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Aimed at the problems of a high leakage rate, a high cutting injury rate, and uneven root cutting in the existing combined garlic harvesting and root-cutting technology, we researched the key technologies used in a garlic harvester for adaptive root cutting based on machine vision. Firstly, research was carried out on the conveyor alignment and assembly of the garlic harvester to realize the adjustment of the garlic plant position and the alignment of the bulb's upper surface before the roots were cut, to establish the parameter equations and to modify the structure of the conveyor to form the adaptive garlic root-cutting system. Then, a root-cutting test using the double-knife disk-type cutting device was carried out to examine the root-cutting ability of the cutting device. Finally, a bulb detector trained with the IRM-YOLO model was deployed on the Jetson Nano device (NVIDIA, Jetson Nano(4GB), Santa Clara, CA, USA) to conduct a harvester field trial study. The pass rate for the root cutting was 82.8%, and the cutting injury rate was 2.7%, which tested the root cutting performance of the adaptive root cutting system and its field environment adaptability, providing a reference for research into combined garlic harvesting technology. [ABSTRACT FROM AUTHOR]

In this study, a leading–drawing–cutting–type profiled root–trimming device was designed to address the problems of high impurity and damage rates that occur with the operation of a pull–cut garlic harvester. The main components of the designed device include a pull–clamp mechanism, roll–pulling mechanism, root–trimming knife mechanism, lifter, gearbox, universal drive shaft, motor, and frame that, together, can complete the root–trimming operation for a pull–cut garlic harvester. An orthogonal regression test was carried out by taking the roller diameter, the roller inclination angle, the knife rotation speed, and the working speed as factors and by taking the impurity rate and the damage rate as indices. The results of the orthogonal regression test showed that the impurity rate was most strongly affected by the roller diameter, followed by the knife rotation speed, the working speed, and the roller inclination angle. Meanwhile, the damage rate was most strongly affected by the knife rotation speed, followed by the roller diameter, the working speed, and the roller inclination angle. The regression analysis showed that when the roller diameter was 100 mm, the roller inclination angle was 25°, the knife rotation speed was 200 r·min−1, and the working speed was 1.22 km·h−1, the comprehensive trimming quality reached its maximum value of 97.82%. The verification result of the parallel test gave a value of 97.52%, which was mainly affected by the irregular sizes of the bulbs, but it showed no significant difference from the regression analysis results. The tests verified that the profiled root–trimming device could be applied to develop the technology of garlic pull–cut harvesters. [ABSTRACT FROM AUTHOR]

The complex disaster of gas and coal spontaneous combustion is a major challenge in coal gob, especially under conditions of three-dimensional extraction. Taking the 15,101 mining face in Shigang Mine as the field background, COMSOL Multiphysics software was employed to construct models of airflow, methane migration, and stress distribution in gob under the stereo extraction method of "U+high-low level roadway." The range of oxidation zone was divided by combining the oxygen concentration and wind velocity field. The results showed that the methane can be discharged through the low-level airway and the return airway, and most of the methane at the top area in gob can also be discharged from the high-level roadway, indicating that the stereo ventilation was beneficial for methane dilution at both the upper and lower region. However, the oxidation zone in the middle of gob was the widest and closed to the mining face, it on the return side was narrower than intake side, and its distribution range was closer to the mining face. And finally, the range of the oxidation zone expanded with the increase in height in the vertical direction. These indicate the dangerous area for preventing gas and coal spontaneous combustion disasters in gob. [ABSTRACT FROM AUTHOR]

To rapidly dry peanut pods and effectively address mold issues resulting from rainy weather, this article provides an analysis of the current research status of global peanut digging, inverting, and harvesting technologies. Based on a two-stage peanut harvesting model, the operating principles of a high-quality peanut digging-inverter are elaborated upon, and the design of key machine components is discussed. The evaluation metrics for the operation of a high-quality peanut digging-inverter include the rate of vine inverting, the soil content rate, the rate of fallen pods, and the rate of buried pods. Utilizing theoretical analysis, the Box–Behnken experimental design is employed to investigate the operating parameters of these machines, with the tractor's running speed, the linear speed of the inverting roller, and the linear speed of the conveyor chain serving as the experimental factors in a three-factor, three-level experimental study. A regression model is established to analyze the impact of each factor on operational quality and to comprehensively optimize the influencing factors. The experimental results indicate that all factors significantly affect the rate of vine inverting. The tractor's running speed (X1) and the linear speed of the inverting roller (X3) significantly influence the rate of buried pods, while the linear speed of the conveyor chain (X2) does not have a significant effect on this rate. Similarly, the tractor's running speed (X1) and the linear speed of the inverting roller (X3) significantly affect the rate of fallen pods, whereas the linear speed of the conveyor chain (X2) does not. Furthermore, the linear speed of the conveyor chain (X2) and the linear speed of the inverting roller (X3) significantly impact the soil content rate, while the tractor's running speed (X1) does not. The optimal combination of operating parameters is a tractor running speed of 1 m/s, a conveyor chain linear speed of 1.3 m/s, and an inverting roller linear speed of 2.1 m/s. Under these conditions, the high-quality peanut digging-inverter achieves a vine inverting rate of 89.29%, a buried pod rate of 0.31%, a fallen pod rate of 0.74%, and a soil content rate of 8.11%. The experimental values for each evaluation index exhibit relative errors of 1.14%, 6.45%, 1.35%, and 0.13% compared to the optimized values provided by the Design-Expert software. The findings of this research will facilitate the development of hardware conditions for the future intelligent and information-based harvesting of peanuts, thereby establishing a solid foundation for the high-quality initial processing of oilseeds. [ABSTRACT FROM AUTHOR]

Off-road driving activities are common in many protected areas. This study aimed at applying a curvelet-based approach for the automatic extraction, mapping and separation of off-road tracks and animal paths in Masai Mara National Reserve, Kenya, using high-resolution GeoEye-1 panchromatic satellite imagery (50 cm). A novel hybrid remote sensing-GIS method comprising three main blocks is proposed: (1) extracting the high-contrast curvilinear feature from curvelet magnitudes derived from the finer scale of curvelet coefficient; (2) extracting the low-contrast curvilinear feature from coarser scale curvelets and refine the shape by deformable active contour (Snake), and (3) categorizing the extracted curvilinear feature into vehicle tracks and animal paths by a fuzzy logic inference system. Results from quantification of extraction and categorization performance of the trails were 77.5% for completeness, 89.2% for correctness, and 4.5% for redundancy, with an overall accuracy of 79.5%. Using grid matching, we find a high correlation between off-road vehicle tracks and animal paths in the area (r = 0.75, p < 0.05) indicating co-occurrence of these two types of trails. The proposed approach provides a basis for large-scale mapping and monitoring of off-road tracks and animal paths in the African savanna from space. [ABSTRACT FROM AUTHOR]

Due to various errors in actual use, MEMS inertial sensors have large errors in the detection of motion trajectories. Therefore, it is necessary to analyse and model the errors to decrease the impact of error sources on the detection system. This errors mainly include systematic random errors and accumulated errors generated during double integral operation, and different filtering methods are used for different types of errors. For random errors, the wavelet fuzzy threshold method is used to filter the sensor output signal. For the accumulated error, the zero-state adaptive compensation algorithm is used to correct the acceleration and integral velocity. Experiments show that the wavelet threshold denoising algorithm combined with the zero-state adaptive compensation algorithm can enhance the preciseness of the MEMS inertial sensor in object trajectory detection.

Facing the increasingly complex electromagnetic environment, how to make the detection instrument still have better detection performance is one of the current research hotspots. This paper proposes an anti-electromagnetic interference method based on high-order cumulant and PRI sorting. The former identifies the modulation type of the signal, the latter sorts the signals with different modulation parameters of the same modulation type, and finally selects the signal to be processed. The simulation results show that the algorithm is accurate and effective.

Mobility restriction measures were the main tools to control the spread of COVID-19, but the extent to which the mobility has decreased remained unsure. We investigated the change in local population mobility and its correlation with COVID-19 infections, using 1185 billion aggregated mobile phone data records in nine main cities in China from 10 January to 24 February 2020. The mobility fell by as much as 79.57% compared to the normal days in 2020 and by 58.13% compared to the same lunar period in 2019. The daily incidence of COVID-19 was significantly correlated with local daily mobility (R2 = 0.77, P < 0.001). The instantaneous reproduction number R(t) declined by 3% when mobility was reduced by 10% in the GLM analysis (P < 0.05). Our study indicated that the decreased mobility level, driven by a mixture effect of holiday and public health interventions, could substantially reduce the transmission of COVID-19 to a low level. Our study could provide evidence of mobility restriction to control local transmission for other places facing COVID-19 outbreaks or potential next waves. [ABSTRACT FROM AUTHOR]

The autofluorescence phenomenon is an inherent characteristic of lignified cells. However, in the case of Lophira alata (L. alata), the autofluorescence is nearly imperceptible during occasional fluorescence observations. The aim of this study is to investigate the mechanism behind the quenching of lignin's autofluorescence in L. alata by conducting associated experiments. Notably, the autofluorescence image of L. alata observed using optical microscopy appears to be quite indistinct. Abundant extractives are found in the longitudinal parenchyma, fibers, and vessels of L. alata. Remarkably, when subjected to a benzene–alcohol extraction treatment, the autofluorescence of L. alata becomes progressively enhanced under a fluorescence microscope. Additionally, UV–Vis absorption spectra demonstrate that the extractives derived from L. alata exhibit strong light absorption within the wavelength range of 200–500 nm. This suggests that the abundant extractives in L. alata are probably responsible for the autofluorescence quenching observed in the cell walls. Moreover, the presence and quantity of these extractives have a significant impact on the fluorescence intensity of lignin in wood, resulting in a significant decrease therein. In future studies, it would be interesting to explore the role of complex compounds such as polyphenols or terpenoids, which are present in the abundant extractives, in interfering with the fluorescence quenching of lignin in L. alata. [ABSTRACT FROM AUTHOR]

The primary objective of the current fire protection system in high-rise buildings is to extinguish fires in close proximity to the detectors. However, in the event of rapidly spreading fires, it is more effective to limit the transmission of fire and smoke. This study aims to develop an IoT-based real-time pre-response system for high-rise building fires that is capable of limiting the spread of fire and smoke. The proposed system collects fire data from sensors and transmits them to a cloud computer for real-time analysis. Based on the analysis results, the cloud computer controls the actions of alarm devices, ventilation equipment, and fine water mist nozzles. The system can dynamically adjust the entire system's behavior in real time by adopting pre-response measures to extinguish fires and limit the spread of fires and smoke. The system was tested on a simulation platform similar to actual high-rise buildings to evaluate its impact on fires and smoke. The results demonstrate the system's effectiveness in extinguishing fires and suppressing the spread of fires and smoke. [ABSTRACT FROM AUTHOR]

To satisfy the demand for rapid prediction of smoke transmission paths in high-rise building fires, a graph-based model was developed. The model represents a high-rise building as a Directed Acyclic Graph (DAG) grid model and employs computer simulation to determine the smoke transmission path and generate prediction results. The results were compared with those from similar simulations and were found to be consistent, indicating the feasibility and objective nature of the prediction results. Compared to other methods, this model has a shorter modeling time and can quickly provide prediction results. Furthermore, it can be applied to buildings of any structure, thus serving as a reference for smoke control design in high-rise building fire protection systems, particularly in cases involving complex internal structures. [ABSTRACT FROM AUTHOR]

In this study, we quantified and analyzed the root-cutting process of garlic with a test bench with pressure sensors on the basis of the comparative analysis of various information perception methods. On the basis of the output value of the pressure sensor, the force curve of garlic roots was plotted, and the double round blade cutting module is optimized on the basis of the force curve diagram. The innovative proposal of slotted round blades for garlic root cutting is presented here. The round blade diameter is 110 mm, the center distance is 100 mm, the blade thickness is 1 mm, and the blade speed is 1200 r/min. According to the analysis of the force curve, it was found that the slotted round blade with the slanted blade could generate a strong thrust to cut the roots. The cutting effect was better and the cutting surface of the roots was straight. The slotted blade meets the need for cutting garlic roots. [ABSTRACT FROM AUTHOR]

The technology of the divider and lifter mechanisms of a garlic harvester using the depth limit, straw divide, and straw lift modes was studied in Lanling County, Shandong Province, China, according to the characteristics of high hardness, good uprightness and narrow row spacing of garlic planting. A test prototype of the divider and lifter mechanisms of the garlic harvester was designed and manufactured. Single-factor experiments and orthogonal regression experiments were carried out using the experimental factors of working speed, the angle of the divider, the height of the tip of the divider's tooth from the ground, the ratio of the lifter's speed to working speed and the length of the lifter's tooth. The index was the success rate of feed. The results showed that the working speed, the angle of the divider and the length of the lifter's tooth had a significant influence on the success rate of feed (p < 0.05), but the experimental factors of the height of the tip of the divider's tooth from the ground and the ratio of the lifter's speed to working speed did not have a significant influence on the success rate of feed (p > 0.05). The effects of the angle of the divider, the working speed, and the length of the divider's tooth on the success rate of feed decreased in significance. When the working speed was 0.72 km·h−1, the length of the lifter's tooth was 343.5 mm and the angle of the divider was 20°, the success rate of feed was the highest (98.18%). The research results are conducive to promoting high-quality and efficient combined harvesting of garlic in Lanling County, Shandong Province, China. [ABSTRACT FROM AUTHOR]

Potato stem removal is one of the critical technical problems of potato mechanized harvesting; it directly affects the quality of potato harvesting and potato storage. There have been several studies on potato stem removal mechanisms. In practice, however, it was found that the potato stem removal rate was greatly influenced by the posture of the stem before it entered the removal mechanism. In this study, we designed a potato stem posture adjustment mechanism consisting of elastic curtains. A test rig was built to investigate the effect of curtain height, curtain width, and curtain suspension height on potato passage rate and potato stem removal rate. The Box–Behnken design (BBD), combined with the response surface method, was used to conduct the test. The optimal construction and installation parameters for each elastic curtain were determined as 278.93 mm for the curtain height, 20 mm for the curtain width, and 260 mm for the curtain suspension height. The predicted values of potato passage rate and potato stem removal rate under the optimal parameters were 92.36% and 82.83%, which were consistent with the validation test results. Based on the optimization results, a rigid-flexible coupled simulation model for a potato stem transported-posture adjustment process based on Abaqus and Adams was constructed. The maximum impact of the elastic curtain of the stem posture adjustment mechanism on the potato stem was 15.91 N and caused the stem to spring back. The projection angle β′ of the stem posture angle in the xoz plane before posture adjustment was 19.07°, and the β′ of the stem after posture adjustment was 87.18°. At this time, the stem was basically parallel to the rod of the separating sieve and had a high probability of falling from the gap of the bar to complete the removal of the stem. Overall, the stem transport position adjustment mechanism effectively adjusted the stem transported posture and improved the stem removal rate in potato mechanical harvesting. [ABSTRACT FROM AUTHOR]

In order to improve the operational performance of the self-developed 4HLB-4 half-feed four-row peanut combine harvester, single-factor and multifactor field tests were conducted on key operational parameters affecting the quality of harvesting. The response surface methodology was used to study the effects of the forward speed, clamping height, peanut picking roller rotational speed, and cleaning sieve vibrational frequency on the loss rate and impurity rate. A response surface regression model of the loss rate and impurity rate was constructed. A multi-objective integrated optimization was carried out for each factor. The results showed that, in terms of the order of significance, the influence of each factor on the impurity rate was as follows: cleaning sieve vibrational frequency > clamping height > forward speed > peanut picking roller rotational speed. The order of significance of the influence of each factor on the loss rate was as follows: peanut picking roller rotational speed > forward speed > clamping height > cleaning sieve vibrational frequency. The optimal combination of parameters was a forward speed of 0.85 m/s, clamping height of 190 mm, peanut picking roller rotational speed of 550 rpm, and cleaning sieve vibrational frequency of 590 cpm. Under these conditions, the impurity rate of 2.62% and the loss rate of 2.05% were obtained, which effectively reduced the impurity rate and loss rate and met the quality requirements of Chinese peanut mechanized harvesting operations. The results of this study can provide a basis for the improvement and optimization of the 4HLB-4 half-feed four-row peanut combine harvester and the optimization of its operating parameters. [ABSTRACT FROM AUTHOR]

Garlic root cutting is generally performed manually; it is easy for the workers to sustain hand injuries, and the labor efficiency is low. However, the significant differences between individual garlic bulbs limit the development of an automatic root cutting system. To address this problem, a deep learning model based on transfer learning and a low-cost computer vision module was used to automatically detect garlic bulb position, adjust the root cutter, and cut garlic roots on a garlic root cutting test bed. The proposed object detection model achieved good performance and high detection accuracy, running speed, and detection reliability. The visual image of the output layer channel of the backbone network showed the high-level features extracted by the network vividly, and the differences in learning of different networks clearly. The position differences of the cutting lines predicted by different backbone networks were analyzed through data visualization. The excellent and stable performance indicated that the proposed model had learned the correct features in the data of different brightness. Finally, the root cutting system was verified experimentally. The results of three experiments with 100 garlic bulbs each indicated that the mean qualified value of the system was 96%. Therefore, the proposed deep learning system can be applied in garlic root cutting which belongs to food primary processing. [ABSTRACT FROM AUTHOR]

Traditional manual garlic root cutting is inefficient and can cause food safety problems. To develop food processing equipment, a novel and accurate object detection method for garlic using deep learning—a convolutional neural network—is proposed in this study. The you-only-look-once (YOLO) algorithm, which is based on lightweight and transfer learning, is the most advanced computer vision method for single large object detection. To detect the bulb, the YOLOv2 model was modified using an inverted residual module and residual structure. The modified model was trained based on images of bulbs with varied brightness, surface attachment, and shape, which enabled sufficient learning of the detector. The optimum minibatches and epochs were obtained by comparing the test results of different training parameters. Research shows that IRM-YOLOv2 is superior to the SqueezeNet, ShuffleNet, and YOLOv2 models of classical neural networks, as well as the YOLOv3 and YOLOv4 algorithm models. The confidence score, average accuracy, deviation, standard deviation, detection time, and storage space of IRM-YOLOv2 were 0.98228, 99.2%, 2.819 pixels, 4.153, 0.0356 s, and 24.2 MB, respectively. In addition, this study provides an important reference for the application of the YOLO algorithm in food research. [ABSTRACT FROM AUTHOR]

Potato stems removal is an important part of mechanized potato harvesting. However, there is still limited research on the physical properties of potato stems, especially the determination of Poisson's ratio and Young's modulus. This study determined the Poisson's ratio and Young's modulus of the potato main stems at different heights above the ground. Since the Potato stems are viscoelastic cylinders with non-standard circular cross-sections and complex textures, the existing determination methods are difficult to apply. We propose a new method to determine Poisson's ratio and Young's modulus by combining image processing in the mechanical compression process. The feasibility of this method was verified by determining the hardness value of 65 Shore 'A' nitrile rubber specimens, and the measured Poisson's ratio and Young's modulus were close to the relevant literature. This method can be used for the determination of potato stems. Atlantic potatoes are widely grown for their high solids content, resistance to pests and diseases, and good processing quality. Ten Atlantic potato main stems were randomly selected at harvest time. Specimens with a length of 11 ± 1 mm were taken at 0 cm, 10 cm, 20 cm, and 30 cm above the ground from each stem. The average values of the axial Poisson's ratio were determined as: 0.21, 0.28, 0.30, 0.32, and the axial Young's modulus as: 15.90 MPa, 12.38 MPa, 11.68 MPa, 11.28 MPa. This study has provided critical basic data for the discrete element model construction of potato stems and numerical simulation of potato haulm killers and potato harvesters, which is beneficial for improving the harvest quality of potato. It also provides new ideas for Poisson's ratio and Young's modulus measurement of non-regular cross-sectional cylindrical viscoelastic materials. [ABSTRACT FROM AUTHOR]

Pasteurella multocida is the causative agent of fowl cholera, and florfenicol (FF) has potent antibacterial activity against P. multocida and is widely used in the poultry industry. In this study, we established a P. multocida infection model in ducks and studied the pharmacokinetics of FF in serum and lung tissues after oral administration of 30 mg/kg bodyweight. The maximum concentrations reached (Cmax) were lower in infected ducks (13.88 ± 2.70 μg/ml) vs. healthy control animals (17.86 ± 1.57 μg/ml). In contrast, the mean residence time (MRT: 2.35 ± 0.13 vs. 2.27 ± 0.18 hr) and elimination half‐life (T½β: 1.63 ± 0.08 vs. 1.57 ± 0.12 hr) were similar for healthy and diseased animals, respectively. As a result, the area under the concentration curve for 0–12 hr (AUC0–12 hr) for FF in healthy ducks was significantly greater than that in infected ducks (49.47 ± 5.31 vs. 34.52 ± 8.29 μg hr/ml). The pharmacokinetic differences of FF in lung tissues between the two groups correlated with the serum pharmacokinetic differences. The Cmax and AUC0–12 hr values of lung tissue in healthy ducks were higher than those in diseased ducks. The concentration of FF in lung tissues was approximately 1.2‐fold higher than that in serum both in infected and healthy ducks indicating that FF is effective in treating respiratory tract infections in ducks. [ABSTRACT FROM AUTHOR]