MEs) were used to wet coal seam compared with water and sodium dodecyl sulfate solution (SDS). Wetting effects were characterized by contact angle, X-ray diffraction, Fourier infrared spectroscopy. The results showed that the microemulsion has better spreadability on coal surface and has stronger wettability for coals of different ranks and different particle sizes than traditional wetting agents. The W/O type microemulsion is more affinity to coal than the O/W type and the bicontinuous type.Oxygen and hydrogen contents contributed to wetting. Different wetting agents have the greatest impact on the oxygen-containing functional group absorption zone of coal, but have little impact on the change of clay mineral composition.As the content of quartz increased, the content of montmorillonite was decreased, and the hydrophilicity of coal was increased. This research proposes new ideas for solving coal dust problems and reducing coal mine disasters.

Regional Climatic Comfort Index (CCI) deteriorated significantly due to the climate change and anthropogenic interference. Knowledge regarding the long-term temporal dynamics of CCI in typical regions should be strengthened. In this study, we analyze the temporal and spatial evolution of CCI from 1969 to 2018 in Guangdong Province, based on meteorological indicators, including heat, humidity, wind and cloth loading etc.. Additionally, the population exposure to climate unconformity was examined since 1990 with the help of population data. Our study found that: (1) the warming and humidifying of the summer climate served as the main driving force for the continuous deterioration of CCI, with the comfortable days decreased by 1.06d/10a and the extremely muggy days increased by 2.83d/10a; (2) spatially, the lowest climate comfortability concentrated in southwestern Guangdong with more than 50 uncomfortable days each year, while the climate comfortability in northeastern Guangdong tends to deteriorated whit higher rate, which can reach as high as 6d/10a; (3) in summer, the population exposure to uncomfortable climate highly centralized in the Pearl River Delta, Shantou, Jieyang, and the surrounding areas, and both area and population exposure showed increasing trends. Particularly, Shenzhen held the highest growth rate of population exposure with an increase rate of 2.94 million/10a; (4) although the discomfort distribution and deterioration rate vary across the province, the spatial heterogeneity of comfortability is diminishing in Guangdong Province. This study will provide scientific reference for regional urban planning, thermal environment improvement, local resident health risk analysis, and key strategy implementation, etc.

Plants of the genus Monochoria have long been utilized in food, cosmetics, and traditional herbal treatment. Thailand has the highest species diversity of this genus and a new member, Monochoria angustifolia (G. X. Wang) Boonkerd & Tungmunnithum has been recently described. This plant is called “Siam Violet Pearl” as a common name or “ไข่มุกสีม่วงแห่งสยาม” as its vernacular name in the same meaning in Thai language. Despite their importance, few researches on Monochoria species have been conducted. This study, thus, provided the results to fill in this gap by: i) determining flavonoids phytochemical profiles of 25 natural populations of M. angustifolia covering the whole floristic regions in Thailand, and ii) determining antioxidant activity using various antioxidant assays to investigate the probable mechanism. The results revealed that M. angustifolia presented a higher flavonoid content than the outgroup, M. hastata. Our results also revealed that flavonoids might be used to investigate Monochoria evolutionary connections and for botanical authentication. The various antioxidant assays revealed that M. angustifolia extracts preferentially act through a hydrogen atom transfer antioxidant mechanism. Pearson correlation analysis indicated significant correlations emphasizing that the antioxidant capacity is most probably the result of a complex phytochemical combinations rather than of a single molecule. Altogether, these results showed that this new species provide an attractive alternative starting material with phytochemical variety and antioxidant potential for the phytopharmaceutical industry.

Intelligent systems are increasingly present in various areas of society, gaining special relevance in healthcare environments. In this work, grounded on previous developments proposed by the authors, the evolution and improvement of a novel intelligent system focused on the diagnosis of obstructive sleep apnea (OSA) is addressed. To do this, starting from two packages of information of a heterogeneous nature, and deploying a set of Machine Learning classification algorithms, focused each of them on different levels of the apnea-hypopnea index (AHI), as well as a set of cascaded expert systems, it is possible to obtain a series of risk metric pairs (Statistical Risk, Symbolic Risk) for each AHI level, understood as a warning forecast associated with the early detection of the pathology. The risk indicators of each pair are subsequently aggregated by means of a symbolic inference system, whose knowledge base was determined using the automatic rule generation approach proposed by Wang and Mendel. At the output of each inference system, a risk indicator is obtained for each AHI level, the Apnea Risk, whose interpretation makes it possible to discriminate between patients who could suffer OSA and those who do not, as well as to generate the appropriate recommendations. For the initial tests of the system, the design and development of a specific software artifact was carried out using data from 4,400 patients from the Álvaro Cunqueiro Hospital in Vigo, obtaining when applied to the test set AUC values within the range 0.74–0.88, which invites optimism and points to the benefits expected from the architecture of the proposed intelligent system.

Salinity acts as a critical environmental filter on microbial communities in natural systems, negatively affecting microbial diversity. However, how salinity affects the community assembly remains unclear. This study used Wendeng multi-pond saltern as a model to evaluate the prokaryotic community composition and diversity and quantify the relative importance of ecological processes across salinity gradients. Results showed that low saline salterns (45-80 g/L) exhibited higher bacterial diversity than those in high saline salterns (175-265 g/L). The relative abundance of taxa assigned to Halanaerobiaceae, Haloferacaceae, Desulfohalobiaceae, Phormidiaceae, Rohodobacteraceae, and Nitrococcaceae was higher with increasing salinity. Salinity and pH were the primary environmental factors that directly or indirectly determined the composition and diversity of prokaryotic communities. Microbial co-occurrence network dynamics were more complex in the sediment than in water of salterns. An infer Community Assembly Mechanisms by Phylogenetic-bin-based null model analysis (iCAMP) showed that microbial community assembly in sediment and water differed. Our findings provide more information about microbial community structure and the importance of various ecological processes in controlling microbial community diversity and succession along salinity gradients in water and sediment environments.

Ce-promoted NiMgAl mixed-oxide (NiCex-C, x = 0, 1,5,10) catalysts were prepared from the quaternary hydrotalcite precursors for CO2 hydrogenation to methane. By engineering the Ce contents, NiCe5-C showed its prior catalytic performance in low-temperature CO2 hydrogenation, being about 3 times higher than that of Ce-free NiCe0-C catalyst (TOF of NiCe5-C and NiCe0-C: 1.19 h-1 vs 0.39 h-1 @ 250 oC). With extensive characterization, it was found that Ce dopants promoted the reduction of NiO by adjusting the interaction between Ni and Mg(Ce)AlOx support. The higest ratio of surface Ni0/(Ni2+Ni0) was obtained over NiCe5-C. Meanwhile, the surface basicity was tailored with Ce dopants. The strongest medium-strength basicity and highest capacity of CO2 adsorption was achieved on NiCe5-C with 5wt% Ce content. The TOF tests indicated a good correlation with medium-strength basicity over the NiCex-C samples. The results showed that the high medium-strength and Ce-promoted surface Ni0 species endows the enhanced low-temperature catalytic performance in CO2 hydrogenation to methane.

The COVID-19 pandemic has now become very severe as never before due to the overwhelming spread of Omicron. We found that Omicron outbreak can be effectively prevented by inactivated vaccines, which averted an outbreak of more than 1.6 million people in Hangzhou, China. The 36 mutations in the target spike protein of Omicron neutralizing antibody enable it to evade the immune protection afforded by vaccines. This is because that mRNA and adenovirus-vector vaccines are designed to recognize the spike (S) glycoprotein of the SARS-CoV-2 wild-type (WT) strain. However, Inactivated vaccines contain the whole viral antigens and remain stable in their recognition of newly emerging variants of SARS-CoV-2. Our study confirmed the advantage of inactivated vaccines in the face of highly mutated Omicron variant and provided a basis for the development of effective vaccines to prevent future long-term transmission, mutation and recurrence of SARS-CoV-2.

Due to the intermittency and fluctuation of photovoltaic (PV) output power, a high proportion of grid-connected PV power generation systems has a significant impact on power systems. Accurate PV power forecasting can alleviate the uncertainty of the PV power and is of great significance for the stable operation and scheduling of the power systems. Therefore, in this study, a feature rise-dimensional (FRD) two-layer ensemble learning (TLEL) model for short-term PV power deterministic forecasting and probability forecasting is proposed. First， based on the eXtreme Gradient Boosting (XGBoost), Random Forest (RF), CatBoost, and Long-short-term memory (LSTM) models, a TLEL model is constructed utilizing the ensemble learning algorithm. Meanwhile, the FRD method is introduced to construct the FRD-XGBoost-LSTM (R-XGBL), FRD-RF-LSTM(R-RFL), and FRD- CatBoost - LSTM (R-CatBL) models. Subsequently, the above models are combined to construct the FRD-TLEL model for deterministic forecasting, and perform probability interval forecasting based on quantile regression(QR). Finally, the performance of the proposed model is demonstrated with a real-world dataset. By comparing with other models, the proposed model displays better forecasting accuracy for deterministic forecasting and reliable forecasting intervals for probability forecasting, and good generalization ability in the datasets of different seasons and weather types.

Dredging is a common technique for managing eutrophication problems in waters, reducing the accumulation of pollutants by removing sediments from the bottom of water bodies. However, dredging can cause complex impacts on lake ecosystems, and it is crucial to understand benefits and mechanisms for environments. In this paper, the dredged and undredged areas in the Caohai portion of Dianchi Lake were studied to analyze the effects of dredging on nitrogen-phosphorus transport and conversion and changes in nitrogen-phosphorus morphology content and its mechanisms by comparing the nitrogen-phosphorus morphology content, percentage; nitro-gen-phosphorus ratio, and release contribution of the two areas. It was found that the ratio of sta-bilized nitrogen (SN) to stabilized phosphorus (SP) in the dredged area was lower than that in the non-dredged area; the BD-P and TOC contents had a large turnaround at the 16-20 cm position of the sediment in the dredged area; and the main conclusions were that the dredging would disrupt the internal equilibrium of the lake system for many years, and in particular, it would have the greatest effect on the balance of the BD-P in the phosphorus forms of the sediment, and that the column cores of the dredged area from 0 to 16 cm might be newly accumulated sediments after the dredging project. However, with time, the distribution of nitrogen and phosphorus forms in the newly accumulated sediments will gradually reach a new equilibrium. In addition, dredging will also cause significant changes in the retention efficiency of nitrogen and phosphorus in the sediment, and the stable nitrogen and phosphorus forms will be released and transformed into unstable ni-trogen and phosphorus forms.

Bees (Apoidea), the largest and most crucial radiation of pollinators, play a vital role in ecosystem balance. Transposons are widely distributed in nature and are important drivers of species diversity. However, transposons are rarely reported in important pollinators such as bees. Here, we surveyed 37 genomes in Apoidea, annotated the pogo and Tc1/mariner transposons in the genome of each species and performed a phylogenetic analysis to determine their overall distribution. The pogo and Tc1/mariner families showed high diversity and low abundance in the 37 species, and their proportion was significantly higher in solitary bees than in social bees. DD34D/mariner was found to be distributed in almost all species and was found in Apis mellifera, Apis mellifera carnica, Apis mellifera caucasica and Apis mellifera mellifera and Euglossa dilemma may still be active. Using horizontal transfer analysis, we found that DD30D/Tigger, DD33D/Tigger and DD34D/mariner may have experienced horizontal transfer events. The current study displayed the evolution profiles (including diversity, activity, and abundance) of the pogo and Tc1/mariner transposons across 37 species of Apoidea. Our data revealed their contributions to the genomic variations across these species and facilitated in understanding of the genome evolution of this lineage.

Abstract: This study aims to set up a system to evaluate nursing competencies in disaster preparedness for undergraduates and influencing factors in China. The evaluation system was established by using the modified Delphi. There were 3 phases in this study: 1) an environmental scan; 2) setting framework; 3) adjusting indicators based on the modified Delphi. The questionnaire for these undergraduates lied in their basic information and assessment of nursing competencies in disaster preparedness. Based on the survey, the average score of nursing competencies in disaster preparedness for undergraduate nursing students surveyed was 3.10 (out of 5). In addition, gender, grade, inhabitation, and disaster drills of the students were four factors affecting nursing competencies of undergraduates. This study indicates that the present nursing competencies in disaster preparedness for undergraduates are weak, and it is essential to strengthen nursing education in disaster preparedness for undergraduates.

A full connected world is expected to gain in the 6th generation mobile network (6G). As a typi-cal fully connected scenario, the internet of vehicle (IoV) enables intelligent vehicle operations via artificial intelligence (AI) and edge computing technologies. In the future of vehicular net-works, wide variety of services need powerful computing resources and higher quality of ser-vice (QoS). Existing resources are insufficient to match these requirements. Aim to this problem, An intelligent service offloading framework is provided. Based on the framework, an Algorithm of Improved Gradient Descent (AIGD) is created to accelerate the speed of iteration. So, the con-vergence of convolutional neural network (CNN) based on AIGD is able to be accelerated too. Then, an Algorithm of convolutional long short-term memory (CN_LSTM) Based Traffic Predic-tion (ACLBTP) is designed to gain the predicted number of vehicles belonged to the edge node. At last, an Algorithm of Service Offloading Based on CN_LSTM (ASOBCL) is conducted to of-fload these services to the vehicles belonged to the edge node. In ASOBCL, sorting technique is adopted to speed up the offloading work. Simulation results demonstrate the fact that the pre-diction strategy designed in this paper has high accuracy. The low offloading time and main-taining stable load balance is gained via running ASOBCL. Low offloading time means short response time. And, the QoS is guaranteed. So, these strategies designed in this paper are effec-tive and valuable.

In this work, thermo-responsive block copolymer brushes modified graphene oxide (GO) nanohybrid was fabricated successfully via the host-guest interaction between β-cyclodextrin functionalized GO and azobenzene-terminated PNIPAM-b-P(St-co-MQ). The block copolymer was synthesized using reversible addition fragmentation chain transfer (RAFT) polymerization based on the monomers of N-isopropylacrylamide (NIPAM), 5-(2-methacryloyl-ethyloxymethyl) -8-quinolinol (MQ), styrene (St) and an azobenzene functional RAFT agent. The 8-hydroxyquinoline units containing in the block polymer can coordinate with CdSe/ZnS quantum dots(QDs) to form a CdSe/ZnS QDs-block copolymer brushes modified graphene oxide fluorescence nanohybrid (QDs/polymer/GO fluorescence nanohybrid) and the resulting fluorescence nanohybrid had a robust temperature responsive property which result from the change in the PNIPAM conformation in the block copolymer on the surface of GO.

This study describes a novel method for grading pathological sections of gliomas. Our own integrated hyperspectral imaging system was employed to characterize 270 bands of cancerous tissue samples from microarray slides of gliomas. These samples were then classified according to the guidelines developed by the World Health Organization, which define the subtypes and grades of diffuse gliomas. We explored a hyperspectral feature extraction model called SMLME-Resnet using microscopic hyperspectral images of brain gliomas of different malignancy grades. The model combines the channel attention mechanism and multi-scale image features to automatically learn the pathological organization of gliomas and obtain hierarchical feature representations, effectively removing the interference of redundant information. It also completes multi-modal, multi-scale spatial and spectral feature extraction to improve the automatic classification of glioma subtypes. The proposed classification method demonstrated high average classification accuracy (>97.3\%) and Kappa coefficient (0.954), indicating its effectiveness in improving the automatic classification of hyperspectral gliomas. The method is readily applicable in a wide range of clinical settings, offering valuable assistance in alleviating the workload of clinical pathologists. Furthermore, the study contributes to the development of more personalized and refined treatment plans, as well as subsequent follow-up and adjustment of treatment, by providing physicians with insights into the underlying pathological organization of gliomas.

The production of plants and crops is influenced by environmental stress, which is a serious scientific issue. Cotton is an essential crop for producing natural fibers that are used to make biofuel and edible oils. Salinity is the main element that influences cotton growth during the beginning of germination. The type of salt and the growth stage affects how sensitive a plant is to salt stress. Developing ways to enhance cotton performance in salty circumstances can be aided by an understanding of the response of cotton to salt, its mechanism of resistance, and its management methods. Osmotic and ionic imbalances originate due to the deposition of soluble salts under salinity stress in the plant's root zone. Soil salinity significantly reduces plant growth due to several factors, such as nutritional ion imbalance, which reduces K+, PO4-, and NO- absorption, excessive salt chloride concentrations, and osmotic stress, which hinders water availability. Research has revealed that compared to subsequent stages, the germination, emergence, and seedling phases are more vulnerable to salinity stress, which ultimately affects the seed cotton yield by delaying blooming, reducing fruiting positions, shedding fewer fruits, and reducing boll weight. The morphology, growth of cotton roots, shoots, yield, and fiber quality are all strongly impacted by salinity stress. It slows down plant feeding, cellular metabolism, and photosynthesis. The soil, water, and climate all affect how the plant responds to salinity stress. During salt stress, excessive exclusion of sodium or its compartmentalization is the key adaptation process in cotton. A major adaptive potential to create cotton types that can withstand salt is provided by the up-regulation of both physicochemical and non-enzymatic antioxidant genes. A successful strategy to increase cotton germination in saline soils is seed priming. Moreover, the transgenic strategy might be a viable choice for improving cotton yield in saline environments. Our review focuses on the impacts of salinity on cotton productivity as well as how plants react to salt stress. It also clarifies recent genetic advancements and molecular breeding for cotton's resistance to soil salt. To create salt-tolerant cultivars, a combination of traditional breeding and novel molecular approaches will be useful.

Video quality assessment (VQA) plays an important role in video applications for quality evaluation and resource allocation. It aims to evaluate the video quality consistent with the human perception. In this letter, a hierarchical gradient similarity based VQA metric is proposed inspired by the structure of the primate visual cortex, in which visual information is processed through sequential visual areas. These areas are modeled with the corresponding measures to evaluate the overall perceptual quality. Experimental results on the LIVE database show that the proposed VQA metric significantly outperforms the state-of-the-art VQA metrics.

Percutaneous kyphoplasty (PKP) is a highly successful treatment option for Kümmell's disease (KD). Due to the obstruction of the fibrocartilaginous membrane at the periphery of the intervertebral vacuum cleft (IVC) and inadequate osteointegration of conventional bone cement, there is insufficient locking strength between trabecular bone and bone cement in Kümmell's disease (KD), leading to postoperative displacement of the bone cement and sub-sequent early surgical failure. However, there is no standard strategy managing this complica-tion at present. We reported a rare case of premature bone cement displacement resulting in adjacent vertebra fracture. An 80-year-old male with Kümmell's disease at T10 received per-cutaneous kyphoplasty (PKP) with bone cement leaking into the upper disc. Only 3 days after the surgery, the patient complained of severe back pain again. X-ray and MRI showed bone cement displacement at T10, adjacent vertebra fracture at T9. In consideration of poor toler-ance of open surgery for the old patient, we successfully revised by using percutaneous ky-phoplasty with multi-point anchoring technique (A-PKP). During a 10-month postoperative follow-up, the patient reported pain relief. X-ray and three-dimensional CT scan revealed no obvious progress of bone cement displacement. Although the exact mechanism underlying this rare complication remains unclear, we observed that the premature bone cement dis-placement can result in adjacent vertebra fracture especially when the pattern of bone cement is blocky. Percutaneous kyphoplasty with multi-point anchoring technique (A-PKP) appears effective in managing this complication.

In the field of clinical medicine, the real-time monitoring of carbon dioxide gas exhaled by the human body is of great significance. At present, the detection devices in the market are mainly detected by sucking a small amount of gas in the nasal cavity to the detection device, and there are some problems such as too long sampling tubes, easy blockage or distortion, and abnormal gas dispersion. In this paper, a micro-nano optical fiber sensor that can directly detect the concentration of end-tidal carbon dioxide is proposed. The measurement is achieved by using the principle of high evanescent field absorption, and the operating band is 2.004 μm. The sensor uses micro-nano optical fiber as the sensing area, and then detects the presence of carbon dioxide gas exhaled by human body through optical power attenuation. The function of micro-nano fiber is to realize the transmission of signal light and also serve as the absorption medium of the gas to be measured. In addition, the variation of light power also reflects the respiratory cycle of the human body. The sensor can realize rapid real-time response to carbon dioxide gas detection, with small size, low cost, and easy to replace. It has great application potential in clinical scenarios such as Gastrointestinal Endoscopes that require real-time monitoring of human respiration.

Declining agricultural productivity caused by soil salinization are becoming global dilemmas in recent years. Biofertilizers show great potential as a sustainable and environmentally friendly fertilization strategy for soil improvement, but their effectiveness for saline soil amendment and improving plant growth under saline stress is not well understood. Assess the effectiveness of biofertilizers in improving saline soils and enhancing crop growth under saline stress, as well as investigate its related potential mechanisms. Changes in soil physico-chemical properties, plant physiological parameters and soil microbial communities were analyzed through pot experiments. The results showed that the application of biofertilizer reduced total soluble salts (TSS) in soil by 30.8% and increased the Brassica rapa L. biomass by 8.4 times. Biofertilizer application increased soil organic matter (SOM), total nitrogen (TN) and available phosphorus (AP). Biofertilizer applications also increased the SOD, CAT, chl.a, chl.b, total soluble sugars, and Proline content. Biofertilizers present plant growth promotion and potential pathogenic fungi reduction by increasing the abundance of Bacillus and Planococcus and decreasing the abundance of Mortierella and Aspergillus. Overall, the results of this study demonstrated the excellent efficacy of biofertilizers in improving saline soils, and the application of biofertilizer strategies will greatly promote agricultural production.

Iris laevigata Fisch. is a perennial aquatic plant with strong cold resistance and showy flowers. However, the flowering period of a single flower is only two days, greatly limiting its potential use in landscaping and the cutting-flower industry. In addition, I. laevigata is often challenged with various abiotic stresses including high salinity and drought in its native habitat. Thus, breeding novel cultivars with prolonged flowering time and higher resistance to abiotic stress is of high importance. In this study, we first performed genome-wide identification of WRKYs, key transcription factors in modulating flowering time and abiotic stress responses. We overexpressed IlWRKY22 in Arabidopsis thaliana and found the flowering time was delayed in the transgenic plants. Molecular characterization further revealed that IlWRKY22 promotes the expression of CO and GA20OX genes in the photoperiod and gibberellin pathways, respectively, and inhibits the expression of SPL3 in the aging pathway. We also created transgenic Nicotiana tabacum overexpressing IlWRKY22, which showed significantly improved resistance to both salt and drought compared to control plants. Specifically, the photosynthetic rate, maximum potential quantum efficiency of Photosystem II (Fv/Fm), and chlorophyll content were higher in the transgenic plants, which was accompanied with higher antioxidant enzyme activity and lower levels of reactive oxygen species. Thus, our study revealed a unique dual function of IlWRKY22, an excellent candidate gene for breeding novel I. laevigata cultivars of desirable traits.

Establishing an effective evaluation model to analyze the actual environmental level of the multi-indicator systems is an urgent challenge. However, due to the complexity of the environmental system, the factors that determine the practical system are usually interrelated. To solve this problem, many methods have been proposed and verified. However, the disadvantage of unreasonable weight determination and only single-indicator assessment limits the practical application of these analysis methods. Here, we established an optimized entropy weight model and integrate it with the fuzzy comprehensive evaluation (FCE) method to quantify the complex environmental system. By introducing the linear programming method into the entropy weight solution, we can obtain high accuracy weight values and strong resistance to extreme data. Theoretical and simulation results demonstrate that our method can enhance the precision of weight calculation and evaluation results for multi-factor systems. Our work develops an effective method to quantify the complex environment system comprehensively and is significant to real applications of evaluation method.

Civic participation is of great significance to urban management decision-making. In order to facilitate citizens to participate in city management decision-making, this paper proposes a large-scale group decision-making (LSGDM) method based on multi-granular probabilistic linguistic preference relations (MG-PLPRs). First, each decision maker selects a language terms set from the multi-granularity language terms set to represent individual preference relations and the MG-PLPRs are obtained by statistical calculation to represent sub-group’s preferences information. Then, an optimization model based on the expected consistency of PLPR and consensus measure of groups is established to achieving consensus reaching processes, which can ensure satisfactory individual consistency and group consensus. Finally, the validity and applicability of the proposed method is verified by a case of a city "shared garden" site selection with the participation of citizens.