Synthetic transmit focusing (STF) methods using unfocused waves or plane waves (PWs) have recently been investigated extensively. However, STF using PWs with a convex array (PWSTF-CA) has not been rigorously studied for high-resolution sector imaging. In this paper, the authors suggest an analytical model for accurate characterization of the spatial beam patterns of PWSTF-CA using a large range of either uniformly or non-uniformly distributed PW angles. On the basis of the model, a frame-based PWSTF-CA approach with non-uniform PW angles is suggested to achieve superior image quality at a higher frame rate than conventional transmit focusing (CTF). The analytical model can also be used for optimal selection of a set of PW angles to scan the entire sectorial field of view and its subsets employed for STF at each imaging point. The authors also investigate how to select transmit subarrays for each of the PWs to obtain the best spatial resolution. A theoretical analysis and simulations are conducted for the verification of the analytical model and the optimal utilization strategy of PWSTF-CA. The results indicate that the PWSTF-CA improves not only the frame rate but also the contrast, signal-to-noise ratio, and resolution compared with the CTF, as in the case of PWSTF with linear arrays.
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http://dx.doi.org/10.1121/1.5065391 | DOI Listing |
Bone Marrow Transplant
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Université de Franche-Comté, EFS, INSERM, UMR RIGHT, F-, 25000, Besançon, France.
The accessibility of CAR-T cells in centralized production models faces significant challenges, primarily stemming from logistical complexities and prohibitive costs. However, European Regulation EC No. 1394/2007 introduced a pivotal provision known as the hospital exemption.
View Article and Find Full Text PDFSci Data
January 2025
Remote Sensing Centre for Earth System Research (RSC4Earth), Leipzig University, Leipzig, 04103, Germany.
With climate extremes' rising frequency and intensity, robust analytical tools are crucial to predict their impacts on terrestrial ecosystems. Machine learning techniques show promise but require well-structured, high-quality, and curated analysis-ready datasets. Earth observation datasets comprehensively monitor ecosystem dynamics and responses to climatic extremes, yet the data complexity can challenge the effectiveness of machine learning models.
View Article and Find Full Text PDFTransl Psychiatry
January 2025
Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA.
Peripheral inflammatory markers (PIMs), such as C-reactive protein (CRP) or white blood cell count (WBC), have been associated with depression severity in meta-analyses and large cohort studies. However, in typically-sized psychoimmunology studies (N < 200) that explore associations between PIMs and neurobiological/psychosocial constructs related to depression and studies that examine less-studied PIMs (e.g.
View Article and Find Full Text PDFISA Trans
January 2025
Toronto Metropolitan University, Toronto, Canada. Electronic address:
This research introduces an innovative approach to optimal control for a class of linear systems with input saturation. It leverages the synergy of Takagi-Sugeno (T-S) fuzzy models and reinforcement learning (RL) techniques. To enhance interpretability and analytical accessibility, our approach applies T-S models to approximate the value function and generate optimal control laws while incorporating prior knowledge.
View Article and Find Full Text PDFAm J Kidney Dis
January 2025
Department of Community Health Sciences, University of Calgary, Calgary, Alberta, CANADA; O'Brien Institute for Public Health, Cumming School of Medicine, University of Calgary, Calgary, Alberta, CANADA.
Rationale & Objective: People with advanced kidney disease undergo more non-cardiac operations compared to the general population, with a higher risk of perioperative cardiac events and death. However, little is known about the associations between severity of preoperative kidney dysfunction with postoperative length of hospitalization and discharge disposition; these were the focus of this study.
Study Design: Population-based retrospective cohort.
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