Dielectric spectroscopy technology combined with machine learning methods for nondestructive detection of protein content in fresh milk.

To quickly achieve nondestructive detection of protein content in fresh milk, this study utilized a network analyzer and an open coaxial probe to analyze the dielectric spectra of milk samples at 100 frequency points within the 2-20 GHz range, focusing on the dielectric constant ε' and the dielectric loss factor ε''. Feature variables were extracted from the full dielectric spectra using the successive projections algorithm (SPA), uninformative variables elimination (UVE), and the combined UVE-SPA method. These variables were then used to develop partial least squares regression (PLSR), support vector machine (SVM), decision tree (DT), random forest (RF), and least squares boosting (LSBOOST) models for predicting protein content.

A liquid metal diffusion measurement technique integrating the x-ray radiography and multi-slice sliding cell.

For measuring melt diffusion with in situ and high accuracy, this paper proposes a multi-slice sliding radiography technique. This technique combines the multi-sliding cell technique and x-ray radiography and inherits the advantages of both. It not only visualizes the diffusion process but is also suitable for the diffusion coefficient measurement of systems with low or even no absorption contrast.

Ultrasensitive Electrochemical Biosensor for Rapid Screening of Chemicals with Estrogenic Effect.

Estrogenic chemicals are widely distributed and structurally diverse. They primarily disrupt estrogen-related metabolism in animals or humans by mimicking the agonistic receptor effects of natural estrogens, thereby influencing the transcription of estrogen receptors to regulate their quantity and sensitivity. This disruption of estrogen-related metabolism can lead to estrogen-related effects, posing risks to biological health, emphasizing the urgent need for simple and effective methods to screen compounds with estrogenic effects.

Deep Learning-Based Biomimetic Identification Method for Mask Wearing Standardization.

Deep learning technology can automatically learn features from large amounts of data, with powerful feature extraction and pattern recognition capabilities, thereby improving the accuracy and efficiency of object detection. [The objective of this study]: In order to improve the accuracy and speed of mask wearing deep learning detection models in the post pandemic era, the [Problem this study aimed to resolve] was based on the fact that no research work has been reported on standardized detection models for mask wearing with detecting nose targets specially. [The topic and method of this study]: A mask wearing normalization detection model (towards the wearing style exposing the nose to outside, which is the most obvious characteristic of non-normalized style) based on improved YOLOv5s (You Only Look Once v5s is an object detection network model) was proposed.

Evaluating the tensile properties of high-strength stainless steels using small punch testing.

Accurately measuring the mechanical properties of high-strength stainless steels is of great significance for ensuring structural safety, predicting long-term performance and optimizing design. However, the standardized tensile test specimens used to obtain strength properties must be fabricated from bulk materials from an in-service structure or component, result in the loss of structural integrity or a reduction in remaining service life. Small punch tests require only miniscule material samples and are widely used to estimate in-service component material characteristics.

MLG-YOLO: A Model for Real-Time Accurate Detection and Localization of Winter Jujube in Complex Structured Orchard Environments.

Our research focuses on winter jujube trees and is conducted in a greenhouse environment in a structured orchard to effectively control various growth conditions. The development of a robotic system for winter jujube harvesting is crucial for achieving mechanized harvesting. Harvesting winter jujubes efficiently requires accurate detection and location.

Understanding the hierarchical structure of collagen fibers of the human periodontal ligament: Implications for biomechanical characteristics.

The periodontal ligament (PDL) is a unique fibrous connective tissue that regulates periodontal homeostasis mechanisms. Its biomechanical properties primarily reside in the hierarchical and non-uniform collagenous network. This study aimed to investigate the region-specific structure and composition of collagen fibers in the PDL at various scales and to explore their relationship with mechanical properties in a split-mouth design.

Recent Advances in Light Penetration Depth for Postharvest Quality Evaluation of Fruits and Vegetables.

Light penetration depth, as a characteristic parameter reflecting light attenuation and transmission in biological tissues, has been applied in nondestructive detection of fruits and vegetables. Recently, with emergence of new optical detection technologies, researchers have begun to explore methods evaluating optical properties of double-layer or even multilayer fruit and vegetable tissues due to the differences between peel and pulp in the chemical composition and physical properties, which has gradually promoted studies on light penetration depth. A series of demonstrated research on light penetration depth could ensure the accuracy of the optical information obtained from each layer of tissue, which is beneficial to enhance detection accuracy for quality assessment of fruits and vegetables.

Microbial mechanisms for higher hydrogen production in anaerobic digestion at constant temperature versus gradient heating.

Background: Clean energy hydrogen (H) produced from abundant lignocellulose is an alternative to fossil energy. As an essential influencing factor, there is a lack of comparison between constant temperatures (35, 55 and 65 °C) and gradient heating temperature (35 to 65 °C) on the H production regulation potential from lignocellulose-rich straw via high-solid anaerobic digestion (HS-AD). More importantly, the microbial mechanism of temperature regulating H accumulation needs to be investigated.

Optical blood glucose non-invasive detection and its research progress.

Blood glucose concentration is an important index for the diagnosis of diabetes, its self-monitoring technology is the method for scientific diabetes management. Currently, the typical household blood glucose meters have achieved great success in diabetes management, but they are discrete detection methods, and involve invasive blood sampling procedures. Optical detection technologies, which use the physical properties of light to detect the glucose concentration in body fluids non-invasively, have shown great potential in non-invasive blood glucose detection.

Lightweight CNN combined with knowledge distillation for the accurate determination of black tea fermentation degree.

Black tea is the second most common type of tea in China. Fermentation is one of the most critical processes in its production, and it affects the quality of the finished product, whether it is insufficient or excessive. At present, the determination of black tea fermentation degree completely relies on artificial experience.

Experimental and numerical study on explosion resistance of polyurea-coated shelter in petrochemical industry.

To reduce the number of casualties in explosion accidents, blast-resistant shelters can be used to protect personnel in high-risk areas of petrochemical processing plants. In this work, the deformation behaviours of uncoated and polyurea-coated blast-resistant plates were studied through gas explosion tests. An ANSYS/LS-DYNA model of a polyurea-coated shelter was established, and the dynamic responses of the shelter under various explosion loads were analysed.

River Surface Velocity Measurement for Rapid Levee Breach Emergency Response Based on DFP-P-LK Algorithm.

In recent years, the increasing frequency of climate change and extreme weather events has significantly elevated the risk of levee breaches, potentially triggering large-scale floods that threaten surrounding environments and public safety. Rapid and accurate measurement of river surface velocities is crucial for developing effective emergency response plans. Video image velocimetry has emerged as a powerful new approach due to its non-invasive nature, ease of operation, and low cost.

Calibration and Validation of Simulation Parameters for Maize Straw Based on Discrete Element Method and Genetic Algorithm-Backpropagation.

There is a significant difference between the simulation effect and the actual effect in the design process of maize straw-breaking equipment due to the lack of accurate simulation model parameters in the breaking and processing of maize straw. This article used a combination of physical experiments, virtual simulation, and machine learning to calibrate the simulation parameters of maize straw. A bimodal-distribution discrete element model of maize straw was established based on the intrinsic and contact parameters measured via physical experiments.

A Novel Cross-Domain Mechanical Fault Diagnosis Method Fusing Acoustic and Vibration Signals by Vision Transformer.

Changes in operating conditions often cause the distribution of signal features to shift during the bearing fault diagnosis process, which will result in reduced diagnostic accuracy of the model. Therefore, this paper proposes a dual-channel parallel adversarial network (DPAN) based on vision transformer, which extracts features from acoustic and vibration signals through parallel networks and enhances feature robustness through adversarial training during the feature fusion process. In addition, the Wasserstein distance is used to reduce domain differences in the fused features, thereby enhancing the network's generalization ability.

Development of a Portable Residual Chlorine Detection Device with a Combination of Microfluidic Chips and LS-BP Algorithm to Achieve Accurate Detection of Residual Chlorine in Water.

Chlorine is widely used for sterilization and disinfection of water, but the presence of excess residual chlorine in water poses a substantial threat to human health. At present, there is no portable device which can achieve accurate, rapid, low-cost, and convenient detection of residual chlorine in water. Therefore, it is necessary to develop a device that can perform accurate, rapid, low-cost, and convenient detection of residual chlorine in water.

Comprehensive Analysis of Laser Peening Forming Effects on 5083 Aluminum Alloy.

In order to investigate the laws of the laser peening forming process and the effects of laser peening on the surface quality and tensile properties of 5083 aluminum alloy, experiments were conducted utilizing various laser peening paths, energies, and plate thicknesses. Subsequently, laser peening forming experiments were performed on S-shaped and different shapes of aluminum alloy substrates. The impact of different laser peening durations on surface morphology and tensile properties was then analyzed.

Fatigue life prediction of cracked cross beam of mining linear vibrating screen under cyclic load.

The cross beam of a mining linear vibrating screen is prone to cracking under long-term cyclic load. In order to accurately predict the fatigue life of the cracked cross beam, a coupled analysis method of vibration and crack propagation is proposed. A 2D dynamic model of the vibrating screen is established based on the finite element method, which is verified by the vibration test platform.

Dynamics of a cross beam with a straight crack in a mining linear vibrating screen.

Cross beam fracture is one of the common failures of vibrating screens, and crack is the early manifestation of fracture, which is hard to detect. In order to meet the screening requirement of the vibrating screen and improve the service life of the cracked beam, the cracked Euler-Bernoulli beam model is established to investigate the dynamics of the cross beam with a straight crack under different weights of eccentric block, processing capacities, and Rayleigh damping coefficients based on the finite element method in this paper. The local flexibility coefficients are derived from the principles of fracture mechanics and strain release energy and solved by the adaptive five-point Gaussian Legende algorithm.

Efficient and low-energy degradation of chlorobenzene via catA-mediated cleavage and bedC1 docking in a novel Burkholderia stabilis TF-2.

In this study, a novel strain Burkholderia stabilis TF-2 capable of assimilatory and co-metabolic degradation of chlorobenzenes was obtained. The interaction between chlorobenzene (CB) and target enzymes, as well as the metabolic pathways in TF-2, were elucidated using multi-omics and molecular docking techniques. Results of degradation experiments indicated that TF-2 assimilated CB at a rate of 0.