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The discrete element method (DEM) has been extensively utilized to investigate the mechanical properties of granules, particularly their microscopic behavior, overcoming limitations in field tests such as cost, time consumption, and soil condition restrictions. To ensure the development of reliable DEM simulations, proper contact model selection and parameter calibration are essential. In this research, a DEM parameter calibration method that could represent the nonlinear relationship between clayey soil pressure and sinkage at different moisture contents was proposed. Firstly, the sinking modulus K and the soil deformation exponent n were identified to reflect the nonlinear pressure–sinkage relationship. Then, sensitive DEM parameters on the soli pressure–sinkage relationship were investigated and calibrated, and the effect of moisture content on them was explored. Finally, the transfer of soil internal stress during subsidence was analyzed using the constructed discrete element model. The average error of the sinking modulus K and the soil deformation exponent n between the DEM and the experimental result at four moisture contents were 4.7% and 4.9%, respectively. The relative error of soil internal stress between simulation and experiment was 6.7%, 4.4%, and 9.7% at depths of 50 mm, 100 mm, and 150 mm, respectively. The soil particle trajectory, soil internal stress distribution, and variations during plate pressure–sinkage progress were analyzed by the constructed DEM model. The results demonstrated good agreement with theoretical models and experimental findings. The proposed clayey soil DEM modeling process that considers the pressure–sinkage nonlinear relationship at different moisture contents can be applied in machine-soil research.

An innovative technology for the direct reduction of copper slag was studied while smelting Cu-Fe alloy by carbon to recover the main valuable elements from the copper smelting slag. The melting temperature of samples first decreased, followed by an increase in Fe3O4 content in slag. The melting temperature reached the minimum temperature of 1157 °C once the Fe3O4 content was about 8 wt%. The recovery rate of copper and iron first increased gradually, followed by a rapid increase in the modifier (CaO). Subsequently, the rise in the recovery rate slowed down. The reduction rate of copper and iron only increased by 1.61% and 1.05% from 5 wt% CaO to 10 wt% CaO, but significantly increased by 8.89% and 14.21% from 10 wt% CaO to 25 wt% CaO, and remained almost unchanged beyond 25 wt% CaO. This could be attributed to the reaction between modifier (CaO) and silicate in acidic copper slag to generate low melting point composite oxide while replacing free iron oxides, improving the melting properties and reduction reaction. Meanwhile, the recovery rates of copper and iron increased with the increase of reaction time, reaction temperature, and reduction agent in a certain range. To obtain good element yield, the optimum conditions for reducing copper and iron from the molten copper slag were determined to be 1500 °C, 14 wt% C, 20–25 wt% CaO, and 60–80 min. The recovery rates of iron and copper reached about 90% and 85%, and the contents of iron and copper in alloy reached about 91–93 wt% and 5–7 wt%, respectively. The tailing was mainly composed of Ca3Si3O9, Ca(Mg,Al)(Si,Al)2O6, and SiO2, which could be used as a raw material for cement and pelletizing.

The 7A04 Al alloy is a commonly used lightweight metal material; however, its low wear resistance limits its application. In this study, the wear resistance of this alloy was improved by preparing micro-arc oxidation (MAO) coatings, MAO/MoS2 composite coatings, and hard-anodized (HA) coatings on its surface. The friction and wear behaviors of these three coatings with diamond-like coated (DLC) rings under oil lubrication conditions were investigated using a ring–block friction tester. The wear rates of the coatings on the block surfaces were determined using laser confocal microscopy, and the wear trajectories of the coatings were examined using scanning electron microscopy. The results indicated that, among the three coatings, the MAO/MoS2 coating had the lowest coefficient of friction of 0.059, whereas the HA coating had the lowest wear rate of 1.47 × 10−6 mm/Nm. The MAO/MoS2 coatings exhibited excellent antifriction properties compared to the other coatings, whereas the HA coatings exhibited excellent anti-wear properties. The porous structure of the MAO coatings stored lubricant and replenished the lubrication film under oil lubrication. Meanwhile, the introduced MoS2 enhanced the densification of the coating and functioned as a solid lubricant. The HA coating exhibited good wear resistance owing to the dense structure of the amorphous-phase aluminum oxide. The mechanisms of abrasive and adhesive wear of the coatings under oil lubrication conditions and the optimization of the tribological properties by the solid–liquid synergistic lubrication effect were investigated. This study provides an effective method for the surface modification of Al alloys with potential applications in the aerospace and automotive industries.

The hybrid plant edible grass (Rumex patientia L. × Rumex tianschanicus A. LOS), a member of the Rumex genus, presents a novel food source with a protein content of approximately 30–40%. By incorporating non-traditional feed sources, such as edible grass leaf powder (EGLP), into broiler production, costs could be reduced. The experimental subjects of this study were Arbor Acres (AA) broilers. A total of 300 newly hatched broilers were randomly divided into to five groups, with each group consisting of six cages, housing 10 birds per cage. The control group was fed a basal diet composed of maize and soybean meal. In the experimental groups, varying percentages (3%, 6%, 9%, and 12%) of EGLP were substituted for the corn–soybean meal in the basal diet. In the diet, for days 1–21, the corn content was reduced from 1.90% to 8.20%, and the soybean meal content was lowered from 1.50% to 6.00%. Similarly, in the diet, for days 22–42, the corn content was decreased from 1.17% to 7.00%, while the soybean meal content was reduced by 1.50% to 6.00%. The experiment lasted 42 days and was divided into two phases: the brooding phase (days 1 to 21) and the finishing phase (days 22 to 42). The results show that substituting 3% and 6% EGLP for corn and soybean meal significantly increased the average daily gain (ADG) during the brooding period compared to the control group (p < 0.01). Additionally, the group with a 3% substitution rate exhibited a significant increase in the average daily feed intake (ADFI) during the brooding phase (p < 0.01). Throughout the 42-day experiment, substituting 3% and 6% of EGLP for maize and soybean meal did not significantly affect the overall growth performance of broilers (p > 0.05). However, a 6% supplementation notably reduced the feed conversion ratio (FCR) (p < 0.01). Both the 3% (EG3) EGLP and 6% (EG6) EGLP replacement meals significantly enhanced the antioxidant capacity of broiler chickens, as indicated by the increased levels of the total antioxidant capacity (T-AOC), superoxide dismutase (SOD), and glutathione peroxidase (GSH-Px) (p < 0.01). Additionally, broilers supplemented with 3–12% showed a marked increase in cecal short-chain fatty acids (SCFAs) compared to the control group (p < 0.01). The 3% EGLP replacement diet also significantly boosted the prevalence of Lactobacillus in the cecum (p < 0.01). Furthermore, after EGLP supplementation, there was a higher abundance of SCFA-metabolizing bacteria, particularly Alistipes and Christensenellaceae_R-7, compared to pre-treatment (p < 0.05). The prevalence of Clostridium was significantly greater in the groups receiving 9% and 12% EGLP (p < 0.05), while Butyrivibrio levels were notably higher after supplementation with 12% EGLP (p < 0.05).

Chitosan, a cationic polysaccharide derived from the deacetylation of chitin, is widely distributed in nature. Its antibacterial activity, biocompatibility, biodegradability, and non-toxicity have given it extensive uses in medicine, food, and cosmetics. However, the significant impact of variations in the physicochemical properties of chitosan extracted from different sources on its application efficacy, as well as the considerable differences in its antimicrobial mechanisms under varying conditions, limit the full realization of its biological functions. Therefore, this paper provides a comprehensive review of the structural characteristics of chitosan, its preparation methods from different sources, its antimicrobial mechanisms, and the factors influencing its antimicrobial efficacy. Furthermore, we highlight the latest applications of chitosan and its derivatives across various fields. We found that the use of microbial extraction shows promise as a new method for producing high-quality chitosan. By analyzing the different physicochemical properties of chitosan from various sources and the application of chitosan-based materials (such as nanoparticles, films, sponges, and hydrogels) prepared using different methods in biomedicine, food, agriculture, and cosmetics, we expect these findings to provide theoretical support for the broader utilization of chitosan.

To address the challenges of labor-intensive and costly manual oyster spat insertion in longline-suspended farming, an automated oyster spat insertion device was designed based on negative pressure suction and bundling fixation technologies. Using this device as the experimental platform, a three-factor, three-level Box–Behnken experiment was conducted, with fixation mechanism inclination, negative pressure suction cup span, and horizontal distance between turnover and fixation mechanisms as the experimental factors. The performance of the device was evaluated using the effective fixation rate and damage rate as the experimental indicators. The quadratic polynomial regression models were established to assess the impact of these factors on operational performance, while the response surface method was employed to analyze the interaction effects between factors. Parameter optimization and experimental validation were also performed. The results indicate that the factors affecting the effective fixation rate, in order of significance, are as follows: fixation mechanism inclination, horizontal distance between turnover and fixation mechanisms, and negative pressure suction cup span. For the damage rate, the order of significance is as follows: fixation mechanism inclination > negative pressure suction cup span < horizontal distance between turnover and fixation mechanisms. The optimization results show that when the fixation mechanism inclination is set at 43°, the negative pressure suction cup span at 27 mm, and the horizontal distance between turnover and fixation mechanisms at 179 mm, the effective fixation rate reaches 92.08%, and the damage rate is 4.71%. The relative errors between the measured and model-predicted values are less than 5%, indicating that the regression models are reliable. This research provides valuable insights for advancing the mechanization of the oyster farming industry and replacing manual labor with mechanized equipment.

The potential benefits of biochar, a carbon-rich substance derived from biomass, for enhancing agricultural yield and soil health have drawn increasing interest. Nevertheless, owing to the lack of specialized studies, the role of its poly-spatial structure in the success of fostering plant growth remains unclear. This study aimed to assess the effects of various biochar pore shapes on tobacco growth and the underlying microbiological processes. Three pyrolysis temperatures (250 °C, 400 °C, and 550 °C) were used to produce biochar from tobacco stems, resulting in different pore structures (T3 > T2 > T1). We then used BET-specific surface area (BET), t.Plot micropore specific surface area (t.Plot), mesopore specific surface area (MSSA), specific pore volume (SPV), average pore size (AP), and mesopore pore volume (MPV) measurements to evaluate the effects of these biochars on tobacco growth and biomass accumulation, and microbial analyses were performed to investigate the underlying mechanisms. When applied to plants, biochar increased their growth compared to untreated controls. The most notable improvement in tobacco growth was observed in the biochar produced at 400 °C (T3), which possessed the largest and most advantageous pore structure among all treatments. Further studies demonstrated that biochars with greater specific surface areas (BET, t.Plot, and MSSA) positively altered the abundance of key microbial taxa (e.g., Stenotrophobacter, Ensifer, Claroideoglomus) and community composition, thereby encouraging plant development and biomass accumulation. Conversely, greater pore volumes (SPV, AP, and MPV) inhibited microbial activity and significantly affected growth and biomass accumulation. Structural equation modeling further demonstrated that the pore structure of biochar greatly affected plant growth by changing the relative abundance and community composition of soil microbes. Maximizing the benefits of biochar in stimulating plant growth and improving soil microbial communities depends on optimizing the material’s pore structure, particularly by increasing the specific surface area. These findings will help expand the use of biochar in sustainable agriculture.

In the paper, we consider the PH2-distribution, which is a particular case of the PH-distribution. In other words, The first service phase is exponentially distributed, and the service rate is μ. After the first service phase, the customer can to go away with probability p or continue the service with probability (1−p) and service rate μ′. We study an analysis of an M/PH2/1 queue model with catastrophes, which is regarded as a generalization of an M/M/1 queue model with catastrophes. Whenever a catastrophe happens, all customers will be cleaned up immediately, and the queuing system is empty. The customers arrive at the queuing system based on a Poisson process, and the total service duration has two phases. Transient probabilities and steady-state probabilities of this queuing system are considered using practical applications of the modified Bessel function of the first kind, the Laplace transform, and probability-generating function techniques. Moreover, some important performance measures are obtained in the system. Finally, numerical illustrations are used to discuss the system’s behavior, and conclusions and future directions of the model are given.

The application of air-core reactors in power systems is extensive and primarily aimed at enhancing system stability, limiting short-circuit currents, and providing reactive power compensation. Currently, the type most commonly used in power systems is the cylindrical-shaped air-core reactor (CAR), known for its stable mechanical structure and mature manufacturing process. However, the external magnetic field generated by this reactor propagates over a considerable distance in the air, which can interfere with the normal operation of many power electronic devices. This paper presents a comparative analysis between a novel annular-shaped air-core bridge arm reactor (AABAR) and the widely used cylindrical-shaped air-core bridge arm reactor (CABAR) within a DC transformer system. The comparison focuses on the magnetic field distribution, including magnetic flux density, magnetic field radiation range, and magnetic field energy, as well as the attenuation characteristics of these physical quantities. The concept of magnetic clearance (MC) is introduced as a quantitative metric. Through finite element simulation software (AEDT 2021 R1), it is demonstrated that the annular-shaped air-core reactor design can significantly improve spatial utilization and reduce the actual usage space of the reactors in DC transformer systems.

With the unprecedented growth of the Internet, online evaluations of teaching have emerged as a pivotal tool in assessing the quality of university education. Leveraging data mining technology, we can extract invaluable insights from these evaluations, offering a robust scientific foundation for enhancing both teaching quality and administrative oversight. This study utilizes teaching evaluation data from a mathematics course at a university in Beijing to propose a comprehensive data mining framework covering both subjective and objective evaluations. The raw data are first cleaned, annotated, and preprocessed. Subsequently, for subjective evaluation data, a model combining Bidirectional Encoder Representations from Transformers (BERT) pre-trained models and Long Short-Term Memory (LSTM) networks is constructed to predict sentiment tendencies, achieving an accuracy of 92.76% and validating the model’s effectiveness. For objective evaluation data, the Apriori algorithm is employed to mine association rules, from which meaningful rules are selected for analysis. This research effectively explores teaching evaluation data, providing technical support for enhancing teaching quality and devising educational reform initiatives.

Ulcerative colitis (UC) is a typical inflammatory bowel disease (IBD), impairing the quality of life of patients. Dehydroevodiamine (DHE) is an active alkaloid isolated from Tetradium ruticarpum that exerts significant anti-inflammatory effects in gastrointestinal diseases. However, the effect and mechanisms of DHE on UC remain unclear. We performed a DSS-induced experimental UC rat model to reveal the efficacy and potential mechanisms of DHE on UC. HE and AB-PAS staining were used for the evaluation of pathologies, and 16S rRNA sequencing was used to detect changes in gut microbes. Metabolomics was used to detect changes in serum metabolites. Network pharmacology and transcriptomics were conducted to reveal the underlying mechanisms of DHE for UC. HuProt proteome microarrays, molecular docking, and SPR were used to reveal the targets of action of DHE. WB, RT-qPCR, and IHC were used to assess the action effects of DHE. DHE demonstrated significant alleviation of DSS-induced colitis symptoms in rats by suppressing inflammatory and oxidative stress responses, amending colonic barrier injury, and inhibiting apoptosis. In terms of gut microbial modulation, DHE decreased the abundance of Allobaculum, Clostridium, Escherichia, Enterococcus, and Barnesiella and increased the abundance of Lactobacillus, Bifidobacterium, and SMB5. Moreover, metabolomics suggested that the regulation of DHE in DSS-induced UC rats mainly involved aminoacyl-tRNA biosynthesis, vitamin B6 metabolism, phenylalanine, tyrosine, and so on. Mechanically, DHE alleviated UC in rats by targeting AKT1, thereby inhibiting the PI3K/AKT/NF-κB signaling pathway.

Accurately calculating winding losses has always been a significant challenge in the design of large-capacity medium-frequency transformers. This paper presents an accurate design algorithm for calculating the winding losses of a large-capacity medium-frequency distribution transformer. First, the peculiarities of winding losses in medium-frequency distribution transformers are analyzed. Various commonly used winding conductor types for medium-frequency transformers are introduced. The mechanisms of and differences between AC and DC winding losses in medium-frequency transformers are explained, and an effective analytical method for calculating the AC-to-DC resistance ratio is provided. Finally, the analytical calculation results of different types of winding losses are compared with those obtained through finite element simulations and experimental methods applied to a real transformer prototype. The discrepancies between the analytical results and those obtained using the other two methods were found to be within acceptable error margins, thereby validating the accuracy and effectiveness of the proposed algorithm.

The impacts of the growth and linkage of fault segments on sedimentation in a lacustrine rift basin, the Weixinan Depression, the Beibuwan Basin, in the northern South China Sea, which has been demonstrated to have huge petroleum potential, are elucidated on the basis of well-constrained 3D seismic data. Two main fault systems, the No. 1 boundary fault system and the No. 2 fault system, were developed in the Weixinan Depression. The evolution of the lower basement is based on the No. 1 fault system, which controls the distribution of depocenters (ranging from 450–800 m) within the lower structural layer. It includes the five fault segments isolated at the initial stage, the interaction and propagation stage, the linkage stage, and the decline stage. The No. 2 fault system governs the deposition of the upper structural layer with a series of discrete depocenters in the hangingwall. Initially, it comprises several right-order echelon branching faults. Each branch fault rapidly reached the existing length and maintained a constant length while establishing soft links with each other in the subsequent displacement accrual. The development of topographic slopes, transition zones, transverse anticlines, and related fault troughs and gullies related to the activity of the No. 1 boundary fault system is the main controlling factor that induces the differential development of the western, middle, and eastern sections of steep slope fans. The differential subsidence effect along the No. 2 fault system is responsible for the multiple ‘rising-stable’ stage changes in the relative lake level during the development of axial delta deposits. This study will help elucidate the different controls of extensional fault systems on associated sedimentation, as well as rift basin development in the South China Sea and similar areas throughout the world.

The development of reusable liquid rocket turbopumps has gradually highlighted the disadvantages of rolling bearings, particularly the contradiction between long service life and high rotational speed. It is critical to explore a feasible bearing scheme offering a long wear life and high stability to replace the existing rolling bearings. In this study, liquid nitrogen is adopted to simulate the ultra-low temperature environment of liquid rocket turbopumps, and theoretical evaluations of the lubrication performance of thrust-type foil bearings in liquid nitrogen are conducted. A link-spring model for the bump foil structure and a thin-plate finite element model for the top foil structure are established. The static and dynamic characteristics of the bearings are analyzed using methods including the finite difference method, the Newton–Raphson iteration method, and the finite element method. Detailed analysis includes the effects of factors such as rotational speed, fluid film thickness, thrust disk tilt angle, and the friction coefficient of the bump foil interface on the static and dynamic characteristics of thrust-type foil bearings. The research results indicate that thrust-type foil bearings have a good load-carrying capacity and low frictional power consumption. The adaptive deformation of the foil structure increases the fluid film thickness, preventing dry friction due to direct contact between the rotor journal and the bearing surface. When faced with thrust disk tilt, the direct translational stiffness and damping coefficient of the bearing do not undergo significant changes, ensuring system stability. Based on the results of this study, the exceptional performance characteristics of thrust-type foil bearings make them a promising alternative to rolling bearings for the development of reusable liquid rocket turbopumps.

“Not In My Back Yard” (NIMBY) conflicts have emerged as a significant challenge in the siting and construction of power grid projects. Traditional risk management methods are often inadequate for addressing the complex interactions between the multiple factors involved in such projects. To explain the relationship between different influencing factors, this paper constructs the hierarchy between the influencing factors using the Interpretive Structural Model (ISM) and carries out a causal analysis of NIMBY conflicts in power grid construction projects using the Bayesian network model. The results of the ISM hierarchical map show that high risk perception and construction practices lacking refinement are the most direct causes of NIMBY incidents. The Bayesian network model indicates that poor construction practices, negative public opinion, high risk perception, inadequate risk assessment and emergency response mechanisms, and negative externalities are the most sensitive factors within the causal system of NIMBY incidents and require priority attention. An increase in risk perception is also found to significantly escalate the severity of NIMBY conflicts. The insights gleaned in this study may provide valuable guidance for managing NIMBY conflicts in power grid construction projects.

In order to address the problems of range ambiguity and azimuth ambiguity in the wide-swath imaging of synthetic aperture radar (SAR), this paper proposes a multi-beam SAR two-dimensional ambiguity suppression method based on azimuth phase coding (APC). The scheme employs an elevation simultaneous multi-beam transmission system with azimuth under-sampling, transmitting different APC waveforms to various range-ambiguous sub-regions. After receiving the echoes, the azimuth digital beamforming (DBF) is used to separate the APC waveform echoes with multi-order Doppler ambiguity, achieving azimuth reconstruction and range ambiguity suppression simultaneously. Finally, the elevation nulling DBF is used to further suppress range ambiguity and obtain the SAR wide-swath image. The superiority of this scheme is reflected in the following aspects: the azimuth DBF simultaneously suppresses azimuth and range ambiguity, the influence of height fluctuations on the ability to suppress range ambiguity is weakened, the use of elevation nulling DBF further enhances the level of range ambiguity suppression, and different range sub-regions can adopt different range resolutions and working modes. The feasibility of this scheme is verified through theoretical analysis and simulation.

The drive at the center of gravity (DCG) concept-based twin-ball-screw drive mechanism (TBSDM) is vital in automated factories for its robustness and reliability. However, changes in the worktable mass or position result in changes in the center of gravity (CG), significantly affecting the system’s dynamic properties. In this regard, this paper introduces a novel analytical model using improved receptance coupling to analyze vibrations in four modes. A mathematical framework for the twin TBSDM is generated, and the effect of changing the worktable position–mass on each mode is examined. The applicability of the proposed method is verified based on dynamic experiments that were carried out on a TBSDM of a CNC grinding wheel machine tool. After thoroughly analyzing the experimental and theoretical results, it is revealed that changing the worktable position primarily influences the rotational and axial vibrations of the twin ball screw (TBS). Furthermore, changes in the worktable mass significantly affect the coupling vibration among the TBSs and rotors or bearings. Moreover, in terms of performance, the variances between the theoretical and experimental natural frequencies are consistently below 5%. Thus, the proposed method is promising for the improvement of the modeling and analysis of the TBSDM.

In order to improve the accuracy of internal temperature estimation in batteries, a 10-parameter time-varying multi-surface heat transfer model including internal heat production, heat transfer and external heat transfer is established based on the structure of a lithium iron phosphate pouch battery and its three directional anisotropic heat conduction characteristics. The entropy heat coefficient, internal equivalent heat capacity and internal equivalent thermal resistance related to the SOC and temperature state of the battery were identified using experimental tests and the least square fitting method, and were then used for online calculation of internal heat production and heat transfer in the battery. According to the time-varying and nonlinear characteristics of the heat transfer between the surface and the environment of the battery, an internal temperature estimation algorithm based on the square root cubature Kalman filter was designed and developed. By iteratively calculating the estimated surface temperature and the measured value, dynamic tracking and online correction of the internal temperature of the battery can be achieved. The verification results using FUDS and US06 dynamic working condition data show that the proposed method can quickly eliminate the influence of initial temperature deviations and accumulated process errors and has the characteristics of a high estimation accuracy and good robustness. Compared with the estimation results of the adaptive Kalman filter, the proposed method improves the estimation accuracy of FUDS and US06 working conditions by 67% and 54%, respectively, with a similar computational efficiency.

Long waiting times and crowded services are the current medical situation in China. Especially in hierarchic healthcare systems, as high-quality medical resources are mainly concentrated in comprehensive hospitals, patients are too concentrated in these hospitals, which leads to overcrowding. This paper constructs a game-theoretical queueing model to analyze the strategic queueing behavior of patients. In such hospitals, patients are divided into first-visit and referred patients, and the hospitals provide patients with two service phases of “diagnosis” and “treatment”. We first obtain the expected sojourn time. By defining the patience level of patients, the queueing behavior of patients in equilibrium is studied. The results suggest that as long as the patients with low patience levels join the queue, the patients with high patience levels also join the queue. As more patients arrive at the hospitals, the queueing behavior of patients with high patience levels may have a negative effect on that of patients with low patience levels. The numerical results also show that the equilibrium behavior deviates from a socially optimal solution; therefore, to reach maximal social welfare, the social planner should adopt some regulatory policies to control the arrival rates of patients.

In response to the high breakage rate of pigeon eggs and the significant labor costs associated with egg-producing pigeon farming, this study proposes an improved YOLOv8-PG (real versus fake pigeon egg detection) model based on YOLOv8n. Specifically, the Bottleneck in the C2f module of the YOLOv8n backbone network and neck network are replaced with Fasternet-EMA Block and Fasternet Block, respectively. The Fasternet Block is designed based on PConv (Partial Convolution) to reduce model parameter count and computational load efficiently. Furthermore, the incorporation of the EMA (Efficient Multi-scale Attention) mechanism helps mitigate interference from complex environments on pigeon-egg feature-extraction capabilities. Additionally, Dysample, an ultra-lightweight and effective upsampler, is introduced into the neck network to further enhance performance with lower computational overhead. Finally, the EXPMA (exponential moving average) concept is employed to optimize the SlideLoss and propose the EMASlideLoss classification loss function, addressing the issue of imbalanced data samples and enhancing the model’s robustness. The experimental results showed that the F1-score, mAP50-95, and mAP75 of YOLOv8-PG increased by 0.76%, 1.56%, and 4.45%, respectively, compared with the baseline YOLOv8n model. Moreover, the model’s parameter count and computational load are reduced by 24.69% and 22.89%, respectively. Compared to detection models such as Faster R-CNN, YOLOv5s, YOLOv7, and YOLOv8s, YOLOv8-PG exhibits superior performance. Additionally, the reduction in parameter count and computational load contributes to lowering the model deployment costs and facilitates its implementation on mobile robotic platforms.

Ground settlement (GS) in an oil tank determines its structural integrity and commercial service. However, GS monitoring faces challenges, particularly due to the significant temperature differences induced by solar radiation around the tank in daytime. To address this problem, this paper digs out a prior and proposes a temperature uncertainty reduction algorithm based on that. This prior has a spatial Gaussian distribution of temperature around the tank, and numerical simulation and practical tests are conducted to demonstrate it. In addition, combining uniformly packaged sensor probes and the spatial prior of temperature, the temperature uncertainty is verified to be Gaussian-distributed too. Then, the overall temperature uncertainty can be captured by Gaussian fitting and then removed. The practical test verified a 91% reduction rate in temperature uncertainty, and this approach enables GS sensors to effectively perform daytime monitoring by mitigating temperature-related uncertainties.

This research used fly ash and slag to create geopolymer foam concrete. They were activated with an alkali, resulting in a chemical reaction that produced a gel that strengthened the concrete’s structural integrity. The experimental approach involved varying the fly ash content in the precursors at incremental percentages (10%, 30%, 50%, 70% and 90%) and subjecting the fly ash to mechanical activation through a planetary ball mill at distinct rotational speeds (380, 400, 420 and 440 rpm). The investigation discerned that the fly ash content and particle structure exert a discernible influence on macroscopic properties, including flowability, air generation height, compressive strength, dry density and microstructural characteristics such as pore distribution and hydration product arrangement in the geopolymer foam concrete. Employing analytical techniques such as X-ray diffraction (XRD) and scanning electron microscopy (SEM), it was deduced that diminishing the fly ash content correlates with an enhancement in compressive strength. Furthermore, the specific strength of the geopolymer foam concrete reached a peak of 0.041 when the activated fly ash in the planetary ball mill rotated at 420 rpm, manifesting a lightweight and high-strength outcome.

Kelp, often referred to as a “sea vegetable”, holds substantial economic significance. Currently, the drying process for kelp in China primarily relies on outdoor sun-drying methods. Detecting kelp in the field presents challenges arising from issues such as overlapping and obstruction. To address these challenges, this study introduces a lightweight model, K-YOLOv5, specifically designed for the precise detection of sun-dried kelp. YOLOv5-n serves as the base model, with several enhancements implemented in this study: the addition of a detection head incorporating an upsampling layer and a convolution module to improve the recognition of small objects; the integration of an enhanced I-CBAM attention mechanism, focusing on key features to enhance the detection accuracy; the replacement of the CBS module in the neck network with GSConv to reduce the computational burden and accelerate the inference speed; and the optimization of the IoU algorithm to improve the identification of overlapping kelp. Utilizing drone-captured images of sun-dried kelp, a dataset comprising 2190 images is curated. Validation on this self-constructed dataset indicates that the improved K-YOLOv5 model significantly enhances the detection accuracy, achieving 88% precision and 78.4% recall. These values represent 6.8% and 8.6% improvements over the original model, respectively, meeting the requirements for the real-time recognition of sun-dried kelp.

α-Conotoxins (α-CTxs) are structurally related peptides that antagonize nicotinic acetylcholine receptors (nAChRs), which may serve as new alternatives to opioid-based treatment for pain-related conditions. The non-natural amino acid analogues of α-CTxs have been demonstrated with improved potency compared to the native peptide. In this study, we chemically synthesized Dab/Dap-substituted analogues of α-CTx PeIA and evaluated their activity at heterologously expressed human α9α10 nAChRs. PeIA[S4Dap, S9Dap] had the most potent half-maximal inhibitory concentration (IC50) of 0.93 nM. Molecular dynamic simulations suggested that the side chain amino group of Dap4 formed additional hydrogen bonds with S168 and D169 of the receptor and Dap9 formed an extra hydrogen bond interaction with Q34, which is distinctive to PeIA. Overall, our findings provide new insights into further development of more potent analogues of α-CTxs, and PeIA[S4Dap, S9Dap] has potential as a drug candidate for the treatment of chronic neuropathic pain.

One of the most significant problems affecting a concrete bridge’s safety is cracks. However, detecting concrete bridge cracks is still challenging due to their slender nature, low contrast, and background interference. The existing convolutional methods with square kernels struggle to capture crack features effectively, fail to perceive the long-range dependencies between crack regions, and have weak suppression ability for background noises, leading to low detection precision of bridge cracks. To address this problem, a multi-stage feature aggregation and structure awareness network (MFSA-Net) for pixel-level concrete bridge crack detection is proposed in this paper. Specifically, in the coding stage, a structure-aware convolution block is proposed by combining square convolution with strip convolution to perceive the linear structure of concrete bridge cracks. Square convolution is used to capture detailed local information. In contrast, strip convolution is employed to interact with the local features to establish the long-range dependence relationship between discrete crack regions. Unlike the self-attention mechanism, strip convolution also suppresses background interference near crack regions. Meanwhile, the feature attention fusion block is presented for fusing features from the encoder and decoder at the same stage, which can sharpen the edges of concrete bridge cracks. In order to fully utilize the shallow detail features and deep semantic features, the features from different stages are aggregated to obtain fine-grained segmentation results. The proposed MFSA-Net was trained and evaluated on the publicly available concrete bridge crack dataset and achieved average results of 73.74%, 77.04%, 75.30%, and 60.48% for precision, recall, F1 score, and IoU, respectively, on three typical sub-datasets, thus showing optimal performance in comparison with other existing methods. MFSA-Net also gained optimal performance on two publicly available concrete pavement crack datasets, thereby indicating its adaptability to crack detection across diverse scenarios.

Part of the gas phase within the bearing emanates from the gaseous lubricating medium generated by the phase transition of the liquid lubricant under low pressure, while the remaining portion originates from the expansion of gases, such as air, present in the lubricant. This study delves into the impact of vapor and gas cavitation on the stability of the rotor-journal bearing system. Utilizing computational fluid dynamics (CFD), a 3D transient lubrication model is developed for the rotor-journal bearing system. This model integrates a combined cavitation approach, encompassing both vaporous and gaseous cavitation phenomena. Based on a new structured dynamic mesh method, the journal orbits are obtained when the journal moves in the rotor-journal bearing system. In vaporous and gaseous cavitation, shear stress and non-condensable gases (NCG) are incorporated successively. Compared with the combined cavitation model, the basic cavitation model journal orbit amplitude is significantly larger than the combined cavitation model. The carrying capacity of journal bearings under the basic cavitation model is overestimated, leading to a more conservative prediction for system stability.

Water-lubricated bearings can effectively solve the pollution problem caused by lubricant leakage and are used in offshore engineering equipment for this reason. Aiming at the problems of unclear and undefined micro-interface lubrication mechanisms of water-lubricated bearings, this paper investigates the influence of non-parallel micro-cavities on the micro-interface lubrication mechanism of bearings. Based on a single micro-cavity model, the lubrication mechanism of micro-cavities is studied in this paper. Lubrication models of the non-parallel contact friction pairs model are built, and the effect of the non-parallelism on the lubrication performance of the micro-cavities is obtained using the computational fluid dynamics method. The results show that, under the same Reynolds number and cavitation pressure, the wedge effect caused by the non-parallelism causes the pressure at the inlet to rise, thus increasing the load-carrying capacity. The existence of non-parallelism limits the rise of the high pressure of the inertia effect on the micro-cavities and reduces the load-carrying capacity. The presence of non-parallelism decreases the area of the negative pressure proportion and increases the proportion of the positive pressure zone inside the micro-cavities, thus increasing the load-carrying capacity.

Since camera and LiDAR sensors provide complementary information for the 3D semantic segmentation of intelligent vehicles, extensive efforts have been invested to fuse information from multi-modal data. Despite considerable advantages, fusion-based methods still have inevitable limitations: field-of-view disparity between two modal inputs, demanding precise paired data as inputs in both the training and inferring stages, and consuming more resources. These limitations pose significant obstacles to the practical application of fusion-based methods in real-world scenarios. Therefore, we propose a robust 3D semantic segmentation method based on multi-modal collaborative learning, aiming to enhance feature extraction and segmentation performance for point clouds. In practice, an attention based cross-modal knowledge distillation module is proposed to effectively acquire comprehensive information from multi-modal data and guide the pure point cloud network; then, a confidence-map-driven late fusion strategy is proposed to dynamically fuse the results of two modalities at the pixel-level to complement their advantages and further optimize segmentation results. The proposed method is evaluated on two public datasets (urban dataset SemanticKITTI and off-road dataset RELLIS-3D) and our unstructured test set. The experimental results demonstrate the competitiveness of state-of-the-art methods in diverse scenarios and a robustness to sensor faults.

Amid the conflict between the current huge data volumes and the requirement for large-compression-ratio compression in space-borne multichannel SAR, this paper proposes a data compression method that uses the adaptive bit allocation BAQ method in the Doppler domain of space-borne multichannel SAR. Specifically, 3MBAQ, which denotes multichannel, multipulse, multiweight block-adaptive quantization, performs signal reconstruction through a Krieger filter to obtain the Doppler spectrum under azimuthal multichannel and multipulse conditions and then achieves nonuniform bit allocation by using the multiple weight contributions between subband spectra. Furthermore, large-compression-ratio compression can be realized in homogeneous scenarios by using the adaptive bit allocation BAQ method together with the improved bit error control (BEC) algorithm. In this paper, the effectiveness of the 3MBAQ method is verified on GF3 measured data. Moreover, compared to the SQNR and NMSE of the BAQ, A-BAQ, A-BAQ-BEC, MCBAQ-ASQ, and MCBAQ-BEC methods under the same conditions, it is shown that there is an optimal 1.3434 dB improvement in SQNR and a 0.0241 improvement in NMSE using the 3MBAQ algorithm, and the complexity of the algorithm for 3MBAQ is O(N2log(N)), which is within acceptable limits, clearly proving the superiority of the 3MBAQ method.

Kelp, as a kind of climate-friendly food, animal feed, and bioplastics material, has been gradually cultivated worldwide. In the process of kelp culture, clipping seedling operation is essential to guarantee the yield. Traditionally, the clipping seedling operation is conducted by hand with low production efficiency and high labor intensity. In this paper, a novel automatic clipping seedling machine is developed to improve efficiency. The machine consists of an automatic seedling clipping core device, an automatic seedling feeding device, an automatic seedling rope conveyor, and an automatic product storage device. The corresponding structure, mechanism, and control system are introduced and analyzed. The performances of the automatic machine are tested and compared to manual kelp seedling clipping. Compared to manual kelp seedling clipping, the automatic machine can improve efficiency by 35%. Additionally, the quality of kelp seedling clipping is investigated. The attaching force of the kelp seedling clipped by the automatic machine is 2.179 N (224.4 g × 9.8 N/Kg × 10−3). The rate of the clipped kelp seedlings falling off the rope is only 1.3%. These performances prove that the automatic machine Is feasible and can be used to improve clipping efficiency and ensure clipping quality at the same time.

Sensors operating in open-air environments can be affected by various environmental factors. Specifically, ground settlement (GS) monitoring sensors installed in oil tanks are susceptible to non-uniform temperature fields caused by uneven sunshine exposure. This disparity in environmental conditions can lead to errors in sensor readings. To address this issue, this study aimed to analyze the impact of temperature on GS monitoring sensors and establish a mapping relationship between temperature uncertainty (fluctuations of measurement caused by temperature variation) and temperature variation. By collecting the temperature information and inferring the temperature uncertainty being introduced, this interference can be removed. However, it is crucial to note that in real-world complex scenarios, the relationship between temperature uncertainty and temperature variation is not always a constant positive correlation, which limits the data available for certain periods. Moreover, the limited availability of data presents a challenge when analyzing the complex mapping relationship. To overcome these challenges, a transfer-learning-based algorithm was introduced to develop a more accurate model for predicting temperature uncertainty based on temperature variation, even with limited data. Subsequently, a practical test was conducted to validate the proposed algorithm’s performance. The results demonstrated that the algorithm outperformed a simple linear fitting model using the least squares method (LSM), achieving an improvement of up to 21.9%. This outcome highlights the algorithm’s potential for enhancing the performance of GS sensors in daytime monitoring and contributing to the safe operation of oil tank facilities and infrastructure health monitoring.

To confirm whether Chinese mitten crabs (Eriocheir sinensis), commonly known as hairy crabs or river crabs, in non-Yangcheng Lake areas undergo morphological convergence with the original crabs in the Yangcheng Lake purse seine and high-standard modified aquaculture ponds after being “introduced” or “bathed”-cultured, we employed a geometric morphometrics approach. This approach allowed us to compare and analyze the dynamic changes in the carapace morphology of both the original and “introduced” crabs in Yangcheng Lake and high-standard ponds in Kunshan City at 0, 7, 14, and 30 days after “bathing” culture. The geometric morphological analysis of the carapace was conducted using a system of 35 established landmarks. The stepwise discriminant analysis of the relative distortion score revealed morphological differences between “introduced” and resident original crabs in the Yangcheng Lake area and in high-standard modified ponds after 7, 14, and 30 days of bathing culture. The accuracy of the discriminant analysis was 100%. The results of the geometric morphological visualization demonstrated that the carapaces of the bathed crabs underwent adaptive changes in the water. However, even after one month of bathing culture, the “introduced” crabs in lakes and ponds could not reach the morphological characteristics of the original crabs, i.e., their carapaces did not exhibit the characteristics of the original crabs.

The study of damage mechanisms for wind turbine blades is important. Generally, modal localization tends to accelerate structural damage. This is a new approach to studying these damage mechanisms for wind turbine blades through modal localization theory. Therefore, this paper investigates whether modal localization phenomena exist in wind turbine blades, as well as the impact of different forms of detuning on modal localization. Based on perturbation theory, a mechanism for mode localization is described quantitatively using the degree of detuning, the degree of mode density, and the mode assurance criterion. A finite element model for wind turbine blades was established using ANSYS software (R15.0), and three detuning cases were simulated by changing the density, elastic modulus, and installation angles of the blades. Moreover, an improved mode localization factor is proposed to quantitatively evaluate the degree of mode localization in wind turbine blades. The numerical results indicate that the degree of modal localization increases with an increasing degree of detuning, but the increase in modal localization gradually slows. Finally, the detuning modal shape composition, which includes harmonic components, is analyzed. The results show that the closer the composition of the detuning modes is, the stronger the degree of mode localization.

The Daguangbao (DGB) landslide was the largest landslide that was triggered by the 2008 Wenchuan earthquake with a magnitude of Ms8.0. The sliding surface of this landslide was constrained on a bedding fault 400 m below the ground surface. Seismic records show that the landslide suffered not only from strong horizontal but also vertical ground shaking that was almost equal to the horizontal component. In this study, to reveal the landslide triggering mechanism of the DGB landslide, this study ignores the steep dipping tension fracture section and the leading edge-locking section of the trailing edge of the DGB landslide, and the geological model of the large optical package landslide is generalized into a block model with the bottom controlled slip soft zone as the interface. Based on the improved Newmark method that considers vertical ground motion, the three-way seismic acceleration data and the shear strength parameter of the sliding surface being taken as a variable are used to calculate the cumulative permanent displacement of the slider. Then, by considering the cumulative permanent displacement ratio of vertical seismic acceleration or not and the cumulative permanent displacement ratio value considering the inertial force as the index, the response characteristics of the cumulative permanent displacement of the block-to-vertical ground motion and inertial forces were analyzed. The results show that both the horizontal inertial force and the vertical acceleration significantly increased the permanent displacement. The permanent displacement is 4.9 cm when considering the vertical acceleration, whereas it is only 2.0 cm without taking this into account. The contribution of vertical acceleration is significantly enlarged (87.8–90.7%) by the decreasing of the internal friction angle of the slide surface, while it is less influenced (5–27.4%) by the cohesion. Compared with the lower shear strength parameter of the sliding surface, the contributions of vertical acceleration and inertial force to the permanent displacement are more obvious when the shear strength parameter of the sliding surface is higher. When ϕ > 18°, the D/D* is greater than 1, and the maximum D/D* reaches 7. The fast accumulation event of permanent displacement is triggered in the concentration stage of the seismic energy release. In the DGB landslide area, 50% of the energy is released within 30–50 s, as indicated by the acceleration peaks recorded at the nearest seismic station, Qingping station. It is assumed that the DGB landslide may be triggered at 30–50 s due to half of the seismic energy being released during that time span.

The development of photocatalysts for organic degradation is a hot research topic. In this study, CdZnS was selected as the carrier, and ZIF-8 was combined with it to explore the photocatalytic performance of the composite. In addition, the compound material, CdZnS@ZIF-8, was used as a photocatalyst for the decomposition of methylene blue dye, and the performance of pure CdZnS and pure ZIF-8 was compared. The photocatalytic efficiency of CdZnS@ZIF-8 was significantly higher than that of the other two. In the experimental reaction, the amount of catalyst was 0.04 g, the pH value was 7, the initial concentration of methylene blue aqueous solution was 20 mg/L, and the degradation of methylene blue in 50 mL aqueous solution could reach 99.5% under visible light irradiation for 90 min, showing excellent photocatalytic efficiency in the visible light range. It demonstrated excellent photocatalytic function in the visible light region, and the electron transfer phenomenon at the interface occurred in the het-junction and the separation of the photo-generating electron–hole as an electron acceptor of ZIF-8 further promoted the photocatalytic effect.

Deep, unstable slopes are highly developed in mountainous areas, especially in the Minjiang River Basin, Sichuan Province, China. In this study, to reveal their deformation evolution characteristics for stability evaluation and disaster prevention, multi-period optical remote sensing images (2010–2019), SBAS-InSAR data (January 2018–December 2019), and on-site real-time monitoring (December 2017–September 2020) were utilized to monitor the deformation of a large deep-seated toppling, named the Tizicao (TZC) Toppling. The obtained results by different techniques were cross-validated and synthesized in order to introduce the spatial and temporal characteristics of the toppling. It was found that the displacements on the north side of the toppling are much larger than those on the south side, and the leading edge exhibits a composite damage pattern of “collapse failure” and “bulging cracking”. The development process of the toppling from the formation of a tensile crack at the northern leading edge to the gradual pulling of the rear edge was revealed for a time span of up to ten years. In addition, the correlation between rainfall, earthquakes, and GNSS time series showed that the deformation of the toppling is sensitive to rainfall but does not change under the effect of earthquakes. The surface-displacement-monitoring method in this study can provide a reference for the evolution analysis of unstable slopes with a large span of deformation.

The rapid growth of electronic health records (EHRs) has led to unprecedented biomedical data. Clinician access to the latest patient information can improve the quality of healthcare. However, clinicians have difficulty finding information quickly and easily due to the sheer data mining volume. Biomedical information retrieval (BIR) systems can help clinicians find the information required by automatically searching EHRs and returning relevant results. However, traditional BIR systems cannot understand the complex relationships between EHR entities. Transformers are a new type of neural network that is very effective for natural language processing (NLP) tasks. As a result, transformers are well suited for tasks such as machine translation and text summarization. In this paper, we propose a new BIR system for EHRs that uses transformers for predicting cancer treatment from EHR. Our system can understand the complex relationships between the different entities in an EHR, which allows it to return more relevant results to clinicians. We evaluated our system on a dataset of EHRs and found that it outperformed state-of-the-art BIR systems on various tasks, including medical question answering and information extraction. Our results show that Transformers are a promising approach for BIR in EHRs, reaching an accuracy and an F1-score of 86.46%, and 0.8157, respectively. We believe that our system can help clinicians find the information they need more quickly and easily, leading to improved patient care.

Vibration in state-of-the-art machining impacts accuracy by diminishing the machine’s dynamic precision and the workpiece surface quality. The dependability of the cutters and productivity becomes a severe problem for optimizing the computer numerical control machine tools’ (CNCMT) efficiency. Therefore, investigating the twin ball screw drive system vibration properties as well as its corresponding control measures is vital. This paper thoroughly reviews the recent works on methods of analyzing and controlling vibration for dual-driven feed systems (DDFS). The research on vibration control technologies, parameter identification, and system modeling are identified and summarized; the merits and drawbacks of various methods are discussed for comparative purposes. Furthermore, the asymmetrical relation between DDFS and single-driven feed systems are thoroughly discussed based on their dynamic properties. Finally, based on existing studies, related research prospects are described systematically, and these research directions are sure to markedly contribute to developing methods for dampening vibrations on DDFS of CNCMT.

A nonuniform temperature field can deteriorate the performance of sensors, especially those working in the field, such as an optical sensor for oil-tank ground settlement (GS) monitoring. In this case, the GS monitoring employs hydraulic-level-based sensors (HLBS), which are uniformly installed along with the oil-tank basement perimeter and are all connected by hydraulic tubes. Then, the cylinder structure of the oil tank itself can create a strong temperature difference between the sensors installed in the sunlit front and those in the shadow. Practically, this sunlight-dependent difference can be over 30 °C, by which the thermal expansion of the measuring liquid inside the connecting hydraulic tubes keeps on driving a movement and, thereby, leads to fluctuations in the final result of the oil-tank GS monitoring system. Now, this system can work well at night when the temperature difference becomes negligible. However, temperature uncertainty is generated in the GS sensors due to the large temperature difference between the sensors in the daytime. In this paper, we measured the temperature where the sensor was located. Then, we compared the results of the GS sensors with their corresponding temperatures and fitted them with two separate curves, respectively. After observing the similarity in the tendency of the two curves, we found that there was a qualitative correlative relationship between the change in temperature and the uncertainty in the sensor results. Then, a curve similarity analysis (CSA) principle based on the minimum mean square error (MMSE) criteria was employed to establish an algorithm, by which the temperature uncertainty in the GS sensors was reduced. A practical test proved that the standard deviation was improved by 73.4% by the algorithm. This work could be an example for reducing the temperature uncertainty from in-field sensors through the CSA method.

In severe low-visibility environments full of smoke, because of the performance degeneration of the near-infrared (NIR) collimation system of quantum drones communication networks, the improved dual-threshold method based on trend line analysis for long-wave infrared (LWIR) quantum cascade lasers (QCLs) is proposed, to achieve target acquisition. The simulation results show that smoke-scattering noise is a steeply varying medium–high-frequency modulation. At particle sizes less than 4 μm, the traditional dual-threshold method can effectively distinguish the target information from the smoke noise, which is the advantage of the LWIR laser compared to the NIR laser. For detecting lasers with high signal-to-noise ratios (SNRs), the method can achieve good target acquisition, by setting reasonable conventional thresholds, such as 0.7 times the peak intensity and 0.8 times the peak rising velocity. At low SNRs and steep intensity variation, the method can also achieve good target acquisition, by adaptively resetting new thresholds after filtering the detecting laser, such as 0.6 times the peak intensity and 0.6 times the peak rising velocity. The results of this paper will provide a reference for the performance improvement and refinement of the collimation system for wireless quantum communication networks in low visibility.

Autonomous underwater manipulation is very important for the robotic and intelligence operations of oceanic engineering. However, a small target often involves limited features and results in inaccurate visual matching. In order to improve visual measurement accuracy, this paper has proposed an improved unsharp masking algorithm to further enhance the weak texture region of blurred and low contrast images. Moreover, an improved ORB feature-matching method with adaptive threshold, non-maximum suppression and improved random sample consensus has also been proposed. To overcome unknown underwater disturbances and uncertain system parameters in the underwater robotic manipulations, an adaptive non-singular terminal sliding mode controller has been proposed with a quasi-barrier function to suppress the chattering problem and improve grasp accuracy for small target. Oceanic experiments have been conducted to prove the performance of the proposed method.

Angiogenesis refers to the process of growing new blood vessels from pre-existing capillaries or post-capillary veins. This process plays a critical role in promoting tumorigenesis and metastasis. As a result, developing antiangiogenic agents has become an attractive strategy for tumor treatment. Sirtuin6 (SIRT6), a member of nicotinamide adenine (NAD+)-dependent histone deacetylases, regulates various biological processes, including metabolism, oxidative stress, angiogenesis, and DNA damage and repair. Some SIRT6 inhibitors have been identified, but the effects of SIRT6 inhibitors on anti-angiogenesis have not been reported. We have identified a pyrrole-pyridinimidazole derivative 8a as a highly effective inhibitor of SIRT6 and clarified its anti-pancreatic-cancer roles. This study investigated the antiangiogenic roles of 8a. We found that 8a was able to inhibit the migration and tube formation of HUVECs and downregulate the expression of angiogenesis-related proteins, including VEGF, HIF-1α, p-VEGFR2, and N-cadherin, and suppress the activation of AKT and ERK pathways. Additionally, 8a significantly blocked angiogenesis in intersegmental vessels in zebrafish embryos. Notably, in a pancreatic cancer xenograft mouse model, 8a down-regulated the expression of CD31, a marker protein of angiogenesis. These findings suggest that 8a could be a promising antiangiogenic and cancer therapeutic agent.

Quantum tunneling electrical probes, consisting of a pair of nanoelectrodes with a gap width of less than 5 nm, can be used as a robust electrical sensing platform for the detection of various nanoscale objects. To achieve this, stable and gap-width-controllable electrodes are essential. Although various methods, including lithography and electrochemical strategies, have been proposed for the fabrication of tunneling electrodes, the ability to precisely control the gap width and ensure reproducibility is still lacking. Here, we report a feedback-controlled electrochemical etching approach to fabricate the tunneling electrodes with a controlled nanogap. The connected nanoelectrodes, derived from a dual-barrel nanopipette, were subjected to a controlled electrochemical etching process from a short-circuited state to a tunneling gap. The resulting tunneling electrodes exhibited solvent-response current–voltage electrical behavior, which was well fitted with the Simons model, indicating the formation of tunneling electrodes. Overall, a success rate of more than 60% could be achieved to obtain the tunneling gaps. Furthermore, to verify the function of tunneling electrodes, we used the etched-tunneling electrodes for free-diffusing protein detection, showing the potential of etched-tunneling electrodes as single-molecule sensors.

Ports in China are facing significant pressure to reduce carbon emissions in alignment with carbon peak and carbon neutrality goals. Onshore power supply (OPS) is regarded as a promising approach to accomplish these targets, necessitating a thorough evaluation of its impact for port authorities to make informed decisions regarding its adoption. This research focuses on Ningbo Zhoushan Port, the largest port globally, as a case study. Two metrics are proposed to quantify the energy efficiency of ships powered by onshore energy while berthed. The installation and connection status of OPS in the port area are analyzed. Subsequently, the energy demand of berthed ships is assessed, and the potential for energy efficiency improvement resulting from OPS implementation is evaluated using Monte Carlo methods. The findings reveal untapped potential in the studied port area, with OPS demonstrating the ability to improve energy efficiency of berthed ships at a rate parallel to the connection rate, excluding indirect emissions. However, considering indirect emissions and energy loss diminishes the effectiveness of OPS. The paper discusses practical implications for enhancing the energy efficiency of OPS, enabling port authorities to make well-informed decisions. These findings are invaluable for Chinese port authorities striving to achieve carbon reduction goals and enhance sustainability in the maritime industry.

Depression is a leading cause of disease worldwide. The association between gut microbiota and depression has barely been investigated in the Japanese population. We analyzed Iwaki health check-up data collected from 2017 to 2019 and constructed generalized linear mixed models. The independent variable was the relative abundance of each of the 37 gut microbiota genera that were reported to be associated with depression. The dependent variable was the presence of depression assessed by the Center for Epidemiologic Studies Depression Scale. Potential confounders, including grip strength, gender, height, weight, smoking, and drinking habits, were adjusted in the regression models. Nine genera’s regression coefficients (Alistipes, Blautia, Coprococcus, Dorea, Faecalibacterium, Holdemania, Lactobacillus, Mitsuokella, and Oscillibacter) showed statistical significance after multiple comparisons adjustment. Among these nine gut bacteria genera, Alistipes, Blautia, Coprococcus, Dorea, Faecalibacterium, and Oscillibacter were reported to be associated with butyrate production in the intestine. Our results indicate that gut microbiotas may influence the depression condition of the host via the butyrate-producing process.

Herein, a series of novel long afterglow nanophosphors BaYAl3O7:Eu2+, Nd3+ was synthesized by the combustion method. The investigation encompassed the characterization of X-ray diffraction, morphology, chemical valence, elemental composition, and photoluminescence behavior of BaYAl3O7:Eu2+ and BaYAl3O7:Eu2+, Nd3+ nanoparticles. Under 365 nm excitation, BaYAl3O7:Eu2+ and BaYAl3O7:Eu2+, Nd3+ show emission bands centered at 497 nm and 492 nm, which are attributed to the 4f65d→4f7 transition of Eu2+ ions. The optimal samples of BaYAl3O7:0.03Eu2+ and BaYAl3O7:0.03Eu2+, 0.02Nd3+ have average fluorescence lifetimes of 850 ns and 1149 ns, respectively. The co-doping of Nd3+ ions as the trap centers produced long afterglow luminescence properties, and the afterglow time could reach up to 8 min. Furthermore, the fluorescent powder can be mixed with polyacrylic acid to prepare anti-counterfeiting inks; a clover pattern and snowflake pattern have been successfully printed using screen printing technology, proving its potential application in the field of anti-counterfeiting.

(1) Background: Despite the evidence that ferroptosis is involved in myocardial ischemia-reperfusion (MIR), the critical regulator of ferroptosis in MIR remains unclear. (2) Methods: We included three GEO datasets and a set of ferroptosis-related genes with 259 genes. Following the identification of the differentially expressed ferroptosis-related genes (DEFRGs) and hub genes, we performed the functional annotation, protein–protein interaction network, and immune infiltration analysis. The GSE168610 dataset, a cell model, and an animal model were then used to verify key genes. (3) Results: We identified 17 DEFRGs and 9 hub genes in the MIR samples compared to the control. Heme oxygenase 1 (Hmox1), activating transcription factor 3 (Atf3), epidermal growth factor receptor (Egfr), and X-box binding protein 1 (Xbp1) were significantly upregulated in response to ischemic and hypoxic stimuli. In contrast, glutathione peroxidase 4 (Gpx4) and vascular endothelial growth factor A (Vegfa) were consistently decreased in either the oxygen and glucose deprivation/reoxygenation cell or the MIR mouse model. (4) Conclusions: This study emphasized the relevance of ferroptosis in MIR. It has been successfully demonstrated that nine ferroptosis-related genes (Hmox1, Atf3, Egfr, Gpx4, Cd44, Vegfa, asparagine synthetase (Asns), Xbp1, and bromodomain containing 4 (Brd4)) are involved in the process. Additional studies are needed to explore potential therapeutic targets for MIR.

The advantages of low cost, high theoretical capacity, and dependable safety of aqueous zinc ion hybrid supercapacitors (ZHSCs) enable their promising use in flexible and wearable energy storage devices. However, achieving extended cycling stability in ZHSCs is still challenged by the limited availability of carbon cathode materials that can effectively pair with zinc anode materials. Here, we report a method for synthesising heteroatom-doped carbon nanofibers using electrostatic spinning and metal-organic frameworks (specifically ZIF-8). Assembled Zn//ZPCNF-1.5 ZHSCs exhibited 193 mA h g−1 specific capacity at 1 A g−1 and 162.6 Wh kg−1 energy density at 841.2 kW kg−1. Additionally, the device showed an ultra-long cycle life, maintaining 98% capacity after 20,000 cycles. Experimental analysis revealed an increase in the number of pores and active sites after adding ZIF-8 to the precursor. Furthermore, N doping effectively enhanced Zn2+ ions chemical adsorption and improved Zn-ion storage performance. This work provides a feasible design strategy to enhance ZHSC energy storage capability for practical applications.

Escherichia coli O157:H7, Staphylococcus aureus, and Salmonella are major foodborne pathogens that are widespread in nature and responsible for several outbreaks of food safety accidents. Thus, a rapid and practical technique (PMA-mPCR) was developed for the simultaneous detection of viable E. coli O157:H7, S. aureus, and Salmonella in pure culture and in a food matrix. To eliminate false positive results, propidium monoazide (PMA) was applied to selectively suppress the DNA amplification of dead cells. The results showed the optimum concentration of PMA is 5.0 µg/mL. The detection limit of this assay by mPCR was 103 CFU/mL in the culture broth, and by PMA-mPCR was 104 CFU/mL both in pure culture and a food matrix (milk and ground beef). In addition, the detection of mixed viable and dead cells was also explored in this study. The detection sensitivity ratio of viable and dead counts was less than 1:10. Therefore, the PMA-mPCR assay proposed here might provide an efficient detection tool for the simultaneous detection of viable E. coli O157:H7, S. aureus, and Salmonella and also have great potential for the detection and concentration assessment of VBNC cells.

This study aimed to reveal the energy loss characteristics of each part of the shaft tubular pump device (STPD) under stall conditions. Numerical simulations were conducted by using the SST k-ω turbulence model with curvature correction, and the reliability of the simulation results was verified by a model test. The entropy production method was used to evaluate and visualize the energy loss. The results show that turbulent entropy production (TEP) is the main source of energy loss in each component of the STPD, and the TEP increases significantly with the deterioration of stall. The energy loss in the impeller is mainly concentrated near the shroud and hub, while in the guide vanes it is mainly concentrated near the shroud and suction surface of the blades. In addition, with the deterioration of stall, the energy loss in the inlet of the impeller and guide vanes increases significantly. Influenced by the backflow from the impeller, there is a significant amount of energy loss at the outlet segment of the inlet passage, and the location of the high-energy-loss region is consistent with the backflow region. Affected by the flow separation vortex at the tail of the guide vanes, the energy loss in the outlet passage is mainly concentrated at the inlet segment.