Divide and Conquer Partition for Fourier Reconstruction Sparse Inversion with its Applications

A partition method, with an efficient divide and conquer partition strategy, for the non-uniform sampling signal reconstruction based on Fourier reconstruction sparse inversion (FRSI) is developed. The novel partition FRSI(P-FRSI) is motivated by the observation that the partition processing of multi-dimensional signals can reduce the reconstruction difficulty and save the reconstruction time. Moreover, it is helpful to choose suitable reconstruction parameters. The P-FRSI employs divide and conquer strategy, and the signal is firstly partitioned into some blocks. Following that, traditional FRSI is applied to reconstruct signals in each block. We adopt linear or nonlinear superposition to determine the weight coefficients during integrating these blocks. Finally, P-FRSI is applied to two-dimensional seismic signal reconstruction. The superiority of the new method over conventional FRSI is demonstrated by numerical reconstruction experiments

Chance Constrained Programs with Gaussian Mixture Models

10.1080/24725854.2021.2001608IISE Transactions54121117-113

Effect of a typical systemic hospital reform on inpatient expenditure for rural population: the Sanming model in China

Abstract Background Considering catastrophic health expenses in rural households with hospitalised members were unproportionally high, in 2013, China developed a model of systemic reform in Sanming by adjusting payment method, pharmaceutical system, and medical services price. The reform was expected to control the excessive growth of hospital expenditures by reducing inefficiency and waste in health system or shortening the length of stay. This study analyzed the systemic reform’s impact on the financial burden and length of stay for the rural population in Sanming. Methods A total of 1,113,615 inpatient records for the rural population were extracted from the rural new cooperative medical scheme (NCMS) database in Sanming from 2007 to 2012 (before the reform) and from 2013 to 2016 (after the reform). We calculated the average growth rate of total inpatient expenditures and costs of different medical service categories (medications, diagnostic testing, physician services and therapeutic services) in these two periods. Generalized linear models (GLM) were employed to examine the effect of reform on out-of-pocket (OOP) expenditures and length of stay, controlling for some covariates. Furthermore, we controlled the fixed effects of the year and hospitals, and included cluster standard errors by hospital to assess the robustness of the findings in the GLM analysis. Results The typical systemic reform decreased the average growth rate of total inpatient expenditures by 1.34%, compared with the period before the reform. The OOP expenditures as a share of total expenditures showed a downward trend after the reform (42.34% in 2013). Holding all else constant, individuals after the reform spent ¥308.42 less on OOP expenditures (p < 0.001) than they did before the reform. Moreover, length of stay had a decrease of 0.67 days after the reform (p < 0.001). Conclusions These results suggested that the typical systemic hospital reform of the Sanming model had some positive effects on cost control and reducing financial burden for the rural population. Considering the OOP expenditures as a share of total expenditures was still high, China still has a long way to go to improve the benefits rural people have enjoyed from the NCMS

Non-orthogonal beam coordinate system wave propagation and reverse time migration

Grid size has a significant influence on the computation efficiency and accuracy of finite-difference seismic modeling and can change the workload of reverse time migration (RTM) remarkably. This paper proposes a non-orthogonal analytical coordinate system, beam coordinate system (BCS), for the solution of seismic wave propagation and RTM. Starting with an optical Gaussian beam width equation, we expand the representation on vertically variable velocity media, which is the most common scenario in seismic exploration. The BCS based on this representation can be used to implement an irregular-grid increment finite-difference that improves the efficiency of RTM. Based on the Laplacian expression in Riemannian space, we derive the wave equation in the BCS. The new coordinate system can generate an irregular grid with increment increasing vertically along depth. Through paraxial ray tracing, it can be extended to non-analytical beam coordinate system (NBCS). Experiments for the RTM on the Marmousi model with the BCS demonstrate that the proposed method improves the efficiency about 52% while maintaining good image quality

A primer on near-field communications for next-generation multiple access

Multiple-antenna technologies are advancing toward the development of extremely large aperture arrays and the utilization of extremely high frequencies, driving the progress of next-generation multiple access (NGMA). This evolution is accompanied by the emergence of near-field communications (NFCs), characterized by spherical-wave propagation, which introduces additional range dimensions to the channel and enhances system throughput. In this context, a tutorial-based primer on NFC is presented, emphasizing its applications in multiuser communications and multiple access (MA). The following areas are investigated: 1) the commonly used near-field channel models are reviewed along with their simplifications under various near-field conditions; 2) building upon these models, the information-theoretic capacity limits of NFC-MA are analyzed, including the derivation of the sum-rate capacity and capacity region, and their upper limits for both downlink and uplink scenarios; and 3) a detailed investigation of near-field multiuser beamforming design is presented, offering low-complexity and effective NFC-MA design methodologies in both the spatial and wavenumber (angular) domains. Throughout these investigations, near-field MA is compared with its far-field counterpart to highlight its superiority and flexibility in terms of interference management, thereby laying the groundwork for achieving NGMA

Identification and pathogenicity analysis of Fusarium spp. on peach in China

Abstract Background Vascular system is affected by diseases that can seriously damage plant health by inducing browning and death of branches. This study aimed to identify and analyze the pathogenicity of Fusarium spp. isolates obtained from diseased peach branches in several peach-producing areas of China. Results We obtained and confirmed nine Fusarium isolates based on morphological and molecular characteristics. Phylogenetic relationships using a combination of rDNA-internal transcribed spacer (ITS), elongation factor (EF)-1α, and mitochondrial small subunit (mtSSU) gene sequences were analyzed. GJH-Z1, GJH-6, and GJH-1 were identified as F. avenaceum; HYR-Z3, and ZLZT-6 as F. concentricum, HH-2020-G2, and HYTZ-4 as F. solani, GG-2020-1 as F. asiaticum, SYGZ-1 as F. equiseti. Through acupuncture comparison, the pathogenicity of F. equiseti (SYGZ-1) was highest amongst nine strains. Meanwhile, F. concentricum (HYR-Z3 and ZLZT-6), and F. solaini (HYTZ-4) had a higher level of pathogenicity as revealed by impregnation. Conclusions Our study shed light on the findings that Fusarium spp. can inflict vascular bundle browning of peach plants. Our results will extend the understanding of pathogenic diseases in China’s peach industry

Hybrid Attention-Based 3D Object Detection with Differential Point Clouds

Object detection based on point clouds has been widely used for autonomous driving, although how to improve its detection accuracy remains a significant challenge. Foreground points are more critical for 3D object detection than background points; however, most current detection frameworks cannot effectively preserve foreground points. Therefore, this work proposes a hybrid attention-based 3D object detection method with differential point clouds, which we name HA-RCNN. The method differentiates the foreground points from the background ones to preserve the critical information of foreground points. Extensive experiments conducted on the KITTI dataset show that the model outperforms the state-of-the-art methods, especially in recognizing large objects such as cars and cyclists

Development of a Sandwiched Piezoelectric Accelerometer for Low-Frequency and Wide-Band Seismic Exploration

A sandwiched piezoelectric accelerometer is developed and optimized for acquiring low-frequency, wide-band seismic data. The proposed accelerometer addresses the challenges of capturing seismic signals in the low-frequency range while maintaining a broad frequency response through the design of multi-stage charge amplifiers and a sandwiched structure. The device’s design, fabrication process, and performance evaluation are discussed in detail. Experimental results demonstrate its performance in amplitude and phase response characteristics