Analysis of Interaction Features of Cyclo[13]carbon with Small Molecules and Formation Mechanism of Its Dimer.

The newly discovered cyclo[13]carbon, the first artificially synthesized odd-numbered carbon ring, is an intriguing carbon isomer that provides a valuable subject for studying low-symmetry carbon materials. In this work, we employed first-principles calculations to explore the geometric structure and electronic properties of cyclo[13]carbon through various techniques such as vibrational mode analysis, bond order analysis, spin density analysis, electron localization analysis, electrostatic potential and van der Waals potential analysis, visualization of weak interactions, and energy decomposition analysis. We investigated the interaction characteristics of cyclo[13]carbon with small molecules and examined its dimer formation mechanism and dynamics features using ab initio molecular dynamics.

Identifying hub genes and key functional modules in leaf tissue of Populus species based on WGCNA.

As one of the most important parts of plants, the genetic mechanisms of photosynthesis or the response of leaf to a single abiotic and biotic stress have been well studied. However, few researches have involved in the integration of data analysis from system level in leaf tissue under multiple abiotic stresses by utilizing biological networks. In this study, the weighted gene co-expression network analysis (WGCNA) strategy was used to integrate multiple data in leaf tissue of Populus species under different sample treatments.

Automated Structural Bolt Micro Looseness Monitoring Method Using Deep Learning.

The detection of bolt loosening in key components of aircraft engines faces problems such as complex and difficult-to-establish bolt loosening mechanism models, difficulty in identifying early loosening, and difficulty in extracting signal features with nonlinear and non-stationary characteristics. Therefore, the automated structural bolt micro looseness monitoring method using deep learning was proposed. Specifically, the addition of batch normalization methods enables the established Batch Normalized Stacked Autoencoders (BNSAEs) model to converge quickly and effectively, making the model easy to build and effective.

Numerical and Experimental Study on the Jet Behavior of Ultrafine Dry Powder Based on a Supersonic Nozzle.

To improve the dry powder jet extinguishing efficiency, the velocity change and spatial distribution of ultrafine dry powder particles under the action of high Mach number compressible air are studied by using the SST turbulence model and the gas-solid two-phase coupled model. The effects of nozzle pressure ratio, particle diameter, and mass flow on parameters such as Mach number and radial diffusion width are analyzed,and the influence of injection pressure and jet performance is verified by ultrafine dry powder jet experiment. The results show that the increase in the particle size will weaken particle flowability; the Saffman lift force has a significant effect on the particles when the nozzle expansion angle is large, and a particle-free zone is produced near the center axis; increasing the nozzle pressure ratio or reducing the dry powder mass flow rate will help improve the particle velocity in the core jet area outside the nozzle, and the accuracy of this law is proved by experiments.

Optimization and control of robotic vertebral plate grinding: Predictive modeling, parameter optimization, and fuzzy control strategies for minimizing bone damage in laminectomy procedures.

During the robotic grinding of vertebral plates in high-risk laminectomy procedures, programmed operations may inadvertently induce force or temperature-related damage to the bone tissue. Therefore, it is imperative to explore a control methodology aimed at minimizing such damage during the robotic grinding of vertebral plate cortical bone, contingent upon optimal grinding parameters. Initially, predictive models for both the grinding force and temperature of vertebral plate cortical bone were developed using the response surface design (RSD) methodology.

Influence of the induced Na/Cl ionic polarization effects on multi-scale structures of maize starch during radio frequency heating.

Structural modification/unfolding of starch molecules can be improved by radio frequency (RF) treatment. This necessitates a better understanding of its action mechanism through rapid heating and dipolar/ionic molecular vibration effects. Native maize starch (NS) was subjected to RF heating in a NaCl solution to five target temperatures, and its effect on structural modifications was evaluated.

Design and performance evaluation of a spiral bar precision weeding mechanism for corn fields.

This paper focuses on addressing the limitations of existing mechanical weeding methods for corn plants by introducing a spiral tendon-type precision weeding device specifically designed for corn fields. The study encompasses mechanical design and theoretical analysis to determine the overall structure, component parts, application scenarios, operation modes, and working principles of the device. The force applied to the spiral tendon weeding cutter head, a crucial working component of the device, is analyzed, along with its motion characteristics.

Interregional imbalance in the Yellow River Basin: Insights from flood-sediment transport, socioeconomic, and environmental subsystems.

The ecological environment, resource endowment, and the level of socioeconomic development vary extensively amongst regions in the Yellow River Basin (YRB). To ensure the basin's sustainable development, the supply and demand relationship of ecosystem services (ESs) within the basin was analysed from the perspective of three subsystems: flood-sediment transport, socioeconomics, and ecological environment. The supply, demand, and the ratio of supply to demand of typical ESs were initially computed for 385 counties and districts within the YRB.

PLC based laser scanning system for conveyor belt surface monitoring.

This paper presents the design, implementation, and testing of an advanced conveyor belt surface monitoring system, specifically engineered for harsh and complex industrial environments. The system integrates multiple cutting-edge technologies, including programmable logic controllers (PLC), laser scanning, industrial-grade cameras, and deep learning algorithms, particularly YOLOv7, to achieve real-time, high-precision monitoring of conveyor belt conditions. Key innovations include optimized detection location based on failure modes, advanced PLC integration for seamless automation, and intelligent dust-proof features to maintain accuracy in challenging conditions.

The Study on Nondestructive Detection Methods for Internal Quality of Korla Fragrant Pears Based on Near-Infrared Spectroscopy and Machine Learning.

Quality control and grading of Korla fragrant pears significantly impact their commercial value. Rapid and non-destructive detection of soluble solids content (SSC) and firmness is crucial to improving this. This study proposes a method combining near-infrared spectroscopy (NIRS) with machine learning for the rapid, non-destructive detection of SSC and firmness in Korla pears.

Feasibility and potential of terahertz spectral and imaging technology for Apple Valsa canker detection: A preliminary investigation.

Apple Valsa canker (AVC) caused by the Ascomycete Valsa mali, seriously constrains the production and quality of apple fruits. The symptomless incubation characteristics of Valsa mali make it highly challenging to detect AVC at an early infection stage. After infecting the wound of apple bark, the pathogenic hyphae of AVC will expand and colonize the phloem tissue.

Researches on the tender leaf identification and mechanically perceptible plucking finger for high-quality green tea.

Background: Intelligent identification and precise plucking are the keys to intelligent tea harvesting robots, which are currently of increasing significance. Aiming at plucking tender leaves for high-quality green tea production, in this study, a tender leaf identification algorithm and a mechanically perceptible plucking finger have been proposed.

Results: Based on the segmentation algorithm and color features, the tender leaf identification algorithm shows an average identification accuracy of over 92.

Public preferences and willingness to pay for environmental benefits of straw return: Empirical evidence from Northeast China.

Straw management is an important issue for many developing countries. In China, straw return is an effective way of straw management, involving substantial financial subsidies and impacts on public welfare through environmental improvements. The public plays a significant role as a financial source and beneficiary, and sustainable straw return policies need to respond to the public's interests and concerns.

A Candy Defect Detection Method Based on StyleGAN2 and Improved YOLOv7 for Imbalanced Data.

Quality management in the candy industry is a vital part of food quality management. Defective candies significantly affect subsequent packaging and consumption, impacting the efficiency of candy manufacturers and the consumer experience. However, challenges exist in candy defect detection on food production lines due to the small size of the targets and defects, as well as the difficulty of batch sampling defects from automated production lines.

Metagenomic insights into the mechanism of sophorolipid in facilitating co-anaerobic digestion of mushroom residues and cattle manure: Functional microorganisms and metabolic pathway analysis.

The present study aimed to enhance the co-anaerobic digestion system of mushroom residues and cattle manure by incorporating biosurfactant sophorolipid. Results demonstrated that the addition of 75 mg/L sophorolipid increased cumulative methane production by 33.68%, acetate content by 9-10 times, and the abundance of Methanosarcina by 69.

Active Vibration Control and Parameter Optimization of Genetic Algorithm for Partially Damped Composites Beams.

The paper partially covered Active Constrained Layer Damping (ACLD) cantilever beams' dynamic modeling, active vibration control, and parameter optimization techniques as the main topic of this research. The dynamic model of the viscoelastic sandwich beam is created by merging the finite element approach with the Golla Hughes McTavish (GHM) model. The governing equation is constructed based on Hamilton's principle.

Optical Fiber HMS Ammonia Sensor with Cellular-like N-CQDs/MgZnO at Room Temperature.

This paper presents an optical fiber hollow malposition structure (HMS) elaborated with cellular-like N-CQDs/MgZnO for detecting ammonia (NH) at room temperature. The gas detection was realized by combining the HMS to excite the surface evanescent field on the outer surface of the hollow core fiber (HCF) and the surface-coated cellular-like N-CQDs/MgZnO material for improving sensitivity. Experimental results demonstrate that the sensor coated with N-CQDs/MgZnO exhibits the highest sensitivity, reaching 8.

Thermo-mechanical coupling characteristics of the shearer's guiding shoe during the friction.

The reliability and longevity of the guiding shoe are crucial for the proper functioning of coal mining machines. The heavy wear of the sliding surface under thermal stress coupling is the primary factor influencing the service life of the guiding shoe. To reveal the heat flow distribution patterns and the thermo-stress coupling mechanisms of the guiding surface, a thermo-mechanical coupling model of the guiding shoe and the pin row is established.

An integrated three-stream network model for discriminating fish feeding intensity using multi-feature analysis and deep learning.

Feed costs constitute a significant part of the expenses in the aquaculture industry. However, feeding practices in fish farming often rely on the breeder's experience, leading to feed wastage and environmental pollution. To achieve precision in feeding, it is crucial to adjust the feed according to the fish's feeding state.

Quality Evaluation and Heat and Mass Transfer Mechanism of Microwave Vacuum Drying of Roots.

In this research, the objective was to optimize the drying process of by investigating the effects of microwave vacuum drying parameters, including temperature (30, 35, 40, 45, and 50 °C) and slice thickness (2, 3, 4, 5, and 6 mm). In addition, utilizing COMSOL 6.0 finite element analysis software, we delved into the distribution of heat and moisture during the drying process.

Sowing depth stability analysis and test verification of no-tillage planter parallel 4-bar row unit.

The sowing depth stability and consistency of the no-tillage planter, particularly the high-speed operation, are poor. A reason for this is that the structure and parameter selection of no-tillage planter row unit profiling mechanism are unreasonable. The stability and consistency of sowing depth is beneficial when the upper and lower links of the parallel 4-bar profiling mechanism (PFPM) are parallel to the ground, but this principle is not satisfied on the uneven no-till soil.