Development of a doorframe-typed swinging seedling pick-up device for automatic field transplantation

A doorframe-typed swing seedling pick-up device for automatic field transplanters was developed and evaluated in a laboratory. The device, consisting of a path manipulator and two grippers, can move the pins slowly to extract seedlings from the tray cells and return quickly to the pick-up point for the next extraction. The path manipulator was constructed with the creative design of type-Ⅱ mechanism combination in series. It consists of an oscillating guide linkage mechanism and a grooved globoidal cam mechanism. The gripper is a pincette-type mechanism using the pick-up pins to penetrate into the root mass for seedling extraction. The dynamic analysis of the designed seedling pick-up device was simulated with ADAMS software. Being the first prototype, various performance tests under local production conditions were conducted to find out the optimal machine operation parameters and transplant production conditions. As the gripper with multiple fine pins was moved by the swing pick-up device, it can effectively complete the transplanting work cycle of extracting, transferring, and discharging a seedling. The laboratory evaluation showed that the pick-up device equipped with two grippers can extract 80 seedlings/min with a 90% success and a 3% failure in discharging seedlings, using 42-day-old tomato plantlets. The quality of extracting seedlings was satisfactory

A whole row automatic pick-up device using air force to blow out vegetable plug seedlings

Aim of study: To develop a whole row automatic pick-up device using air force to blow out plug seedlings, to avoid the damage to seedlings that the current way of seedling picking by needle insertion induces.Area of study: Jiangsu Province, China.Material and methods: We designed a pick-up device which mainly consists of a seedling transporting device, a seedling air loosening device, a seedling clamping device and an automatic control system. The damage rate of seedling was significantly reduced and the success rate of seedling picking was increased by using the new seedling air loosening method and the new designed end-effectors. A prototype of the new pick-up device was produced according to the calculation results, and the performance tests were arranged under actual production conditions in an indoor laboratory.Main results: The calculation showed that when the diameter of the blowhole in air nozzle is 3.5 mm, and the air pressure is between 0.146 MPa and 0.315 MPa, the seedlings can be blown out successfully. Besides, the clamping strain test showed that the new designed end-effector can meet the requirements of seedling picking. The orthogonal test showed that both the air pressure and water content significantly affected the success ratio. The success ratio reached 96.64% when air pressure was 0.4 MPa, water content was 55%-60% and airflow rate was 100%, what meets the current requirements of transplanting.Research highlights: This research can provide some references for the automatic transplanting technology

Self-sustainable protonic ceramic electrochemical cells using a triple conducting electrode for hydrogen and power production.

The protonic ceramic electrochemical cell (PCEC) is an emerging and attractive technology that converts energy between power and hydrogen using solid oxide proton conductors at intermediate temperatures. To achieve efficient electrochemical hydrogen and power production with stable operation, highly robust and durable electrodes are urgently desired to facilitate water oxidation and oxygen reduction reactions, which are the critical steps for both electrolysis and fuel cell operation, especially at reduced temperatures. In this study, a triple conducting oxide of PrNi0.5Co0.5O3-δ perovskite is developed as an oxygen electrode, presenting superior electrochemical performance at 400~600 °C. More importantly, the self-sustainable and reversible operation is successfully demonstrated by converting the generated hydrogen in electrolysis mode to electricity without any hydrogen addition. The excellent electrocatalytic activity is attributed to the considerable proton conduction, as confirmed by hydrogen permeation experiment, remarkable hydration behavior and computations

Distracted driving behavior recognition based on improved MobileNetV2

In recent years, research on distracted driving behavior recognition has made significant progress, with an increasing number of researchers focusing on deep-learning-based algorithms. Aiming at the problems of the existing distracted driving recognition algorithm, such as its oversized model and difficulty in adapting to low computing environments, a lightweight network MobileNetV2, is chosen as the backbone network and improved to design a distracted driving behavior detection method that is both accurate and practical. The Ghost module is employed to replace point-by-point convolution to reduce the computation, the Leaky ReLU function helps mitigate the problem of dead neurons, as it prevents gradients from becoming zero for negative inputs. Finally, the channel pruning algorithm is used to further reduce the model parameters. The experiment results on the State Farm dataset show that the model’s test accuracy can reach 94.66%, and the number of parameters is only 0.23 M. The improved model has significantly fewer parameters than the baseline model, which demonstrates the effectiveness and applicability of the method

SGCRNN: A ChebNet-GRU fusion model for eeg emotion recognition

The paper proposes a deep learning model based on Chebyshev Network Gated Recurrent Units, which is called Spectral Graph Convolution Recurrent Neural Network, for multichannel electroencephalogram emotion recognition. First, in this paper, an adjacency matrix capturing the local relationships among electroencephalogram channels is established based on the cosine similarity of the spatial locations of electroencephalogram electrodes. The training efficiency is improved by utilizing the computational speed of the cosine distance. This advantage enables our method to have the potential for real-time emotion recognition, allowing for fast and accurate emotion classification in real-time application scenarios. Secondly, the spatial and temporal dependence of the Spectral Graph Convolution Recurrent Neural Network for capturing electroencephalogram sequences is established based on the characteristics of the Chebyshev network and Gated Recurrent Units to extract the spatial and temporal features of electroencephalogram sequences. The proposed model was tested on the publicly accessible dataset DEAP. Its average recognition accuracy is 88%, 89.5%, and 89.7% for valence, arousal, and dominance, respectively. The experiment results demonstrated that the Spectral Graph Convolution Recurrent Neural Network method performed better than current models for electroencephalogram emotion identification. This model has broad applicability and holds potential for use in real-time emotion recognition scenarios

Comprehensive comparative analysis of prognostic value of serum systemic inflammation biomarkers for colorectal cancer: Results from a large multicenter collaboration

BackgroundThe incidence of colorectal cancer (CRC) is common and reliable biomarkers are lacking. We aimed to systematically and comprehensively compare the ability of various combinations of serum inflammatory signatures to predict the prognosis of CRC. Moreover, particular attention has been paid to the clinical feasibility of the newly developed inflammatory burden index (IBI) as a prognostic biomarker for CRC.MethodsThe discrimination capacity of the biomarkers was compared using receiver operating characteristic curves and Harrell’s C-index. Kaplan-Meier curves and log-rank tests were used to compare survival differences between the groups. Cox proportional hazard regression analysis was used to determine the independent prognostic factors. Logistic regression analysis was used to assess the relationship between IBI, short-term outcomes, and malnutrition.ResultsIBI had the optimal prediction accuracy among the systemic inflammation biomarkers for predicting the prognosis of CRC. Taking IBI as a reference, none of the remaining systemic inflammation biomarkers showed a gain. Patients with high IBI had significantly worse overall survival than those with low IBI (56.7% vs. 80.2%; log-rank P<0.001). Multivariate Cox regression analysis showed that continuous IBI was an independent risk factor for the prognosis of CRC patients (hazard ratio = 1.165, 95% confidence interval [CI] = 1.043–1.302, P<0.001). High IBI was an independent risk factor for short-term outcomes (odds ratio [OR] = 1.537, 95% CI = 1.258–1.878, P<0.001), malnutrition (OR = 2.996, 95% CI = 1.471–6.103, P=0.003), and recurrence (OR = 1.744, 95% CI = 1.176–2.587, p = 0.006) in CRC patients.ConclusionsIBI, as a reflection of systemic inflammation, is a feasible and promising biomarker for assessing the prognosis of CRC patients

Development of a riding-type fully automatic transplanter for vegetable plug seedlings

 Aim of study: The aim of this study was to develop a riding-type fully automatic vegetable seedling transplanter enabling continuous transplanting work on 2 rows simultaneously with plug seedlings fed automatically.Material and methods: In design, the transplanter consists of a 4-wheel drive system, a seedling pick-up mechanism, a seedling feeding mechanism, a rotation discharging mechanism, a 2-row planting mechanisms, and a multi-source control unit. The 4-wheel drive system is a riding type well adapting to slops. The seedling pick-up mechanism could extract several seedlings at a time from the tray cells conveyed by the feeding mechanism, and then transfer them to the rotation discharging mechanism where they would be released into the 2-row planting mechanisms. The multi-source control unit was constructed to carry out the flexible automation of seedling transplanting. Being the first prototype, the performance tests under actual production conditions were conducted on a vegetable base.Main results: The testing results showed that the developed fully automatic transplanter could well grasp seedlings from the trays, transfer them, discharge them, and plant them into the ground. The success ratio in picking up seedlings and the qualified percent in planting seedlings were all up to 90%, and the coefficient of variation of plant spacing was less than 5% at the working speed of 60 plants row-1 min-1.Research highlights: The overall planting effects could well meet the requirements of agronomy cultivation, and the quality of automatic transplanting was satisfactor

Multiscale Entropy Analysis on Human Operating Behavior

By exploiting the statistical analysis method, human dynamics provides new insights to the research of human behavior. In this paper, we analyze the characteristics of the computer operating behavior through a modified multiscale entropy algorithm with both the interval time series and the number series of individuals’ operating behavior been investigated. We also discuss the activity of individuals’ behavior from the three groups denoted as the retiree group, the student group and the worker group based on the nature of their jobs. We find that the operating behavior of the retiree group exhibits more complex dynamics than the other two groups and further present a reasonable explanation for this phenomenon. Our findings offer new insights for the further understanding of individual behavior at different time scales

Solution for acoustic field of thermo-acoustic emission from arbitrary source

In this work, an expression for acoustic field of thermo-acoustic (TA) emission from arbitrary source is presented by deriving the solutions of TA emission from spherical surface and point source in gas and then taking advantage of the point sources superposition and the surface heat distribution factor. Accordingly, the computational analysis of acoustic pressure field of TA emission is extended to three-dimensional cases. The theory developed in this work is in good agreement with the experimental results and applicable for solving many complex and important TA emission problems including nanothermophones and phased array and impulse-driven TA emissions