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In the traditional control scheme of a 12/8-pole bearingless switched reluctance motor (BSRM), radial force and torque are usually controlled as a compromise due to the conflict between their effective output areas. Additionally, each phase requires individual power circuits and is excited in turn to produce a continuous levitation force, resulting in high power device requirements and high controller costs. This paper discusses a 12/8-pole single-winding hybrid-rotor bearingless switched reluctance motor (HBSRM) with a hybrid rotor consisting of cylindrical and salient-pole lamination segments. The asymmetric rotor of the HBSRM slightly increases the complexity of its structure and magnetic circuit, but makes it possible to generate the desired radial force at any rotor angular position. A control scheme for the HBSRM is developed to utilize the independent excitation of the four windings in one phase to generate the desired levitation force at any rotor angular position, and it requires only half the number of power circuits used in the conventional control scheme of a 12/8-pole single-winding BSRM. Different from the average torque chosen to be controlled in traditional methods, this scheme directly regulates the instantaneous total torque produced by all excited phases together and presents a current algorithm to optimize the torque contribution of each phase so as to reduce torque pulsation, and the improved performance of this bearingless motor is finally validated by simulation analysis. [ABSTRACT FROM AUTHOR]

Featured Application: In this study, we report on fast and robust autofocus for non-mydriatic fundus photography under less stringent imaging conditions. Based on image sharpness evaluations, the adaptive focus window and path-optimized search are used to detect the focus position accurately. This method can be applied to fundus cameras or similar ophthalmic instruments, effectively alleviating imaging challenges posed by patients with fixation difficulties. Non-mydriatic fundus photography (NMFP) plays a vital role in diagnosing eye diseases, with its performance primarily dependent on the autofocus process. However, even minor maloperations or eye micro-movements can compromise fundus imaging quality, leading to autofocus inaccuracy and a heightened risk of misdiagnosis. To enhance the autofocus performance in NMFP, a fast and robust fundus autofocus method with adaptive window and path-optimized search is proposed. In this method, the adaptive focus window is used to suppress irrelevant image contents and correct the sharpness curve, and the path-optimized search is constructed to overcome the curve's local extrema, in order to achieve rapid focus position convergence. This method was simulated and clinically studied with the self-developed autofocus system for NMFP. The results of 80 cases of human eye imaging show that, compared with similar autofocus methods, this method achieves a focus success rate of 90% with the least axial scanning, and can adapt to non-ideal imaging conditions such as pupil misalignment, eyelash occlusion, and nystagmus. [ABSTRACT FROM AUTHOR]

Keypoint detection plays a pivotal role in three-dimensional computer vision, with widespread applications in improving registration precision and efficiency. However, current keypoint detection methods often suffer from poor robustness and low discriminability. In this study, a novel keypoint detection approach based on the local variation of surface (LVS) is proposed. The LVS keypoint detection method comprises three main steps. Firstly, the surface variation index for each point is calculated using the local coordinate system. Subsequently, points with a surface variation index lower than the local average are identified as initial keypoints. Lastly, the final keypoints are determined by selecting the minimum value within the neighborhood from the initial keypoints. Additionally, a sampling consensus correspondence estimation algorithm based on geometric constraints (SAC-GC) for efficient and robust estimation of optimal transformations in correspondences is proposed. By combining LVS and SAC-GC, we propose a coarse-to-fine point cloud registration algorithm. Experimental results on four public datasets demonstrate that the LVS keypoint detection algorithm offers improved repeatability and robustness, particularly when dealing with noisy, occluded, or cluttered point clouds. The proposed coarse-to-fine point cloud registration algorithm also exhibits enhanced robustness and computational efficiency. [ABSTRACT FROM AUTHOR]

In recent years, deep learning has been increasingly used in fault diagnosis of rotating machinery. However, the actual acquisition of rolling bearing fault signals often contains ambient noise, making it difficult to determine the optimal values of the parameters. In this paper, a sparrow search algorithm (LSSA) based on backward learning of lens imaging and Gaussian Cauchy variation is proposed. The lens imaging reverse learning strategy enhances the traversal capability of the algorithm and allows for a better balance of algorithm exploration and development. Then, the performance of the proposed LSSA was tested on the benchmark function. Finally, LSSA is used to find the optimal modal component K and the optimal penalty factor α in VMD-GRU, which in turn realizes the fault diagnosis of rolling bearings. The experimental results show that the model can achieve a 96.61% accuracy in rolling bearing fault diagnosis, which proves the effectiveness of the method. [ABSTRACT FROM AUTHOR]

Hail, known as an agricultural meteorological disaster, can substantially constrain the growth of the apple industry. Presently, apple orchards use a variety of colored (photo-selective) hail nets as a preventative measure. However, it is unclear which color proves most effective for apple orchards. This study provides a systematic investigation of the impact of four photo-selective colored hail nets (white, blue, black, and green; with white being the control) on the microenvironment of apple orchards, fruit tree development, fruit quality, and yield over a two-year period (2020–2021). Different photo-selective nets do not evidently alter the intensity of light, although the nets' shading effects decrease in the order from black to green to blue. Among them, blue nets increased the proportion of blue light, while green nets enhanced the proportion of green light. On the other hand, black, green, and blue nets diminished the proportion of red and far-red light. Such photo-selective nets effectively lowered soil temperature but did not have an impact on relative humidity and air temperature. Encasing apple trees with blue nets promoted growth, increasing shoot length, thickness, leaf area, and water content, while simultaneously decreasing leaf thickness. Black nets had comparable effects, although the impacts of green nets were inconsistent. Different photo-selective nets did not significantly influence the leaf shape index or overall chlorophyll content. However, black and green nets reduced the chlorophyll a/b ratio, while blue nets slightly boosted this ratio. Additionally, blue nets proved beneficial for apple trees' photosynthesis. With the employment of a principal component analysis and comprehensive evaluation, this study concludes that blue nets offer the most favorable environmental conditions for apple growth while protecting apple orchards against hail, compared to black, white, and green nets. [ABSTRACT FROM AUTHOR]

Despite the acknowledged importance of terrestrial ecosystems in achieving carbon neutrality, current carbon accounting predominantly focuses on CO2 uptake, neglecting indirect contributions from ecosystem services, such as temperature regulation and air purification. We established a carbon benefit (C benefit) accounting framework that integrated these services and analyzed the drivers influencing the spatial and temporal changes in the C benefit. It was found that the average annual growth rate of C benefits in Chengdu over the past 20 years was 0.91 Tg/a, and the CO2 emissions reduction due to ecosystem services was 22.47 times that of carbon sinks. Therefore, the contribution of ecosystem regulating services to carbon neutrality cannot be ignored. In addition, the elevation, gross domestic product (GDP), and normalized differential vegetation index (NDVI) are key factors affecting C benefits. It is worth noting that the intensive management of constructed ecosystems can result in significant reductions in ecosystem C benefits. Finally, our findings underline the need for low-carbon policies to not only promote carbon sink projects but also enhance the overall capacity of ecosystem services, which could substantially mitigate global climate change. [ABSTRACT FROM AUTHOR]

The occurrence of microplastics in drinking water has drawn increasing attention due to their ubiquity and unresolved implications regarding human health. Despite achieving high reduction efficiencies (70 to >90%) at conventional drinking water treatment plants (DWTPs), microplastics remain. Since human consumption represents a small portion of typical household water use, point-of-use (POU) water treatment devices may provide the additional removal of microplastics (MPs) prior to consumption. The primary objective of this study was to evaluate the performance of commonly used pour-through POU devices, including those that utilize combinations of granular activated carbon (GAC), ion exchange (IX), and microfiltration (MF), with respect to MP removal. Treated drinking water was spiked with polyethylene terephthalate (PET) and polyvinyl chloride (PVC) fragments, along with nylon fibers representing a range of particle sizes (30–1000 µm) at concentrations of 36–64 particles/L. Samples were collected from each POU device following 25, 50, 75, 100 and 125% increases in the manufacturer's rated treatment capacity, and subsequently analyzed via microscopy to determine their removal efficiency. Two POU devices that incorporate MF technologies exhibited 78–86% and 94–100% removal values for PVC and PET fragments, respectively, whereas one device that only incorporates GAC and IX resulted in a greater number of particles in its effluent when compared to the influent. When comparing the two devices that incorporate membranes, the device with the smaller nominal pore size (0.2 µm vs. ≥1 µm) exhibited the best performance. These findings suggest that POU devices that incorporate physical treatment barriers, including membrane filtration, may be optimal for MP removal (if desired) from drinking water. [ABSTRACT FROM AUTHOR]

A bearingless switched reluctance motor (BSRM) has the combined characteristics of a switched reluctance motor (SRM) and a magnetic bearing. The hybrid-rotor BSRM (HBSRM) discussed in the paper has a twelve-pole stator and an eight-pole hybrid rotor, which is composed of a cylindrical rotor and a salient-pole rotor. Although the asymmetry of the hybrid rotor makes the structure and magnetic field of the HBSRM more complex, it can always produce a significant amount of magnetic pulling force to levitate a rotor shaft at all the rotor angular positions of each phase, which is not available in a traditional BSRM. The classical mathematical model for a conventional BSRM is valid only when its rotor rotates from the start of the overlap position to the aligned position, and the radial force and torque derived from this model are discontinuous at the aligned positon, which is harmful to the motor's stable operation. In this paper, a full-period mathematical model on the assumption that the gap permeance is cut apart by straight lines or improved elliptical lines for a 12/8-pole HBSRM is provided. On the basis of this mathematical model, the continuity of the radial force and torque at all the rotor angular positions can be guaranteed, and the fine characteristics of this mathematical model have been verified by simulations. [ABSTRACT FROM AUTHOR]

Alcohol addiction is regarded as a series of dynamic changes to neural circuitries. A comparison of the global network during different stages of alcohol addiction could provide an efficient way to understand the neurobiological basis of addiction. Two animal models (P-rats screened from an alcohol preference family, and NP-rats screened from an alcohol non-preference family) were trained for alcohol preference with a two-bottle free choice method for 4 weeks. To examine the changes in the neural response to alcohol during the development of alcohol preference and acute stimulation, different trials were studied with resting-state fMRI methods during different periods of alcohol preference. The correlation coefficients of 28 regions in the whole brain were calculated, and the results were compared for alcohol preference related to the genetic background/training association. The variety of coherence patterns was highly related to the state and development of alcohol preference. We observed significant special brain connectivity changes during alcohol preference in P-rats. The comparison between the P- and NP-rats highlighted the role of genetic background in alcohol preference. The results of this study support the alterations of the neural network connection during the formation of alcohol preference and confirm that alcohol preference is highly related to the genetic background. This study could provide an effective approach for understanding the neurobiological basis of alcohol addiction. [ABSTRACT FROM AUTHOR]

A progressive price scheme (PPS) has been implemented in Shanghai since 2013 in consideration of residents' ability to pay, and charges are based on the actual water consumption of the residents, in an effort to balance the rational allocation of water resources and the goal of saving water between rich and poor families. In the current work, the effect of the PPS for water use was evaluated based on the water use of 6661 households from 14 communities in Shanghai. It was found that the PPS did not reduce household water consumption when comparing the water consumption per household both before and after the implementation of the PPS policy. To investigate the weakness of the PPS, a principal component analysis (PCA) and a hierarchical cluster analysis (HCA) were conducted to access the relationships between mean household water use and community factors such as housing price, management fees, and the number of parking sites. Moreover, a significant inverted U-shaped curve between housing price and water use was found, which demonstrates that rental households shared by several tenants were the main consumers of residential water, and they were not sensitive to the water price improvement in the PPS due to sharing water prices. Therefore, a proposal was made in this work to increase the proportion of water fee expenditure in the total household income and to use 3% as the benchmark for water affordability. Our results provided a new picture of residential water use in big cities and a method for saving and balancing urban water resources. [ABSTRACT FROM AUTHOR]