Search

To meet the demand for constant current and constant voltage charging of batteries and to increase the system output power, the LCC-LCL/S-type self-switching wireless power transfer system is proposed. The system does not require communication between the primary and secondary circuits, and its output mode is controlled by simply changing the status of two switches on the secondary side. Notably, the system satisfies the zero phase angle characteristic before and after mode switching. The parameter design method is proposed based on the circuit topology and the maximum safe current constraint. To make the output voltage fluctuation as small as possible, the optimum load switching point for the system has been designed, and its optimality has been validated by simulation. Furthermore, the switching control strategy is proposed, considering the effects of the system no-load and load short-circuit in real situations. Finally, an experimental platform was built to achieve the high efficiency output of the system with the maximum output voltage of 46.21 V, the maximum output power of 180 W, and the maximum efficiency of 93.4%, which verified the applicability of the proposed method. [ABSTRACT FROM AUTHOR]

Cardiovascular diseases pose a long-term risk to human health. This study focuses on the rich-spectrum mechanical vibrations generated during cardiac activity. By combining Fourier series theory, we propose a multi-frequency vibration model for the heart, decomposing cardiac vibration into frequency bands and establishing a systematic interpretation for detecting multi-frequency cardiac vibrations. Based on this, we develop a small multi-frequency vibration sensor module based on flexible polyvinylidene fluoride (PVDF) films, which is capable of synchronously collecting ultra-low-frequency seismocardiography (ULF-SCG), seismocardiography (SCG), and phonocardiography (PCG) signals with high sensitivity. Comparative experiments validate the sensor's performance and we further develop an algorithm framework for feature extraction based on 1D-CNN models, achieving continuous recognition of multiple vibration features. Testing shows that the recognition coefficient of determination ( R 2 ), mean absolute error (MAE), and root mean square error (RMSE) of the 8 features are 0.95, 2.18 ms, and 4.89 ms, respectively, with an average prediction speed of 60.18 us/point, meeting the re-quirements for online monitoring while ensuring accuracy in extracting multiple feature points. Finally, integrating the vibration model, sensor, and feature extraction algorithm, we propose a dynamic monitoring system for multi-frequency cardiac vibration, which can be applied to portable monitoring devices for daily dynamic cardiac monitoring, providing a new approach for the early diagnosis and prevention of cardiovascular diseases. [ABSTRACT FROM AUTHOR]

Chrysanthemum wilt is a plant disease that exerts a substantial influence on the cultivation of Chrysanthemum zawadskii (Herb.) for tea and beverage production. The rhizosphere microbial population exhibits a direct correlation with the overall health of plants. Therefore, studying the rhizosphere microbial community of Chrysanthemum zawadskii (Herb.) Tzvel. is of great significance for finding methods to control this disease. This study obtained rhizosphere soil samples from both diseased and healthy plant individuals and utilized high-throughput sequencing technology to analyze their microbial composition. The results showed that the rhizosphere microbial diversity decreased significantly, and the microbial community structure changed significantly. In the affected soil, the relative abundance of pathogenic microorganisms such as rhizospora and Phytophthora was greatly increased, while the relative abundance of beneficial microorganisms such as antagonistic fungi and actinomyces was greatly decreased. In addition, this study also found that soil environmental variables have an important impact on plant resistance; the environmental factors mainly include soil properties, content of major microorganisms, and resistance characteristics of samples. Redundancy analysis showed that the drug-resistant population had a greater impact on the 10 species with the highest abundance, and the environmental factors were more closely related to the sensitive population. In the fungal community, the resistant sample group was more sensitive to the influence of environmental factors and high-abundance fungi. These findings provide a theoretical basis for improving microbial community structure by optimizing fertilization structure, thus affecting the distribution of bacteria and fungi, and thus improving the disease resistance of chrysanthemum. In addition, by regulating and optimizing microbial community structure, new ideas and methods can be provided for the prevention and control of chrysanthemum wilt disease. [ABSTRACT FROM AUTHOR]

Recently, object detection has become a research hotspot in computer vision, which often detects regular images with small viewing angles. In order to obtain a field of view without blind spots, fisheye cameras, which have distortions and discontinuities, have come into use. The fisheye camera, which has a wide viewing angle, and an unmanned aerial vehicle equipped with a fisheye camera are used to obtain a field of view without blind spots. However, distorted and discontinuous objects appear in the captured fisheye images due to the unique viewing angle of fisheye cameras. It poses a significant challenge to some existing object detectors. To solve this problem, this paper proposes a PGDS-YOLOv8s model to solve the issue of detecting distorted and discontinuous objects in fisheye images. First, two novel downsampling modules are proposed. Among them, the Max Pooling and Ghost's Downsampling (MPGD) module effectively extracts the essential feature information of distorted and discontinuous objects. The Average Pooling and Ghost's Downsampling (APGD) module acquires rich global features and reduces the feature loss of distorted and discontinuous objects. In addition, the proposed C2fs module uses Squeeze-and-Excitation (SE) blocks to model the interdependence of the channels to acquire richer gradient flow information about the features. The C2fs module provides a better understanding of the contextual information in fisheye images. Subsequently, an SE block is added after the Spatial Pyramid Pooling Fast (SPPF), thus improving the model's ability to capture features of distorted, discontinuous objects. Moreover, the UAV-360 dataset is created for object detection in fisheye images. Finally, experiments show that the proposed PGDS-YOLOv8s model on the VOC-360 dataset improves mAP@0.5 by 19.8% and mAP@0.5:0.95 by 27.5% compared to the original YOLOv8s model. In addition, the improved model on the UAV-360 dataset achieves 89.0% for mAP@0.5 and 60.5% for mAP@0.5:0.95. Furthermore, on the MS-COCO 2017 dataset, the PGDS-YOLOv8s model improved AP by 1.4%, AP 50 by 1.7%, and AP 75 by 1.2% compared with the original YOLOv8s model. [ABSTRACT FROM AUTHOR]

In this paper, a novel plasmonic all-optical half-subtractor and full-subtractor are designed for optical computing. The structure of plasmonic subtractors consists of a metal–insulator–metal (MIM) waveguide and rectangular ring resonators covered by a graphene layer. Due to the nonlinear optical properties of graphene, the states of the plasmonic resonators can be controlled by the pump intensity of a pump beam focused on the graphene layer. The resonators can work as all-optical switches with an ultra-fast response time to constitute optical logic devices according to the directed logic mechanism. A finite-difference time-domain method is utilized to numerically investigate the transmission of the output signals which represent the results of subtraction operations. Simulation results obtained indicate that the proposed plasmonic devices have the ability to implement half-subtraction and full-subtraction with a small feature size and fast response time, and provide a new concept and method for the design and realization of optical computing devices. [ABSTRACT FROM AUTHOR]

In this work, a series of chitosan (CS)-grafted carbon oxynitride (OCN) nanoparticles (denoted as CS-OCN) were successfully synthesized for the first time by thermal polycondensation and subsequent esterification. The structure and photocatalytic performance of CS-OCN nanoparticles were investigated. The XPS spectra of CS-OCN-3 showed the presence of amino bonds. The optimal photocatalytic degradation efficiency of the synthesized CS-OCN-3 could reach 94.3% within 390 min, while the photocurrent response intensity was about 150% more than that of pure OCN. The improved photocatalytic performance may be mainly attributed to the enhanced photogenerated carrier's separation and transportation and stronger visible light response after CS grafting. In addition, the inhibition diameter of CS-OCN-3 reached 23 mm against E. coli within 24 h under visible light irradiation, exhibiting excellent photocatalytic bactericidal ability. The results of bacterial inhibition were supported by absorbance measurements (OD600) studies of E. coli. In a word, this work provided a rational design of an efficient novel metal-free photocatalyst to remove bacterial contamination and accelerate the degradation of organic dyes. [ABSTRACT FROM AUTHOR]

First-principles calculations were used to simulate the aggregation of the peroxy chain defect POL and the oxygen vacancy defect ODC(I). Defect aggregation's electronic structure and optical properties were investigated. The two defects were most likely to accumulate on a 6-membered ring in ortho-position. When the two defects are aggregated, it is discovered that 0.75 ev absorption peaks appear in the near-infrared band, which may be brought on by the addition of oxygen vacancy defect ODC(I). We can draw the conclusion that the absorption peak of the aggregation defect of ODC(I) defect and POL is more prominent in the near infrared region and visible light area than ODC(I) defect and POL defect. [ABSTRACT FROM AUTHOR]

The use of 360° omnidirectional images has occurred widely in areas where comprehensive visual information is required due to their large visual field coverage. However, many extant convolutional neural networks based on 360° omnidirectional images have not performed well in computer vision tasks. This occurs because 360° omnidirectional images are processed into plane images by equirectangular projection, which generates discontinuities at the edges and can result in serious distortion. At present, most methods to alleviate these problems are based on multi-projection and resampling, which can result in huge computational overhead. Therefore, a novel edge continuity distortion-aware block (ECDAB) for 360° omnidirectional images is proposed here, which prevents the discontinuity of edges and distortion by recombining and segmenting features. To further improve the performance of the network, a novel convolutional row-column attention block (CRCAB) is also proposed. CRCAB captures row-to-row and column-to-column dependencies to aggregate global information, enabling stronger representation of the extracted features. Moreover, to reduce the memory overhead of CRCAB, we propose an improved convolutional row-column attention block (ICRCAB), which can adjust the number of vectors in the row-column direction. Finally, to verify the effectiveness of the proposed networks, we conducted experiments on both traditional images and 360° omnidirectional image datasets. The experimental results demonstrated that better performance than for the baseline model was obtained by the network using ECDAB or CRCAB. [ABSTRACT FROM AUTHOR]

Electronic noses are one of the predominant technological choices for gas mixture detection, but their application in real-world atmospheric environments still leaves several issues to be resolved. The key bottleneck is the effect of turbulence caused by the diffusion of gases in the atmosphere on the quantitative and qualitative analytical performance of the electronic nose. In light of this, this paper presents a quantitative and qualitative analysis strategy for gas mixture monitoring. This strategy adopts baseline manipulation of the raw sensor data to reduce drift interference, and then performs feature extraction on the multidimensional response signals of the MOS gas sensor array using principal component analysis (PCA). In order to improve gas mixture recognition accuracy, the whale optimization algorithm (WOA) is used to optimize the network structure of the long short-term memory (LSTM) model for turbulent gas mixture composition recognition. The least squares support vector machine (LSSVM) algorithm is adopted to implement turbulent gas mixture concentration prediction. This paper focuses on two aspects of hyper-parameter optimization for the development of an LSSVM with particle swarm optimization (PSO) and for improved training sample selection for the LSSVM which should subsequently increase the accuracy of concentration estimation. The effectiveness of the proposed strategy is evaluated with a dataset from a chemical sensor array exposed to turbulent gas mixtures. Experimental results revealed that the proposed strategy for turbulent gas mixtures has satisfactory outcomes for both qualitative gas composition recognition and quantitative gas concentration prediction. [ABSTRACT FROM AUTHOR]

Line-of-sight (LOS) indoor optical wireless communications (OWC) enable a high data rate transmission while potentially suffering from optical channel obstructions. Additional LOS links using diversity techniques can tackle the received signal performance degradation, where channel gains often differ in multiple LOS channels. In this paper, a novel active transmitter detection scheme in spatial modulation (SM) is proposed to be incorporated with signal space diversity (SSD) technique to enable an increased OWC system throughput with an improved bit-error-rate (BER). This transmitter detection scheme is composed of a signal pre-distortion technique at the transmitter and a power-based statistical detection method at the receiver, which can address the problem of power-based transmitter detection in SM using carrierless amplitude and phase modulation waveforms with numerous signal levels. Experimental results show that, with the proposed transmitter detection scheme, SSD can be effectively provided with ~0.61 dB signal-to-noise-ratio (SNR) improvement. Additionally, an improved data rate ~7.5 Gbit/s is expected due to effective transmitter detection in SM. The SSD performances at different constellation rotation angles and under different channel gain distributions are also investigated, respectively. The proposed scheme provides a practical solution to implement power-based SM and thus aids the SSD realization for improving system performance. [ABSTRACT FROM AUTHOR]

In this study, we aimed to assess the effect of diet ZEA on serum hormones, the location and expression of estrogen receptor ERα/β and progesterone receptor (PR) of the uterus in weaned piglets and to reveal the mechanism underneath. A total of 40 healthy weaned gilts were randomly allocated to basal diet supplemented with 0 (Control), 0.5 (ZEA0.5), 1.0 (ZEA1.0) and 1.5 (ZEA1.5) mg ZEA/kg and fed individually for 35 days. Meanwhile, the porcine endometrial epithelial cells (PECs) were incubated for 24 h with ZEA at 0 (Control), 5 (ZEA5), 20 (ZEA20) and 80 (ZEA80) μmol/L, respectively. The results showed that nutrient apparent digestibility (CP and GE), nutrient apparent availability (ME/GE, BV and NPU), the uterine immunoreactive integrated optic density (IOD), relative mRNA and protein expression of ER-α, ER-β and PR and the relative mRNA and protein expression of ER-α and ER-β in PECs all increased linearly (p < 0.05) with ZEA. Collectively, ZEA can interfere with the secretion of some reproductive hormones in the serum and promote the expression of estrogen/progesterone receptors in the uterus and PECs. All these indicate that ZEA may promote the development of the uterus in weaned gilts through estrogen receptor pathway. [ABSTRACT FROM AUTHOR]

The nuclear factor Y (NF-Y) gene family is an important transcription factor family consisting of three subfamilies, NF-YA, NF-YB and NF-YC, which are widely involved in plant growth and development, stress responses and other processes. In this study, we identified 64 members of the NF-Y gene family in the M. sativa L. (Xinjiang Daye) genome, including 11 MsNF-YAs, 33 MsNF-YBs and 20 MsNF-YCs. Analysis of conserved motifs indicated that each unit included unique compounds of motifs, although certain members lost some motifs. Conserved functional domain analysis showed that each subunit contained a specific set of functional domains. Analysis of cis-acting elements in the promoter region of the MsNF-Y genes identified a series of cis-acting elements associated with stress responses. In addition, the transcriptome data and qRT-PCR analysis showed that MsNF-Y genes were significantly induced or downregulated by alkali treatment. The results of this study may help to establish a basis for further cloning and functional studies of NF-Y genes in Medicago sativa and other related legume species. [ABSTRACT FROM AUTHOR]

Video-based dynamic facial emotion recognition (FER) is a challenging task, as one must capture and distinguish tiny facial movements representing emotional changes while ignoring the facial differences of different objects. Recent state-of-the-art studies have usually adopted more complex methods to solve this task, such as large-scale deep learning models or multimodal analysis with reference to multiple sub-models. According to the characteristics of the FER task and the shortcomings of existing methods, in this paper we propose a lightweight method and design three attention modules that can be flexibly inserted into the backbone network. The key information for the three dimensions of space, channel, and time is extracted by means of convolution layer, pooling layer, multi-layer perception (MLP), and other approaches, and attention weights are generated. By sharing parameters at the same level, the three modules do not add too many network parameters while enhancing the focus on specific areas of the face, effective feature information of static images, and key frames. The experimental results on CK+ and eNTERFACE'05 datasets show that this method can achieve higher accuracy. [ABSTRACT FROM AUTHOR]

A widely used clustering algorithm, density peak clustering (DPC), assigns different attribute values to data points through the distance between data points, and then determines the number and range of clustering by attribute values. However, DPC is inefficient when dealing with scenes with a large amount of data, and the range of parameters is not easy to determine. To fix these problems, we propose a quantum DPC (QDPC) algorithm based on a quantum D i s t C a l c circuit and a Grover circuit. The time complexity is reduced to O (log (N 2) + 6 N + N) , whereas that of the traditional algorithm is O (N 2) . The space complexity is also decreased from O (N · ⌈ log N ⌉) to O (⌈ log N ⌉) . [ABSTRACT FROM AUTHOR]

Optical network-on-chip (ONoC) is based on optical interconnects and optical routers (ORs), which have obvious advantages in bandwidth and power consumption. Transmission capacity is a significant performance in ONoC architecture, which has to be fully considered during the design process. Relying on mode-division multiplexing (MDM) technology, the system capacity of optical interconnection is greatly improved compared to the traditional multiplexing technology. With the explosion in MDM technology, the optical router supporting MDM came into being. In this paper, we design a multimode optical router (MDM-OR) model and analyze its indicators. Above all, we propose a novel multimode switching element and design an N-port universal multimode optical router (MDM-OR) model. Secondly, we analyze the insertion loss model of different optical devices and the crosstalk noise model of N-port MDM-OR. On this basis, a multimode router structure of a single-mode five-port optical router is proposed. At the same time, we analyze the transmission loss, crosstalk noise, signal-to-noise radio (OSNR), and bit error rate (BER) of different input–output pairs by inputting the 1550 nm TE 0 , TE 1 , and TE 2 modes to the router. [ABSTRACT FROM AUTHOR]

With the continuous increase in atmospheric carbon dioxide emissions, nitrogen (N) and phosphorus (P) as mineral elements increasingly restrict plant growth. To explore the effect of deficiency of P and N on growth and physiology, Fraxinus mandshurica (hereafter "F. mandshurica") Rupr. annual seedlings of Wuchang (WC) provenance with fast growth and Dailing (DL) provenance with slow growth were treated with complete nutrition or starvation of N (N-), P (P-) or both elements (NP-). Although P- and N- increased the use efficiency of P (PUE) and N (NUE), respectively, they reduced the leaf area, chlorophyll content and activities of N assimilation enzymes (NR, GS, GOGAT), which decreased the dry weight and P or N amount. The free amino acid content and activities of Phosphoenolpyruvate carboxylase (PEPC) and acid phosphatase enzymes were reduced by N-. The transcript levels of NRT2.1, NRT2.4, NRT2.5, NRT2.7, AVT1, AAP3, NIA2, PHT1-3, PHT1-4 and PHT2-1 in roots were increased, but those of NRT2.1, NRT2.4, NRT2.5, PHT1-3, PHT1-4, PHT2-1 and AAP3 in leaves were reduced by P-. WC was significantly greater than DL under P- in dry weight, C amount, N amount, leaf area, PUE, NUE, which related to greater chlorophyll content, PEPC enzyme activity, N assimilation enzyme activities, and transcript levels of N and P transporter genes in roots and foliage, indicating a greater ability of WC to absorb, transport and utilize N and P under P-. WC was also greater than DL under N- in terms of the above indicators except the transcript levels of N and P assimilation genes, but most of the indicators did not reach a significant level, indicating that WC might be more tolerant to N- than DL, which requires further verification. In summary, WC was identified as a P-efficient provenance, as the growth rate was greater for the genetic type with high than low tolerance to P-. [ABSTRACT FROM AUTHOR]

A signal space diversity (SSD) scheme was proposed to be incorporated with spatial modulation (SM) in an intensity-modulation/direct-detection-based multiple-input-single-output (MISO) indoor optical wireless communication (OWC) system to improve bit-error-rate (BER) performance and system throughput. SSD was realized via signal constellation rotation and diversity interleaving using different channel gains to improve the BER. With SM incorporated, the MISO-OWC system throughput increased. Theoretical BER expressions of the SSD scheme were established for the first time by investigating the distance of neighboring constellation symbols upon maximum-likelihood detection. Such BER expressions were further verified by numerical results. The results showed that, except for the slightly-lower-accuracy performance brought by comparable distances of neighboring constellation symbols in cases of low signal-to-noise ratios, these BER expressions were accurate in most scenarios. Moreover, theoretical investigations of channel gain distributions were performed at different signal constellation rotation angles to show the capability of the SSD scheme to improve the BER. The results showed that a significantly improved BER by two orders of magnitude could be achieved using a reasonably high channel-gain ratio and a larger constellation rotation angle. The SSD-SM scheme provides a promising option to achieve transmitter diversity with an enhanced throughput in high-speed indoor OWC systems. [ABSTRACT FROM AUTHOR]

Quantum dual-signature means that two signed quantum messages are combined and expected to be sent to two different recipients. A quantum signature requires the cooperation of two verifiers to complete the whole verification process. As an important quantum signature aspect, the trusted third party is introduced to the current protocols, which affects the practicability of the quantum signature protocols. In this paper, we propose a quantum dual-signature protocol without arbitrator and entanglement for the first time. In the proposed protocol, two independent verifiers are introduced, here they may be dishonest but not collaborate. Furthermore, strongly nonlocal orthogonal product states are used to preserve the protocol security, i.e., no one can deny or forge a valid signature, even though some of them conspired. Compared with existing quantum signature protocols, this protocol does not require a trusted third party and entanglement resources. [ABSTRACT FROM AUTHOR]

In this paper, the nonlinear dynamics of a novel model based on optically pumped spin-polarized vertical-cavity surface-emitting lasers (spin-VCSELs) with optical feedback is investigated numerically. Due to optical feedback being the external disturbance component, the complex nonlinear dynamical behaviors can be enhanced and the regions of different nonlinear dynamics in size can be extended with appropriate parameters of spin-VCSELs. According to the equations of the modified spin-flip model (SFM), the comparison of bifurcation diagrams is first presented for the clear presentation of different routes to chaos. Meanwhile, numerous bifurcation diagrams in color are illustrated to demonstrate the rich dynamical regimes intuitively, and the crucial effects of optical feedback strength, feedback delay, linewidth enhancement factor, and spin-flip relaxation rate on the region evolvement of complex dynamics of the proposed model are revealed to investigate the dependence of dynamical behaviors on external and internal parameters when the optical feedback scheme is introduced. These parameters play a remarkable role in enhancing the mechanism of complex dynamic oscillations. Furthermore, utilizing combination with time series, power spectra, and phase portraits, the various dynamical behaviors observed in the bifurcation diagram are simulated numerically. Correspondingly, the powerful measure 0–1 test is employed to distinguish between chaos and non-chaos. [ABSTRACT FROM AUTHOR]

Insertion loss and crosstalk noise will influence network performance severely, especially in optical networks-on-chip (ONoCs) when wavelength division multiplexing (WDM) technology is employed. In this paper, an insertion loss and crosstalk analysis model for WDM-based torus ONoCs is proposed to evaluate the network performance. To demonstrate the feasibility of the proposed methods, numerical simulations of the WDM-based torus ONoCs with optimized crossbar and crux optical routers are presented, and the worst-case link and network scalability are also revealed. The numerical simulation results demonstrate that the scale of the WDM-based torus ONoCs with the crux optical router can reach 6 × 5 or 5 × 6 before the noise power exceeds the signal power, and the network scale is 5 × 4 in the worst case when the optimized crossbar router is employed. Additionally, the simulated results of OptiSystem reveal that WDM-based torus ONoCs have better signal transmission quality when using the crux optical router, which is consistent with previous numerical simulations. Furthermore, compared with the single-wavelength network, WDM-based ONoCs have a great performance improvement in end-to-end (ETE) delay and throughput according to the simulated results of OPNET. The proposed network analysis method provides a reliable theoretical basis and technical support for the design and performance optimization of ONoCs. [ABSTRACT FROM AUTHOR]

Various plasmonic nanocavities possessing an extremely small mode volume have been developed and applied successfully in the study of strong light-matter coupling. Driven by the desire of constructing quantum networks and other functional quantum devices, a growing trend of strong coupling research is to explore the possibility of fabricating simple strong coupling nanosystems as the building blocks to construct complex systems or devices. Herein, we investigate such a nanocube-exciton building block (i.e. AuNC@J-agg), which is fabricated by coating Au nanocubes with excitonic J-aggregate molecules. The extinction spectra of AuNC@J-agg assembly, as well as the dark field scattering spectra of the individual nanocube-exciton, exhibit Rabi splitting of 100–140 meV, which signifies strong plasmon–exciton coupling. We further demonstrate the feasibility of constructing a more complex system of AuNC@J-agg on Au film, which achieves a much stronger coupling, with Rabi splitting of 377 meV. This work provides a practical pathway of building complex systems from building blocks, which are simple strong coupling systems, which lays the foundation for exploring further fundamental studies or inventing novel quantum devices. [ABSTRACT FROM AUTHOR]