This paper first discusses a fractional-order Liu system of order as low as 2.7 and shows its chaotic characteristics by carrying out numerical simulations such as Lyapunov exponents, bifurcation diagrams and phase portraits. Then, by using the topological horseshoe theory and computer-assisted proof, the existence of chaos in the system is verified theoretically. Finally, the fractional-order system is implemented on a Field Programmable Gate Array (FPGA) and the results obtained show that the fractional-order Liu system is indeed chaotic.

This article puts forward the bi-matrix games with crisp parametric payoffs based on interval value function approach. We conclude that the equilibrium solution of the game model can converted into optimal solutions of the pair of the non-linear optimization problem. Finally, experiment results show the efficiency of the model.

Earth observation satellites can capture images of specific areas in Earth's orbit based on user requirements. Despite the high demand for satellite imagery, satellites remain a scarce resource. When there are many observation tasks that are large and dense, they may interfere with each other due to satellite mobility. To address this issue, a multi-satellite scheduling algorithm based on a task merging mechanism has been proposed. This paper proposes a two-stage approach to the problem: task merging phase and merging task scheduling phase. The task merging phase introduces two methods based on Mean Shift and Complete Graph to generate the merging task set. In the merging task scheduling phase, a multi-satellite scheduling algorithm based on merging tasks is employed to solve the problem. Finally, certain measurement experiments suggest the effectiveness of the algorithm.

Monin-Obukhov similarity theory (MOST) overestimates wind shear in some atmospheric stable conditions, i.e. Richardson number $R_f<0.25$. The overestimated wind shear that leads to an under-predicted friction wind speed and a lower ambient turbulence intensity for a given hub-height reference wind speed and a given roughness length, could influence wake modeling of a wind turbine. This work investigates the side effects of the breakdown of MOST on wake modeling under stable conditions and makes some modifications to the flow similarity functions to eliminate these side effects. Based on a field measurement in a wind farm, we firstly show that MOST predicts a larger wind shear for the atmospheric stability parameter $\zeta>0.1$ and proposes new flow similarity functions without constraining $R_f$ to limit the overestimated wind shear by MOST. Next, different turbulence models based on MOST and a modified one based on the new similarity functions are investigated through numerical simulations. These turbulence models are combined with the actuator disk model (AD) and Reynolds-averaged Navier–Stokes equations (RANS) to model wind turbine wakes under stable conditions. As compared to measurements, numerical results show that turbulence models based on MOST result in larger wake deficits and slower wake recovery rate with a square root of the mean-squared-error (RSME) of wake deficit in the range of 0.07-0.18. This overestimated wake effect is improved by applying the new similarity functions and the RSME of wake deficit is averagely reduced by 0.05. Finally, we check the role of the under-predicted turbulence intensity playing in the larger wake deficit predicted by models based MOST. Additional numerical simulations using the modified turbulence model are carried out, in which the roughness length is reduced to impose a hub-height ambient turbulence intensity equivalent to the MOST case. Simulation results show that reducing turbulence intensity enhances wake effects, however, it cannot reproduce the large wake deficit predicted by models based on MOST, which suggests that the overestimated wake effect by MOST could be also related to the overestimated wind shear.

Lithium batteries are widely used due to their advantages such as high energy density, stable performance, low pollution, and long recyclable life. Accurate SOC estimation is important for the use of lithium batteries. To address the problem of low accuracy of SOC estimation by traditional methods, this paper proposes a joint method of fractional order robust unscented Kalman filter (FORUKF) and robust unscented Kalman filter (RUKF) to estimate SOC. The method is based on a fractional order model (FOM) that combines the unscented transformation (UT) technique, the H∞ observer and the joint estimator. Specifically, an adaptive genetic algorithm (AGA) was first used to identify the parameters of the FOM for lithium batteries and to verify the accuracy of the model. Estimation and updating of the ohmic resistance R0 and the capacity QN in the model in real-time by RUKF and then estimation of the SOC by FORUKF. Finally, the accuracy of FORUKF-RUKF was verified under the Federal Urban Driving Schedule (FUDS), US06 Highway Driving Schedule and Beijing Dynamic Stress Test (BJDST). According to the results, the FORUKF-RUKF estimated SOC was found to have better accuracy and robustness than the RUKF, FOUKF and EKF.

Atmospheric stability affects wind turbine wakes significantly. High-fidelity approaches such as large eddy simulations (LES) with the actuator line (AL) model which predicts detailed wake structures, fail to be applied in wind farm engineering applications due to its expensive cost. In order to make wind farm simulations computationally affordable, this paper proposes a new actuator disk model (AD) based on the blade element method (BEM) and combined with Reynolds-averaged Navier–Stokes equations (RANS) to model turbine wakes under different atmospheric stability conditions. In the proposed model, the upstream reference velocity is firstly estimated from the disk averaged velocity based on the one-dimensional momentum theory, and then is used to evaluate the rotor speed to calculate blade element forces. Flow similarity functions based on field measurement are applied to limit wind shear under strongly stable conditions, and turbulence source terms are added to take the buoyant-driven effects into consideration. Results from the new AD model are compared with field measurements and results from the AD model based on the thrust coefficient, the BEM-AD model with classical similarity functions and a high-fidelity LES approach. The results show that the proposed method is better in simulating wakes under various atmospheric stability conditions than the other AD models and has a similar performance to the high-fidelity LES approach however in much lower computational cost.

The increasing prevalence of obesity and sedentary lifestyles has led to an increased incidence of metabolic syndrome (MetS) worldwide. In Taiwan, middle-aged women are at a greater risk of MetS, type 2 diabetes, and cardiovascular disease than men are because they have more subcutaneous fat and larger waist circumferences compared to men with equal visceral fat levels. This study investigated the effects of calorie restriction supplemented with fish oil (CRF) in middle-aged women with MetS. For 12 weeks, 75 eligible participants were randomly assigned either calorie restriction (CR) or CRF. Both dietary intervention groups were further divided into two age groups: ≤45 and >45 years. The changes in MetS severity, inflammatory status, iron status, and red blood cell fatty acid profile were evaluated. Seventy-one participants completed the trial. Both dietary interventions significantly ameliorated MetS and improved the participants’ inflammatory status. CR significantly increased total iron binding capacity, whereas CRF increased hepcidin levels. Furthermore, CRF significantly increased the n-6/n-3 and arachidonic acid/docosahexaenoic acid ratios. In conclusion, CR and CRF improved the anthropometric and MetS characteristics of early-middle aged women, including body weight, blood glucose levels, triglyceride levels, as well as the scores for the homeostasis model assessment of insulin resistance and quantitative insulin sensitivity cheque index. Dietary intervention was more effective in >45-year-old women than ≤45-year-old women.

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.

Glioblastoma (GBM) is the most common malignant brain tumor in adults. Despite advancements in treatment, the prognosis for patients with GBM remains poor due to its aggressive nature and resistance to therapy. CRISPR-based genetic screening has emerged as a powerful tool for identifying genes crucial for tumor progression and treatment resistance, offering promising targets for tumor therapy. In this review, we provide an overview of the recent advancements in CRISPR-based genetic screening approaches and their applications in GBM. We highlight how these approaches have been used to uncover genetic determinants of GBM progression and susceptibility to various therapies. Furthermore, we discuss ongoing challenges and future directions of CRISPR-based screening methods in advancing GBM research.

When ground-penetrating radar is used to detect targets within concrete, the location of the targets, the identification of different shapes, properties and less obvious echoes all greatly increase the interpretation time of the staff and can easily cause misjudgment of the echo images. In this paper, the ground-penetrating radar echo images (B-scan) after processing are mean filtered to eliminate the direct waves that interfere greatly with the echoes. The RFB-s structure is added to the YOLOv3-SPP network structure, while the Anchor value is optimized and the EIOU loss function is introduced. For four types of data with different shapes and properties at random target locations, three models, YOLOv3, YOLOv3-SPP and the improved YOLOv3-SPP, are used for classification and identification, and the proposed algorithm models are comprehensively evaluated using model evaluation metrics. The experimental results show that the algorithm models proposed in this paper have good recognition effect in ground-penetrating radar echo image target detection.

After long years of development, the technology of analyzing the working condition of power units based on vibration signals has had relatively stable applications, but the accuracy and the degree of automation and intelligence for fault diagnosis are still inadequate due to the limitations of the current development of key technologies. With the development of big data and artificial intelligence technology, the involvement of new technologies will be an important boost to the development of this field. To support the subsequent research, bibliometrics is used as a tool to sort out the development of the technology in this field at the macro level; at the micro level, the classical and key literature is studied to grasp the development status at the technical level and prepare for the selection of entry points to continue in-depth innovation afterwards.

We have successfully synthesized a series of Bi doped BaFe2As2 high quality single crystals for the first time. The x-ray diffraction (XRD) patterns show an expansion of lattice parameter c with Bi doping, indicating a negative pressure effect. By investigating the resistivity, a Fermi liquid (FL) to non-Fermi liquid (NFL) crossover is observed from normal state to antiferromagnetic order state, accompanied by three superconducting transitions labeled as SC I, SC II and SC III which are supposed to be induced from three superconducting realms with various Bi concentration. Thus, the NFL behavior is proposed to be closely related with the presence of superconductivity. The magnetic susceptibility measurements further speculates that the SC I and SC III phases should be filamentary superconductivity while the SC II be a possible bulk superconductivity with TC 7 K.

Peanut (Arachis hypogaea) is a crop plant with high economic value, but the epigenetic regulation of its growth and development has only rarely been studied. The peanut histone deacetylase 1 gene (AhHDA1) has been isolated and is known to be ABA- and drought-responsive. In this paper, we investigate the role of AhHDA1 in more detail, focussing on the effect of altered AhHDA1 expression in hairy roots at both the phenotypic and transcriptional levels. Agrobacterium rhizogenes-mediated transformation of A. hypogaea hairy roots was used to analyse how overexpression or RNA interference of AhHDA1 affects this tissue. In both types of transgenic hairy root, RNA sequencing was adopted to identify genes that were differentially expressed, and these genes were assigned to specific metabolic pathways. AhHDA1-overexpressing hairy roots were growth-retarded after 20 d in vitro cultivation, and superoxide anions and hydrogen peroxide accumulated to a greater extent than in control or RNAi groups. Overexpression of AhHDA1 is likely to accelerate flux through various secondary synthetic metabolic pathways in hairy roots, as well as reduce photosynthesis and oxidative phosphorylation. Genes encoding the critical enzymes caffeoyl-CoA O-methyltransferase (Araip.XGB85) and caffeic acid 3-O-methyltransferase (Araip.Z3XZX) in the phenylpropanoid biosynthesis pathway, chalcone synthase (Araip.B8TJ0) and polyketide reductase (Araip.MKZ27) in the flavonoid biosynthesis pathway, and hydroxyisoflavanone synthase (Araip.0P3RJ) and isoflavone 2'-hydroxylase (Araip.S5EJ7) in the isoflavonoid biosynthesis pathway were significantly upregulated by AhHDA1 overexpression, while their expression in AhHDA1-RNAi and control hairy roots remained at a lower level or was unchanged. Our results suggest that alteration of secondary metabolism activities is related to overexpression of AhHDA1, which is mainly reflected in phenylpropanoid, flavonoid and flavonoid biosynthesis. Future studies will focus on the function of AhHDA1 interacting proteins and their action on cell growth and stress responses.

The shape of the knee is a chain-like structure of an ellipsoid. This suggests that, in the latest study, in addition to rolling, there is slippage in the motion of the knee. This paper selects a mechanical braking model for cattle based on two mechanical structures in different directions at the joints. The experimental results show that the modified dynamical system has strong chaotic properties. This can be one of the basis for judging various health states.

Many studies have focused on the impacts of rainfall duration and intensity while overlooking the role of rainfall patterns on intensive tillage erosion in hilly agricultural landscapes. The objective of this study was to determine the combined effects of rainfall patterns and intensive tillage erosion on surface runoff and soil loss on sloping farmland in the purple-soil area of China. Five simulated rainfall patterns (constant, rising, falling, rising-falling, and falling-rising) with the same total precipitation were designed, and the intensive tillage erosion treatment (IT) and no-tillage treatment (NT) were subjected to simulated rainfall using rectangular steel tanks (2 m × 5 m) with a slope of 15°. To analyse the differences in the hydrodynamic characteristics induced by tillage erosion, we calculated the flow velocity (V), Reynolds number (Re), Froude number (Fr), and Darcy-Weisbach resistance coefficient (f). The results indicate that significant differences in surface runoff and soil loss were found among different rainfall patterns and stages (P < 0.05). The falling pattern and falling-rising pattern had faster runoff-initiating times and larger sediment yields than those of the other rainfall patterns. f varied from 0.30 to 9.05 for the IT and 0.48 to 11.57 for the NT and exhibited an approximately inverse trend to V and Fr over the course of the rainfall events. Compared with the NT, the mean sediment yield rates from the IT increased the dynamic range of 8.34%–16.21% among different rainfall patterns. The net contributions of the IT ranged from 2.77% to 46.39% on surface runoff and 10.14%–78.95% on soil loss on sloping farmland. Surface runoff and soil loss were positively correlated with rainfall intensity, V, and Fr but negatively correlated with f irrespective of tillage intensive (P < 0.05). For varying-intensity rainfall patterns, soil and water loss fluctuated during rainfall events, suggesting that the changes in rainfall intensity and tillage intensity would result in drastic variations in soil hydrological characteristics and sediment transport mechanisms. The time sequences of rainfall intensity in each rainfall pattern significantly affected surface runoff, soil erosion, and their contribution rates to total soil and water loss. Moreover, tillage erosion effects on soil and water loss were closely related to rainfall patterns in hilly agricultural landscapes. Our study not only sheds light on the mechanism of tillage erosion and rainfall erosion but also provides useful insights for developing tillage-water erosion prediction models to evaluate soil and water loss on cultivated hillslopes.

Wild Chinese prickly ash with elevated antioxidants is a valuable genetic resource for Zanthoxylum bungeanum Maxim improvement. There are rich wild germplasm resources in the Qinling Mountains. In a study with wild germplasm resources from different altitudes and six cultivated varieties, the phenolic and flavonoid compounds were analyzed by high performance liquid chromatography (HPLC). The chromatograms of them were basically the same, although their chemical composition content was greatly different. The thirty samples were divided into three categories through the hierarchical clustering analysis. And catechin, hyperoside and quercitrin were considered to be key compound for the quality evaluation, by contrast, the wild samples with an altitude of 2300±50 m (Ⅳ group) had the highest content of key compounds, and showed stronger antioxidant activity and antibacterial ability, indicating that these wild samples could be used as an excellent breeding resource. This is the first time to evaluate the quality of wild Chinese prickly ash in different altitude areas of Qinling Mountains. These excellent wild germplasm resources provided substantial potential accessions for use directly in Chinese prickly ash breeding programs.

Huntington's disease (HD) is caused by an expansion of a CAG repeat in the gene that encodes the huntingtin protein (HTT). The exact function of HTT is still not fully understood, and previous studies have mainly focused on identifying proteins that interact with HTT to gain insights into its function. Numerous HTT-interacting proteins have been discovered, shedding light on the functions and structure of HTT. Most of these proteins interact with the N-terminal region of HTT. Among the various HTT-interacting proteins, huntingtin-associated protein 1 (HAP1) and HTT-interacting protein 1 (HIP1) have been extensively studied. Recent research has uncovered differences in the distribution of HAP1 in monkey and human brains compared to mice. This finding suggests that there may be species-specific variations in the regulation and function of HTT-interacting proteins. Understanding these differences could provide crucial insights into the development of HD. In this review, we will focus on the recent advancements in the study of HTT-interacting proteins, with particular attention to the differential distributions of HTT and HAP1 in larger animal models.

In an effort to enhance the efficiency and safety of open-pit mines, this study explores the optimization of end slope road parameters and slope structures, specifically focusing on unmanned driving lanes.A significant aspect of the study is the development of a truck trajectory offset model, which considers the different reaction times between automated sensors and human drivers in adapting to environmental changes. To test these concepts, the study uses numerical simulations to confirm the stability of the proposed end slope designs. Using Victory West Mine No. 1 as a case study, the research determines the optimized width for unmanned driving lanes and the maximum angle for safe steepening of end slopes. The findings indicate that the optimized unmanned lane width for NTE240 mining dump trucks is 1743 mm, allowing for a 2-degree increase in the slope angle at the south end slope. This optimization leads to a steep mining stripping volume of 3.2735 million m³ and a coal output of 2.49628 million tons, maintaining a stripping ratio of 1.31m³/t. These results demonstrate that the unmanned driving road width optimization not only ensures slope safety but also significantly boosts the economic benefits of steep mining in open-pit mines.

Helicosporous hyphomycetes is a class of filamentous fungi that shows promising application prospects in metabolizing bioactive natural compounds. During a study of helicosporous fungi in China, six new helicosporous taxa were collected and isolated from decaying wood in Guangxi Zhuang Autonomous Region, China. Morphological comparisons with multi-gene phylogenetic analyses revealed that these six taxa belong to Helicosporium (Tubeufiaceae, Tubeufiales), and they can be recognized as three novel species, named Helicosporium liuzhouense, H. multidentatum and H. nanningense. Detailed descriptions and illustrations of the newly discovered taxa and comparisons with similar fungi are provided. In addition, a list and a key to accepted Helicosporium species are provided.

Upon the implementation of the European Union Carbon Border Adjustment Mechanism (CBAM), substantial challenges are anticipated to impact the international trade of Chinese steel products. To safeguard the competitiveness of Chinese steel products on the global stage, this paper establishes a tripartite evolutionary game model, involving large steel enterprises, small and medium-sized steel enterprises, and the government. The model integrates collaborative emission reduction and free-riding benefits among enterprises, along with the government's dynamic subsidies and penalties. The paper analyzes the evolutionary trends and stable states of the three parties during different stages of CBAM, including a sensitivity analysis of key parameters. The findings indicate that large enterprises demonstrate a heightened sensitivity to CBAM, while small and medium-sized enterprises are more significantly influenced by free-riding benefits. Government intervention should be strategically timed and incline towards passive management during the strengthening phase of CBAM. Additionally, the refinement of the Chinese carbon market emerges as an effective means to counter CBAM. This paper provides theoretical support for how steel enterprises and the government can respond to CBAM, aiding stakeholders in selecting optimal strategies during different implementation stages and mitigating the impacts of CBAM to the maximum extent possible.

Synthetic Aperture Radar (SAR) is an active sensor that uses microwave for sense, it is unrestricted by weather and illumination conditions, and it can observe targets all day and weather. Aircraft targets are important monitoring objects in military and civilian fields, and how to efficiently detect and recognize aircraft targets is an important topic in the field of SAR image interpretation. Based on the features of SAR images, such as complex background, high resolution, and multi-scale, we proposed an improved method based on YOLOv5s. Firstly, this paper proposed the structure of the multi-scale receptive field and channel attention fusion, which is applied to the shallow layer of the backbone of YOLOv5s, it can adjust the weights of the multi-scale receptive field during the training process to enhance the extraction ability of feature information. Secondly, we proposed four de-coupled detection heads to replace the original part in YOLOv5s, which can improve the efficiency and accuracy of SAR image interpretation for small targets. Thirdly, in the case of the limited amount of SAR images, this paper proposed multi methods of data augmentation, which can enhance the diversity and generalization of the network. Fourthly, this paper proposed the K-means++ to re-place the original K-means to improve the network convergence speed and detection accuracy. Finally, Experiments demonstrate that the improved YOLOv5s can enhance the accuracy of SAR image interpretation by 9.3%, and the accuracy of small targets is improved more obviously, reaching 13.1%.

This paper focuses on robust multi-criteria traffic network equilibrium problems with path capacity constraints. The concepts of robust vector equilibrium and robust vector equilibrium with respect to worst case are introduced, respectively. To generate a subset of robust vector equilibrium, an equivalent min-max optimization problem is constructed. In addition, a direct search algorithm, in which the step size without derivatives and redundant parameters, for solving this min-max problem is proposed. To find a subset of robust vector equilibrium with respect to worst case, an equivalent smoothing optimization problem based on a variant version of ReLU activation function is established. Numerical experiments are also presented to expound the advantages of the algorithms.

Premature ventricular contraction (PVC) is one of the common ventricular arrhythmias, which may cause stroke or sudden cardiac death. Automatic long-term electrocardiogram (ECG) analysis algorithms could provide diagnosis suggestion even early warning for physicians, however, they are mutually-exclusive in terms of robustness, generalization and low complexity. In this study, a novel PVC recognition algorithm that combines deep learning-based heartbeat template clusterer and expert system-based heartbeat classifier is proposed. Long short-term memory-based auto-encoder (LSTM-AE) network was used to extract features from ECG heartbeats for K-means clustering. Thus, the templates were constructed and determined based on clustering results. Finally, the PVC heartbeats were recognized based on a combination of multiple rules, including template matching and rhythm characteristics. Three quantitative parameters, sensitivity (Se), positive predictive value (P+) and accuracy (ACC), were used to evaluate the performances of the proposed method on the MIT-BIH Arrhythmia database and the St. Petersburg Institute of Cardiological Technics database. Se on the two test databases was 87.51% and 87.92%, respectively; P+ was 92.47% and 93.18%, respectively; and ACC was 98.63% and 97.89%, respectively. The PVC scores on the 3rd China Physiological Signal Challenge 2020 training set and hidden test set were 36,256 and 46,706, respectively, which could rank first in the open-source codes. The results showed that the combination strategy of expert system and deep learning can provide new insights for robust and generalized PVC identification from long-term single-lead ECG recordings.

In this paper, the distributed formation tracking control problem of quadrotor unmanned aerial vehicles (UAVs) is considered. Adaptive backstepping technology is used to design flight control schemes for quadrotor UAVs. For the position subsystem, a distributed robust formation tracking control scheme is developed to achieve formation flight of quadrotor UAVs and track the desired flight trajectory. For the attitude subsystem, an adaptive disturbance rejection control scheme is proposed to achieve attitude stabilization during UAV flight under uncertain disturbances. Compared with the existing results, the novelty of this paper is that the proposed formation control scheme does not require the use of the quadrotor model parameters. Finally, a quadrotor UAV swarm system is used to verify the effectiveness of the proposed control scheme.

BiVO4 powder was synthesized by a simple hydrothermal method. The nanobelts with well dispersed and uniform morphology were synthesized by controlling the temperature. The structure of BiVO4 powder was studied by scanning electron microscopy (SEM) and transmission electron microscopy (TEM). The diameter of the nanobelts was about 50 nm. The structure and composition of the nanobelts were studied by X-ray diffraction (XRD), photoluminescence (PL) and X-ray photoelectron spectroscopy (XPS). The absorption intensity of BiVO4 powder in UV-Vis region was compared by UV–vis diffuse reflectance spectroscopy. As a photocatalyst, BiVO4 nanobelts have good photocatalytic ability under visible light irradiation, which is very useful for the treatment of environmental wastewater. The synthesized nanobelts photocatalyst can be reused without destroying its structure. The reusability and chemical stability of photocatalysts are of great significance for practical application.

Poverty alleviation is a hallmark of post-revolution Chinese policymaking. Since 1978, the Communist Party of China (CPC) has implemented successive waves of poverty alleviation policies whose effects have become the focus of an ever-increasing body of academic literature. This paper reviews this diverse but limited literature that evaluates the impact of the CPC’s poverty reduction programs through four major channels, namely fiscal investment programs, social safety nets, rural governance on the village-, county- and provincial level, and the relocation of rural populations from destitute regions. This paper aims to synthesize results and evaluate whether and how the abovementioned poverty alleviation programs have had distinct positive or negative impacts on regional development outcomes. Furthermore, I highlight contradictions in empirical findings to motivate the discussion about contextual importance when designing and implementing future poverty alleviation programs. Finally, I suggest that an exhaustive and critical appraisal of the empirical strategies used in this literature would further the development and application of more accurate and informative methodologies.

Drug delivery systems consist of cyclodextrins (CyDs) have kept constant attention for good compatibility, negligible toxicity, and improved pharmacokinetics of drugs. The unique hollow structure has endowed a lot of functions, such as inclusion of guest molecules, functional modification of active hydroxyl groups, and noncovalent interactions. Besides, the polyhydroxy structure has further extended the functions of CyDs by inter/intramolecular interactions and chemical modification. Furthermore, the versatile functions of the complex contribute to physicochemical characteristics alteration of the drugs, therapeutic talent, stimulus-responsive switch, self-assemble capability, and fiber formation. This review attempts to list the recent progress of CyDs and discuss their roles in the drug delivery system. Future perspectives of the construction of CyD-based drug delivery systems are also discussed at the end of this review, which may be the possible directions for the construction of more rational and cost-effective delivery vehicles.

Glycosidic linkage analysis was conducted on the unfractionated polysaccharides in the alcohol-insoluble residues (AIRs) prepared from six red seaweeds (Gracilariopsis sp., Prionitis sp., Mastocarpus papillatus, Callophyllis sp., Mazzaella splendens, and Palmaria palmata) using GC-MS/FID analysis of partially methylated alditol acetates (PMAAs). The cell walls of P. palmata primarily contained mixed-linkage xylans and small amounts of sulfated galactans and cellulose. In contrast, the unfractionated polysaccharides of the other five species were rich in galactans displaying diverse 3,6-anhydro-galactose and galactose linkages with varied sulfation patterns. Different levels of cellulose were also observed. This glycosidic linkage method offers advantages for cellulose analysis over traditional monosaccharide analysis that is known for underrepresenting glucose in crystalline cellulose. Relative linkage compositions calculated from GC-MS and GC-FID measurements showed that anhydro sugar linkages generated more response in the latter detection method. This improved linkage workflow presents a useful tool for studying polysaccharide structural variations across red seaweed species. Furthermore, for the first time, relative linkage compositions from GC-MS and GC-FID measurements, along with normalized FID and total ion current (TIC) chromatograms without peak assignments, were analyzed using principal component analysis (PCA) as a proof-of-concept demonstration of the technique's potential to differentiate various red seaweed species.

In this paper, a novel permanent magnet-assisted synchronous reluctance machine (PMASynRM) with rare-earth PMs and ferrite magnets is proposed. The performance of PMASynRM is discussed with respected to the different magnet ratio of rare-earth PMs and ferrite magnets. Some characteristics including the flux density, output torque, cogging torque, output power, power factor, torque ripple, loss, efficiency, and demagnetization are calculated by 2-D finite element analysis (FEA). The analysis results show that the excellent performance can be obtained by using hybrid magnet of rare-earth PMs and ferrite magnets with the suitable magnet ratio, and provide some desirable cost-performance trade-off.

The three-pronged sliding universal coupling is a new kind of three-pronged coupling. To study its kinematic and dynamic characteristics, directional cosine matrices are utilized as tools to analyze the coordinate systems by establishing simplified geometric models and corresponding motions. Through the analysis of the motions of the input and output shafts and employing the method of single-force element, a set of equilibrium equations for the forces acting on the output shaft and the input shaft are formulated for solution analysis. The research indicates that during the rotation process, there exists a small angular difference between the input shaft and the intermediate shaft, demonstrating the quasi-constant angular velocity characteristics of the new tripod sliding universal coupling. The curves of the forces and torques acting on each component of the coupling approximate sinusoidal curves. The optimal operating angle range for the new tripod universal coupling is at angle , during which the system exhibits good transmission and mechanical performance.

The Paeonia suffruticosa, called as 'Feng Dan', has been used for thousands of years in traditional Chinese medicine. In our chemical investigation on the root bark of the plant, five new phenolic dimers, namely paeobenzofuranone A‒E (1‒5), have been characterized. Their structures were determined by spectroscopic analysis including 1D and 2D NMR, HRESIMS, UV, and IR, as well as ECD calculations. Compounds 2, 4, and 5 showed cytotoxicity against three human cancer cell lines with IC50 values ranging from 6.7 to 25.1 μM. Compounds 1 and 2 showed certain inhibitory activity on NO production. To the best of our knowledge, the benzofuranone dimers and their cytotoxicity of P. suffruticosa are reported for the first time.

In order to develop novel botanical insecticides, the joint action of Ligusticum chuanxiong oil (LCO) and lemongrass oil (LO) against Aphis citricola van der Goot was determined systematically indoors and outdoors. The chemical profiles of LCO and LO as determined by gas chromatography- mass spectrometry analysis revealed that main compounds from LCO were Z-Ligustilide (44.58%) and Senkyunolide A (26.92%), and that of LO were geranial (42.16%) and neral (32.58%), respectively. The mixture of LCO and LO showed significant synergy against A. citricola, with a common-toxicity coefficient (CTC) value of 221.46 at the optimal ratio of LCO to LO (4: 1, w/w). Based on the results of solvents and emulsifiers screening, L. Chuanxiong oil · Lemongrass oil 20% emulsifiable concentrate (20% LCO · LO EC) was developed, which was confirmed to meet the requirements of a commercial pesticide by quality test. Field trials indicated that the insecticidal activity of the diluted 20% LCO · LO EC (1000 fold dilution) was comparable to conventional pesticide (20% imidacloprid EC) on A. citricola 7 days after application. Thus, the mixture of LCO and LO has the potential to be further developed as a botanical pesticide.

COX II containing a dual core CuA active site is one of the three core subunits of mitochondrial Cco, which plays a significant role in the physiological process. In this report, the full-length cDNA of COXⅡ gene was cloned from Sitophilus zeamais, which had an ORF of 684 bp encoding 227 amino acids residues. The predicted COXⅡ protein had a molecular mass of 26.2 kDa with pI value of 6.37, and multiple sequence alignment and phylogenetic analysis indicated that Sitophilus zeamais COXⅡ had high sequence identity 78.51% with the COXⅡ of other insect species, especially similarity to sitophilus oryzae. This gene was subcloned into the prokaryotic expression vector pET-32a, and induced by IPTG in E.coli Transetta (DE3) expression system. Finally the COXⅡ with 6-His tag was purified using affinity chromatography with Ni²⁺-NTA agarose. WB showed the recombinant COXⅡ was about 44 kD, and the concentration of fusion protein was 50μg/mL. UV-spectrophotometer and infrared spectrometer analysis showed that recombinant COXⅡ could catalyze the oxidation of substrate Cytc, and influenced by AITC. It was found that AITC could form a hydrophobic region with COXⅡ protein via molecular docking, besides, a sulfur atom of AITC structure could form a length of 2.9 Å hydrogen bond with Leu-31. These results will provide valuable information for elucidating the role of COXⅡ in Sitophilus zeamais responses to AITC, meanwhile, it will helpful to carry out a point mutation in AITC binding sites for the future research.

Rapid and accurate detection of road cracks is of great significance for road health monitoring, but currently this work is mainly completed through manual site surveys. Low-altitude UAV remote sensing can obtain images with centimeter or even subcentimeter ground resolution, which provides a new efficient and economical approach for rapid crack detection. Nevertheless, crack detection networks face challenges such as edge blurring and misidentification due to the heterogeneity of road cracks and the complexity of the background. To address these issues, we propose a real-time edge reconstruction crack detection network (ERNet) which adopts multi-level information aggregation to reconstruct crack edges and improve the accuracy of segmentation between the target and background. To capture global dependencies across spatial and channel levels, we propose an efficient bilateral decomposed convolutional attention module (BDAM) that combines depth separable convolution and dilated convolution to capture global dependencies across spatial and channel levels. To enhance the accuracy of crack detection, we use a coordinate-based fusion module that integrates spatial, semantic, and edge reconstruction information. In addition, we propose an automatic measurement of crack information for extracting the crack trunk and its corresponding length and width. Experimental results demonstrate that our network achieves the best balance between accuracy and inference speed.

The ever deepening population aging has brought opportunities and challenges to the continued expansion of tourism consumption in China. In this article, the impact of population aging on household tourism consumption was studied from both theoretical and empirical aspects. First, the micro mechanisms of the impact of population aging on household tourism consumption were analyzed, which include economic condition mechanism, intergenerational care mechanism, health status mechanism and Internet use mechanism. Subsequently, the impact of population aging on household tourism consumption and its impact mechanisms were tested, and the heterogeneity analysis was conducted, by using the data of China Family Panel Studies (CFPS) from 2014, 2016 and 2018. The main conclusions of the article are as follows: (1) Population aging has a significant negative impact on household tourism consumption, and a series of robustness test results such as endogenous treatment support this finding. (2) The results of the impact mechanism test show that population aging has a negative mediating effect on household tourism consumption by reducing household economic conditions. The moderating effect of intergenerational care on the effect of population aging on household tourism consumption is insignificant. Health status of the elderly and Internet use have a significant positive moderating effect on the impact of population aging on household tourism consumption. (3) The results of the heterogeneity analysis show that the negative impact of population aging on household tourism consumption in urban areas is greater than that in rural areas, and the negative impact of population aging on household tourism consumption of families with the old-old elderly is greater than that of falimies with the young-old elderly. The conclusions of this article provide important references for activating tourism consumption in China in the context of population aging.

Reverse water gas shift reaction (RWGS) is an important process which plays a vital role in many CO2 utilization related reactions. Noble metals are the most active catalysts in RWGS, but the high price and low reserve strangled their applications. In the present work, we reported a non-transition-metal MgAl2O4 catalyst which showed outstanding activity and stability at high temperatures in the RWGS reaction and improved performance after doping of single atomic Nin+. The catalyst can obtain 46% of CO2 conversion in durability test of 75 h at 800 °C under high weight hourly space velocities (225 000 ml g-1 h-1). The adsorption sites, possible reaction route, and effects of Nin+ single atoms on the (111) surface of MgAl2O4 for RWGS were investigated by in situ DRIFTS and DFT calculations. The results indicated that the rate determining reaction step of RWGS on MgAl2O4 and Ni (SA)/MgAl2O4 were both the reaction of OH* + H* → H2O* + *, but the energy barrier was significantly reduced after introducing single atomic Nin+. Nin+ atoms can increase the hydroxyl coverage on the surface of catalyst and Al3+ sites near the Nin+ ion are considered as the predominant active sites for RWGS reactions.

Titanium alloys are difficult to machine and have poor tribological properties. This paper investigates the lubricating performance of γ-Al2O3/ZnO hybrid nanofluids for Ti-6Al-4V. The pure and hybrid nanofluid are compared, and the effects of γ-Al2O3/ZnO ratios are studied. The results show that γ-Al2O3/ZnO hybrid nanofluids outperform pure nanofluid in terms of lower friction coefficients and better surface quality. Moreover, the hybrid nanofluid with a mass ratio of Al2O3 to ZnO of 2:1 demonstrates the best lubrication performance with a reduced friction coefficient of up to 22.1% compared to the base solution, resulting in improved surface quality. Al2O3 nanoparticles can adhere to the surface of ZnO nanoparticles and work as a coating, which further enhances the lubrication performance of the water-based nanofluid.

In order to solve the problem of feature extraction of underwater acoustic signals in complex ocean environment, a new method for feature extraction from ship radiated noise is presented based on empirical mode decomposition theory and permutation entropy. It analyzes the separability for permutation entropies of the intrinsic mode functions of three types of ship radiated noise signals, and discusses the permutation entropy of the intrinsic mode function with the highest energy. In this study, ship radiated noise signals measured from three types of ships are decomposed into a set of intrinsic mode functions with empirical mode decomposition method. Then, the permutation entropies of all intrinsic mode functions are calculated with appropriate parameters. The permutation entropies are obviously different in the intrinsic mode functions with the highest energy, thus, the permutation entropy of the intrinsic mode function with the highest energy is regarded as a new characteristic parameter to extract the feature of ship radiated noise. After that, the characteristic parameters, namely, the energy difference between high and low frequency, permutation entropy, and multi-scale permutation entropy, are compared with the permutation entropy of the intrinsic mode function with the highest energy. It is discovered that the four characteristic parameters are at the same level for similar ships, however, there are differences in the parameters for different types of ships. The results demonstrate that the permutation entropy of the intrinsic mode function with the highest energy is better in separability as the characteristic parameter than the other three parameters by comparing their fluctuation ranges and the average values of the four characteristic parameters. Hence, the feature of ship radiated noise can be extracted efficiently with the method.

Inducer of C-Repeat Binding Factor (CBF) expression (ICE), a well-known MYC-type bHLH transcription factor, plays a crucial role in the ICE-CBF-cold regulated (COR) cold signaling pathway. Brassica rapa (B. rapa), an important oilseed and vegetable crop, exhibits strong chilling and freezing tolerance. However, the exact molecular mechanisms by which ICE1 functions in B. rapa remain unclear. Here, 41 ICE1 homologous genes were identified from six widely cultivated Brassica species using a bioinformatics approach. These genes exhibit high conservation but reveal evolutionary complexity between diploid and allotetraploid species. Low-temperature stress induced ICE1 homolog expression, with patterns differing between strong and weak cold-tolerant varieties. Two novel ICE1 paralogs, BrICE1 and BrICE2, were cloned from Longyou 6. They positively regulate cold tolerance in B. rapa via a CBF-dependent pathway, contributing to reactive oxygen species (ROS) scavenfging and osmotic adjustment. Immunoblot analysis revealed that low temperatures induce BrICE1 and BrICE2 degradation via the 26S-proteasome pathway. In summary, ICE1 exhibits complex evolutionary relationships in Brassica species. BrICE1 and BrICE2 positively regulate cold tolerance via the CBF-dependent pathway and ROS scavenging mechanism and are also responsible for balancing the development and cold defense of B. rapa.

The task of weakly supervised point cloud semantic segmentation has received widespread attention and also has been widely used in autonomous driving, robotics, and modern industries. Due to the high dimensionality and large volume of point cloud data, many technical difficulties appeal to weakly supervised semantic processing, especially segmentation. However, weakly-supervised schemes usually provide only partial labelling information of the underlying point cloud data and thus need to effectively extract local features, geometric information, and contextual relationships only using these limited labelled data for supervised learning. To improve weakly-supervised semantic segmentation, we propose a novel segmentation network through the boundary-based feature aggregation based on a K-NN algorithm with down-sampling operation, and also introduce the smoothness loss and Siamese loss for effective segmentation. The experiments on public datasets demonstrate that our presented segmentation method exceeds most of the existing fully supervised and weakly-supervised methods in terms of mIoU. Specifically, our network has high segmentation accuracy on the labels of objects with similar geometrical structures, such as ceiling, wall, floor, chair and table, reaching 91.2%, 98.8%, 83.3%, 75.3% and 80.2%, respectively. Extensive experiments also illustrate its robustness, effectiveness, and generalization of the proposed weakly supervised segmentation network.

Habitat quality has great significance for regional ecological conservation and human welfare. In this study, we evaluated the spatial and temporal characteristics of land use and habitat quality in the temperate desert sub-region of Ordos Plateau using patch-generating land use simulation (PLUS) and integrated valuation of ecosystem services and trade-offs (InVEST) models. From 2000 to 2020, the areas of grassland, cropland, and unused land in the study area increased significantly; the areas of water bodies and woodland increased slightly; and the area of wasteland decreased significantly. Moreover, the habitat quality in the temperate desert subzone of the Ordos Plateau showed a trend of increasing and then decreasing from 2000 to 2020. The areas of lower and low habitat quality first decreased and then increased, and the overall area decreased over time. Conversely, the areas of high and higher habitat quality initially increased and then decreased, and the overall area increased over time. The area of medium habitat quality first decreased and then increased, although the overall change was minimal. Based on the PLUS model, the habitat quality of the study area in 2025 predicted under the natural development scenario was compared with that predicted under the ecological conservation scenario, showing higher habitat quality and lower habitat degradation under the ecological conservation development scenario. These results can be used to provide a scientific basis and decision reference for the sustainable use of land resources and high-quality socio-economic development in the temperate desert sub-region of the Ordos Plateau.

Pyrethroid pesticides (PYRs) as the third most widely used pesticides, following organophosphorus and carbamate pesticides, which are of significant importance in the analysis and detection of vegetables. However, the current pretreatment technology for PYRs confronts challenges of difficult separation and low enrichment efficiency, resulting in a cumbersome and time-consuming pretreatment process with poor selectivity. Here, a simple and efficient magnetic solid-phase extraction (MSPE) strategy was developed to simultaneously purify and enrich five PYRs in vegetables, with the magnetic covalent organic framework nanomaterial COF-SiO2@Fe3O4 as an adsorbent. The COF-SiO2@Fe3O4 was prepared by a simple solvothermal conditions method, using Fe3O4 as magnetic core, benzidine and 3,3,5,5-tetraaldehyde biphenyl as two building units. COF-SiO2@Fe3O4 could effectively capture the targeted PYRs by virtue of its abundant π-electron system and hydroxyl groups. The impact of various experimental parameters on extraction efficiency was investigated to optimize the MSPE conditions, including adsorbent amount, extraction time, elution solvent type and elution time. Subsequently, method validation was conducted under the optimal conditions in conjunction with gas chromatography-mass spectrometry (GC-MS). Within the range of 5.00–100 μg·kg-1 (1.00–100 μg·kg-1 for bifenthrin and 2.5–100 μg·kg-1 for fenpropathrin), the five PYRs exhibited a strong linear relationship, with determination coefficients ranging from 0.9990 to 0.9997. The limits of detection (LODs) were 0.3–1.5 μg·kg-1, and the limits of quantification (LOQs) were 0.9–4.5 μg·kg-1. The recoveries were 80.2–116.7% with relative standard deviations (RSDs) below 7.0%. Finally, COF-SiO2@Fe3O4, NH2-SiO2@Fe3O4 and Fe3O4 were compared as MSPE adsorbents for PYRs. The results indicated that COF-SiO2@Fe3O4 was an efficient and rapid selective adsorbent for PYRs. This method holds promising prospects for the determination of PYRs in real samples.

Background: Many randomized controlled trials (RCTs) and systematic reviews (SRs) on acupuncture treatment for post-acute stroke dysphagia have been published. Due to conflicting results an overview of SRs to summarize and assess the quality of this evidence to determine whether acupuncture is effective for this disease was conducted. Methods: Seven databases were searched for SRs and/or Meta-analysis of RCTs and quasi-RCTs on acupuncture for post-acute stroke dysphagia. Two authors independently identified SRs and meta-analyses, collected data to assess the quality of included SRs and meta analyses according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and the revised Assessment of Multiple Systematic Reviews (AMSTAR 2). Results: 31 SRs were identified. Quality of 22 SRs was critically low, 5 SRs were low, and 4 Cochrane SRs were moderate when evaluated by AMSTAR2. 17 SRs reported 85.2-96.3% items of PRISMA. Five SRs included explanatory RCTs, 16 SRs included pragmatic RCTs, and 10 SRs included both. Conclusion: Currently evidence on the effectiveness of acupuncture on post-acute stroke dysphagia is low quality. Type of study appeared to have no direct influence on the result, but the primary outcome measures showed a relationship with the quality of SRs. High quality trials with large sample sizes should be the focus of future research. PROSPERO REGISTRATION NUMBER: CRD42019134163

In this paper, we study the well-posedness and asymptotics of a one-dimensional thermoelastic laminated beam system either with or without structural damping, where the heat conduction is given by Fourier's law effective in the rotation angle displacements. We show that the system is well-posed by using Lumer-Philips theorem, and prove that the system is exponentially stable if and only if the wave speeds are equal, by using the perturbed energy method and Gearhart-Herbst-Prüss-Huang theorem. Furthermore, we show that the system with structural damping is polynomially stable provided that the wave speeds are not equal, by using the second-order energy method.

In this study, based on a new quantum integral identity, the authors establish some quantum estimates of Hermite-Hadamard type inequalities for convex functions. These results generalize and improve some known results given in literatures.

Concrete is more stable than filler as a false roof in a downward approach type infill quarry, but the mechanical model of a concrete false roof is not clear. As a result, there has been limited application. Therefore, it is necessary to establish the mechanical model of a concrete artificial false roof to enhance the stability of the downward approach infill quarry. This paper combines theoretical analysis, model derivation, finite element analysis and field application methods. Firstly, the basic assumptions of thin plate theory and elasticity mechanics are used as the premise to establish the differential equations of the deflection curve of the concrete thin plate false roof. Then, the three types of bending moment generation of the concrete thin plate false roof are explored. Secondly, the relationship between the location of dangerous surface and dangerous point in hard-supported weak-slab structure and soft-supported weak-slab structure is analyzed, and the type of uniform load and calculation model of concrete thin-slab false roof are improved. Finally, according to the established mechanical model of thin slab false roof, finite element analysis and field application were carried out. The results show that there are three types of deflection curve differential equations in the concrete thin slab false roof perpendicular to the strike, and three extreme points exist in the middle section of the thin slab and on both sides of the surrounding rock. The hazardous surface of the hard-supported weak-slab structure is present at the intersection of the encircling rock and the thin-slab fake ceiling, with the perilous point situated on the top of this surface. The hazardous surface of the soft-supported weak-slab structure can be found in the centre section of the thin-slab fake ceiling, with the perilous point being located at the bottom of this surface. Moreover, the damage mode for both structures is that of maximum tensile stress damage. Upon conducting a finite element analysis, the results indicate that the concrete's maximum tensile stress is significantly high.

Practical applications of CsPbX3 nanocrystals (NCs) are limited by their poor stability. The formation of heterojunction between CsPbX3 NCs and oxides is an effective means to protect perovskite from polar solvents and other external factors. Significantly improving the stability and photocatalytic properties of the core/shell perovskite is very important for its application in photoelectric and photocatalytic technology. Here, we report the synthesis of asymmetrical CsPbBr3/TiO2 core-shell heterostructure NCs at single particle level by hot injection liquid phase synthesis and sol-gel method, where each CsPbBr3 NCs is partially covered by titanium dioxide. It is shown that the type II arrangement is generated at the heterogeneous interface, which greatly facilitates the separation of electron-hole pairs and increases the carrier transport efficiency. More crucial, due to the protection of titanium dioxide shell, the product has higher long-term stability in humid air compared with bare CsPbBr3 NCs. The asymmetrical core-shell heterostructure prepared in this study not only improves the stability of CsPbX3 NCs, but also provides some ideas for optoelectronic device applications and TiO2-based photocatalysts.

In this paper, we consider a fourth-order suspension bridge equation with nonlinear damping term |u_t|^m-2u_t and source term |u|^p-2u. We give necessary and sufficient condition for global existence and energy decay results without considering the relation between m and p. Moreover, when p>m, we give sufficient condition for finite time blow-up of solutions. The lower bound of the blow-up time T_max is also established. It worth to mention that our obtained results extend the recent results of Wang (J. Math. Anal. Appl., 2014) to the nonlinear damping case.

Co-integration and Causality was built to conduct studies on causality relation between carbon intensity and coal consumption leading to providing important basis for the transition to a low carbon economy. The EG two-step method was performed to study the relation between carbon intensity and coal consumption of China during 1990-2015 and the co-integration and Granger test was constructed to build up the co-integration and error correction models for analysis of the interaction between carbon intensity and coal consumption. The results showed that in long term there is a stable co-integration relation and a positive correlation between carbon intensity and coal consumption; whereas fluctuations exist in short term and there is a one-way Granger causality of carbon intensity with respect to coal consumption.

Currently, in some domestic and foreign mines, the backfill drilling pipeline experience a rupture phenomenon even when the wear degree is low. This results in a delay in production due to the filling becoming 'sick'. This paper presents, for the first time, the damage mechanism from a mechanical perspective and re-derives the anti-extrusion strength model of the backfill drilling pipeline. We investigate the influence of law on the anti-extrusion strength of pipelines from the perspective of stratum and cement ring. We then verify the theoretical and simulation results through engineering examples. The results demonstrate that the Mises stress criterion is a suitable modification principle for the anti-extrusion strength model of the backfill drilling pipeline. The anti-extrusion strength of the pipeline is related to the elastic modulus and Poisson's ratio of the stratum, and the thickness of the cement ring. It is negatively affected by the depth of the stratum. For hard strata, a cement ring with a smaller elastic modulus is suitable, while for soft stratum, a cement ring with a larger elastic modulus is recommended. When the missing angle of the cement ring is less than 60°, the stress concentration factor increases up to 2.2. The stress unloading capacity of the cement ring ranges from 32.7% to 37.8%, and optimal performance of the cement ring is achieved when it has high strength and low rigidity. The backfill filling pipeline of a copper mine abroad was destroyed due to external extrusion force exceeding its anti-extrusion strength value. The modified pipeline anti-extrusion strength model is 18.2% higher than the casing API strength value. This finding can inform the design of the backfill filling pipeline for China's kilometer-deep wells in the future.

This paper addresses the input coupling problem for the shape memory alloy (SMA) actuated parallel platform with completely unknown nonlinear dynamics. The problem means that in a parallel platform with multiple SMA actuators acting together, the displacement of one of the actuators will simultaneously affect the remaining actuators to change. Due to the coupling problem and nonlinear characteristics of the SMA actuators, it is not easy to control the platform to achieve bi-directional swing with completely unknown nonlinear dynamics. Therefore, a model-free adaptive sliding mode control method is proposed to improve the control accuracy of the complex motion of the platform, avoiding the complex modeling process of the SMA actuated parallel platform. Based on the model-free adaptive control (MFAC) theory, a multiple input and multiple output (MIMO) dynamic linearized mathematical model of the parallel platform is established using the online input and output data of the system. Then, a sliding mode controller is designed based on the dynamic model. A rigorous theoretical analysis proves that the proposed model-free adaptive sliding mode controller is able to stably control the SMA actuated parallel platform, and its tracking error is uniformly ultimately bounded (UUB). Finally, experiments are conducted on the established SMA actuated parallel platform. The results show that the proposed model-free controller is feasible and effective, and can control the system well to achieve the complex motion of bi-directional swing.

Promoting green development has become an important way to optimize the ecological and economic structure and promote sustainable development. The Yangtze River Economic Belt is an important economic corridor in China, and it remains to be examined whether the implementation of environmental regulations has enhanced the green total factor productivity (GTFP) of cities. This paper calculates the green total factor productivity of 107 cities within the Yangtze River Economic Belt by using the super-efficient SBM model and the GML index with Chinese city panel data from 2007-2019 and measures the intensity of environmental regulations through textual analysis. The bidirectional fixed-effects model constructed in this paper suggests an inverted U-shaped relationship between environmental regulation and GTFP, which is confirmed by a series of robustness tests. Green technology innovation and advanced industrial structure play a mechanism role in this. In regions with lower levels of green technology and industrial structure, the inverted U-shaped relationship between environmental regulation and green total factor productivity is more significant. In addition, the phenomenon of GTFP rising and then falling because of environmental regulation is more obvious in cities in the middle and upper reaches of the Yangtze River and outside the urban agglomerations. Therefore, when formulating environmental regulation policies, it is necessary to balance the relationship between economic development and environmental protection and harmonize the environment and economic development of the entire Yangtze River Basin.

In this paper, four lithological parameters, i.e. thermal conductivity, particle size, porosity and saturation, are investigated by combining experimental observations with numerical simulations to study the influence laws and mechanisms of action on the combustion process of methane hydrate sediments. The variation of combustion characteristics parameters such as flame height, effective combustion ratio and dimensionless discharge water mass with the lithological parameters are studied. In addition, the combustion mechanism of lithologic parameters on methane hydrate deposits is revealed. Combining the experimental results and simulation calculations, to optimize the combustion of methane hydrate sediments, it is recommended to use methane hydrate sediment samples with high saturation and low thermal conductivity, while the oxidant concentration and porosity of methane hydrate sediment samples should be increased.

Air conditioners are indispensable necessities in daily life and industrial production. However, the heat generation of their internal core power components can limit their performance release. In this work, we explore the application of thermoelectric coolers (TECs) in the field of power device heat dissipation through finite element simulation. First, we geometrically modeled the structure and typical operating conditions of core power devices in air conditioners. We compared the temperature fields in air cooling and TEC active cooling modes for high power consumption power devices in a 319 K operating environment. The simulation results show that in the single air cooling mode, the maximum temperature of the 173.8 W power device reaches 394.4 K and the average temperature reaches 373.9 K, which exceeds its rated operating temperature of 368.1 K. However, after adding TEC, the maximum temperature of the power device drops to 331.8 K at an operating current of 7.5 A and the average temperature of the device is 326.5 K. It indicates that TEC active cooling has a significant effect on the temperature control of the power device. At the same time, we also studied the effect of TEC working current on the temperature control effect of power devices. For TEC, there is a minimum working current of 5 A; when it is less than 5 A, TEC has no cooling effect; the cooling effect of TEC increases with an increase in working current. When the TEC working current is 10 A, the average temperature of the power device can be reduced to 292.9 K. This study has made a meaningful exploration of the application of TEC in chip temperature control and heat dissipation, providing a new solution for chip thermal management and accurate temperature control.

Dry eye disease (DED) is one of the most common eye diseases. There is at least one DED patient in almost every five people. AI-based research methods increasingly become the focus of DED diagnosis research. This study utilizes a systematic review method on DED AI-based diagnosis. 2112 unduplicated records are extracted from Google Scholar, Web of Science (WOS), PubMed, China National Knowledge Infrastructure (CNKI), and Scopus databases. The most contributed countries, institutions, authors, journals, references, and disciplines are recognized. Keyword distribution and hot topics are identified. Popular databases of ophthalmic images, videos, and electronic demographic medical records are discussed. The DED diagnosis, classification, and grading criteria are identified. The major diagnosing methods are clustered, compared, and investigated. Findings show that diagnosing method research could be classified into three categories based on the relationship between AI techniques, which are (1) ground truth and/or comparable standards for AI DED diagnosis (TBUT, S Ⅰ T, TMH, and OSDI), (2) potential methods for AI-based methods have a great advantage(DED detection based on meibometry Images, CASPs, IVCM Images, OCT Images, blink videos and ultrasonic imaging), (3) and the potential direction and supplemented methods for AI-based DED detection (DED detections based on tear osmolarity, proteomic analysis, TCM and demographic information). AI-based approaches based on digital ophthalmologic images play an important role in early screening. Challenges and future perspectives are discussed at the end of this article, academically and practically.

The fusion of "innovation theory" and "ecology" gave birth to a large number of studies on "innovation ecology", which mainly studies how to build an industrial ecological chain at the regional level, focusing on self-evolution, achieving ecological balance, and enabling the regional economy to take the path of sustainable innovation. This type of research borrows a lot of concepts from ecology, and very vividly describes the competition and cooperation relationships formed by various agents in the innovation system, laying a good foundation for qualitative analysis of the inherent dynamics of innovation development. However, many studies focus on the analogous description of ecosystems and economic systems, lacking scientifically and rigorously quantitative empirical research as a support. This paper uses network-based indicators such as degree, cluster coefficient, and betweenness centrality to measure the function and position of high-tech enterprises in the Z-Park in a business environment, so as to clarify the socio-economic meaning of the topological structure of the regional innovation system. On this basis, it provides theoretical references for regional innovation development and sustainable development policy formulation.

Various sudden shifts in financial market conditions over the past decades have demonstrated the significant impact of market structural breaks on firms' credit behavior. To characterize such effect quantitatively, we develop a continuous-time modulated Markov model for firms' credit rating transitions with the possibility of market structural breaks. The model takes a semi-parametric multiplicative regression form, in which the effects of firms' observable covariates and macroeconomic variables are represented parametrically and nonparametrically, respectively, and the frailty effects of unobserved firm-specific and market-wide variables are incorporated via the integration form of the model assumption. We further develop a mixtured-estimating-equation approach to make inference on the effect of market variations, baseline intensities of all firms' credit rating transitions, and rating transition intensities for each individual firm. We then use the developed model and inference procedure to analyze the monthly credit rating of U.S. firms from January 1986 to December 2012, and study the effect of market structural breaks on firms' credit rating transitions.

Although crop conversion from annual to perennial crops has been considered as one path towards climate-smart and resource-efficient agriculture, the effects of this conversion on soil multifunctionality and biomass yields remain unclear. Here, we investigated the effects of one annual and three perennial crops (a grass (Lolium perenne), a legume (Medicago sativa), and their mixture) on soil multifunctionality and biomass yield on the Yellow River floodplain. Soil multifunctionality was assessed by the capacity of water regulation and the multifunctionality of carbon (C), nitrogen (N), and phosphorus (P) cycles. Results showed that perennial crops enhanced soil multifunctionality by 207% for L. perenne, 311% for M. sativa, and 438% for L. perenne + M. sativa, compared with annual winter wheat (Triticum aestivum). The effect of perennial crops on soil multifunctionality increased with infiltration rate, dissolved organic C, microbial biomass C, and extracellular enzymatic activities for both C and N acquisition. However, we observed that perennial crops had lower biomass yield than annual crop. Therefore, the transition of agricultural landscapes to perennials needs to take into account the balance between environmental protection and food security, as well as environmental heterogeneity, to promote sustainable agricultural development.

The teaching and learning environment have changed significantly over the last decade with the integration of an increasing amount of information and communication technologies, especially in distance education due to global pandemics, total lockdowns, isolation, and quarantine periods. The number of numerous virtual and non-virtual tools involved in educational processes is growing day by day. In terms of technological innovations used in learning environments, many researchers and educators are trying their best to bring more creative ideas into the technology- based learning environments. Although higher educational institutions have greatly benefited from the growing number of hardware and software resources in the educational process, they have also faced some setbacks that have harmed the learning processes. These technologies have in turn complicated some of the processes in the learning atmosphere. Therefore, we take Spanish teaching course as an example to present the challenging smarter teaching and learning systems that higher educational institutions face today.

JBIR-99 is a secondary metabolite of marine fungi that has been shown to possess strong antibiotic activity. An efficient approach using a combination of size exclusion chromatography with a Sephadex LH-20 and high-speed counter-current chromatography (HSCCC) has been successfully developed for the isolation and purification of a polyketide from the solid-state fermentation of Meyerozyma guilliermondii. The active compound was isolated with purity >95% by HSCCC using an optimized solvent system composed of petroleum ether–ethyl acetate– 95% ethanol–water (5:3:5:3, v/v/v/v) after size exclusion chromatography. This compound was successfully purified in the quantity of 68 mg from 120 mg of the crude extract. The structure of JBIR-99 was elucidated and assigned by 1D, 2D NMR spectroscopic, and positive HRESITOFMS. Moreover, the relative configuration of compound JBIR-99, displaying a quite complex multi-ring structure, is determined by X-ray crystallography for the first time. The purification method developed for JBIR-99 will facilitate the further investigation and development of this antibiotic agent as a lead compound. Furthermore, it is suggested that the combination of size exclusion chromatography and HSCCC could be more widely applied for the isolation and purification of polyketides from marine fungi.

In this paper, we study the semilinear pseudo-parabolic equations $\displaystyle u_{t} - \triangle_{\mathbb{B}}u - \triangle_{\mathbb{B}}u_{t} = \left|u\right|^{p-1}u$ on a manifold with conical singularity, where $\triangle _{\mathbb{B}}$ is Fuchsian type Laplace operator investigated with totally characteristic degeneracy on the boundary $x_{1} = 0$. Firstly, we discuss the invariant sets and the vacuum isolating behavior of solutions with the help of a family of potential wells. Then, we derive a threshold result of existence and nonexistence of global weak solution: for the low initial energy $J(u_{0})<d$, the solution is global in time with $I(u_{0}) >0$ or $\displaystyle\Vert \nabla_{\mathbb{B}}u_{0}\Vert_{L_{2}^{\frac{n}{2}}(\mathbb{B})} = 0$ and blows up in finite time with $I(u_{0}) < 0$; for the critical initial energy $J(u_{0}) = d$, the solution is global in time with $I(u_{0}) \geq0$ and blows up in finite time with $I(u_{0}) < 0$. The decay estimate of the energy functional for the global solution and the estimates of the lifespan of local solution are also given.

Taiwan’s auditors have suffered from processing excessive audit data, including drawing audit evidence. This study advances sampling techniques by integrating machine learning with sampling. This machine learning integration helps avoid sampling bias, keep randomness and variability, and target the risker samples. We first apply a Naive Bayes classifier to classify data into some classes. Next, a user-based, item-based, or hybrid approach is employed to draw audit evidence. The representativeness index is the primary metric for measuring the representativeness of audit evidence. The user-based approach denotes the selection of samples between two percentiles in a class as audit evidence. It may be equivalent to a combination of monetary and variable sampling methods. The item-based approach represents the choice of risky samples as audit evidence. It may be identical to a combination of non-statistical and monetary sampling methods. Auditors can hybridize those user-based and item-based approaches to balance representativeness and riskiness in selecting audit evidence. Three experiments show that sampling using machine learning integration has the benefits of drawing unbiased samples, handling complex patterns, correlations, and unstructured data, and improving efficiency in sampling big data. However, the limitations are the classification accuracy output by machine learning algorithms and the range of prior probabilities.

There are rich proper noun derivative semantic relationships in geographic entity vector data. The identification of traditional proper noun derivative semantic relationships usually requires toponym researchers to examine the source of derived toponyms by consulting a large number of toponym documents. This method cannot adapt to the mining of proper noun derivative semantic relationships for large-scale geographical entity. In this regard, this paper proposes a method of identifying the proper noun derivative semantic relationships for geographical entity by combining prompt learning and XGBoost model. This method transforms the extraction problem of proper noun derivative semantic relationships into a binary classification problem by analyzing the characteristics of the derivation relationship of toponyms in the form of toponyms and the spatial and temporal distribution of geography. Firstly, prompt learning and gaussian mixture model are used to extract and cluster the derivation words of toponyms, so as to realize the recognition of derived toponyms collections. Then, enumerate the possible proper noun derivations in the toponym set, and then the XGBoost model is used to identify the semantic relations derived from the proper noun of geographical entities. In the experiment, the recognition method of proper noun derivative semantic relationships based on prompt learning and XGBoost proposed in this paper has achieved good relationship recognition effect in the experiment. This method has certain practical value in the fields of toponym management and toponym translation.

System-of-systems (SoS) evolution is a complex and unpredictable process. Although various principles to facilitate collaborative SoS evolution have been proposed, there is a lack of experimental data validating their effectiveness. To address these issues, we present an Agent-Based Model (ABM) for SoS evolution in the Internet of Vehicles (IoV) , serving as a quantitative analysis tool for SoS research. By integrating multiple complex and rational behaviors of individuals, we aim to simulate real-world scenarios as accurately as possible. To simulate the SoS evolution process, our model employs multiple agents with autonomous interactions and incorporates external environmental variables. Furthermore, we propose three evaluation metrics: evolutionary time, degree of variation, and evolutionary cost, to assess the performance of SoS evolution. Our study demonstrates that enhanced information transparency significantly improves the evolutionary performance of distributed SoS. Conversely, the adoption of uniform standards only brings limited performance enhancement to distributed SoSs. Although our proposed model has limitations, it stands out from other approaches that utilize Agent-Based Modeling to analyze SoS theories. Our model focuses on realistic problem contexts and simulates realistic interaction behaviors. This study enhances the comprehension of SoS evolution processes and provides valuable insights for the formulation of effective evolutionary strategies.

To understand the molecular mechanism underlying yellowing in pineapples during ripening, coupled with alterations in fruit quality, comprehensive metabolome and transcriptome investigations were carried out. These investigations were conducted using the pulp samples collected at three distinct stages of maturity: young fruit (YF), mature fruit (MF), and fully mature fruit (FMF). This study revealed a noteworthy increase in the levels of total phenols and flavones, coupled with a concurrent decline in lignin and total acid content, as the fruit transitioned from YF to FMF. Furthermore, the analysis yielded 167 differentially accumulated metabolites (DAMs) and 2194 differentially expressed genes (DEGs). Kyoto Encyclopedia of Genes and Genomes enrichment analysis based on DAMs and DEGs revealed that the biosynthesis of plant secondary metabolites, particularly the flavonol, flavonoid, and phenypropanoid pathways, plays a pivotal role in fruit yellowing. Additionally, a comprehensive regulatory network encompassing genes that contribute to metabolisms of flavones, flavonols, lignin, and organic acids was proposed. This network sheds light on the intricate processes that underlies fruit yellowing and quality alterations. These findings enhance our understanding of the regulatory pathways governing pineapple ripening and offer valuable scientific insight into the molecular breeding of pineapples.

In this paper, we study the global existence and exponential decay for a dynamic contact problem between a Timoshenko beam with second sound and two rigid obstacles, of which the heat flux is given by Cattaneo's law instead of the usual Fourier's law. The main difficulties arise from the irregular boundary terms, from the low regularity of the weak solution and from the weaker dissipative effects of heat conduction induced by Cattaneo's law. By considering related penalized problems, proving some a priori estimates and passing to the limit, we prove the global existence of the solutions. By considering the approximate framework, constructing some new functionals and applying the perturbed energy method, we obtain the exponential decay result for the approximate solution, and then prove the exponential decay rate to the original problem by utilizing the weak lower semicontinuity arguments.

Following Dirac’s notation in Quantum Mechanics (QM), we propose the Probability Bracket Notation (PBN), by defining a probability-bra (P-bra), P-ket, P-bracket, P-identity, etc…Using the PBN, many formulas, such as normalizations and expectations in systems of one or more random variables, can now be written in abstract basis-independent expressions, easy to expand by inserting a proper P-identity. The time evolution of homogeneous Markov processes can also be formatted in such a way. Our system P-kets are identified with probability vectors and our P-bra system is comparable with Doi’s state function or Peliti’s standard bra. In the Heisenberg picture of the PBN, a random variable becomes a stochastic process, and the Chapman-Kolmogorov equations are obtained by inserting a time-dependent P-identity. Also, some QM expressions in Dirac notation are naturally transformed to probability expressions in PBN by a special Wick rotation. Potential Applications show the usefulness of the PBN beyond the constrained domain and range of Hermitian operators on Hilbert Spaces in QM all the way to IT.

The internal wave recognition algorithm in an ocean data buoy system can be used to realize the real-time and flexible observation of internal waves, but there is no accurate automatic recognition method. To meet the need for automatic, real-time, and reliable internal wave recognition, an automatic internal wave recognition algorithm has been proposed for a tightly profiled intelligent buoy system. The sea profile temperature data collected by the Bailong buoy system in the Andaman Sea in 2018 were used to train and test the internal wave recognition neural network model, which consists of two parts: feature extraction and feature classification. The experiment compares the long short-term memory network (LSTM), convolutional neural network (CNN) with different layers, and deep neural network (DNN) without a feature extraction network and adjusts the number of convolutional nuclei and convolutional strides to improve the feature extraction efficiency. Experiments show that the best results can be obtained when a CNN layer is used as the feature extraction network, the convolutional step length is 4, the number of convolutional kernels is 5. The recall reaches 95.31% and the precision is 97.53%. The internal wave identification delay of the algorithm is 5.0862 minutes, the number of parameters is 1593, and the number of calculations is 3024. The algorithm can be directly deployed to the ocean data buoy system to realize the demand for automatic, real-time and reliable internal wave identification at the buoy end.

Agricultural activities are the second largest source of greenhouse gas emissions, and carbon emissions from agricultural land use (CEALU) have become a hot issue across the world. However, few scholars explored the impact of agricultural land policies on carbon emissions, such as the High-standard farmland construction(HSFC) in China.Thus，by relying on provincial panel data for China for the period 2005-2017, the effect of the high-standard basic farmland construction policy on carbon emissions from agricultural land use per unit area and its regional differences were quantitatively analyzed using the difference-in-difference (DID) model. The results showed that: 1) China's CEALU per unit area presented a fluctuating upward trend during the period 2005-2017, from 392.58 kg/ha to 457.72 kg/ha, with an average annual growth rate of 1.31%. 2) The high-standard farmland construction(HSFC) policy produced a significant carbon emission reduction effect in agricultural land use, and reduced the CEALU per unit area by 10.80% on average. With the promotion of this policy, its carbon emission reduction effect in agricultural land use presented an overall increasing trend. 3) The carbon emission reduction effect of the high-standard farmland construction policy in agricultural land use was significant in central China, but non-significant in eastern China and western China.

To evaluate the relative importance of IGF-I expression in various cell types for endochon-dral ossification, we quantified the trabecular bone at the secondary spongiosa and epiphysis of the distal femur in 8-12-week-old male mice with a global knockout of the Igf-I gene as well as conditional deletion of the Igf-I gene in osteoblasts, chondrocytes, osteo-blasts/chondrocytes, and their corresponding control wild type littermates. The osteoblast-, chondrocyte- and osteoblast/chondrocyte-specific Igf-I conditional knockout mice were generated by crossing Igf-I floxed mice with Cre transgenic mice in which Cre expression is under the control of Col1α2 or Col2α1 promoter. We found that global disruption of Igf-I resulted in 80% and 70% reduction in bone size, which is defined as total volume, at the secondary spongiosa and epiphysis of the distal femur, respectively. Abrogation of Igf-I in Col1α2-producing osteoblasts, but not Col2α1-producing chondrocytes, decreased bone size by 25% at both the secondary spongiosa and epiphysis while deletion of the Igf-I globally or specifically in osteoblasts or chondrocytes reduced trabecular bone mass by 25%. By contrast, global Igf-I knockout but not conditional knockout of Igf-I in osteoblasts and/or chondrocytes reduced trabecular bone mass in the epiphysis. The reduced trabecu-lar bone mass at the secondary spongiosa in osteoblast- and/or chondrocyte-specific Igf-I conditional knockout mice is caused by reduced trabecular number and increased trabec-ular separation. Immunohistochemistry studies revealed that expression levels of chon-drocyte (COL10, MMP13) and osteoblast (BSP) markers were reduced in the secondary spongiosa and the epiphyses in the global Igf-I knockout mice. Our data indicate that local and endocrine IGF-I actions in bone are pleiotropic and dependent on cell type as well as the bone compartment where IGF-I acts.

This study investigates the impact of specimen size on the mechanical properties of wood, specifically focusing on compression strength, elastic modulus, and Poisson's ratio. Compression tests were conducted using three different specimen sizes (20mm×20mm×30mm, 40mm×40mm×60mm, 60mm×90mm×90mm) in the longitudinal, radial, and tangential directions. Mechanical parameters, failure mechanisms, load-displacement curves, and stress-strain relationships were systematically analyzed for each size. The study also evaluated the influence of specimen size on the accuracy of finite element numerical simulations by utilizing the obtained mechanical parameters. The results reveal a significant correlation between compressive strength and specimen size, indicating a decrease in compressive strength with increasing specimen size. Conversely, elastic modulus and Poisson's ratio exhibit less sensitivity to variations in specimen size. Notably, parameters derived from small-sized specimens (20mm×20mm×30mm) exhibited substantial errors, while those obtained from medium-sized (40mm×40mm×60mm) and large-sized specimens (60mm×90mm×90mm) demonstrated greater reliability, providing precise results in finite element numerical simulations.

Promoting the sustainable development of resource-based cities is of great significance to the ecological protection and high-quality development of the Yellow River Basin. Combining the environmental status and economic development, we objectively evaluate the ecological safety level of resource-based cities in the Yellow River Basin, compare and analysis the main factors affecting the ecological safety of different resource-based cities, and formulate precise and differentiated ecological safety protection measures in river basins to achieve high-quality development. Taking the Yellow River Basin as an example, this paper analyses the ecological level of the Yellow River Basin based on the theory of sustainable development, calculates the ecological safety level of 30 resource-based cities in the Yellow River Basin from 2006 to 2020 by TOPSIS model, and makes convergence analysis by classification. Through the DID empirical test of sustainable development planning policy on ecological safety factors, distinguish the development characteristics of different resource-based cities. The results show that: (1) the ecological safety level of resource-based cities in the Yellow River Basin is generally developing well, and there are differences among different types of resource-based cities; (2) the kinetic energy of sustainable development of resource-based cities in the Yellow River Basin is mainly industrial transformation, and the power of science and technology is insufficient; (3) local governments pay limited attention to environmental protection, and the sustainable development planning of resource-based cities in 2013 mainly promotes the adjustment of industrial structure of resource-based cities.

This paper seeks to model the crack propagation in of AAs (aluminum-alloys) 2524-T3 and 7050-T7452 subjected to fatigue loading at low temperature. Fatigue crack growth tests were performed on AAs 2524-T3 and 7050-T7452 subjected to constant-amplitude and actual random-spectra loading histories at room temperature of about 25 °C and at cryogenic temperature of -70 °C, respectively, to determine their crack growth properties and residual lives. The interaction mechanisms between cryogenic temperature and the fatigue load were deduced on the basis of the results of fractographic analysis. Temperature-dependent residual lives under actual random-spectrum load history were modeled based on a modified accumulation damage rule by accounting for the load interaction. Good correlation was achieved between the predictions and actual experiments, demonstrating the practical and effective use of the proposed method.

Hypoglossal nerve stimulator (HGNS) is a minimally invasive device used for treating obstructive sleep apnea (OSA). The conventional implantable HGNS is a device that consists of a stimuli generator, a breathing sensor, and electrodes connected to the hypoglossal nerve via leads. However, this implant is bulky and causes significant trauma. In this paper, we propose a minimally invasive HGNS based on an electrocardiogram (ECG) sensor and a wireless power transfer (WPT), consisting of a wearable breathing monitor and an implantable stimulator. The breathing external monitor utilizes an ECG sensor to identify abnormal breathing patterns associated with OSA with 88.68$\%$ accuracy, achieved through the utilization of a Convolutional Neural Network (CNN) algorithm. With a skin thickness of 5mm and a receiving coil diameter of 9mm, the power conversion efficiency was measured at 31.8$\%$. The implantable device, on the other hand, is composed of a front-end CMOS Power Management Module (PMM), a Binary Phase Shift Keying (BPSK)-based data demodulator, and a bipolar biphasic current stimuli generator. The PMM, with a silicon area of 0.06 $mm^2$ (excluding pads), demonstrates a power conversion efficiency of 77.5$\%$ when operating at a receiving frequency of 2 MHz. Furthermore, it offers three-voltage options (1.2V, 1.8V, and 3.1V). Within the data receiver component, a low-power BPSK demodulator has been ingeniously incorporated, consuming only 42 $\mu$W when supplied with a voltage of 0.7V. The performance is achieved through the implementation of the self-biased phase-locked loop (PLL) technique. The stimuli generator delivers biphasic constant currents, providing a 5-bit programmable range spanning from 0 to 2.4 mA. The functionality of proposed ECG and WPT-based HGNS was validated, representing a highly promising solution for the effective management of OSA, all while minimizing trauma and space requirements.

Coarse-grained molecular dynamics simulations are employed to investigate the spatiotemporal evolution of vesicles (polymersomes) by the self-assembly of randomly distributed amphiphilic BAB triblock copolymers with hydrophilic A and hydrophobic B blocks in an aqueous solution. The vesiculation pathway consists of several intermediate structures, such as an interconnected network of copolymer aggregates, a cage of cylindrical micelles and a lamellar cage. The cage-to-vesicle transition occurs at a constant aggregation number and practically eliminates the hydrophobic interfacial area between the B block and solvent. Molecular reorganization under-lying the sequence of morphology transitions from a cage-like aggregate to a vesicle is nearly isentropic. The end-to-end distances of isolated copolymer chains in solution and those within a vesicular assembly follow log normal probability distributions. This is attributed to the pre-ponderance of folded chain configurations in which the two hydrophobic end groups of a given chain stay close to each other. However, the probability distribution of end-to-end distances is broader for chains within the vesicle as compared to that of a single chain. This is due to the swelling of the folded configurations within the hydrophobic bilayer. Increasing the hydropho-bicity of the B block reduces the vesiculation time without qualitatively altering the self-assembly pathway.

Cellular substructure has been widely observed in the sample fabricated by laser powder bed fusion, while its growth direction and the crystallographic orientation have seldom been studied. This research tries to build a general model to construct the substructure from its two-dimensional morphology. All the three Bunge Euler angles to specify a unique growth direction are determined, and the crystallographic orientation corresponding to the growth direction is also obtained. Based on the crystallographic orientation, the substructure in the single track of austenitic stainless steel 316L is distinguished between the cell-like dendrite and the cell. It is found that, with the increase of scanning velocity, the substructure transits from cell-like dendrite to cell. When the power is 200 W, the critical growth rate of the transition in the single track can be around 0.31 ms^-1.

A number of challenging combinatorial optimization problems in logistics, transportations, aeronautics, and astronautics can be modeled as orienteering problems (OPs). To address the classic OP and its real-world variants, a parallel adaptive local-search algorithm based on competition and evolution (Palace) is proposed in this paper. In this algorithm, the parallelism runs proper local-search metaheuristics and operators to obtain the population per generation; then the competition grades those metaheuristics and operators to highlight the outperforming and eliminate the underperforming; also, the evolution explores large solution space and reproduces the best solutions for next generation. In this manner, the parallelism, competition, and evolution are organized in an easy-to-use algorithm and enable the expansibility, adaptivity, and exploration abilities, respectively. The Palace is examined on the classic and real-world Benchmarks about the OP, the time-dependent/independent OP with time windows, and the unmanned aerial vehicle and agile earth observation satellite planning. As a result, the Palace shows good performance in applicability and effectiveness in comparison with the state-of-the-art algorithms.

The article delves into the intricate phase transitions of 1-Octadecanol and n-Nonadecane within a binary system, unveiling dynamic structural changes under varying conditions. Through Fouri-er-transform infrared (FTIR) analysis, specific molecular vibrations were identified, shedding light on the molecular composition and interactions. The study highlights the challenges in detecting subtle phase transitions and emphasizes the individuality of molecular behaviours in closely related compounds. The findings underscore the complexity of phase transitions in binary systems and advocate for a nuanced approach to studying molecular structures and behaviours. Addi-tionally, the research contributes valuable insights into the molecular dynamics of Organic Polymer Functional Adsorption Materials, offering implications for synthetic waxy layers in plant epidermis.

This paper mainly explores the feasibility of using desert sand (DS) and recycled aggregate in cement stabilized base. Recycled coarse aggregate (RCA) and DS serve as the substitutes of natural coarse and fine aggregates, respectively, in cement stabilized base. A four-factor and four-level orthogonal test is designed to analyze the unconfined compressive strength, splitting tensile strength, and compressive resilient modulus. Furthermore, this paper investigates the effects of cement content, fly ash (FA) replacement rate, RCA replacement rate, and DS replacement rate on the road performance of cement stabilized base composing of RCA and DS. The test results reveal that the performance of cement stabilized base with partial RCA instead of natural coarse aggregate (NCA) and partial DS instead of natural fine aggregate satisfy the road use. Meanwhile, DS is beneficial to improve the strength of cement stabilized base. The correlation and microscopic analyses of the test results imply the feasibility of applying DS and recycled aggregate to cement stabilized base. It is hoped that this paper can offer a solid theoretical foundation for promoting the application of DS and recycled aggregate in road engineering.

Domain generalization has led to remarkable achievements in Hyperspectral Image (HSI) classification. Inspired by contrastive language-image pre-training (CLIP), the language-aware domain generalization method has been explored to learn cross-domain-invariant representation. However, existing methods face some challenges: 1) The weak capacity to extract long-range contextual information and inter-class correlation. 2) Due to the inadequacies of the large-scale pre-training for HSI data, the spatial-spectral features of HSI and linguistic features can not be straightforwardly alignment. To address the above problems, a novel network has been proposed with a CLIP framework, which consists of an image encoder, based on an encoder-only transformer to obtain the global contextual information and inter-class correlation, a frozen text encoder, and a cross-attention mechanism, named Linguistic-Interact-with-Visual Engager (LIVE), enhances the interaction between two modalities. Extensive experiments demonstrating superior performance over state-of-the-art methods in HSI Domain Generalization with a CLIP framework.

The present paper investigates numerically the resistance at full-scale of a zero-emission, high-speed catamaran in both deep and shallow water, with the Froude number ranging from 0.2 to 0.8. The numerical methods are validated by two means: a) comparison with available model tests; b) a blind validation using two different flow solvers. The resistance, sinkage and trim of the catamaran, as well as the wave pattern, longitudinal wave cuts and cross-flow fields, are examined. The total resistance curve in deep water shows a continuous increase with the Froude number while in shallow water, a hump is witnessed near the critical speed. This difference is mainly caused by the pressure component of total resistance, which is significantly affected by the interaction between the wave systems created by the demihulls. The pressure resistance in deep water is maximised at a Froude number around 0.58, whereas the peak in shallow water is achieved near the critical speed (Froude number ≈ 0.3). Insight into the underlying physics is obtained by analysing the wave creation between the demihulls. Profoundly different wave patterns within the inner region are observed in deep and shallow water. Specifically, in deep water, both crests and troughs are generated and moved astern as the increase of the Froude number. The maximum pressure resistance is accomplished when the secondary trough is created at the stern, leading to the largest trim angle. In contrast, the catamaran generates a critical wave normal to the advance direction in shallow water, which significantly elevates the bow and creates the highest trim angle as well as pressure resistance. Moreover, significant wave elevations are observed between the demihulls at supercritical speeds in shallow water which may affect the decision for the location of the wet deck.

Ischemic stroke is one of the most disabling diseases and a leading cause of death globally. Despite advances in medical care, the global burden of stroke continues to grow, as no effective treatments to limit or reverse ischemic injury to the brain are available. However, recent preclinical findings have revealed the potential role of transient receptor potential cation 6 (TRPC6) channels as endogenous protectors of neuronal tissue. Activating TRPC6 in various cerebral ischemia models has been found to prevent neuronal death, whereas blocking TRPC6 enhances sensitivity to ischemia. Evidence has shown that Ca2+ influx through TRPC6 activates cAMP response element-binding protein (CREB), an important transcription factor linked to neuronal survival. Additionally, TRPC6 activation may counter excitotoxic damage resulting from glutamate release by attenuating the activity of NMDA receptors of neurons by posttranslational means. Unresolved though, are the roles of TRPC6 channels in non-neuronal cells such as astrocytes and endothelial cells. Moreover, TRPC6 channels may have detrimental effects on the blood-brain barrier, although their exact role in neurovascular coupling requires further investigation. This review discusses evidence-based cell-specific aspects of TRPC6 in the brain to assess the potential targets for ischemic stroke management.

The design and fabrication of low-cost catalysts for highly efficient oxygen reduction is of paramount importance for various renewable energy-related technologies, such as fuel cells and metal-air batteries. Herein, we report the in situ growth of Fe3N nanoparticles encapsulated N-doped carbon nanotubes on the surface of flexible biomass-derived carbon cloth (Fe3N@CNTs/CC) via a simple one-step carbonization process. Taking advantage of its unique structure, Fe3N@CNTs/CC was employed as a self-standing electrocatalyst for oxygen reduction reaction (ORR) and possessed high activity as well as excellent long-term stability and methanol resistance in alkaline media. Remarkably, Fe3N@CNT/CC can directly play the role of both gas diffusion layer and electrocatalytic cathode in a zinc-air battery without additional means of catalyst loading, and display higher open circuit voltage, power density, and specific capacity in comparison with the commercial Pt/C catalyst. This work is anticipated to inspire the design of cost-effective, easy-preparation, and high-performance air electrodes for advanced electrochemical applications.

To ensure consumers can purchase high-quality rice, accurate identification of rice varieties is particularly important. Methods: This article conducts research based on machine learning algorithms from the perspectives of image, spectrum, and spectrogram fusion. Six types of hyperspectral image data of rice were preprocessed using convolutional smoothing (SG) and multiple scatter correction (MSC). Texture information of the images was extracted using gray-level co-occurrence matrix. Spectra, texture, and spectrogram data were fused into a new matrix. Spectral, texture, and spectrogram fusion data were used as inputs for the model, and support vector machines (SVM), logistic regression (LR), and K-nearest neighbors (KNN) classification models were constructed and compared. Results: From the classification results, the spectrogram fusion classification performance was better than classification models using only spectra or texture. Conclusion: The research results showed that the accuracy of SVM and LR classification models exceeded 90%, and the LR model performed the best, effectively classifying rice varieties.

Inflammation is the response of the immune system to infection and injury, with complex interactions with the body, tissues and cells, and plays an important role in the initiation and progression of many diseases such as cancer and cardiovascular disease. Traditional excipients functioning as drug delivery systems can reduce the side effects of systemic distribution of inflammatory drugs. Oil phase, a common excipient in nanoemulsions (NEs), has the advantages of assisting the formation of emulsions, loading lipophilic drugs, thermodynamic stability, wide sources, low price and easy availability. In particular, some of them, like linolenic acid and medium chain triglyceride (MCT), also function as inhibitors of systemic inflammation marker and vascular inflammation marker. However, the influences of different oil phases on the construction of NEs and their distribution in vivo have not been fully investigated. Herein, Tween 80 and ethyl alcohol were screened out as emulsifiers and co-emulsifiers, and three different oil phases used in clinical practice widely, including MCT, oleic acid (OA), and ethyl oleate (EO), were selected as the oil phase to prepare NEs delivery platform. Three NEs had consistent size, potential, morphology, excellent stability and mitochondrial localization function. Importantly, they exhibited superior cellular uptake capacity in inflammatory-injuried human umbilical vein endothelial cells and significantly targeted the brain, lung, heart and thoracic aorta in the lipopolysaccharide-induced mouse and zebrafish larvae inflammation models. Meanwhile, the fluorescence intensities of three NEs were different in these organs, suggesting that their differential enrichment might provide alternative delivery platform for disease treatment in the corresponding organs.

The multi-modal data fusion method based on IA-net and CHMM technical proposed is designed to solve the problem that the incompleteness of target behavior information in complex family environment leads to the low accuracy of human behavior recognition.The two improved neural networks(STA-ResNet50、STA-GoogleNet)are combined with LSTM to form two IA-Nets respectively to extract RGB and skeleton modal behavior features in video. The two modal feature sequences are input CHMM to construct the probability fusion model of multi-modal behavior recognition.The experimental results show that the human behavior recognition model proposed in this paper has higher accuracy than the previous fusion methods on HMDB51 and UCF101 datasets. New contributions: attention mechanism is introduced to improve the efficiency of video target feature extraction and utilization. A skeleton based feature extraction framework is proposed, which can be used for human behavior recognition in complex environment. In the field of human behavior recognition, probability theory and neural network are cleverly combined and applied, which provides a new method for multi-modal information fusion.

Sinojackia Hu. comprises five to eight Chinese endemic species with high ornamental and medicinal value. However, the generic limits, interspecific relationships and evolutionary history of the genus remain unresolved. In this study, we newly sequenced and assembled three plastomes of S. oblongicarpa and compared them with those of the other congeneric species to explore the taxonomic delimitation of the species and the evolutionary history of the genus. Plastomes structure of Sinojackia species were extremely conserved in terms of number of genes, sequence length and GC content. Codon usage patterns revealed that natural selection may be the main factor shaping codon usage bias. Our phylogenetic tree shows that Sinojackia is monophyletic and can be divided into two clades. Sinojackia oblongicarpa as a distinct species is supported for it is distantly related to S. sarcocarpa. The evolutionary analysis of morphological features indicates that woody mesocarp is an ancestral feature, while mesocarp undeveloped, spongy and fleshy are the later derived. Sinojackia originated in Central-Southeast China during the early Miocene. In this period, it experienced elevated diversification and migrated from the Central-Southeast China to Hunan Province and Sichuan Province with the development of the Asian monsoon and East Asian flora. Sinojackia experienced elevated diversification at intraspecies levels that mainly occurred in the Quaternary. Glacial-interglacial interactions with the monsoon climate may provide favorable expansion conditions for Sinojackia on a small-scale.

Controlling surface-protein interaction during wastewater treatment is the key motivation for developing functionally modified membranes. A new biocatalytic thermo-responsive poly(vinylidene fluoride)(PVDF)/nylon-6,6/poly(N-isopropylacrylamide)(PNIPAAm) ultrafiltration membrane was fabricated to achieve dual functionality of protein-digestion and thermo-responsive self-cleaning. The PVDF/nylon-6,6/PNIPAAm composite membranes were constructed by integrating a hydrophobic PVDF cast layer and hydrophilic nylon-6,6/PNIPAAm nanofiber layer where trypsin enzymes were covalently immobilized. The immobilization density of enzymes on the membrane surface decreased with increasing PNIPAAm concentration, due to the decreased number of amine functional sites. Through a ultrafiltration study using a model solution containing BSA/NaCl/CaCl₂, the PNIPAAm containing biocatalytic membranes demonstrated a combined effect of enzymatic and thermo-switchable self-cleaning. The membrane without PNIPAAm revealed superior fouling resistance and self-cleaning with an R_PD of 22%, compared to membranes with 2 and 4 wt% PNIPAAm with 26% and 33% R_PD, respectively, after an intermediate temperature cleaning at 50°C, indicating that higher enzyme density offers more efficient self-cleaning than the combined effect of enzyme and PNIPAAm at low concentration. The conformational volume phase transition of PNIPAAm did not affect the stability of immobilized trypsin on membrane surface. Such novel surface engineering design offer a promising route to severe surface-protein contamination remediation in food and wastewater applications.

Underwater visual detection technology plays a pivotal role in fields such as marine exploration. With the increasing demand for underwater monitoring, the quest for efficient and reliable methods for underwater target recognition has become particularly significant. To address this requirement, this study developed an innovative underwater object detection architecture based on YOLOv8, named YOLOv8-MU, aimed at significantly enhancing detection accuracy.By integrating the LarK module proposed in UniRepLKNet to optimize the backbone network, YOLOv8-MU aims to achieve a larger receptive field without increasing the model’s depth. Further, this research introduces C2fSTR, an innovative method that combines Swin Transformer with the C2f module. Additionally, we have incorporated the SPPFCSPC_EMA module, which combines Cross-Stage Partial Fast Spatial Pyramid Pooling (SPPFCSPC) with attention mechanisms, significantly improving the detection accuracy and robustness of various biological targets. Moreover, by introducing a fusion block based on DAMO-YOLO into the neck of the model, we further enhanced the model’s capability in multi-scale feature extraction. Finally, the adoption of the MPDIoU loss function, designed around vertex distance, effectively tackles the challenges of localization accuracy and boundary clarity in underwater organism detection. Experimental results on the URPC2019 dataset demonstrate that the YOLOv8-MU model achieved an [email protected] of 78.4%, marking improvements of 5.6%, 1.1%, and 4.0% over YOLOv5s, YOLOv7, and YOLOv8n respectively, indicating the leading performance (SOTA) of this method. On the other hand, further evaluation on the URPC2020 dataset confirmed the generalization capability of the YOLOv8-MU architecture, with its [email protected] reaching 80.4%, surpassing various models including YOLOv5x and YOLOv8n, showcasing the wide applicability of our proposed improved model architecture.

Hierarchical tungsten oxide assemblies such as spindle-like, flowers with sharp petals, nanowires and regular hexagonal structures are successfully synthesized via a solvothermal reduction method by simply adjusting the reaction conditions. On the basis of the experimental results, it is determined that the reaction time significantly influences the phase transition, microstructure and photocatalytic activity of the prepared samples. The possible mechanisms for the phase transition and morphology evolution process have been systematically proposed. Moreover, the as-prepared products exhibit significant morphology-depended photocatalytic activity. The flower-like W18O49 prepared at 6 h possesses large specific surface area (150.1 m²g^-1), improved separation efficiency of electron-hole pairs and decreased electron-transfer resistance by the photoelectrochemical measurements. As a result, the flower-like W₁₈O₄₉ prepared at 6 h exhibits the highest photocatalytic activity for the degradation of Methyl orange aqueous solution. The radical trap experiments showed that the degradation of MO was driven mainly by the participation of h⁺ and •O²⁻ radicals.

This paper presents a piezoresistive pressure sensor with a shield layer for improved stability. Compared with the conventional piezoresistive pressure sensors, p-type piezoresistors are covered by an n-type shield layer, which is formed by ion implantation. The proposed pressure sensors have been successfully fabricated by bulk micromachining techniques. The impact of electrical field on piezoresistors is studied by simulation. The temperature drift of the pressure sensor has been investigated by both simulation and experimental measurement. Characteristics of developed pressure sensors are tested from -40 C to 125 C. A sensitivity of 0.022 mV/V/KPa and a maximum non-linearity of 0.085% FS are measured for the fabricated sensor in a pressure range of 1 MPa. The temperature coefficients of resistance of shielded piezoresistors are found to be smaller than those of un-shielded ones. It is demonstrated that the shield layer is able to reduce the drift caused by electrical field and ambient temperature variation.

Amid the swift progression of the global automobile industry, the aspiration for lightweight vehicle design has surfaced as a crucial approach to boost fuel efficiency and curtail environmental impact. The objective of this study revolves around achieving holistic optimization of vehicle structure via detailed scrutiny of vehicle process characteristics, amalgamated with a Back Propagation neural network (BPNN) optimized by a genetic algorithm (GA) and a topology optimization (TO) method.The process initiates with an examination of the vehicle's technical characteristics, succeeded by an optimization protocol that couples GA with BPNN. This exhaustive optimization procedure derives the best-fit values of design parameters and identifies the globally optimal lightweight design approach. Subsequently, a comprehensive structural optimization is actualized by modifying the topological distribution of the structure.A simulation experiment of the conceptual car body beam skeleton is conducted as a conclusive step, and the anti-collision capacity of the car body beam skeleton is assessed by measuring deformation intrusion. The findings reveal that in the vehicle topology optimization, a comparative analysis of pre and post-optimization results indicates an improved topological density across diverse sections. The topological density of the vehicle's frontal structure escalates from 0.75 to 0.8. Following optimization, the stiffness assessment records a marginal increase (within the range of 0.02–0.05), implying that the lightweight design does not compromise the general rigidity of the structure.The optimized body structure manifests superior crashworthiness in the crash test: the deformation intrusion diminishes by 27% in front-end collisions. In side impacts, the deformation and intrusion at critical points are reduced by 13.15% to 10% respectively. The comprehensive method proposed herein proves to be an efficient strategy to actualize the lightweight design of vehicles.

Parental phubbing behavior is a significant factor in predicting adolescent smartphone dependence, but prior research has predominantly focused on a unidirectional perspective from the child's viewpoint, overlooking potential perceptual differences between parents and their children regarding parental phubbing. Therefore, are there differences in the perceptions of parental phubbing between parents and their children? Based on the "Discrepancy-Maladaptive" hypothesis, the presence of perceptual discrepancies in family factors can lead to adverse developmental outcomes in children. Does the parent-child perceptual discrepancy in parental phubbing influence adolescent smartphone dependence? And what role does parent-child relationship play in this context? This study selected 728 families from a middle school in Wuhan, and surveys were administered to both children and parents. The findings reveal: (1) There exist significant parent-child perceptual discrepancies in parental phubbing. (2) Parent-child perceptual discrepancies in parental phubbing significantly positively predict adolescent smartphone dependence and negatively predict parent-child relationships, while parent-child relationships significantly negatively predict adolescent smartphone dependence. (3) The parent-child relationship plays a mediating role between parent-child perceptual differences in parental phubbing behavior and adolescent smartphone dependence.

The composition, structure and functionalities of prolamins from highland barley was investigated. These parameters of was compared with the widely applied prolamins (zein). There are more charged and hydrophilic amino acids in prolamins from highland barley than zein. The molecu-lar weight of prolamins from highland barley were between 30 to 63 kDa, which was larger than zein (20 to 24 kDa). β-turn helices is the main secondary structure in prolamins from highland barley, while α-helical structure is the main secondary structure in zein. The water holding capacity, thermal stability, emulsifying capacity and stability of prolamins from highland barley is quite lager than zein, while opposite results can be observed for oil absorption capacity. The diameter of fibers prepared with prolamins from highland barley was almost 6 times that of zein, while ribbon structures rather than fibers were formed by prolamins from highland barley. The results would provide the guidance for application of prolamins from highland barley.

Randomized block Kaczmarz Method and randomized extended block Kaczmarz Method are proposed for solving matrix equation AXB=C, where the matrix A and B may be full rank or rank deficient. These methods are iterative methods without matrix multiplication, and are especially suitable for solving large-scale matrix equations. It is theoretically proved these methods converge to the solution or least square solution of the matrix equation. The numerical results show that these methods are more efficient than the existing algorithms for high-dimensional matrix equations.

Road cracks significantly affect the serviceability and safety of roadways, especially in mountainous terrain. Traditional inspection methods, such as manual detection, are excessively time-consuming, labor-intensive, and inefficient. Additionally, multi-function detection vehicles equipped with various sensors are expensive and not suitable for mountainous roads due to poor conditions. To address these challenges, this study proposes a customized Unmanned Aerial Vehicles (UAV) inspection system designed for automatic crack detection. The system focuses on enhancing autonomous capabilities in mountainous terrains by incorporating embedded algorithms for route planning, autonomous navigation, and automatic crack detection. The slide window method is proposed to enhance the autonomous navigation of UAV flights by generating path planning in mountainous roads. This method compensates for GPS/IMU positioning errors, particularly in GPS-denied or GPS-drift scenarios. Moreover, the YOLOv8 algorithm is introduced to conduct autonomous crack detection from UAV imagery in the offboard module. To validate our UAV inspection system's performance, we conducted several experiments to assess its accuracy, robustness, and efficiency. The experimental results demonstrate that our UAS inspection system accurately estimates the flight trajectory along the mountainous road for autonomous navigation. Furthermore, the experimental detection results also demonstrate that the YOLOv8 algorithm achieves higher recognition accuracy compared to the YOLOv5, and YOLOv7-tiny algorithms, exceeding 3.1%,and 6.8% of mAP, respectively. In summary, the UAV inspection system proposed in this study can provide a useful tool and technological guidance for the regular inspection of mountainous roads.

Histone demethylases, enzymes responsible for removing methyl groups from histone proteins, have emerged as critical players in regulating gene expression and chromatin dynamics, thereby influencing various cellular processes. LSD2 and LSD1 have attracted considerable interest among these demethylases because of their associations with cancer. However, while LSD1 has received significant attention, LSD2 has not been recognized to the same extent. In this study, we conduct a comprehensive comparison between LSD2 and LSD1, with a focus on exploring LSD2's implications. While both share structural similarities, LSD2 possesses unique features. Functionally, LSD2 shows diverse roles, particularly in cancer, with tissue-dependent roles. Additionally, LSD2 extends beyond histone demethylation, impacting DNA methylation and DNA damage repair pathways. This study underscores the distinct roles of LSD2, providing insights into their contributions to cancer and other cellular processes.

Contaminants of Emerging Concern (CECs), a new category of contaminants in limelight, is a major issue of global concern. The pervasive nature of CECs and its harmful effects, such as cancer, reproductive disorders, neurotoxicity etc., make the situation alarming. The perilous nature of CECs lies in the fact that even very small concentration of CECs can cause great impacts on living beings. It also has a nature of bioaccumulation. Thus, it is the ultimate need to have efficient sensors for detection of CECs to ensure safe living environment. Electrochemical sensors are an efficient platform for CEC detection as they are highly selective, sensitive, stable, reproducible, and prompt, and can detect very low concentrations of analyte. Major classes of CECs are pharmaceuticals, illicit drugs, personal care products, endocrine disruptors, newly registered pesticides, and disinfection by-products. This review focusses on CECs, including their sources and pathways, health effects caused by them, and electrochemical sensors as reported in literatures under each category for the detection of major CECs.

Pavement crack detection is one of the key links in highway pavement maintenance management. In the current road crack detection, the network model easily ignores the shallow geometric features of cracks and cannot extract the key feature information of cracks. Aiming at the above problems, an EC-YOLOX network model is proposed. The CFPN is constructed to cross-fuse different scale features to solve the feature scale invariance. In the strengthen feature extraction layer, ECANet is fused to enhance the ability to pay attention to key information. The WEIoU loss function is proposed, which assigns different penalty terms to the target box in the vertical and horizontal directions. In terms of data, geometric distortion constraint correction is performed on the single-point perspective pavement image. The experimental data show that the accuracy of EC-YOLOX on the self-built data set reaches 76.34% [email protected], which is 4.45% higher than that of YOLOX. The loss curve of EC-YOLOX is smoother than that of YOLOX, and the minimum training loss value is 2.136, which is 0.648 lower than the minimum loss value 2.784 of YOLOX. Many experiments have verified the effectiveness of EC-YOLOX in improving the detection effect in pavement crack detection.

The ergosterol pathway is a prime antifungal target. The minimum inhibitory concentration (MIC) assay is a simple research tool that determines the lowest concentration at which a novel antimicrobial with limited scope to determine the mechanism of action for a drug. In this study, we show that by adding hydrogen peroxide, an oxidative stressor, or glutathione (GSH), an antioxidant, to modify a commonly performed MIC assay allowed us to screen selectively for new antifungal drugs that target ergosterol biosynthesis in fungi. A human pathogen, Microsporum gypseum, was used as a test organism. When exposed to ergosterol targeting drugs, the hydrogen peroxide treatment significantly decreased fungal survival by reducing ergosterol in the cell wall, whereas GSH increased survival of M. gypseum. Further, by performing a series of experiments with M. gypseum, it was determined that the oxidative stress from hydrogen peroxide causes cell death at different developmental stages. These findings allow us to describe a simple, high-throughput method for simultaneously screening new antifungal drugs for activity and effects on the ergosterol pathway. By using this tool, two isoquinoline alkaloids were discovered to be potent inhibitors of ergosterol biosynthesis by reducing the amount of ergosterol without affecting the expression of 1,3-β-glucan.