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Active Disturbance Rejection Control—New Trends in Agricultural Cybernetics in the Future: A Comprehensive Review
With the development of smart and precision agriculture, new challenges have emerged in terms of response speed and adaptability in agricultural equipment control. Active Disturbance Rejection Control (ADRC), an advanced control strategy known for its strong robustness and disturbance rejection capabilities, has demonstrated exceptional performance in various fields, such as aerospace, healthcare, and military applications. Therefore, investigating the application of ADRC in agricultural control systems is of great significance. This review focuses on the fundamental principles of ADRC and its applications in agriculture, exploring its potential use and achievements in precision agriculture management, intelligent agricultural control, and other agricultural control sectors. These include the control of agricultural machinery, field navigation and trajectory tracking, agricultural production processes, as well as fisheries and greenhouse management in various agricultural scenarios. Additionally, this paper summarizes the integration of ADRC with other control technologies (e.g., LADRC, SMC) in agricultural applications and discusses the advantages and limitations of ADRC in the aforementioned areas. Furthermore, the challenges, development trends, and future research directions of ADRC in agricultural applications are examined to provide a reference for its future development.
Journal Article
Automatic Lettuce Weed Detection and Classification Based on Optimized Convolutional Neural Networks for Robotic Weed Control
Weed management plays a crucial role in the growth and yield of lettuce, with timely and effective weed control significantly enhancing production. However, the increasing labor costs and the detrimental environmental impact of chemical herbicides have posed serious challenges to the development of lettuce farming. Mechanical weeding has emerged as an effective solution to address these issues. In precision agriculture, the prerequisite for autonomous weeding is the accurate identification, classification, and localization of lettuce and weeds. This study used an intelligent mechanical intra-row lettuce-weeding system based on a vision system, integrating the newly proposed LettWd-YOLOv8l model for lettuce–weed recognition and lettuce localization. The proposed LettWd-YOLOv8l model was compared with other YOLOv8 series and YOLOv10 series models in terms of performance, and the experimental results demonstrated its superior performance in precision, recall, F1-score, mAP50, and mAP95, achieving 99.732%, 99.907%, 99.500%, 99.500%, and 98.995%, respectively. Additionally, the mechanical component of the autonomous intra-row lettuce-weeding system, consisting of an oscillating pneumatic mechanism, effectively performs intra-row weeding. The system successfully completed lettuce localization tasks with an accuracy of 89.273% at a speed of 3.28 km/h and achieved a weeding rate of 83.729% for intra-row weed removal. This integration of LettWd-YOLOv8l and a robust mechanical system ensures efficient and precise weed control in lettuce cultivation.
Journal Article
Heterogeneous Integration of Atomically‐Thin Indium Tungsten Oxide Transistors for Low‐Power 3D Monolithic Complementary Inverter
In this work, the authors demonstrate a novel vertically‐stacked thin film transistor (TFT) architecture for heterogeneously complementary inverter applications, composed of p‐channel polycrystalline silicon (poly‐Si) and n‐channel amorphous indium tungsten oxide (a‐IWO), with a low footprint than planar structure. The a‐IWO TFT with channel thickness of approximately 3‐4 atomic layers exhibits high mobility of 24 cm2 V−1 s−1, near ideally subthreshold swing of 63 mV dec−1, low leakage current below 10−13 A, high on/off current ratio of larger than 109, extremely small hysteresis of 0 mV, low contact resistance of 0.44 kΩ‐µm, and high stability after encapsulating a passivation layer. The electrical characteristics of n‐channel a‐IWO TFT are well‐matched with p‐channel poly‐Si TFT for superior complementary metal–oxide‐semiconductor technology applications. The inverter can exhibit a high voltage gain of 152 V V−1 at low supply voltage of 1.5 V. The noise margin can be up to 80% of supply voltage and perform the symmetrical window. The pico‐watt static power consumption inverter is achieved by the wide energy bandgap of a‐IWO channel and atomically‐thin channel. The vertically‐stacked complementary field‐effect transistors (CFET) with high energy‐efficiency can increase the circuit density in a chip to conform the development of next‐generation semiconductor technology. The 3D monolithic heterogeneous complementary field‐effect transistor (CFET) integrated with polycrystalline silicon (Poly‐Si) and atomically‐thin amorphous indium tungsten oxide (a‐IWO) TFTs for a vertically stack architecture realizes high voltage gain and low‐power logic circuit, showing the high potential to meet the requirements of next‐generation IC technology with a tiny footprint and extremely high chip density.
Journal Article
Effect of restricting bedtime mobile phone use on sleep, arousal, mood, and working memory: A randomized pilot trial
This study aimed to assess the effects of restricting mobile phone use before bedtime on sleep, pre-sleep arousal, mood, and working memory.
Thirty-eight participants were randomized to either an intervention group (n = 19), where members were instructed to avoid using their mobile phone 30 minutes before bedtime, or a control group (n = 19), where the participants were given no such instructions. Sleep habit, sleep quality, pre-sleep arousal and mood were measured using the sleep diary, the Pittsburgh sleep quality index, the Pre-sleep Arousal Scale and the Positive and Negative Affect Schedule respectively. Working memory was tested by using the 0-,1-,2-back task (n-back task).
Restricting mobile phone use before bedtime for four weeks was effective in reducing sleep latency, increasing sleep duration, improving sleep quality, reducing pre-sleep arousal, and improving positive affect and working memory.
Restricting mobile phone use close to bedtime reduced sleep latency and pre-sleep arousal and increased sleep duration and working memory. This simple change to moderate usage was recommended to individuals with sleep disturbances.
Journal Article
Correlation analysis between disease severity and inflammation-related parameters in patients with COVID-19: a retrospective study
Background
COVID-19 is highly contagious, and the crude mortality rate could reach 49% in critical patients. Inflammation concerns on disease progression. This study analyzed blood inflammation indicators among mild, severe and critical patients, helping to identify severe or critical patients early.
Methods
In this cross-sectional study, 100 patients were included and divided into mild, severe or critical groups according to disease condition. Correlation of peripheral blood inflammation-related indicators with disease criticality was analyzed. Cut-off values for critically ill patients were speculated through the ROC curve.
Results
Significantly, disease severity was associated with age (
R
= -0.564,
P
< 0.001), interleukin-2 receptor (IL2R) (
R
= -0.534,
P
< 0.001), interleukin-6 (IL-6) (
R
= -0.535,
P
< 0.001), interleukin-8 (IL-8) (
R
= -0.308,
P
< 0.001), interleukin-10 (IL-10) (
R
= -0.422,
P
< 0.001), tumor necrosis factor α (TNFα) (
R
= -0.322,
P
< 0.001), C-reactive protein (CRP) (
R
= -0.604,
P
< 0.001), ferroprotein (
R
= -0.508,
P
< 0.001), procalcitonin (
R
= -0.650,
P
< 0.001), white cell counts (WBC) (
R
= -0.54,
P
< 0.001), lymphocyte counts (LC) (
R
= 0.56,
P
< 0.001), neutrophil count (NC) (
R
= -0.585,
P
< 0.001) and eosinophil counts (EC) (
R
= 0.299,
P
< 0.001). With IL2R > 793.5 U/mL or CRP > 30.7 ng/mL, the progress of COVID-19 to critical stage should be closely observed and possibly prevented.
Conclusions
Inflammation is closely related to severity of COVID-19, and IL-6 and TNFα might be promising therapeutic targets.
Journal Article
Methods for detecting charge fractionalization and winding numbers in an interacting fermionic ladder
We consider a spin-1/2 fermionic ladder with spin-orbit coupling and a perpendicular magnetic field, which shares important similarities with topological superconducting wires. We fully characterize the symmetry-protected topological phase of this ladder through the identification of fractionalized edge modes and non-trivial spin winding numbers. We propose an experimental scheme to engineer such a ladder system with cold atoms in optical lattices, and we present two protocols that can be used to extract the topological signatures from density and momentum-distribution measurements. We then consider the presence of interactions and discuss the effects of a contact on-site repulsion on the topological phase. We find that such interactions could enhance the extension of the topological phase in certain parameters regimes.
Journal Article
The chronic kidney disease and acute kidney injury involvement in COVID-19 pandemic: A systematic review and meta-analysis
Currently, the SARS-CoV-2 promptly spread across China and around the world. However, there are controversies about whether preexisting chronic kidney disease (CKD) and acute kidney injury complication (AKI) are involved in the COVID-19 pandemic.
Studies reported the kidney outcomes in different severity of COVID-19 were included in this study. Standardized mean differences or odds ratios were calculated by employing Review Manager meta-analysis software.
Thirty-six trials were included in this systematic review with a total of 6395 COVID-19 patients. The overall effects indicated that preexisting CKD (OR = 3.28), complication of AKI (OR = 11.02), serum creatinine (SMD = 0.68), abnormal serum creatinine (OR = 4.86), blood urea nitrogen (SMD = 1.95), abnormal blood urea nitrogen (OR = 6.53), received continuous renal replacement therapy (CRRT) (OR = 23.63) were significantly increased in severe group than that in nonsevere group. Additionally, the complication of AKI (OR = 13.92) and blood urea nitrogen (SMD = 1.18) were remarkably elevated in the critical group than that in the severe group.
CKD and AKI are susceptible to occur in patients with severe COVID-19. CRRT is applied frequently in severe COVID-19 patients than that in nonsevere COVID-19 patients. The risk of AKI is higher in the critical group than that in the severe group.
Journal Article
Deep Learning for Sustainable Agriculture: A Systematic Review on Applications in Lettuce Cultivation
Lettuce, a vital economic crop, benefits significantly from intelligent advancements in its production, which are crucial for sustainable agriculture. Deep learning, a core technology in smart agriculture, has revolutionized the lettuce industry through powerful computer vision techniques like convolutional neural networks (CNNs) and YOLO-based models. This review systematically examines deep learning applications in lettuce production, including pest and disease diagnosis, precision spraying, pesticide residue detection, crop condition monitoring, growth stage classification, yield prediction, weed management, and irrigation and fertilization management. Notwithstanding its significant contributions, several critical challenges persist, including constrained model generalizability in dynamic settings, exorbitant computational requirements, and the paucity of meticulously annotated datasets. Addressing these challenges is essential for improving the efficiency, adaptability, and sustainability of deep learning-driven solutions in lettuce production. By enhancing resource efficiency, reducing chemical inputs, and optimizing cultivation practices, deep learning contributes to the broader goal of sustainable agriculture. This review explores research progress, optimization strategies, and future directions to strengthen deep learning’s role in fostering intelligent and sustainable lettuce farming.
Journal Article
3D segmentation denoising technology of millimeter wave human body security imaging
To meet the demand of noise reduction in millimeter‐wave human body security imaging, this paper proposes a new method for 3D segmentation denoising in millimeter‐wave images. The test results indicate that with the incorporation of 3D segmentation denoising technology, the noise in the background area of millimeter wave images has decreased by approximately 20–40 dB, significantly improving image quality. The detection rate has increased from 90% to 95%, while the false positive rate has decreased from 13% to 5%. This has important practical significance for real‐world applications. To meet the demand of noise reduction in millimeter‐wave human body security imaging, this paper proposes a new method for 3D segmentation denoising in millimeter‐wave images. The test results indicate that with the incorporation of 3D segmentation denoising technology, the noise in the background area of millimeter wave images has decreased by approximately 20–40 dB, significantly improving image quality. The detection rate has increased from 90% to 95%, while the false positive rate has decreased from 13% to 5%. This has important practical significance for real‐world applications.
Journal Article